Objective evaluation of the latissimus dorsi flap for breast reconstruction using three-dimensional imaging.

PubMed

Henseler, Helga; Smith, Joanna; Bowman, Adrian; Khambay, Balvinder S; Ju, Xiangyang; Ayoub, Ashraf; Ray, Arup K

2012-09-01

The latissimus dorsi muscle flap is a common method for the reconstruction of the breast following mastectomy. The study aimed to assess the quality of this reconstruction using a three-dimensional (3D) imaging method. The null hypothesis was that there was no difference in volume between the reconstructed breast and the opposite side. This study was conducted in forty-four patients who had had immediate unilateral breast reconstruction by latissimus dorsi muscle flap. The breast was captured using the 3D imaging system. Ten landmarks were digitised on the 3D images. The volume of each breast was measured by the application of Breast Analysis Tool software. The symmetry of the breast was measured using Procrustes analysis. The impact of breast position, orientation, size and intrinsic shape on the overall breast asymmetry was investigated. The null hypothesis was rejected. The reconstructed breast showed a significantly smaller volume when compared to the opposite side, p < 0.0001, a mean difference of 176.8 cc and 95% CI (103.5, 250.0). The shape and the position of the reconstructed breast were the main contributing factors to the measured asymmetry score. 3D imaging was efficient in evaluating the outcome of breast surgery. The latissimus dorsi muscle flap on its own for breast reconstruction did not restore the volume and shape of the breast fully lost due to complete mastectomy. The modification of this method and the selection of other or additional surgical techniques for breast reconstruction should be considered. The asymmetry analysis through reflection and Procrustes matching was a useful method for the objective shape analysis of the female breast and presented a new approach for breast shape assessment. The intrinsic breast shape and the positioning of the breast were major components of postoperative breast asymmetry. The reconstructed breast was smaller overall than the un-operated breast at a significant level when assessing the breast volume using the surface area. 3D imaging by multiple stereophotogrammetry was a useful tool for volume measurements, shape analysis and the evaluation of symmetry. Copyright © 2012 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Attenuation correction with region growing method used in the positron emission mammography imaging system

NASA Astrophysics Data System (ADS)

Gu, Xiao-Yue; Li, Lin; Yin, Peng-Fei; Yun, Ming-Kai; Chai, Pei; Huang, Xian-Chao; Sun, Xiao-Li; Wei, Long

2015-10-01

The Positron Emission Mammography imaging system (PEMi) provides a novel nuclear diagnosis method dedicated for breast imaging. With a better resolution than whole body PET, PEMi can detect millimeter-sized breast tumors. To address the requirement of semi-quantitative analysis with a radiotracer concentration map of the breast, a new attenuation correction method based on a three-dimensional seeded region growing image segmentation (3DSRG-AC) method has been developed. The method gives a 3D connected region as the segmentation result instead of image slices. The continuity property of the segmentation result makes this new method free of activity variation of breast tissues. The threshold value chosen is the key process for the segmentation method. The first valley in the grey level histogram of the reconstruction image is set as the lower threshold, which works well in clinical application. Results show that attenuation correction for PEMi improves the image quality and the quantitative accuracy of radioactivity distribution determination. Attenuation correction also improves the probability of detecting small and early breast tumors. Supported by Knowledge Innovation Project of The Chinese Academy of Sciences (KJCX2-EW-N06)

Novel Multistatic Adaptive Microwave Imaging Methods for Early Breast Cancer Detection

NASA Astrophysics Data System (ADS)

Xie, Yao; Guo, Bin; Li, Jian; Stoica, Petre

2006-12-01

Multistatic adaptive microwave imaging (MAMI) methods are presented and compared for early breast cancer detection. Due to the significant contrast between the dielectric properties of normal and malignant breast tissues, developing microwave imaging techniques for early breast cancer detection has attracted much interest lately. MAMI is one of the microwave imaging modalities and employs multiple antennas that take turns to transmit ultra-wideband (UWB) pulses while all antennas are used to receive the reflected signals. MAMI can be considered as a special case of the multi-input multi-output (MIMO) radar with the multiple transmitted waveforms being either UWB pulses or zeros. Since the UWB pulses transmitted by different antennas are displaced in time, the multiple transmitted waveforms are orthogonal to each other. The challenge to microwave imaging is to improve resolution and suppress strong interferences caused by the breast skin, nipple, and so forth. The MAMI methods we investigate herein utilize the data-adaptive robust Capon beamformer (RCB) to achieve high resolution and interference suppression. We will demonstrate the effectiveness of our proposed methods for breast cancer detection via numerical examples with data simulated using the finite-difference time-domain method based on a 3D realistic breast model.

Breast EIT using a new projected image reconstruction method with multi-frequency measurements.

PubMed

Lee, Eunjung; Ts, Munkh-Erdene; Seo, Jin Keun; Woo, Eung Je

2012-05-01

We propose a new method to produce admittivity images of the breast for the diagnosis of breast cancer using electrical impedance tomography(EIT). Considering the anatomical structure of the breast, we designed an electrode configuration where current-injection and voltage-sensing electrodes are separated in such a way that internal current pathways are approximately along the tangential direction of an array of voltage-sensing electrodes. Unlike conventional EIT imaging methods where the number of injected currents is maximized to increase the total amount of measured data, current is injected only twice between two pairs of current-injection electrodes attached along the circumferential side of the breast. For each current injection, the induced voltages are measured from the front surface of the breast using as many voltage-sensing electrodes as possible. Although this electrode configurational lows us to measure induced voltages only on the front surface of the breast,they are more sensitive to an anomaly inside the breast since such an injected current tends to produce a more uniform internal current density distribution. Furthermore, the sensitivity of a measured boundary voltage between two equipotential lines on the front surface of the breast is improved since those equipotential lines are perpendicular to the primary direction of internal current streamlines. One should note that this novel data collection method is different from those of other frontal plane techniques such as the x-ray projection and T-scan imaging methods because we do not get any data on the plane that is perpendicular to the current flow. To reconstruct admittivity images using two measured voltage data sets, a new projected image reconstruction algorithm is developed. Numerical simulations demonstrate the frequency-difference EIT imaging of the breast. The results show that the new method is promising to accurately detect and localize small anomalies inside the breast.

Proposal of a novel method for observing the breast by high-resolution ultrasound imaging: understanding the normal breast structure and its application in an observational method for detecting deviations.

PubMed

Izumori, Ayumi; Horii, Rie; Akiyama, Futoshi; Iwase, Takuji

2013-01-01

With the recent advances in modalities for diagnostic imaging of the breast, it is now essential to detect isoechoic masses and small nonmass lesions, to which little attention has so far been paid using ultrasound (US) of the breast. It will be possible with the observation method to understand normal breast structural images and anatomy. We elucidated the detailed histological architecture of the normal breast, information indispensable for diagnostic US of the breast. Verification of the above hypotheses was carried out using the breasts of 11 patients who underwent total mastectomy at our clinic. Isoechoic structures with fat are lobules, all ducts, and surrounding stroma that support the ducts; intervening hyperechoic areas are edematous stroma and fat-containing stroma that support the breast. By taking an isoechoic structure that reflects the course of the ducts as the basic structure for observation, the boundary between the lobes can be inferred. Detection of deviations from the normal structure using the method for interpreting three-dimensional ultrasound images of mammary lobes is a radical new approach for diagnosing breast cancer. This technique is very simple and amenable to standardization once one understands the underlying theory. Furthermore, it is useful as a screening method as well as for easy detection of faint minute lesions that can only be detected by magnetic resonance imaging or second-look targeted US.

Automated breast segmentation in ultrasound computer tomography SAFT images

NASA Astrophysics Data System (ADS)

Hopp, T.; You, W.; Zapf, M.; Tan, W. Y.; Gemmeke, H.; Ruiter, N. V.

2017-03-01

Ultrasound Computer Tomography (USCT) is a promising new imaging system for breast cancer diagnosis. An essential step before further processing is to remove the water background from the reconstructed images. In this paper we present a fully-automated image segmentation method based on three-dimensional active contours. The active contour method is extended by applying gradient vector flow and encoding the USCT aperture characteristics as additional weighting terms. A surface detection algorithm based on a ray model is developed to initialize the active contour, which is iteratively deformed to capture the breast outline in USCT reflection images. The evaluation with synthetic data showed that the method is able to cope with noisy images, and is not influenced by the position of the breast and the presence of scattering objects within the breast. The proposed method was applied to 14 in-vivo images resulting in an average surface deviation from a manual segmentation of 2.7 mm. We conclude that automated segmentation of USCT reflection images is feasible and produces results comparable to a manual segmentation. By applying the proposed method, reproducible segmentation results can be obtained without manual interaction by an expert.

Breast Volume Measurement by Recycling the Data Obtained From 2 Routine Modalities, Mammography and Magnetic Resonance Imaging.

PubMed

Itsukage, Shizu; Sowa, Yoshihiro; Goto, Mariko; Taguchi, Tetsuya; Numajiri, Toshiaki

2017-01-01

Objective: Preoperative prediction of breast volume is important in the planning of breast reconstructive surgery. In this study, we prospectively estimated the accuracy of measurement of breast volume using data from 2 routine modalities, mammography and magnetic resonance imaging, by comparison with volumes of mastectomy specimens. Methods: The subjects were 22 patients (24 breasts) who were scheduled to undergo total mastectomy for breast cancer. Preoperatively, magnetic resonance imaging volume measurement was performed using a medical imaging system and the mammographic volume was calculated using a previously proposed formula. Volumes of mastectomy specimens were measured intraoperatively using a method based on Archimedes' principle and Newton's third law. Results: The average breast volumes measured on magnetic resonance imaging and mammography were 318.47 ± 199.4 mL and 325.26 ± 217.36 mL, respectively. The correlation coefficients with mastectomy specimen volumes were 0.982 for magnetic resonance imaging and 0.911 for mammography. Conclusions: Breast volume measurement using magnetic resonance imaging was highly accurate but requires data analysis software. In contrast, breast volume measurement with mammography requires only a simple formula and is sufficiently accurate, although the accuracy was lower than that obtained with magnetic resonance imaging. These results indicate that mammography could be an alternative modality for breast volume measurement as a substitute for magnetic resonance imaging.

Breast Volume Measurement by Recycling the Data Obtained From 2 Routine Modalities, Mammography and Magnetic Resonance Imaging

PubMed Central

Itsukage, Shizu; Goto, Mariko; Taguchi, Tetsuya; Numajiri, Toshiaki

2017-01-01

Objective: Preoperative prediction of breast volume is important in the planning of breast reconstructive surgery. In this study, we prospectively estimated the accuracy of measurement of breast volume using data from 2 routine modalities, mammography and magnetic resonance imaging, by comparison with volumes of mastectomy specimens. Methods: The subjects were 22 patients (24 breasts) who were scheduled to undergo total mastectomy for breast cancer. Preoperatively, magnetic resonance imaging volume measurement was performed using a medical imaging system and the mammographic volume was calculated using a previously proposed formula. Volumes of mastectomy specimens were measured intraoperatively using a method based on Archimedes’ principle and Newton's third law. Results: The average breast volumes measured on magnetic resonance imaging and mammography were 318.47 ± 199.4 mL and 325.26 ± 217.36 mL, respectively. The correlation coefficients with mastectomy specimen volumes were 0.982 for magnetic resonance imaging and 0.911 for mammography. Conclusions: Breast volume measurement using magnetic resonance imaging was highly accurate but requires data analysis software. In contrast, breast volume measurement with mammography requires only a simple formula and is sufficiently accurate, although the accuracy was lower than that obtained with magnetic resonance imaging. These results indicate that mammography could be an alternative modality for breast volume measurement as a substitute for magnetic resonance imaging. PMID:29308107

Initial In Vivo Quantification of Tc-99m Sestamibi Uptake as a Function of Tissue Type in Healthy Breasts Using Dedicated Breast SPECT-CT

PubMed Central

Mann, Steve D.; Perez, Kristy L.; McCracken, Emily K. E.; Shah, Jainil P.; Wong, Terence Z.; Tornai, Martin P.

2012-01-01

A pilot study is underway to quantify in vivo the uptake and distribution of Tc-99m Sestamibi in subjects without previous history of breast cancer using a dedicated SPECT-CT breast imaging system. Subjects undergoing diagnostic parathyroid imaging studies were consented and imaged as part of this IRB-approved breast imaging study. For each of the seven subjects, one randomly selected breast was imaged prone-pendant using the dedicated, compact breast SPECT-CT system underneath the shielded patient support. Iteratively reconstructed and attenuation and/or scatter corrected images were coregistered; CT images were segmented into glandular and fatty tissue by three different methods; the average concentration of Sestamibi was determined from the SPECT data using the CT-based segmentation and previously established quantification techniques. Very minor differences between the segmentation methods were observed, and the results indicate an average image-based in vivo Sestamibi concentration of 0.10 ± 0.16 μCi/mL with no preferential uptake by glandular or fatty tissues. PMID:22956950

Segmentation of breast ultrasound images based on active contours using neutrosophic theory.

PubMed

Lotfollahi, Mahsa; Gity, Masoumeh; Ye, Jing Yong; Mahlooji Far, A

2018-04-01

Ultrasound imaging is an effective approach for diagnosing breast cancer, but it is highly operator-dependent. Recent advances in computer-aided diagnosis have suggested that it can assist physicians in diagnosis. Definition of the region of interest before computer analysis is still needed. Since manual outlining of the tumor contour is tedious and time-consuming for a physician, developing an automatic segmentation method is important for clinical application. The present paper represents a novel method to segment breast ultrasound images. It utilizes a combination of region-based active contour and neutrosophic theory to overcome the natural properties of ultrasound images including speckle noise and tissue-related textures. First, due to inherent speckle noise and low contrast of these images, we have utilized a non-local means filter and fuzzy logic method for denoising and image enhancement, respectively. This paper presents an improved weighted region-scalable active contour to segment breast ultrasound images using a new feature derived from neutrosophic theory. This method has been applied to 36 breast ultrasound images. It generates true-positive and false-positive results, and similarity of 95%, 6%, and 90%, respectively. The purposed method indicates clear advantages over other conventional methods of active contour segmentation, i.e., region-scalable fitting energy and weighted region-scalable fitting energy.

Applicability of active infrared thermography for screening of human breast: a numerical study

NASA Astrophysics Data System (ADS)

Dua, Geetika; Mulaveesala, Ravibabu

2018-03-01

Active infrared thermography is a fast, painless, noncontact, and noninvasive imaging method, complementary to mammography, ultrasound, and magnetic resonance imaging methods for early diagnosis of breast cancer. This technique plays an important role in early detection of breast cancer to women of all ages, including pregnant or nursing women, with different sizes of breast, irrespective of either fatty or dense breast. This proposed complementary technique makes use of infrared emission emanating from the breast. Emanating radiations from the surface of the breast under test are detected with an infrared camera to map the thermal gradients over it, in order to reveal hidden tumors inside it. One of the reliable active infrared thermographic technique, linear frequency modulated thermal wave imaging is adopted to detect tumors present inside the breast. Further, phase and amplitude images are constructed using frequency and time-domain data analysis schemes. Obtained results show the potential of the proposed technique for early diagnosis of breast cancer in fatty as well as dense breasts.

Segmentation of the pectoral muscle in breast MR images using structure tensor and deformable model

NASA Astrophysics Data System (ADS)

Lee, Myungeun; Kim, Jong Hyo

2012-02-01

Recently, breast MR images have been used in wider clinical area including diagnosis, treatment planning, and treatment response evaluation, which requests quantitative analysis and breast tissue segmentation. Although several methods have been proposed for segmenting MR images, segmenting out breast tissues robustly from surrounding structures in a wide range of anatomical diversity still remains challenging. Therefore, in this paper, we propose a practical and general-purpose approach for segmenting the pectoral muscle boundary based on the structure tensor and deformable model. The segmentation work flow comprises four key steps: preprocessing, detection of the region of interest (ROI) within the breast region, segmenting the pectoral muscle and finally extracting and refining the pectoral muscle boundary. From experimental results we show that the proposed method can segment the pectoral muscle robustly in diverse patient cases. In addition, the proposed method will allow the application of the quantification research for various breast images.

SU-C-207B-04: Automated Segmentation of Pectoral Muscle in MR Images of Dense Breasts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Verburg, E; Waard, SN de; Veldhuis, WB

Purpose: To develop and evaluate a fully automated method for segmentation of the pectoral muscle boundary in Magnetic Resonance Imaging (MRI) of dense breasts. Methods: Segmentation of the pectoral muscle is an important part of automatic breast image analysis methods. Current methods for segmenting the pectoral muscle in breast MRI have difficulties delineating the muscle border correctly in breasts with a large proportion of fibroglandular tissue (i.e., dense breasts). Hence, an automated method based on dynamic programming was developed, incorporating heuristics aimed at shape, location and gradient features.To assess the method, the pectoral muscle was segmented in 91 randomly selectedmore » participants (mean age 56.6 years, range 49.5–75.2 years) from a large MRI screening trial in women with dense breasts (ACR BI-RADS category 4). Each MR dataset consisted of 178 or 179 T1-weighted images with voxel size 0.64 × 0.64 × 1.00 mm3. All images (n=16,287) were reviewed and scored by a radiologist. In contrast to volume overlap coefficients, such as DICE, the radiologist detected deviations in the segmented muscle border and determined whether the result would impact the ability to accurately determine the volume of fibroglandular tissue and detection of breast lesions. Results: According to the radiologist’s scores, 95.5% of the slices did not mask breast tissue in such way that it could affect detection of breast lesions or volume measurements. In 13.1% of the slices a deviation in the segmented muscle border was present which would not impact breast lesion detection. In 70 datasets (78%) at least 95% of the slices were segmented in such a way it would not affect detection of breast lesions, and in 60 (66%) datasets this was 100%. Conclusion: Dynamic programming with dedicated heuristics shows promising potential to segment the pectoral muscle in women with dense breasts.« less

An approach to analyze the breast tissues in infrared images using nonlinear adaptive level sets and Riesz transform features.

PubMed

Prabha, S; Suganthi, S S; Sujatha, C M

2015-01-01

Breast thermography is a potential imaging method for the early detection of breast cancer. The pathological conditions can be determined by measuring temperature variations in the abnormal breast regions. Accurate delineation of breast tissues is reported as a challenging task due to inherent limitations of infrared images such as low contrast, low signal to noise ratio and absence of clear edges. Segmentation technique is attempted to delineate the breast tissues by detecting proper lower breast boundaries and inframammary folds. Characteristic features are extracted to analyze the asymmetrical thermal variations in normal and abnormal breast tissues. An automated analysis of thermal variations of breast tissues is attempted using nonlinear adaptive level sets and Riesz transform. Breast thermal images are initially subjected to Stein's unbiased risk estimate based orthonormal wavelet denoising. These denoised images are enhanced using contrast-limited adaptive histogram equalization method. The breast tissues are then segmented using non-linear adaptive level set method. The phase map of enhanced image is integrated into the level set framework for final boundary estimation. The segmented results are validated against the corresponding ground truth images using overlap and regional similarity metrics. The segmented images are further processed with Riesz transform and structural texture features are derived from the transformed coefficients to analyze pathological conditions of breast tissues. Results show that the estimated average signal to noise ratio of denoised images and average sharpness of enhanced images are improved by 38% and 6% respectively. The interscale consideration adopted in the denoising algorithm is able to improve signal to noise ratio by preserving edges. The proposed segmentation framework could delineate the breast tissues with high degree of correlation (97%) between the segmented and ground truth areas. Also, the average segmentation accuracy and sensitivity are found to be 98%. Similarly, the maximum regional overlap between segmented and ground truth images obtained using volume similarity measure is observed to be 99%. Directionality as a feature, showed a considerable difference between normal and abnormal tissues which is found to be 11%. The proposed framework for breast thermal image analysis that is aided with necessary preprocessing is found to be useful in assisting the early diagnosis of breast abnormalities.

Magnetoacoustic Tomography with Magnetic Induction (MAT-MI) for Breast Tumor Imaging: Numerical Modeling and Simulation

PubMed Central

Zhou, Lian; Li, Xu; Zhu, Shanan; He, Bin

2011-01-01

Magnetoacoustic tomography with magnetic induction (MAT-MI) was recently introduced as a noninvasive electrical conductivity imaging approach with high spatial resolution close to ultrasound imaging. In the present study, we test the feasibility of the MAT-MI method for breast tumor imaging using numerical modeling and computer simulation. Using the finite element method, we have built three dimensional numerical breast models with varieties of embedded tumors for this simulation study. In order to obtain an accurate and stable forward solution that does not have numerical errors caused by singular MAT-MI acoustic sources at conductivity boundaries, we first derive an integral forward method for calculating MAT-MI acoustic sources over the entire imaging volume. An inverse algorithm for reconstructing the MAT-MI acoustic source is also derived with spherical measurement aperture, which simulates a practical setup for breast imaging. With the numerical breast models, we have conducted computer simulations under different imaging parameter setups and all the results suggest that breast tumors that have large conductivity contrast to its surrounding tissues as reported in literature may be readily detected in the reconstructed MAT-MI images. In addition, our simulations also suggest that the sensitivity of imaging breast tumors using the presented MAT-MI setup depends more on the tumor location and the conductivity contrast between the tumor and its surrounding tissues than on the tumor size. PMID:21364262

A novel method based on learning automata for automatic lesion detection in breast magnetic resonance imaging.

PubMed

Salehi, Leila; Azmi, Reza

2014-07-01

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. In this way, magnetic resonance imaging (MRI) is emerging as a powerful tool for the detection of breast cancer. Breast MRI presently has two major challenges. First, its specificity is relatively poor, and it detects many false positives (FPs). Second, the method involves acquiring several high-resolution image volumes before, during, and after the injection of a contrast agent. The large volume of data makes the task of interpretation by the radiologist both complex and time-consuming. These challenges have led to the development of the computer-aided detection systems to improve the efficiency and accuracy of the interpretation process. Detection of suspicious regions of interests (ROIs) is a critical preprocessing step in dynamic contrast-enhanced (DCE)-MRI data evaluation. In this regard, this paper introduces a new automatic method to detect the suspicious ROIs for breast DCE-MRI based on region growing. The results indicate that the proposed method is thoroughly able to identify suspicious regions (accuracy of 75.39 ± 3.37 on PIDER breast MRI dataset). Furthermore, the FP per image in this method is averagely 7.92, which shows considerable improvement comparing to other methods like ROI hunter.

Application of Abbreviated Protocol of Magnetic Resonance Imaging for Breast Cancer Screening in Dense Breast Tissue.

PubMed

Chen, Shuang-Qing; Huang, Min; Shen, Yu-Ying; Liu, Chen-Lu; Xu, Chuan-Xiao

2017-03-01

The study aimed to evaluate the usefulness of an abbreviated protocol (AP) of magnetic resonance imaging (MRI) in comparison to a full diagnostic protocol (FDP) of MRI in the breast cancer screening with dense breast tissue. There are 478 female participants with dense breast tissue and negative mammography results, who were imaged with MRI using AP and FDP. The AP and FDP images were analyzed separately, and the sensitivity and specificity of breast cancer detection were calculated. The chi-square test and receiver operating characteristics curves were used to assess the breast cancer diagnostic capabilities of the two protocols. Sixteen cases of breast cancer from 478 patients with dense breasts were detected using the FDP method, with pathologic confirmation of nine cases of ductal carcinoma in situ, six cases of invasive ductal carcinoma, and one case of mucinous carcinoma. Fifteen cases of breast cancer were successfully screened using the AP method. The sensitivity showed no obvious significant difference between AP and FDP (χ 2  = 0.592, P = 0.623), but the specificity showed a statistically significant difference (χ 2  = 4.619, P = 0.036). The receiver operating characteristics curves showed high efficacy of both methods in the detection of breast cancer in dense breast tissue (the areas under the curve were 0.931 ± 0.025 and 0.947 ± 0.024, respectively), and the ability to diagnose breast cancer was not statistically significantly different between the two methods. The AP of MRI may improve the detection rate of breast cancer in dense breast tissue, and it may be useful in efficient breast cancer screening. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Computerized mass detection in whole breast ultrasound images: reduction of false positives using bilateral subtraction technique

NASA Astrophysics Data System (ADS)

Ikedo, Yuji; Fukuoka, Daisuke; Hara, Takeshi; Fujita, Hiroshi; Takada, Etsuo; Endo, Tokiko; Morita, Takako

2007-03-01

The comparison of left and right mammograms is a common technique used by radiologists for the detection and diagnosis of masses. In mammography, computer-aided detection (CAD) schemes using bilateral subtraction technique have been reported. However, in breast ultrasonography, there are no reports on CAD schemes using comparison of left and right breasts. In this study, we propose a scheme of false positive reduction based on bilateral subtraction technique in whole breast ultrasound images. Mass candidate regions are detected by using the information of edge directions. Bilateral breast images are registered with reference to the nipple positions and skin lines. A false positive region is detected based on a comparison of the average gray values of a mass candidate region and a region with the same position and same size as the candidate region in the contralateral breast. In evaluating the effectiveness of the false positive reduction method, three normal and three abnormal bilateral pairs of whole breast images were employed. These abnormal breasts included six masses larger than 5 mm in diameter. The sensitivity was 83% (5/6) with 13.8 (165/12) false positives per breast before applying the proposed reduction method. By applying the method, false positives were reduced to 4.5 (54/12) per breast without removing a true positive region. This preliminary study indicates that the bilateral subtraction technique is effective for improving the performance of a CAD scheme in whole breast ultrasound images.

Applicability of active infrared thermography for screening of human breast: a numerical study.

PubMed

Dua, Geetika; Mulaveesala, Ravibabu

2018-03-01

Active infrared thermography is a fast, painless, noncontact, and noninvasive imaging method, complementary to mammography, ultrasound, and magnetic resonance imaging methods for early diagnosis of breast cancer. This technique plays an important role in early detection of breast cancer to women of all ages, including pregnant or nursing women, with different sizes of breast, irrespective of either fatty or dense breast. This proposed complementary technique makes use of infrared emission emanating from the breast. Emanating radiations from the surface of the breast under test are detected with an infrared camera to map the thermal gradients over it, in order to reveal hidden tumors inside it. One of the reliable active infrared thermographic technique, linear frequency modulated thermal wave imaging is adopted to detect tumors present inside the breast. Further, phase and amplitude images are constructed using frequency and time-domain data analysis schemes. Obtained results show the potential of the proposed technique for early diagnosis of breast cancer in fatty as well as dense breasts. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Investigation of optimal parameters for penalized maximum-likelihood reconstruction applied to iodinated contrast-enhanced breast CT

NASA Astrophysics Data System (ADS)

Makeev, Andrey; Ikejimba, Lynda; Lo, Joseph Y.; Glick, Stephen J.

2016-03-01

Although digital mammography has reduced breast cancer mortality by approximately 30%, sensitivity and specificity are still far from perfect. In particular, the performance of mammography is especially limited for women with dense breast tissue. Two out of every three biopsies performed in the U.S. are unnecessary, thereby resulting in increased patient anxiety, pain, and possible complications. One promising tomographic breast imaging method that has recently been approved by the FDA is dedicated breast computed tomography (BCT). However, visualizing lesions with BCT can still be challenging for women with dense breast tissue due to the minimal contrast for lesions surrounded by fibroglandular tissue. In recent years there has been renewed interest in improving lesion conspicuity in x-ray breast imaging by administration of an iodinated contrast agent. Due to the fully 3-D imaging nature of BCT, as well as sub-optimal contrast enhancement while the breast is under compression with mammography and breast tomosynthesis, dedicated BCT of the uncompressed breast is likely to offer the best solution for injected contrast-enhanced x-ray breast imaging. It is well known that use of statistically-based iterative reconstruction in CT results in improved image quality at lower radiation dose. Here we investigate possible improvements in image reconstruction for BCT, by optimizing free regularization parameter in method of maximum likelihood and comparing its performance with clinical cone-beam filtered backprojection (FBP) algorithm.

Early Diagnosis of Breast Cancer.

PubMed

Wang, Lulu

2017-07-05

Early-stage cancer detection could reduce breast cancer death rates significantly in the long-term. The most critical point for best prognosis is to identify early-stage cancer cells. Investigators have studied many breast diagnostic approaches, including mammography, magnetic resonance imaging, ultrasound, computerized tomography, positron emission tomography and biopsy. However, these techniques have some limitations such as being expensive, time consuming and not suitable for young women. Developing a high-sensitive and rapid early-stage breast cancer diagnostic method is urgent. In recent years, investigators have paid their attention in the development of biosensors to detect breast cancer using different biomarkers. Apart from biosensors and biomarkers, microwave imaging techniques have also been intensely studied as a promising diagnostic tool for rapid and cost-effective early-stage breast cancer detection. This paper aims to provide an overview on recent important achievements in breast screening methods (particularly on microwave imaging) and breast biomarkers along with biosensors for rapidly diagnosing breast cancer.

DIEP Flap Breast Reconstruction in Patients with Breast Ptosis: 2-Stage Reconstruction Using 3-Dimensional Surface Imaging and a Printed Mold

PubMed Central

Yano, Kenji; Taminato, Mifue; Nomori, Michiko; Hosokawa, Ko

2017-01-01

Background: Autologous breast reconstruction can be performed for breasts with ptosis to a certain extent, but if patients desire to correct ptosis, mastopexy of the contralateral breast is indicated. However, accurate prediction of post-mastopexy breast shape is difficult to make, and symmetrical breast reconstruction requires certain experience. We have previously reported the use of three-dimensional (3D) imaging and printing technologies in deep inferior epigastric artery perforator (DIEP) flap breast reconstruction. In the present study, these technologies were applied to the reconstruction of breasts with ptosis. Methods: Eight breast cancer patients with ptotic breasts underwent two-stage unilateral DIEP flap breast reconstruction. In the initial surgery, tissue expander (TE) placement and contralateral mastopexy are performed simultaneously. Four to six months later, 3D bilateral breast imaging is performed after confirming that the shape of the contralateral breast (post-mastopexy) is somewhat stabilized, and a 3D-printed breast mold is created based on the mirror image of the shape of the contralateral breast acquired using analytical software. Then, DIEP flap surgery is performed, where the breast mold is used to determine the required flap volume and to shape the breast mound. Results: All flaps were engrafted without any major perioperative complications during both the initial and DIEP flap surgeries. Objective assessment of cosmetic outcome revealed that good breast symmetry was achieved in all cases. Conclusions: The method described here may allow even inexperienced surgeons to achieve reconstruction of symmetrical, non-ptotic breasts with ease and in a short time. While the requirement of two surgeries is a potential disadvantage, our method will be particularly useful in cases involving TEs, i.e., delayed reconstruction or immediate reconstruction involving significant skin resection. PMID:29184728

Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

NASA Astrophysics Data System (ADS)

Javanshir Moghaddam, Mandana; Tan, Tao; Karssemeijer, Nico; Platel, Bram

2014-03-01

Recent studies have demonstrated that applying Automated Breast Ultrasound in addition to mammography in women with dense breasts can lead to additional detection of small, early stage breast cancers which are occult in corresponding mammograms. In this paper, we proposed a fully automatic method for detecting the nipple location in 3D ultrasound breast images acquired from Automated Breast Ultrasound Systems. The nipple location is a valuable landmark to report the position of possible abnormalities in a breast or to guide image registration. To detect the nipple location, all images were normalized. Subsequently, features have been extracted in a multi scale approach and classification experiments were performed using a gentle boost classifier to identify the nipple location. The method was applied on a dataset of 100 patients with 294 different 3D ultrasound views from Siemens and U-systems acquisition systems. Our database is a representative sample of cases obtained in clinical practice by four medical centers. The automatic method could accurately locate the nipple in 90% of AP (Anterior-Posterior) views and in 79% of the other views.

Association between mammogram density and background parenchymal enhancement of breast MRI

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Danala, Gopichandh; Wang, Yunzhi; Zarafshani, Ali; Qian, Wei; Liu, Hong; Zheng, Bin

2018-02-01

Breast density has been widely considered as an important risk factor for breast cancer. The purpose of this study is to examine the association between mammogram density results and background parenchymal enhancement (BPE) of breast MRI. A dataset involving breast MR images was acquired from 65 high-risk women. Based on mammography density (BIRADS) results, the dataset was divided into two groups of low and high breast density cases. The Low-Density group has 15 cases with mammographic density (BIRADS 1 and 2), while the High-density group includes 50 cases, which were rated by radiologists as mammographic density BIRADS 3 and 4. A computer-aided detection (CAD) scheme was applied to segment and register breast regions depicted on sequential images of breast MRI scans. CAD scheme computed 20 global BPE features from the entire two breast regions, separately from the left and right breast region, as well as from the bilateral difference between left and right breast regions. An image feature selection method namely, CFS method, was applied to remove the most redundant features and select optimal features from the initial feature pool. Then, a logistic regression classifier was built using the optimal features to predict the mammogram density from the BPE features. Using a leave-one-case-out validation method, the classifier yields the accuracy of 82% and area under ROC curve, AUC=0.81+/-0.09. Also, the box-plot based analysis shows a negative association between mammogram density results and BPE features in the MRI images. This study demonstrated a negative association between mammogram density and BPE of breast MRI images.

Computerized analysis of sonograms for the detection of breast lesions

NASA Astrophysics Data System (ADS)

Drukker, Karen; Giger, Maryellen L.; Horsch, Karla; Vyborny, Carl J.

2002-05-01

With a renewed interest in using non-ionizing radiation for the screening of high risk women, there is a clear role for a computerized detection aid in ultrasound. Thus, we are developing a computerized detection method for the localization of lesions on breast ultrasound images. The computerized detection scheme utilizes two methods. Firstly, a radial gradient index analysis is used to distinguish potential lesions from normal parenchyma. Secondly, an image skewness analysis is performed to identify posterior acoustic shadowing. We analyzed 400 cases (757 images) consisting of complex cysts, solid benign lesions, and malignant lesions. The detection method yielded an overall sensitivity of 95% by image, and 99% by case at a false-positive rate of 0.94 per image. In 51% of all images, only the lesion itself was detected, while in 5% of the images only the shadowing was identified. For malignant lesions these numbers were 37% and 9%, respectively. In summary, we have developed a computer detection method for lesions on ultrasound images of the breast, which may ultimately aid in breast cancer screening.

Automated Segmentation of Nuclei in Breast Cancer Histopathology Images.

PubMed

Paramanandam, Maqlin; O'Byrne, Michael; Ghosh, Bidisha; Mammen, Joy John; Manipadam, Marie Therese; Thamburaj, Robinson; Pakrashi, Vikram

2016-01-01

The process of Nuclei detection in high-grade breast cancer images is quite challenging in the case of image processing techniques due to certain heterogeneous characteristics of cancer nuclei such as enlarged and irregularly shaped nuclei, highly coarse chromatin marginalized to the nuclei periphery and visible nucleoli. Recent reviews state that existing techniques show appreciable segmentation accuracy on breast histopathology images whose nuclei are dispersed and regular in texture and shape; however, typical cancer nuclei are often clustered and have irregular texture and shape properties. This paper proposes a novel segmentation algorithm for detecting individual nuclei from Hematoxylin and Eosin (H&E) stained breast histopathology images. This detection framework estimates a nuclei saliency map using tensor voting followed by boundary extraction of the nuclei on the saliency map using a Loopy Back Propagation (LBP) algorithm on a Markov Random Field (MRF). The method was tested on both whole-slide images and frames of breast cancer histopathology images. Experimental results demonstrate high segmentation performance with efficient precision, recall and dice-coefficient rates, upon testing high-grade breast cancer images containing several thousand nuclei. In addition to the optimal performance on the highly complex images presented in this paper, this method also gave appreciable results in comparison with two recently published methods-Wienert et al. (2012) and Veta et al. (2013), which were tested using their own datasets.

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keller, Brad M.; Nathan, Diane L.; Wang Yan

Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., 'FOR PROCESSING') andmore » vendor postprocessed (i.e., 'FOR PRESENTATION'), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Results: Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r= 0.82, p < 0.001) and processed (r= 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r= 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's {kappa}{>=} 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). Conclusions: The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies.« less

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation

PubMed Central

Keller, Brad M.; Nathan, Diane L.; Wang, Yan; Zheng, Yuanjie; Gee, James C.; Conant, Emily F.; Kontos, Despina

2012-01-01

Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., “FOR PROCESSING”) and vendor postprocessed (i.e., “FOR PRESENTATION”), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Results: Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r = 0.82, p < 0.001) and processed (r = 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r = 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's κ ≥ 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). Conclusions: The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies. PMID:22894417

Compound Radar Approach for Breast Imaging.

PubMed

Byrne, Dallan; Sarafianou, Mantalena; Craddock, Ian J

2017-01-01

Multistatic radar apertures record scattering at a number of receivers when the target is illuminated by a single transmitter, providing more scattering information than its monostatic counterpart per transmission angle. This paper considers the well-known problem of detecting tumor targets within breast phantoms using multistatic radar. To accurately image potentially cancerous targets size within the breast, a significant number of multistatic channels are required in order to adequately calibrate-out unwanted skin reflections, increase the immunity to clutter, and increase the dynamic range of a breast radar imaging system. However, increasing the density of antennas within a physical array is inevitably limited by the geometry of the antenna elements designed to operate with biological tissues at microwave frequencies. A novel compound imaging approach is presented to overcome these physical constraints and improve the imaging capabilities of a multistatic radar imaging modality for breast scanning applications. The number of transmit-receive (TX-RX) paths available for imaging are increased by performing a number of breast scans with varying array positions. A skin calibration method is presented to reduce the influence of skin reflections from each channel. Calibrated signals are applied to receive a beamforming method, compounding the data from each scan to produce a microwave radar breast profile. The proposed imaging method is evaluated with experimental data obtained from constructed phantoms of varying complexity, skin contour asymmetries, and challenging tumor positions and sizes. For each imaging scenario outlined in this study, the proposed compound imaging technique improves skin calibration, clearly detects small targets, and substantially reduces the level of undesirable clutter within the profile.

A comparative study of volumetric breast density estimation in digital mammography and magnetic resonance imaging: results from a high-risk population

NASA Astrophysics Data System (ADS)

Kontos, Despina; Xing, Ye; Bakic, Predrag R.; Conant, Emily F.; Maidment, Andrew D. A.

2010-03-01

We performed a study to compare methods for volumetric breast density estimation in digital mammography (DM) and magnetic resonance imaging (MRI) for a high-risk population of women. DM and MRI images of the unaffected breast from 32 women with recently detected abnormalities and/or previously diagnosed breast cancer (age range 31-78 yrs, mean 50.3 yrs) were retrospectively analyzed. DM images were analyzed using QuantraTM (Hologic Inc). The MRI images were analyzed using a fuzzy-C-means segmentation algorithm on the T1 map. Both methods were compared to Cumulus (Univ. Toronto). Volumetric breast density estimates from DM and MRI are highly correlated (r=0.90, p<=0.001). The correlation between the volumetric and the area-based density measures is lower and depends on the training background of the Cumulus software user (r=0.73-84, p<=0.001). In terms of absolute values, MRI provides the lowest volumetric estimates (mean=14.63%), followed by the DM volumetric (mean=22.72%) and area-based measures (mean=29.35%). The MRI estimates of the fibroglandular volume are statistically significantly lower than the DM estimates for women with very low-density breasts (p<=0.001). We attribute these differences to potential partial volume effects in MRI and differences in the computational aspects of the image analysis methods in MRI and DM. The good correlation between the volumetric and the area-based measures, shown to correlate with breast cancer risk, suggests that both DM and MRI volumetric breast density measures can aid in breast cancer risk assessment. Further work is underway to fully-investigate the association between volumetric breast density measures and breast cancer risk.

Imaging Breast Density: Established and Emerging Modalities1

PubMed Central

Chen, Jeon-Hor; Gulsen, Gultekin; Su, Min-Ying

2015-01-01

Mammographic density has been proven as an independent risk factor for breast cancer. Women with dense breast tissue visible on a mammogram have a much higher cancer risk than women with little density. A great research effort has been devoted to incorporate breast density into risk prediction models to better estimate each individual’s cancer risk. In recent years, the passage of breast density notification legislation in many states in USA requires that every mammography report should provide information regarding the patient’s breast density. Accurate definition and measurement of breast density are thus important, which may allow all the potential clinical applications of breast density to be implemented. Because the two-dimensional mammography-based measurement is subject to tissue overlapping and thus not able to provide volumetric information, there is an urgent need to develop reliable quantitative measurements of breast density. Various new imaging technologies are being developed. Among these new modalities, volumetric mammographic density methods and three-dimensional magnetic resonance imaging are the most well studied. Besides, emerging modalities, including different x-ray–based, optical imaging, and ultrasound-based methods, have also been investigated. All these modalities may either overcome some fundamental problems related to mammographic density or provide additional density and/or compositional information. The present review article aimed to summarize the current established and emerging imaging techniques for the measurement of breast density and the evidence of the clinical use of these density methods from the literature. PMID:26692524

Fully automated chest wall line segmentation in breast MRI by using context information

NASA Astrophysics Data System (ADS)

Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.; Localio, A. Russell; Schnall, Mitchell D.; Kontos, Despina

2012-03-01

Breast MRI has emerged as an effective modality for the clinical management of breast cancer. Evidence suggests that computer-aided applications can further improve the diagnostic accuracy of breast MRI. A critical and challenging first step for automated breast MRI analysis, is to separate the breast as an organ from the chest wall. Manual segmentation or user-assisted interactive tools are inefficient, tedious, and error-prone, which is prohibitively impractical for processing large amounts of data from clinical trials. To address this challenge, we developed a fully automated and robust computerized segmentation method that intensively utilizes context information of breast MR imaging and the breast tissue's morphological characteristics to accurately delineate the breast and chest wall boundary. A critical component is the joint application of anisotropic diffusion and bilateral image filtering to enhance the edge that corresponds to the chest wall line (CWL) and to reduce the effect of adjacent non-CWL tissues. A CWL voting algorithm is proposed based on CWL candidates yielded from multiple sequential MRI slices, in which a CWL representative is generated and used through a dynamic time warping (DTW) algorithm to filter out inferior candidates, leaving the optimal one. Our method is validated by a representative dataset of 20 3D unilateral breast MRI scans that span the full range of the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) fibroglandular density categorization. A promising performance (average overlay percentage of 89.33%) is observed when the automated segmentation is compared to manually segmented ground truth obtained by an experienced breast imaging radiologist. The automated method runs time-efficiently at ~3 minutes for each breast MR image set (28 slices).

Current and Future Methods for Measuring Breast Density: A Brief Comparative Review

PubMed Central

Sak, Mark A.; Littrup, Peter J.; Duric, Neb; Mullooly, Maeve; Sherman, Mark E.; Gierach, Gretchen L.

2017-01-01

Breast density is one of the strongest predictors of breast cancer risk. Women with the densest breasts are 4 to 6 times more likely to develop cancer compared with those with the lowest densities. Breast density is generally assessed using mammographic imaging; however, this approach has limitations. Magnetic resonance imaging and ultrasound tomography are some alternative imaging modalities that can aid mammography in patient screening and the measurement of breast density. As breast density becomes more commonly discussed, knowledge of the advantages and limitations of breast density as a marker of risk will become more critical. This review article discusses the relationship between breast density and breast cancer risk, lists the benefits and drawbacks of using multiple different imaging modalities to measure density and briefly discusses how breast density will be applied to aid in breast cancer prevention and treatment. PMID:28943893

Retrospective and comparative analysis of (99m)Tc-Sestamibi breast specific gamma imaging versus mammography, ultrasound, and magnetic resonance imaging for the detection of breast cancer in Chinese women.

PubMed

Yu, Xiuyan; Hu, Guoming; Zhang, Zhigang; Qiu, Fuming; Shao, Xuan; Wang, Xiaochen; Zhan, Hongwei; Chen, Yiding; Deng, Yongchuan; Huang, Jian

2016-07-11

Diagnosing breast cancer during the early stage may be helpful for decreasing cancer-related mortality. In Western developed countries, mammographies have been the gold standard for breast cancer detection. However, Chinese women usually have denser and smaller-sized breasts compared to Caucasian women, which decreases the diagnostic accuracy of mammography. However, breast specific gamma imaging, a type of molecular functional breast imaging, has been used for the accurate diagnosis of breast cancer and is not influenced by breast density. Our objective was to analyze the breast specific gamma imaging (BSGI) diagnostic value for Chinese women. During a 2-year period, 357 women were diagnosed and treated at our oncology department and received BSGI in addition to mammography (MMG), ultrasound (US) and magnetic resonance imaging (MRI) for diagnostic assessment. We investigated the sensitivity and specificity of each method of detection and compared the biological profiles of the four imaging methods. A total of 357 women received a final surgical pathology diagnosis, with 168 malignant diseases (58.5 %) and 119 benign diseases (41.5 %). Of these, 166 underwent the four imaging tests preoperatively. The sensitivity of BSGI was 80.35 and 82.14 % by US, 75.6 % by MMG, and 94.06 % by MRI. Furthermore, the breast cancer diagnosis specificity of BSGI was high (83.19 % vs. 77.31 % vs. 66.39 % vs. 67.69 %, respectively). The BSGI diagnostic sensitivity for mammographic breast density in women was superior to mammography and more sensitive for non-luminal A subtypes (luminal A vs. non-luminal A, 68.63 % vs. 88.30 %). BSGI may help improve the ability to diagnose early stage breast cancer for Chinese women, particularly for ductal carcinoma in situ (DCIS), mammographic breast density and non-luminal A breast cancer.

A comparison of methods to evaluate gray scale response of tomosynthesis systems using a software breast phantom

NASA Astrophysics Data System (ADS)

Sousa, Maria A. Z.; Bakic, Predrag R.; Schiabel, Homero; Maidment, Andrew D. A.

2017-03-01

Digital breast tomosynthesis (DBT) has been shown to be an effective imaging tool for breast cancer diagnosis as it provides three-dimensional images of the breast with minimal tissue overlap. The quality of the reconstructed image depends on many factors that can be assessed using uniform or realistic phantoms. In this paper, we created four models of phantoms using an anthropomorphic software breast phantom and compared four methods to evaluate the gray scale response in terms of the contrast, noise and detectability of adipose and glandular tissues binarized according to phantom ground truth. For each method, circular regions of interest (ROIs) were selected with various sizes, quantity and positions inside a square area in the phantom. We also estimated the percent density of the simulated breast and the capability of distinguishing both tissues by receiver operating characteristic (ROC) analysis. Results shows a sensitivity of the methods to the ROI size, placement and to the slices considered.

Optical Breast Shape Capture and Finite Element Mesh Generation for Electrical Impedance Tomography

PubMed Central

Forsyth, J.; Borsic, A.; Halter, R.J.; Hartov, A.; Paulsen, K.D.

2011-01-01

X-Ray mammography is the standard for breast cancer screening. The development of alternative imaging modalities is desirable because Mammograms expose patients to ionizing radiation. Electrical Impedance Tomography (EIT) may be used to determine tissue conductivity, a property which is an indicator of cancer presence. EIT is also a low-cost imaging solution and does not involve ionizing radiation. In breast EIT, impedance measurements are made using electrodes placed on the surface of the patient’s breast. The complex conductivity of the volume of the breast is estimated by a reconstruction algorithm. EIT reconstruction is a severely ill-posed inverse problem. As a result, noisy instrumentation and incorrect modelling of the electrodes and domain shape produce significant image artefacts. In this paper, we propose a method that has the potential to reduce these errors by accurately modelling the patient breast shape. A 3D hand-held optical scanner is used to acquire the breast geometry and electrode positions. We develop methods for processing the data from the scanner and producing volume meshes accurately matching the breast surface and electrode locations, which can be used for image reconstruction. We demonstrate this method for a plaster breast phantom and a human subject. Using this approach will allow patient-specific finite element meshes to be generated which has the potential to improve the clinical value of EIT for breast cancer diagnosis. PMID:21646711

Limited angle breast ultrasound tomography with a priori information and artifact removal

NASA Astrophysics Data System (ADS)

Jintamethasawat, Rungroj; Zhu, Yunhao; Kripfgans, Oliver D.; Yuan, Jie; Goodsitt, Mitchell M.; Carson, Paul L.

2017-03-01

In B-mode images from dual-sided ultrasound, it has been shown that by delineating structures suspected of being relatively homogeneous, one can enhance limited angle tomography to produce speed of sound images in the same view as X-ray Digital Breast Tomography (DBT). This could allow better breast cancer detection and discrimination, as well as improved registration of the ultrasound and X-ray images, because of the similarity of SOS and X-ray contrast in the breast. However, this speed of sound reconstruction method relies strongly on B-mode or other reflection mode segmentation. If that information is limited or incorrect, artifacts will appear in the reconstructed images. Therefore, the iterative speed of sound reconstruction algorithm has been modified in a manner of simultaneously utilizing the image segmentations and removing most artifacts. The first step of incorporating a priori information is solved by any nonlinearnonconvex optimization method while artifact removal is accomplished by employing the fast split Bregman method to perform total-variation (TV) regularization for image denoising. The proposed method was demonstrated in simplified simulations of our dual-sided ultrasound scanner. To speed these computations two opposed 40-element ultrasound linear arrays with 0.5 MHz center frequency were simulated for imaging objects in a uniform background. The proposed speed of sound reconstruction method worked well with both bent-ray and full-wave inversion methods. This is also the first demonstration of successful full-wave medical ultrasound tomography in the limited angle geometry. Presented results lend credibility to a possible translation of this method to clinical breast imaging.

Denoised ordered subset statistically penalized algebraic reconstruction technique (DOS-SPART) in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Garrett, John; Li, Yinsheng; Li, Ke; Chen, Guang-Hong

2017-03-01

Digital breast tomosynthesis (DBT) is a three dimensional (3D) breast imaging modality in which projections are acquired over a limited angular span around the compressed breast and reconstructed into image slices parallel to the detector. DBT has been shown to help alleviate the breast tissue overlapping issues of two dimensional (2D) mammography. Since the overlapping tissues may simulate cancer masses or obscure true cancers, this improvement is critically important for improved breast cancer screening and diagnosis. In this work, a model-based image reconstruction method is presented to show that spatial resolution in DBT volumes can be maintained while dose is reduced using the presented method when compared to that of a state-of-the-art commercial reconstruction technique. Spatial resolution was measured in phantom images and subjectively in a clinical dataset. Noise characteristics were explored in a cadaver study. In both the quantitative and subjective results the image sharpness was maintained and overall image quality was maintained at reduced doses when the model-based iterative reconstruction was used to reconstruct the volumes.

Review of optical breast imaging and spectroscopy

NASA Astrophysics Data System (ADS)

Grosenick, Dirk; Rinneberg, Herbert; Cubeddu, Rinaldo; Taroni, Paola

2016-09-01

Diffuse optical imaging and spectroscopy of the female breast is an area of active research. We review the present status of this field and discuss the broad range of methodologies and applications. Starting with a brief overview on breast physiology, the remodeling of vasculature and extracellular matrix caused by solid tumors is highlighted that is relevant for contrast in optical imaging. Then, the various instrumental techniques and the related methods of data analysis and image generation are described and compared including multimodality instrumentation, fluorescence mammography, broadband spectroscopy, and diffuse correlation spectroscopy. We review the clinical results on functional properties of malignant and benign breast lesions compared to host tissue and discuss the various methods to improve contrast between healthy and diseased tissue, such as enhanced spectroscopic information, dynamic variations of functional properties, pharmacokinetics of extrinsic contrast agents, including the enhanced permeability and retention effect. We discuss research on monitoring neoadjuvant chemotherapy and on breast cancer risk assessment as potential clinical applications of optical breast imaging and spectroscopy. Moreover, we consider new experimental approaches, such as photoacoustic imaging and long-wavelength tissue spectroscopy.

Technical Note: Validation of two methods to determine contact area between breast and compression paddle in mammography.

PubMed

Branderhorst, Woutjan; de Groot, Jerry E; van Lier, Monique G J T B; Highnam, Ralph P; den Heeten, Gerard J; Grimbergen, Cornelis A

2017-08-01

To assess the accuracy of two methods of determining the contact area between the compression paddle and the breast in mammography. An accurate method to determine the contact area is essential to accurately calculate the average compression pressure applied by the paddle. For a set of 300 breast compressions, we measured the contact areas between breast and paddle, both capacitively using a transparent foil with indium-tin-oxide (ITO) coating attached to the paddle, and retrospectively from the obtained mammograms using image processing software (Volpara Enterprise, algorithm version 1.5.2). A gold standard was obtained from video images of the compressed breast. During each compression, the breast was illuminated from the sides in order to create a dark shadow on the video image where the breast was in contact with the compression paddle. We manually segmented the shadows captured at the time of x-ray exposure and measured their areas. We found a strong correlation between the manual segmentations and the capacitive measurements [r = 0.989, 95% CI (0.987, 0.992)] and between the manual segmentations and the image processing software [r = 0.978, 95% CI (0.972, 0.982)]. Bland-Altman analysis showed a bias of -0.0038 dm 2 for the capacitive measurement (SD 0.0658, 95% limits of agreement [-0.1329, 0.1252]) and -0.0035 dm 2 for the image processing software [SD 0.0962, 95% limits of agreement (-0.1921, 0.1850)]. The size of the contact area between the paddle and the breast can be determined accurately and precisely, both in real-time using the capacitive method, and retrospectively using image processing software. This result is beneficial for scientific research, data analysis and quality control systems that depend on one of these two methods for determining the average pressure on the breast during mammographic compression. © 2017 Sigmascreening B.V. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Image segmentation and 3D visualization for MRI mammography

NASA Astrophysics Data System (ADS)

Li, Lihua; Chu, Yong; Salem, Angela F.; Clark, Robert A.

2002-05-01

MRI mammography has a number of advantages, including the tomographic, and therefore three-dimensional (3-D) nature, of the images. It allows the application of MRI mammography to breasts with dense tissue, post operative scarring, and silicon implants. However, due to the vast quantity of images and subtlety of difference in MR sequence, there is a need for reliable computer diagnosis to reduce the radiologist's workload. The purpose of this work was to develop automatic breast/tissue segmentation and visualization algorithms to aid physicians in detecting and observing abnormalities in breast. Two segmentation algorithms were developed: one for breast segmentation, the other for glandular tissue segmentation. In breast segmentation, the MRI image is first segmented using an adaptive growing clustering method. Two tracing algorithms were then developed to refine the breast air and chest wall boundaries of breast. The glandular tissue segmentation was performed using an adaptive thresholding method, in which the threshold value was spatially adaptive using a sliding window. The 3D visualization of the segmented 2D slices of MRI mammography was implemented under IDL environment. The breast and glandular tissue rendering, slicing and animation were displayed.

TU-A-17A-02: In Memoriam of Ben Galkin: Virtual Tools for Validation of X-Ray Breast Imaging Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myers, K; Bakic, P; Abbey, C

2014-06-15

This symposium will explore simulation methods for the preclinical evaluation of novel 3D and 4D x-ray breast imaging systems – the subject of AAPM taskgroup TG234. Given the complex design of modern imaging systems, simulations offer significant advantages over long and costly clinical studies in terms of reproducibility, reduced radiation exposures, a known reference standard, and the capability for studying patient and disease subpopulations through appropriate choice of simulation parameters. Our focus will be on testing the realism of software anthropomorphic phantoms and virtual clinical trials tools developed for the optimization and validation of breast imaging systems. The symposium willmore » review the stateof- the-science, as well as the advantages and limitations of various approaches to testing realism of phantoms and simulated breast images. Approaches based upon the visual assessment of synthetic breast images by expert observers will be contrasted with approaches based upon comparing statistical properties between synthetic and clinical images. The role of observer models in the assessment of realism will be considered. Finally, an industry perspective will be presented, summarizing the role and importance of virtual tools and simulation methods in product development. The challenges and conditions that must be satisfied in order for computational modeling and simulation to play a significantly increased role in the design and evaluation of novel breast imaging systems will be addressed. Learning Objectives: Review the state-of-the science in testing realism of software anthropomorphic phantoms and virtual clinical trials tools; Compare approaches based upon the visual assessment by expert observers vs. the analysis of statistical properties of synthetic images; Discuss the role of observer models in the assessment of realism; Summarize the industry perspective to virtual methods for breast imaging.« less

Determination of female breast tumor and its parameter estimation by thermal simulation

NASA Astrophysics Data System (ADS)

Chen, Xin-guang; Xu, A.-qing; Yang, Hong-qin; Wang, Yu-hua; Xie, Shu-sen

2010-02-01

Thermal imaging is an emerging method for early detection of female breast tumor. The main challenge for thermal imaging used in breast clinics lies in how to detect or locate the tumor and obtain its related parameters. The purpose of this study is to apply an improved method which combined a genetic algorithm with finite element thermal analysis to determine the breast tumor and its parameters, such as the size, location, metabolic heat generation and blood perfusion rate. A finite element model for breast embedded a tumor was used to investigate the temperature distribution, and then the influences of tumor metabolic heat generation, tumor location and tumor size on the temperature were studied by use of an improved genetic algorithm. The results show that thermal imaging is a potential and effective detection tool for early breast tumor, and thermal simulation may be helpful for the explanation of breast thermograms.

Breast surface estimation for radar-based breast imaging systems.

PubMed

Williams, Trevor C; Sill, Jeff M; Fear, Elise C

2008-06-01

Radar-based microwave breast-imaging techniques typically require the antennas to be placed at a certain distance from or on the breast surface. This requires prior knowledge of the breast location, shape, and size. The method proposed in this paper for obtaining this information is based on a modified tissue sensing adaptive radar algorithm. First, a breast surface detection scan is performed. Data from this scan are used to localize the breast by creating an estimate of the breast surface. If required, the antennas may then be placed at specified distances from the breast surface for a second tumor-sensing scan. This paper introduces the breast surface estimation and antenna placement algorithms. Surface estimation and antenna placement results are demonstrated on three-dimensional breast models derived from magnetic resonance images.

Automatic segmentation of mammogram and tomosynthesis images

NASA Astrophysics Data System (ADS)

Sargent, Dusty; Park, Sun Young

2016-03-01

Breast cancer is a one of the most common forms of cancer in terms of new cases and deaths both in the United States and worldwide. However, the survival rate with breast cancer is high if it is detected and treated before it spreads to other parts of the body. The most common screening methods for breast cancer are mammography and digital tomosynthesis, which involve acquiring X-ray images of the breasts that are interpreted by radiologists. The work described in this paper is aimed at optimizing the presentation of mammography and tomosynthesis images to the radiologist, thereby improving the early detection rate of breast cancer and the resulting patient outcomes. Breast cancer tissue has greater density than normal breast tissue, and appears as dense white image regions that are asymmetrical between the breasts. These irregularities are easily seen if the breast images are aligned and viewed side-by-side. However, since the breasts are imaged separately during mammography, the images may be poorly centered and aligned relative to each other, and may not properly focus on the tissue area. Similarly, although a full three dimensional reconstruction can be created from digital tomosynthesis images, the same centering and alignment issues can occur for digital tomosynthesis. Thus, a preprocessing algorithm that aligns the breasts for easy side-by-side comparison has the potential to greatly increase the speed and accuracy of mammogram reading. Likewise, the same preprocessing can improve the results of automatic tissue classification algorithms for mammography. In this paper, we present an automated segmentation algorithm for mammogram and tomosynthesis images that aims to improve the speed and accuracy of breast cancer screening by mitigating the above mentioned problems. Our algorithm uses information in the DICOM header to facilitate preprocessing, and incorporates anatomical region segmentation and contour analysis, along with a hidden Markov model (HMM) for processing the multi-frame tomosynthesis images. The output of the algorithm is a new set of images that have been processed to show only the diagnostically relevant region and align the breasts so that they can be easily compared side-by-side. Our method has been tested on approximately 750 images, including various examples of mammogram, tomosynthesis, and scanned images, and has correctly segmented the diagnostically relevant image region in 97% of cases.

Imaging-Assisted Large-Format Breast Pathology: Program Rationale and Development in a Nonprofit Health System in the United States

PubMed Central

Tucker, F. Lee

2012-01-01

Modern breast imaging, including magnetic resonance imaging, provides an increasingly clear depiction of breast cancer extent, often with suboptimal pathologic confirmation. Pathologic findings guide management decisions, and small increments in reported tumor characteristics may rationalize significant changes in therapy and staging. Pathologic techniques to grossly examine resected breast tissue have changed little during this era of improved breast imaging and still rely primarily on the techniques of gross inspection and specimen palpation. Only limited imaging information is typically conveyed to pathologists, typically in the form of wire-localization images from breast-conserving procedures. Conventional techniques of specimen dissection and section submission destroy the three-dimensional integrity of the breast anatomy and tumor distribution. These traditional methods of breast specimen examination impose unnecessary limitations on correlation with imaging studies, measurement of cancer extent, multifocality, and margin distance. Improvements in pathologic diagnosis, reporting, and correlation of breast cancer characteristics can be achieved by integrating breast imagers into the specimen examination process and the use of large-format sections which preserve local anatomy. This paper describes the successful creation of a large-format pathology program to routinely serve all patients in a busy interdisciplinary breast center associated with a community-based nonprofit health system in the United States. PMID:23316372

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akhbardeh, Alireza; Jacobs, Michael A.; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

2012-04-15

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), andmore » diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.« less

Analysis of percent density estimates from digital breast tomosynthesis projection images

NASA Astrophysics Data System (ADS)

Bakic, Predrag R.; Kontos, Despina; Zhang, Cuiping; Yaffe, Martin J.; Maidment, Andrew D. A.

2007-03-01

Women with dense breasts have an increased risk of breast cancer. Breast density is typically measured as the percent density (PD), the percentage of non-fatty (i.e., dense) tissue in breast images. Mammographic PD estimates vary, in part, due to the projective nature of mammograms. Digital breast tomosynthesis (DBT) is a novel radiographic method in which 3D images of the breast are reconstructed from a small number of projection (source) images, acquired at different positions of the x-ray focus. DBT provides superior visualization of breast tissue and has improved sensitivity and specificity as compared to mammography. Our long-term goal is to test the hypothesis that PD obtained from DBT is superior in estimating cancer risk compared with other modalities. As a first step, we have analyzed the PD estimates from DBT source projections since the results would be independent of the reconstruction method. We estimated PD from MLO mammograms (PD M) and from individual DBT projections (PD T). We observed good agreement between PD M and PD T from the central projection images of 40 women. This suggests that variations in breast positioning, dose, and scatter between mammography and DBT do not negatively affect PD estimation. The PD T estimated from individual DBT projections of nine women varied with the angle between the projections. This variation is caused by the 3D arrangement of the breast dense tissue and the acquisition geometry.

System Optimization and Iterative Image Reconstruction in Photoacoustic Computed Tomography for Breast Imaging

NASA Astrophysics Data System (ADS)

Lou, Yang

Photoacoustic computed tomography(PACT), also known as optoacoustic tomography (OAT), is an emerging imaging technique that has developed rapidly in recent years. The combination of the high optical contrast and the high acoustic resolution of this hybrid imaging technique makes it a promising candidate for human breast imaging, where conventional imaging techniques including X-ray mammography, B-mode ultrasound, and MRI suffer from low contrast, low specificity for certain breast types, and additional risks related to ionizing radiation. Though significant works have been done to push the frontier of PACT breast imaging, it is still challenging to successfully build a PACT breast imaging system and apply it to wide clinical use because of various practical reasons. First, computer simulation studies are often conducted to guide imaging system designs, but the numerical phantoms employed in most previous works consist of simple geometries and do not reflect the true anatomical structures within the breast. Therefore the effectiveness of such simulation-guided PACT system in clinical experiments will be compromised. Second, it is challenging to design a system to simultaneously illuminate the entire breast with limited laser power. Some heuristic designs have been proposed where the illumination is non-stationary during the imaging procedure, but the impact of employing such a design has not been carefully studied. Third, current PACT imaging systems are often optimized with respect to physical measures such as resolution or signal-to-noise ratio (SNR). It would be desirable to establish an assessing framework where the detectability of breast tumor can be directly quantified, therefore the images produced by such optimized imaging systems are not only visually appealing, but most informative in terms of the tumor detection task. Fourth, when imaging a large three-dimensional (3D) object such as the breast, iterative reconstruction algorithms are often utilized to alleviate the need to collect densely sampled measurement data hence a long scanning time. However, the heavy computation burden associated with iterative algorithms largely hinders its application in PACT breast imaging. This dissertation is dedicated to address these aforementioned problems in PACT breast imaging. A method that generates anatomically realistic numerical breast phantoms is first proposed to facilitate computer simulation studies in PACT. The non-stationary illumination designs for PACT breast imaging are then systematically investigated in terms of its impact on reconstructed images. We then apply signal detection theory to assess different system designs to demonstrate how an objective, task-based measure can be established for PACT breast imaging. To address the slow computation time of iterative algorithms for PACT imaging, we propose an acceleration method that employs an approximated but much faster adjoint operator during iterations, which can reduce the computation time by a factor of six without significantly compromising image quality. Finally, some clinical results are presented to demonstrate that the PACT breast imaging can resolve most major and fine vascular structures within the breast, along with some pathological biomarkers that may indicate tumor development.

Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prado, T. L.; Galuzio, P. P.; Lopes, S. R.

Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with amore » better control over the spurious fragments in the image.« less

Modification of Kirchhoff migration with variable sound speed and attenuation for acoustic imaging of media and application to tomographic imaging of the breast

PubMed Central

Schmidt, Steven; Duric, Nebojsa; Li, Cuiping; Roy, Olivier; Huang, Zhi-Feng

2011-01-01

Purpose: To explore the feasibility of improving cross-sectional reflection imaging of the breast using refractive and attenuation corrections derived from ultrasound tomography data. Methods: The authors have adapted the planar Kirchhoff migration method, commonly used in geophysics to reconstruct reflection images, for use in ultrasound tomography imaging of the breast. Furthermore, the authors extended this method to allow for refractive and attenuative corrections. Using clinical data obtained with a breast imaging prototype, the authors applied this method to generate cross-sectional reflection images of the breast that were corrected using known distributions of sound speed and attenuation obtained from the same data. Results: A comparison of images reconstructed with and without the corrections showed varying degrees of improvement. The sound speed correction resulted in sharpening of detail, while the attenuation correction reduced the central darkening caused by path length dependent losses. The improvements appeared to be greatest when dense tissue was involved and the least for fatty tissue. These results are consistent with the expectation that denser tissues lead to both greater refractive effects and greater attenuation. Conclusions: Although conventional ultrasound techniques use time-gain control to correct for attenuation gradients, these corrections lead to artifacts because the true attenuation distribution is not known. The use of constant sound speed leads to additional artifacts that arise from not knowing the sound speed distribution. The authors show that in the context of ultrasound tomography, it is possible to construct reflection images of the breast that correct for inhomogeneous distributions of both sound speed and attenuation. PMID:21452737

Medical imaging and computers in the diagnosis of breast cancer

NASA Astrophysics Data System (ADS)

Giger, Maryellen L.

2014-09-01

Computer-aided diagnosis (CAD) and quantitative image analysis (QIA) methods (i.e., computerized methods of analyzing digital breast images: mammograms, ultrasound, and magnetic resonance images) can yield novel image-based tumor and parenchyma characteristics (i.e., signatures that may ultimately contribute to the design of patient-specific breast cancer management plans). The role of QIA/CAD has been expanding beyond screening programs towards applications in risk assessment, diagnosis, prognosis, and response to therapy as well as in data mining to discover relationships of image-based lesion characteristics with genomics and other phenotypes; thus, as they apply to disease states. These various computer-based applications are demonstrated through research examples from the Giger Lab.

Automatic correspondence detection in mammogram and breast tomosynthesis images

NASA Astrophysics Data System (ADS)

Ehrhardt, Jan; Krüger, Julia; Bischof, Arpad; Barkhausen, Jörg; Handels, Heinz

2012-02-01

Two-dimensional mammography is the major imaging modality in breast cancer detection. A disadvantage of mammography is the projective nature of this imaging technique. Tomosynthesis is an attractive modality with the potential to combine the high contrast and high resolution of digital mammography with the advantages of 3D imaging. In order to facilitate diagnostics and treatment in the current clinical work-flow, correspondences between tomosynthesis images and previous mammographic exams of the same women have to be determined. In this paper, we propose a method to detect correspondences in 2D mammograms and 3D tomosynthesis images automatically. In general, this 2D/3D correspondence problem is ill-posed, because a point in the 2D mammogram corresponds to a line in the 3D tomosynthesis image. The goal of our method is to detect the "most probable" 3D position in the tomosynthesis images corresponding to a selected point in the 2D mammogram. We present two alternative approaches to solve this 2D/3D correspondence problem: a 2D/3D registration method and a 2D/2D mapping between mammogram and tomosynthesis projection images with a following back projection. The advantages and limitations of both approaches are discussed and the performance of the methods is evaluated qualitatively and quantitatively using a software phantom and clinical breast image data. Although the proposed 2D/3D registration method can compensate for moderate breast deformations caused by different breast compressions, this approach is not suitable for clinical tomosynthesis data due to the limited resolution and blurring effects perpendicular to the direction of projection. The quantitative results show that the proposed 2D/2D mapping method is capable of detecting corresponding positions in mammograms and tomosynthesis images automatically for 61 out of 65 landmarks. The proposed method can facilitate diagnosis, visual inspection and comparison of 2D mammograms and 3D tomosynthesis images for the physician.

Evaluation of a new breast-shaped compensation filter for a newly built breast imaging system

NASA Astrophysics Data System (ADS)

Cai, Weixing; Ning, Ruola; Zhang, Yan; Conover, David

2007-03-01

A new breast-shaped compensation filter has been designed and fabricated for breast imaging using our newly built breast imaging (CBCTBI) system, which is able to scan an uncompressed breast with pendant geometry. The shape of this compensation filter is designed based on an average-sized breast phantom. Unlike conventional bow-tie compensation filters, its cross-sectional profile varies along the chest wall-to-nipple direction for better compensation for the shape of a breast. Breast phantoms of three different sizes are used to evaluate the performance of this compensation filter. The reconstruction image quality was studied and compared to that obtained without the compensation filter in place. The uniformity of linear attenuation coefficient and the uniformity of noise distribution are significantly improved, and the contrast-to-noise ratios (CNR) of small lesions near the chest wall are increased as well. Multi-normal image method is used in the reconstruction process to correct compensation flood field and to reduce ring artifacts.

Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation.

PubMed

Keller, Brad M; Nathan, Diane L; Wang, Yan; Zheng, Yuanjie; Gee, James C; Conant, Emily F; Kontos, Despina

2012-08-01

The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., "FOR PROCESSING") and vendor postprocessed (i.e., "FOR PRESENTATION"), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r = 0.82, p < 0.001) and processed (r = 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r = 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's κ ≥ 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies.

Three-dimensional holographic display of ultrasound computed tomograms

NASA Astrophysics Data System (ADS)

Andre, Michael P.; Janee, Helmar S.; Ysrael, Mariana Z.; Hodler, Jeurg; Olson, Linda K.; Leopold, George R.; Schulz, Raymond

1997-05-01

Breast ultrasound is a valuable adjunct to mammography but is limited by a very small field of view, particularly with high-resolution transducers necessary for breast diagnosis. We have been developing an ultrasound system based on a diffraction tomography method that provides slices through the breast on a large 20-cm diameter circular field of view. Eight to fifteen images are typically produced in sequential coronal planes from the nipple to the chest wall with either 0.25 or 0.5 mm pixels. As a means to simplify the interpretation of this large set of images, we report experience with 3D life-sized displays of the entire breast of human volunteers using a digital holographic technique. The compound 3D holographic images are produced from the digital image matrix, recorded on 14 X 17 inch transparency and projected on a special white-light viewbox. Holographic visualization of the entire breast has proved to be the preferred method for 3D display of ultrasound computed tomography images. It provides a unique perspective on breast anatomy and may prove useful for biopsy guidance and surgical planning.

[Imaging of breast tissues changes--early detection, screening and problem solving].

PubMed

Wruk, Daniela

2008-04-01

In the industrialised countries breast cancer is the cancer with the highest prevalence and causes the highest rate of cancer deaths among women. In Switzerland alone, about 5000 newly diagnosed cases occur per year. Our three main diagnostic tools in imaging diseases of the breast in the setting of screening, early detection or problem solving are mammography, ultrasound and MRI with intravenous contrast application. The most important imaging technique is mammography, which as only method has shown evidence to be suitable for screening so far. As a major accomplishing imaging tool there is sonography, which in women under 30 years of age is the first method of choice in examination of the breasts. The MRI is able to provide additional information about the perfusion of tissue changes within the breast; because of its low specificity, however, it should cautiously be applied for specific questions.

The evolving role of new imaging methods in breast screening.

PubMed

Houssami, Nehmat; Ciatto, Stefano

2011-09-01

The potential to avert breast cancer deaths through screening means that efforts continue to identify methods which may enhance early detection. While the role of most new imaging technologies remains in adjunct screening or in the work-up of mammography-detected abnormalities, some of the new breast imaging tests (such as MRI) have roles in screening groups of women defined by increased cancer risk. This paper highlights the evidence and the current role of new breast imaging technologies in screening, focusing on those that have broader application in population screening, including digital mammography, breast ultrasound in women with dense breasts, and computer-aided detection. It highlights that evidence on new imaging in screening comes mostly from non-randomised studies that have quantified test detection capability as adjunct to mammography, or have compared measures of screening performance for new technologies with that of conventional mammography. Two RCTs have provided high-quality evidence on the equivalence of digital and conventional mammography and on outcomes of screen-reading complemented by CAD. Many of these imaging technologies enhance cancer detection but also increase recall and false positives in screening. Copyright © 2011 Elsevier Inc. All rights reserved.

Early Breast Cancer Detection by Ultrawide Band Imaging with Dispersion Consideration

NASA Astrophysics Data System (ADS)

Xiao, Xia; Kikkawa, Takamaro

2008-04-01

Ultrawide band (UWB) microwave imaging is a promising method for early-stage breast cancer detection based on the large contrast of electric parameters between the tumor and the normal breast tissue. The tumor can be detected by analyzing the reflection and scattering behavior of the UWB microwave propagating in the breast. In this study, the tumor location is determined by comparing the waveforms resulted from the tumor-containing and tumor-free breasts. The frequency dispersive characteristics of the fatty breast tissue, skin and tumor are considered in the study to approach the actual electrical properties of the breast. The correct location and size are visualized for an early-stage tumor embedded in the breast using the principle of a confocal microwave imaging technique.

Automated ultrasound scanning on a dual-modality breast imaging system: coverage and motion issues and solutions.

PubMed

Sinha, Sumedha P; Goodsitt, Mitchell M; Roubidoux, Marilyn A; Booi, Rebecca C; LeCarpentier, Gerald L; Lashbrook, Christine R; Thomenius, Kai E; Chalek, Carl L; Carson, Paul L

2007-05-01

We are developing an automated ultrasound imaging-mammography system wherein a digital mammography unit has been augmented with a motorized ultrasound transducer carriage above a special compression paddle. Challenges of this system are acquiring complete coverage of the breast and minimizing motion. We assessed these problems and investigated methods to increase coverage and stabilize the compressed breast. Visual tracings of the breast-to-paddle contact area and breast periphery were made for 10 patients to estimate coverage area. Various motion artifacts were evaluated in 6 patients. Nine materials were tested for coupling the paddle to the breast. Fourteen substances were tested for coupling the transducer to the paddle in lateral-to-medial and medial-to-lateral views and filling the gap between the peripheral breast and paddle. In-house image registration software was used to register adjacent ultrasound sweeps. The average breast contact area was 56%. The average percentage of the peripheral air gap filled with ultrasound gel was 61%. Shallow patient breathing proved equivalent to breath holding, whereas speech and sudden breathing caused unacceptable artifacts. An adhesive spray that preserves image quality was found to be best for coupling the breast to the paddle and minimizing motion. A highly viscous ultrasound gel proved most effective for coupling the transducer to the paddle for lateral-to-medial and medial-to-lateral views and for edge fill-in. The challenges of automated ultrasound scanning in a multimodality breast imaging system have been addressed by developing methods to fill in peripheral gaps, minimize patient motion, and register and reconstruct multisweep ultrasound image volumes.

Automated Segmentation of Nuclei in Breast Cancer Histopathology Images

PubMed Central

Paramanandam, Maqlin; O’Byrne, Michael; Ghosh, Bidisha; Mammen, Joy John; Manipadam, Marie Therese; Thamburaj, Robinson; Pakrashi, Vikram

2016-01-01

The process of Nuclei detection in high-grade breast cancer images is quite challenging in the case of image processing techniques due to certain heterogeneous characteristics of cancer nuclei such as enlarged and irregularly shaped nuclei, highly coarse chromatin marginalized to the nuclei periphery and visible nucleoli. Recent reviews state that existing techniques show appreciable segmentation accuracy on breast histopathology images whose nuclei are dispersed and regular in texture and shape; however, typical cancer nuclei are often clustered and have irregular texture and shape properties. This paper proposes a novel segmentation algorithm for detecting individual nuclei from Hematoxylin and Eosin (H&E) stained breast histopathology images. This detection framework estimates a nuclei saliency map using tensor voting followed by boundary extraction of the nuclei on the saliency map using a Loopy Back Propagation (LBP) algorithm on a Markov Random Field (MRF). The method was tested on both whole-slide images and frames of breast cancer histopathology images. Experimental results demonstrate high segmentation performance with efficient precision, recall and dice-coefficient rates, upon testing high-grade breast cancer images containing several thousand nuclei. In addition to the optimal performance on the highly complex images presented in this paper, this method also gave appreciable results in comparison with two recently published methods—Wienert et al. (2012) and Veta et al. (2013), which were tested using their own datasets. PMID:27649496

Breast tissue stiffness estimation for surgical guidance using gravity-induced excitation

NASA Astrophysics Data System (ADS)

Griesenauer, Rebekah H.; Weis, Jared A.; Arlinghaus, Lori R.; Meszoely, Ingrid M.; Miga, Michael I.

2017-06-01

Tissue stiffness interrogation is fundamental in breast cancer diagnosis and treatment. Furthermore, biomechanical models for predicting breast deformations have been created for several breast cancer applications. Within these applications, constitutive mechanical properties must be defined and the accuracy of this estimation directly impacts the overall performance of the model. In this study, we present an image-derived computational framework to obtain quantitative, patient specific stiffness properties for application in image-guided breast cancer surgery and interventions. The method uses two MR acquisitions of the breast in different supine gravity-loaded configurations to fit mechanical properties to a biomechanical breast model. A reproducibility assessment of the method was performed in a test-retest study using healthy volunteers and was further characterized in simulation. In five human data sets, the within subject coefficient of variation ranged from 10.7% to 27% and the intraclass correlation coefficient ranged from 0.91-0.944 for assessment of fibroglandular and adipose tissue stiffness. In simulation, fibroglandular content and deformation magnitude were shown to have significant effects on the shape and convexity of the objective function defined by image similarity. These observations provide an important step forward in characterizing the use of nonrigid image registration methodologies in conjunction with biomechanical models to estimate tissue stiffness. In addition, the results suggest that stiffness estimation methods using gravity-induced excitation can reliably and feasibly be implemented in breast cancer surgery/intervention workflows.

Breast tissue stiffness estimation for surgical guidance using gravity-induced excitation.

PubMed

Griesenauer, Rebekah H; Weis, Jared A; Arlinghaus, Lori R; Meszoely, Ingrid M; Miga, Michael I

2017-06-21

Tissue stiffness interrogation is fundamental in breast cancer diagnosis and treatment. Furthermore, biomechanical models for predicting breast deformations have been created for several breast cancer applications. Within these applications, constitutive mechanical properties must be defined and the accuracy of this estimation directly impacts the overall performance of the model. In this study, we present an image-derived computational framework to obtain quantitative, patient specific stiffness properties for application in image-guided breast cancer surgery and interventions. The method uses two MR acquisitions of the breast in different supine gravity-loaded configurations to fit mechanical properties to a biomechanical breast model. A reproducibility assessment of the method was performed in a test-retest study using healthy volunteers and was further characterized in simulation. In five human data sets, the within subject coefficient of variation ranged from 10.7% to 27% and the intraclass correlation coefficient ranged from 0.91-0.944 for assessment of fibroglandular and adipose tissue stiffness. In simulation, fibroglandular content and deformation magnitude were shown to have significant effects on the shape and convexity of the objective function defined by image similarity. These observations provide an important step forward in characterizing the use of nonrigid image registration methodologies in conjunction with biomechanical models to estimate tissue stiffness. In addition, the results suggest that stiffness estimation methods using gravity-induced excitation can reliably and feasibly be implemented in breast cancer surgery/intervention workflows.

Geometrical study on two tilting arcs based exact cone-beam CT for breast imaging

NASA Astrophysics Data System (ADS)

Zeng, Kai; Yu, Hengyong; Fajardo, Laurie L.; Wang, Ge

2006-08-01

Breast cancer is the second leading cause of cancer death in women in the United States. Currently, X-ray mammography is the method of choice for screening and diagnosing breast cancer. However, this 2D projective modality is far from perfect; with up to 17% breast cancer going unidentified. Over past several years, there has been an increasing interest in cone-beam CT for breast imaging. However, previous methods utilizing cone-beam CT only produce approximate reconstructions. Following Katsevich's recent work, we propose a new scanning mode and associated exact cone-beam CT method for breast imaging. In our design, cone-beam scans are performed along two tilting arcs for collection of a sufficient amount of data for exact reconstruction. In our Katsevich-type algorithm, conebeam data is filtered in a shift-invariant fashion and then backprojected in 3D for the final reconstruction. This approach has several desirable features. First, it allows data truncation unavoidable in practice. Second, it optimizes image quality for quantitative analysis. Third, it is efficient for sequential/parallel computation. Furthermore, we analyze the reconstruction region and the detection window in detail, which are important for numerical implementation.

Anatomical background noise power spectrum in differential phase contrast breast images

NASA Astrophysics Data System (ADS)

Garrett, John; Ge, Yongshuai; Li, Ke; Chen, Guang-Hong

2015-03-01

In x-ray breast imaging, the anatomical noise background of the breast has a significant impact on the detection of lesions and other features of interest. This anatomical noise is typically characterized by a parameter, β, which describes a power law dependence of anatomical noise on spatial frequency (the shape of the anatomical noise power spectrum). Large values of β have been shown to reduce human detection performance, and in conventional mammography typical values of β are around 3.2. Recently, x-ray differential phase contrast (DPC) and the associated dark field imaging methods have received considerable attention as possible supplements to absorption imaging for breast cancer diagnosis. However, the impact of these additional contrast mechanisms on lesion detection is not yet well understood. In order to better understand the utility of these new methods, we measured the β indices for absorption, DPC, and dark field images in 15 cadaver breast specimens using a benchtop DPC imaging system. We found that the measured β value for absorption was consistent with the literature for mammographic acquisitions (β = 3.61±0.49), but that both DPC and dark field images had much lower values of β (β = 2.54±0.75 for DPC and β = 1.44±0.49 for dark field). In addition, visual inspection showed greatly reduced anatomical background in both DPC and dark field images. These promising results suggest that DPC and dark field imaging may help provide improved lesion detection in breast imaging, particularly for those patients with dense breasts, in whom anatomical noise is a major limiting factor in identifying malignancies.

Comparison of time-series registration methods in breast dynamic infrared imaging

NASA Astrophysics Data System (ADS)

Riyahi-Alam, S.; Agostini, V.; Molinari, F.; Knaflitz, M.

2015-03-01

Automated motion reduction in dynamic infrared imaging is on demand in clinical applications, since movement disarranges time-temperature series of each pixel, thus originating thermal artifacts that might bias the clinical decision. All previously proposed registration methods are feature based algorithms requiring manual intervention. The aim of this work is to optimize the registration strategy specifically for Breast Dynamic Infrared Imaging and to make it user-independent. We implemented and evaluated 3 different 3D time-series registration methods: 1. Linear affine, 2. Non-linear Bspline, 3. Demons applied to 12 datasets of healthy breast thermal images. The results are evaluated through normalized mutual information with average values of 0.70 ±0.03, 0.74 ±0.03 and 0.81 ±0.09 (out of 1) for Affine, Bspline and Demons registration, respectively, as well as breast boundary overlap and Jacobian determinant of the deformation field. The statistical analysis of the results showed that symmetric diffeomorphic Demons' registration method outperforms also with the best breast alignment and non-negative Jacobian values which guarantee image similarity and anatomical consistency of the transformation, due to homologous forces enforcing the pixel geometric disparities to be shortened on all the frames. We propose Demons' registration as an effective technique for time-series dynamic infrared registration, to stabilize the local temperature oscillation.

Breast tissue classification in digital tomosynthesis images based on global gradient minimization and texture features

NASA Astrophysics Data System (ADS)

Qin, Xulei; Lu, Guolan; Sechopoulos, Ioannis; Fei, Baowei

2014-03-01

Digital breast tomosynthesis (DBT) is a pseudo-three-dimensional x-ray imaging modality proposed to decrease the effect of tissue superposition present in mammography, potentially resulting in an increase in clinical performance for the detection and diagnosis of breast cancer. Tissue classification in DBT images can be useful in risk assessment, computer-aided detection and radiation dosimetry, among other aspects. However, classifying breast tissue in DBT is a challenging problem because DBT images include complicated structures, image noise, and out-of-plane artifacts due to limited angular tomographic sampling. In this project, we propose an automatic method to classify fatty and glandular tissue in DBT images. First, the DBT images are pre-processed to enhance the tissue structures and to decrease image noise and artifacts. Second, a global smooth filter based on L0 gradient minimization is applied to eliminate detailed structures and enhance large-scale ones. Third, the similar structure regions are extracted and labeled by fuzzy C-means (FCM) classification. At the same time, the texture features are also calculated. Finally, each region is classified into different tissue types based on both intensity and texture features. The proposed method is validated using five patient DBT images using manual segmentation as the gold standard. The Dice scores and the confusion matrix are utilized to evaluate the classified results. The evaluation results demonstrated the feasibility of the proposed method for classifying breast glandular and fat tissue on DBT images.

Ultrasonic Imaging Techniques for Breast Cancer Detection

NASA Astrophysics Data System (ADS)

Goulding, N. R.; Marquez, J. D.; Prewett, E. M.; Claytor, T. N.; Nadler, B. R.

2008-02-01

Improving the resolution and specificity of current ultrasonic imaging technology is needed to enhance its relevance to breast cancer detection. A novel ultrasonic imaging reconstruction method is described that exploits classical straight-ray migration. This novel method improves signal processing for better image resolution and uses novel staging hardware options using a pulse-echo approach. A breast phantom with various inclusions is imaged using the classical migration method and is compared to standard computed tomography (CT) scans. These innovative ultrasonic methods incorporate ultrasound data acquisition, beam profile characterization, and image reconstruction. For an ultrasonic frequency of 2.25 MHz, imaged inclusions of approximately 1 cm are resolved and identified. Better resolution is expected with minor modifications. Improved image quality and resolution enables earlier detection and more accurate diagnoses of tumors thus reducing the number of biopsies performed, increasing treatment options, and lowering remission percentages. Using these new techniques the inclusions in the phantom are resolved and compared to the results of standard methods. Refinement of this application using other imaging techniques such as time-reversal mirrors (TRM), synthetic aperture focusing technique (SAFT), decomposition of the time reversal operator (DORT), and factorization methods is also discussed.

Design and validation of realistic breast models for use in multiple alternative forced choice virtual clinical trials

NASA Astrophysics Data System (ADS)

Elangovan, Premkumar; Mackenzie, Alistair; Dance, David R.; Young, Kenneth C.; Cooke, Victoria; Wilkinson, Louise; Given-Wilson, Rosalind M.; Wallis, Matthew G.; Wells, Kevin

2017-04-01

A novel method has been developed for generating quasi-realistic voxel phantoms which simulate the compressed breast in mammography and digital breast tomosynthesis (DBT). The models are suitable for use in virtual clinical trials requiring realistic anatomy which use the multiple alternative forced choice (AFC) paradigm and patches from the complete breast image. The breast models are produced by extracting features of breast tissue components from DBT clinical images including skin, adipose and fibro-glandular tissue, blood vessels and Cooper’s ligaments. A range of different breast models can then be generated by combining these components. Visual realism was validated using a receiver operating characteristic (ROC) study of patches from simulated images calculated using the breast models and from real patient images. Quantitative analysis was undertaken using fractal dimension and power spectrum analysis. The average areas under the ROC curves for 2D and DBT images were 0.51  ±  0.06 and 0.54  ±  0.09 demonstrating that simulated and real images were statistically indistinguishable by expert breast readers (7 observers); errors represented as one standard error of the mean. The average fractal dimensions (2D, DBT) for real and simulated images were (2.72  ±  0.01, 2.75  ±  0.01) and (2.77  ±  0.03, 2.82  ±  0.04) respectively; errors represented as one standard error of the mean. Excellent agreement was found between power spectrum curves of real and simulated images, with average β values (2D, DBT) of (3.10  ±  0.17, 3.21  ±  0.11) and (3.01  ±  0.32, 3.19  ±  0.07) respectively; errors represented as one standard error of the mean. These results demonstrate that radiological images of these breast models realistically represent the complexity of real breast structures and can be used to simulate patches from mammograms and DBT images that are indistinguishable from patches from the corresponding real breast images. The method can generate about 500 radiological patches (~30 mm  ×  30 mm) per day for AFC experiments on a single workstation. This is the first study to quantitatively validate the realism of simulated radiological breast images using direct blinded comparison with real data via the ROC paradigm with expert breast readers.

TU-CD-207-09: Analysis of the 3-D Shape of Patients’ Breast for Breast Imaging and Surgery Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agasthya, G; Sechopoulos, I

2015-06-15

Purpose: Develop a method to accurately capture the 3-D shape of patients’ external breast surface before and during breast compression for mammography/tomosynthesis. Methods: During this IRB-approved, HIPAA-compliant study, 50 women were recruited to undergo 3-D breast surface imaging during breast compression and imaging for the cranio-caudal (CC) view on a digital mammography/breast tomosynthesis system. Digital projectors and cameras mounted on tripods were used to acquire 3-D surface images of the breast, in three conditions: (a) positioned on the support paddle before compression, (b) during compression by the compression paddle and (c) the anterior-posterior view with the breast in its natural,more » unsupported position. The breast was compressed to standard full compression with the compression paddle and a tomosynthesis image was acquired simultaneously with the 3-D surface. The 3-D surface curvature and deformation with respect to the uncompressed surface was analyzed using contours. The 3-D surfaces were voxelized to capture breast shape in a format that can be manipulated for further analysis. Results: A protocol was developed to accurately capture the 3-D shape of patients’ breast before and during compression for mammography. Using a pair of 3-D scanners, the 50 patient breasts were scanned in three conditions, resulting in accurate representations of the breast surfaces. The surfaces were post processed, analyzed using contours and voxelized, with 1 mm{sup 3} voxels, converting the breast shape into a format that can be easily modified as required. Conclusion: Accurate characterization of the breast curvature and shape for the generation of 3-D models is possible. These models can be used for various applications such as improving breast dosimetry, accurate scatter estimation, conducting virtual clinical trials and validating compression algorithms. Ioannis Sechopoulos is consultant for Fuji Medical Systems USA.« less

Breast cancer histopathology image analysis: a review.

PubMed

Veta, Mitko; Pluim, Josien P W; van Diest, Paul J; Viergever, Max A

2014-05-01

This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.

Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging.

PubMed

Nissan, Noam; Furman-Haran, Edna; Feinberg-Shapiro, Myra; Grobgeld, Dov; Eyal, Erez; Zehavi, Tania; Degani, Hadassa

2014-12-15

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.

Are Breast Masses in Teenagers Always Benign? Undifferentiated Mesenchymal Sarcoma in a 14-Year-Old Girl

PubMed Central

Tekbas, Guven; Ince, Tülay; Kapan, Murat; Ekici, Faysal; Önder, Akin; Kucukonen, Mehmet; Bilici, Aslan; Gumus, Hatice

2012-01-01

Background This article is concerned with the evaluation of an adolescent breast mass using imaging methods. Case Report A 14-year-old girl presented with progressive asymmetric enlargement of the left breast. She had felt a breast lump about 4 months earlier, and over the last 2 months it had been growing progressively. Tumor markers, including AFP, CEA, CA15-3, and CA125, were all normal. Ultrasonography showed a hypoechoichyperechoic, solid mass. Magnetic resonance imaging of the breast revealed a well marginated mass with hypointensity on T1-weighted images and mild hyperintensity on T2-weighted images, which showed mild contrast uptake. Biopsy revealed an undifferentiated malignant mesenchymal sarcoma. The patient underwent mastectomy with axillary lymph node sampling. After the operation, she received 3 cycles of chemotherapy and radiotherapy. Conclusion Due to the rarity of breast sarcoma and inadequate imaging methods to establish an exact diagnosis, radiologists and clinicians may misdiagnose and merely follow these tumors. As in our case, the histology of the patient may be the leading factor in the management of these tumors. Even in very young patients, progressively growing breast masses should alert the clinician to check for malignancy verified by biopsy. PMID:22740802

Microwave Sensors for Breast Cancer Detection

PubMed Central

2018-01-01

Breast cancer is the leading cause of death among females, early diagnostic methods with suitable treatments improve the 5-year survival rates significantly. Microwave breast imaging has been reported as the most potential to become the alternative or additional tool to the current gold standard X-ray mammography for detecting breast cancer. The microwave breast image quality is affected by the microwave sensor, sensor array, the number of sensors in the array and the size of the sensor. In fact, microwave sensor array and sensor play an important role in the microwave breast imaging system. Numerous microwave biosensors have been developed for biomedical applications, with particular focus on breast tumor detection. Compared to the conventional medical imaging and biosensor techniques, these microwave sensors not only enable better cancer detection and improve the image resolution, but also provide attractive features such as label-free detection. This paper aims to provide an overview of recent important achievements in microwave sensors for biomedical imaging applications, with particular focus on breast cancer detection. The electric properties of biological tissues at microwave spectrum, microwave imaging approaches, microwave biosensors, current challenges and future works are also discussed in the manuscript. PMID:29473867

Microwave Sensors for Breast Cancer Detection.

PubMed

Wang, Lulu

2018-02-23

Breast cancer is the leading cause of death among females, early diagnostic methods with suitable treatments improve the 5-year survival rates significantly. Microwave breast imaging has been reported as the most potential to become the alternative or additional tool to the current gold standard X-ray mammography for detecting breast cancer. The microwave breast image quality is affected by the microwave sensor, sensor array, the number of sensors in the array and the size of the sensor. In fact, microwave sensor array and sensor play an important role in the microwave breast imaging system. Numerous microwave biosensors have been developed for biomedical applications, with particular focus on breast tumor detection. Compared to the conventional medical imaging and biosensor techniques, these microwave sensors not only enable better cancer detection and improve the image resolution, but also provide attractive features such as label-free detection. This paper aims to provide an overview of recent important achievements in microwave sensors for biomedical imaging applications, with particular focus on breast cancer detection. The electric properties of biological tissues at microwave spectrum, microwave imaging approaches, microwave biosensors, current challenges and future works are also discussed in the manuscript.

Computer-aided, multi-modal, and compression diffuse optical studies of breast tissue

NASA Astrophysics Data System (ADS)

Busch, David Richard, Jr.

Diffuse Optical Tomography and Spectroscopy permit measurement of important physiological parameters non-invasively through ˜10 cm of tissue. I have applied these techniques in measurements of human breast and breast cancer. My thesis integrates three loosely connected themes in this context: multi-modal breast cancer imaging, automated data analysis of breast cancer images, and microvascular hemodynamics of breast under compression. As per the first theme, I describe construction, testing, and the initial clinical usage of two generations of imaging systems for simultaneous diffuse optical and magnetic resonance imaging. The second project develops a statistical analysis of optical breast data from many spatial locations in a population of cancers to derive a novel optical signature of malignancy; I then apply this data-derived signature for localization of cancer in additional subjects. Finally, I construct and deploy diffuse optical instrumentation to measure blood content and blood flow during breast compression; besides optics, this research has implications for any method employing breast compression, e.g., mammography.

A stepwedge-based method for measuring breast density: observer variability and comparison with human reading

NASA Astrophysics Data System (ADS)

Diffey, Jenny; Berks, Michael; Hufton, Alan; Chung, Camilla; Verow, Rosanne; Morrison, Joanna; Wilson, Mary; Boggis, Caroline; Morris, Julie; Maxwell, Anthony; Astley, Susan

2010-04-01

Breast density is positively linked to the risk of developing breast cancer. We have developed a semi-automated, stepwedge-based method that has been applied to the mammograms of 1,289 women in the UK breast screening programme to measure breast density by volume and area. 116 images were analysed by three independent operators to assess inter-observer variability; 24 of these were analysed on 10 separate occasions by the same operator to determine intra-observer variability. 168 separate images were analysed using the stepwedge method and by two radiologists who independently estimated percentage breast density by area. There was little intra-observer variability in the stepwedge method (average coefficients of variation 3.49% - 5.73%). There were significant differences in the volumes of glandular tissue obtained by the three operators. This was attributed to variations in the operators' definition of the breast edge. For fatty and dense breasts, there was good correlation between breast density assessed by the stepwedge method and the radiologists. This was also observed between radiologists, despite significant inter-observer variation. Based on analysis of thresholds used in the stepwedge method, radiologists' definition of a dense pixel is one in which the percentage of glandular tissue is between 10 and 20% of the total thickness of tissue.

SU-E-I-53: Variation in Measurements of Breast Skin Thickness Obtained Using Different Imaging Modalities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, U; Kumaraswamy, N; Markey, M

Purpose: To investigate variation in measurements of breast skin thickness obtained using different imaging modalities, including mammography, computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI). Methods: Breast skin thicknesses as measured by mammography, CT, ultrasound, and MRI were compared. Mammographic measurements of skin thickness were obtained from published studies that utilized standard positioning (upright) and compression. CT measurements of skin thickness were obtained from a published study of a prototype breast CT scanner in which the women were in the prone position and the breast was uncompressed. Dermatological ultrasound exams of the breast skin were conducted at our institution,more » with the subjects in the upright position and the breast uncompressed. Breast skin thickness was calculated from breast MRI exams at our institution, with the patient in the prone position and the breast uncompressed. Results: T tests for independent samples demonstrated significant differences in the mean breast skin thickness as measured by different imaging modalities. Repeated measures ANOVA revealed significant differences in breast skin thickness across different quadrants of the breast for some modalities. Conclusion: The measurement of breast skin thickness is significantly different across different imaging modalities. Differences in the amount of compression and differences in patient positioning are possible reasons why measurements of breast skin thickness vary by modality.« less

Feasibility of spatial frequency-domain imaging for monitoring palpable breast lesions

NASA Astrophysics Data System (ADS)

Robbins, Constance M.; Raghavan, Guruprasad; Antaki, James F.; Kainerstorfer, Jana M.

2017-12-01

In breast cancer diagnosis and therapy monitoring, there is a need for frequent, noninvasive disease progression evaluation. Breast tumors differ from healthy tissue in mechanical stiffness as well as optical properties, which allows optical methods to detect and monitor breast lesions noninvasively. Spatial frequency-domain imaging (SFDI) is a reflectance-based diffuse optical method that can yield two-dimensional images of absolute optical properties of tissue with an inexpensive and portable system, although depth penetration is limited. Since the absorption coefficient of breast tissue is relatively low and the tissue is quite flexible, there is an opportunity for compression of tissue to bring stiff, palpable breast lesions within the detection range of SFDI. Sixteen breast tissue-mimicking phantoms were fabricated containing stiffer, more highly absorbing tumor-mimicking inclusions of varying absorption contrast and depth. These phantoms were imaged with an SFDI system at five levels of compression. An increase in absorption contrast was observed with compression, and reliable detection of each inclusion was achieved when compression was sufficient to bring the inclusion center within ˜12 mm of the phantom surface. At highest compression level, contrasts achieved with this system were comparable to those measured with single source-detector near-infrared spectroscopy.

Filtering of high noise breast thermal images using fast non-local means.

PubMed

Suganthi, S S; Ramakrishnan, S

2014-01-01

Analyses of breast thermograms are still a challenging task primarily due to the limitations such as low contrast, low signal to noise ratio and absence of clear edges. Therefore, always there is a requirement for preprocessing techniques before performing any quantitative analysis. In this work, a noise removal framework using fast non-local means algorithm, method noise and median filter was used to denoise breast thermograms. The images considered were subjected to Anscombe transformation to convert the distribution from Poisson to Gaussian. The pre-denoised image was obtained by subjecting the transformed image to fast non-local means filtering. The method noise which is the difference between the original and pre-denoised image was observed with the noise component merged in few structures and fine detail of the image. The image details presented in the method noise was extracted by smoothing the noise part using the median filter. The retrieved image part was added to the pre-denoised image to obtain the final denoised image. The performance of this technique was compared with that of Wiener and SUSAN filters. The results show that all the filters considered are able to remove the noise component. The performance of the proposed denoising framework is found to be good in preserving detail and removing noise. Further, the method noise is observed with negligible image details. Similarly, denoised image with no noise and smoothed edges are observed using Wiener filter and its method noise is contained with few structures and image details. The performance results of SUSAN filter is found to be blurred denoised image with little noise and also method noise with extensive structure and image details. Hence, it appears that the proposed denoising framework is able to preserve the edge information and generate clear image that could help in enhancing the diagnostic relevance of breast thermograms. In this paper, the introduction, objectives, materials and methods, results and discussion and conclusions are presented in detail.

Methods for Evaluating Mammography Imaging Techniques

DTIC Science & Technology

1999-06-01

Distribution Unlimited 12b. DIS5TRIBUTION CODE 13. ABSTRACT (Maximum 200 words) This Department of Defense Breast Cancer Research Program Career...Development Award is enabling Dr. Rütter to develop bio’statistical methods for breast cancer research. Dr. Rutter is focusing on methods for...evaluating the accuracy of breast cancer screening. This four year program includes advanced training in the epidemiology of breast cancer , training in

Effects of cognitive behavioral counseling on body Image following mastectomy*

PubMed Central

Fadaei, Simin; Janighorban, Mojgan; Mehrabi, Tayebe; Ahmadi, Sayed Ahmadi; Mokaryan, Fariborz; Gukizade, Abbas

2011-01-01

BACKGROUND: Breast cancer is the most common cancer in women. Surgical treatment of breast cancer may cause body image alterations. The purpose of the current study was to examine the effects of cognitive behavioral counseling on body image among Iranian women with primary breast cancer. METHODS: In this quasi-experimental designed study, 72 patients diagnosed as breast cancer and surgically treated were enrolled in Isfahan, Iran. The patients were entered the study by convenience sampling method and were randomly divided in two groups of intervention (n = 32) and control (n = 40). The intervention group received consultation based on Ellis rational emotive behavior therapy (REBT) method for 6 sessions during 3 weeks. The control group did not receive any consultation Paired t-test was used to compare the changes in groups and independent t-test was conducted to compare two groups. The average values represented as mean ± standard deviation. RESULTS: Before the study, the body image score was not significantly different between the intervention (16 97 ± 5 44) and control (15 95 ± 4 66) groups (t = 0 86, P = 0 395). The body image score was significantly lower in the interven-tion group (9 03 ± 6 11) compared to control group (17 18 ± 5 27) after the intervention (t = -6 07, P < 0 001). CONCLUSIONS: Since a woman's body image influences her breast cancer treatment decision, oncology professionals need to recognize the value of a woman's favorite about appearance and body image. This study emphasizes the importance of offering consultation in breast cancer patients. PMID:22279481

Breast tissue stiffness estimation for surgical guidance using gravity-induced excitation

PubMed Central

Griesenauer, Rebekah H; Weis, Jared A; Arlinghaus, Lori R; Meszoely, Ingrid M; Miga, Michael I

2017-01-01

Tissue stiffness interrogation is fundamental in breast cancer diagnosis and treatment. Furthermore, biomechanical models for predicting breast deformations have been created for several breast cancer applications. Within these applications, constitutive mechanical properties must be defined and the accuracy of this estimation directly impacts the overall performance of the model. In this study, we present an image-derived computational framework to obtain quantitative, patient specific stiffness properties for application in image-guided breast cancer surgery and interventions. The method uses two MR acquisitions of the breast in different supine gravity-loaded configurations to fit mechanical properties to a biomechanical breast model. A reproducibility assessment of the method was performed in a test–retest study using healthy volunteers and was further characterized in simulation. In five human data sets, the within subject coefficient of variation ranged from 10.7% to 27% and the intraclass correlation coefficient ranged from 0.91–0.944 for assessment of fibroglandular and adipose tissue stiffness. In simulation, fibroglandular content and deformation magnitude were shown to have significant effects on the shape and convexity of the objective function defined by image similarity. These observations provide an important step forward in characterizing the use of nonrigid image registration methodologies in conjunction with biomechanical models to estimate tissue stiffness. In addition, the results suggest that stiffness estimation methods using gravity-induced excitation can reliably and feasibly be implemented in breast cancer surgery/intervention workflows. PMID:28520556

Using x-ray mammograms to assist in microwave breast image interpretation.

PubMed

Curtis, Charlotte; Frayne, Richard; Fear, Elise

2012-01-01

Current clinical breast imaging modalities include ultrasound, magnetic resonance (MR) imaging, and the ubiquitous X-ray mammography. Microwave imaging, which takes advantage of differing electromagnetic properties to obtain image contrast, shows potential as a complementary imaging technique. As an emerging modality, interpretation of 3D microwave images poses a significant challenge. MR images are often used to assist in this task, and X-ray mammograms are readily available. However, X-ray mammograms provide 2D images of a breast under compression, resulting in significant geometric distortion. This paper presents a method to estimate the 3D shape of the breast and locations of regions of interest from standard clinical mammograms. The technique was developed using MR images as the reference 3D shape with the future intention of using microwave images. Twelve breast shapes were estimated and compared to ground truth MR images, resulting in a skin surface estimation accurate to within an average Euclidean distance of 10 mm. The 3D locations of regions of interest were estimated to be within the same clinical area of the breast as corresponding regions seen on MR imaging. These results encourage investigation into the use of mammography as a source of information to assist with microwave image interpretation as well as validation of microwave imaging techniques.

Generation of anatomically realistic numerical phantoms for photoacoustic and ultrasonic breast imaging

NASA Astrophysics Data System (ADS)

Lou, Yang; Zhou, Weimin; Matthews, Thomas P.; Appleton, Catherine M.; Anastasio, Mark A.

2017-04-01

Photoacoustic computed tomography (PACT) and ultrasound computed tomography (USCT) are emerging modalities for breast imaging. As in all emerging imaging technologies, computer-simulation studies play a critically important role in developing and optimizing the designs of hardware and image reconstruction methods for PACT and USCT. Using computer-simulations, the parameters of an imaging system can be systematically and comprehensively explored in a way that is generally not possible through experimentation. When conducting such studies, numerical phantoms are employed to represent the physical properties of the patient or object to-be-imaged that influence the measured image data. It is highly desirable to utilize numerical phantoms that are realistic, especially when task-based measures of image quality are to be utilized to guide system design. However, most reported computer-simulation studies of PACT and USCT breast imaging employ simple numerical phantoms that oversimplify the complex anatomical structures in the human female breast. We develop and implement a methodology for generating anatomically realistic numerical breast phantoms from clinical contrast-enhanced magnetic resonance imaging data. The phantoms will depict vascular structures and the volumetric distribution of different tissue types in the breast. By assigning optical and acoustic parameters to different tissue structures, both optical and acoustic breast phantoms will be established for use in PACT and USCT studies.

Method and device for intraoperative imaging of lumpectomy specimens to provide feedback to breast surgeon for prompt re-excision during the same procedure

NASA Astrophysics Data System (ADS)

Krol, Andrzej; Hemingway, Susan; Kort, Kara; de la Rosa, Gustavo; Adhikary, Ravi; Masrani, Deepa; Feiglin, David; O'Connell, Avice; Nagarajan, Mahesh; Yang, Chien-Chun; Wismüller, Axel

2014-03-01

Breast conserving therapy (BCT) of breast cancer is now widely accepted due to improved cosmetic outcome and improved patients' quality of life. One of the critical issues in performing breast-conserving surgery is trying to achieve microscopically clear surgical margins while maintaining excellent cosmesis. Unfortunately, unacceptably close or positive surgical margins occur in at least 20-25% of all patients undergoing BCT requiring repeat surgical excision days or weeks later, as permanent histopathology routinely takes days to complete. Our aim is to develop a better method for intraoperative imaging of non-palpable breast malignancies excised by wire or needle localization. Providing non-deformed three dimensional imaging of the excised breast tissue should allow more accurate assessment of tumor margins and consequently allow further excision at the time of initial surgery thus limiting the enormous financial and emotional burden of additional surgery. We have designed and constructed a device that allows preservation of the excised breast tissue in its natural anatomic position relative to the breast as it is imaged to assess adequate excision. We performed initial tests with needle-guided lumpectomy specimens using micro-CT and digital breast tomosynthesis (DBT). Our device consists of a plastic sphere inside a cylindrical holder. The surgeon inserts a freshly excised piece of breast tissue into the sphere and matches its anatomic orientation with the fiducial markers on the sphere. A custom-shaped foam is placed inside the sphere to prevent specimen deformation due to gravity. DBT followed by micro-CT images of the specimen were obtained. We confirmed that our device preserved spatial orientation of the excised breast tissue and that the location error was lower than 10mm and 10 degrees. The initial obtained results indicate that breast lesions containing microcalcifications allow a good 3D imaging of margins providing immediate intraoperative feedback for further excision as needed at the initial operation.

Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images.

PubMed

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-07-21

This study presents a finite element-based computational model to simulate the three-dimensional deformation of a breast and fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and craniocaudal and mediolateral oblique compression, as used in mammography, was applied. The geometry of the whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the nonlinear elastic tissue deformation under compression, using the MSC.Marc software package. The model was tested in four cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these four cases at a compression ratio of 60% was in the range of 5-7 cm, which is a typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at a compression ratio of 60% was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on magnetic resonance imaging (MRI), which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities--such as MRI, mammography, whole breast ultrasound and molecular imaging--that are performed using different body positions and under different compression conditions.

Optical Imaging in Breast Cancer Diagnosis: The Next Evolution

PubMed Central

Ruibal, Alvaro

2012-01-01

Breast cancer is one of the most common cancers among the population of the Western world. Diagnostic methods include mammography, ultrasound, and magnetic resonance; meanwhile, nuclear medicine techniques have a secondary role, being useful in regional assessment and therapy followup. Optical imaging is a very promising imaging technique that uses near-infrared light to assess optical properties of tissues and is expected to play an important role in breast cancer detection. Optical breast imaging can be performed by intrinsic breast tissue contrast alone (hemoglobin, water, and lipid content) or with the use of exogenous fluorescent probes that target specific molecules for breast cancer. Major advantages of optical imaging are that it does not use any radioactive components, very high sensitivity, relatively inexpensive, easily accessible, and the potential to be combined in a multimodal approach with other technologies such as mammography, ultrasound, MRI, and positron emission tomography. Moreover, optical imaging agents could, potentially, be used as “theranostics,” combining the process of diagnosis and therapy. PMID:23304141

Multimodal breast cancer imaging using coregistered dynamic diffuse optical tomography and digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Zimmermann, Bernhard B.; Deng, Bin; Singh, Bhawana; Martino, Mark; Selb, Juliette; Fang, Qianqian; Sajjadi, Amir Y.; Cormier, Jayne; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.; Saksena, Mansi A.; Carp, Stefan A.

2017-04-01

Diffuse optical tomography (DOT) is emerging as a noninvasive functional imaging method for breast cancer diagnosis and neoadjuvant chemotherapy monitoring. In particular, the multimodal approach of combining DOT with x-ray digital breast tomosynthesis (DBT) is especially synergistic as DBT prior information can be used to enhance the DOT reconstruction. DOT, in turn, provides a functional information overlay onto the mammographic images, increasing sensitivity and specificity to cancer pathology. We describe a dynamic DOT apparatus designed for tight integration with commercial DBT scanners and providing a fast (up to 1 Hz) image acquisition rate to enable tracking hemodynamic changes induced by the mammographic breast compression. The system integrates 96 continuous-wave and 24 frequency-domain source locations as well as 32 continuous wave and 20 frequency-domain detection locations into low-profile plastic plates that can easily mate to the DBT compression paddle and x-ray detector cover, respectively. We demonstrate system performance using static and dynamic tissue-like phantoms as well as in vivo images acquired from the pool of patients recalled for breast biopsies at the Massachusetts General Hospital Breast Imaging Division.

Evaluation of a novel collimator for molecular breast tomosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilland, David R.; Welch, Benjamin L.; Lee, Seungjoon

Here, this study investigated a novel gamma camera for molecular breast tomosynthesis (MBT), which is a nuclear breast imaging method that uses limited angle tomography. The camera is equipped with a variable angle, slant-hole (VASH) collimator that allows the camera to remain close to the breast throughout the acquisition. The goal of this study was to evaluate the spatial resolution and count sensitivity of this camera and to compare contrast and contrast-to-noise ratio (CNR) with conventional planar imaging using an experimental breast phantom. Methods The VASH collimator mounts to a commercial gamma camera for breast imaging that uses a pixelatedmore » (3.2 mm), 15 × 20 cm NaI crystal. Spatial resolution was measured in planar images over a range of distances from the collimator (30-100 mm) and a range of slant angles (–25° to 25°) using 99mTc line sources. Spatial resolution was also measured in reconstructed MBT images including in the depth dimension. The images were reconstructed from data acquired over the -25° to 25° angular range using an iterative algorithm adapted to the slant-hole geometry. Sensitivity was measured over the range of slant angles using a disk source. Measured spatial resolution and sensitivity were compared to theoretical values. Contrast and CNR were measured using a breast phantom containing spherical lesions (6.2 mm and 7.8 mm diameter) and positioned over a range of depths in the phantom. The MBT and planar methods had equal scan time, and the count density in the breast phantom data was similar to that in clinical nuclear breast imaging. The MBT method used an iterative reconstruction algorithm combined with a postreconstruction Metz filter. Results The measured spatial resolution in planar images agreed well with theoretical calculations over the range of distances and slant angles. The measured FWHM was 9.7 mm at 50 mm distance. In reconstructed MBT images, the spatial resolution in the depth dimension was approximately 2.2 mm greater than the other two dimensions due to the limited angle data. The measured count sensitivity agreed closely with theory over all slant angles when using a wide energy window. At 0° slant angle, measured sensitivity was 19.7 counts sec -1 μCi -1 with the open energy window and 11.2 counts sec -1 μCi -1 with a 20% wide photopeak window (126 to 154 keV). The measured CNR in the MBT images was significantly greater than in the planar images for all but the lowest CNR cases where the lesion detectability was extremely low for both MBT and planar. The 7.8 mm lesion at 37 mm depth was marginally detectable in the planar image but easily visible in the MBT image. The improved CNR with MBT was due to a large improvement in contrast, which out-weighed the increase in image noise. Conclusion The spatial resolution and count sensitivity measurements with the prototype MBT system matched theoretical calculations, and the measured CNR in breast phantom images was generally greater with the MBT system compared to conventional planar imaging. These results demonstrate the potential of the proposed MBT system to improve lesion detection in nuclear breast imaging.« less

Evaluation of a novel collimator for molecular breast tomosynthesis

DOE PAGES

Gilland, David R.; Welch, Benjamin L.; Lee, Seungjoon; ...

2017-09-06

Here, this study investigated a novel gamma camera for molecular breast tomosynthesis (MBT), which is a nuclear breast imaging method that uses limited angle tomography. The camera is equipped with a variable angle, slant-hole (VASH) collimator that allows the camera to remain close to the breast throughout the acquisition. The goal of this study was to evaluate the spatial resolution and count sensitivity of this camera and to compare contrast and contrast-to-noise ratio (CNR) with conventional planar imaging using an experimental breast phantom. Methods The VASH collimator mounts to a commercial gamma camera for breast imaging that uses a pixelatedmore » (3.2 mm), 15 × 20 cm NaI crystal. Spatial resolution was measured in planar images over a range of distances from the collimator (30-100 mm) and a range of slant angles (–25° to 25°) using 99mTc line sources. Spatial resolution was also measured in reconstructed MBT images including in the depth dimension. The images were reconstructed from data acquired over the -25° to 25° angular range using an iterative algorithm adapted to the slant-hole geometry. Sensitivity was measured over the range of slant angles using a disk source. Measured spatial resolution and sensitivity were compared to theoretical values. Contrast and CNR were measured using a breast phantom containing spherical lesions (6.2 mm and 7.8 mm diameter) and positioned over a range of depths in the phantom. The MBT and planar methods had equal scan time, and the count density in the breast phantom data was similar to that in clinical nuclear breast imaging. The MBT method used an iterative reconstruction algorithm combined with a postreconstruction Metz filter. Results The measured spatial resolution in planar images agreed well with theoretical calculations over the range of distances and slant angles. The measured FWHM was 9.7 mm at 50 mm distance. In reconstructed MBT images, the spatial resolution in the depth dimension was approximately 2.2 mm greater than the other two dimensions due to the limited angle data. The measured count sensitivity agreed closely with theory over all slant angles when using a wide energy window. At 0° slant angle, measured sensitivity was 19.7 counts sec -1 μCi -1 with the open energy window and 11.2 counts sec -1 μCi -1 with a 20% wide photopeak window (126 to 154 keV). The measured CNR in the MBT images was significantly greater than in the planar images for all but the lowest CNR cases where the lesion detectability was extremely low for both MBT and planar. The 7.8 mm lesion at 37 mm depth was marginally detectable in the planar image but easily visible in the MBT image. The improved CNR with MBT was due to a large improvement in contrast, which out-weighed the increase in image noise. Conclusion The spatial resolution and count sensitivity measurements with the prototype MBT system matched theoretical calculations, and the measured CNR in breast phantom images was generally greater with the MBT system compared to conventional planar imaging. These results demonstrate the potential of the proposed MBT system to improve lesion detection in nuclear breast imaging.« less

Recent Advances in Microwave Imaging for Breast Cancer Detection

PubMed Central

Kwon, Sollip

2016-01-01

Breast cancer is a disease that occurs most often in female cancer patients. Early detection can significantly reduce the mortality rate. Microwave breast imaging, which is noninvasive and harmless to human, offers a promising alternative method to mammography. This paper presents a review of recent advances in microwave imaging for breast cancer detection. We conclude by introducing new research on a microwave imaging system with time-domain measurement that achieves short measurement time and low system cost. In the time-domain measurement system, scan time would take less than 1 sec, and it does not require very expensive equipment such as VNA. PMID:28096808

Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging

PubMed Central

Pertuz, Said; McDonald, Elizabeth S.; Weinstein, Susan P.; Conant, Emily F.

2016-01-01

Purpose To assess a fully automated method for volumetric breast density (VBD) estimation in digital breast tomosynthesis (DBT) and to compare the findings with those of full-field digital mammography (FFDM) and magnetic resonance (MR) imaging. Materials and Methods Bilateral DBT images, FFDM images, and sagittal breast MR images were retrospectively collected from 68 women who underwent breast cancer screening from October 2011 to September 2012 with institutional review board–approved, HIPAA-compliant protocols. A fully automated computer algorithm was developed for quantitative estimation of VBD from DBT images. FFDM images were processed with U.S. Food and Drug Administration–cleared software, and the MR images were processed with a previously validated automated algorithm to obtain corresponding VBD estimates. Pearson correlation and analysis of variance with Tukey-Kramer post hoc correction were used to compare the multimodality VBD estimates. Results Estimates of VBD from DBT were significantly correlated with FFDM-based and MR imaging–based estimates with r = 0.83 (95% confidence interval [CI]: 0.74, 0.90) and r = 0.88 (95% CI: 0.82, 0.93), respectively (P < .001). The corresponding correlation between FFDM and MR imaging was r = 0.84 (95% CI: 0.76, 0.90). However, statistically significant differences after post hoc correction (α = 0.05) were found among VBD estimates from FFDM (mean ± standard deviation, 11.1% ± 7.0) relative to MR imaging (16.6% ± 11.2) and DBT (19.8% ± 16.2). Differences between VDB estimates from DBT and MR imaging were not significant (P = .26). Conclusion Fully automated VBD estimates from DBT, FFDM, and MR imaging are strongly correlated but show statistically significant differences. Therefore, absolute differences in VBD between FFDM, DBT, and MR imaging should be considered in breast cancer risk assessment. © RSNA, 2015 Online supplemental material is available for this article. PMID:26491909

Development of a fully automatic scheme for detection of masses in whole breast ultrasound images.

PubMed

Ikedo, Yuji; Fukuoka, Daisuke; Hara, Takeshi; Fujita, Hiroshi; Takada, Etsuo; Endo, Tokiko; Morita, Takako

2007-11-01

Ultrasonography has been used for breast cancer screening in Japan. Screening using a conventional hand-held probe is operator dependent and thus it is possible that some areas of the breast may not be scanned. To overcome such problems, a mechanical whole breast ultrasound (US) scanner has been proposed and developed for screening purposes. However, another issue is that radiologists might tire while interpreting all images in a large-volume screening; this increases the likelihood that masses may remain undetected. Therefore, the aim of this study is to develop a fully automatic scheme for the detection of masses in whole breast US images in order to assist the interpretations of radiologists and potentially improve the screening accuracy. The authors database comprised 109 whole breast US imagoes, which include 36 masses (16 malignant masses, 5 fibroadenomas, and 15 cysts). A whole breast US image with 84 slice images (interval between two slice images: 2 mm) was obtained by the ASU-1004 US scanner (ALOKA Co., Ltd., Japan). The feature based on the edge directions in each slice and a method for subtracting between the slice images were used for the detection of masses in the authors proposed scheme. The Canny edge detector was applied to detect edges in US images; these edges were classified as near-vertical edges or near-horizontal edges using a morphological method. The positions of mass candidates were located using the near-vertical edges as a cue. Then, the located positions were segmented by the watershed algorithm and mass candidate regions were detected using the segmented regions and the low-density regions extracted by the slice subtraction method. For the removal of false positives (FPs), rule-based schemes and a quadratic discriminant analysis were applied for the distribution between masses and FPs. As a result, the sensitivity of the authors scheme for the detection of masses was 80.6% (29/36) with 3.8 FPs per whole breast image. The authors scheme for a computer-aided detection may be useful in improving the screening performance and efficiency.

Computer-aided classification of breast masses using contrast-enhanced digital mammograms

NASA Astrophysics Data System (ADS)

Danala, Gopichandh; Aghaei, Faranak; Heidari, Morteza; Wu, Teresa; Patel, Bhavika; Zheng, Bin

2018-02-01

By taking advantages of both mammography and breast MRI, contrast-enhanced digital mammography (CEDM) has emerged as a new promising imaging modality to improve efficacy of breast cancer screening and diagnosis. The primary objective of study is to develop and evaluate a new computer-aided detection and diagnosis (CAD) scheme of CEDM images to classify between malignant and benign breast masses. A CEDM dataset consisting of 111 patients (33 benign and 78 malignant) was retrospectively assembled. Each case includes two types of images namely, low-energy (LE) and dual-energy subtracted (DES) images. First, CAD scheme applied a hybrid segmentation method to automatically segment masses depicting on LE and DES images separately. Optimal segmentation results from DES images were also mapped to LE images and vice versa. Next, a set of 109 quantitative image features related to mass shape and density heterogeneity was initially computed. Last, four multilayer perceptron-based machine learning classifiers integrated with correlationbased feature subset evaluator and leave-one-case-out cross-validation method was built to classify mass regions depicting on LE and DES images, respectively. Initially, when CAD scheme was applied to original segmentation of DES and LE images, the areas under ROC curves were 0.7585+/-0.0526 and 0.7534+/-0.0470, respectively. After optimal segmentation mapping from DES to LE images, AUC value of CAD scheme significantly increased to 0.8477+/-0.0376 (p<0.01). Since DES images eliminate overlapping effect of dense breast tissue on lesions, segmentation accuracy was significantly improved as compared to regular mammograms, the study demonstrated that computer-aided classification of breast masses using CEDM images yielded higher performance.

TH-AB-209-08: Next Generation Dedicated 3D Breast Imaging with XACT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, S; Chen, J; Samant, P

Purpose: Exposure to radiation increases the risk of cancer. We have designed a new imaging paradigm, X-ray induced acoustic computed tomography (XACT). Applying this innovative technology to breast imaging, an X-ray exposure can generate a 3D acoustic image, which dramatically reduces the radiation dose to patients when compared to conventional breast CT. Methods: Theoretical calculations are done to determine the appropriate X-ray energy and ultrasound frequency in breast XACT imaging. A series of breast CT image along the coronal plane from a patient with calcifications in the breast tissue are used as the source image. HU value based segmentation ismore » done to distinguish the skin, adipose tissue, glandular tissue, breast calcification, and chest bone from each CT image. X-ray dose deposition in each pixel is calculated based on the tissue type by using GEANT4 Monte Carlo toolkits. The initial pressure rise caused by X-ray energy deposition is calculated according to tissue properties. Then, the X-ray induced acoustic wave propagation is simulated by K-WAVE toolkit. Breast XACT images are reconstructed from the recorded time-dependent ultrasound waves. Results: For imaging a breast with large size (16cm in diameter at chest wall), the photon energy of X-ray source and the central frequency of ultrasound detector is determined as 20keV and 5.5MHz. Approximately 10 times contrast between a calcification and the breast tissue can be acquire from XACT image. The calcification can be clearly identified from the reconstructed XACT image. Conclusion: XACT technique takes the advantages of X-ray absorption contrast and high ultrasonic resolution. With the proposed innovative technology, one can potentially reduce radiation dose to patient in 3D breast imaging as compared with current x-ray modalities, while still maintaining high imaging contrast and spatial resolution.« less

The evaluation of correction algorithms of intensity nonuniformity in breast MRI images: a phantom study

NASA Astrophysics Data System (ADS)

Borys, Damian; Serafin, Wojciech; Gorczewski, Kamil; Kijonka, Marek; Frackiewicz, Mariusz; Palus, Henryk

2018-04-01

The aim of this work was to test the most popular and essential algorithms of the intensity nonuniformity correction of the breast MRI imaging. In this type of MRI imaging, especially in the proximity of the coil, the signal is strong but also can produce some inhomogeneities. Evaluated methods of signal correction were: N3, N3FCM, N4, Nonparametric, and SPM. For testing purposes, a uniform phantom object was used to obtain test images using breast imaging MRI coil. To quantify the results, two measures were used: integral uniformity and standard deviation. For each algorithm minimum, average and maximum values of both evaluation factors have been calculated using the binary mask created for the phantom. In the result, two methods obtained the lowest values in these measures: N3FCM and N4, however, for the second method visually phantom was the most uniform after correction.

Breast tumor segmentation in high resolution x-ray phase contrast analyzer based computed tomography.

PubMed

Brun, E; Grandl, S; Sztrókay-Gaul, A; Barbone, G; Mittone, A; Gasilov, S; Bravin, A; Coan, P

2014-11-01

Phase contrast computed tomography has emerged as an imaging method, which is able to outperform present day clinical mammography in breast tumor visualization while maintaining an equivalent average dose. To this day, no segmentation technique takes into account the specificity of the phase contrast signal. In this study, the authors propose a new mathematical framework for human-guided breast tumor segmentation. This method has been applied to high-resolution images of excised human organs, each of several gigabytes. The authors present a segmentation procedure based on the viscous watershed transform and demonstrate the efficacy of this method on analyzer based phase contrast images. The segmentation of tumors inside two full human breasts is then shown as an example of this procedure's possible applications. A correct and precise identification of the tumor boundaries was obtained and confirmed by manual contouring performed independently by four experienced radiologists. The authors demonstrate that applying the watershed viscous transform allows them to perform the segmentation of tumors in high-resolution x-ray analyzer based phase contrast breast computed tomography images. Combining the additional information provided by the segmentation procedure with the already high definition of morphological details and tissue boundaries offered by phase contrast imaging techniques, will represent a valuable multistep procedure to be used in future medical diagnostic applications.

Library based x-ray scatter correction for dedicated cone beam breast CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Linxi; Zhu, Lei, E-mail: leizhu@gatech.edu

Purpose: The image quality of dedicated cone beam breast CT (CBBCT) is limited by substantial scatter contamination, resulting in cupping artifacts and contrast-loss in reconstructed images. Such effects obscure the visibility of soft-tissue lesions and calcifications, which hinders breast cancer detection and diagnosis. In this work, we propose a library-based software approach to suppress scatter on CBBCT images with high efficiency, accuracy, and reliability. Methods: The authors precompute a scatter library on simplified breast models with different sizes using the GEANT4-based Monte Carlo (MC) toolkit. The breast is approximated as a semiellipsoid with homogeneous glandular/adipose tissue mixture. For scatter correctionmore » on real clinical data, the authors estimate the breast size from a first-pass breast CT reconstruction and then select the corresponding scatter distribution from the library. The selected scatter distribution from simplified breast models is spatially translated to match the projection data from the clinical scan and is subtracted from the measured projection for effective scatter correction. The method performance was evaluated using 15 sets of patient data, with a wide range of breast sizes representing about 95% of general population. Spatial nonuniformity (SNU) and contrast to signal deviation ratio (CDR) were used as metrics for evaluation. Results: Since the time-consuming MC simulation for library generation is precomputed, the authors’ method efficiently corrects for scatter with minimal processing time. Furthermore, the authors find that a scatter library on a simple breast model with only one input parameter, i.e., the breast diameter, sufficiently guarantees improvements in SNU and CDR. For the 15 clinical datasets, the authors’ method reduces the average SNU from 7.14% to 2.47% in coronal views and from 10.14% to 3.02% in sagittal views. On average, the CDR is improved by a factor of 1.49 in coronal views and 2.12 in sagittal views. Conclusions: The library-based scatter correction does not require increase in radiation dose or hardware modifications, and it improves over the existing methods on implementation simplicity and computational efficiency. As demonstrated through patient studies, the authors’ approach is effective and stable, and is therefore clinically attractive for CBBCT imaging.« less

Library based x-ray scatter correction for dedicated cone beam breast CT

PubMed Central

Shi, Linxi; Karellas, Andrew; Zhu, Lei

2016-01-01

Purpose: The image quality of dedicated cone beam breast CT (CBBCT) is limited by substantial scatter contamination, resulting in cupping artifacts and contrast-loss in reconstructed images. Such effects obscure the visibility of soft-tissue lesions and calcifications, which hinders breast cancer detection and diagnosis. In this work, we propose a library-based software approach to suppress scatter on CBBCT images with high efficiency, accuracy, and reliability. Methods: The authors precompute a scatter library on simplified breast models with different sizes using the geant4-based Monte Carlo (MC) toolkit. The breast is approximated as a semiellipsoid with homogeneous glandular/adipose tissue mixture. For scatter correction on real clinical data, the authors estimate the breast size from a first-pass breast CT reconstruction and then select the corresponding scatter distribution from the library. The selected scatter distribution from simplified breast models is spatially translated to match the projection data from the clinical scan and is subtracted from the measured projection for effective scatter correction. The method performance was evaluated using 15 sets of patient data, with a wide range of breast sizes representing about 95% of general population. Spatial nonuniformity (SNU) and contrast to signal deviation ratio (CDR) were used as metrics for evaluation. Results: Since the time-consuming MC simulation for library generation is precomputed, the authors’ method efficiently corrects for scatter with minimal processing time. Furthermore, the authors find that a scatter library on a simple breast model with only one input parameter, i.e., the breast diameter, sufficiently guarantees improvements in SNU and CDR. For the 15 clinical datasets, the authors’ method reduces the average SNU from 7.14% to 2.47% in coronal views and from 10.14% to 3.02% in sagittal views. On average, the CDR is improved by a factor of 1.49 in coronal views and 2.12 in sagittal views. Conclusions: The library-based scatter correction does not require increase in radiation dose or hardware modifications, and it improves over the existing methods on implementation simplicity and computational efficiency. As demonstrated through patient studies, the authors’ approach is effective and stable, and is therefore clinically attractive for CBBCT imaging. PMID:27487870

Combination of two-dimensional shear wave elastography with ultrasound breast imaging reporting and data system in the diagnosis of breast lesions: a new method to increase the diagnostic performance.

PubMed

Li, Dan-Dan; Xu, Hui-Xiong; Guo, Le-Hang; Bo, Xiao-Wan; Li, Xiao-Long; Wu, Rong; Xu, Jun-Mei; Zhang, Yi-Feng; Zhang, Kun

2016-09-01

To evaluate the diagnostic performance of a new method of combined two-dimensional shear wave elastography (i.e. virtual touch imaging quantification, VTIQ) and ultrasound (US) Breast Imaging Reporting and Data System (BI-RADS) in the differential diagnosis of breast lesions. From September 2014 to December 2014, 276 patients with 296 pathologically proven breast lesions were enrolled in this study. The conventional US images were interpreted by two independent readers. The diagnosis performances of BI-RADS and combined BI-RADS and VTIQ were evaluated, including the area under the receiver operating characteristic curve (AUROC), sensitivity and specificity. Observer consistency was also evaluated. Pathologically, 212 breast lesions were benign and 84 were malignant. Compared with BI-RADS alone, the AUROCs and specificities of the combined method for both readers increased significantly (AUROC: 0.862 vs. 0.693 in reader 1, 0.861 vs. 0.730 in reader 2; specificity: 91.5 % vs. 38.7 % in reader 1, 94.8 % vs. 47.2 % in reader 2; all P < .05). The Kappa value between the two readers for BI-RADS assessment was 0.614, and 0.796 for the combined method. The combined VTIQ and BI-RADS had a better diagnostic performance in the diagnosis of breast lesions in comparison with BI-RADS alone. • Combination of conventional ultrasound and elastography distinguishes breast cancers more effectively. • Combination of conventional ultrasound and elastography increases observer consistency. • BI-RADS weights more than the 2D-SWE with an increase in malignancy probability.

Body image disturbance and surgical decision making in egyptian post menopausal breast cancer patients

PubMed Central

Shoma, Ashraf M; Mohamed, Madiha H; Nouman, Nashaat; Amin, Mahmoud; Ibrahim, Ibtihal M; Tobar, Salwa S; Gaffar, Hanan E; Aboelez, Warda F; Ali, Salwa E; William, Soheir G

2009-01-01

Background In most developing countries, as in Egypt; postmenopausal breast cancer cases are offered a radical form of surgery relying on their unawareness of the subsequent body image disturbance. This study aimed at evaluating the effect of breast cancer surgical choice; Breast Conservative Therapy (BCT) versus Modified Radical Mastectomy (MRM); on body image perception among Egyptian postmenopausal cases. Methods One hundred postmenopausal women with breast cancer were divided into 2 groups, one group underwent BCT and the other underwent MRM. Pre- and post-operative assessments of body image distress were done using four scales; Breast Impact of Treatment Scale (BITS), Impact of Event Scale (IES), Situational Discomfort Scale (SDS), and Body Satisfaction Scale (BSS). Results Preoperative assessment showed no statistical significant difference regarding cognitive, affective, behavioral and evaluative components of body image between both studied groups. While in postoperative assessment, women in MRM group showed higher levels of body image distress among cognitive, affective and behavioral aspects. Conclusion Body image is an important factor for postmenopausal women with breast cancer in developing countries where that concept is widely ignored. We should not deprive those cases from their right of less mutilating option of treatment as BCT. PMID:19678927

Comparison of temporal and spectral scattering methods using acoustically large breast models derived from magnetic resonance images.

PubMed

Hesford, Andrew J; Tillett, Jason C; Astheimer, Jeffrey P; Waag, Robert C

2014-08-01

Accurate and efficient modeling of ultrasound propagation through realistic tissue models is important to many aspects of clinical ultrasound imaging. Simplified problems with known solutions are often used to study and validate numerical methods. Greater confidence in a time-domain k-space method and a frequency-domain fast multipole method is established in this paper by analyzing results for realistic models of the human breast. Models of breast tissue were produced by segmenting magnetic resonance images of ex vivo specimens into seven distinct tissue types. After confirming with histologic analysis by pathologists that the model structures mimicked in vivo breast, the tissue types were mapped to variations in sound speed and acoustic absorption. Calculations of acoustic scattering by the resulting model were performed on massively parallel supercomputer clusters using parallel implementations of the k-space method and the fast multipole method. The efficient use of these resources was confirmed by parallel efficiency and scalability studies using large-scale, realistic tissue models. Comparisons between the temporal and spectral results were performed in representative planes by Fourier transforming the temporal results. An RMS field error less than 3% throughout the model volume confirms the accuracy of the methods for modeling ultrasound propagation through human breast.

Towards Dynamic Contrast Specific Ultrasound Tomography

NASA Astrophysics Data System (ADS)

Demi, Libertario; van Sloun, Ruud J. G.; Wijkstra, Hessel; Mischi, Massimo

2016-10-01

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast.

Towards Dynamic Contrast Specific Ultrasound Tomography.

PubMed

Demi, Libertario; Van Sloun, Ruud J G; Wijkstra, Hessel; Mischi, Massimo

2016-10-05

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast.

Towards Dynamic Contrast Specific Ultrasound Tomography

PubMed Central

Demi, Libertario; Van Sloun, Ruud J. G.; Wijkstra, Hessel; Mischi, Massimo

2016-01-01

We report on the first study demonstrating the ability of a recently-developed, contrast-enhanced, ultrasound imaging method, referred to as cumulative phase delay imaging (CPDI), to image and quantify ultrasound contrast agent (UCA) kinetics. Unlike standard ultrasound tomography, which exploits changes in speed of sound and attenuation, CPDI is based on a marker specific to UCAs, thus enabling dynamic contrast-specific ultrasound tomography (DCS-UST). For breast imaging, DCS-UST will lead to a more practical, faster, and less operator-dependent imaging procedure compared to standard echo-contrast, while preserving accurate imaging of contrast kinetics. Moreover, a linear relation between CPD values and ultrasound second-harmonic intensity was measured (coefficient of determination = 0.87). DCS-UST can find clinical applications as a diagnostic method for breast cancer localization, adding important features to multi-parametric ultrasound tomography of the breast. PMID:27703251

Comparison of digital breast tomosynthesis and 2D digital mammography using a hybrid performance test

NASA Astrophysics Data System (ADS)

Cockmartin, Lesley; Marshall, Nicholas W.; Van Ongeval, Chantal; Aerts, Gwen; Stalmans, Davina; Zanca, Federica; Shaheen, Eman; De Keyzer, Frederik; Dance, David R.; Young, Kenneth C.; Bosmans, Hilde

2015-05-01

This paper introduces a hybrid method for performing detection studies in projection image based modalities, based on image acquisitions of target objects and patients. The method was used to compare 2D mammography and digital breast tomosynthesis (DBT) in terms of the detection performance of spherical densities and microcalcifications. The method starts with the acquisition of spheres of different glandular equivalent densities and microcalcifications of different sizes immersed in a homogeneous breast tissue simulating medium. These target objects are then segmented and the subsequent templates are fused in projection images of patients and processed or reconstructed. This results in hybrid images with true mammographic anatomy and clinically relevant target objects, ready for use in observer studies. The detection study of spherical densities used 108 normal and 178 hybrid 2D and DBT images; 156 normal and 321 hybrid images were used for the microcalcifications. Seven observers scored the presence/absence of the spheres/microcalcifications in a square region via a 5-point confidence rating scale. Detection performance in 2D and DBT was compared via ROC analysis with sub-analyses for the density of the spheres, microcalcification size, breast thickness and z-position. The study was performed on a Siemens Inspiration tomosynthesis system using patient acquisitions with an average age of 58 years and an average breast thickness of 53 mm providing mean glandular doses of 1.06 mGy (2D) and 2.39 mGy (DBT). Study results showed that breast tomosynthesis (AUC = 0.973) outperformed 2D (AUC = 0.831) for the detection of spheres (p  <  0.0001) and this applied for all spherical densities and breast thicknesses. By way of contrast, DBT was worse than 2D for microcalcification detection (AUC2D = 0.974, AUCDBT = 0.838, p  <  0.0001), with significant differences found for all sizes (150-354 µm), for breast thicknesses above 40 mm and for heights above the detector of 20 mm and above. In conclusion, the hybrid method was successfully used to produce images for a detection study; results showed breast tomosynthesis outperformed 2D for spherical densities while further optimization of DBT for microcalcifications is suggested.

Fusion of digital breast tomosynthesis images via wavelet synthesis for improved lesion conspicuity

NASA Astrophysics Data System (ADS)

Hariharan, Harishwaran; Pomponiu, Victor; Zheng, Bin; Whiting, Bruce; Gur, David

2014-03-01

Full-field digital mammography (FFDM) is the most common screening procedure for detecting early breast cancer. However, due to complications such as overlapping breast tissue in projection images, the efficacy of FFDM reading is reduced. Recent studies have shown that digital breast tomosynthesis (DBT), in combination with FFDM, increases detection sensitivity considerably while decreasing false-positive, recall rates. There is a huge interest in creating diagnostically accurate 2-D interpretations from the DBT slices. Most of the 2-D syntheses rely on visualizing the maximum intensities (brightness) from each slice through different methods. We propose a wavelet based fusion method, where we focus on preserving holistic information from larger structures such as masses while adding high frequency information that is relevant and helpful for diagnosis. This method enables the spatial generation of a 2D image from a series of DBT images, each of which contains both smooth and coarse structures distributed in the wavelet domain. We believe that the wavelet-synthesized images, generated from their DBT image datasets, provide radiologists with improved lesion and micro-calcification conspicuity as compared with FFDM images. The potential impact of this fusion method is (1) Conception of a device-independent, data-driven modality that increases the conspicuity of lesions, thereby facilitating early detection and potentially reducing recall rates; (2) Reduction of the accompanying radiation dose to the patient.

Direct Extraction of Tumor Response Based on Ensemble Empirical Mode Decomposition for Image Reconstruction of Early Breast Cancer Detection by UWB.

PubMed

Li, Qinwei; Xiao, Xia; Wang, Liang; Song, Hang; Kono, Hayato; Liu, Peifang; Lu, Hong; Kikkawa, Takamaro

2015-10-01

A direct extraction method of tumor response based on ensemble empirical mode decomposition (EEMD) is proposed for early breast cancer detection by ultra-wide band (UWB) microwave imaging. With this approach, the image reconstruction for the tumor detection can be realized with only extracted signals from as-detected waveforms. The calibration process executed in the previous research for obtaining reference waveforms which stand for signals detected from the tumor-free model is not required. The correctness of the method is testified by successfully detecting a 4 mm tumor located inside the glandular region in one breast model and by the model located at the interface between the gland and the fat, respectively. The reliability of the method is checked by distinguishing a tumor buried in the glandular tissue whose dielectric constant is 35. The feasibility of the method is confirmed by showing the correct tumor information in both simulation results and experimental results for the realistic 3-D printed breast phantom.

Optical tomographic imaging for breast cancer detection

NASA Astrophysics Data System (ADS)

Cong, Wenxiang; Intes, Xavier; Wang, Ge

2017-09-01

Diffuse optical breast imaging utilizes near-infrared (NIR) light propagation through tissues to assess the optical properties of tissues for the identification of abnormal tissue. This optical imaging approach is sensitive, cost-effective, and does not involve any ionizing radiation. However, the image reconstruction of diffuse optical tomography (DOT) is a nonlinear inverse problem and suffers from severe illposedness due to data noise, NIR light scattering, and measurement incompleteness. An image reconstruction method is proposed for the detection of breast cancer. This method splits the image reconstruction problem into the localization of abnormal tissues and quantification of absorption variations. The localization of abnormal tissues is performed based on a well-posed optimization model, which can be solved via a differential evolution optimization method to achieve a stable reconstruction. The quantification of abnormal absorption is then determined in localized regions of relatively small extents, in which a potential tumor might be. Consequently, the number of unknown absorption variables can be greatly reduced to overcome the underdetermined nature of DOT. Numerical simulation experiments are performed to verify merits of the proposed method, and the results show that the image reconstruction method is stable and accurate for the identification of abnormal tissues, and robust against the measurement noise of data.

Efficient Segmentation of a Breast in B-Mode Ultrasound Tomography Using Three-Dimensional GrabCut (GC3D)

PubMed Central

Wu, Shibin; Zhuang, Ling; Wei, Xinhua; Sak, Mark; Neb, Duric; Hu, Jiani; Xie, Yaoqin

2017-01-01

As an emerging modality for whole breast imaging, ultrasound tomography (UST), has been adopted for diagnostic purposes. Efficient segmentation of an entire breast in UST images plays an important role in quantitative tissue analysis and cancer diagnosis, while major existing methods suffer from considerable time consumption and intensive user interaction. This paper explores three-dimensional GrabCut (GC3D) for breast isolation in thirty reflection (B-mode) UST volumetric images. The algorithm can be conveniently initialized by localizing points to form a polygon, which covers the potential breast region. Moreover, two other variations of GrabCut and an active contour method were compared. Algorithm performance was evaluated from volume overlap ratios (TO, target overlap; MO, mean overlap; FP, false positive; FN, false negative) and time consumption. Experimental results indicate that GC3D considerably reduced the work load and achieved good performance (TO = 0.84; MO = 0.91; FP = 0.006; FN = 0.16) within an average of 1.2 min per volume. Furthermore, GC3D is not only user friendly, but also robust to various inputs, suggesting its great potential to facilitate clinical applications during whole-breast UST imaging. In the near future, the implemented GC3D can be easily automated to tackle B-mode UST volumetric images acquired from the updated imaging system. PMID:28786946

Development of time-resolved reflectance diffuse optical tomography for breast cancer monitoring

NASA Astrophysics Data System (ADS)

Yoshimoto, Kenji; Ohmae, Etsuko; Yamashita, Daisuke; Suzuki, Hiroaki; Homma, Shu; Mimura, Tetsuya; Wada, Hiroko; Suzuki, Toshihiko; Yoshizawa, Nobuko; Nasu, Hatsuko; Ogura, Hiroyuki; Sakahara, Harumi; Yamashita, Yutaka; Ueda, Yukio

2017-02-01

We developed a time-resolved reflectance diffuse optical tomography (RDOT) system to measure tumor responses to chemotherapy in breast cancer patients at the bedside. This system irradiates the breast with a three-wavelength pulsed laser (760, 800, and 830 nm) through a source fiber specified by an optical switch. The light collected by detector fibers is guided to a detector unit consisting of variable attenuators and photomultiplier tubes. Thirteen irradiation and 12 detection points were set to a measurement area of 50 × 50 mm for a hand-held probe. The data acquisition time required to obtain the temporal profiles within the measurement area is about 2 minutes. The RDOT system generates topographic and tomographic images of tissue properties such as hemoglobin concentration and tissue oxygen saturation using two imaging methods. Topographic images are obtained from the optical properties determined for each source-detector pair using a curve-fitting method based on the photon diffusion theory, while tomographic images are reconstructed using an iterative image reconstruction method. In an experiment using a tissue-like solid phantom, a tumor-like cylindrical target (15 mm diameter, 15 mm high) embedded in a breast tissue-like background medium was successfully reconstructed. Preliminary clinical measurements indicated that the tumor in a breast cancer patient was detected as a region of high hemoglobin concentration. In addition, the total hemoglobin concentration decreased during chemotherapy. These results demonstrate the potential of RDOT for evaluating the effectiveness of chemotherapy in patients with breast cancer.

Full automatic fiducial marker detection on coil arrays for accurate instrumentation placement during MRI guided breast interventions

NASA Astrophysics Data System (ADS)

Filippatos, Konstantinos; Boehler, Tobias; Geisler, Benjamin; Zachmann, Harald; Twellmann, Thorsten

2010-02-01

With its high sensitivity, dynamic contrast-enhanced MR imaging (DCE-MRI) of the breast is today one of the first-line tools for early detection and diagnosis of breast cancer, particularly in the dense breast of young women. However, many relevant findings are very small or occult on targeted ultrasound images or mammography, so that MRI guided biopsy is the only option for a precise histological work-up [1]. State-of-the-art software tools for computer-aided diagnosis of breast cancer in DCE-MRI data offer also means for image-based planning of biopsy interventions. One step in the MRI guided biopsy workflow is the alignment of the patient position with the preoperative MR images. In these images, the location and orientation of the coil localization unit can be inferred from a number of fiducial markers, which for this purpose have to be manually or semi-automatically detected by the user. In this study, we propose a method for precise, full-automatic localization of fiducial markers, on which basis a virtual localization unit can be subsequently placed in the image volume for the purpose of determining the parameters for needle navigation. The method is based on adaptive thresholding for separating breast tissue from background followed by rigid registration of marker templates. In an evaluation of 25 clinical cases comprising 4 different commercial coil array models and 3 different MR imaging protocols, the method yielded a sensitivity of 0.96 at a false positive rate of 0.44 markers per case. The mean distance deviation between detected fiducial centers and ground truth information that was appointed from a radiologist was 0.94mm.

A new bias field correction method combining N3 and FCM for improved segmentation of breast density on MRI.

PubMed

Lin, Muqing; Chan, Siwa; Chen, Jeon-Hor; Chang, Daniel; Nie, Ke; Chen, Shih-Ting; Lin, Cheng-Ju; Shih, Tzu-Ching; Nalcioglu, Orhan; Su, Min-Ying

2011-01-01

Quantitative breast density is known as a strong risk factor associated with the development of breast cancer. Measurement of breast density based on three-dimensional breast MRI may provide very useful information. One important step for quantitative analysis of breast density on MRI is the correction of field inhomogeneity to allow an accurate segmentation of the fibroglandular tissue (dense tissue). A new bias field correction method by combining the nonparametric nonuniformity normalization (N3) algorithm and fuzzy-C-means (FCM)-based inhomogeneity correction algorithm is developed in this work. The analysis is performed on non-fat-sat T1-weighted images acquired using a 1.5 T MRI scanner. A total of 60 breasts from 30 healthy volunteers was analyzed. N3 is known as a robust correction method, but it cannot correct a strong bias field on a large area. FCM-based algorithm can correct the bias field on a large area, but it may change the tissue contrast and affect the segmentation quality. The proposed algorithm applies N3 first, followed by FCM, and then the generated bias field is smoothed using Gaussian kernal and B-spline surface fitting to minimize the problem of mistakenly changed tissue contrast. The segmentation results based on the N3+FCM corrected images were compared to the N3 and FCM alone corrected images and another method, coherent local intensity clustering (CLIC), corrected images. The segmentation quality based on different correction methods were evaluated by a radiologist and ranked. The authors demonstrated that the iterative N3+FCM correction method brightens the signal intensity of fatty tissues and that separates the histogram peaks between the fibroglandular and fatty tissues to allow an accurate segmentation between them. In the first reading session, the radiologist found (N3+FCM > N3 > FCM) ranking in 17 breasts, (N3+FCM > N3 = FCM) ranking in 7 breasts, (N3+FCM = N3 > FCM) in 32 breasts, (N3+FCM = N3 = FCM) in 2 breasts, and (N3 > N3+FCM > FCM) in 2 breasts. The results of the second reading session were similar. The performance in each pairwise Wilcoxon signed-rank test is significant, showing N3+FCM superior to both N3 and FCM, and N3 superior to FCM. The performance of the new N3+FCM algorithm was comparable to that of CLIC, showing equivalent quality in 57/60 breasts. Choosing an appropriate bias field correction method is a very important preprocessing step to allow an accurate segmentation of fibroglandular tissues based on breast MRI for quantitative measurement of breast density. The proposed algorithm combining N3+FCM and CLIC both yield satisfactory results.

Measurement of breast density with digital breast tomosynthesis—a systematic review

PubMed Central

McEntee, M F

2014-01-01

Digital breast tomosynthesis (DBT) has gained acceptance as an adjunct to digital mammography in screening. Now that breast density reporting is mandated in several states in the USA, it is increasingly important that the methods of breast density measurement be robust, reliable and consistent. Breast density assessment with DBT needs some consideration since quantitative methods are modelled for two-dimensional (2D) mammography. A review of methods used for breast density assessment with DBT was performed. Existing evidence shows Cumulus has better reproducibility than that of the breast imaging reporting and data system (BI-RADS®) but still suffers from subjective variability; MedDensity is limited by image noise, whilst Volpara and Quantra are robust and consistent. The reported BI-RADs inter-reader breast density agreement (k) ranged from 0.65 to 0.91, with inter-reader correlation (r) ranging from 0.70 to 0.93. The correlation (r) between BI-RADS and Cumulus ranged from 0.54–0.94, whilst that of BI-RADs and MedDensity ranged from 0.48–0.78. The reported agreement (k) between BI-RADs and Volpara is 0.953. Breast density correlation between DBT and 2D mammography ranged from 0.73 to 0.97, with agreement (k) ranging from 0.56 to 0.96. To avoid variability and provide more reliable breast density information for clinicians, automated volumetric methods are preferred. PMID:25146640

Assessment of automatic exposure control performance in digital mammography using a no-reference anisotropic quality index

NASA Astrophysics Data System (ADS)

Barufaldi, Bruno; Borges, Lucas R.; Bakic, Predrag R.; Vieira, Marcelo A. C.; Schiabel, Homero; Maidment, Andrew D. A.

2017-03-01

Automatic exposure control (AEC) is used in mammography to obtain acceptable radiation dose and adequate image quality regardless of breast thickness and composition. Although there are physics methods for assessing the AEC, it is not clear whether mammography systems operate with optimal dose and image quality in clinical practice. In this work, we propose the use of a normalized anisotropic quality index (NAQI), validated in previous studies, to evaluate the quality of mammograms acquired using AEC. The authors used a clinical dataset that consists of 561 patients and 1,046 mammograms (craniocaudal breast views). The results show that image quality is often maintained, even at various radiation levels (mean NAQI = 0.14 +/- 0.02). However, a more careful analysis of NAQI reveals that the average image quality decreases as breast thickness increases. The NAQI is reduced by 32% on average, when the breast thickness increases from 31 to 71 mm. NAQI also decreases with lower breast density. The variation in breast parenchyma alone cannot fully account for the decrease of NAQI with thickness. Examination of images shows that images of large, fatty breasts are often inadequately processed. This work shows that NAQI can be applied in clinical mammograms to assess mammographic image quality, and highlights the limitations of the automatic exposure control for some images.

Using deep learning to segment breast and fibroglandular tissue in MRI volumes.

PubMed

Dalmış, Mehmet Ufuk; Litjens, Geert; Holland, Katharina; Setio, Arnaud; Mann, Ritse; Karssemeijer, Nico; Gubern-Mérida, Albert

2017-02-01

Automated segmentation of breast and fibroglandular tissue (FGT) is required for various computer-aided applications of breast MRI. Traditional image analysis and computer vision techniques, such atlas, template matching, or, edge and surface detection, have been applied to solve this task. However, applicability of these methods is usually limited by the characteristics of the images used in the study datasets, while breast MRI varies with respect to the different MRI protocols used, in addition to the variability in breast shapes. All this variability, in addition to various MRI artifacts, makes it a challenging task to develop a robust breast and FGT segmentation method using traditional approaches. Therefore, in this study, we investigated the use of a deep-learning approach known as "U-net." We used a dataset of 66 breast MRI's randomly selected from our scientific archive, which includes five different MRI acquisition protocols and breasts from four breast density categories in a balanced distribution. To prepare reference segmentations, we manually segmented breast and FGT for all images using an in-house developed workstation. We experimented with the application of U-net in two different ways for breast and FGT segmentation. In the first method, following the same pipeline used in traditional approaches, we trained two consecutive (2C) U-nets: first for segmenting the breast in the whole MRI volume and the second for segmenting FGT inside the segmented breast. In the second method, we used a single 3-class (3C) U-net, which performs both tasks simultaneously by segmenting the volume into three regions: nonbreast, fat inside the breast, and FGT inside the breast. For comparison, we applied two existing and published methods to our dataset: an atlas-based method and a sheetness-based method. We used Dice Similarity Coefficient (DSC) to measure the performances of the automated methods, with respect to the manual segmentations. Additionally, we computed Pearson's correlation between the breast density values computed based on manual and automated segmentations. The average DSC values for breast segmentation were 0.933, 0.944, 0.863, and 0.848 obtained from 3C U-net, 2C U-nets, atlas-based method, and sheetness-based method, respectively. The average DSC values for FGT segmentation obtained from 3C U-net, 2C U-nets, and atlas-based methods were 0.850, 0.811, and 0.671, respectively. The correlation between breast density values based on 3C U-net and manual segmentations was 0.974. This value was significantly higher than 0.957 as obtained from 2C U-nets (P < 0.0001, Steiger's Z-test with Bonferoni correction) and 0.938 as obtained from atlas-based method (P = 0.0016). In conclusion, we applied a deep-learning method, U-net, for segmenting breast and FGT in MRI in a dataset that includes a variety of MRI protocols and breast densities. Our results showed that U-net-based methods significantly outperformed the existing algorithms and resulted in significantly more accurate breast density computation. © 2016 American Association of Physicists in Medicine.

Mammogram registration: a phantom-based evaluation of compressed breast thickness variation effects.

PubMed

Richard, Frédéric J P; Bakić, Predrag R; Maidment, Andrew D A

2006-02-01

The temporal comparison of mammograms is complex; a wide variety of factors can cause changes in image appearance. Mammogram registration is proposed as a method to reduce the effects of these changes and potentially to emphasize genuine alterations in breast tissue. Evaluation of such registration techniques is difficult since ground truth regarding breast deformations is not available in clinical mammograms. In this paper, we propose a systematic approach to evaluate sensitivity of registration methods to various types of changes in mammograms using synthetic breast images with known deformations. As a first step, images of the same simulated breasts with various amounts of simulated physical compression have been used to evaluate a previously described nonrigid mammogram registration technique. Registration performance is measured by calculating the average displacement error over a set of evaluation points identified in mammogram pairs. Applying appropriate thickness compensation and using a preferred order of the registered images, we obtained an average displacement error of 1.6 mm for mammograms with compression differences of 1-3 cm. The proposed methodology is applicable to analysis of other sources of mammogram differences and can be extended to the registration of multimodality breast data.

New look inside human breast ducts with Raman imaging. Raman candidates as diagnostic markers for breast cancer prognosis: Mammaglobin, palmitic acid and sphingomyelin.

PubMed

Abramczyk, Halina; Brozek-Pluska, Beata

2016-02-25

Looking inside the human body fascinated mankind for thousands of years. Current diagnostic and therapy methods are often limited by inadequate sensitivity, specificity and spatial resolution. Raman imaging may bring revolution in monitoring of disease and treatment. The main advantage of Raman imaging is that it gives spatial information about various chemical constituents in defined cellular organelles in contrast to conventional methods (liquid chromatography/mass spectrometry, NMR, HPLC) that rely on bulk or fractionated analyses of extracted components. We demonstrated how Raman imaging can drive the progress on breast cancer just unimaginable a few years ago. We looked inside human breast ducts answering fundamental questions about location and distribution of various biochemical components inside the lumen, epithelial cells of the duct and the stroma around the duct during cancer development. We have identified Raman candidates as diagnostic markers for breast cancer prognosis: carotenoids, mammaglobin, palmitic acid and sphingomyelin as key molecular targets in ductal breast cancer in situ, and propose the molecular mechanisms linking oncogenes with lipid programming. Copyright © 2016 Elsevier B.V. All rights reserved.

Liquid crystal foil for the detection of breast cancer

NASA Astrophysics Data System (ADS)

Biernat, Michał; Trzyna, Marcin; Byszek, Agnieszka; Jaremek, Henryk

2016-09-01

Breast cancer is the most common malignant tumor in females around the world, representing 25.2% of all cancers in women. About 1.7 million women were diagnosed with breast cancer worldwide in 2012 with a death rate of about 522,0001,2. The most frequently used methods in breast cancer screening are imaging methods, i.e. ultrasonography and mammography. A common feature of these methods is that they inherently involve the use of expensive and advanced equipment. The development of advanced computer systems allowed for the continuation of research started already in the 1980s3 and the use of contact thermography in breast cancer screening. The physiological basis for the application of thermography in medical imaging diagnostics is the so-called dermothermal effect related to higher metabolism rate around focal neoplastic lesion. This phenomenon can occur on breast surface as localized temperature anomalies4. The device developed by Braster is composed of a detector that works on the basis of thermotropic liquid crystals, image acquisition device and a computer system for image data processing and analysis. Production of the liquid crystal detector was based on a proprietary CLCF technology (Continuous Liquid Crystal Film). In 2014 Braster started feasibility study to prove that there is a potential for artificial intelligence in early breast cancer detection using Braster's proprietary technology. The aim of this study was to develop a computer system, using a client-server architecture, to an automatic interpretation of thermographic pictures created by the Braster devices.

Estimation of effective x-ray tissue attenuation differences for volumetric breast density measurement

NASA Astrophysics Data System (ADS)

Chen, Biao; Ruth, Chris; Jing, Zhenxue; Ren, Baorui; Smith, Andrew; Kshirsagar, Ashwini

2014-03-01

Breast density has been identified to be a risk factor of developing breast cancer and an indicator of lesion diagnostic obstruction due to masking effect. Volumetric density measurement evaluates fibro-glandular volume, breast volume, and breast volume density measures that have potential advantages over area density measurement in risk assessment. One class of volume density computing methods is based on the finding of the relative fibro-glandular tissue attenuation with regards to the reference fat tissue, and the estimation of the effective x-ray tissue attenuation differences between the fibro-glandular and fat tissue is key to volumetric breast density computing. We have modeled the effective attenuation difference as a function of actual x-ray skin entrance spectrum, breast thickness, fibro-glandular tissue thickness distribution, and detector efficiency. Compared to other approaches, our method has threefold advantages: (1) avoids the system calibration-based creation of effective attenuation differences which may introduce tedious calibrations for each imaging system and may not reflect the spectrum change and scatter induced overestimation or underestimation of breast density; (2) obtains the system specific separate and differential attenuation values of fibroglandular and fat for each mammographic image; and (3) further reduces the impact of breast thickness accuracy to volumetric breast density. A quantitative breast volume phantom with a set of equivalent fibro-glandular thicknesses has been used to evaluate the volume breast density measurement with the proposed method. The experimental results have shown that the method has significantly improved the accuracy of estimating breast density.

Newly Diagnosed Breast Cancer: Comparison of Contrast-enhanced Spectral Mammography and Breast MR Imaging in the Evaluation of Extent of Disease.

PubMed

Lee-Felker, Stephanie A; Tekchandani, Leena; Thomas, Mariam; Gupta, Esha; Andrews-Tang, Denise; Roth, Antoinette; Sayre, James; Rahbar, Guita

2017-11-01

Purpose To compare the diagnostic performances of contrast material-enhanced spectral mammography and breast magnetic resonance (MR) imaging in the detection of index and secondary cancers in women with newly diagnosed breast cancer by using histologic or imaging follow-up as the standard of reference. Materials and Methods This institutional review board-approved, HIPAA-compliant, retrospective study included 52 women who underwent breast MR imaging and contrast-enhanced spectral mammography for newly diagnosed unilateral breast cancer between March 2014 and October 2015. Of those 52 patients, 46 were referred for contrast-enhanced spectral mammography and targeted ultrasonography because they had additional suspicious lesions at MR imaging. In six of the 52 patients, breast cancer had been diagnosed at an outside institution. These patients were referred for contrast-enhanced spectral mammography and targeted US as part of diagnostic imaging. Images from contrast-enhanced spectral mammography were analyzed by two fellowship-trained breast imagers with 2.5 years of experience with contrast-enhanced spectral mammography. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated for both imaging modalities and compared by using the Bennett statistic. Results Fifty-two women with 120 breast lesions were included for analysis (mean age, 50 years; range, 29-73 years). Contrast-enhanced spectral mammography had similar sensitivity to MR imaging (94% [66 of 70 lesions] vs 99% [69 of 70 lesions]), a significantly higher PPV than MR imaging (93% [66 of 71 lesions] vs 60% [69 of 115 lesions]), and fewer false-positive findings than MR imaging (five vs 45) (P < .001 for all results). In addition, contrast-enhanced spectral mammography depicted 11 of the 11 secondary cancers (100%) and MR imaging depicted 10 (91%). Conclusion Contrast-enhanced spectral mammography is potentially as sensitive as MR imaging in the evaluation of extent of disease in newly diagnosed breast cancer, with a higher PPV. © RSNA, 2017.

A novel deep learning-based approach to high accuracy breast density estimation in digital mammography

NASA Astrophysics Data System (ADS)

Ahn, Chul Kyun; Heo, Changyong; Jin, Heongmin; Kim, Jong Hyo

2017-03-01

Mammographic breast density is a well-established marker for breast cancer risk. However, accurate measurement of dense tissue is a difficult task due to faint contrast and significant variations in background fatty tissue. This study presents a novel method for automated mammographic density estimation based on Convolutional Neural Network (CNN). A total of 397 full-field digital mammograms were selected from Seoul National University Hospital. Among them, 297 mammograms were randomly selected as a training set and the rest 100 mammograms were used for a test set. We designed a CNN architecture suitable to learn the imaging characteristic from a multitudes of sub-images and classify them into dense and fatty tissues. To train the CNN, not only local statistics but also global statistics extracted from an image set were used. The image set was composed of original mammogram and eigen-image which was able to capture the X-ray characteristics in despite of the fact that CNN is well known to effectively extract features on original image. The 100 test images which was not used in training the CNN was used to validate the performance. The correlation coefficient between the breast estimates by the CNN and those by the expert's manual measurement was 0.96. Our study demonstrated the feasibility of incorporating the deep learning technology into radiology practice, especially for breast density estimation. The proposed method has a potential to be used as an automated and quantitative assessment tool for mammographic breast density in routine practice.

Automatic classification of tissue malignancy for breast carcinoma diagnosis.

PubMed

Fondón, Irene; Sarmiento, Auxiliadora; García, Ana Isabel; Silvestre, María; Eloy, Catarina; Polónia, António; Aguiar, Paulo

2018-05-01

Breast cancer is the second leading cause of cancer death among women. Its early diagnosis is extremely important to prevent avoidable deaths. However, malignancy assessment of tissue biopsies is complex and dependent on observer subjectivity. Moreover, hematoxylin and eosin (H&E)-stained histological images exhibit a highly variable appearance, even within the same malignancy level. In this paper, we propose a computer-aided diagnosis (CAD) tool for automated malignancy assessment of breast tissue samples based on the processing of histological images. We provide four malignancy levels as the output of the system: normal, benign, in situ and invasive. The method is based on the calculation of three sets of features related to nuclei, colour regions and textures considering local characteristics and global image properties. By taking advantage of well-established image processing techniques, we build a feature vector for each image that serves as an input to an SVM (Support Vector Machine) classifier with a quadratic kernel. The method has been rigorously evaluated, first with a 5-fold cross-validation within an initial set of 120 images, second with an external set of 30 different images and third with images with artefacts included. Accuracy levels range from 75.8% when the 5-fold cross-validation was performed to 75% with the external set of new images and 61.11% when the extremely difficult images were added to the classification experiment. The experimental results indicate that the proposed method is capable of distinguishing between four malignancy levels with high accuracy. Our results are close to those obtained with recent deep learning-based methods. Moreover, it performs better than other state-of-the-art methods based on feature extraction, and it can help improve the CAD of breast cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

Breast percent density estimation from 3D reconstructed digital breast tomosynthesis images

NASA Astrophysics Data System (ADS)

Bakic, Predrag R.; Kontos, Despina; Carton, Ann-Katherine; Maidment, Andrew D. A.

2008-03-01

Breast density is an independent factor of breast cancer risk. In mammograms breast density is quantitatively measured as percent density (PD), the percentage of dense (non-fatty) tissue. To date, clinical estimates of PD have varied significantly, in part due to the projective nature of mammography. Digital breast tomosynthesis (DBT) is a 3D imaging modality in which cross-sectional images are reconstructed from a small number of projections acquired at different x-ray tube angles. Preliminary studies suggest that DBT is superior to mammography in tissue visualization, since superimposed anatomical structures present in mammograms are filtered out. We hypothesize that DBT could also provide a more accurate breast density estimation. In this paper, we propose to estimate PD from reconstructed DBT images using a semi-automated thresholding technique. Preprocessing is performed to exclude the image background and the area of the pectoral muscle. Threshold values are selected manually from a small number of reconstructed slices; a combination of these thresholds is applied to each slice throughout the entire reconstructed DBT volume. The proposed method was validated using images of women with recently detected abnormalities or with biopsy-proven cancers; only contralateral breasts were analyzed. The Pearson correlation and kappa coefficients between the breast density estimates from DBT and the corresponding digital mammogram indicate moderate agreement between the two modalities, comparable with our previous results from 2D DBT projections. Percent density appears to be a robust measure for breast density assessment in both 2D and 3D x-ray breast imaging modalities using thresholding.

MO-F-CAMPUS-I-04: Characterization of Fan Beam Coded Aperture Coherent Scatter Spectral Imaging Methods for Differentiation of Normal and Neoplastic Breast Structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morris, R; Albanese, K; Lakshmanan, M

Purpose: This study intends to characterize the spectral and spatial resolution limits of various fan beam geometries for differentiation of normal and neoplastic breast structures via coded aperture coherent scatter spectral imaging techniques. In previous studies, pencil beam raster scanning methods using coherent scatter computed tomography and selected volume tomography have yielded excellent results for tumor discrimination. However, these methods don’t readily conform to clinical constraints; primarily prolonged scan times and excessive dose to the patient. Here, we refine a fan beam coded aperture coherent scatter imaging system to characterize the tradeoffs between dose, scan time and image quality formore » breast tumor discrimination. Methods: An X-ray tube (125kVp, 400mAs) illuminated the sample with collimated fan beams of varying widths (3mm to 25mm). Scatter data was collected via two linear-array energy-sensitive detectors oriented parallel and perpendicular to the beam plane. An iterative reconstruction algorithm yields images of the sample’s spatial distribution and respective spectral data for each location. To model in-vivo tumor analysis, surgically resected breast tumor samples were used in conjunction with lard, which has a form factor comparable to adipose (fat). Results: Quantitative analysis with current setup geometry indicated optimal performance for beams up to 10mm wide, with wider beams producing poorer spatial resolution. Scan time for a fixed volume was reduced by a factor of 6 when scanned with a 10mm fan beam compared to a 1.5mm pencil beam. Conclusion: The study demonstrates the utility of fan beam coherent scatter spectral imaging for differentiation of normal and neoplastic breast tissues has successfully reduced dose and scan times whilst sufficiently preserving spectral and spatial resolution. Future work to alter the coded aperture and detector geometries could potentially allow the use of even wider fans, thereby making coded aperture coherent scatter imaging a clinically viable method for breast cancer detection. United States Department of Homeland Security; Duke University Medical Center - Department of Radiology; Carl E Ravin Advanced Imaging Laboratories; Duke University Medical Physics Graduate Program.« less

Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.

Purpose: Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Studies suggest that the relative amount of fibroglandular (i.e., dense) tissue in the breast as quantified in MR images can be predictive of the risk for developing breast cancer, especially for high-risk women. Automated segmentation of the fibroglandular tissue and volumetric density estimation in breast MRI could therefore be useful for breast cancer risk assessment. Methods: In this work the authors develop and validate a fully automated segmentation algorithm, namely, an atlas-aided fuzzy C-means (FCM-Atlas) method, to estimate the volumetric amount of fibroglandularmore » tissue in breast MRI. The FCM-Atlas is a 2D segmentation method working on a slice-by-slice basis. FCM clustering is first applied to the intensity space of each 2D MR slice to produce an initial voxelwise likelihood map of fibroglandular tissue. Then a prior learned fibroglandular tissue likelihood atlas is incorporated to refine the initial FCM likelihood map to achieve enhanced segmentation, from which the absolute volume of the fibroglandular tissue (|FGT|) and the relative amount (i.e., percentage) of the |FGT| relative to the whole breast volume (FGT%) are computed. The authors' method is evaluated by a representative dataset of 60 3D bilateral breast MRI scans (120 breasts) that span the full breast density range of the American College of Radiology Breast Imaging Reporting and Data System. The automated segmentation is compared to manual segmentation obtained by two experienced breast imaging radiologists. Segmentation performance is assessed by linear regression, Pearson's correlation coefficients, Student's pairedt-test, and Dice's similarity coefficients (DSC). Results: The inter-reader correlation is 0.97 for FGT% and 0.95 for |FGT|. When compared to the average of the two readers’ manual segmentation, the proposed FCM-Atlas method achieves a correlation ofr = 0.92 for FGT% and r = 0.93 for |FGT|, and the automated segmentation is not statistically significantly different (p = 0.46 for FGT% and p = 0.55 for |FGT|). The bilateral correlation between left breasts and right breasts for the FGT% is 0.94, 0.92, and 0.95 for reader 1, reader 2, and the FCM-Atlas, respectively; likewise, for the |FGT|, it is 0.92, 0.92, and 0.93, respectively. For the spatial segmentation agreement, the automated algorithm achieves a DSC of 0.69 ± 0.1 when compared to reader 1 and 0.61 ± 0.1 for reader 2, respectively, while the DSC between the two readers’ manual segmentation is 0.67 ± 0.15. Additional robustness analysis shows that the segmentation performance of the authors' method is stable both with respect to selecting different cases and to varying the number of cases needed to construct the prior probability atlas. The authors' results also show that the proposed FCM-Atlas method outperforms the commonly used two-cluster FCM-alone method. The authors' method runs at ∼5 min for each 3D bilateral MR scan (56 slices) for computing the FGT% and |FGT|, compared to ∼55 min needed for manual segmentation for the same purpose. Conclusions: The authors' method achieves robust segmentation and can serve as an efficient tool for processing large clinical datasets for quantifying the fibroglandular tissue content in breast MRI. It holds a great potential to support clinical applications in the future including breast cancer risk assessment.« less

Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.

2013-12-15

Purpose: Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Studies suggest that the relative amount of fibroglandular (i.e., dense) tissue in the breast as quantified in MR images can be predictive of the risk for developing breast cancer, especially for high-risk women. Automated segmentation of the fibroglandular tissue and volumetric density estimation in breast MRI could therefore be useful for breast cancer risk assessment. Methods: In this work the authors develop and validate a fully automated segmentation algorithm, namely, an atlas-aided fuzzy C-means (FCM-Atlas) method, to estimate the volumetric amount of fibroglandularmore » tissue in breast MRI. The FCM-Atlas is a 2D segmentation method working on a slice-by-slice basis. FCM clustering is first applied to the intensity space of each 2D MR slice to produce an initial voxelwise likelihood map of fibroglandular tissue. Then a prior learned fibroglandular tissue likelihood atlas is incorporated to refine the initial FCM likelihood map to achieve enhanced segmentation, from which the absolute volume of the fibroglandular tissue (|FGT|) and the relative amount (i.e., percentage) of the |FGT| relative to the whole breast volume (FGT%) are computed. The authors' method is evaluated by a representative dataset of 60 3D bilateral breast MRI scans (120 breasts) that span the full breast density range of the American College of Radiology Breast Imaging Reporting and Data System. The automated segmentation is compared to manual segmentation obtained by two experienced breast imaging radiologists. Segmentation performance is assessed by linear regression, Pearson's correlation coefficients, Student's pairedt-test, and Dice's similarity coefficients (DSC). Results: The inter-reader correlation is 0.97 for FGT% and 0.95 for |FGT|. When compared to the average of the two readers’ manual segmentation, the proposed FCM-Atlas method achieves a correlation ofr = 0.92 for FGT% and r = 0.93 for |FGT|, and the automated segmentation is not statistically significantly different (p = 0.46 for FGT% and p = 0.55 for |FGT|). The bilateral correlation between left breasts and right breasts for the FGT% is 0.94, 0.92, and 0.95 for reader 1, reader 2, and the FCM-Atlas, respectively; likewise, for the |FGT|, it is 0.92, 0.92, and 0.93, respectively. For the spatial segmentation agreement, the automated algorithm achieves a DSC of 0.69 ± 0.1 when compared to reader 1 and 0.61 ± 0.1 for reader 2, respectively, while the DSC between the two readers’ manual segmentation is 0.67 ± 0.15. Additional robustness analysis shows that the segmentation performance of the authors' method is stable both with respect to selecting different cases and to varying the number of cases needed to construct the prior probability atlas. The authors' results also show that the proposed FCM-Atlas method outperforms the commonly used two-cluster FCM-alone method. The authors' method runs at ∼5 min for each 3D bilateral MR scan (56 slices) for computing the FGT% and |FGT|, compared to ∼55 min needed for manual segmentation for the same purpose. Conclusions: The authors' method achieves robust segmentation and can serve as an efficient tool for processing large clinical datasets for quantifying the fibroglandular tissue content in breast MRI. It holds a great potential to support clinical applications in the future including breast cancer risk assessment.« less

A novel pre-processing technique for improving image quality in digital breast tomosynthesis.

PubMed

Kim, Hyeongseok; Lee, Taewon; Hong, Joonpyo; Sabir, Sohail; Lee, Jung-Ryun; Choi, Young Wook; Kim, Hak Hee; Chae, Eun Young; Cho, Seungryong

2017-02-01

Nonlinear pre-reconstruction processing of the projection data in computed tomography (CT) where accurate recovery of the CT numbers is important for diagnosis is usually discouraged, for such a processing would violate the physics of image formation in CT. However, one can devise a pre-processing step to enhance detectability of lesions in digital breast tomosynthesis (DBT) where accurate recovery of the CT numbers is fundamentally impossible due to the incompleteness of the scanned data. Since the detection of lesions such as micro-calcifications and mass in breasts is the purpose of using DBT, it is justified that a technique producing higher detectability of lesions is a virtue. A histogram modification technique was developed in the projection data domain. Histogram of raw projection data was first divided into two parts: One for the breast projection data and the other for background. Background pixel values were set to a single value that represents the boundary between breast and background. After that, both histogram parts were shifted by an appropriate amount of offset and the histogram-modified projection data were log-transformed. Filtered-backprojection (FBP) algorithm was used for image reconstruction of DBT. To evaluate performance of the proposed method, we computed the detectability index for the reconstructed images from clinically acquired data. Typical breast border enhancement artifacts were greatly suppressed and the detectability of calcifications and masses was increased by use of the proposed method. Compared to a global threshold-based post-reconstruction processing technique, the proposed method produced images of higher contrast without invoking additional image artifacts. In this work, we report a novel pre-processing technique that improves detectability of lesions in DBT and has potential advantages over the global threshold-based post-reconstruction processing technique. The proposed method not only increased the lesion detectability but also reduced typical image artifacts pronounced in conventional FBP-based DBT. © 2016 American Association of Physicists in Medicine.

Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation.

PubMed

Sturgeon, Gregory M; Kiarashi, Nooshin; Lo, Joseph Y; Samei, E; Segars, W P

2016-05-01

The authors are developing a series of computational breast phantoms based on breast CT data for imaging research. In this work, the authors develop a program that will allow a user to alter the phantoms to simulate the effect of gravity and compression of the breast (craniocaudal or mediolateral oblique) making the phantoms applicable to multimodality imaging. This application utilizes a template finite-element (FE) breast model that can be applied to their presegmented voxelized breast phantoms. The FE model is automatically fit to the geometry of a given breast phantom, and the material properties of each element are set based on the segmented voxels contained within the element. The loading and boundary conditions, which include gravity, are then assigned based on a user-defined position and compression. The effect of applying these loads to the breast is computed using a multistage contact analysis in FEBio, a freely available and well-validated FE software package specifically designed for biomedical applications. The resulting deformation of the breast is then applied to a boundary mesh representation of the phantom that can be used for simulating medical images. An efficient script performs the above actions seamlessly. The user only needs to specify which voxelized breast phantom to use, the compressed thickness, and orientation of the breast. The authors utilized their FE application to simulate compressed states of the breast indicative of mammography and tomosynthesis. Gravity and compression were simulated on example phantoms and used to generate mammograms in the craniocaudal or mediolateral oblique views. The simulated mammograms show a high degree of realism illustrating the utility of the FE method in simulating imaging data of repositioned and compressed breasts. The breast phantoms and the compression software can become a useful resource to the breast imaging research community. These phantoms can then be used to evaluate and compare imaging modalities that involve different positioning and compression of the breast.

Computational Simulation of Breast Compression Based on Segmented Breast and Fibroglandular Tissues on Magnetic Resonance Images

PubMed Central

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-01-01

This study presents a finite element based computational model to simulate the three-dimensional deformation of the breast and the fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and the craniocaudal and mediolateral oblique compression as used in mammography was applied. The geometry of whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo® 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the non-linear elastic tissue deformation under compression, using the MSC.Marc® software package. The model was tested in 4 cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these 4 cases at 60% compression ratio was in the range of 5-7 cm, which is the typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at 60% compression ratio was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on MRI, which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density measurements needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities – such as MRI, mammography, whole breast ultrasound, and molecular imaging – that are performed using different body positions and different compression conditions. PMID:20601773

High-Spatial- and High-Temporal-Resolution Dynamic Contrast-enhanced MR Breast Imaging with Sweep Imaging with Fourier Transformation: A Pilot Study

PubMed Central

Benson, John C.; Idiyatullin, Djaudat; Snyder, Angela L.; Snyder, Carl J.; Hutter, Diane; Everson, Lenore I.; Eberly, Lynn E.; Nelson, Michael T.; Garwood, Michael

2015-01-01

Purpose To report the results of sweep imaging with Fourier transformation (SWIFT) magnetic resonance (MR) imaging for diagnostic breast imaging. Materials and Methods Informed consent was obtained from all participants under one of two institutional review board–approved, HIPAA-compliant protocols. Twelve female patients (age range, 19–54 years; mean age, 41.2 years) and eight normal control subjects (age range, 22–56 years; mean age, 43.2 years) enrolled and completed the study from January 28, 2011, to March 5, 2013. Patients had previous lesions that were Breast Imaging Reporting and Data System 4 and 5 based on mammography and/or ultrasonographic imaging. Contrast-enhanced SWIFT imaging was completed by using a 4-T research MR imaging system. Noncontrast studies were completed in the normal control subjects. One of two sized single-breast SWIFT-compatible transceiver coils was used for nine patients and five controls. Three patients and five control subjects used a SWIFT-compatible dual breast coil. Temporal resolution was 5.9–7.5 seconds. Spatial resolution was 1.00 mm isotropic, with later examinations at 0.67 mm isotropic, and dual breast at 1.00 mm or 0.75 mm isotropic resolution. Results Two nonblinded breast radiologists reported SWIFT image findings of normal breast tissue, benign fibroadenomas (six of six lesions), and malignant lesions (10 of 12 lesions) concordant with other imaging modalities and pathologic reports. Two lesions in two patients were not visualized because of coil field of view. The images yielded by SWIFT showed the presence and extent of known breast lesions. Conclusion The SWIFT technique could become an important addition to breast imaging modalities because it provides high spatial resolution at all points during the dynamic contrast-enhanced examination. © RSNA, 2014 PMID:25247405

Computing mammographic density from a multiple regression model constructed with image-acquisition parameters from a full-field digital mammographic unit

PubMed Central

Lu, Lee-Jane W.; Nishino, Thomas K.; Khamapirad, Tuenchit; Grady, James J; Leonard, Morton H.; Brunder, Donald G.

2009-01-01

Breast density (the percentage of fibroglandular tissue in the breast) has been suggested to be a useful surrogate marker for breast cancer risk. It is conventionally measured using screen-film mammographic images by a labor intensive histogram segmentation method (HSM). We have adapted and modified the HSM for measuring breast density from raw digital mammograms acquired by full-field digital mammography. Multiple regression model analyses showed that many of the instrument parameters for acquiring the screening mammograms (e.g. breast compression thickness, radiological thickness, radiation dose, compression force, etc) and image pixel intensity statistics of the imaged breasts were strong predictors of the observed threshold values (model R2=0.93) and %density (R2=0.84). The intra-class correlation coefficient of the %-density for duplicate images was estimated to be 0.80, using the regression model-derived threshold values, and 0.94 if estimated directly from the parameter estimates of the %-density prediction regression model. Therefore, with additional research, these mathematical models could be used to compute breast density objectively, automatically bypassing the HSM step, and could greatly facilitate breast cancer research studies. PMID:17671343

Modeling digital breast tomosynthesis imaging systems for optimization studies

NASA Astrophysics Data System (ADS)

Lau, Beverly Amy

Digital breast tomosynthesis (DBT) is a new imaging modality for breast imaging. In tomosynthesis, multiple images of the compressed breast are acquired at different angles, and the projection view images are reconstructed to yield images of slices through the breast. One of the main problems to be addressed in the development of DBT is the optimal parameter settings to obtain images ideal for detection of cancer. Since it would be unethical to irradiate women multiple times to explore potentially optimum geometries for tomosynthesis, it is ideal to use a computer simulation to generate projection images. Existing tomosynthesis models have modeled scatter and detector without accounting for oblique angles of incidence that tomosynthesis introduces. Moreover, these models frequently use geometry-specific physical factors measured from real systems, which severely limits the robustness of their algorithms for optimization. The goal of this dissertation was to design the framework for a computer simulation of tomosynthesis that would produce images that are sensitive to changes in acquisition parameters, so an optimization study would be feasible. A computer physics simulation of the tomosynthesis system was developed. The x-ray source was modeled as a polychromatic spectrum based on published spectral data, and inverse-square law was applied. Scatter was applied using a convolution method with angle-dependent scatter point spread functions (sPSFs), followed by scaling using an angle-dependent scatter-to-primary ratio (SPR). Monte Carlo simulations were used to generate sPSFs for a 5-cm breast with a 1-cm air gap. Detector effects were included through geometric propagation of the image onto layers of the detector, which were blurred using depth-dependent detector point-spread functions (PRFs). Depth-dependent PRFs were calculated every 5-microns through a 200-micron thick CsI detector using Monte Carlo simulations. Electronic noise was added as Gaussian noise as a last step of the model. The sPSFs and detector PRFs were verified to match published data, and noise power spectrum (NPS) from simulated flat field images were shown to match empirically measured data from a digital mammography unit. A novel anthropomorphic software breast phantom was developed for 3D imaging simulation. Projection view images of the phantom were shown to have similar structure as real breasts in the spatial frequency domain, using the power-law exponent beta to quantify tissue complexity. The physics simulation and computer breast phantom were used together, following methods from a published study with real tomosynthesis images of real breasts. The simulation model and 3D numerical breast phantoms were able to reproduce the trends in the experimental data. This result demonstrates the ability of the tomosynthesis physics model to generate images sensitive to changes in acquisition parameters.

3D MRI for Quantitative Analysis of Quadrant Percent Breast Density: Correlation with Quadrant Location of Breast Cancer.

PubMed

Chen, Jeon-Hor; Liao, Fuyi; Zhang, Yang; Li, Yifan; Chang, Chia-Ju; Chou, Chen-Pin; Yang, Tsung-Lung; Su, Min-Ying

2017-07-01

Breast cancer occurs more frequently in the upper outer (UO) quadrant, but whether this higher cancer incidence is related to the greater amount of dense tissue is not known. Magnetic resonance imaging acquires three-dimensional volumetric images and is the most suitable among all breast imaging modalities for regional quantification of density. This study applied a magnetic resonance imaging-based method to measure quadrant percent density (QPD), and evaluated its association with the quadrant location of the developed breast cancer. A total of 126 cases with pathologically confirmed breast cancer were reviewed. Only women who had unilateral breast cancer located in a clear quadrant were selected for analysis. A total of 84 women, including 47 Asian women and 37 western women, were included. An established computer-aided method was used to segment the diseased breast and the contralateral normal breast, and to separate the dense and fatty tissues. Then, a breast was further separated into four quadrants using the nipple and the centroid as anatomic landmarks. The tumor was segmented using a computer-aided method to determine its quadrant location. The distribution of cancer quadrant location, the quadrant with the highest QPD, and the proportion of cancers occurring in the highest QPD were analyzed. The highest incidence of cancer occurred in the UO quadrant (36 out of 84, 42.9%). The highest QPD was also noted most frequently in the UO quadrant (31 out of 84, 36.9%). When correlating the highest QPD with the quadrant location of breast cancer, only 17 women out of 84 (20.2%) had breast cancer occurring in the quadrant with the highest QPD. The results showed that the development of breast cancer in a specific quadrant could not be explained by the density in that quadrant, and further studies are needed to find the biological reasons accounting for the higher breast cancer incidence in the UO quadrant. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

New method for generating breast models featuring glandular tissue spatial distribution

NASA Astrophysics Data System (ADS)

Paixão, L.; Oliveira, B. B.; Oliveira, M. A.; Teixeira, M. H. A.; Fonseca, T. C. F.; Nogueira, M. S.

2016-02-01

Mammography is the main radiographic technique used for breast imaging. A major concern with mammographic imaging is the risk of radiation-induced breast cancer due to the high sensitivity of breast tissue. The mean glandular dose (DG) is the dosimetric quantity widely accepted to characterize the risk of radiation induced cancer. Previous studies have concluded that DG depends not only on the breast glandular content but also on the spatial distribution of glandular tissue within the breast. In this work, a new method for generating computational breast models featuring skin composition and glandular tissue distribution from patients undergoing digital mammography is proposed. Such models allow a more accurate way of calculating individualized breast glandular doses taking into consideration the glandular tissue fraction. Sixteen breast models of four patients with different glandularity breasts were simulated and the results were compared with those obtained from recommended DG conversion factors. The results show that the internationally recommended conversion factors may be overestimating the mean glandular dose to less dense breasts and underestimating the mean glandular dose for denser breasts. The methodology described in this work constitutes a powerful tool for breast dosimetry, especially for risk studies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brun, E., E-mail: emmanuel.brun@esrf.fr; Grandl, S.; Sztrókay-Gaul, A.

Purpose: Phase contrast computed tomography has emerged as an imaging method, which is able to outperform present day clinical mammography in breast tumor visualization while maintaining an equivalent average dose. To this day, no segmentation technique takes into account the specificity of the phase contrast signal. In this study, the authors propose a new mathematical framework for human-guided breast tumor segmentation. This method has been applied to high-resolution images of excised human organs, each of several gigabytes. Methods: The authors present a segmentation procedure based on the viscous watershed transform and demonstrate the efficacy of this method on analyzer basedmore » phase contrast images. The segmentation of tumors inside two full human breasts is then shown as an example of this procedure’s possible applications. Results: A correct and precise identification of the tumor boundaries was obtained and confirmed by manual contouring performed independently by four experienced radiologists. Conclusions: The authors demonstrate that applying the watershed viscous transform allows them to perform the segmentation of tumors in high-resolution x-ray analyzer based phase contrast breast computed tomography images. Combining the additional information provided by the segmentation procedure with the already high definition of morphological details and tissue boundaries offered by phase contrast imaging techniques, will represent a valuable multistep procedure to be used in future medical diagnostic applications.« less

Department of Defense Era of Hope Scholar Award Nanotechnology-Enabled Optical Molecular Imaging of Breast Cancer

DTIC Science & Technology

2009-07-01

detection, and management of breast cancer today. A variety of imaging methods including screening and diagnostic x- ray mammography and resonance...profile of a tumor. In addition, techniques such as x- ray imaging and MRI are not able to detect small early cancers or pre-cancerous breast...227 (2007). 18. S. Oldenburg , J. Jackson, S. Westcott, and N. Halas, “Infrared extinction properties of gold nanoshells,” Appl. Phys. Lett. 75, 2897

Performance of a Method to Standardize Breast Ultrasound Interpretation Using Image Processing and Case-Based Reasoning

NASA Astrophysics Data System (ADS)

André, M. P.; Galperin, M.; Berry, A.; Ojeda-Fournier, H.; O'Boyle, M.; Olson, L.; Comstock, C.; Taylor, A.; Ledgerwood, M.

Our computer-aided diagnostic (CADx) tool uses advanced image processing and artificial intelligence to analyze findings on breast sonography images. The goal is to standardize reporting of such findings using well-defined descriptors and to improve accuracy and reproducibility of interpretation of breast ultrasound by radiologists. This study examined several factors that may impact accuracy and reproducibility of the CADx software, which proved to be highly accurate and stabile over several operating conditions.

3D frequency-domain ultrasound waveform tomography breast imaging

NASA Astrophysics Data System (ADS)

Sandhu, Gursharan Yash; West, Erik; Li, Cuiping; Roy, Olivier; Duric, Neb

2017-03-01

Frequency-domain ultrasound waveform tomography is a promising method for the visualization and characterization of breast disease. It has previously been shown to accurately reconstruct the sound speed distributions of breasts of varying densities. The reconstructed images show detailed morphological and quantitative information that can help differentiate different types of breast disease including benign and malignant lesions. The attenuation properties of an ex vivo phantom have also been assessed. However, the reconstruction algorithms assumed a 2D geometry while the actual data acquisition process was not. Although clinically useful sound speed images can be reconstructed assuming this mismatched geometry, artifacts from the reconstruction process exist within the reconstructed images. This is especially true for registration across different modalities and when the 2D assumption is violated. For example, this happens when a patient's breast is rapidly sloping. It is also true for attenuation imaging where energy lost or gained out of the plane gets transformed into artifacts within the image space. In this paper, we will briefly review ultrasound waveform tomography techniques, give motivation for pursuing the 3D method, discuss the 3D reconstruction algorithm, present the results of 3D forward modeling, show the mismatch that is induced by the violation of 3D modeling via numerical simulations, and present a 3D inversion of a numerical phantom.

Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drukker, Karen, E-mail: kdrukker@uchicago.edu; Giger, Maryellen L.; Li, Hui

2014-03-15

Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CBmore » alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference in AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.« less

ImageParser: a tool for finite element generation from three-dimensional medical images

PubMed Central

Yin, HM; Sun, LZ; Wang, G; Yamada, T; Wang, J; Vannier, MW

2004-01-01

Background The finite element method (FEM) is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures) of interest (ROIs) may be irregular and fuzzy. Methods A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements. Results The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues. Conclusion The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information. PMID:15461787

MO-FG-209-05: Towards a Feature-Based Anthropomorphic Model Observer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Avanaki, A.

2016-06-15

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, andmore » radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; Summarize the state of the science in optimized integration of modules in the simulated imaging chain; Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graff, C.

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, andmore » radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; Summarize the state of the science in optimized integration of modules in the simulated imaging chain; Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants.« less

One step linear reconstruction method for continuous wave diffuse optical tomography

NASA Astrophysics Data System (ADS)

Ukhrowiyah, N.; Yasin, M.

2017-09-01

The method one step linear reconstruction method for continuous wave diffuse optical tomography is proposed and demonstrated for polyvinyl chloride based material and breast phantom. Approximation which used in this method is selecting regulation coefficient and evaluating the difference between two states that corresponding to the data acquired without and with a change in optical properties. This method is used to recovery of optical parameters from measured boundary data of light propagation in the object. The research is demonstrated by simulation and experimental data. Numerical object is used to produce simulation data. Chloride based material and breast phantom sample is used to produce experimental data. Comparisons of results between experiment and simulation data are conducted to validate the proposed method. The results of the reconstruction image which is produced by the one step linear reconstruction method show that the image reconstruction almost same as the original object. This approach provides a means of imaging that is sensitive to changes in optical properties, which may be particularly useful for functional imaging used continuous wave diffuse optical tomography of early diagnosis of breast cancer.

The Fast Spiral-SelMQC Technique for In Vivo MR Spectroscopic Imaging of Polyunsaturated Fatty Acids (PUFA) in Human Breast Tissue‡

PubMed Central

Zhu, He; Rubin, Denis; He, Qiuhong

2011-01-01

The Selective Multiple-Quantum Coherence Transfer (Sel-MQC) method has been applied to image polyunsaturated fatty acids (PUFA) distributions in human breast tissues in vivo for cancer detection, with complete suppression of the unwanted lipid and water signals in a single scan. The Cartesian k-space mapping of PUFA in vivo using the Sel-MQC CSI technique, however, requires excessive MR scan time. In this article, we report a fast Spiral-SelMQC sequence employing a rapid spiral k-space sampling scheme. The Spiral-SelMQC images of PUFA distribution in human breast were acquired using two-interleaved spirals on a 3T GE Signa MRI scanner. Approximately 160-fold reduction of acquisition time was observed as compared to the corresponding Sel-MQC CSI method with an equivalent number of scans, permitting acquisition of high-resolution PUFA images in minutes. The reconstructed Spiral-SelMQC PUFA images of human breast tissues achieved a sub-millimeter resolution of 0.54×0.54 or 0.63×0.63mm2/pixel for FOV = 14 or 16cm, respectively. The Spiral-SelMQC parameters for PUFA detection were optimized in 2D Sel-MQC experiments to suppress monounsaturated fatty acids (MUFA) and other lipid signals. The fast in vivo Spiral-SelMQC imaging method will be applied to study human breast cancer and other human diseases in extracranial organs. PMID:22028250

Segmenting breast cancerous regions in thermal images using fuzzy active contours

PubMed Central

Ghayoumi Zadeh, Hossein; Haddadnia, Javad; Rahmani Seryasat, Omid; Mostafavi Isfahani, Sayed Mohammad

2016-01-01

Breast cancer is the main cause of death among young women in developing countries. The human body temperature carries critical medical information related to the overall body status. Abnormal rise in total and regional body temperature is a natural symptom in diagnosing many diseases. Thermal imaging (Thermography) utilizes infrared beams which are fast, non-invasive, and non-contact and the output created images by this technique are flexible and useful to monitor the temperature of the human body. In some clinical studies and biopsy tests, it is necessary for the clinician to know the extent of the cancerous area. In such cases, the thermal image is very useful. In the same line, to detect the cancerous tissue core, thermal imaging is beneficial. This paper presents a fully automated approach to detect the thermal edge and core of the cancerous area in thermography images. In order to evaluate the proposed method, 60 patients with an average age of 44/9 were chosen. These cases were suspected of breast tissue disease. These patients referred to Tehran Imam Khomeini Imaging Center. Clinical examinations such as ultrasound, biopsy, questionnaire, and eventually thermography were done precisely on these individuals. Finally, the proposed model is applied for segmenting the proved abnormal area in thermal images. The proposed model is based on a fuzzy active contour designed by fuzzy logic. The presented method can segment cancerous tissue areas from its borders in thermal images of the breast area. In order to evaluate the proposed algorithm, Hausdorff and mean distance between manual and automatic method were used. Estimation of distance was conducted to accurately separate the thermal core and edge. Hausdorff distance between the proposed and the manual method for thermal core and edge was 0.4719 ± 0.4389, 0.3171 ± 0.1056 mm respectively, and the average distance between the proposed and the manual method for core and thermal edge was 0.0845 ± 0.0619, 0.0710 ± 0.0381 mm respectively. Furthermore, the sensitivity in recognizing the thermal pattern in breast tissue masses is 85 % and its accuracy is 91.98 %.A thermal imaging system has been proposed that is able to recognize abnormal breast tissue masses. This system utilizes fuzzy active contours to extract the abnormal regions automatically. PMID:28096784

Breast imaging using the Twente photoacoustic mammoscope (PAM): new clinical measurements

NASA Astrophysics Data System (ADS)

Heijblom, Michelle; Piras, Daniele; Ten Tije, Ellen; Xia, Wenfeng; van Hespen, Johan; Klaase, Joost; van den Engh, Frank; van Leeuwen, Ton; Steenbergen, Wiendelt; Manohar, Srirang

2011-07-01

Worldwide, yearly about 450,000 women die from the consequences of breast cancer. Current imaging modalities are not optimal in discriminating benign from malignant tissue. Visualizing the malignancy-associated increased hemoglobin concentration might significantly improve early diagnosis of breast cancer. Since photoacoustic imaging can visualize hemoglobin in tissue with optical contrast and ultrasound-like resolution, it is potentially an ideal method for early breast cancer imaging. The Twente Photoacoustic Mammoscope (PAM) has been developed specifically for breast imaging. Recently, a large clinical study has been started in the Medisch Spectrum Twente in Oldenzaal using PAM. In PAM, the breast is slightly compressed between a window for laser light illumination and a flat array ultrasound detector. The measurements are performed using a Q-switched Nd:YAG laser, pulsed at 1064 nm and a 1 MHz unfocused ultrasound detector array. Three-dimensional data are reconstructed using a delay and sum reconstruction algorithm. Those reconstructed images are compared with conventional imaging and histopathology. In the first phase of the study 12 patients with a malignant lesion and 2 patients with a benign cyst have been measured. The results are used to guide developments in photoacoustic mammography in order to pave the way towards an optimal technique for early diagnosis of breast cancer.

Assessing the future of diffuse optical imaging technologies for breast cancer management

PubMed Central

Tromberg, Bruce J.; Pogue, Brian W.; Paulsen, Keith D.; Yodh, Arjun G.; Boas, David A.; Cerussi, Albert E.

2008-01-01

Diffuse optical imaging (DOI) is a noninvasive optical technique that employs near-infrared (NIR) light to quantitatively characterize the optical properties of thick tissues. Although NIR methods were first applied to breast transillumination (also called diaphanography) nearly 80 years ago, quantitative DOI methods employing time- or frequency-domain photon migration technologies have only recently been used for breast imaging (i.e., since the mid-1990s). In this review, the state of the art in DOI for breast cancer is outlined and a multi-institutional Network for Translational Research in Optical Imaging (NTROI) is described, which has been formed by the National Cancer Institute to advance diffuse optical spectroscopy and imaging (DOSI) for the purpose of improving breast cancer detection and clinical management. DOSI employs broadband technology both in near-infrared spectral and temporal signal domains in order to separate absorption from scattering and quantify uptake of multiple molecular probes based on absorption or fluorescence contrast. Additional dimensionality in the data is provided by integrating and co-registering the functional information of DOSI with x-ray mammography and magnetic resonance imaging (MRI), which provide structural information or vascular flow information, respectively. Factors affecting DOSI performance, such as intrinsic and extrinsic contrast mechanisms, quantitation of biochemical components, image formation∕visualization, and multimodality co-registration are under investigation in the ongoing research NTROI sites. One of the goals is to develop standardized DOSI platforms that can be used as stand-alone devices or in conjunction with MRI, mammography, or ultrasound. This broad-based, multidisciplinary effort is expected to provide new insight regarding the origins of breast disease and practical approaches for addressing several key challenges in breast cancer, including: Detecting disease in mammographically dense tissue, distinguishing between malignant and benign lesions, and understanding the impact of neoadjuvant chemotherapies. PMID:18649477

Enhancing breast projection in autologous reconstruction using the St Andrew’s coning technique and 3D volumetric analysis

PubMed Central

Chae, Michael P.; Patel, Nakul Gamanlal; Hunter-Smith, David J.; Ramakrishnan, Venkat

2017-01-01

Background An increasing number of women undergo mastectomy for breast cancer and post-mastectomy autologous breast reconstruction has been shown to significantly improve the psychosexual wellbeing of the patients. A goal of treatment is to achieve symmetry and projection to match the native breast, and/or the contralateral breast in the case of a unilateral reconstruction. Autologous reconstruction, particularly with the deep inferior epigastric artery perforator (DIEP) flap, is particularly advantageous as it can be manipulated to mimic the shape and turgor of the native breast. However, very few techniques of shaping the breast conus when insetting the DIEP flap to enhance aesthetic outcome have been reported to date. With the aide of three-dimension (3D) photography and 3D-printed mirrored image of the contralateral breast as a guide intraoperatively, we describe our St Andrew’s coning technique to create a personalized flap projection. Method We report a prospective case series of 3 delayed unilateral breast reconstructions where symmetrization procedure to the contralateral breast was not indicated. Using a commercial 3D scanner (VECTRA XR, Canfield Scientific), the breast region was imaged. The mirrored image was 3D-printed in-house using a desktop 3D printer. Results In all cases, projection of the breast mound was able to be safely achieved, with a demonstrated central volume (or ‘cone’) able to be highlighted on imaging and a 3D printed breast. A 3D print of the contralateral breast was able to be used intraoperatively to guide the operative approach. Conclusions The St Andrew’s coning technique is a useful aesthetic maneuver for achieving breast projection during DIEP flap breast reconstruction, with 3D imaging techniques able to assist in perioperative assessment of breast volume. PMID:29302489

SU-F-I-14: 3D Breast Digital Phantom for XACT Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, S; Laaroussi, R; Chen, J

Purpose: The X-ray induced acoustic computed tomography (XACT) is a new imaging modality which combines X-ray contrast and high ultrasonic resolution in a single modality. Using XACT in breast imaging, a 3D breast volume can be imaged by only one pulsed X-ray radiation, which could dramatically reduce the imaging dose for patients undergoing breast cancer screening and diagnosis. A 3D digital phantom that contains both X-ray properties and acoustic properties of different tissue types is indeed needed for developing and optimizing the XACT system. The purpose of this study is to offer a realistic breast digital phantom as a valuablemore » tool for improving breast XACT imaging techniques and potentially leading to better diagnostic outcomes. Methods: A series of breast CT images along the coronal plane from a patient who has breast calcifications are used as the source images. A HU value based segmentation algorithm is employed to identify breast tissues in five categories, namely the skin tissue, fat tissue, glandular tissue, chest bone and calcifications. For each pixel, the dose related parameters, such as material components and density, and acoustic related parameters, such as frequency-dependent acoustic attenuation coefficient and bandwidth, are assigned based on tissue types. Meanwhile, other parameters which are used in sound propagation, including the sound speed, thermal expansion coefficient, and heat capacity are also assigned to each tissue. Results: A series of 2D tissue type image is acquired first and the 3D digital breast phantom is obtained by using commercial 3D reconstruction software. When giving specific settings including dose depositions and ultrasound center frequency, the X-ray induced initial pressure rise can be calculated accordingly. Conclusion: The proposed 3D breast digital phantom represents a realistic breast anatomic structure and provides a valuable tool for developing and evaluating the system performance for XACT.« less

A Global Covariance Descriptor for Nuclear Atypia Scoring in Breast Histopathology Images.

PubMed

Khan, Adnan Mujahid; Sirinukunwattana, Korsuk; Rajpoot, Nasir

2015-09-01

Nuclear atypia scoring is a diagnostic measure commonly used to assess tumor grade of various cancers, including breast cancer. It provides a quantitative measure of deviation in visual appearance of cell nuclei from those in normal epithelial cells. In this paper, we present a novel image-level descriptor for nuclear atypia scoring in breast cancer histopathology images. The method is based on the region covariance descriptor that has recently become a popular method in various computer vision applications. The descriptor in its original form is not suitable for classification of histopathology images as cancerous histopathology images tend to possess diversely heterogeneous regions in a single field of view. Our proposed image-level descriptor, which we term as the geodesic mean of region covariance descriptors, possesses all the attractive properties of covariance descriptors lending itself to tractable geodesic-distance-based k-nearest neighbor classification using efficient kernels. The experimental results suggest that the proposed image descriptor yields high classification accuracy compared to a variety of widely used image-level descriptors.

Breast mass detection in mammography and tomosynthesis via fully convolutional network-based heatmap regression

NASA Astrophysics Data System (ADS)

Zhang, Jun; Cain, Elizabeth Hope; Saha, Ashirbani; Zhu, Zhe; Mazurowski, Maciej A.

2018-02-01

Breast mass detection in mammography and digital breast tomosynthesis (DBT) is an essential step in computerized breast cancer analysis. Deep learning-based methods incorporate feature extraction and model learning into a unified framework and have achieved impressive performance in various medical applications (e.g., disease diagnosis, tumor detection, and landmark detection). However, these methods require large-scale accurately annotated data. Unfortunately, it is challenging to get precise annotations of breast masses. To address this issue, we propose a fully convolutional network (FCN) based heatmap regression method for breast mass detection, using only weakly annotated mass regions in mammography images. Specifically, we first generate heat maps of masses based on human-annotated rough regions for breast masses. We then develop an FCN model for end-to-end heatmap regression with an F-score loss function, where the mammography images are regarded as the input and heatmaps for breast masses are used as the output. Finally, the probability map of mass locations can be estimated with the trained model. Experimental results on a mammography dataset with 439 subjects demonstrate the effectiveness of our method. Furthermore, we evaluate whether we can use mammography data to improve detection models for DBT, since mammography shares similar structure with tomosynthesis. We propose a transfer learning strategy by fine-tuning the learned FCN model from mammography images. We test this approach on a small tomosynthesis dataset with only 40 subjects, and we show an improvement in the detection performance as compared to training the model from scratch.

Chest wall segmentation in automated 3D breast ultrasound scans.

PubMed

Tan, Tao; Platel, Bram; Mann, Ritse M; Huisman, Henkjan; Karssemeijer, Nico

2013-12-01

In this paper, we present an automatic method to segment the chest wall in automated 3D breast ultrasound images. Determining the location of the chest wall in automated 3D breast ultrasound images is necessary in computer-aided detection systems to remove automatically detected cancer candidates beyond the chest wall and it can be of great help for inter- and intra-modal image registration. We show that the visible part of the chest wall in an automated 3D breast ultrasound image can be accurately modeled by a cylinder. We fit the surface of our cylinder model to a set of automatically detected rib-surface points. The detection of the rib-surface points is done by a classifier using features representing local image intensity patterns and presence of rib shadows. Due to attenuation of the ultrasound signal, a clear shadow is visible behind the ribs. Evaluation of our segmentation method is done by computing the distance of manually annotated rib points to the surface of the automatically detected chest wall. We examined the performance on images obtained with the two most common 3D breast ultrasound devices in the market. In a dataset of 142 images, the average mean distance of the annotated points to the segmented chest wall was 5.59 ± 3.08 mm. Copyright © 2012 Elsevier B.V. All rights reserved.

NearSense - Advances Towards a Silicon-Based Terahertz Near-Field Imaging Sensor for Ex Vivo Breast Tumour Identification

NASA Astrophysics Data System (ADS)

Mavarani, Laven; Hillger, Philipp; Bücher, Thomas; Grzyb, Janusz; Pfeiffer, Ullrich R.; Cassar, Quentin; Al-Ibadi, Amel; Zimmer, Thomas; Guillet, Jean-Paul; Mounaix, Patrick; MacGrogan, Gaëtan

2018-03-01

Breast Cancer is one of the most frequently diagnosed cancer diseases worldwide, and the most common invasive tumour for women. As with all cancers, early detection plays a major role in reducing the mortality and morbidity rate. Currently, most breast cancers are detected due to clinical symptoms, or by screening mammography. The limitations of these techniques have resulted in research of alternative methods for imaging and detecting breast cancer. Apart from this, it is essential to define precise tumour margins during breast-conserving surgeries to reduce the re-excision rate. This study presents the advances in the development of a silicon-based THz sub-wavelength imager usable in life science applications, especially for tumour margin identification.

Evaluation of a novel collimator for molecular breast tomosynthesis.

PubMed

Gilland, David R; Welch, Benjamin L; Lee, Seungjoon; Kross, Brian; Weisenberger, Andrew G

2017-11-01

This study investigated a novel gamma camera for molecular breast tomosynthesis (MBT), which is a nuclear breast imaging method that uses limited angle tomography. The camera is equipped with a variable angle, slant-hole (VASH) collimator that allows the camera to remain close to the breast throughout the acquisition. The goal of this study was to evaluate the spatial resolution and count sensitivity of this camera and to compare contrast and contrast-to-noise ratio (CNR) with conventional planar imaging using an experimental breast phantom. The VASH collimator mounts to a commercial gamma camera for breast imaging that uses a pixelated (3.2 mm), 15 × 20 cm NaI crystal. Spatial resolution was measured in planar images over a range of distances from the collimator (30-100 mm) and a range of slant angles (-25° to 25°) using 99m Tc line sources. Spatial resolution was also measured in reconstructed MBT images including in the depth dimension. The images were reconstructed from data acquired over the -25° to 25° angular range using an iterative algorithm adapted to the slant-hole geometry. Sensitivity was measured over the range of slant angles using a disk source. Measured spatial resolution and sensitivity were compared to theoretical values. Contrast and CNR were measured using a breast phantom containing spherical lesions (6.2 mm and 7.8 mm diameter) and positioned over a range of depths in the phantom. The MBT and planar methods had equal scan time, and the count density in the breast phantom data was similar to that in clinical nuclear breast imaging. The MBT method used an iterative reconstruction algorithm combined with a postreconstruction Metz filter. The measured spatial resolution in planar images agreed well with theoretical calculations over the range of distances and slant angles. The measured FWHM was 9.7 mm at 50 mm distance. In reconstructed MBT images, the spatial resolution in the depth dimension was approximately 2.2 mm greater than the other two dimensions due to the limited angle data. The measured count sensitivity agreed closely with theory over all slant angles when using a wide energy window. At 0° slant angle, measured sensitivity was 19.7 counts sec -1 μCi -1 with the open energy window and 11.2 counts sec -1 μCi -1 with a 20% wide photopeak window (126 to 154 keV). The measured CNR in the MBT images was significantly greater than in the planar images for all but the lowest CNR cases where the lesion detectability was extremely low for both MBT and planar. The 7.8 mm lesion at 37 mm depth was marginally detectable in the planar image but easily visible in the MBT image. The improved CNR with MBT was due to a large improvement in contrast, which out-weighed the increase in image noise. The spatial resolution and count sensitivity measurements with the prototype MBT system matched theoretical calculations, and the measured CNR in breast phantom images was generally greater with the MBT system compared to conventional planar imaging. These results demonstrate the potential of the proposed MBT system to improve lesion detection in nuclear breast imaging. © 2017 American Association of Physicists in Medicine.

Angiogenesis - a crucial step in breast cancer growth, progression and dissemination by Raman imaging

NASA Astrophysics Data System (ADS)

Kopeć, Monika; Abramczyk, Halina

2018-06-01

Combined micro-Raman imaging and AFM imaging are efficient methods for analyzing human tissue due to their high spatial and spectral resolution as well as sensitivity to subtle chemical, structural and topographical changes. The aim of this study was to determine biochemical composition and mechanical topography around blood vessels in the tumor mass of human breast tissue. Significant alterations of the chemical composition and structural architecture around the blood vessel were found compared to the normal breast tissue. A pronounced increase of collagen-fibroblast-glycocalyx network, as well as enhanced lactic acid, and glycogen activity in patients affected by breast cancer were reported.

Anti-epidermal growth factor receptor (anti-EGFR) antibody conjugated fluorescent nanoparticles probe for breast cancer imaging

NASA Astrophysics Data System (ADS)

Hun, Xu; Zhang, Zhujun

2009-10-01

Fluorescent nanoparticles (FNs) with unique optical properties may be useful as biosensors in living cancer cell imaging and cancer targeting. In this study, anti-EGFR antibody conjugated fluorescent nanoparticles (FNs) (anti-EGFR antibody conjugated FNs) probe was used to detect breast cancer cells. FNs with excellent character such as non-toxicity and photostability were first synthesized with a simple, cost-effective and environmentally friendly modified Stőber synthesis method, and then successfully modified with anti-EGFR antibody. This kind of fluorescence probe based on the anti-EGFR antibody conjugated FNs has been used to detect breast cancer cells with fluorescence microscopy imaging technology. The experimental results demonstrate that the anti-EGFR antibody conjugated FNs can effectively recognize breast cancer cells and exhibited good sensitivity and exceptional photostability, which would provide a novel way for the diagnosis and curative effect observation of breast cancer cells and offer a new method in detecting EGFR.

Adherence to Guidelines for Breast Surveillance in Breast Cancer Survivors.

PubMed

Ruddy, Kathryn J; Sangaralingham, Lindsey; Freedman, Rachel A; Mougalian, Sarah; Neuman, Heather; Greenberg, Caprice; Jemal, Ahmedin; Duma, Narjust; Haddad, Tufia C; Lemaine, Valerie; Ghosh, Karthik; Hieken, Tina J; Hunt, Katie; Vachon, Celine; Gross, Cary; Shah, Nilay D

2018-05-01

Background: Guidelines recommend annual mammography after curative-intent treatment for breast cancer. The goal of this study was to assess contemporary patterns of breast imaging after breast cancer treatment. Methods: Administrative claims data were used to identify privately insured and Medicare Advantage beneficiaries with nonmetastatic breast cancer who had residual breast tissue (not bilateral mastectomy) after breast surgery between January 2005 and May 2015. We calculated the proportion of patients who had a mammogram, MRI, both, or neither during each of 5 subsequent 13-month periods. Multinomial logistic regression was used to assess associations between patient characteristics, healthcare use, and breast imaging in the first and fifth years after surgery. Results: A total of 27,212 patients were followed for a median of 2.9 years (interquartile range, 1.8-4.6) after definitive breast cancer surgery. In year 1, 78% were screened using mammography alone, 1% using MRI alone, and 8% using both tests; 13% did not undergo either. By year 5, the proportion of the remaining cohort (n=4,790) who had no breast imaging was 19%. Older age was associated with an increased likelihood of mammography and a decreased likelihood of MRI during the first and fifth years. Black race, mastectomy, chemotherapy, and no MRI at baseline were all associated with a decreased likelihood of both types of imaging. Conclusions: Even in an insured cohort, a substantial proportion of breast cancer survivors do not undergo annual surveillance breast imaging, particularly as time passes. Understanding factors associated with imaging in cancer survivors may help improve adherence to survivorship care guidelines. Copyright © 2018 by the National Comprehensive Cancer Network.

Investigation of statistical iterative reconstruction for dedicated breast CT

PubMed Central

Makeev, Andrey; Glick, Stephen J.

2013-01-01

Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images were compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue. Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters. Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved performance (by a factor of greater than 10) compared to FBP. The hyperbolic prior was also observed to be superior to the TV norm. A few of the best-performing parameter pairs for the PML method also demonstrated superior performance for various radiation doses. In fact, using PML with certain parameter values results in better images, acquired using 2 mGy dose, than FBP-reconstructed images acquired using 6 mGy dose. Conclusions: A range of optimal free parameters for the PML algorithm with hyperbolic and TV norm-based potentials is presented for the microcalcification detection task, in dedicated breast CT. The reported values can be used as starting values of the free parameters, when SIR techniques are used for image reconstruction. Significant improvement in image quality can be achieved by using PML with optimal combination of parameters, as compared to FBP. Importantly, these results suggest improved detection of microcalcifications can be obtained by using PML with lower radiation dose to the patient, than using FBP with higher dose. PMID:23927318

Assessment of female breast dose for thoracic cone-beam CT using MOSFET dosimeters

PubMed Central

Qiu, Bo; Liang, Jian; Xie, Weihao; Deng, Xiaowu; Qi, Zhenyu

2017-01-01

Objective: To assess the breast dose during a routine thoracic cone-beam CT (CBCT) check with the efforts to explore the possible dose reduction strategy. Materials and Methods: Metal oxide semiconductor field-effect transistor (MOSFET) dosimeters were used to measure breast surface doses during a thorax kV CBCT scan in an anthropomorphic phantom. Breast doses for different scanning protocols and breast sizes were compared. Dose reduction was attempted by using partial arc CBCT scan with bowtie filter. The impact of this dose reduction strategy on image registration accuracy was investigated. Results: The average breast surface doses were 20.02 mGy and 11.65 mGy for thoracic CBCT without filtration and with filtration, respectively. This indicates a dose reduction of 41.8% by use of bowtie filter. It was found 220° partial arc scanning significantly reduced the dose to contralateral breast (44.4% lower than ipsilateral breast), while the image registration accuracy was not compromised. Conclusions: Breast dose reduction can be achieved by using ipsilateral 220° partial arc scan with bowtie filter. This strategy also provides sufficient image quality for thorax image registration in daily patient positioning verification. PMID:28423624

Radionuclide Methods and Instrumentation for Breast Cancer Detection and Diagnosis

PubMed Central

Surti, Suleman

2013-01-01

Breast cancer mammography is a well-acknowledged technique for patient screening due to its high sensitivity. However, in addition to its low specificity the sensitivity of mammography is limited when imaging patients with dense breasts. Radionuclide imaging techniques, such as coincidence photon-based positron emission tomography and single photon emission computed tomography or scintimammography, can play a role in assisting screening of such patients. Radionuclide techniques can also be useful in assessing treatment response of patients with breast cancer to therapy, and staging of patients to diagnose the disease extent. However, the performance of these imaging modalities is generally limited because of the poor spatial resolution and sensitivity of the commercially available multipurpose imaging systems. Here, we describe some of the dedicated imaging systems (positron emission mammography [PEM] and breast-specific gamma imaging [BSGI]) that have been developed both commercially and in research laboratories for radionuclide imaging of breast cancer. Clinical studies with dedicated PEM scanners show improved sensitivity to detecting cancer in patients when using PEM in conjunction with additional imaging modalities, such as magnetic resonance imaging or mammography or both, as well as improved disease staging that can have an effect on surgical planning. High-resolution BSGI systems are more widely available commercially and several clinical studies have shown very high sensitivity and specificity in detecting cancer in high-risk patients. Further development of dedicated PEM and BSGI systems is ongoing, promising further expansion of radionuclide imaging techniques in the realm of breast cancer detection and treatment. PMID:23725989

Regularized Reconstruction of Dynamic Contrast-Enhanced MR Images for Evaluation of Breast Lesions

DTIC Science & Technology

2011-01-01

Magnetic resonance imaging contrast-enhanced relaxometry of breast tumors: an MRI multicenter investigation concerning 100 patients,” Mag. Res. Im., vol...The overall goal of this project was to develop, implement, and evaluate methods for im- proving image quality in dynamic magnetic resonance imaging ...Olafsson, H. R. Shi, and D. C. Noll, “Toeplitz-based iterative image reconstruction for MRI with correction for magnetic field inhomogeneity,” IEEE

Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors: Automated measurement development for full field digital mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fowler, E. E.; Sellers, T. A.; Lu, B.

Purpose: The Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors are used for standardized mammographic reporting and are assessed visually. This reporting is clinically relevant because breast composition can impact mammographic sensitivity and is a breast cancer risk factor. New techniques are presented and evaluated for generating automated BI-RADS breast composition descriptors using both raw and calibrated full field digital mammography (FFDM) image data.Methods: A matched case-control dataset with FFDM images was used to develop three automated measures for the BI-RADS breast composition descriptors. Histograms of each calibrated mammogram in the percent glandular (pg) representation were processed tomore » create the new BR{sub pg} measure. Two previously validated measures of breast density derived from calibrated and raw mammograms were converted to the new BR{sub vc} and BR{sub vr} measures, respectively. These three measures were compared with the radiologist-reported BI-RADS compositions assessments from the patient records. The authors used two optimization strategies with differential evolution to create these measures: method-1 used breast cancer status; and method-2 matched the reported BI-RADS descriptors. Weighted kappa (κ) analysis was used to assess the agreement between the new measures and the reported measures. Each measure's association with breast cancer was evaluated with odds ratios (ORs) adjusted for body mass index, breast area, and menopausal status. ORs were estimated as per unit increase with 95% confidence intervals.Results: The three BI-RADS measures generated by method-1 had κ between 0.25–0.34. These measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.87 (1.34, 2.59) for BR{sub pg}; (b) OR = 1.93 (1.36, 2.74) for BR{sub vc}; and (c) OR = 1.37 (1.05, 1.80) for BR{sub vr}. The measures generated by method-2 had κ between 0.42–0.45. Two of these measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.95 (1.24, 3.09) for BR{sub pg}; (b) OR = 1.42 (0.87, 2.32) for BR{sub vc}; and (c) OR = 2.13 (1.22, 3.72) for BR{sub vr}. The radiologist-reported measures from the patient records showed a similar association, OR = 1.49 (0.99, 2.24), although only borderline statistically significant.Conclusions: A general framework was developed and validated for converting calibrated mammograms and continuous measures of breast density to fully automated approximations for the BI-RADS breast composition descriptors. The techniques are general and suitable for a broad range of clinical and research applications.« less

A post-reconstruction method to correct cupping artifacts in cone beam breast computed tomography

PubMed Central

Altunbas, M. C.; Shaw, C. C.; Chen, L.; Lai, C.; Liu, X.; Han, T.; Wang, T.

2007-01-01

In cone beam breast computed tomography (CT), scattered radiation leads to nonuniform biasing of CT numbers known as a cupping artifact. Besides being visual distractions, cupping artifacts appear as background nonuniformities, which impair efficient gray scale windowing and pose a problem in threshold based volume visualization/segmentation. To overcome this problem, we have developed a background nonuniformity correction method specifically designed for cone beam breast CT. With this technique, the cupping artifact is modeled as an additive background signal profile in the reconstructed breast images. Due to the largely circularly symmetric shape of a typical breast, the additive background signal profile was also assumed to be circularly symmetric. The radial variation of the background signals were estimated by measuring the spatial variation of adipose tissue signals in front view breast images. To extract adipose tissue signals in an automated manner, a signal sampling scheme in polar coordinates and a background trend fitting algorithm were implemented. The background fits compared with targeted adipose tissue signal value (constant throughout the breast volume) to get an additive correction value for each tissue voxel. To test the accuracy, we applied the technique to cone beam CT images of mastectomy specimens. After correction, the images demonstrated significantly improved signal uniformity in both front and side view slices. The reduction of both intra-slice and inter-slice variations in adipose tissue CT numbers supported our observations. PMID:17822018

Quantitative breast MRI radiomics for cancer risk assessment and the monitoring of high-risk populations

NASA Astrophysics Data System (ADS)

Mendel, Kayla R.; Li, Hui; Giger, Maryellen L.

2016-03-01

Breast density is routinely assessed qualitatively in screening mammography. However, it is challenging to quantitatively determine a 3D density from a 2D image such as a mammogram. Furthermore, dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used more frequently in the screening of high-risk populations. The purpose of our study is to segment parenchyma and to quantitatively determine volumetric breast density on pre-contrast axial DCE-MRI images (i.e., non-contrast) using a semi-automated quantitative approach. In this study, we retroactively examined 3D DCE-MRI images taken for breast cancer screening of a high-risk population. We analyzed 66 cases with ages between 28 and 76 (mean 48.8, standard deviation 10.8). DCE-MRIs were obtained on a Philips 3.0 T scanner. Our semi-automated DCE-MRI algorithm includes: (a) segmentation of breast tissue from non-breast tissue using fuzzy cmeans clustering (b) separation of dense and fatty tissues using Otsu's method, and (c) calculation of volumetric density as the ratio of dense voxels to total breast voxels. We examined the relationship between pre-contrast DCE-MRI density and clinical BI-RADS density obtained from radiology reports, and obtained a statistically significant correlation [Spearman ρ-value of 0.66 (p < 0.0001)]. Our method within precision medicine may be useful for monitoring high-risk populations.

Effects of cognitive behavioral counseling on body Image following mastectomy.

PubMed

Fadaei, Simin; Janighorban, Mojgan; Mehrabi, Tayebe; Ahmadi, Sayed Ahmadi; Mokaryan, Fariborz; Gukizade, Abbas

2011-08-01

Breast cancer is the most common cancer in women. Surgical treatment of breast cancer may cause body image alterations. The purpose of the current study was to examine the effects of cognitive behavioral counseling on body image among Iranian women with primary breast cancer. In this quasi-experimental designed study, 72 patients diagnosed as breast cancer and surgically treated were enrolled in Isfahan, Iran. The patients were entered the study by convenience sampling method and were randomly divided in two groups of intervention (n = 32) and control (n = 40). The intervention group received consultation based on Ellis rational emotive behavior therapy (REBT) method for 6 sessions during 3 weeks. The control group did not receive any consultation Paired t-test was used to compare the changes in groups and independent t-test was conducted to compare two groups. The average values represented as mean ± standard deviation. Before the study, the body image score was not significantly different between the intervention (16 97 ± 5 44) and control (15 95 ± 4 66) groups (t = 0 86, P = 0 395). The body image score was significantly lower in the interven-tion group (9 03 ± 6 11) compared to control group (17 18 ± 5 27) after the intervention (t = -6 07, P < 0 001). Since a woman's body image influences her breast cancer treatment decision, oncology professionals need to recognize the value of a woman's favorite about appearance and body image. This study emphasizes the importance of offering consultation in breast cancer patients.

Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging.

PubMed

Pertuz, Said; McDonald, Elizabeth S; Weinstein, Susan P; Conant, Emily F; Kontos, Despina

2016-04-01

To assess a fully automated method for volumetric breast density (VBD) estimation in digital breast tomosynthesis (DBT) and to compare the findings with those of full-field digital mammography (FFDM) and magnetic resonance (MR) imaging. Bilateral DBT images, FFDM images, and sagittal breast MR images were retrospectively collected from 68 women who underwent breast cancer screening from October 2011 to September 2012 with institutional review board-approved, HIPAA-compliant protocols. A fully automated computer algorithm was developed for quantitative estimation of VBD from DBT images. FFDM images were processed with U.S. Food and Drug Administration-cleared software, and the MR images were processed with a previously validated automated algorithm to obtain corresponding VBD estimates. Pearson correlation and analysis of variance with Tukey-Kramer post hoc correction were used to compare the multimodality VBD estimates. Estimates of VBD from DBT were significantly correlated with FFDM-based and MR imaging-based estimates with r = 0.83 (95% confidence interval [CI]: 0.74, 0.90) and r = 0.88 (95% CI: 0.82, 0.93), respectively (P < .001). The corresponding correlation between FFDM and MR imaging was r = 0.84 (95% CI: 0.76, 0.90). However, statistically significant differences after post hoc correction (α = 0.05) were found among VBD estimates from FFDM (mean ± standard deviation, 11.1% ± 7.0) relative to MR imaging (16.6% ± 11.2) and DBT (19.8% ± 16.2). Differences between VDB estimates from DBT and MR imaging were not significant (P = .26). Fully automated VBD estimates from DBT, FFDM, and MR imaging are strongly correlated but show statistically significant differences. Therefore, absolute differences in VBD between FFDM, DBT, and MR imaging should be considered in breast cancer risk assessment.

Breast Histopathological Image Retrieval Based on Latent Dirichlet Allocation.

PubMed

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu

2017-07-01

In the field of pathology, whole slide image (WSI) has become the major carrier of visual and diagnostic information. Content-based image retrieval among WSIs can aid the diagnosis of an unknown pathological image by finding its similar regions in WSIs with diagnostic information. However, the huge size and complex content of WSI pose several challenges for retrieval. In this paper, we propose an unsupervised, accurate, and fast retrieval method for a breast histopathological image. Specifically, the method presents a local statistical feature of nuclei for morphology and distribution of nuclei, and employs the Gabor feature to describe the texture information. The latent Dirichlet allocation model is utilized for high-level semantic mining. Locality-sensitive hashing is used to speed up the search. Experiments on a WSI database with more than 8000 images from 15 types of breast histopathology demonstrate that our method achieves about 0.9 retrieval precision as well as promising efficiency. Based on the proposed framework, we are developing a search engine for an online digital slide browsing and retrieval platform, which can be applied in computer-aided diagnosis, pathology education, and WSI archiving and management.

An effective approach of lesion segmentation within the breast ultrasound image based on the cellular automata principle.

PubMed

Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong

2012-10-01

In this paper, a novel lesion segmentation within breast ultrasound (BUS) image based on the cellular automata principle is proposed. Its energy transition function is formulated based on global image information difference and local image information difference using different energy transfer strategies. First, an energy decrease strategy is used for modeling the spatial relation information of pixels. For modeling global image information difference, a seed information comparison function is developed using an energy preserve strategy. Then, a texture information comparison function is proposed for considering local image difference in different regions, which is helpful for handling blurry boundaries. Moreover, two neighborhood systems (von Neumann and Moore neighborhood systems) are integrated as the evolution environment, and a similarity-based criterion is used for suppressing noise and reducing computation complexity. The proposed method was applied to 205 clinical BUS images for studying its characteristic and functionality, and several overlapping area error metrics and statistical evaluation methods are utilized for evaluating its performance. The experimental results demonstrate that the proposed method can handle BUS images with blurry boundaries and low contrast well and can segment breast lesions accurately and effectively.

Robust linearized image reconstruction for multifrequency EIT of the breast.

PubMed

Boverman, Gregory; Kao, Tzu-Jen; Kulkarni, Rujuta; Kim, Bong Seok; Isaacson, David; Saulnier, Gary J; Newell, Jonathan C

2008-10-01

Electrical impedance tomography (EIT) is a developing imaging modality that is beginning to show promise for detecting and characterizing tumors in the breast. At Rensselaer Polytechnic Institute, we have developed a combined EIT-tomosynthesis system that allows for the coregistered and simultaneous analysis of the breast using EIT and X-ray imaging. A significant challenge in EIT is the design of computationally efficient image reconstruction algorithms which are robust to various forms of model mismatch. Specifically, we have implemented a scaling procedure that is robust to the presence of a thin highly-resistive layer of skin at the boundary of the breast and we have developed an algorithm to detect and exclude from the image reconstruction electrodes that are in poor contact with the breast. In our initial clinical studies, it has been difficult to ensure that all electrodes make adequate contact with the breast, and thus procedures for the use of data sets containing poorly contacting electrodes are particularly important. We also present a novel, efficient method to compute the Jacobian matrix for our linearized image reconstruction algorithm by reducing the computation of the sensitivity for each voxel to a quadratic form. Initial clinical results are presented, showing the potential of our algorithms to detect and localize breast tumors.

Breast Cancer Screening, Mammography, and Other Modalities.

PubMed

Fiorica, James V

2016-12-01

This article is an overview of the modalities available for breast cancer screening. The modalities discussed include digital mammography, digital breast tomosynthesis, breast ultrasonography, magnetic resonance imaging, and clinical breast examination. There is a review of pertinent randomized controlled trials, studies and meta-analyses which contributed to the evolution of screening guidelines. Ultimately, 5 major medical organizations formulated the current screening guidelines in the United States. The lack of consensus in these guidelines represents an ongoing controversy about the optimal timing and method for breast cancer screening in women. For mammography screening, the Breast Imaging Reporting and Data System lexicon is explained which corresponds with recommended clinical management. The presentation and discussion of the data in this article are designed to help the clinician individualize breast cancer screening for each patient.

Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drukker, Karen, E-mail: kdrukker@uchicago.edu; Sennett, Charlene A.; Giger, Maryellen L.

2014-01-15

Purpose: Develop a computer-aided detection method and investigate its feasibility for detection of breast cancer in automated 3D ultrasound images of women with dense breasts. Methods: The HIPAA compliant study involved a dataset of volumetric ultrasound image data, “views,” acquired with an automated U-Systems Somo•V{sup ®} ABUS system for 185 asymptomatic women with dense breasts (BI-RADS Composition/Density 3 or 4). For each patient, three whole-breast views (3D image volumes) per breast were acquired. A total of 52 patients had breast cancer (61 cancers), diagnosed through any follow-up at most 365 days after the original screening mammogram. Thirty-one of these patientsmore » (32 cancers) had a screening-mammogram with a clinically assigned BI-RADS Assessment Category 1 or 2, i.e., were mammographically negative. All software used for analysis was developed in-house and involved 3 steps: (1) detection of initial tumor candidates, (2) characterization of candidates, and (3) elimination of false-positive candidates. Performance was assessed by calculating the cancer detection sensitivity as a function of the number of “marks” (detections) per view. Results: At a single mark per view, i.e., six marks per patient, the median detection sensitivity by cancer was 50.0% (16/32) ± 6% for patients with a screening mammogram-assigned BI-RADS category 1 or 2—similar to radiologists’ performance sensitivity (49.9%) for this dataset from a prior reader study—and 45.9% (28/61) ± 4% for all patients. Conclusions: Promising detection sensitivity was obtained for the computer on a 3D ultrasound dataset of women with dense breasts at a rate of false-positive detections that may be acceptable for clinical implementation.« less

3D ultrasound computer tomography: update from a clinical study

NASA Astrophysics Data System (ADS)

Hopp, T.; Zapf, M.; Kretzek, E.; Henrich, J.; Tukalo, A.; Gemmeke, H.; Kaiser, C.; Knaudt, J.; Ruiter, N. V.

2016-04-01

Ultrasound Computer Tomography (USCT) is a promising new imaging method for breast cancer diagnosis. We developed a 3D USCT system and tested it in a pilot study with encouraging results: 3D USCT was able to depict two carcinomas, which were present in contrast enhanced MRI volumes serving as ground truth. To overcome severe differences in the breast shape, an image registration was applied. We analyzed the correlation between average sound speed in the breast and the breast density estimated from segmented MRIs and found a positive correlation with R=0.70. Based on the results of the pilot study we now carry out a successive clinical study with 200 patients. For this we integrated our reconstruction methods and image post-processing into a comprehensive workflow. It includes a dedicated DICOM viewer for interactive assessment of fused USCT images. A new preview mode now allows intuitive and faster patient positioning. We updated the USCT system to decrease the data acquisition time by approximately factor two and to increase the penetration depth of the breast into the USCT aperture by 1 cm. Furthermore the compute-intensive reflectivity reconstruction was considerably accelerated, now allowing a sub-millimeter volume reconstruction in approximately 16 minutes. The updates made it possible to successfully image first patients in our ongoing clinical study.

Setup errors and effectiveness of Optical Laser 3D Surface imaging system (Sentinel) in postoperative radiotherapy of breast cancer.

PubMed

Wei, Xiaobo; Liu, Mengjiao; Ding, Yun; Li, Qilin; Cheng, Changhai; Zong, Xian; Yin, Wenming; Chen, Jie; Gu, Wendong

2018-05-08

Breast-conserving surgery (BCS) plus postoperative radiotherapy has become the standard treatment for early-stage breast cancer. The aim of this study was to compare the setup accuracy of optical surface imaging by the Sentinel system with cone-beam computerized tomography (CBCT) imaging currently used in our clinic for patients received BCS. Two optical surface scans were acquired before and immediately after couch movement correction. The correlation between the setup errors as determined by the initial optical surface scan and CBCT was analyzed. The deviation of the second optical surface scan from the reference planning CT was considered an estimate for the residual errors for the new method for patient setup correction. The consequences in terms for necessary planning target volume (PTV) margins for treatment sessions without setup correction applied. We analyzed 145 scans in 27 patients treated for early stage breast cancer. The setup errors of skin marker based patient alignment by optical surface scan and CBCT were correlated, and the residual setup errors as determined by the optical surface scan after couch movement correction were reduced. Optical surface imaging provides a convenient method for improving the setup accuracy for breast cancer patient without unnecessary imaging dose.

Image guided versus palpation guided core needle biopsy of palpable breast masses: a prospective study

PubMed Central

Hari, Smriti; Kumari, Swati; Srivastava, Anurag; Thulkar, Sanjay; Mathur, Sandeep; Veedu, Prasad Thotton

2016-01-01

Background & objectives: Biopsy of palpable breast masses can be performed manually by palpation guidance or under imaging guidance. Based on retrospective studies, image guided biopsy is considered more accurate than palpation guided breast biopsy; however, these techniques have not been compared prospectively. We conducted this prospective study to verify the superiority and determine the size of beneficial effect of image guided biopsy over palpation guided biopsy. Methods: Over a period of 18 months, 36 patients each with palpable breast masses were randomized into palpation guided and image guided breast biopsy arms. Ultrasound was used for image guidance in 33 patients and mammographic (stereotactic) guidance in three patients. All biopsies were performed using 14 gauge automated core biopsy needles. Inconclusive, suspicious or imaging-histologic discordant biopsies were repeated. Results: Malignancy was found in 30 of 36 women in palpation guided biopsy arm and 27 of 36 women in image guided biopsy arm. Palpation guided biopsy had sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 46.7, 100, 100, 27.3 per cent, respectively, for diagnosing breast cancer. Nineteen of 36 women (52.8%) required repeat biopsy because of inadequate samples (7 of 19), suspicious findings (2 of 19) or imaging-histologic discordance (10 of 19). On repeat biopsy, malignancy was found in all cases of imaging-histologic discordance. Image guided biopsy had 96.3 per cent sensitivity and 100 per cent specificity. There was no case of inadequate sample or imaging-histologic discordance with image guided biopsy. Interpretation & conclusions: Our results showed that in palpable breast masses, image guided biopsy was superior to palpation guided biopsy in terms of sensitivity, false negative rate and repeat biopsy rates. PMID:27488003

Are Qualitative Assessments of Background Parenchymal Enhancement, Amount of Fibroglandular Tissue on MR Images, and Mammographic Density Associated with Breast Cancer Risk?

PubMed Central

Dontchos, Brian N.; Partridge, Savannah C.; Korde, Larissa A.; Lam, Diana L.; Scheel, John R.; Peacock, Sue; Lehman, Constance D.

2015-01-01

Purpose To investigate whether qualitative magnetic resonance (MR) imaging assessments of background parenchymal enhancement (BPE), amount of fibroglandular tissue (FGT), and mammographic density are associated with risk of developing breast cancer in women who are at high risk. Materials and Methods In this institutional review board–approved HIPAA-compliant retrospective study, all screening breast MR images obtained from January 2006 to December 2011 in women aged 18 years or older and at high risk for but without a history of breast cancer were identified. Women in whom breast cancer was diagnosed after index MR imaging comprised the cancer cohort, and one-to-one matching (age and BRCA status) of each woman with breast cancer to a control subject was performed by using MR images obtained in women who did not develop breast cancer with follow-up time maximized. Amount of BPE, BPE pattern (peripheral vs central), amount of FGT at MR imaging, and mammographic density were assessed on index images. Imaging features were compared between cancer and control cohorts by using conditional logistic regression. Results Twenty-three women at high risk (mean age, 47 years ± 10 [standard deviation]; six women had BRCA mutations) with no history of breast cancer underwent screening breast MR imaging; in these women, a diagnosis of breast cancer (invasive, n = 12; in situ, n = 11) was made during the follow-up interval. Women with mild, moderate, or marked BPE were nine times more likely to receive a diagnosis of breast cancer during the follow-up interval than were those with minimal BPE (P = .007; odds ratio = 9.0; 95% confidence interval: 1.1, 71.0). BPE pattern, MR imaging amount of FGT, and mammographic density were not significantly different between the cohorts (P = .5, P = .5, and P = .4, respectively). Conclusion Greater BPE was associated with a higher probability of developing breast cancer in women at high risk for cancer and warrants further study. © RSNA, 2015 Online supplemental material is available for this article. PMID:25965809

Breast boundary detection with active contours

NASA Astrophysics Data System (ADS)

Balic, I.; Goyal, P.; Roy, O.; Duric, N.

2014-03-01

Ultrasound tomography is a modality that can be used to image various characteristics of the breast, such as sound speed, attenuation, and reflectivity. In the considered setup, the breast is immersed in water and scanned along the coronal axis from the chest wall to the nipple region. To improve image visualization, it is desirable to remove the water background. To this end, the 3D boundary of the breast must be accurately estimated. We present an iterative algorithm based on active contours that automatically detects the boundary of a breast using a 3D stack of attenuation images obtained from an ultrasound tomography scanner. We build upon an existing method to design an algorithm that is fast, fully automated, and reliable. We demonstrate the effectiveness of the proposed technique using clinical data sets.

A review of the effectiveness of cognitive-behavioral group therapy on the reduction of body image concern in patients with breast cancer.

PubMed

Faraji, J; Mahdavi, A; Samkhaniyan, E; Asadi, S H; Dezhkam, N

2015-01-01

Objective: Taking the appropriate psychological actions to boost the mental health of patients with breast cancer is critical. This research was performed with the aim of examining the effectiveness of cognitive-behavioral group therapy on reducing body image concerns in patients with breast cancer. Methodology: TThe method used was quasi-experimental with a pretest-posttest plan and control group. Therefore, 40 patients with breast cancer who had referred to the oncology and radiotherapy department of Imam Hossein Hospital of Tehran were selected by convenience sampling method and organized into two groups: experimental and control group. Both groups were pretested by using demographic and body image concern questionnaires. Then the experimental group received cognitive-behavioral group therapy training for eight sessions and the control group did not receive any intervention. Afterwards, both groups were post-tested, and the data were analyzed by using SPSS software with descriptive and inferential statistics methods. Findings: The findings showed that the cognitive-behavioral group therapy training significantly contributed to the reduction of body image concern in patients with cancer (p < 0.001). Conclusions: It was concluded from this research that cognitive-behavioral group therapy training is an effective strategy to help patients with breast cancer who suffer from the concern about body image due to its high efficiency, especially when it was held in groups, it had low cost, and it was acceptable by the patients.

Image quality, threshold contrast and mean glandular dose in CR mammography

NASA Astrophysics Data System (ADS)

Jakubiak, R. R.; Gamba, H. R.; Neves, E. B.; Peixoto, J. E.

2013-09-01

In many countries, computed radiography (CR) systems represent the majority of equipment used in digital mammography. This study presents a method for optimizing image quality and dose in CR mammography of patients with breast thicknesses between 45 and 75 mm. Initially, clinical images of 67 patients (group 1) were analyzed by three experienced radiologists, reporting about anatomical structures, noise and contrast in low and high pixel value areas, and image sharpness and contrast. Exposure parameters (kV, mAs and target/filter combination) used in the examinations of these patients were reproduced to determine the contrast-to-noise ratio (CNR) and mean glandular dose (MGD). The parameters were also used to radiograph a CDMAM (version 3.4) phantom (Artinis Medical Systems, The Netherlands) for image threshold contrast evaluation. After that, different breast thicknesses were simulated with polymethylmethacrylate layers and various sets of exposure parameters were used in order to determine optimal radiographic parameters. For each simulated breast thickness, optimal beam quality was defined as giving a target CNR to reach the threshold contrast of CDMAM images for acceptable MGD. These results were used for adjustments in the automatic exposure control (AEC) by the maintenance team. Using optimized exposure parameters, clinical images of 63 patients (group 2) were evaluated as described above. Threshold contrast, CNR and MGD for such exposure parameters were also determined. Results showed that the proposed optimization method was effective for all breast thicknesses studied in phantoms. The best result was found for breasts of 75 mm. While in group 1 there was no detection of the 0.1 mm critical diameter detail with threshold contrast below 23%, after the optimization, detection occurred in 47.6% of the images. There was also an average MGD reduction of 7.5%. The clinical image quality criteria were attended in 91.7% for all breast thicknesses evaluated in both patient groups. Finally, this study also concluded that the use of the AEC of the x-ray unit based on the constant dose to the detector may bring some difficulties to CR systems to operate under optimal conditions. More studies must be performed, so that the compatibility between systems and optimization methodologies can be evaluated, as well as this optimization method. Most methods are developed for phantoms, so comparative studies including clinical images must be developed.

Angiogenesis - a crucial step in breast cancer growth, progression and dissemination by Raman imaging.

PubMed

Kopeć, Monika; Abramczyk, Halina

2018-06-05

Combined micro-Raman imaging and AFM imaging are efficient methods for analyzing human tissue due to their high spatial and spectral resolution as well as sensitivity to subtle chemical, structural and topographical changes. The aim of this study was to determine biochemical composition and mechanical topography around blood vessels in the tumor mass of human breast tissue. Significant alterations of the chemical composition and structural architecture around the blood vessel were found compared to the normal breast tissue. A pronounced increase of collagen-fibroblast-glycocalyx network, as well as enhanced lactic acid, and glycogen activity in patients affected by breast cancer were reported. Copyright © 2018 Elsevier B.V. All rights reserved.

Force balancing in mammographic compression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Branderhorst, W., E-mail: w.branderhorst@amc.nl; Groot, J. E. de; Lier, M. G. J. T. B. van

Purpose: In mammography, the height of the image receptor is adjusted to the patient before compressing the breast. An inadequate height setting can result in an imbalance between the forces applied by the image receptor and the paddle, causing the clamped breast to be pushed up or down relative to the body during compression. This leads to unnecessary stretching of the skin and other tissues around the breast, which can make the imaging procedure more painful for the patient. The goal of this study was to implement a method to measure and minimize the force imbalance, and to assess itsmore » feasibility as an objective and reproducible method of setting the image receptor height. Methods: A trial was conducted consisting of 13 craniocaudal mammographic compressions on a silicone breast phantom, each with the image receptor positioned at a different height. The image receptor height was varied over a range of 12 cm. In each compression, the force exerted by the compression paddle was increased up to 140 N in steps of 10 N. In addition to the paddle force, the authors measured the force exerted by the image receptor and the reaction force exerted on the patient body by the ground. The trial was repeated 8 times, with the phantom remounted at a slightly different orientation and position between the trials. Results: For a given paddle force, the obtained results showed that there is always exactly one image receptor height that leads to a balance of the forces on the breast. For the breast phantom, deviating from this specific height increased the force imbalance by 9.4 ± 1.9 N/cm (6.7%) for 140 N paddle force, and by 7.1 ± 1.6 N/cm (17.8%) for 40 N paddle force. The results also show that in situations where the force exerted by the image receptor is not measured, the craniocaudal force imbalance can still be determined by positioning the patient on a weighing scale and observing the changes in displayed weight during the procedure. Conclusions: In mammographic breast compression, even small changes in the image receptor height can lead to a severe imbalance of the applied forces. This may make the procedure more painful than necessary and, in case the image receptor is set too low, may lead to image quality issues and increased radiation dose due to undercompression. In practice, these effects can be reduced by monitoring the force imbalance and actively adjusting the position of the image receptor throughout the compression.« less

Neutrosophic segmentation of breast lesions for dedicated breast CT

NASA Astrophysics Data System (ADS)

Lee, Juhun; Nishikawa, Robert M.; Reiser, Ingrid; Boone, John M.

2017-03-01

We proposed the neutrosophic approach for segmenting breast lesions in breast Computer Tomography (bCT) images. The neutrosophic set (NS) considers the nature and properties of neutrality (or indeterminacy), which is neither true nor false. We considered the image noise as an indeterminate component, while treating the breast lesion and other breast areas as true and false components. We first transformed the image into the NS domain. Each voxel in the image can be described as its membership in True, Indeterminate, and False sets. Operations α-mean, β-enhancement, and γ-plateau iteratively smooth and contrast-enhance the image to reduce the noise level of the true set. Once the true image no longer changes, we applied one existing algorithm for bCT images, the RGI segmentation, on the resulting image to segment the breast lesions. We compared the segmentation performance of the proposed method (named as NS-RGI) to that of the regular RGI segmentation. We used a total of 122 breast lesions (44 benign, 78 malignant) of 123 non-contrasted bCT cases. We measured the segmentation performances of the NS-RGI and the RGI using the DICE coefficient. The average DICE value of the NS-RGI was 0.82 (STD: 0.09), while that of the RGI was 0.8 (STD: 0.12). The difference between the two DICE values was statistically significant (paired t test, p-value = 0.0007). We conducted a subsequent feature analysis on the resulting segmentations. The classifier performance for the NS-RGI (AUC = 0.8) improved over that of the RGI (AUC = 0.69, p-value = 0.006).

Alignment of multimodality, 2D and 3D breast images

NASA Astrophysics Data System (ADS)

Grevera, George J.; Udupa, Jayaram K.

2003-05-01

In a larger effort, we are studying methods to improve the specificity of the diagnosis of breast cancer by combining the complementary information available from multiple imaging modalities. Merging information is important for a number of reasons. For example, contrast uptake curves are an indication of malignancy. The determination of anatomical locations in corresponding images from various modalities is necessary to ascertain the extent of regions of tissue. To facilitate this fusion, registration becomes necessary. We describe in this paper a framework in which 2D and 3D breast images from MRI, PET, Ultrasound, and Digital Mammography can be registered to facilitate this goal. Briefly, prior to image acquisition, an alignment grid is drawn on the breast skin. Modality-specific markers are then placed at the indicated grid points. Images are then acquired by a specific modality with the modality specific external markers in place causing the markers to appear in the images. This is the first study that we are aware of that has undertaken the difficult task of registering 2D and 3D images of such a highly deformable (the breast) across such a wide variety of modalities. This paper reports some very preliminary results from this project.

NMR Reconstructive Elasticity Imaging of Breast: Surrogate Remote Palpation Using Quantitative 3-D Displacement

DTIC Science & Technology

1998-09-01

breast tissues may provide unique information which could increase detection and/or characterization of potentially malignant masses not accessible... masses deep in the breast , or within relatively dense, stiff, or heterogeneous tissues, is poor. The principal objective of this project is to develop...or propagating shear wave is documented by imaging devices. In the original MRI method, spatial magnetization tagging was applied, but this had poor

Optimization of propagation-based x-ray phase-contrast tomography for breast cancer imaging

NASA Astrophysics Data System (ADS)

Baran, P.; Pacile, S.; Nesterets, Y. I.; Mayo, S. C.; Dullin, C.; Dreossi, D.; Arfelli, F.; Thompson, D.; Lockie, D.; McCormack, M.; Taba, S. T.; Brun, F.; Pinamonti, M.; Nickson, C.; Hall, C.; Dimmock, M.; Zanconati, F.; Cholewa, M.; Quiney, H.; Brennan, P. C.; Tromba, G.; Gureyev, T. E.

2017-03-01

The aim of this study was to optimise the experimental protocol and data analysis for in-vivo breast cancer x-ray imaging. Results are presented of the experiment at the SYRMEP beamline of Elettra Synchrotron using the propagation-based phase-contrast mammographic tomography method, which incorporates not only absorption, but also x-ray phase information. In this study the images of breast tissue samples, of a size corresponding to a full human breast, with radiologically acceptable x-ray doses were obtained, and the degree of improvement of the image quality (from the diagnostic point of view) achievable using propagation-based phase-contrast image acquisition protocols with proper incorporation of x-ray phase retrieval into the reconstruction pipeline was investigated. Parameters such as the x-ray energy, sample-to-detector distance and data processing methods were tested, evaluated and optimized with respect to the estimated diagnostic value using a mastectomy sample with a malignant lesion. The results of quantitative evaluation of images were obtained by means of radiological assessment carried out by 13 experienced specialists. A comparative analysis was performed between the x-ray and the histological images of the specimen. The results of the analysis indicate that, within the investigated range of parameters, both the objective image quality characteristics and the subjective radiological scores of propagation-based phase-contrast images of breast tissues monotonically increase with the strength of phase contrast which in turn is directly proportional to the product of the radiation wavelength and the sample-to-detector distance. The outcomes of this study serve to define the practical imaging conditions and the CT reconstruction procedures appropriate for low-dose phase-contrast mammographic imaging of live patients at specially designed synchrotron beamlines.

Ratiometric spectral imaging for fast tumor detection and chemotherapy monitoring in vivo

PubMed Central

Hwang, Jae Youn; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

2011-01-01

We report a novel in vivo spectral imaging approach to cancer detection and chemotherapy assessment. We describe and characterize a ratiometric spectral imaging and analysis method and evaluate its performance for tumor detection and delineation by quantitatively monitoring the specific accumulation of targeted gallium corrole (HerGa) into HER2-positive (HER2 +) breast tumors. HerGa temporal accumulation in nude mice bearing HER2 + breast tumors was monitored comparatively by a. this new ratiometric imaging and analysis method; b. established (reflectance and fluorescence) spectral imaging; c. more commonly used fluorescence intensity imaging. We also tested the feasibility of HerGa imaging in vivo using the ratiometric spectral imaging method for tumor detection and delineation. Our results show that the new method not only provides better quantitative information than typical spectral imaging, but also better specificity than standard fluorescence intensity imaging, thus allowing enhanced in vivo outlining of tumors and dynamic, quantitative monitoring of targeted chemotherapy agent accumulation into them. PMID:21721808

Automated 3D Ultrasound Image Segmentation to Aid Breast Cancer Image Interpretation

PubMed Central

Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A.; Yuan, Jie; Wang, Xueding; Carson, Paul L.

2015-01-01

Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer. PMID:26547117

Tight-frame based iterative image reconstruction for spectral breast CT

PubMed Central

Zhao, Bo; Gao, Hao; Ding, Huanjun; Molloi, Sabee

2013-01-01

Purpose: To investigate tight-frame based iterative reconstruction (TFIR) technique for spectral breast computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The experimental data were acquired with a fan-beam breast CT system based on a cadmium zinc telluride photon-counting detector. The images were reconstructed with a varying number of projections using the TFIR and filtered backprojection (FBP) techniques. The image quality between these two techniques was evaluated. The image's spatial resolution was evaluated using a high-resolution phantom, and the contrast to noise ratio (CNR) was evaluated using a postmortem breast sample. The postmortem breast samples were decomposed into water, lipid, and protein contents based on images reconstructed from TFIR with 204 projections and FBP with 614 projections. The volumetric fractions of water, lipid, and protein from the image-based measurements in both TFIR and FBP were compared to the chemical analysis. Results: The spatial resolution and CNR were comparable for the images reconstructed by TFIR with 204 projections and FBP with 614 projections. Both reconstruction techniques provided accurate quantification of water, lipid, and protein composition of the breast tissue when compared with data from the reference standard chemical analysis. Conclusions: Accurate breast tissue decomposition can be done with three fold fewer projection images by the TFIR technique without any reduction in image spatial resolution and CNR. This can result in a two-third reduction of the patient dose in a multislit and multislice spiral CT system in addition to the reduced scanning time in this system. PMID:23464320

Adaptable Near-Infrared Spectroscopy Fiber Array for Improved Coupling to Different Breast Sizes During Clinical MRI

PubMed Central

Mastanduno, Michael A.; El-Ghussein, Fadi; Jiang, Shudong; DiFlorio-Alexander, Roberta; Junqing, Xu; Hong, Yin; Pogue, Brian W.; Paulsen, Keith D.

2016-01-01

Rationale and Objectives Near-infrared spectroscopy (NIRS) of breast can provide functional information on the vascular and structural compartments of tissues in regions identified during simultaneous magnetic resonance imaging (MRI). NIRS can be acquired during dynamic contrast-enhanced MRI (DCE-MRI) to accomplish image-guided spectroscopy of the enhancing regions, potentially increasing the diagnostic specificity of the examination and reducing the number of biopsies performed as a result of inconclusive MRI breast imaging studies. Materials and Methods We combine synergistic attributes of concurrent DCE-MRI and NIRS with a new design of the clinical NIRS breast interface that couples to a standard MR breast coil and allows imaging of variable breast sizes. Spectral information from healthy volunteers and cancer patients is recovered, providing molecular information in regions defined by the segmented MR image volume. Results The new coupling system significantly improves examination utility by allowing improved coupling of the NIR fibers to breasts of all cup sizes and lesion locations. This improvement is demonstrated over a range of breast sizes (cup size A through D) and normal tissue heterogeneity using a group of eight healthy volunteers and two cancer patients. Lesions located in the axillary region and medial-posterior breast are now accessible to NIRS optodes. Reconstructed images were found to have biologically plausible hemoglobin content, oxygen saturation, and water and lipid fractions. Conclusions In summary, a new NIRS/MRI breast interface was developed to accommodate the variation in breast sizes and lesion locations that can be expected in clinical practice. DCE-MRI–guided NIRS quantifies total hemoglobin, oxygenation, and scattering in MR-enhancing regions, increasing the diagnostic information acquired from MR examinations. PMID:24439327

Introducing DeBRa: a detailed breast model for radiological studies

NASA Astrophysics Data System (ADS)

Ma, Andy K. W.; Gunn, Spencer; Darambara, Dimitra G.

2009-07-01

Currently, x-ray mammography is the method of choice in breast cancer screening programmes. As the mammography technology moves from 2D imaging modalities to 3D, conventional computational phantoms do not have sufficient detail to support the studies of these advanced imaging systems. Studies of these 3D imaging systems call for a realistic and sophisticated computational model of the breast. DeBRa (Detailed Breast model for Radiological studies) is the most advanced, detailed, 3D computational model of the breast developed recently for breast imaging studies. A DeBRa phantom can be constructed to model a compressed breast, as in film/screen, digital mammography and digital breast tomosynthesis studies, or a non-compressed breast as in positron emission mammography and breast CT studies. Both the cranial-caudal and mediolateral oblique views can be modelled. The anatomical details inside the phantom include the lactiferous duct system, the Cooper ligaments and the pectoral muscle. The fibroglandular tissues are also modelled realistically. In addition, abnormalities such as microcalcifications, irregular tumours and spiculated tumours are inserted into the phantom. Existing sophisticated breast models require specialized simulation codes. Unlike its predecessors, DeBRa has elemental compositions and densities incorporated into its voxels including those of the explicitly modelled anatomical structures and the noise-like fibroglandular tissues. The voxel dimensions are specified as needed by any study and the microcalcifications are embedded into the voxels so that the microcalcification sizes are not limited by the voxel dimensions. Therefore, DeBRa works with general-purpose Monte Carlo codes. Furthermore, general-purpose Monte Carlo codes allow different types of imaging modalities and detector characteristics to be simulated with ease. DeBRa is a versatile and multipurpose model specifically designed for both x-ray and γ-ray imaging studies.

Method to improve cancerous lesion detection sensitivity in a dedicated dual-head scintimammography system

DOEpatents

Kieper, Douglas Arthur [Seattle, WA; Majewski, Stanislaw [Morgantown, WV; Welch, Benjamin L [Hampton, VA

2012-07-03

An improved method for enhancing the contrast between background and lesion areas of a breast undergoing dual-head scintimammographic examination comprising: 1) acquiring a pair of digital images from a pair of small FOV or mini gamma cameras compressing the breast under examination from opposing sides; 2) inverting one of the pair of images to align or co-register with the other of the images to obtain co-registered pixel values; 3) normalizing the pair of images pixel-by-pixel by dividing pixel values from each of the two acquired images and the co-registered image by the average count per pixel in the entire breast area of the corresponding detector; and 4) multiplying the number of counts in each pixel by the value obtained in step 3 to produce a normalization enhanced two dimensional contrast map. This enhanced (increased contrast) contrast map enhances the visibility of minor local increases (uptakes) of activity over the background and therefore improves lesion detection sensitivity, especially of small lesions.

Method to improve cancerous lesion detection sensitivity in a dedicated dual-head scintimammography system

DOEpatents

Kieper, Douglas Arthur [Newport News, VA; Majewski, Stanislaw [Yorktown, VA; Welch, Benjamin L [Hampton, VA

2008-10-28

An improved method for enhancing the contrast between background and lesion areas of a breast undergoing dual-head scintimammographic examination comprising: 1) acquiring a pair of digital images from a pair of small FOV or mini gamma cameras compressing the breast under examination from opposing sides; 2) inverting one of the pair of images to align or co-register with the other of the images to obtain co-registered pixel values; 3) normalizing the pair of images pixel-by-pixel by dividing pixel values from each of the two acquired images and the co-registered image by the average count per pixel in the entire breast area of the corresponding detector; and 4) multiplying the number of counts in each pixel by the value obtained in step 3 to produce a normalization enhanced two dimensional contrast map. This enhanced (increased contrast) contrast map enhances the visibility of minor local increases (uptakes) of activity over the background and therefore improves lesion detection sensitivity, especially of small lesions.

Interactive lesion segmentation on dynamic contrast enhanced breast MRI using a Markov model

NASA Astrophysics Data System (ADS)

Wu, Qiu; Salganicoff, Marcos; Krishnan, Arun; Fussell, Donald S.; Markey, Mia K.

2006-03-01

The purpose of this study is to develop a method for segmenting lesions on Dynamic Contrast-Enhanced (DCE) breast MRI. DCE breast MRI, in which the breast is imaged before, during, and after the administration of a contrast agent, enables a truly 3D examination of breast tissues. This functional angiogenic imaging technique provides noninvasive assessment of microcirculatory characteristics of tissues in addition to traditional anatomical structure information. Since morphological features and kinetic curves from segmented lesions are to be used for diagnosis and treatment decisions, lesion segmentation is a key pre-processing step for classification. In our study, the ROI is defined by a bounding box containing the enhancement region in the subtraction image, which is generated by subtracting the pre-contrast image from 1st post-contrast image. A maximum a posteriori (MAP) estimate of the class membership (lesion vs. non-lesion) for each voxel is obtained using the Iterative Conditional Mode (ICM) method. The prior distribution of the class membership is modeled as a multi-level logistic model, a Markov Random Field model in which the class membership of each voxel is assumed to depend upon its nearest neighbors only. The likelihood distribution is assumed to be Gaussian. The parameters of each Gaussian distribution are estimated from a dozen voxels manually selected as representative of the class. The experimental segmentation results demonstrate anatomically plausible breast tissue segmentation and the predicted class membership of voxels from the interactive segmentation algorithm agrees with the manual classifications made by inspection of the kinetic enhancement curves. The proposed method is advantageous in that it is efficient, flexible, and robust.

Temporal subtraction contrast-enhanced dedicated breast CT

NASA Astrophysics Data System (ADS)

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-09-01

The development of a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, intensity difference adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using normalized cross correlation (NCC), symmetric uncertainty coefficient, normalized mutual information (NMI), mean square error (MSE) and target registration error (TRE). The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE (0-16%), NCC (0-6%), NMI (0-13%) and TRE (0-34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake.

An adaptive Fuzzy C-means method utilizing neighboring information for breast tumor segmentation in ultrasound images.

PubMed

Feng, Yuan; Dong, Fenglin; Xia, Xiaolong; Hu, Chun-Hong; Fan, Qianmin; Hu, Yanle; Gao, Mingyuan; Mutic, Sasa

2017-07-01

Ultrasound (US) imaging has been widely used in breast tumor diagnosis and treatment intervention. Automatic delineation of the tumor is a crucial first step, especially for the computer-aided diagnosis (CAD) and US-guided breast procedure. However, the intrinsic properties of US images such as low contrast and blurry boundaries pose challenges to the automatic segmentation of the breast tumor. Therefore, the purpose of this study is to propose a segmentation algorithm that can contour the breast tumor in US images. To utilize the neighbor information of each pixel, a Hausdorff distance based fuzzy c-means (FCM) method was adopted. The size of the neighbor region was adaptively updated by comparing the mutual information between them. The objective function of the clustering process was updated by a combination of Euclid distance and the adaptively calculated Hausdorff distance. Segmentation results were evaluated by comparing with three experts' manual segmentations. The results were also compared with a kernel-induced distance based FCM with spatial constraints, the method without adaptive region selection, and conventional FCM. Results from segmenting 30 patient images showed the adaptive method had a value of sensitivity, specificity, Jaccard similarity, and Dice coefficient of 93.60 ± 5.33%, 97.83 ± 2.17%, 86.38 ± 5.80%, and 92.58 ± 3.68%, respectively. The region-based metrics of average symmetric surface distance (ASSD), root mean square symmetric distance (RMSD), and maximum symmetric surface distance (MSSD) were 0.03 ± 0.04 mm, 0.04 ± 0.03 mm, and 1.18 ± 1.01 mm, respectively. All the metrics except sensitivity were better than that of the non-adaptive algorithm and the conventional FCM. Only three region-based metrics were better than that of the kernel-induced distance based FCM with spatial constraints. Inclusion of the pixel neighbor information adaptively in segmenting US images improved the segmentation performance. The results demonstrate the potential application of the method in breast tumor CAD and other US-guided procedures. © 2017 American Association of Physicists in Medicine.

TH-AB-209-12: Tissue Equivalent Phantom with Excised Human Tissue for Assessing Clinical Capabilities of Coherent Scatter Imaging Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Albanese, K; Morris, R; Spencer, J

Purpose: Previously we reported the development of anthropomorphic tissue-equivalent scatter phantoms of the human breast. Here we present the first results from the scatter imaging of the tissue equivalent breast phantoms for breast cancer diagnosis. Methods: A breast phantom was designed to assess the capability of coded aperture coherent x-ray scatter imaging to classify different types of breast tissue (adipose, fibroglandular, tumor). The phantom geometry was obtained from a prone breast geometry scanned on a dedicated breast CT system. The phantom was 3D printed using the segmented DICOM breast CT data. The 3D breast phantom was filled with lard (asmore » a surrogate for adipose tissue) and scanned in different geometries alongside excised human breast tissues (obtained from lumpectomy and mastectomy procedures). The raw data were reconstructed using a model-based reconstruction algorithm and yielded the location and form factor (i.e., momentum transfer (q) spectrum) of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x-ray diffraction (XRD) imaging. Results: Our scatter imaging system was able to define the location and composition of the various materials and tissues within the phantom. Cancerous breast tissue was detected and classified through automated spectral matching and an 86% correlation threshold. The total scan time for the sample was approximately 10 minutes and approaches workflow times for clinical use in intra-operative or other diagnostic tasks. Conclusion: This work demonstrates the first results from an anthropomorphic tissue equivalent scatter phantom to characterize a coherent scatter imaging system. The functionality of the system shows promise in applications such as intra-operative margin detection or virtual biopsy in the diagnosis of breast cancer. Future work includes using additional patient-derived tissues (e.g., human fat), and modeling additional organs (e.g., lung).« less

Temporal subtraction contrast-enhanced dedicated breast CT

PubMed Central

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-01-01

Purpose To develop a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. Methods An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, Intensity Difference Adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using Normalized Cross Correlation (NCC), Symmetric Uncertainty Coefficient (SUC), Normalized Mutual Information (NMI), Mean Square Error (MSE) and Target Registration Error (TRE). Results The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE(0–16%), NCC (0–6%), NMI (0–13%) and TRE (0–34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Conclusion Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake. PMID:27494376

Combined Optical Imaging and Mammography of the Healthy Breast: Optical Contrast Derived From Breast Structure and Compression

PubMed Central

Fang, Qianqian; Carp, Stefan A.; Selb, Juliette; Boverman, Greg; Zhang, Quan; Kopans, Daniel B.; Moore, Richard H.; Miller, Eric L.; Brooks, Dana H.; Boas, David A.

2009-01-01

In this paper, we report new progress in developing the instrument and software platform of a combined X-ray mammography/diffuse optical breast imaging system. Particularly, we focus on system validation using a series of balloon phantom experiments and the optical image analysis of 49 healthy patients. Using the finite-element method for forward modeling and a regularized Gauss-Newton method for parameter reconstruction, we recovered the inclusions inside the phantom and the hemoglobin images of the human breasts. An enhanced coupling coefficient estimation scheme was also incorporated to improve the accuracy and robustness of the reconstructions. The recovered average total hemoglobin concentration (HbT) and oxygen saturation (SO2) from 68 breast measurements are 16.2 μm and 71%, respectively, where the HbT presents a linear trend with breast density. The low HbT value compared to literature is likely due to the associated mammographic compression. From the spatially co-registered optical/X-ray images, we can identify the chest-wall muscle, fatty tissue, and fibroglandular regions with an average HbT of 20.1±6.1 μm for fibroglandular tissue, 15.4±5.0 μm for adipose, and 22.2±7.3 μm for muscle tissue. The differences between fibroglandular tissue and the corresponding adipose tissue are significant (p < 0.0001). At the same time, we recognize that the optical images are influenced, to a certain extent, by mammographical compression. The optical images from a subset of patients show composite features from both tissue structure and pressure distribution. We present mechanical simulations which further confirm this hypothesis. PMID:19116186

Surface scanning through a cylindrical tank of coupling fluid for clinical microwave breast imaging exams

PubMed Central

Pallone, Matthew J.; Meaney, Paul M.; Paulsen, Keith D.

2012-01-01

Purpose: Microwave tomographic image quality can be improved significantly with prior knowledge of the breast surface geometry. The authors have developed a novel laser scanning system capable of accurately recovering surface renderings of breast-shaped phantoms immersed within a cylindrical tank of coupling fluid which resides completely external to the tank (and the aqueous environment) and overcomes the challenges associated with the optical distortions caused by refraction from the air, tank wall, and liquid bath interfaces. Methods: The scanner utilizes two laser line generators and a small CCD camera mounted concentrically on a rotating gantry about the microwave imaging tank. Various calibration methods were considered for optimizing the accuracy of the scanner in the presence of the optical distortions including traditional ray tracing and image registration approaches. In this paper, the authors describe the construction and operation of the laser scanner, compare the efficacy of several calibration methods—including analytical ray tracing and piecewise linear, polynomial, locally weighted mean, and thin-plate-spline (TPS) image registrations—and report outcomes from preliminary phantom experiments. Results: The results show that errors in calibrating camera angles and position prevented analytical ray tracing from achieving submillimeter accuracy in the surface renderings obtained from our scanner configuration. Conversely, calibration by image registration reliably attained mean surface errors of less than 0.5 mm depending on the geometric complexity of the object scanned. While each of the image registration approaches outperformed the ray tracing strategy, the authors found global polynomial methods produced the best compromise between average surface error and scanner robustness. Conclusions: The laser scanning system provides a fast and accurate method of three dimensional surface capture in the aqueous environment commonly found in microwave breast imaging. Optical distortions imposed by the imaging tank and coupling bath diminished the effectiveness of the ray tracing approach; however, calibration through image registration techniques reliably produced scans of submillimeter accuracy. Tests of the system with breast-shaped phantoms demonstrated the successful implementation of the scanner for the intended application. PMID:22755695

Sentinel lymph node detection in breast cancer patients using surgical navigation system based on fluorescence molecular imaging technology

NASA Astrophysics Data System (ADS)

Chi, Chongwei; Kou, Deqiang; Ye, Jinzuo; Mao, Yamin; Qiu, Jingdan; Wang, Jiandong; Yang, Xin; Tian, Jie

2015-03-01

Introduction: Precision and personalization treatments are expected to be effective methods for early stage cancer studies. Breast cancer is a major threat to women's health and sentinel lymph node biopsy (SLNB) is an effective method to realize precision and personalized treatment for axillary lymph node (ALN) negative patients. In this study, we developed a surgical navigation system (SNS) based on optical molecular imaging technology for the precise detection of the sentinel lymph node (SLN) in breast cancer patients. This approach helps surgeons in precise positioning during surgery. Methods: The SNS was mainly based on the technology of optical molecular imaging. A novel optical path has been designed in our hardware system and a feature-matching algorithm has been devised to achieve rapid fluorescence and color image registration fusion. Ten in vivo studies of SLN detection in rabbits using indocyanine green (ICG) and blue dye were executed for system evaluation and 8 breast cancer patients accepted the combination method for therapy. Results: The detection rate of the combination method was 100% and an average of 2.6 SLNs was found in all patients. Our results showed that the method of using SNS to detect SLN has the potential to promote its application. Conclusion: The advantage of this system is the real-time tracing of lymph flow in a one-step procedure. The results demonstrated the feasibility of the system for providing accurate location and reliable treatment for surgeons. Our approach delivers valuable information and facilitates more detailed exploration for image-guided surgery research.

Investigation of statistical iterative reconstruction for dedicated breast CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makeev, Andrey; Glick, Stephen J.

2013-08-15

Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images weremore » compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue.Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters.Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved performance (by a factor of greater than 10) compared to FBP. The hyperbolic prior was also observed to be superior to the TV norm. A few of the best-performing parameter pairs for the PML method also demonstrated superior performance for various radiation doses. In fact, using PML with certain parameter values results in better images, acquired using 2 mGy dose, than FBP-reconstructed images acquired using 6 mGy dose.Conclusions: A range of optimal free parameters for the PML algorithm with hyperbolic and TV norm-based potentials is presented for the microcalcification detection task, in dedicated breast CT. The reported values can be used as starting values of the free parameters, when SIR techniques are used for image reconstruction. Significant improvement in image quality can be achieved by using PML with optimal combination of parameters, as compared to FBP. Importantly, these results suggest improved detection of microcalcifications can be obtained by using PML with lower radiation dose to the patient, than using FBP with higher dose.« less

Full-wave Nonlinear Inverse Scattering for Acoustic and Electromagnetic Breast Imaging

NASA Astrophysics Data System (ADS)

Haynes, Mark Spencer

Acoustic and electromagnetic full-wave nonlinear inverse scattering techniques are explored in both theory and experiment with the ultimate aim of noninvasively mapping the material properties of the breast. There is evidence that benign and malignant breast tissue have different acoustic and electrical properties and imaging these properties directly could provide higher quality images with better diagnostic certainty. In this dissertation, acoustic and electromagnetic inverse scattering algorithms are first developed and validated in simulation. The forward solvers and optimization cost functions are modified from traditional forms in order to handle the large or lossy imaging scenes present in ultrasonic and microwave breast imaging. An antenna model is then presented, modified, and experimentally validated for microwave S-parameter measurements. Using the antenna model, a new electromagnetic volume integral equation is derived in order to link the material properties of the inverse scattering algorithms to microwave S-parameters measurements allowing direct comparison of model predictions and measurements in the imaging algorithms. This volume integral equation is validated with several experiments and used as the basis of a free-space inverse scattering experiment, where images of the dielectric properties of plastic objects are formed without the use of calibration targets. These efforts are used as the foundation of a solution and formulation for the numerical characterization of a microwave near-field cavity-based breast imaging system. The system is constructed and imaging results of simple targets are given. Finally, the same techniques are used to explore a new self-characterization method for commercial ultrasound probes. The method is used to calibrate an ultrasound inverse scattering experiment and imaging results of simple targets are presented. This work has demonstrated the feasibility of quantitative microwave inverse scattering by way of a self-consistent characterization formalism, and has made headway in the same area for ultrasound.

Radiation dose reduction using a CdZnTe-based computed tomography system: Comparison to flat-panel detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Le, Huy Q.; Ducote, Justin L.; Molloi, Sabee

2010-03-15

Purpose: Although x-ray projection mammography has been very effective in early detection of breast cancer, its utility is reduced in the detection of small lesions that are occult or in dense breasts. One drawback is that the inherent superposition of parenchymal structures makes visualization of small lesions difficult. Breast computed tomography using flat-panel detectors has been developed to address this limitation by producing three-dimensional data while at the same time providing more comfort to the patients by eliminating breast compression. Flat panels are charge integrating detectors and therefore lack energy resolution capability. Recent advances in solid state semiconductor x-ray detectormore » materials and associated electronics allow the investigation of x-ray imaging systems that use a photon counting and energy discriminating detector, which is the subject of this article. Methods: A small field-of-view computed tomography (CT) system that uses CdZnTe (CZT) photon counting detector was compared to one that uses a flat-panel detector for different imaging tasks in breast imaging. The benefits afforded by the CZT detector in the energy weighting modes were investigated. Two types of energy weighting methods were studied: Projection based and image based. Simulation and phantom studies were performed with a 2.5 cm polymethyl methacrylate (PMMA) cylinder filled with iodine and calcium contrast objects. Simulation was also performed on a 10 cm breast specimen. Results: The contrast-to-noise ratio improvements as compared to flat-panel detectors were 1.30 and 1.28 (projection based) and 1.35 and 1.25 (image based) for iodine over PMMA and hydroxylapatite over PMMA, respectively. Corresponding simulation values were 1.81 and 1.48 (projection based) and 1.85 and 1.48 (image based). Dose reductions using the CZT detector were 52.05% and 49.45% for iodine and hydroxyapatite imaging, respectively. Image-based weighting was also found to have the least beam hardening effect. Conclusions: The results showed that a CT system using an energy resolving detector reduces the dose to the patient while maintaining image quality for various breast imaging tasks.« less

Shear Wave Imaging of Breast Tissue by Color Doppler Shear Wave Elastography.

PubMed

Yamakoshi, Yoshiki; Nakajima, Takahito; Kasahara, Toshihiro; Yamazaki, Mayuko; Koda, Ren; Sunaguchi, Naoki

2017-02-01

Shear wave elastography is a distinctive method to access the viscoelastic characteristic of the soft tissue that is difficult to obtain by other imaging modalities. This paper proposes a novel shear wave elastography [color Doppler shear wave imaging (CD SWI)] for breast tissue. Continuous shear wave is produced by a small lightweight actuator, which is attached to the tissue surface. Shear wave wavefront that propagates in tissue is reconstructed as a binary pattern that consists of zero and the maximum flow velocities on color flow image (CFI). Neither any modifications of the ultrasound color flow imaging instrument nor a high frame rate ultrasound imaging instrument is required to obtain the shear wave wavefront map. However, two conditions of shear wave displacement amplitude and shear wave frequency are needed to obtain the map. However, these conditions are not severe restrictions in breast imaging. This is because the minimum displacement amplitude is [Formula: see text] for an ultrasonic wave frequency of 12 MHz and the shear wave frequency is available from several frequencies suited for breast imaging. Fourier analysis along time axis suppresses clutter noise in CFI. A directional filter extracts shear wave, which propagates in the forward direction. Several maps, such as shear wave phase, velocity, and propagation maps, are reconstructed by CD SWI. The accuracy of shear wave velocity measurement is evaluated for homogeneous agar gel phantom by comparing with the acoustic radiation force impulse method. The experimental results for breast tissue are shown for a shear wave frequency of 296.6 Hz.

Development of an Anthropomorphic Breast Phantom for Combined PET, B-Mode Ultrasound and Elastographic Imaging

NASA Astrophysics Data System (ADS)

Dang, Jun; Frisch, Benjamin; Lasaygues, Philippe; Zhang, Dachun; Tavernier, Stefaan; Felix, Nicolas; Lecoq, Paul; Auffray, Etiennette; Varela, Joao; Mensah, Serge; Wan, Mingxi

2011-06-01

Combining the advantages of different imaging modalities leads to improved clinical results. For example, ultrasound provides good real-time structural information without any radiation and PET provides sensitive functional information. For the ongoing ClearPEM-Sonic project combining ultrasound and PET for breast imaging, we developed a dual-modality PET/Ultrasound (US) phantom. The phantom reproduces the acoustic and elastic properties of human breast tissue and allows labeling the different tissues in the phantom with different concentrations of FDG. The phantom was imaged with a whole-body PET/CT and with the Supersonic Imagine Aixplorer system. This system allows both B-mode US and shear wave elastographic imaging. US elastography is a new imaging method for displaying the tissue elasticity distribution. It was shown to be useful in breast imaging. We also tested the phantom with static elastography. A 6D magnetic positioning system allows fusing the images obtained with the two modalities. ClearPEM-Sonic is a project of the Crystal Clear Collaboration and the European Centre for Research on Medical Imaging (CERIMED).

In vivo intra-operative breast tumor margin detection using a portable OCT system with a handheld surgical imaging probe

NASA Astrophysics Data System (ADS)

Erickson-Bhatt, Sarah J.; Nolan, Ryan; Shemonski, Nathan D.; Adie, Steven G.; Putney, Jeffrey; Darga, Donald; McCormick, Daniel T.; Cittadine, Andrew; Marjanovic, Marina; Chaney, Eric J.; Monroy, Guillermo L.; South, Fredrick; Carney, P. Scott; Cradock, Kimberly A.; Liu, Z. George; Ray, Partha S.; Boppart, Stephen A.

2014-02-01

Breast-conserving surgery is a frequent option for women with stage I and II breast cancer, and with radiation treatment, can be as effective as a mastectomy. However, adequate margin detection remains a challenge, and too often additional surgeries are required. Optical coherence tomography (OCT) provides a potential method for real-time, high-resolution imaging of breast tissue during surgery. Intra-operative OCT imaging of excised breast tissues has been previously demonstrated by several groups. In this study, a novel handheld surgical probe-based OCT system is introduced, which was used by the surgeon to image in vivo, within the tumor cavity, and immediately following tumor removal in order to detect the presence of any remaining cancer. Following resection, study investigators imaged the excised tissue with the same probe for comparison. We present OCT images obtained from over 15 patients during lumpectomy and mastectomy surgeries. Images were compared to post-operative histopathology for diagnosis. OCT images with micron scale resolution show areas of heterogeneity and disorganized features indicative of malignancy, compared to more uniform regions of normal tissue. Video-rate acquisition shows the inside of the tumor cavity as the surgeon sweeps the probe along the walls of the surgical cavity. This demonstrates the potential of OCT for real-time assessment of surgical tumor margins and for reducing the unacceptably high re-operation rate for breast cancer patients.

Evaluation of the absorbed dose to the breast using radiochromic film in a dedicated CT mammotomography system employing a quasi-monochromatic x-ray beam

PubMed Central

Crotty, Dominic J.; Brady, Samuel L.; Jackson, D’Vone C.; Toncheva, Greta I.; Anderson, Colin E.; Yoshizumi, Terry T.; Tornai, Martin P.

2011-01-01

Purpose: A dual modality SPECT-CT prototype system dedicated to uncompressed breast imaging (mammotomography) has been developed. The computed tomography subsystem incorporates an ultrathick K-edge filtration technique producing a quasi-monochromatic x-ray cone beam that optimizes the dose efficiency of the system for lesion imaging in an uncompressed breast. Here, the absorbed dose in various geometric phantoms and in an uncompressed and pendant cadaveric breast using a normal tomographic cone beam imaging protocol is characterized using both thermoluminescent dosimeter (TLD) measurements and ionization chamber-calibrated radiochromic film. Methods: Initially, two geometric phantoms and an anthropomorphic breast phantom are filled in turn with oil and water to simulate the dose to objects that mimic various breast shapes having effective density bounds of 100% fatty and glandular breast compositions, respectively. Ultimately, an excised human cadaver breast is tomographically scanned using the normal tomographic imaging protocol, and the dose to the breast tissue is evaluated and compared to the earlier phantom-based measurements. Results: Measured trends in dose distribution across all breast geometric and anthropomorphic phantom volumes indicate lower doses in the medial breast and more proximal to the chest wall, with consequently higher doses near the lateral peripheries and nipple regions. Measured doses to the oil-filled phantoms are consistently lower across all volume shapes due to the reduced mass energy-absorption coefficient of oil relative to water. The mean measured dose to the breast cadaver, composed of adipose and glandular tissues, was measured to be 4.2 mGy compared to a mean whole-breast dose of 3.8 and 4.5 mGy for the oil- and water-filled anthropomorphic breast phantoms, respectively. Conclusions: Assuming rotational symmetry due to the tomographic acquisition exposures, these results characterize the 3D dose distributions in an uncompressed human breast tissue volume for this dedicated breast imaging device and illustrate advantages of using the novel ultrathick K-edge filtered beam to minimize the dose to the breast during fully-3D imaging. PMID:21815398

Reducing breast biopsies by ultrasonographic analysis and a modified self-organizing map

NASA Astrophysics Data System (ADS)

Zheng, Yi; Greenleaf, James F.; Gisvold, John J.

1997-05-01

Recent studies suggest that visual evaluation of ultrasound images could decrease negative biopsies of breast cancer diagnosis. However, visual evaluation requires highly experienced breast sonographers. The objective of this study is to develop computerized radiologist assistant to reduce breast biopsies needed for evaluating suspected breast cancer. The approach of this study utilizes a neural network and tissue features extracted from digital sonographic breast images. The features include texture parameters of breast images: characteristics of echoes within and around breast lesions, and geometrical information of breast tumors. Clusters containing only benign lesions in the feature space are then identified by a modified self- organizing map. This newly developed neural network objectively segments population distributions of lesions and accurately establishes benign and equivocal regions.t eh method was applied to high quality breast sonograms of a large number of patients collected with a controlled procedure at Mayo Clinic. The study showed that the number of biopsies in this group of women could be decreased by 40 percent to 59 percent with high confidence and that no malignancies would have been included in the nonbiopsied group. The advantages of this approach are that it is robust, simple, and effective and does not require highly experienced sonographers.

Mass Detection in Mammographic Images Using Wavelet Processing and Adaptive Threshold Technique.

PubMed

Vikhe, P S; Thool, V R

2016-04-01

Detection of mass in mammogram for early diagnosis of breast cancer is a significant assignment in the reduction of the mortality rate. However, in some cases, screening of mass is difficult task for radiologist, due to variation in contrast, fuzzy edges and noisy mammograms. Masses and micro-calcifications are the distinctive signs for diagnosis of breast cancer. This paper presents, a method for mass enhancement using piecewise linear operator in combination with wavelet processing from mammographic images. The method includes, artifact suppression and pectoral muscle removal based on morphological operations. Finally, mass segmentation for detection using adaptive threshold technique is carried out to separate the mass from background. The proposed method has been tested on 130 (45 + 85) images with 90.9 and 91 % True Positive Fraction (TPF) at 2.35 and 2.1 average False Positive Per Image(FP/I) from two different databases, namely Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM). The obtained results show that, the proposed technique gives improved diagnosis in the early breast cancer detection.

Fast microcalcification detection in ultrasound images using image enhancement and threshold adjacency statistics

NASA Astrophysics Data System (ADS)

Cho, Baek Hwan; Chang, Chuho; Lee, Jong-Ha; Ko, Eun Young; Seong, Yeong Kyeong; Woo, Kyoung-Gu

2013-02-01

The existence of microcalcifications (MCs) is an important marker of malignancy in breast cancer. In spite of the benefits in mass detection for dense breasts, ultrasonography is believed that it might not reliably detect MCs. For computer aided diagnosis systems, however, accurate detection of MCs has the possibility of improving the performance in both Breast Imaging-Reporting and Data System (BI-RADS) lexicon description for calcifications and malignancy classification. We propose a new efficient and effective method for MC detection using image enhancement and threshold adjacency statistics (TAS). The main idea of TAS is to threshold an image and to count the number of white pixels with a given number of adjacent white pixels. Our contribution is to adopt TAS features and apply image enhancement to facilitate MC detection in ultrasound images. We employed fuzzy logic, tophat filter, and texture filter to enhance images for MCs. Using a total of 591 images, the classification accuracy of the proposed method in MC detection showed 82.75%, which is comparable to that of Haralick texture features (81.38%). When combined, the performance was as high as 85.11%. In addition, our method also showed the ability in mass classification when combined with existing features. In conclusion, the proposed method exploiting image enhancement and TAS features has the potential to deal with MC detection in ultrasound images efficiently and extend to the real-time localization and visualization of MCs.

Modeling of electrical impedance tomography to detect breast cancer by finite volume methods

NASA Astrophysics Data System (ADS)

Ain, K.; Wibowo, R. A.; Soelistiono, S.

2017-05-01

The properties of the electrical impedance of tissue are an interesting study, because changes of the electrical impedance of organs are related to physiological and pathological. Both physiological and pathological properties are strongly associated with disease information. Several experiments shown that the breast cancer has a lower impedance than the normal breast tissue. Thus, the imaging based on impedance can be used as an alternative equipment to detect the breast cancer. This research carries out by modelling of Electrical Impedance Tomography to detect the breast cancer by finite volume methods. The research includes development of a mathematical model of the electric potential field by 2D Finite Volume Method, solving the forward problem and inverse problem by linear reconstruction method. The scanning is done by 16 channel electrode with neighbors method to collect data. The scanning is performed at a frequency of 10 kHz and 100 kHz with three objects numeric includes an anomaly at the surface, an anomaly at the depth and an anomaly at the surface and at depth. The simulation has been successfully to reconstruct image of functional anomalies of the breast cancer at the surface position, the depth position or a combination of surface and the depth.

Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.

PubMed

Robertson, Stephanie; Azizpour, Hossein; Smith, Kevin; Hartman, Johan

2018-04-01

Breast cancer is the most common malignant disease in women worldwide. In recent decades, earlier diagnosis and better adjuvant therapy have substantially improved patient outcome. Diagnosis by histopathology has proven to be instrumental to guide breast cancer treatment, but new challenges have emerged as our increasing understanding of cancer over the years has revealed its complex nature. As patient demand for personalized breast cancer therapy grows, we face an urgent need for more precise biomarker assessment and more accurate histopathologic breast cancer diagnosis to make better therapy decisions. The digitization of pathology data has opened the door to faster, more reproducible, and more precise diagnoses through computerized image analysis. Software to assist diagnostic breast pathology through image processing techniques have been around for years. But recent breakthroughs in artificial intelligence (AI) promise to fundamentally change the way we detect and treat breast cancer in the near future. Machine learning, a subfield of AI that applies statistical methods to learn from data, has seen an explosion of interest in recent years because of its ability to recognize patterns in data with less need for human instruction. One technique in particular, known as deep learning, has produced groundbreaking results in many important problems including image classification and speech recognition. In this review, we will cover the use of AI and deep learning in diagnostic breast pathology, and other recent developments in digital image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

Advances in molecular imaging for breast cancer detection and characterization

PubMed Central

2012-01-01

Advances in our ability to assay molecular processes, including gene expression, protein expression, and molecular and cellular biochemistry, have fueled advances in our understanding of breast cancer biology and have led to the identification of new treatments for patients with breast cancer. The ability to measure biologic processes without perturbing them in vivo allows the opportunity to better characterize tumor biology and to assess how biologic and cytotoxic therapies alter critical pathways of tumor response and resistance. By accurately characterizing tumor properties and biologic processes, molecular imaging plays an increasing role in breast cancer science, clinical care in diagnosis and staging, assessment of therapeutic targets, and evaluation of responses to therapies. This review describes the current role and potential of molecular imaging modalities for detection and characterization of breast cancer and focuses primarily on radionuclide-based methods. PMID:22423895

MR-guided high-intensity focused ultrasound ablation of breast cancer with a dedicated breast platform.

PubMed

Merckel, Laura G; Bartels, Lambertus W; Köhler, Max O; van den Bongard, H J G Desirée; Deckers, Roel; Mali, Willem P Th M; Binkert, Christoph A; Moonen, Chrit T; Gilhuijs, Kenneth G A; van den Bosch, Maurice A A J

2013-04-01

Optimizing the treatment of breast cancer remains a major topic of interest. In current clinical practice, breast-conserving therapy is the standard of care for patients with localized breast cancer. Technological developments have fueled interest in less invasive breast cancer treatment. Magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) is a completely noninvasive ablation technique. Focused beams of ultrasound are used for ablation of the target lesion without disrupting the skin and subcutaneous tissues in the beam path. MRI is an excellent imaging method for tumor targeting, treatment monitoring, and evaluation of treatment results. The combination of HIFU and MR imaging offers an opportunity for image-guided ablation of breast cancer. Previous studies of MR-HIFU in breast cancer patients reported a limited efficacy, which hampered the clinical translation of this technique. These prior studies were performed without an MR-HIFU system specifically developed for breast cancer treatment. In this article, a novel and dedicated MR-HIFU breast platform is presented. This system has been designed for safe and effective MR-HIFU ablation of breast cancer. Furthermore, both clinical and technical challenges are discussed, which have to be solved before MR-HIFU ablation of breast cancer can be implemented in routine clinical practice.

Sci—Thur AM: YIS - 08: Constructing an Attenuation map for a PET/MR Breast coil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patrick, John C.; Imaging, Lawson Health Research Institute, Knoxville, TN; London Regional Cancer Program, Knoxville, TN

2014-08-15

In 2013, around 23000 Canadian women and 200 Canadian men were diagnosed with breast cancer. An estimated 5100 women and 55 men died from the disease. Using the sensitivity of MRI with the selectivity of PET, PET/MRI combines anatomical and functional information within the same scan and could help with early detection in high-risk patients. MRI requires radiofrequency coils for transmitting energy and receiving signal but the breast coil attenuates PET signal. To correct for this PET attenuation, a 3-dimensional map of linear attenuation coefficients (μ-map) of the breast coil must be created and incorporated into the PET reconstruction process.more » Several approaches have been proposed for building hardware μ-maps, some of which include the use of conventional kVCT and Dual energy CT. These methods can produce high resolution images based on the electron densities of materials that can be converted into μ-maps. However, imaging hardware containing metal components with photons in the kV range is susceptible to metal artifacts. These artifacts can compromise the accuracy of the resulting μ-map and PET reconstruction; therefore high-Z components should be removed. We propose a method for calculating μ-maps without removing coil components, based on megavoltage (MV) imaging with a linear accelerator that has been detuned for imaging at 1.0MeV. Containers of known geometry with F18 were placed in the breast coil for imaging. A comparison between reconstructions based on the different μ-map construction methods was made. PET reconstructions with our method show a maximum of 6% difference over the existing kVCT-based reconstructions.« less

A deep learning method for classifying mammographic breast density categories.

PubMed

Mohamed, Aly A; Berg, Wendie A; Peng, Hong; Luo, Yahong; Jankowitz, Rachel C; Wu, Shandong

2018-01-01

Mammographic breast density is an established risk marker for breast cancer and is visually assessed by radiologists in routine mammogram image reading, using four qualitative Breast Imaging and Reporting Data System (BI-RADS) breast density categories. It is particularly difficult for radiologists to consistently distinguish the two most common and most variably assigned BI-RADS categories, i.e., "scattered density" and "heterogeneously dense". The aim of this work was to investigate a deep learning-based breast density classifier to consistently distinguish these two categories, aiming at providing a potential computerized tool to assist radiologists in assigning a BI-RADS category in current clinical workflow. In this study, we constructed a convolutional neural network (CNN)-based model coupled with a large (i.e., 22,000 images) digital mammogram imaging dataset to evaluate the classification performance between the two aforementioned breast density categories. All images were collected from a cohort of 1,427 women who underwent standard digital mammography screening from 2005 to 2016 at our institution. The truths of the density categories were based on standard clinical assessment made by board-certified breast imaging radiologists. Effects of direct training from scratch solely using digital mammogram images and transfer learning of a pretrained model on a large nonmedical imaging dataset were evaluated for the specific task of breast density classification. In order to measure the classification performance, the CNN classifier was also tested on a refined version of the mammogram image dataset by removing some potentially inaccurately labeled images. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to measure the accuracy of the classifier. The AUC was 0.9421 when the CNN-model was trained from scratch on our own mammogram images, and the accuracy increased gradually along with an increased size of training samples. Using the pretrained model followed by a fine-tuning process with as few as 500 mammogram images led to an AUC of 0.9265. After removing the potentially inaccurately labeled images, AUC was increased to 0.9882 and 0.9857 for without and with the pretrained model, respectively, both significantly higher (P < 0.001) than when using the full imaging dataset. Our study demonstrated high classification accuracies between two difficult to distinguish breast density categories that are routinely assessed by radiologists. We anticipate that our approach will help enhance current clinical assessment of breast density and better support consistent density notification to patients in breast cancer screening. © 2017 American Association of Physicists in Medicine.

Prediction of pH of fresh chicken breast fillets by VNIR hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Visible and near-infrared (VNIR) hyperspectral imaging (400–900 nm) was used to evaluate pH of fresh chicken breast fillets (pectoralis major muscle) from the bone (dorsal) side of individual fillets. After the principal component analysis (PCA), a band threshold method was applied to the first prin...

The Future of Mammography: Radiology Residents’ Experiences, Attitudes, and Opinions

PubMed Central

Baxi, Shrujal S.; Snow, Jacqueline G.; Liberman, Laura; Elkin, Elena B.

2011-01-01

OBJECTIVE The objective of our study was to assess the experiences and preferences of radiology residents with respect to breast imaging. MATERIALS AND METHODS We surveyed radiology residents at 26 programs in New York and New Jersey. Survey topics included plans for subspecialty training, beliefs, and attitudes toward breast imaging and breast cancer screening and the likelihood of interpreting mammography in the future. RESULTS Three hundred forty-four residents completed the survey (response rate, 62%). The length of time spent training in breast imaging varied from no dedicated time (37%) to 1–8 weeks (40%) to more than 9 weeks (23%). Most respondents (97%) agreed that mammography is important to women’s health. More than 85% of residents believed that mammography should be interpreted by breast imaging specialists. Respondents shared negative views about mammography, agreeing with statements that the field was associated with a high risk of malpractice (99%), stress (94%), and low reimbursement (68%). Respondents endorsed several positive attributes of mammography, including job availability (97%), flexible work schedules (94%), and few calls or emergencies (93%). Most radiology residents (93%) said that they were likely to pursue subspecialty training, and 7% expressed interest in breast imaging fellowships. CONCLUSION Radiology residents’ negative and positive views about mammography seem to be independent of time spent training in mammography and of future plans to pursue fellowship training in breast imaging. Systematic assessment of the plans and preferences of radiology residents can facilitate the development of strategies to attract trainees to careers in breast imaging. PMID:20489113

Distribution of phthalocyanines and Raman reporters in human cancerous and noncancerous breast tissue as studied by Raman imaging.

PubMed

Brozek-Pluska, Beata; Jarota, Arkadiusz; Jablonska-Gajewicz, Joanna; Kordek, Radzislaw; Czajkowski, Wojciech; Abramczyk, Halina

2012-08-01

There is a considerable interest in the developing new diagnostic techniques allowing noninvasive tracking of the progress of therapies used to treat a cancer. Raman imaging of distribution of phthalocyanine photosensitizers may open new possibilities of Photodynamic Therapy (PDT) to treat a wide range of neoplastic lesions with improved effectiveness of treatment through precise identification of malignant areas. We have employed Raman imaging and Raman spectroscopy to analyze human breast cancer tissue that interacts with photosensitizers used in the photodynamic therapy of cancer. PCA (Principal Component Analysis) has been employed to analyze various areas of the noncancerous and cancerous breast tissues. The results show that the emission spectra combined with the Raman images are very sensitive indicators to specify the aggregation state and the distribution of phthalocyanines in the cancerous and noncancerous breast tissues. Our results provide experimental evidence on the role of aggregation of phthalocyanines as a factor of particular significance in differentiation of the normal and tumourous (cancerous or benign pathology) breast tissues. We conclude that the Raman imaging reported here has a potential to be a novel and effective photodynamic therapeutic method with improved selectivity for the treatment of breast cancer.

Efficient iterative image reconstruction algorithm for dedicated breast CT

NASA Astrophysics Data System (ADS)

Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan

2016-03-01

Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.

TU-AB-207-02: Testing of Body and Breast Tomosynthesis Sytems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, A.

2015-06-15

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact,more » the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. To learn how to test the performance of tomosynthesis imaging systems. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.« less

A multistage selective weighting method for improved microwave breast tomography.

PubMed

Shahzad, Atif; O'Halloran, Martin; Jones, Edward; Glavin, Martin

2016-12-01

Microwave tomography has shown potential to successfully reconstruct the dielectric properties of the human breast, thereby providing an alternative to other imaging modalities used in breast imaging applications. Considering the costly forward solution and complex iterative algorithms, computational complexity becomes a major bottleneck in practical applications of microwave tomography. In addition, the natural tendency of microwave inversion algorithms to reward high contrast breast tissue boundaries, such as the skin-adipose interface, usually leads to a very slow reconstruction of the internal tissue structure of human breast. This paper presents a multistage selective weighting method to improve the reconstruction quality of breast dielectric properties and minimize the computational cost of microwave breast tomography. In the proposed two stage approach, the skin layer is approximated using scaled microwave measurements in the first pass of the inversion algorithm; a numerical skin model is then constructed based on the estimated skin layer and the assumed dielectric properties of the skin tissue. In the second stage of the algorithm, the skin model is used as a priori information to reconstruct the internal tissue structure of the breast using a set of temporal scaling functions. The proposed method is evaluated on anatomically accurate MRI-derived breast phantoms and a comparison with the standard single-stage technique is presented. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Automatic insertion of simulated microcalcification clusters in a software breast phantom

NASA Astrophysics Data System (ADS)

Shankla, Varsha; Pokrajac, David D.; Weinstein, Susan P.; DeLeo, Michael; Tuite, Catherine; Roth, Robyn; Conant, Emily F.; Maidment, Andrew D.; Bakic, Predrag R.

2014-03-01

An automated method has been developed to insert realistic clusters of simulated microcalcifications (MCs) into computer models of breast anatomy. This algorithm has been developed as part of a virtual clinical trial (VCT) software pipeline, which includes the simulation of breast anatomy, mechanical compression, image acquisition, image processing, display and interpretation. An automated insertion method has value in VCTs involving large numbers of images. The insertion method was designed to support various insertion placement strategies, governed by probability distribution functions (pdf). The pdf can be predicated on histological or biological models of tumor growth, or estimated from the locations of actual calcification clusters. To validate the automated insertion method, a 2-AFC observer study was designed to compare two placement strategies, undirected and directed. The undirected strategy could place a MC cluster anywhere within the phantom volume. The directed strategy placed MC clusters within fibroglandular tissue on the assumption that calcifications originate from epithelial breast tissue. Three radiologists were asked to select between two simulated phantom images, one from each placement strategy. Furthermore, questions were posed to probe the rationale behind the observer's selection. The radiologists found the resulting cluster placement to be realistic in 92% of cases, validating the automated insertion method. There was a significant preference for the cluster to be positioned on a background of adipose or mixed adipose/fibroglandular tissues. Based upon these results, this automated lesion placement method will be included in our VCT simulation pipeline.

Automated System for Early Breast Cancer Detection in Mammograms

NASA Technical Reports Server (NTRS)

Bankman, Isaac N.; Kim, Dong W.; Christens-Barry, William A.; Weinberg, Irving N.; Gatewood, Olga B.; Brody, William R.

1993-01-01

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.

Correlates of mammographic density in B-mode ultrasound and real time elastography.

PubMed

Jud, Sebastian Michael; Häberle, Lothar; Fasching, Peter A; Heusinger, Katharina; Hack, Carolin; Faschingbauer, Florian; Uder, Michael; Wittenberg, Thomas; Wagner, Florian; Meier-Meitinger, Martina; Schulz-Wendtland, Rüdiger; Beckmann, Matthias W; Adamietz, Boris R

2012-07-01

The aim of our study involved the assessment of B-mode imaging and elastography with regard to their ability to predict mammographic density (MD) without X-rays. Women, who underwent routine mammography, were prospectively examined with additional B-mode ultrasound and elastography. MD was assessed quantitatively with a computer-assisted method (Madena). The B-mode and elastography images were assessed by histograms with equally sized gray-level intervals. Regression models were built and cross validated to examine the ability to predict MD. The results of this study showed that B-mode imaging and elastography were able to predict MD. B-mode seemed to give a more accurate prediction. R for B-mode image and elastography were 0.67 and 0.44, respectively. Areas in the B-mode images that correlated with mammographic dense areas were either dark gray or of intermediate gray levels. Concerning elastography only the gray levels that represent extremely stiff tissue correlated positively with MD. In conclusion, ultrasound seems to be able to predict MD. Easy and cheap utilization of regular breast ultrasound machines encourages the use of ultrasound in larger case-control studies to validate this method as a breast cancer risk predictor. Furthermore, the application of ultrasound for breast tissue characterization could enable comprehensive research concerning breast cancer risk and breast density in young and pregnant women.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aghaei, Faranak; Tan, Maxine; Liu, Hong

Purpose: To identify a new clinical marker based on quantitative kinetic image features analysis and assess its feasibility to predict tumor response to neoadjuvant chemotherapy. Methods: The authors assembled a dataset involving breast MR images acquired from 68 cancer patients before undergoing neoadjuvant chemotherapy. Among them, 25 patients had complete response (CR) and 43 had partial and nonresponse (NR) to chemotherapy based on the response evaluation criteria in solid tumors. The authors developed a computer-aided detection scheme to segment breast areas and tumors depicted on the breast MR images and computed a total of 39 kinetic image features from bothmore » tumor and background parenchymal enhancement regions. The authors then applied and tested two approaches to classify between CR and NR cases. The first one analyzed each individual feature and applied a simple feature fusion method that combines classification results from multiple features. The second approach tested an attribute selected classifier that integrates an artificial neural network (ANN) with a wrapper subset evaluator, which was optimized using a leave-one-case-out validation method. Results: In the pool of 39 features, 10 yielded relatively higher classification performance with the areas under receiver operating characteristic curves (AUCs) ranging from 0.61 to 0.78 to classify between CR and NR cases. Using a feature fusion method, the maximum AUC = 0.85 ± 0.05. Using the ANN-based classifier, AUC value significantly increased to 0.96 ± 0.03 (p < 0.01). Conclusions: This study demonstrated that quantitative analysis of kinetic image features computed from breast MR images acquired prechemotherapy has potential to generate a useful clinical marker in predicting tumor response to chemotherapy.« less

Concentration analysis of breast tissue phantoms with terahertz spectroscopy

PubMed Central

Truong, Bao C. Q.; Fitzgerald, Anthony J.; Fan, Shuting; Wallace, Vincent P.

2018-01-01

Terahertz imaging has been previously shown to be capable of distinguishing normal breast tissue from its cancerous form, indicating its applicability to breast conserving surgery. The heterogeneous composition of breast tissue is among the main challenges to progressing this potential research towards a practical application. In this paper, two concentration analysis methods are proposed for analyzing phantoms mimicking breast tissue. The dielectric properties and the double Debye parameters were used to determine the phantom composition. The first method is wholly based on the conventional effective medium theory while the second one combines this theoretical model with empirical polynomial models. Through assessing the accuracy of these methods, their potential for application to quantifying breast tissue pathology was confirmed. PMID:29541525

A framework for breast cancer visualization using augmented reality x-ray vision technique in mobile technology

NASA Astrophysics Data System (ADS)

Rahman, Hameedur; Arshad, Haslina; Mahmud, Rozi; Mahayuddin, Zainal Rasyid

2017-10-01

Breast Cancer patients who require breast biopsy has increased over the past years. Augmented Reality guided core biopsy of breast has become the method of choice for researchers. However, this cancer visualization has limitations to the extent of superimposing the 3D imaging data only. In this paper, we are introducing an Augmented Reality visualization framework that enables breast cancer biopsy image guidance by using X-Ray vision technique on a mobile display. This framework consists of 4 phases where it initially acquires the image from CT/MRI and process the medical images into 3D slices, secondly it will purify these 3D grayscale slices into 3D breast tumor model using 3D modeling reconstruction technique. Further, in visualization processing this virtual 3D breast tumor model has been enhanced using X-ray vision technique to see through the skin of the phantom and the final composition of it is displayed on handheld device to optimize the accuracy of the visualization in six degree of freedom. The framework is perceived as an improved visualization experience because the Augmented Reality x-ray vision allowed direct understanding of the breast tumor beyond the visible surface and direct guidance towards accurate biopsy targets.

Improved fuzzy clustering algorithms in segmentation of DC-enhanced breast MRI.

PubMed

Kannan, S R; Ramathilagam, S; Devi, Pandiyarajan; Sathya, A

2012-02-01

Segmentation of medical images is a difficult and challenging problem due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Many researchers have applied various techniques however fuzzy c-means (FCM) based algorithms is more effective compared to other methods. The objective of this work is to develop some robust fuzzy clustering segmentation systems for effective segmentation of DCE - breast MRI. This paper obtains the robust fuzzy clustering algorithms by incorporating kernel methods, penalty terms, tolerance of the neighborhood attraction, additional entropy term and fuzzy parameters. The initial centers are obtained using initialization algorithm to reduce the computation complexity and running time of proposed algorithms. Experimental works on breast images show that the proposed algorithms are effective to improve the similarity measurement, to handle large amount of noise, to have better results in dealing the data corrupted by noise, and other artifacts. The clustering results of proposed methods are validated using Silhouette Method.

Registration of parametric dynamic F-18-FDG PET/CT breast images with parametric dynamic Gd-DTPA breast images

NASA Astrophysics Data System (ADS)

Magri, Alphonso; Krol, Andrzej; Lipson, Edward; Mandel, James; McGraw, Wendy; Lee, Wei; Tillapaugh-Fay, Gwen; Feiglin, David

2009-02-01

This study was undertaken to register 3D parametric breast images derived from Gd-DTPA MR and F-18-FDG PET/CT dynamic image series. Nonlinear curve fitting (Levenburg-Marquardt algorithm) based on realistic two-compartment models was performed voxel-by-voxel separately for MR (Brix) and PET (Patlak). PET dynamic series consists of 50 frames of 1-minute duration. Each consecutive PET image was nonrigidly registered to the first frame using a finite element method and fiducial skin markers. The 12 post-contrast MR images were nonrigidly registered to the precontrast frame using a free-form deformation (FFD) method. Parametric MR images were registered to parametric PET images via CT using FFD because the first PET time frame was acquired immediately after the CT image on a PET/CT scanner and is considered registered to the CT image. We conclude that nonrigid registration of PET and MR parametric images using CT data acquired during PET/CT scan and the FFD method resulted in their improved spatial coregistration. The success of this procedure was limited due to relatively large target registration error, TRE = 15.1+/-7.7 mm, as compared to spatial resolution of PET (6-7 mm), and swirling image artifacts created in MR parametric images by the FFD. Further refinement of nonrigid registration of PET and MR parametric images is necessary to enhance visualization and integration of complex diagnostic information provided by both modalities that will lead to improved diagnostic performance.

Frequency Domain Ultrasound Waveform Tomography: Breast Imaging Using a Ring Transducer

PubMed Central

Sandhu, G Y; Li, C; Roy, O; Schmidt, S; Duric, N

2016-01-01

Application of the frequency domain acoustic wave equation on data acquired from ultrasound tomography scans is shown to yield high resolution sound speed images on the order of the wavelength of the highest reconstructed frequency. Using a signal bandwidth of 0.4–1 MHz and an average sound speed of 1500 m/s, the resolution is approximately 1.5 mm. The quantitative sound speed values and morphology provided by these images have the potential to inform diagnosis and classification of breast disease. In this study, we present the formalism, practical application, and in vivo results of waveform tomography applied to breast data gathered by two different ultrasound tomography scanners that utilize ring transducers. The formalism includes a review of frequency domain modeling of the wave equation using finite difference operators as well as a review of the gradient descent method for the iterative reconstruction scheme. It is shown that the practical application of waveform tomography requires an accurate starting model, careful data processing, and a method to gradually incorporate higher frequency information into the sound speed reconstruction. Following these steps resulted in high resolution quantitative sound speed images of the breast. These images show marked improvement relative to commonly used ray tomography reconstruction methods. The robustness of the method is demonstrated by obtaining similar results from two different ultrasound tomography devices. We also compare our method to MRI to demonstrate concordant findings. The clinical data used in this work was obtained from a HIPAA compliant clinical study (IRB 040912M1F). PMID:26110909

Detection method of visible and invisible nipples on digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Chae, Seung-Hoon; Jeong, Ji-Wook; Lee, Sooyeul; Chae, Eun Young; Kim, Hak Hee; Choi, Young-Wook

2015-03-01

Digital Breast Tomosynthesis(DBT) with 3D breast image can improve detection sensitivity of breast cancer more than 2D mammogram on dense breast. The nipple location information is needed to analyze DBT. The nipple location is invaluable information in registration and as a reference point for classifying mass or micro-calcification clusters. Since there are visible nipple and invisible nipple in 2D mammogram or DBT, the nipple detection of breast must be possible to detect visible and invisible nipple of breast. The detection method of visible nipple using shape information of nipple is simple and highly efficient. However, it is difficult to detect invisible nipple because it doesn't have prominent shape. Mammary glands in breast connect nipple, anatomically. The nipple location is detected through analyzing location of mammary glands in breast. In this paper, therefore, we propose a method to detect the nipple on a breast, which has a visible or invisible nipple using changes of breast area and mammary glands, respectively. The result shows that our proposed method has average error of 2.54+/-1.47mm.

Modeling and simulation of Positron Emission Mammography (PEM) based on double-sided CdTe strip detectors

NASA Astrophysics Data System (ADS)

Ozsahin, I.; Unlu, M. Z.

2014-03-01

Breast cancer is the most common leading cause of cancer death among women. Positron Emission Tomography (PET) Mammography, also known as Positron Emission Mammography (PEM), is a method for imaging primary breast cancer. Over the past few years, PEMs based on scintillation crystals dramatically increased their importance in diagnosis and treatment of early stage breast cancer. However, these detectors have significant limitations like poor energy resolution resulting with false-negative result (missed cancer), and false-positive result which leads to suspecting cancer and suggests an unnecessary biopsy. In this work, a PEM scanner based on CdTe strip detectors is simulated via the Monte Carlo method and evaluated in terms of its spatial resolution, sensitivity, and image quality. The spatial resolution is found to be ~ 1 mm in all three directions. The results also show that CdTe strip detectors based PEM scanner can produce high resolution images for early diagnosis of breast cancer.

Enhancement of breast periphery region in digital mammography

NASA Astrophysics Data System (ADS)

Menegatti Pavan, Ana Luiza; Vacavant, Antoine; Petean Trindade, Andre; Quini, Caio Cesar; Rodrigues de Pina, Diana

2018-03-01

Volumetric breast density has been shown to be one of the strongest risk factor for breast cancer diagnosis. This metric can be estimated using digital mammograms. During mammography acquisition, breast is compressed and part of it loses contact with the paddle, resulting in an uncompressed region in periphery with thickness variation. Therefore, reliable density estimation in the breast periphery region is a problem, which affects the accuracy of volumetric breast density measurement. The aim of this study was to enhance breast periphery to solve the problem of thickness variation. Herein, we present an automatic algorithm to correct breast periphery thickness without changing pixel value from internal breast region. The correction pixel values from periphery was based on mean values over iso-distance lines from the breast skin-line using only adipose tissue information. The algorithm detects automatically the periphery region where thickness should be corrected. A correction factor was applied in breast periphery image to enhance the region. We also compare our contribution with two other algorithms from state-of-the-art, and we show its accuracy by means of different quality measures. Experienced radiologists subjectively evaluated resulting images from the tree methods in relation to original mammogram. The mean pixel value, skewness and kurtosis from histogram of the three methods were used as comparison metric. As a result, the methodology presented herein showed to be a good approach to be performed before calculating volumetric breast density.

SU-E-J-134: An Augmented-Reality Optical Imaging System for Accurate Breast Positioning During Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nazareth, D; Malhotra, H; French, S

Purpose: Breast radiotherapy, particularly electronic compensation, may involve large dose gradients and difficult patient positioning problems. We have developed a simple self-calibrating augmented-reality system, which assists in accurately and reproducibly positioning the patient, by displaying her live image from a single camera superimposed on the correct perspective projection of her 3D CT data. Our method requires only a standard digital camera capable of live-view mode, installed in the treatment suite at an approximately-known orientation and position (rotation R; translation T). Methods: A 10-sphere calibration jig was constructed and CT imaged to provide a 3D model. The (R,T) relating the cameramore » to the CT coordinate system were determined by acquiring a photograph of the jig and optimizing an objective function, which compares the true image points to points calculated with a given candidate R and T geometry. Using this geometric information, 3D CT patient data, viewed from the camera's perspective, is plotted using a Matlab routine. This image data is superimposed onto the real-time patient image, acquired by the camera, and displayed using standard live-view software. This enables the therapists to view both the patient's current and desired positions, and guide the patient into assuming the correct position. The method was evaluated using an in-house developed bolus-like breast phantom, mounted on a supporting platform, which could be tilted at various angles to simulate treatment-like geometries. Results: Our system allowed breast phantom alignment, with an accuracy of about 0.5 cm and 1 ± 0.5 degree. Better resolution could be possible using a camera with higher-zoom capabilities. Conclusion: We have developed an augmented-reality system, which combines a perspective projection of a CT image with a patient's real-time optical image. This system has the potential to improve patient setup accuracy during breast radiotherapy, and could possibly be used for other disease sites as well.« less

F18 EF5 PET/CT Imaging in Patients with Brain Metastases from Breast Cancer

DTIC Science & Technology

2012-07-01

been demonstrated to improve local control and survival in select patients after WBRT . At present we do not have any method of determining a priori...relapse after WBRT would represent a significant step forward in the management of patients with brain metastases from breast cancer. We propose to...use a noninvasive imaging method to detect residual tumor hypoxia in patients receiving WBRT . Body: Task 1. To estimate the degree of hypoxia

Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Hall, Christopher S.

2014-03-01

Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.

Early Detection of Breast Cancer by Using Handycam Camera Manipulation as Thermal Camera Imaging with Images Processing Method

NASA Astrophysics Data System (ADS)

Riantana, R.; Arie, B.; Adam, M.; Aditya, R.; Nuryani; Yahya, I.

2017-02-01

One important thing to pay attention for detecting breast cancer is breast temperature changes. Indications symptoms of breast tissue abnormalities marked by a rise in temperature of the breast. Handycam in night vision mode interferences by external infrared can penetrate into the skin better and can make an infrared image becomes clearer. The program is capable to changing images from a camcorder into a night vision thermal image by breaking RGB into Grayscale matrix structure. The matrix rearranged in the new matrix with double data type so that it can be processed into contour color chart to differentiate the distribution of body temperature. In this program are also features of contrast scale setting of the image is processed so that the color can be set as desired. There was Also a contrast adjustment feature inverse scale that is useful to reverse the color scale so that colors can be changed opposite. There is improfile function used to retrieves the intensity values of pixels along a line what we want to show the distribution of intensity in a graph of relationship between the intensity and the pixel coordinates.

Protocol for Biomarker Ratio Imaging Microscopy with Specific Application to Ductal Carcinoma In situ of the Breast

PubMed Central

Clark, Andrea J.; Petty, Howard R.

2016-01-01

This protocol describes the methods and steps involved in performing biomarker ratio imaging microscopy (BRIM) using formalin fixed paraffin-embedded (FFPE) samples of human breast tissue. The technique is based on the acquisition of two fluorescence images of the same microscopic field using two biomarkers and immunohistochemical tools. The biomarkers are selected such that one biomarker correlates with breast cancer aggressiveness while the second biomarker anti-correlates with aggressiveness. When the former image is divided by the latter image, a computed ratio image is formed that reflects the aggressiveness of tumor cells while increasing contrast and eliminating path-length and other artifacts from the image. For example, the aggressiveness of epithelial cells may be assessed by computing ratio images of N-cadherin and E-cadherin images or CD44 and CD24 images, which specifically reflect the mesenchymal or stem cell nature of the constituent cells, respectively. This methodology is illustrated for tissue samples of ductal carcinoma in situ (DCIS) and invasive breast cancer. This tool should be useful in tissue studies of experimental cancer as well as the management of cancer patients. PMID:27857940

Deep learning in mammography and breast histology, an overview and future trends.

PubMed

Hamidinekoo, Azam; Denton, Erika; Rampun, Andrik; Honnor, Kate; Zwiggelaar, Reyer

2018-07-01

Recent improvements in biomedical image analysis using deep learning based neural networks could be exploited to enhance the performance of Computer Aided Diagnosis (CAD) systems. Considering the importance of breast cancer worldwide and the promising results reported by deep learning based methods in breast imaging, an overview of the recent state-of-the-art deep learning based CAD systems developed for mammography and breast histopathology images is presented. In this study, the relationship between mammography and histopathology phenotypes is described, which takes biological aspects into account. We propose a computer based breast cancer modelling approach: the Mammography-Histology-Phenotype-Linking-Model, which develops a mapping of features/phenotypes between mammographic abnormalities and their histopathological representation. Challenges are discussed along with the potential contribution of such a system to clinical decision making and treatment management. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Vision 20/20: Mammographic breast density and its clinical applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, Kwan-Hoong, E-mail: ngkh@ummc.edu.my; Lau, Susie

2015-12-15

Breast density is a strong predictor of the failure of mammography screening to detect breast cancer and is a strong predictor of the risk of developing breast cancer. The many imaging options that are now available for imaging dense breasts show great promise, but there is still the question of determining which women are “dense” and what imaging modality is suitable for individual women. To date, mammographic breast density has been classified according to the Breast Imaging-Reporting and Data System (BI-RADS) categories from visual assessment, but this is known to be very subjective. Despite many research reports, the authors believemore » there has been a lack of physics-led and evidence-based arguments about what breast density actually is, how it should be measured, and how it should be used. In this paper, the authors attempt to start correcting this situation by reviewing the history of breast density research and the debates generated by the advocacy movement. The authors review the development of breast density estimation from pattern analysis to area-based analysis, and the current automated volumetric breast density (VBD) analysis. This is followed by a discussion on seeking the ground truth of VBD and mapping volumetric methods to BI-RADS density categories. The authors expect great improvement in VBD measurements that will satisfy the needs of radiologists, epidemiologists, surgeons, and physicists. The authors believe that they are now witnessing a paradigm shift toward personalized breast screening, which is going to see many more cancers being detected early, with the use of automated density measurement tools as an important component.« less

Overcoming sampling depth variations in the analysis of broadband hyperspectral images of breast tissue (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kho, Esther; de Boer, Lisanne L.; Van de Vijver, Koen K.; Sterenborg, Henricus J. C. M.; Ruers, Theo J. M.

2017-02-01

Worldwide, up to 40% of the breast conserving surgeries require additional operations due to positive resection margins. We propose to reduce this percentage by using hyperspectral imaging for resection margin assessment during surgery. Spectral hypercubes were collected from 26 freshly excised breast specimens with a pushbroom camera (900-1700nm). Computer simulations of the penetration depth in breast tissue suggest a strong variation in sampling depth ( 0.5-10 mm) over this wavelength range. This was confirmed with a breast tissue mimicking phantom study. Smaller penetration depths are observed in wavelength regions with high water and/or fat absorption. Consequently, tissue classification based on spectral analysis over the whole wavelength range becomes complicated. This is especially a problem in highly inhomogeneous human tissue. We developed a method, called derivative imaging, which allows accurate tissue analysis, without the impediment of dissimilar sampling volumes. A few assumptions were made based on previous research. First, the spectra acquired with our camera from breast tissue are mainly shaped by fat and water absorption. Second, tumor tissue contains less fat and more water than healthy tissue. Third, scattering slopes of different tissue types are assumed to be alike. In derivative imaging, the derivatives are calculated of wavelengths a few nanometers apart; ensuring similar penetration depths. The wavelength choice determines the accuracy of the method and the resolution. Preliminary results on 3 breast specimens indicate a classification accuracy of 93% when using wavelength regions characterized by water and fat absorption. The sampling depths at these regions are 1mm and 5mm.

SU-F-I-53: Coded Aperture Coherent Scatter Spectral Imaging of the Breast: A Monte Carlo Evaluation of Absorbed Dose

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morris, R; Lakshmanan, M; Fong, G

Purpose: Coherent scatter based imaging has shown improved contrast and molecular specificity over conventional digital mammography however the biological risks have not been quantified due to a lack of accurate information on absorbed dose. This study intends to characterize the dose distribution and average glandular dose from coded aperture coherent scatter spectral imaging of the breast. The dose deposited in the breast from this new diagnostic imaging modality has not yet been quantitatively evaluated. Here, various digitized anthropomorphic phantoms are tested in a Monte Carlo simulation to evaluate the absorbed dose distribution and average glandular dose using clinically feasible scanmore » protocols. Methods: Geant4 Monte Carlo radiation transport simulation software is used to replicate the coded aperture coherent scatter spectral imaging system. Energy sensitive, photon counting detectors are used to characterize the x-ray beam spectra for various imaging protocols. This input spectra is cross-validated with the results from XSPECT, a commercially available application that yields x-ray tube specific spectra for the operating parameters employed. XSPECT is also used to determine the appropriate number of photons emitted per mAs of tube current at a given kVp tube potential. With the implementation of the XCAT digital anthropomorphic breast phantom library, a variety of breast sizes with differing anatomical structure are evaluated. Simulations were performed with and without compression of the breast for dose comparison. Results: Through the Monte Carlo evaluation of a diverse population of breast types imaged under real-world scan conditions, a clinically relevant average glandular dose for this new imaging modality is extrapolated. Conclusion: With access to the physical coherent scatter imaging system used in the simulation, the results of this Monte Carlo study may be used to directly influence the future development of the modality to keep breast dose to a minimum while still maintaining clinically viable image quality.« less

SU-E-J-22: A Feasibility Study On KV-Based Whole Breast Radiation Patient Setup

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Q; Zhang, M; Yue, N

Purpose: In room kilovoltage x-ray (kV) imaging provides higher contrast than Megavoltage (MV) imaging with faster acquisition time compared with on-board cone-beam computed tomography (CBCT), thus improving patient setup accuracy and efficiency. In this study we evaluated the clinical feasibility of utilizing kV imaging for whole breast radiation patient setup. Methods: For six breast cancer patients with whole breast treatment plans using two opposed tangential fields, MV-based patient setup was conducted by aligning patient markers with in room lasers and MV portal images. Beam-eye viewed kV images were acquired using Varian OBI system after the set up process. In housemore » software was developed to transfer MLC blocks information overlaying onto kV images to demonstrate the field shape for verification. KV-based patient digital shift was derived by performing rigid registration between kV image and the digitally reconstructed radiography (DRR) to align the bony structure. This digital shift between kV-based and MV-based setup was defined as setup deviation. Results: Six sets of kV images were acquired for breast patients. The mean setup deviation was 2.3mm, 2.2mm and 1.8mm for anterior-posterior, superior-inferior and left-right direction respectively. The average setup deviation magnitude was 4.3±1.7mm for six patients. Patient with large breast had a larger setup deviation (4.4–6.2mm). There was no strong correlation between MV-based shift and setup deviation. Conclusion: A preliminary clinical workflow for kV-based whole breast radiation setup was established and tested. We observed setup deviation of the magnitude below than 5mm. With the benefit of providing higher contrast and MLC block overlaid on the images for treatment field verification, it is feasible to use kV imaging for breast patient setup.« less

Convolutional encoder-decoder for breast mass segmentation in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Zhang, Jun; Ghate, Sujata V.; Grimm, Lars J.; Saha, Ashirbani; Cain, Elizabeth Hope; Zhu, Zhe; Mazurowski, Maciej A.

2018-02-01

Digital breast tomosynthesis (DBT) is a relatively new modality for breast imaging that can provide detailed assessment of dense tissue within the breast. In the domains of cancer diagnosis, radiogenomics, and resident education, it is important to accurately segment breast masses. However, breast mass segmentation is a very challenging task, since mass regions have low contrast difference between their neighboring tissues. Notably, the task might become more difficult in cases that were assigned BI-RADS 0 category since this category includes many lesions that are of low conspicuity and locations that were deemed to be overlapping normal tissue upon further imaging and were not sent to biopsy. Segmentation of such lesions is of particular importance in the domain of reader performance analysis and education. In this paper, we propose a novel deep learning-based method for segmentation of BI-RADS 0 lesions in DBT. The key components of our framework are an encoding path for local-to-global feature extraction, and a decoding patch to expand the images. To address the issue of limited training data, in the training stage, we propose to sample patches not only in mass regions but also in non-mass regions. We utilize a Dice-like loss function in the proposed network to alleviate the class-imbalance problem. The preliminary results on 40 subjects show promise of our method. In addition to quantitative evaluation of the method, we present a visualization of the results that demonstrate both the performance of the algorithm as well as the difficulty of the task at hand.

Using shape contexts method for registration of contra lateral breasts in thermal images.

PubMed

Etehadtavakol, Mahnaz; Ng, Eddie Yin-Kwee; Gheissari, Niloofar

2014-12-10

To achieve symmetric boundaries for left and right breasts boundaries in thermal images by registration. The proposed method for registration consists of two steps. In the first step, shape context, an approach as presented by Belongie and Malik was applied for registration of two breast boundaries. The shape context is an approach to measure shape similarity. Two sets of finite sample points from shape contours of two breasts are then presented. Consequently, the correspondences between the two shapes are found. By finding correspondences, the sample point which has the most similar shape context is obtained. In this study, a line up transformation which maps one shape onto the other has been estimated in order to complete shape. The used of a thin plate spline permitted good estimation of a plane transformation which has capability to map unselective points from one shape onto the other. The obtained aligning transformation of boundaries points has been applied successfully to map the two breasts interior points. Some of advantages for using shape context method in this work are as follows: (1) no special land marks or key points are needed; (2) it is tolerant to all common shape deformation; and (3) although it is uncomplicated and straightforward to use, it gives remarkably powerful descriptor for point sets significantly upgrading point set registration. Results are very promising. The proposed algorithm was implemented for 32 cases. Boundary registration is done perfectly for 28 cases. We used shape contexts method that is simple and easy to implement to achieve symmetric boundaries for left and right breasts boundaries in thermal images.

Investigation of energy weighting using an energy discriminating photon counting detector for breast CT

PubMed Central

Kalluri, Kesava S.; Mahd, Mufeed; Glick, Stephen J.

2013-01-01

Purpose: Breast CT is an emerging imaging technique that can portray the breast in 3D and improve visualization of important diagnostic features. Early clinical studies have suggested that breast CT has sufficient spatial and contrast resolution for accurate detection of masses and microcalcifications in the breast, reducing structural overlap that is often a limiting factor in reading mammographic images. For a number of reasons, image quality in breast CT may be improved by use of an energy resolving photon counting detector. In this study, the authors investigate the improvements in image quality obtained when using energy weighting with an energy resolving photon counting detector as compared to that with a conventional energy integrating detector. Methods: Using computer simulation, realistic CT images of multiple breast phantoms were generated. The simulation modeled a prototype breast CT system using an amorphous silicon (a-Si), CsI based energy integrating detector with different x-ray spectra, and a hypothetical, ideal CZT based photon counting detector with capability of energy discrimination. Three biological signals of interest were modeled as spherical lesions and inserted into breast phantoms; hydroxyapatite (HA) to represent microcalcification, infiltrating ductal carcinoma (IDC), and iodine enhanced infiltrating ductal carcinoma (IIDC). Signal-to-noise ratio (SNR) of these three lesions was measured from the CT reconstructions. In addition, a psychophysical study was conducted to evaluate observer performance in detecting microcalcifications embedded into a realistic anthropomorphic breast phantom. Results: In the energy range tested, improvements in SNR with a photon counting detector using energy weighting was higher (than the energy integrating detector method) by 30%–63% and 4%–34%, for HA and IDC lesions and 12%–30% (with Al filtration) and 32%–38% (with Ce filtration) for the IIDC lesion, respectively. The average area under the receiver operating characteristic curve (AUC) for detection of microcalcifications was higher by greater than 19% (for the different energy weighting methods tested) as compared to the AUC obtained with an energy integrating detector. Conclusions: This study showed that breast CT with a CZT photon counting detector using energy weighting can provide improvements in pixel SNR, and detectability of microcalcifications as compared to that with a conventional energy integrating detector. Since a number of degrading physical factors were not modeled into the photon counting detector, this improvement should be considered as an upper bound on achievable performance. PMID:23927337

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kiarashi, Nooshin; Nolte, Adam C.; Sturgeon, Gregory M.

Purpose: Physical phantoms are essential for the development, optimization, and evaluation of x-ray breast imaging systems. Recognizing the major effect of anatomy on image quality and clinical performance, such phantoms should ideally reflect the three-dimensional structure of the human breast. Currently, there is no commercially available three-dimensional physical breast phantom that is anthropomorphic. The authors present the development of a new suite of physical breast phantoms based on human data. Methods: The phantoms were designed to match the extended cardiac-torso virtual breast phantoms that were based on dedicated breast computed tomography images of human subjects. The phantoms were fabricated bymore » high-resolution multimaterial additive manufacturing (3D printing) technology. The glandular equivalency of the photopolymer materials was measured relative to breast tissue-equivalent plastic materials. Based on the current state-of-the-art in the technology and available materials, two variations were fabricated. The first was a dual-material phantom, the Doublet. Fibroglandular tissue and skin were represented by the most radiographically dense material available; adipose tissue was represented by the least radiographically dense material. The second variation, the Singlet, was fabricated with a single material to represent fibroglandular tissue and skin. It was subsequently filled with adipose-equivalent materials including oil, beeswax, and permanent urethane-based polymer. Simulated microcalcification clusters were further included in the phantoms via crushed eggshells. The phantoms were imaged and characterized visually and quantitatively. Results: The mammographic projections and tomosynthesis reconstructed images of the fabricated phantoms yielded realistic breast background. The mammograms of the phantoms demonstrated close correlation with simulated mammographic projection images of the corresponding virtual phantoms. Furthermore, power-law descriptions of the phantom images were in general agreement with real human images. The Singlet approach offered more realistic contrast as compared to the Doublet approach, but at the expense of air bubbles and air pockets that formed during the filling process. Conclusions: The presented physical breast phantoms and their matching virtual breast phantoms offer realistic breast anatomy, patient variability, and ease of use, making them a potential candidate for performing both system quality control testing and virtual clinical trials.« less

Early Breast Cancer Diagnosis Using Microwave Imaging via Space-Frequency Algorithm

NASA Astrophysics Data System (ADS)

Vemulapalli, Spandana

The conventional breast cancer detection methods have limitations ranging from ionizing radiations, low specificity to high cost. These limitations make way for a suitable alternative called Microwave Imaging, as a screening technique in the detection of breast cancer. The discernible differences between the benign, malignant and healthy breast tissues and the ability to overcome the harmful effects of ionizing radiations make microwave imaging, a feasible breast cancer detection technique. Earlier studies have shown the variation of electrical properties of healthy and malignant tissues as a function of frequency and hence stimulates high bandwidth requirement. A Ultrawideband, Wideband and Narrowband arrays have been designed, simulated and optimized for high (44%), medium (33%) and low (7%) bandwidths respectively, using the EM (electromagnetic software) called FEKO. These arrays are then used to illuminate the breast model (phantom) and the received backscattered signals are obtained in the near field for each case. The Microwave Imaging via Space-Time (MIST) beamforming algorithm in the frequency domain, is next applied to these near field backscattered monostatic frequency response signals for the image reconstruction of the breast model. The main purpose of this investigation is to access the impact of bandwidth and implement a novel imaging technique for use in the early detection of breast cancer. Earlier studies show the implementation of the MIST imaging algorithm on the time domain signals via a frequency domain beamformer. The performance evaluation of the imaging algorithm on the frequency response signals has been carried out in the frequency domain. The energy profile of the breast in the spatial domain is created via the frequency domain Parseval's theorem. The beamformer weights calculated using these the MIST algorithm (not including the effect of the skin) has been calculated for Ultrawideband, Wideband and Narrowband arrays, respectively. Quality metrics such as dynamic range, radiometric resolution etc. are also evaluated for all the three types of arrays.

An infrared image based methodology for breast lesions screening

NASA Astrophysics Data System (ADS)

Morais, K. C. C.; Vargas, J. V. C.; Reisemberger, G. G.; Freitas, F. N. P.; Oliari, S. H.; Brioschi, M. L.; Louveira, M. H.; Spautz, C.; Dias, F. G.; Gasperin, P.; Budel, V. M.; Cordeiro, R. A. G.; Schittini, A. P. P.; Neto, C. D.

2016-05-01

The objective of this paper is to evaluate the potential of utilizing a structured methodology for breast lesions screening, based on infrared imaging temperature measurements of a healthy control group to establish expected normality ranges, and of breast cancer patients, previously diagnosed through biopsies of the affected regions. An analysis of the systematic error of the infrared camera skin temperature measurements was conducted in several different regions of the body, by direct comparison to high precision thermistor temperature measurements, showing that infrared camera temperatures are consistently around 2 °C above the thermistor temperatures. Therefore, a method of conjugated gradients is proposed to eliminate the infrared camera direct temperature measurement imprecision, by calculating the temperature difference between two points to cancel out the error. The method takes into account the human body approximate bilateral symmetry, and compares measured dimensionless temperature difference values (Δ θ bar) between two symmetric regions of the patient's breast, that takes into account the breast region, the surrounding ambient and the individual core temperatures, and doing so, the results interpretation for different individuals become simple and non subjective. The range of normal whole breast average dimensionless temperature differences for 101 healthy individuals was determined, and admitting that the breasts temperatures exhibit a unimodal normal distribution, the healthy normal range for each region was considered to be the dimensionless temperature difference plus/minus twice the standard deviation of the measurements, Δ θ bar ‾ + 2σ Δ θ bar ‾ , in order to represent 95% of the population. Forty-seven patients with previously diagnosed breast cancer through biopsies were examined with the method, which was capable of detecting breast abnormalities in 45 cases (96%). Therefore, the conjugated gradients method was considered effective in breast lesions screening through infrared imaging in order to recommend a biopsy, even with the use of a low optical resolution camera (160 × 120 pixels) and a thermal resolution of 0.1 °C, whose results were compared to the results of a higher resolution camera (320 × 240 pixels). The main conclusion is that the results demonstrate that the method has potential for utilization as a noninvasive screening exam for individuals with breast complaints, indicating whether the patient should be submitted to a biopsy or not.

Breast density quantification with cone-beam CT: A post-mortem study

PubMed Central

Johnson, Travis; Ding, Huanjun; Le, Huy Q.; Ducote, Justin L.; Molloi, Sabee

2014-01-01

Forty post-mortem breasts were imaged with a flat-panel based cone-beam x-ray CT system at 50 kVp. The feasibility of breast density quantification has been investigated using standard histogram thresholding and an automatic segmentation method based on the fuzzy c-means algorithm (FCM). The breasts were chemically decomposed into water, lipid, and protein immediately after image acquisition was completed. The percent fibroglandular volume (%FGV) from chemical analysis was used as the gold standard for breast density comparison. Both image-based segmentation techniques showed good precision in breast density quantification with high linear coefficients between the right and left breast of each pair. When comparing with the gold standard using %FGV from chemical analysis, Pearson’s r-values were estimated to be 0.983 and 0.968 for the FCM clustering and the histogram thresholding techniques, respectively. The standard error of the estimate (SEE) was also reduced from 3.92% to 2.45% by applying the automatic clustering technique. The results of the postmortem study suggested that breast tissue can be characterized in terms of water, lipid and protein contents with high accuracy by using chemical analysis, which offers a gold standard for breast density studies comparing different techniques. In the investigated image segmentation techniques, the FCM algorithm had high precision and accuracy in breast density quantification. In comparison to conventional histogram thresholding, it was more efficient and reduced inter-observer variation. PMID:24254317

A physical breast phantom for 2D and 3D x-ray imaging made through inkjet printing

NASA Astrophysics Data System (ADS)

Ikejimba, Lynda C.; Graff, Christian G.; Rosenthal, Shani; Badal, Andreu; Ghammraoui, Bahaa; Lo, Joseph Y.; Glick, Stephen J.

2017-03-01

Physical breast phantoms are used for imaging evaluation studies with 2D and 3D breast x-ray systems, serving as surrogates for human patients. However, there is a presently a limited selection of available phantoms that are realistic, in terms of containing the complex tissue architecture of the human breast. In addition, not all phantoms can be successfully utilized for both 2D and 3D breast imaging. Additionally, many of the phantoms are uniform or unrealistic in appearance, expensive, or difficult to obtain. The purpose of this work was to develop a new method to generate realistic physical breast phantoms using easy to obtain and inexpensive materials. First, analytical modeling was used to design a virtual model, which was then compressed using finite element modeling. Next, the physical phantom was realized through inkjet printing with a standard inkjet printer using parchment paper and specialized inks, formulated using silver nanoparticles and a bismuth salt. The printed phantom sheets were then aligned and held together using a custom designed support plate made of PMMA, and imaged on clinical FFDM and DBT systems. Objects of interest were also placed within the phantom to simulate microcalcifications, pathologies that often occur in the breast. The linear attenuation coefficients of the inks and parchment were compared against tissue equivalent samples and found to be similar to breast tissue. The phantom is promising for use in imaging studies and developing QC protocols.

A breast-specific, negligible-dose scatter correction technique for dedicated cone-beam breast CT: a physics-based approach to improve Hounsfield Unit accuracy

NASA Astrophysics Data System (ADS)

Yang, Kai; Burkett, George, Jr.; Boone, John M.

2014-11-01

The purpose of this research was to develop a method to correct the cupping artifact caused from x-ray scattering and to achieve consistent Hounsfield Unit (HU) values of breast tissues for a dedicated breast CT (bCT) system. The use of a beam passing array (BPA) composed of parallel-holes has been previously proposed for scatter correction in various imaging applications. In this study, we first verified the efficacy and accuracy using BPA to measure the scatter signal on a cone-beam bCT system. A systematic scatter correction approach was then developed by modeling the scatter-to-primary ratio (SPR) in projection images acquired with and without BPA. To quantitatively evaluate the improved accuracy of HU values, different breast tissue-equivalent phantoms were scanned and radially averaged HU profiles through reconstructed planes were evaluated. The dependency of the correction method on object size and number of projections was studied. A simplified application of the proposed method on five clinical patient scans was performed to demonstrate efficacy. For the typical 10-18 cm breast diameters seen in the bCT application, the proposed method can effectively correct for the cupping artifact and reduce the variation of HU values of breast equivalent material from 150 to 40 HU. The measured HU values of 100% glandular tissue, 50/50 glandular/adipose tissue, and 100% adipose tissue were approximately 46, -35, and -94, respectively. It was found that only six BPA projections were necessary to accurately implement this method, and the additional dose requirement is less than 1% of the exam dose. The proposed method can effectively correct for the cupping artifact caused from x-ray scattering and retain consistent HU values of breast tissues.

TU-F-12A-09: GLCM Texture Analysis for Normal-Tissue Toxicity: A Prospective Ultrasound Study of Acute Toxicity in Breast-Cancer Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, T; Yang, X; Curran, W

2014-06-15

Purpose: To evaluate the morphologic and structural integrity of the breast glands using sonographic textural analysis, and identify potential early imaging signatures for radiation toxicity following breast-cancer radiotherapy (RT). Methods: Thirty-eight patients receiving breast RT participated in a prospective ultrasound imaging study. Each participant received 3 ultrasound scans: 1 week before RT (baseline), and at 6-week and 3-month follow-ups. Patients were imaged with a 10-MHz ultrasound on the four quadrant of the breast. A second order statistical method of texture analysis, called gray level co-occurrence matrix (GLCM), was employed to assess RT-induced breast-tissue toxicity. The region of interest (ROI) wasmore » 28 mm × 10 mm in size at a 10 mm depth under the skin. Twenty GLCM sonographic features, ratios of the irradiated breast and the contralateral breast, were used to quantify breast-tissue toxicity. Clinical assessment of acute toxicity was conducted using the RTOG toxicity scheme. Results: Ninety-seven ultrasound studies (776 images) were analyzed; and 5 out of 20 sonographic features showed significant differences (p < 0.05) among the baseline scans, the acute toxicity grade 1 and 2 groups. These sonographic features quantified the degree of tissue damage through homogeneity, heterogeneity, randomness, and symmetry. Energy ratio value decreased from 108±0.05 (normal) to 0.99±0.05 (Grade 1) and 0.84±0.04 (Grade 2); Entropy ratio value increased from 1.01±0.01 to 1.02±0.01 and 1.04±0.01; Contrast ratio value increased from 1.03±0.03 to 1.07±0.06 and 1.21±0.09; Variance ratio value increased from 1.06±0.03 to 1.20±0.04 and 1.42±0.10; Cluster Prominence ratio value increased from 0.98±0.02 to 1.01±0.04 and 1.25±0.07. Conclusion: This work has demonstrated that the sonographic features may serve as imaging signatures to assess radiation-induced normal tissue damage. While these findings need to be validated in a larger cohort, they suggest that ultrasound imaging may be used to improve early detection of normal-tissue toxicity in breast-cancer RT.« less

Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging

PubMed Central

Yang, Yaliang; Li, Fuhai; Gao, Liang; Wang, Zhiyong; Thrall, Michael J.; Shen, Steven S.; Wong, Kelvin K.; Wong, Stephen T. C.

2011-01-01

We present a label-free, chemically-selective, quantitative imaging strategy to identify breast cancer and differentiate its subtypes using coherent anti-Stokes Raman scattering (CARS) microscopy. Human normal breast tissue, benign proliferative, as well as in situ and invasive carcinomas, were imaged ex vivo. Simply by visualizing cellular and tissue features appearing on CARS images, cancerous lesions can be readily separated from normal tissue and benign proliferative lesion. To further distinguish cancer subtypes, quantitative disease-related features, describing the geometry and distribution of cancer cell nuclei, were extracted and applied to a computerized classification system. The results show that in situ carcinoma was successfully distinguished from invasive carcinoma, while invasive ductal carcinoma (IDC) and invasive lobular carcinoma were also distinguished from each other. Furthermore, 80% of intermediate-grade IDC and 85% of high-grade IDC were correctly distinguished from each other. The proposed quantitative CARS imaging method has the potential to enable rapid diagnosis of breast cancer. PMID:21833355

The electromagnetic-trait imaging computation of traveling wave method in breast tumor microwave sensor system.

PubMed

Tao, Zhi-Fu; Han, Zhong-Ling; Yao, Meng

2011-01-01

Using the difference of dielectric constant between malignant tumor tissue and normal breast tissue, breast tumor microwave sensor system (BRATUMASS) determines the detected target of imaging electromagnetic trait by analyzing the properties of target tissue back wave obtained after near-field microwave radicalization (conelrad). The key of obtained target properties relationship and reconstructed detected space is to analyze the characteristics of the whole process from microwave transmission to back wave reception. Using traveling wave method, we derive spatial transmission properties and the relationship of the relation detected points distances, and valuate the properties of each unit by statistical valuation theory. This chapter gives the experimental data analysis results.

A statistical, task-based evaluation method for three-dimensional x-ray breast imaging systems using variable-background phantoms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Subok; Jennings, Robert; Liu Haimo

Purpose: For the last few years, development and optimization of three-dimensional (3D) x-ray breast imaging systems, such as digital breast tomosynthesis (DBT) and computed tomography, have drawn much attention from the medical imaging community, either academia or industry. However, there is still much room for understanding how to best optimize and evaluate the devices over a large space of many different system parameters and geometries. Current evaluation methods, which work well for 2D systems, do not incorporate the depth information from the 3D imaging systems. Therefore, it is critical to develop a statistically sound evaluation method to investigate the usefulnessmore » of inclusion of depth and background-variability information into the assessment and optimization of the 3D systems. Methods: In this paper, we present a mathematical framework for a statistical assessment of planar and 3D x-ray breast imaging systems. Our method is based on statistical decision theory, in particular, making use of the ideal linear observer called the Hotelling observer. We also present a physical phantom that consists of spheres of different sizes and materials for producing an ensemble of randomly varying backgrounds to be imaged for a given patient class. Lastly, we demonstrate our evaluation method in comparing laboratory mammography and three-angle DBT systems for signal detection tasks using the phantom's projection data. We compare the variable phantom case to that of a phantom of the same dimensions filled with water, which we call the uniform phantom, based on the performance of the Hotelling observer as a function of signal size and intensity. Results: Detectability trends calculated using the variable and uniform phantom methods are different from each other for both mammography and DBT systems. Conclusions: Our results indicate that measuring the system's detection performance with consideration of background variability may lead to differences in system performance estimates and comparisons. For the assessment of 3D systems, to accurately determine trade offs between image quality and radiation dose, it is critical to incorporate randomness arising from the imaging chain including background variability into system performance calculations.« less

Segmented-field radiography in scoliosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daniel, W.W.; Barnes, G.T.; Nasca, R.J.

1985-02-01

A method of scoliosis imaging using segmented fields is presented. The method is advantageous for patients requiring serial radiographic monitoring, as it results in markedly reduced radiation doses to critical organs, particularly the breast. Absorbed dose to the breast was measured to be 8.8 mrad (88 ..mu..Gy) for a full-field examination and 0.051 mrad (5.1 ..mu..Gy) for the segmented-field study. The segmented-field technique also results in improved image quality. Experience with 53 studies in 23 patients is reported.

Characterization of human breast cancer by scanning acoustic microscopy

NASA Astrophysics Data System (ADS)

Chen, Di; Malyarenko, Eugene; Seviaryn, Fedar; Yuan, Ye; Sherman, Mark; Bandyopadhyay, Sudeshna; Gierach, Gretchen; Greenway, Christopher W.; Maeva, Elena; Strumban, Emil; Duric, Neb; Maev, Roman

2013-03-01

Objectives: The purpose of this study was to characterize human breast cancer tissues by the measurement of microacoustic properties. Methods: We investigated eight breast cancer patients using acoustic microscopy. For each patient, seven blocks of tumor tissue were collected from seven different positions around a tumor mass. Frozen sections (10 micrometer, μm) of human breast cancer tissues without staining and fixation were examined in a scanning acoustic microscope with focused transducers at 80 and 200 MHz. Hematoxylin and Eosin (H and E) stained sections from the same frozen breast cancer tissues were imaged by optical microscopy for comparison. Results: The results of acoustic imaging showed that acoustic attenuation and sound speed in cancer cell-rich tissue regions were significantly decreased compared with the surrounding tissue regions, where most components are normal cells/tissues, such as fibroblasts, connective tissue and lymphocytes. Our observation also showed that the ultrasonic properties were influenced by arrangements of cells and tissue patterns. Conclusions: Our data demonstrate that attenuation and sound speed imaging can provide biomechanical information of the tumor and normal tissues. The results also demonstrate the potential of acoustic microscopy as an auxiliary method for operative detection and localization of cancer affected regions.

MR guided breast interventions: role in biopsy targeting and lumpectomies

PubMed Central

Jagadeesan, Jayender; Richman, Danielle M; Kacher, Daniel F

2015-01-01

Synopsis Contrast enhanced breast MRI is increasingly being used to diagnose breast cancer and to perform biopsy procedures. The American Cancer Society has advised women at high risk for breast cancer to have breast MRI screening as an adjunct to screening mammography. This article places special emphasis on biopsy and operative planning involving MRI and reviews utility of breast MRI in monitoring response to neoadjuvant chemotherapy. We describe peer-reviewed data on currently accepted MR-guided therapeutic methods for addressing benign and malignant breast diseases, including intraoperative imaging. PMID:26499274

Medical auditing of whole-breast screening ultrasonography

PubMed Central

2017-01-01

Since breast ultrasonography (US) has been used as an adjunctive screening modality in women with dense breasts, the need has arisen to evaluate and monitor its possible harm and benefits in comparison with other screening modalities such as mammography. Recently, the fifth edition of the Breast Imaging Reporting and Data System published by the American College of Radiology has suggested auditing methods for screening breast US. However, the method proposed therein is slightly different from how diagnostic performance was calculated in previous studies on screening breast US. In this article, the background and core aspects of medical audits of breast cancer screening will be reviewed to provide an introduction to the medical auditing of screening breast US, with the goal of helping radiologists to understand and identify potential ways to improve outcomes. PMID:28322034

Medical auditing of whole-breast screening ultrasonography.

PubMed

Kim, Min Jung

2017-07-01

Since breast ultrasonography (US) has been used as an adjunctive screening modality in women with dense breasts, the need has arisen to evaluate and monitor its possible harm and benefits in comparison with other screening modalities such as mammography. Recently, the fifth edition of the Breast Imaging Reporting and Data System published by the American College of Radiology has suggested auditing methods for screening breast US. However, the method proposed therein is slightly different from how diagnostic performance was calculated in previous studies on screening breast US. In this article, the background and core aspects of medical audits of breast cancer screening will be reviewed to provide an introduction to the medical auditing of screening breast US, with the goal of helping radiologists to understand and identify potential ways to improve outcomes.

Breast volumetric analysis for aesthetic planning in breast reconstruction: a literature review of techniques

PubMed Central

Rozen, Warren Matthew; Spychal, Robert T.; Hunter-Smith, David J.

2016-01-01

Background Accurate volumetric analysis is an essential component of preoperative planning in both reconstructive and aesthetic breast procedures towards achieving symmetrization and patient-satisfactory outcome. Numerous comparative studies and reviews of individual techniques have been reported. However, a unifying review of all techniques comparing their accuracy, reliability, and practicality has been lacking. Methods A review of the published English literature dating from 1950 to 2015 using databases, such as PubMed, Medline, Web of Science, and EMBASE, was undertaken. Results Since Bouman’s first description of water displacement method, a range of volumetric assessment techniques have been described: thermoplastic casting, direct anthropomorphic measurement, two-dimensional (2D) imaging, and computed tomography (CT)/magnetic resonance imaging (MRI) scans. However, most have been unreliable, difficult to execute and demonstrate limited practicability. Introduction of 3D surface imaging has revolutionized the field due to its ease of use, fast speed, accuracy, and reliability. However, its widespread use has been limited by its high cost and lack of high level of evidence. Recent developments have unveiled the first web-based 3D surface imaging program, 4D imaging, and 3D printing. Conclusions Despite its importance, an accurate, reliable, and simple breast volumetric analysis tool has been elusive until the introduction of 3D surface imaging technology. However, its high cost has limited its wide usage. Novel adjunct technologies, such as web-based 3D surface imaging program, 4D imaging, and 3D printing, appear promising. PMID:27047788

Similarity estimation for reference image retrieval in mammograms using convolutional neural network

NASA Astrophysics Data System (ADS)

Muramatsu, Chisako; Higuchi, Shunichi; Morita, Takako; Oiwa, Mikinao; Fujita, Hiroshi

2018-02-01

Periodic breast cancer screening with mammography is considered effective in decreasing breast cancer mortality. For screening programs to be successful, an intelligent image analytic system may support radiologists' efficient image interpretation. In our previous studies, we have investigated image retrieval schemes for diagnostic references of breast lesions on mammograms and ultrasound images. Using a machine learning method, reliable similarity measures that agree with radiologists' similarity were determined and relevant images could be retrieved. However, our previous method includes a feature extraction step, in which hand crafted features were determined based on manual outlines of the masses. Obtaining the manual outlines of masses is not practical in clinical practice and such data would be operator-dependent. In this study, we investigated a similarity estimation scheme using a convolutional neural network (CNN) to skip such procedure and to determine data-driven similarity scores. By using CNN as feature extractor, in which extracted features were employed in determination of similarity measures with a conventional 3-layered neural network, the determined similarity measures were correlated well with the subjective ratings and the precision of retrieving diagnostically relevant images was comparable with that of the conventional method using handcrafted features. By using CNN for determination of similarity measure directly, the result was also comparable. By optimizing the network parameters, results may be further improved. The proposed method has a potential usefulness in determination of similarity measure without precise lesion outlines for retrieval of similar mass images on mammograms.

Recurrent neural networks for breast lesion classification based on DCE-MRIs

NASA Astrophysics Data System (ADS)

Antropova, Natasha; Huynh, Benjamin; Giger, Maryellen

2018-02-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a significant role in breast cancer screening, cancer staging, and monitoring response to therapy. Recently, deep learning methods are being rapidly incorporated in image-based breast cancer diagnosis and prognosis. However, most of the current deep learning methods make clinical decisions based on 2-dimentional (2D) or 3D images and are not well suited for temporal image data. In this study, we develop a deep learning methodology that enables integration of clinically valuable temporal components of DCE-MRIs into deep learning-based lesion classification. Our work is performed on a database of 703 DCE-MRI cases for the task of distinguishing benign and malignant lesions, and uses the area under the ROC curve (AUC) as the performance metric in conducting that task. We train a recurrent neural network, specifically a long short-term memory network (LSTM), on sequences of image features extracted from the dynamic MRI sequences. These features are extracted with VGGNet, a convolutional neural network pre-trained on a large dataset of natural images ImageNet. The features are obtained from various levels of the network, to capture low-, mid-, and high-level information about the lesion. Compared to a classification method that takes as input only images at a single time-point (yielding an AUC = 0.81 (se = 0.04)), our LSTM method improves lesion classification with an AUC of 0.85 (se = 0.03).

Testing a dual-modality system that combines full-field digital mammography and automated breast ultrasound

PubMed Central

Vaughan, Christopher L; Douglas, Tania S; Said-Hartley, Qonita; Baasch, Roland V; Boonzaier, James A; Goemans, Brian C; Harverson, John; Mingay, Michael W; Omar, Shuaib; Smith, Raphael V; Venter, Nielen C; Wilson, Heidi S

2015-01-01

Purpose The aim of this study was to test a novel dual-modality imaging system that combines full-field digital mammography (FFDM) and automated breast ultrasound (ABUS) in a single platform. Our Aceso system, named after the Greek goddess of healing, was specifically designed for the early detection of cancer in women with dense breast tissue. Materials and Methods Aceso was first tested using two industry standards: a CDMAM phantom as endorsed by EUREF was used to assess the FFDM images; and the CIRS 040GSE ultrasound phantom was imaged to evaluate the quality of the ABUS images. In addition, 58 women participated in a clinical trial: 51 were healthy volunteers aged between 40 and 65, while 7 were patients referred by the breast clinic, 6 of whom had biopsy-proven breast cancer. Results The CDMAM tests showed that the FFDM results were “acceptable” but fell short of “achievable” which was attributed to the low dose used. The ABUS images had good depth penetration (80 mm) and adequate axial resolution (0.5 mm) but the lateral resolution of 2 mm was judged to be too coarse. In a 42-year old volunteer with extremely dense breast tissue, the ABUS modality detected a lesion (a benign cyst) that was mammographically occult in the FFDM image. For a 73-year old patient with fatty breasts, a malignant lesion was successfully detected and co-registered in the FFDM and ABUS images. On average, each woman spent less than 11 minutes in the acquisition room. Conclusions While there is room for improvement in the quality of both the FFDM and ABUS images, Aceso has demonstrated its ability to acquire clinically meaningful images for a range of women with varying breast densities and therefore has potential as a screening device. PMID:27133694

Association between background parenchymal enhancement of breast MRI and BIRADS rating change in the subsequent screening

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

2018-03-01

Although breast magnetic resonance imaging (MRI) has been used as a breast cancer screening modality for high-risk women, its cancer detection yield remains low (i.e., <= 3%). Thus, increasing breast MRI screening efficacy and cancer detection yield is an important clinical issue in breast cancer screening. In this study, we investigated association between the background parenchymal enhancement (BPE) of breast MRI and the change of diagnostic (BIRADS) status in the next subsequent breast MRI screening. A dataset with 65 breast MRI screening cases was retrospectively assembled. All cases were rated BIRADS-2 (benign findings). In the subsequent screening, 4 cases were malignant (BIRADS-6), 48 remained BIRADS-2 and 13 were downgraded to negative (BIRADS-1). A computer-aided detection scheme was applied to process images of the first set of breast MRI screening. Total of 33 features were computed including texture feature and global BPE features. Texture features were computed from either a gray-level co-occurrence matrix or a gray level run length matrix. Ten global BPE features were also initially computed from two breast regions and bilateral difference between the left and right breasts. Box-plot based analysis shows positive association between texture features and BIRADS rating levels in the second screening. Furthermore, a logistic regression model was built using optimal features selected by a CFS based feature selection method. Using a leave-one-case-out based cross-validation method, classification yielded an overall 75% accuracy in predicting the improvement (or downgrade) of diagnostic status (to BIRAD-1) in the subsequent breast MRI screening. This study demonstrated potential of developing a new quantitative imaging marker to predict diagnostic status change in the short-term, which may help eliminate a high fraction of unnecessary repeated breast MRI screenings and increase the cancer detection yield.

A 3T Sodium and Proton Composite Array Breast Coil

PubMed Central

Kaggie, Joshua D.; Hadley, J. Rock; Badal, James; Campbell, John R.; Park, Daniel J.; Parker, Dennis L.; Morrell, Glen; Newbould, Rexford D.; Wood, Ali F.; Bangerter, Neal K.

2013-01-01

Purpose The objective of this study was to determine whether a sodium phased array would improve sodium breast MRI at 3T. The secondary objective was to create acceptable proton images with the sodium phased array in place. Methods A novel composite array for combined proton/sodium 3T breast MRI is compared to a coil with a single proton and sodium channel. The composite array consists of a 7-channel sodium receive array, a larger sodium transmit coil, and a 4-channel proton transceive array. The new composite array design utilizes smaller sodium receive loops than typically used in sodium imaging, uses novel decoupling methods between the receive loops and transmit loops, and uses a novel multi-channel proton transceive coil. The proton transceive coil reduces coupling between proton and sodium elements by intersecting the constituent loops to reduce their mutual inductance. The coil used for comparison consists of a concentric sodium and proton loop with passive decoupling traps. Results The composite array coil demonstrates a 2–5x improvement in SNR for sodium imaging and similar SNR for proton imaging when compared to a simple single-loop dual resonant design. Conclusion The improved SNR of the composite array gives breast sodium images of unprecedented quality in reasonable scan times. PMID:24105740

Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

NASA Astrophysics Data System (ADS)

Hopp, T.; Zapf, M.; Ruiter, N. V.

2014-03-01

An essential processing step for comparison of Ultrasound Computer Tomography images to other modalities, as well as for the use in further image processing, is to segment the breast from the background. In this work we present a (semi-) automated 3D segmentation method which is based on the detection of the breast boundary in coronal slice images and a subsequent surface fitting. The method was evaluated using a software phantom and in-vivo data. The fully automatically processed phantom results showed that a segmentation of approx. 10% of the slices of a dataset is sufficient to recover the overall breast shape. Application to 16 in-vivo datasets was performed successfully using semi-automated processing, i.e. using a graphical user interface for manual corrections of the automated breast boundary detection. The processing time for the segmentation of an in-vivo dataset could be significantly reduced by a factor of four compared to a fully manual segmentation. Comparison to manually segmented images identified a smoother surface for the semi-automated segmentation with an average of 11% of differing voxels and an average surface deviation of 2mm. Limitations of the edge detection may be overcome by future updates of the KIT USCT system, allowing a fully-automated usage of our segmentation approach.

Comparative study on the performance of textural image features for active contour segmentation.

PubMed

Moraru, Luminita; Moldovanu, Simona

2012-07-01

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard deviation textural feature and a 5×5 kernel, our curve evolution was able to produce results close to the minimal area error rate (namely 8.88% for breast images and 10.82% for liver images). The image resolution was evaluated using the contrast-to-gradient method. The experiments showed promising segmentation results.

Availability of Advanced Breast Imaging at Screening Facilities Serving Vulnerable Populations

PubMed Central

Lee, Christoph I.; Bogart, Andy; Germino, Jessica C.; Goldman, L. Elizabeth; Hubbard, Rebecca A.; Haas, Jennifer S.; Hill, Deirdre A.; Tosteson, Anna N.A.; Alford-Teaster, Jennifer A.; DeMartini, Wendy B.; Lehman, Constance D.; Onega, Tracy L.

2015-01-01

Objective Among vulnerable women, unequal access to advanced breast imaging modalities beyond screening mammography may lead to delays in cancer diagnosis and unfavorable outcomes. We aimed to compare on-site availability of advanced breast imaging services (ultrasound (US), magnetic resonance imaging (MRI), and image-guided biopsy) between imaging facilities serving vulnerable patient populations and those serving non-vulnerable populations. Setting 73 United States imaging facilities across five Breast Cancer Surveillance Consortium regional registries during calendar years 2011–2012. Methods We examined facility and patient characteristics across a large, national sample of imaging facilities and patients served. We characterized facilities as serving vulnerable populations based on the proportion of mammograms performed on women with lower educational attainment, lower median income, racial/ethnic minority status, and rural residence. We performed multivariable logistic regression to determine relative risks of on-site availability of advanced imaging at facilities serving vulnerable women versus facilities serving non-vulnerable women. Results Facilities serving vulnerable populations were as likely (RR for MRI = 0.71 [95% CI 0.42, 1.19]; RR for MRI-guided biopsy = 1.07 [0.61, 1.90]; RR for stereotactic biopsy = 1.18 [0.75, 1.85]) or more likely (RR for US = 1.38 [95% CI 1.09, 1.74]; RR for US-guided biopsy = 1.67 [1.30, 2.14]) to offer advanced breast imaging services as those serving non-vulnerable populations. Conclusions Advanced breast imaging services are physically available on-site for vulnerable women in the United States, but it is unknown whether factors such as insurance coverage or out-of-pocket costs might limit their use. PMID:26078275

Photoacoustic imaging of breast tumor vascularization: a comparison with MRI and histopathology

NASA Astrophysics Data System (ADS)

Heijblom, Michelle; Piras, Daniele; van den Engh, Frank M.; Klaase, Joost M.; Brinkhuis, Mariël.; Steenbergen, Wiendelt; Manohar, Srirang

2013-06-01

Breast cancer is the most common form of cancer and the leading cause of cancer death among females. Early diagnosis improves the survival chances for the disease and that is why there is an ongoing search for improved methods for visualizing breast cancer. One of the hallmarks of breast cancer is the increase in tumor vascularization that is associated with angiogenesis: a crucial factor for survival of malignancies. Photoacoustic imaging can visualize the malignancyassociated increased hemoglobin concentration with optical contrast and ultrasound resolution, without the use of ionizing radiation or contrast agents and is therefore theoretically an ideal method for breast imaging. Previous clinical studies using the Twente Photoacoustic Mammoscope (PAM), which works in forward mode using a single wavelength (1064 nm), showed that malignancies can indeed be identified in the photoacoustic imaging volume as high contrast areas. However, the specific appearance of the malignancies led to questions about the contrast mechanism in relation to tumor vascularization. In this study, the photoacoustic lesion appearance obtained with an updated version of PAM is compared with the lesion appearance on Magnetic Resonance Imaging (MRI), both in general (19 patients) and on an individual basis (7 patients). Further, in 3 patients an extended histopathology protocol is being performed in which malignancies are stained for vascularity using an endothelial antibody: CD31. The correspondence between PAM and MRI and between PAM and histopathology makes it likely that the high photoacoustic contrast at 1064 nm is indeed largely the consequence of the increased tumor vascularization.

Automated data selection method to improve robustness of diffuse optical tomography for breast cancer imaging

PubMed Central

Vavadi, Hamed; Zhu, Quing

2016-01-01

Imaging-guided near infrared diffuse optical tomography (DOT) has demonstrated a great potential as an adjunct modality for differentiation of malignant and benign breast lesions and for monitoring treatment response of breast cancers. However, diffused light measurements are sensitive to artifacts caused by outliers and errors in measurements due to probe-tissue coupling, patient and probe motions, and tissue heterogeneity. In general, pre-processing of the measurements is needed by experienced users to manually remove these outliers and therefore reduce imaging artifacts. An automated method of outlier removal, data selection, and filtering for diffuse optical tomography is introduced in this manuscript. This method consists of multiple steps to first combine several data sets collected from the same patient at contralateral normal breast and form a single robust reference data set using statistical tests and linear fitting of the measurements. The second step improves the perturbation measurements by filtering out outliers from the lesion site measurements using model based analysis. The results of 20 malignant and benign cases show similar performance between manual data processing and automated processing and improvement in tissue characterization of malignant to benign ratio by about 27%. PMID:27867711

Inverse imaging of the breast with a material classification technique.

PubMed

Manry, C W; Broschat, S L

1998-03-01

In recent publications [Chew et al., IEEE Trans. Blomed. Eng. BME-9, 218-225 (1990); Borup et al., Ultrason. Imaging 14, 69-85 (1992)] the inverse imaging problem has been solved by means of a two-step iterative method. In this paper, a third step is introduced for ultrasound imaging of the breast. In this step, which is based on statistical pattern recognition, classification of tissue types and a priori knowledge of the anatomy of the breast are integrated into the iterative method. Use of this material classification technique results in more rapid convergence to the inverse solution--approximately 40% fewer iterations are required--as well as greater accuracy. In addition, tumors are detected early in the reconstruction process. Results for reconstructions of a simple two-dimensional model of the human breast are presented. These reconstructions are extremely accurate when system noise and variations in tissue parameters are not too great. However, for the algorithm used, degradation of the reconstructions and divergence from the correct solution occur when system noise and variations in parameters exceed threshold values. Even in this case, however, tumors are still identified within a few iterations.

Heterodyne frequency-domain multispectral diffuse optical tomography of breast cancer in the parallel-plane transmission geometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ban, H. Y.; Kavuri, V. C., E-mail: venk@physics.up

Purpose: The authors introduce a state-of-the-art all-optical clinical diffuse optical tomography (DOT) imaging instrument which collects spatially dense, multispectral, frequency-domain breast data in the parallel-plate geometry. Methods: The instrument utilizes a CCD-based heterodyne detection scheme that permits massively parallel detection of diffuse photon density wave amplitude and phase for a large number of source–detector pairs (10{sup 6}). The stand-alone clinical DOT instrument thus offers high spatial resolution with reduced crosstalk between absorption and scattering. Other novel features include a fringe profilometry system for breast boundary segmentation, real-time data normalization, and a patient bed design which permits both axial and sagittalmore » breast measurements. Results: The authors validated the instrument using tissue simulating phantoms with two different chromophore-containing targets and one scattering target. The authors also demonstrated the instrument in a case study breast cancer patient; the reconstructed 3D image of endogenous chromophores and scattering gave tumor localization in agreement with MRI. Conclusions: Imaging with a novel parallel-plate DOT breast imager that employs highly parallel, high-resolution CCD detection in the frequency-domain was demonstrated.« less

Toward a fusion of optical coherence tomography and hyperspectral imaging for poultry meat quality assessment

USDA-ARS?s Scientific Manuscript database

An emerging poultry meat quality concern is associated with chicken breast fillets having an uncharacteristically hard or rigid feel (called the wooden breast condition). The cause of the wooden breast condition is still largely unknown, and there is no single objective evaluation method or system k...

Breast Cancer Detection by B7-H3-Targeted Ultrasound Molecular Imaging.

PubMed

Bachawal, Sunitha V; Jensen, Kristin C; Wilson, Katheryne E; Tian, Lu; Lutz, Amelie M; Willmann, Jürgen K

2015-06-15

Ultrasound complements mammography as an imaging modality for breast cancer detection, especially in patients with dense breast tissue, but its utility is limited by low diagnostic accuracy. One emerging molecular tool to address this limitation involves contrast-enhanced ultrasound using microbubbles targeted to molecular signatures on tumor neovasculature. In this study, we illustrate how tumor vascular expression of B7-H3 (CD276), a member of the B7 family of ligands for T-cell coregulatory receptors, can be incorporated into an ultrasound method that can distinguish normal, benign, precursor, and malignant breast pathologies for diagnostic purposes. Through an IHC analysis of 248 human breast specimens, we found that vascular expression of B7-H3 was selectively and significantly higher in breast cancer tissues. B7-H3 immunostaining on blood vessels distinguished benign/precursors from malignant lesions with high diagnostic accuracy in human specimens. In a transgenic mouse model of cancer, the B7-H3-targeted ultrasound imaging signal was increased significantly in breast cancer tissues and highly correlated with ex vivo expression levels of B7-H3 on quantitative immunofluorescence. Our findings offer a preclinical proof of concept for the use of B7-H3-targeted ultrasound molecular imaging as a tool to improve the diagnostic accuracy of breast cancer detection in patients. ©2015 American Association for Cancer Research.

Fluorescently labeled bevacizumab in human breast cancer: defining the classification threshold

NASA Astrophysics Data System (ADS)

Koch, Maximilian; de Jong, Johannes S.; Glatz, Jürgen; Symvoulidis, Panagiotis; Lamberts, Laetitia E.; Adams, Arthur L. L.; Kranendonk, Mariëtte E. G.; Terwisscha van Scheltinga, Anton G. T.; Aichler, Michaela; Jansen, Liesbeth; de Vries, Jakob; Lub-de Hooge, Marjolijn N.; Schröder, Carolien P.; Jorritsma-Smit, Annelies; Linssen, Matthijs D.; de Boer, Esther; van der Vegt, Bert; Nagengast, Wouter B.; Elias, Sjoerd G.; Oliveira, Sabrina; Witkamp, Arjen J.; Mali, Willem P. Th. M.; Van der Wall, Elsken; Garcia-Allende, P. Beatriz; van Diest, Paul J.; de Vries, Elisabeth G. E.; Walch, Axel; van Dam, Gooitzen M.; Ntziachristos, Vasilis

2017-07-01

In-vivo fluorescently labelled drug (bevacizumab) breast cancer specimen where obtained from patients. We propose a new structured method to determine the optimal classification threshold in targeted fluorescence intra-operative imaging.

Improved Resolution and Reduced Clutter in Ultra-Wideband Microwave Imaging Using Cross-Correlated Back Projection: Experimental and Numerical Results

PubMed Central

Jacobsen, S.; Birkelund, Y.

2010-01-01

Microwave breast cancer detection is based on the dielectric contrast between healthy and malignant tissue. This radar-based imaging method involves illumination of the breast with an ultra-wideband pulse. Detection of tumors within the breast is achieved by some selected focusing technique. Image formation algorithms are tailored to enhance tumor responses and reduce early-time and late-time clutter associated with skin reflections and heterogeneity of breast tissue. In this contribution, we evaluate the performance of the so-called cross-correlated back projection imaging scheme by using a scanning system in phantom experiments. Supplementary numerical modeling based on commercial software is also presented. The phantom is synthetically scanned with a broadband elliptical antenna in a mono-static configuration. The respective signals are pre-processed by a data-adaptive RLS algorithm in order to remove artifacts caused by antenna reverberations and signal clutter. Successful detection of a 7 mm diameter cylindrical tumor immersed in a low permittivity medium was achieved in all cases. Selecting the widely used delay-and-sum (DAS) beamforming algorithm as a benchmark, we show that correlation based imaging methods improve the signal-to-clutter ratio by at least 10 dB and improves spatial resolution through a reduction of the imaged peak full-width half maximum (FWHM) of about 40–50%. PMID:21331362

Improved resolution and reduced clutter in ultra-wideband microwave imaging using cross-correlated back projection: experimental and numerical results.

PubMed

Jacobsen, S; Birkelund, Y

2010-01-01

Microwave breast cancer detection is based on the dielectric contrast between healthy and malignant tissue. This radar-based imaging method involves illumination of the breast with an ultra-wideband pulse. Detection of tumors within the breast is achieved by some selected focusing technique. Image formation algorithms are tailored to enhance tumor responses and reduce early-time and late-time clutter associated with skin reflections and heterogeneity of breast tissue. In this contribution, we evaluate the performance of the so-called cross-correlated back projection imaging scheme by using a scanning system in phantom experiments. Supplementary numerical modeling based on commercial software is also presented. The phantom is synthetically scanned with a broadband elliptical antenna in a mono-static configuration. The respective signals are pre-processed by a data-adaptive RLS algorithm in order to remove artifacts caused by antenna reverberations and signal clutter. Successful detection of a 7 mm diameter cylindrical tumor immersed in a low permittivity medium was achieved in all cases. Selecting the widely used delay-and-sum (DAS) beamforming algorithm as a benchmark, we show that correlation based imaging methods improve the signal-to-clutter ratio by at least 10 dB and improves spatial resolution through a reduction of the imaged peak full-width half maximum (FWHM) of about 40-50%.

Integration of microwave tomography with magnetic resonance for improved breast imaging

PubMed Central

Meaney, Paul M.; Golnabi, Amir H.; Epstein, Neil R.; Geimer, Shireen D.; Fanning, Margaret W.; Weaver, John B.; Paulsen, Keith D.

2013-01-01

Purpose: Breast magnetic resonance imaging is highly sensitive but not very specific for the detection of breast cancer. Opportunities exist to supplement the image acquisition with a more specific modality provided the technical challenges of meeting space limitations inside the bore, restricted breast access, and electromagnetic compatibility requirements can be overcome. Magnetic resonance (MR) and microwave tomography (MT) are complementary and synergistic because the high resolution of MR is used to encode spatial priors on breast geometry and internal parenchymal features that have distinct electrical properties (i.e., fat vs fibroglandular tissue) for microwave tomography. Methods: The authors have overcome integration challenges associated with combining MT with MR to produce a new coregistered, multimodality breast imaging platform—magnetic resonance microwave tomography, including: substantial illumination tank size reduction specific to the confined MR bore diameter, minimization of metal content and composition, reduction of metal artifacts in the MR images, and suppression of unwanted MT multipath signals. Results: MR SNR exceeding 40 dB can be obtained. Proper filtering of MR signals reduces MT data degradation allowing MT SNR of 20 dB to be obtained, which is sufficient for image reconstruction. When MR spatial priors are incorporated into the recovery of MT property estimates, the errors between the recovered versus actual dielectric properties approach 5%. Conclusions: The phantom and human subject exams presented here are the first demonstration of combining MT with MR to improve the accuracy of the reconstructed MT images. PMID:24089930

Intraductal location of the sclerosing adenosis of the breast.

PubMed

Unal, Bulent; Gur, A Serhat; Bhargava, Rohit; Edington, Howard; Ahrendt, Gretchen; Soran, Atilla

2009-01-01

Sclerosing adenosis is a benign breast disease with non-specific images on ultrasound or mammogram. It can mimic infiltrating carcinoma when the above mentioned imaging techniques are used. Herein we present a patient with breast cancer who received neoadjuvant chemotherapy and subsequently underwent mastectomy. Ductoscopy was performed to the mastectomised breast specimen as per the ductoscopy research protocol. Ductoscopy revealed several nodular lesions in the duct with no additional demonstrable intraductal pathology. The lesions were reported as sclerosing adenosis by pathologist. As to our knowledge, this is the first case in literature that demonstrates the use of ductoscopy in diagnosing the sclerosing adenosis in the breast tissue. Ductoscopy and development of ductoscopy guided biopsy techniques may be used as an early diagnostic method for the ductal breast lesions (Fig. 2, Ref. 10). Full Text (Free, PDF) www.bmj.sk.

Automatic detection of the breast border and nipple position on digital mammograms using genetic algorithm for asymmetry approach to detection of microcalcifications.

PubMed

Karnan, M; Thangavel, K

2007-07-01

The presence of microcalcifications in breast tissue is one of the most incident signs considered by radiologist for an early diagnosis of breast cancer, which is one of the most common forms of cancer among women. In this paper, the Genetic Algorithm (GA) is proposed for automatic look at commonly prone area the breast border and nipple position to discover the suspicious regions on digital mammograms based on asymmetries between left and right breast image. The basic idea of the asymmetry approach is to scan left and right images are subtracted to extract the suspicious region. The proposed system consists of two steps: First, the mammogram images are enhanced using median filter, normalize the image, at the pectoral muscle region is excluding the border of the mammogram and comparing for both left and right images from the binary image. Further GA is applied to magnify the detected border. The figure of merit is calculated to evaluate whether the detected border is exact or not. And the nipple position is identified using GA. The some comparisons method is adopted for detection of suspected area. Second, using the border points and nipple position as the reference the mammogram images are aligned and subtracted to extract the suspicious region. The algorithms are tested on 114 abnormal digitized mammograms from Mammogram Image Analysis Society database.

Breast Mass Detection in Digital Mammogram Based on Gestalt Psychology

PubMed Central

Bu, Qirong; Liu, Feihong; Zhang, Min; Ren, Yu; Lv, Yi

2018-01-01

Inspired by gestalt psychology, we combine human cognitive characteristics with knowledge of radiologists in medical image analysis. In this paper, a novel framework is proposed to detect breast masses in digitized mammograms. It can be divided into three modules: sensation integration, semantic integration, and verification. After analyzing the progress of radiologist's mammography screening, a series of visual rules based on the morphological characteristics of breast masses are presented and quantified by mathematical methods. The framework can be seen as an effective trade-off between bottom-up sensation and top-down recognition methods. This is a new exploratory method for the automatic detection of lesions. The experiments are performed on Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM) data sets. The sensitivity reached to 92% at 1.94 false positive per image (FPI) on MIAS and 93.84% at 2.21 FPI on DDSM. Our framework has achieved a better performance compared with other algorithms. PMID:29854359

Maximized Inter-Class Weighted Mean for Fast and Accurate Mitosis Cells Detection in Breast Cancer Histopathology Images.

PubMed

Nateghi, Ramin; Danyali, Habibollah; Helfroush, Mohammad Sadegh

2017-08-14

Based on the Nottingham criteria, the number of mitosis cells in histopathological slides is an important factor in diagnosis and grading of breast cancer. For manual grading of mitosis cells, histopathology slides of the tissue are examined by pathologists at 40× magnification for each patient. This task is very difficult and time-consuming even for experts. In this paper, a fully automated method is presented for accurate detection of mitosis cells in histopathology slide images. First a method based on maximum-likelihood is employed for segmentation and extraction of mitosis cell. Then a novel Maximized Inter-class Weighted Mean (MIWM) method is proposed that aims at reducing the number of extracted non-mitosis candidates that results in reducing the false positive mitosis detection rate. Finally, segmented candidates are classified into mitosis and non-mitosis classes by using a support vector machine (SVM) classifier. Experimental results demonstrate a significant improvement in accuracy of mitosis cells detection in different grades of breast cancer histopathological images.

A Decade of Change: An Institutional Experience with Breast Surgery in 1995 and 2005

PubMed Central

Guth, Amber A.; Shanker, Beth Ann; Roses, Daniel F.; Axelrod, Deborah; Singh, Baljit; Toth, Hildegard; Shapiro, Richard L.; Hiotis, Karen; Diflo, Thomas; Cangiarella, Joan F.

2008-01-01

Introduction: With the adoption of routine screening mammography, breast cancers are being diagnosed at earlier stages, with DCIS now accouting for 22.5% of all newly diagnosed breast cancers. This has been attributed to both increased breast cancer awareness and improvements in breast imaging techniques. How have these changes, including the increased use of image-guided sampling techniques, influenced the clinical practice of breast surgery? Methods: The institutional pathology database was queried for all breast surgeries, including breast reconstruction, performed in 1995 and 2005. Cosmetic procedures were excluded. The results were analysed utilizing the Chi-square test. Results: Surgical indications changed during 10-year study period, with an increase in preoperatively diagnosed cancers undergoing definitive surgical management. ADH, and to a lesser extent, ALH, became indications for surgical excision. Fewer surgical biopsies were performed for indeterminate abnormalities on breast imaging, due to the introduction of stereotactic large core biopsy. While the rate of benign breast biopsies remained constant, there was a higher percentage of precancerous and DCIS cases in 2005. The overall rate of mastectomy decreased from 36.8% in 1995 to 14.5% in 2005. With the increase in sentinel node procedures, the rate of ALND dropped from 18.3% to 13.7%. Accompanying the increased recognition of early-stage cancers, the rate of positive ALND also decreased, from 43.3% to 25.0%. Conclusions: While the rate of benign breast biopsies has remained constant over a recent 10-year period, fewer diagnostic surgical image-guided biopsies were performed in 2005. A greater percentage of patients with breast cancer or preinvasive disease have these diagnoses determined before surgery. More preinvasive and Stage 0 cancers are undergoing surgical management. Earlier stage invasive cancers are being detected, reflected by the lower incidence of axillary nodal metastases. PMID:21655372

Design and evaluation of a grid reciprocation scheme for use in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Patel, Tushita; Sporkin, Helen; Peppard, Heather; Williams, Mark B.

2016-03-01

This work describes a methodology for efficient removal of scatter radiation during digital breast tomosynthesis (DBT). The goal of this approach is to enable grid image obscuration without a large increase in radiation dose by minimizing misalignment of the grid focal point (GFP) and x-ray focal spot (XFS) during grid reciprocation. Hardware for the motion scheme was built and tested on the dual modality breast tomosynthesis (DMT) scanner, which combines DBT and molecular breast tomosynthesis (MBT) on a single gantry. The DMT scanner uses fully isocentric rotation of tube and x-ray detector for maintaining a fixed tube-detector alignment during DBT imaging. A cellular focused copper prototype grid with 80 cm focal length, 3.85 mm height, 0.1 mm thick lamellae, and 1.1 mm hole pitch was tested. Primary transmission of the grid at 28 kV tube voltage was on average 74% with the grid stationary and aligned for maximum transmission. It fell to 72% during grid reciprocation by the proposed method. Residual grid line artifacts (GLAs) in projection views and reconstructed DBT images are characterized and methods for reducing the visibility of GLAs in the reconstructed volume through projection image flat-field correction and spatial frequency-based filtering of the DBT slices are described and evaluated. The software correction methods reduce the visibility of these artifacts in the reconstructed volume, making them imperceptible both in the reconstructed DBT images and their Fourier transforms.

3 Tesla breast MR imaging as a problem-solving tool: Diagnostic performance and incidental lesions

PubMed Central

Spick, Claudio; Szolar, Dieter H. M.; Preidler, Klaus W.; Reittner, Pia; Rauch, Katharina; Brader, Peter; Tillich, Manfred

2018-01-01

Purpose To investigate the diagnostic performance and incidental lesion yield of 3T breast MRI if used as a problem-solving tool. Methods This retrospective, IRB-approved, cross-sectional, single-center study comprised 302 consecutive women (mean: 50±12 years; range: 20–79 years) who were undergoing 3T breast MRI between 03/2013-12/2014 for further workup of conventional and clinical breast findings. Images were read by experienced, board-certified radiologists. The reference standard was histopathology or follow-up ≥ two years. Sensitivity, specificity, PPV, and NPV were calculated. Results were stratified by conventional and clinical breast findings. Results The reference standard revealed 53 true-positive, 243 true-negative, 20 false-positive, and two false-negative breast MRI findings, resulting in a sensitivity, specificity, PPV, and NPV of 96.4% (53/55), 92.4% (243/263), 72.6% (53/73), and 99.2% (243/245), respectively. In 5.3% (16/302) of all patients, incidental MRI lesions classified BI-RADS 3–5 were detected, 37.5% (6/16) of which were malignant. Breast composition and the imaging findings that had led to referral had no significant influence on the diagnostic performance of breast MR imaging (p>0.05). Conclusion 3T breast MRI yields excellent diagnostic results if used as a problem-solving tool independent of referral reasons. The number of suspicious incidental lesions detected by MRI is low, but is associated with a substantial malignancy rate. PMID:29293582

Full Intelligent Cancer Classification of Thermal Breast Images to Assist Physician in Clinical Diagnostic Applications

PubMed Central

Lashkari, AmirEhsan; Pak, Fatemeh; Firouzmand, Mohammad

2016-01-01

Breast cancer is the most common type of cancer among women. The important key to treat the breast cancer is early detection of it because according to many pathological studies more than 75% – 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done to early detection of breast cancer with higher precision and accuracy. Infra-red breast thermography is an imaging technique based on recording temperature distribution patterns of breast tissue. Compared with breast mammography technique, thermography is more suitable technique because it is noninvasive, non-contact, passive and free ionizing radiation. In this paper, a full automatic high accuracy technique for classification of suspicious areas in thermogram images with the aim of assisting physicians in early detection of breast cancer has been presented. Proposed algorithm consists of four main steps: pre-processing & segmentation, feature extraction, feature selection and classification. At the first step, using full automatic operation, region of interest (ROI) determined and the quality of image improved. Using thresholding and edge detection techniques, both right and left breasts separated from each other. Then relative suspected areas become segmented and image matrix normalized due to the uniqueness of each person's body temperature. At feature extraction stage, 23 features, including statistical, morphological, frequency domain, histogram and Gray Level Co-occurrence Matrix (GLCM) based features are extracted from segmented right and left breast obtained from step 1. To achieve the best features, feature selection methods such as minimum Redundancy and Maximum Relevance (mRMR), Sequential Forward Selection (SFS), Sequential Backward Selection (SBS), Sequential Floating Forward Selection (SFFS), Sequential Floating Backward Selection (SFBS) and Genetic Algorithm (GA) have been used at step 3. Finally to classify and TH labeling procedures, different classifiers such as AdaBoost, Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Naïve Bayes (NB) and probability Neural Network (PNN) are assessed to find the best suitable one. These steps are applied on different thermogram images degrees. The results obtained on native database showed the best and significant performance of the proposed algorithm in comprise to the similar studies. According to experimental results, GA combined with AdaBoost with the mean accuracy of 85.33% and 87.42% on the left and right breast images with 0 degree, GA combined with AdaBoost with mean accuracy of 85.17% on the left breast images with 45 degree and mRMR combined with AdaBoost with mean accuracy of 85.15% on the right breast images with 45 degree, and also GA combined with AdaBoost with a mean accuracy of 84.67% and 86.21%, on the left and right breast images with 90 degree, are the best combinations of feature selection and classifier for evaluation of breast images. PMID:27014608

Readout-Segmented Echo-Planar Imaging in Diffusion-Weighted MR Imaging in Breast Cancer: Comparison with Single-Shot Echo-Planar Imaging in Image Quality

PubMed Central

Kim, Yun Ju; Kang, Bong Joo; Park, Chang Suk; Kim, Hyeon Sook; Son, Yo Han; Porter, David Andrew; Song, Byung Joo

2014-01-01

Objective The purpose of this study was to compare the image quality of standard single-shot echo-planar imaging (ss-EPI) and that of readout-segmented EPI (rs-EPI) in patients with breast cancer. Materials and Methods Seventy-one patients with 74 breast cancers underwent both ss-EPI and rs-EPI. For qualitative comparison of image quality, three readers independently assessed the two sets of diffusion-weighted (DW) images. To evaluate geometric distortion, a comparison was made between lesion lengths derived from contrast enhanced MR (CE-MR) images and those obtained from the corresponding DW images. For assessment of image parameters, signal-to-noise ratio (SNR), lesion contrast, and contrast-to-noise ratio (CNR) were calculated. Results The rs-EPI was superior to ss-EPI in most criteria regarding the qualitative image quality. Anatomical structure distinction, delineation of the lesion, ghosting artifact, and overall image quality were significantly better in rs-EPI. Regarding the geometric distortion, lesion length on ss-EPI was significantly different from that of CE-MR, whereas there were no significant differences between CE-MR and rs-EPI. The rs-EPI was superior to ss-EPI in SNR and CNR. Conclusion Readout-segmented EPI is superior to ss-EPI in the aspect of image quality in DW MR imaging of the breast. PMID:25053898

Template-based automatic breast segmentation on MRI by excluding the chest region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Muqing; Chen, Jeon-Hor; Wang, Xiaoyong

2013-12-15

Purpose: Methods for quantification of breast density on MRI using semiautomatic approaches are commonly used. In this study, the authors report on a fully automatic chest template-based method. Methods: Nonfat-suppressed breast MR images from 31 healthy women were analyzed. Among them, one case was randomly selected and used as the template, and the remaining 30 cases were used for testing. Unlike most model-based breast segmentation methods that use the breast region as the template, the chest body region on a middle slice was used as the template. Within the chest template, three body landmarks (thoracic spine and bilateral boundary ofmore » the pectoral muscle) were identified for performing the initial V-shape cut to determine the posterior lateral boundary of the breast. The chest template was mapped to each subject's image space to obtain a subject-specific chest model for exclusion. On the remaining image, the chest wall muscle was identified and excluded to obtain clean breast segmentation. The chest and muscle boundaries determined on the middle slice were used as the reference for the segmentation of adjacent slices, and the process continued superiorly and inferiorly until all 3D slices were segmented. The segmentation results were evaluated by an experienced radiologist to mark voxels that were wrongly included or excluded for error analysis. Results: The breast volumes measured by the proposed algorithm were very close to the radiologist's corrected volumes, showing a % difference ranging from 0.01% to 3.04% in 30 tested subjects with a mean of 0.86% ± 0.72%. The total error was calculated by adding the inclusion and the exclusion errors (so they did not cancel each other out), which ranged from 0.05% to 6.75% with a mean of 3.05% ± 1.93%. The fibroglandular tissue segmented within the breast region determined by the algorithm and the radiologist were also very close, showing a % difference ranging from 0.02% to 2.52% with a mean of 1.03% ± 1.03%. The total error by adding the inclusion and exclusion errors ranged from 0.16% to 11.8%, with a mean of 2.89% ± 2.55%. Conclusions: The automatic chest template-based breast MRI segmentation method worked well for cases with different body and breast shapes and different density patterns. Compared to the radiologist-established truth, the mean difference in segmented breast volume was approximately 1%, and the total error by considering the additive inclusion and exclusion errors was approximately 3%. This method may provide a reliable tool for MRI-based segmentation of breast density.« less

Breast density estimation from high spectral and spatial resolution MRI

PubMed Central

Li, Hui; Weiss, William A.; Medved, Milica; Abe, Hiroyuki; Newstead, Gillian M.; Karczmar, Gregory S.; Giger, Maryellen L.

2016-01-01

Abstract. A three-dimensional breast density estimation method is presented for high spectral and spatial resolution (HiSS) MR imaging. Twenty-two patients were recruited (under an Institutional Review Board--approved Health Insurance Portability and Accountability Act-compliant protocol) for high-risk breast cancer screening. Each patient received standard-of-care clinical digital x-ray mammograms and MR scans, as well as HiSS scans. The algorithm for breast density estimation includes breast mask generating, breast skin removal, and breast percentage density calculation. The inter- and intra-user variabilities of the HiSS-based density estimation were determined using correlation analysis and limits of agreement. Correlation analysis was also performed between the HiSS-based density estimation and radiologists’ breast imaging-reporting and data system (BI-RADS) density ratings. A correlation coefficient of 0.91 (p<0.0001) was obtained between left and right breast density estimations. An interclass correlation coefficient of 0.99 (p<0.0001) indicated high reliability for the inter-user variability of the HiSS-based breast density estimations. A moderate correlation coefficient of 0.55 (p=0.0076) was observed between HiSS-based breast density estimations and radiologists’ BI-RADS. In summary, an objective density estimation method using HiSS spectral data from breast MRI was developed. The high reproducibility with low inter- and low intra-user variabilities shown in this preliminary study suggest that such a HiSS-based density metric may be potentially beneficial in programs requiring breast density such as in breast cancer risk assessment and monitoring effects of therapy. PMID:28042590

An anatomically oriented breast model for MRI

NASA Astrophysics Data System (ADS)

Kutra, Dominik; Bergtholdt, Martin; Sabczynski, Jörg; Dössel, Olaf; Buelow, Thomas

2015-03-01

Breast cancer is the most common cancer in women in the western world. In the breast cancer care-cycle, MRIis e.g. employed in lesion characterization and therapy assessment. Reading of a single three dimensional image or comparing a multitude of such images in a time series is a time consuming task. Radiological reporting is done manually by translating the spatial position of a finding in an image to a generic representation in the form of a breast diagram, outlining quadrants or clock positions. Currently, registration algorithms are employed to aid with the reading and interpretation of longitudinal studies by providing positional correspondence. To aid with the reporting of findings, knowledge about the breast anatomy has to be introduced to translate from patient specific positions to a generic representation. In our approach we fit a geometric primitive, the semi-super-ellipsoid to patient data. Anatomical knowledge is incorporated by fixing the tip of the super-ellipsoid to the mammilla position and constraining its center-point to a reference plane defined by landmarks on the sternum. A coordinate system is then constructed by linearly scaling the fitted super-ellipsoid, defining a unique set of parameters to each point in the image volume. By fitting such a coordinate system to a different image of the same patient, positional correspondence can be generated. We have validated our method on eight pairs of baseline and follow-up scans (16 breasts) that were acquired for the assessment of neo-adjuvant chemotherapy. On average, the location predicted and the actual location of manually set landmarks are within a distance of 5.6 mm. Our proposed method allows for automatic reporting simply by uniformly dividing the super-ellipsoid around its main axis.

Detection of microcalcifications by characteristic magnetic susceptibility effects using MR phase image cross-correlation analysis

PubMed Central

Baheza, Richard A.; Welch, E. Brian; Gochberg, Daniel F.; Sanders, Melinda; Harvey, Sara; Gore, John C.; Yankeelov, Thomas E.

2015-01-01

Purpose: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. Methods: Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragments within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method’s performance. Results: The method detected calcium fragments with sizes of 0.14–0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4–1.0 mm in images with voxel sizes between (0.2 mm)3 and (0.6 mm)3. In images acquired at 7 T with voxel sizes of (0.2 mm)3–(0.4 mm)3, calcium fragments (size 0.3–0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%–90%, 51%–68%, and 0.77%–0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12 min, and voxel sizes of (0.4 mm)3–(0.6 mm)3, simulated microcalcifications with sizes of 0.6–1.0 mm were detected with a sensitivity, specificity, and AUC of 75%–87%, 54%–87%, and 0.76%–0.90%, respectively. However, different microcalcification shapes were indistinguishable. Conclusions: The new method is promising for detecting relatively large microcalcifications (i.e., 0.6–0.9 mm) within the breast at 7 T in reasonable times. Detection of smaller deposits at high field may be possible with higher spatial resolution, but such images require relatively long scan times. Although mammography can detect and distinguish the shape of smaller microcalcifications with superior sensitivity and specificity, this alternative method does not expose tissue to ionizing radiation, is not affected by breast density, and can be combined with other MRI methods (e.g., dynamic contrast-enhanced MRI and diffusion weighted MRI), to potentially improve diagnostic performance. PMID:25735297

Detection of microcalcifications by characteristic magnetic susceptibility effects using MR phase image cross-correlation analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baheza, Richard A.; Welch, E. Brian; Gochberg, Daniel F.

Purpose: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. Methods: Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragmentsmore » within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method’s performance. Results: The method detected calcium fragments with sizes of 0.14–0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4–1.0 mm in images with voxel sizes between (0.2 mm){sup 3} and (0.6 mm){sup 3}. In images acquired at 7 T with voxel sizes of (0.2 mm){sup 3}–(0.4 mm){sup 3}, calcium fragments (size 0.3–0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%–90%, 51%–68%, and 0.77%–0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12 min, and voxel sizes of (0.4 mm){sup 3}–(0.6 mm){sup 3}, simulated microcalcifications with sizes of 0.6–1.0 mm were detected with a sensitivity, specificity, and AUC of 75%–87%, 54%–87%, and 0.76%–0.90%, respectively. However, different microcalcification shapes were indistinguishable. Conclusions: The new method is promising for detecting relatively large microcalcifications (i.e., 0.6–0.9 mm) within the breast at 7 T in reasonable times. Detection of smaller deposits at high field may be possible with higher spatial resolution, but such images require relatively long scan times. Although mammography can detect and distinguish the shape of smaller microcalcifications with superior sensitivity and specificity, this alternative method does not expose tissue to ionizing radiation, is not affected by breast density, and can be combined with other MRI methods (e.g., dynamic contrast-enhanced MRI and diffusion weighted MRI), to potentially improve diagnostic performance.« less

Direct-Conversion Molecular Breast Imaging of Invasive Breast Cancer: Imaging Features, Extent of Invasive Disease, and Comparison Between Invasive Ductal and Lobular Histology.

PubMed

Conners, Amy Lynn; Jones, Katie N; Hruska, Carrie B; Geske, Jennifer R; Boughey, Judy C; Rhodes, Deborah J

2015-09-01

The purposes of this study were to compare the tumor appearance of invasive breast cancer on direct-conversion molecular breast imaging using a standardized lexicon and to determine how often direct-conversion molecular breast imaging identifies all known invasive tumor foci in the breast, and whether this differs for invasive ductal versus lobular histologic profiles. Patients with prior invasive breast cancer and concurrent direct-conversion molecular breast imaging examinations were retrospectively reviewed. Blinded review of direct-conversion molecular breast imaging examinations was performed by one of two radiologists, according to a validated lexicon. Direct-conversion molecular breast imaging findings were matched with lesions described on the pathology report to exclude benign reasons for direct-conversion molecular breast imaging findings and to document direct-conversion molecular breast imaging-occult tumor foci. Associations between direct-conversion molecular breast imaging findings and tumor histologic profiles were examined using chi-square tests. In 286 patients, 390 invasive tumor foci were present in 294 breasts. A corresponding direct-conversion molecular breast imaging finding was present for 341 of 390 (87%) tumor foci described on the pathology report. Invasive ductal carcinoma (IDC) tumor foci were more likely to be a mass (40% IDC vs 15% invasive lobular carcinoma [ILC]; p < 0.001) and to have marked intensity than were ILC foci (63% IDC vs 32% ILC; p < 0.001). Direct-conversion molecular breast imaging correctly revealed all pathology-proven foci of invasive disease in 79.8% of cases and was more likely to do so for IDC than for ILC (86.1% vs 56.7%; p < 0.0001). Overall, direct-conversion molecular breast imaging showed all known invasive foci in 249 of 286 (87%) patients. Direct-conversion molecular breast imaging features of invasive cancer, including lesion type and intensity, differ by histologic subtype. Direct-conversion molecular breast imaging is less likely to show all foci of ILC compared with IDC.

Estimation of T2* Relaxation Time of Breast Cancer: Correlation with Clinical, Imaging and Pathological Features

PubMed Central

Seo, Mirinae; Jahng, Geon-Ho; Sohn, Yu-Mee; Rhee, Sun Jung; Oh, Jang-Hoon; Won, Kyu-Yeoun

2017-01-01

Objective The purpose of this study was to estimate the T2* relaxation time in breast cancer, and to evaluate the association between the T2* value with clinical-imaging-pathological features of breast cancer. Materials and Methods Between January 2011 and July 2013, 107 consecutive women with 107 breast cancers underwent multi-echo T2*-weighted imaging on a 3T clinical magnetic resonance imaging system. The Student's t test and one-way analysis of variance were used to compare the T2* values of cancer for different groups, based on the clinical-imaging-pathological features. In addition, multiple linear regression analysis was performed to find independent predictive factors associated with the T2* values. Results Of the 107 breast cancers, 92 were invasive and 15 were ductal carcinoma in situ (DCIS). The mean T2* value of invasive cancers was significantly longer than that of DCIS (p = 0.029). Signal intensity on T2-weighted imaging (T2WI) and histologic grade of invasive breast cancers showed significant correlation with T2* relaxation time in univariate and multivariate analysis. Breast cancer groups with higher signal intensity on T2WI showed longer T2* relaxation time (p = 0.005). Cancer groups with higher histologic grade showed longer T2* relaxation time (p = 0.017). Conclusion The T2* value is significantly longer in invasive cancer than in DCIS. In invasive cancers, T2* relaxation time is significantly longer in higher histologic grades and high signal intensity on T2WI. Based on these preliminary data, quantitative T2* mapping has the potential to be useful in the characterization of breast cancer. PMID:28096732

Detection of mitotic nuclei in breast histopathology images using localized ACM and Random Kitchen Sink based classifier.

PubMed

Beevi, K Sabeena; Nair, Madhu S; Bindu, G R

2016-08-01

The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmentation of nuclei from breast histopathology images are carried out by Localized Active Contour Model (LACM) utilizing bio-inspired optimization techniques in the detection stage, in order to handle diffused intensities present along object boundaries. Further, the application of a new optimal machine learning algorithm capable of classifying strong non-linear data such as Random Kitchen Sink (RKS), shows improved classification performance. The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS) dataset provided for MITOS-ATYPIA CONTEST 2014. The proposed framework achieved 95% recall, 98% precision and 96% F-score.

Fully automated segmentation of the pectoralis muscle boundary in breast MR images

NASA Astrophysics Data System (ADS)

Wang, Lei; Filippatos, Konstantinos; Friman, Ola; Hahn, Horst K.

2011-03-01

Dynamic Contrast Enhanced MRI (DCE-MRI) of the breast is emerging as a novel tool for early tumor detection and diagnosis. The segmentation of the structures in breast DCE-MR images, such as the nipple, the breast-air boundary and the pectoralis muscle, serves as a fundamental step for further computer assisted diagnosis (CAD) applications, e.g. breast density analysis. Moreover, the previous clinical studies show that the distance between the posterior breast lesions and the pectoralis muscle can be used to assess the extent of the disease. To enable automatic quantification of the distance from a breast tumor to the pectoralis muscle, a precise delineation of the pectoralis muscle boundary is required. We present a fully automatic segmentation method based on the second derivative information represented by the Hessian matrix. The voxels proximal to the pectoralis muscle boundary exhibit roughly the same Eigen value patterns as a sheet-like object in 3D, which can be enhanced and segmented by a Hessian-based sheetness filter. A vector-based connected component filter is then utilized such that only the pectoralis muscle is preserved by extracting the largest connected component. The proposed method was evaluated quantitatively with a test data set which includes 30 breast MR images by measuring the average distances between the segmented boundary and the annotated surfaces in two ground truth sets, and the statistics showed that the mean distance was 1.434 mm with the standard deviation of 0.4661 mm, which shows great potential for integration of the approach in the clinical routine.

Real-Time Intraoperative Detection of Breast Cancer using Near-infrared Fluorescence Imaging and Methylene Blue

PubMed Central

Tummers, Quirijn R.J.G.; Verbeek, Floris P.R.; Schaafsma, Boudewijn E.; Boonstra, Martin C.; van der Vorst, Joost R.; Liefers, Gerrit-Jan; van de Velde, Cornelis J.H.; Frangioni, John V.; Vahrmeijer, Alexander L.

2014-01-01

Background Despite recent developments in preoperative breast cancer imaging, intraoperative localization of tumor tissue can be challenging, resulting in tumor-positive resection margins during breast-conserving surgery. Based on certain physicochemical similarities between Technetium(99mTc)-sestamibi (MIBI), a SPECT radiodiagnostic with a sensitivity of 83–90% to detect breast cancer preoperatively, and the near-infrared (NIR) fluorophore Methylene Blue (MB), we hypothesized that MB might detect breast cancer intraoperatively using NIR fluorescence imaging. Methods Twenty-four patients with breast cancer, planned for surgical resection, were included. Patients were divided in 2 administration groups, which differed with respect to the timing of MB administration. N = 12 patients per group were administered 1.0 mg/kg MB intravenously either immediately or 3 h before surgery. The mini-FLARE imaging system was used to identify the NIR fluorescent signal during surgery and on post-resected specimens transferred to the pathology department. Results were confirmed by NIR fluorescence microscopy. Results 20/24 (83%) of breast tumors (carcinoma in N=21 and ductal carcinoma in situ in N=3) were identified in the resected specimen using NIR fluorescence imaging. Patients with non-detectable tumors were significantly older. No significant relation to receptor status or tumor grade was seen. Overall tumor-to-background ratio (TBR) was 2.4 ± 0.8. There was no significant difference between TBR and background signal between administration groups. In 2/4 patients with positive resection margins, breast cancer tissue identified in the wound bed during surgery would have changed surgical management. Histology confirmed the concordance of fluorescence signal and tumor tissue. Conclusions This feasibility study demonstrated an overall breast cancer identification rate using MB of 83%, with real-time intraoperative guidance having the potential to alter patient management. PMID:24862545

PubMed Central

Schulz-Wendtland, Rüdiger; Jud, Sebastian M.; Fasching, Peter A.; Hartmann, Arndt; Radicke, Marcus; Rauh, Claudia; Uder, Michael; Wunderle, Marius; Gass, Paul; Langemann, Hanna; Beckmann, Matthias W.; Emons, Julius

2017-01-01

Aim The combination of different imaging modalities through the use of fusion devices promises significant diagnostic improvement for breast pathology. The aim of this study was to evaluate image quality and clinical feasibility of a prototype fusion device (fusion prototype) constructed from a standard tomosynthesis mammography unit and a standard 3D ultrasound probe using a new method of breast compression. Materials and Methods Imaging was performed on 5 mastectomy specimens from patients with confirmed DCIS or invasive carcinoma (BI-RADS ™ 6). For the preclinical fusion prototype an ABVS system ultrasound probe from an Acuson S2000 was integrated into a MAMMOMAT Inspiration (both Siemens Healthcare Ltd) and, with the aid of a newly developed compression plate, digital mammogram and automated 3D ultrasound images were obtained. Results The quality of digital mammogram images produced by the fusion prototype was comparable to those produced using conventional compression. The newly developed compression plate did not influence the applied x-ray dose. The method was not more labour intensive or time-consuming than conventional mammography. From the technical perspective, fusion of the two modalities was achievable. Conclusion In this study, using only a few mastectomy specimens, the fusion of an automated 3D ultrasound machine with a standard mammography unit delivered images of comparable quality to conventional mammography. The device allows simultaneous ultrasound – the second important imaging modality in complementary breast diagnostics – without increasing examination time or requiring additional staff. PMID:28713173

Estimation and imaging of breast lesions using a two-layer tissue structure by ultrasound-guided optical tomography

PubMed Central

Xu, Yan; Zhu, Quing

2015-01-01

Abstract. A new two-step estimation and imaging method is developed for a two-layer breast tissue structure consisting of a breast tissue layer and a chest wall underneath. First, a smaller probe with shorter distance source-detector pairs was used to collect the reflected light mainly from the breast tissue layer. Then, a larger probe with 9×14 source-detector pairs and a centrally located ultrasound transducer was used to collect reflected light from the two-layer tissue structure. The data collected from the smaller probe were used to estimate breast tissue optical properties. With more accurate estimation of the average breast tissue properties, the second layer properties can be assessed from data obtained from the larger probe. Using this approach, the unknown variables have been reduced from four to two and the estimated bulk tissue optical properties are more accurate and robust. In addition, a two-step reconstruction using a genetic algorithm and conjugate gradient method is implemented to simultaneously reconstruct the absorption and reduced scattering maps of targets inside a two-layer tissue structure. Simulations and phantom experiments have been performed to validate the new reconstruction method, and a clinical example is given to demonstrate the feasibility of this approach. PMID:26046722

Magnetic resonance guided optical spectroscopy imaging of human breast cancer using a combined frequency domain and continuous wave approach

NASA Astrophysics Data System (ADS)

Mastanduno, Michael A.; Davis, Scott C.; Jiang, Shudong; diFlorio-Alexander, Roberta; Pogue, Brian W.; Paulsen, Keith D.

2012-03-01

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used to image high-risk patients for breast cancer because of its higher sensitivity to tumors (approaching 100%) than traditional x-ray mammography. We focus on Near Infrared Spectroscopy (NIRS) as an emerging functional and molecular imaging technique that non-invasively quantifies optical properties of total hemoglobin, oxygen saturation, water content, scattering, and lipid concentration to increase the relatively low specificity of DCE-MRI. Our optical imaging system combines six frequency domain wavelengths, measured using PMT detectors with three continuous wave wavelengths measured using CCD/spectrometers. We present methods on combining the synergistic attributes of DCE-MR and NIRS for in-vivo imaging of breast cancer in three dimensions using a custom optical MR breast coil and diffusion based light modeling software, NIRFAST. We present results from phantom studies, healthy subjects, and breast cancer patients. Preliminary results show contrast recovery within 10% in phantoms and spatial resolution less than 5mm. Images from healthy subjects were recovered with properties similar to literature values and previous studies. Patient images have shown elevated total hemoglobin values and water fraction, agreeing with histology and previous results. The additional information gained from NIRS may improve the ability to distinguish between malignant and benign lesions during MR imaging. These dual modality instruments will provide complex anatomical and molecular prognostic information, and may decrease the number of biopsies, thereby improving patient care.

Raman imaging at biological interfaces: applications in breast cancer diagnosis.

PubMed

Surmacki, Jakub; Musial, Jacek; Kordek, Radzislaw; Abramczyk, Halina

2013-05-24

One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment. The paper reviews recent progress in understanding structure and interactions at biological interfaces of the human tissue by using confocal Raman imaging and IR spectroscopy. The important differences between the noncancerous and cancerous human breast tissues were found in regions characteristic for vibrations of carotenoids, fatty acids, proteins, and interfacial water. Particular attention was paid to the role played by unsaturated fatty acids and their derivatives as well as carotenoids and interfacial water. We demonstrate that Raman imaging has reached a clinically relevant level in regard to breast cancer diagnosis applications. The results presented in the paper may have serious implications on understanding mechanisms of interactions in living cells under realistically crowded conditions of biological tissue.

Breast cancer margin delineation with fluorescence lifetime imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Phipps, Jennifer E.; Gorpas, Dimitris; Darrow, Morgan; Unger, Jakob; Bold, Richard; Marcu, Laura

2017-02-01

The current standard of care for early stages of breast cancer is breast-conserving surgery (BCS). BCS involves a lumpectomy procedure, during which the tumor is removed with a rim of normal tissue-if cancer cells found in that rim of tissue, it is called a positive margin and means part of the tumor remains in the breast. Currently there is no method to determine if cancer cells exist at the margins of lumpectomy specimens aside from time-intensive histology methods that result in reoperations in up to 38% of cases. We used fluorescence lifetime imaging (FLIm) to measure time-resolved autofluorescence from N=13 ex vivo human breast cancer specimens (N=10 patients undergoing lumpectomy or mastectomy) and compared our results to histology. Tumor (both invasive and ductal carcinoma in situ), fibrous tissue, fat and fat necrosis have unique fluorescence signatures. For instance, between 500-580 nm, fluorescence lifetime of tumor was shortest (4.7 +/- 0.4 ns) compared to fibrous tissue (5.5 +/- 0.7 ns) and fat (7.0 +/- 0.1 ns), P<0.05 (ANOVA). These differences are due to the biochemical properties of lipid, nicotineamide adenine dinucleotide (NADH) and collagen fibers in the fat, tumor and fibrous tissue, respectively. Additionally, the FLIm data is augmented to video of the breast tissue with image processing algorithms that track a blue (450 nm) aiming beam used in parallel with the 355 nm excitation beam. This allows for accurate histologic co-registration and in the future will allow for three-dimensional lumpectomy surfaces to be imaged for cancer margin delineation.

Evaluation of the Possible Utilization of 68Ga-DOTATOC in Diagnosis of Adenocarcinoma Breast Cancer

PubMed Central

Zolghadri, Samaneh; Naderi, Mojdeh; Yousefnia, Hassan; Alirezapour, Behrouz; Beiki, Davood

2018-01-01

Objective(s): Studies have indicated advantageous properties of [DOTA-DPhe1, Tyr3] octreotide (DOTATOC) in tumor models and labeling with gallium. Breast cancer is the second leading cause of cancer mortality in women, and most of these cancers are often an adenocarcinoma. Due to the importance of target to non-target ratios in the efficacy of diagnosis, the pharmacokinetic of 68Ga-DOTATOC in an adenocarcinoma breast cancer animal model was studied in this research, and the optimized time for imaging was determined. Methods: 68Ga was obtained from 68Ge/68Ga generator. The complex was prepared at optimized conditions. Radiochemical purity of the complex was checked using both HPLC and ITLC methods. Biodistribution of the complex was studied in BALB/c mice bearing adenocarcinoma breast cancer. Also, PET/CT imaging was performed up to 120 min post injection. Results: The complex was produced with radiochemical purity of greater than 98% and specific activity of about 40 GBq/mM at optimized conditions. Biodistribution of the complex was studied in BALB/c mice bearing adenocarcinoma breast cancer indicated fast blood clearance and significant uptake in the tumor. Significant tumor: blood and tumor:muscle uptake ratios were observed even at early times post-injection. PET/CT images were also confirmed the considerable accumulation of the tracer in the tumor. Conclusion: Generally, the results proved the possible application of the radiolabelled complex for the detection of the adenocarcinoma breast cancer and according to the pharmacokenitic data, the suitable time for imaging was determined as at least 30 min after injection. PMID:29333466

Multimodality Imaging-based Evaluation of Single-Lumen Silicone Breast Implants for Rupture.

PubMed

Seiler, Stephen J; Sharma, Pooja B; Hayes, Jody C; Ganti, Ramapriya; Mootz, Ann R; Eads, Emily D; Teotia, Sumeet S; Evans, W Phil

2017-01-01

Breast implants are frequently encountered on breast imaging studies, and it is essential for any radiologist interpreting these studies to be able to correctly assess implant integrity. Ruptures of silicone gel-filled implants often occur without becoming clinically obvious and are incidentally detected at imaging. Early diagnosis of implant rupture is important because surgical removal of extracapsular silicone in the breast parenchyma and lymphatics is difficult. Conversely, misdiagnosis of rupture may prompt a patient to undergo unnecessary additional surgery to remove the implant. Mammography is the most common breast imaging examination performed and can readily depict extracapsular free silicone, although it is insensitive for detection of intracapsular implant rupture. Ultrasonography (US) can be used to assess the internal structure of the implant and may provide an economical method for initial implant assessment. Common US signs of intracapsular rupture include the "keyhole" or "noose" sign, subcapsular line sign, and "stepladder" sign; extracapsular silicone has a distinctive "snowstorm" or echogenic noise appearance. Magnetic resonance (MR) imaging is the most accurate and reliable means for assessment of implant rupture and is highly sensitive for detection of both intracapsular and extracapsular rupture. MR imaging findings of intracapsular rupture include the keyhole or noose sign, subcapsular line sign, and "linguine" sign, and silicone-selective MR imaging sequences are highly sensitive to small amounts of extracapsular silicone. © RSNA, 2017.

A method to measure paddle and detector pressures and footprints in mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogg, Peter; Szczepura, Katy; Darlington, Alison

2013-04-15

Purpose: Compression is necessary in mammography to improve image quality and reduce radiation burden. Maximizing the amount of breast in contact with the image receptor (IR) is important. To achieve this, for the craniocaudal projection, there is no consensus within the literature regarding how the IR should be positioned relative to the inframammary fold (IMF). No information exists within the literature to describe how pressure balancing between IR and paddle, and IR breast footprint, might be optimized. This paper describes a novel method for measuring the respective pressures applied to the breast from the IR and the paddle and amore » method to simultaneously measure the breast footprints on the IR and the paddle. Methods: Using a deformable breast phantom and electronic pressure-sensitive mat, area and pressure readings were gathered from two mammography machines and four paddles at 60, 80, and 100 N with the IR positioned at -2, -1, 0, +1, and +2 cm relative to the IMF (60 combinations in total). Results: Paddle and IR footprints were calculated along with a uniformity index (UI). For all four paddle/machine/pressure combinations the greatest IR footprint was achieved at IMF +2 cm. The UI indicates that the best pressure/footprint balance is achieved at IMF +1 cm. Conclusions: The authors' method appears to be suited to measuring breast footprints and pressures on IR and paddle and a human female study is planned.« less

Fourier domain image fusion for differential X-ray phase-contrast breast imaging.

PubMed

Coello, Eduardo; Sperl, Jonathan I; Bequé, Dirk; Benz, Tobias; Scherer, Kai; Herzen, Julia; Sztrókay-Gaul, Anikó; Hellerhoff, Karin; Pfeiffer, Franz; Cozzini, Cristina; Grandl, Susanne

2017-04-01

X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well. Copyright © 2017 Elsevier B.V. All rights reserved.

A similarity measure method combining location feature for mammogram retrieval.

PubMed

Wang, Zhiqiong; Xin, Junchang; Huang, Yukun; Li, Chen; Xu, Ling; Li, Yang; Zhang, Hao; Gu, Huizi; Qian, Wei

2018-05-28

Breast cancer, the most common malignancy among women, has a high mortality rate in clinical practice. Early detection, diagnosis and treatment can reduce the mortalities of breast cancer greatly. The method of mammogram retrieval can help doctors to find the early breast lesions effectively and determine a reasonable feature set for image similarity measure. This will improve the accuracy effectively for mammogram retrieval. This paper proposes a similarity measure method combining location feature for mammogram retrieval. Firstly, the images are pre-processed, the regions of interest are detected and the lesions are segmented in order to get the center point and radius of the lesions. Then, the method, namely Coherent Point Drift, is used for image registration with the pre-defined standard image. The center point and radius of the lesions after registration are obtained and the standard location feature of the image is constructed. This standard location feature can help figure out the location similarity between the image pair from the query image to each dataset image in the database. Next, the content feature of the image is extracted, including the Histogram of Oriented Gradients, the Edge Direction Histogram, the Local Binary Pattern and the Gray Level Histogram, and the image pair content similarity can be calculated using the Earth Mover's Distance. Finally, the location similarity and content similarity are fused to form the image fusion similarity, and the specified number of the most similar images can be returned according to it. In the experiment, 440 mammograms, which are from Chinese women in Northeast China, are used as the database. When fusing 40% lesion location feature similarity and 60% content feature similarity, the results have obvious advantages. At this time, precision is 0.83, recall is 0.76, comprehensive indicator is 0.79, satisfaction is 96.0%, mean is 4.2 and variance is 17.7. The results show that the precision and recall of this method have obvious advantage, compared with the content-based image retrieval.

Diagnosis of breast cancer biopsies using quantitative phase imaging

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Kandel, Mikhail E.; Han, Kevin; Luo, Zelun; Macias, Virgilia; Tangella, Krishnarao; Balla, Andre; Popescu, Gabriel

2015-03-01

The standard practice in the histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope. The pathologist looks at certain morphological features, visible under the stain, to diagnose whether a tumor is benign or malignant. This determination is made based on qualitative inspection making it subject to investigator bias. Furthermore, since this method requires a microscopic examination by the pathologist it suffers from low throughput. A quantitative, label-free and high throughput method for detection of these morphological features from images of tissue biopsies is, hence, highly desirable as it would assist the pathologist in making a quicker and more accurate diagnosis of cancers. We present here preliminary results showing the potential of using quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated optical path length maps of unstained breast tissue biopsies using Spatial Light Interference Microscopy (SLIM). As a first step towards diagnosis based on quantitative phase imaging, we carried out a qualitative evaluation of the imaging resolution and contrast of our label-free phase images. These images were shown to two pathologists who marked the tumors present in tissue as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on H&E stained tissue images and the number of agreements were counted. In our experiment, the agreement between SLIM and H&E based diagnosis was measured to be 88%. Our preliminary results demonstrate the potential and promise of SLIM for a push in the future towards quantitative, label-free and high throughput diagnosis.

MO-E-BRD-03: Intra-Operative Breast Brachytherapy: Is One Stop Shopping Best? [Non-invasive Image-Guided Breast Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Libby, B.

2015-06-15

Is Non-invasive Image-Guided Breast Brachytherapy Good? – Jess Hiatt, MS Non-invasive Image-Guided Breast Brachytherapy (NIBB) is an emerging therapy for breast boost treatments as well as Accelerated Partial Breast Irradiation (APBI) using HDR surface breast brachytherapy. NIBB allows for smaller treatment volumes while maintaining optimal target coverage. Considering the real-time image-guidance and immobilization provided by the NIBB modality, minimal margins around the target tissue are necessary. Accelerated Partial Breast Irradiation in brachytherapy: is shorter better? - Dorin Todor, PhD VCU A review of balloon and strut devices will be provided together with the origins of APBI: the interstitial multi-catheter implant.more » A dosimetric and radiobiological perspective will help point out the evolution in breast brachytherapy, both in terms of devices and the protocols/clinical trials under which these devices are used. Improvements in imaging, delivery modalities and convenience are among the factors driving the ultrashort fractionation schedules but our understanding of both local control and toxicities associated with various treatments is lagging. A comparison between various schedules, from a radiobiological perspective, will be given together with a critical analysis of the issues. to review and understand the evolution and development of APBI using brachytherapy methods to understand the basis and limitations of radio-biological ‘equivalence’ between fractionation schedules to review commonly used and proposed fractionation schedules Intra-operative breast brachytherapy: Is one stop shopping best?- Bruce Libby, PhD. University of Virginia A review of intraoperative breast brachytherapy will be presented, including the Targit-A and other trials that have used electronic brachytherapy. More modern approaches, in which the lumpectomy procedure is integrated into an APBI workflow, will also be discussed. Learning Objectives: To review past and current clinical trials for IORT To discuss lumpectomy-scan-plan-treat workflow for IORT.« less

Breast magnetic resonance imaging for surveillance of women with a personal history of breast cancer: outcomes stratified by interval between definitive surgery and surveillance MR imaging.

PubMed

Park, Vivian Youngjean; Kim, Eun-Kyung; Kim, Min Jung; Moon, Hee Jung; Yoon, Jung Hyun

2018-01-22

Women with a personal history of breast cancer are at increased risk of future breast cancer events, and may benefit from supplemental screening methods that could enhance early detection of subclinical disease. However, current literature on breast magnetic resonance (MR) imaging surveillance is limited. We investigated outcomes of surveillance breast magnetic resonance (MR) imaging in women with a personal history of breast cancer. We reviewed 1053 consecutive breast MR examinations that were performed for surveillance in 1044 women (median age, 53 years; range, 20-85 years) previously treated for breast cancer between August 2014 and February 2016. All patients had previously received supplemental surveillance with ultrasound. Cancer detection rate (CDR), abnormal interpretation rate and characteristics of MR-detected cancers were assessed, including extramammary cancers. We also calculated the PPV 1 , PPV 3 , sensitivity and specificity for MR-detected intramammary lesions. Performance statistics were stratified by interval following initial surgery. The CDR for MR-detected cancers was 6.7 per 1000 examinations (7 of 1053) and was 3.8 per 1000 examinations (4 of 1053) for intramammary cancers. The overall abnormal interpretation rate was 8.0%, and the abnormal interpretation rate for intramammary lesions was 7.2%. The PPV 1 , PPV 3 , sensitivity and specificity for intramammary lesions was 5.3% (4 of 76), 15.8% (3 of 19), 75.0% (3 of 4) and 98.3% (1031 of 1049), respectively. For MR examinations performed ≤36 months after surgery, the overall CDR was 1.4 per 1000 examinations. For MR examinations performed > 36 months after surgery, the overall CDR was 17.4 per 1000 examinations. Surveillance breast MR imaging may be considered in women with a history of breast cancer, considering the low abnormal interpretation rate and its high specificity. However, the cancer detection rate was low and implementation may be more effective after more than 3 years after surgery.

Integrated PET/MR breast cancer imaging: Attenuation correction and implementation of a 16-channel RF coil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oehmigen, Mark, E-mail: mark.oehmigen@uni-due.de

Purpose: This study aims to develop, implement, and evaluate a 16-channel radiofrequency (RF) coil for integrated positron emission tomography/magnetic resonance (PET/MR) imaging of breast cancer. The RF coil is designed for optimized MR imaging performance and PET transparency and attenuation correction (AC) is applied for accurate PET quantification. Methods: A 16-channel breast array RF coil was designed for integrated PET/MR hybrid imaging of breast cancer lesions. The RF coil features a lightweight rigid design and is positioned with a spacer at a defined position on the patient table of an integrated PET/MR system. Attenuation correction is performed by generating andmore » applying a dedicated 3D CT-based template attenuation map. Reposition accuracy of the RF coil on the system patient table while using the positioning frame was tested in repeated measurements using MR-visible markers. The MR, PET, and PET/MR imaging performances were systematically evaluated using modular breast phantoms. Attenuation correction of the RF coil was evaluated with difference measurements of the active breast phantoms filled with radiotracer in the PET detector with and without the RF coil in place, serving as a standard of reference measurement. The overall PET/MR imaging performance and PET quantification accuracy of the new 16-channel RF coil and its AC were then evaluated in first clinical examinations on ten patients with local breast cancer. Results: The RF breast array coil provides excellent signal-to-noise ratio and signal homogeneity across the volume of the breast phantoms in MR imaging and visualizes small structures in the phantoms down to 0.4 mm in plane. Difference measurements with PET revealed a global loss and thus attenuation of counts by 13% (mean value across the whole phantom volume) when the RF coil is placed in the PET detector. Local attenuation ranging from 0% in the middle of the phantoms up to 24% was detected in the peripheral regions of the phantoms at positions closer to attenuating hardware structures of the RF coil. The position accuracy of the RF coil on the patient table when using the positioning frame was determined well below 1 mm for all three spatial dimensions. This ensures perfect position match between the RF coil and its three-dimensional attenuation template during the PET data reconstruction process. When applying the CT-based AC of the RF coil, the global attenuation bias was mostly compensated to ±0.5% across the entire breast imaging volume. The patient study revealed high quality MR, PET, and combined PET/MR imaging of breast cancer. Quantitative activity measurements in all 11 breast cancer lesions of the ten patients resulted in increased mean difference values of SUV{sub max} 11.8% (minimum 3.2%; maximum 23.2%) between nonAC images and images when AC of the RF breast coil was applied. This supports the quantitative results of the phantom study as well as successful attenuation correction of the RF coil. Conclusions: A 16-channel breast RF coil was designed for optimized MR imaging performance and PET transparency and was successfully integrated with its dedicated attenuation correction template into a whole-body PET/MR system. Systematic PET/MR imaging evaluation with phantoms and an initial study on patients with breast cancer provided excellent MR and PET image quality and accurate PET quantification.« less

Metal artifact reduction using a patch-based reconstruction for digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Borges, Lucas R.; Bakic, Predrag R.; Maidment, Andrew D. A.; Vieira, Marcelo A. C.

2017-03-01

Digital breast tomosynthesis (DBT) is rapidly emerging as the main clinical tool for breast cancer screening. Although several reconstruction methods for DBT are described by the literature, one common issue is the interplane artifacts caused by out-of-focus features. For breasts containing highly attenuating features, such as surgical clips and large calcifications, the artifacts are even more apparent and can limit the detection and characterization of lesions by the radiologist. In this work, we propose a novel method of combining backprojected data into tomographic slices using a patch-based approach, commonly used in denoising. Preliminary tests were performed on a geometry phantom and on an anthropomorphic phantom containing metal inserts. The reconstructed images were compared to a commercial reconstruction solution. Qualitative assessment of the reconstructed images provides evidence that the proposed method reduces artifacts while maintaining low noise levels. Objective assessment supports the visual findings. The artifact spread function shows that the proposed method is capable of suppressing artifacts generated by highly attenuating features. The signal difference to noise ratio shows that the noise levels of the proposed and commercial methods are comparable, even though the commercial method applies post-processing filtering steps, which were not implemented on the proposed method. Thus, the proposed method can produce tomosynthesis reconstructions with reduced artifacts and low noise levels.

Between-race differences in the effects of breast density information and information about new imaging technology on breast-health decision-making

PubMed Central

Manning, Mark; Purrington, Kristen; Penner, Louis; Duric, Neb; Albrecht, Terrance L.

2016-01-01

Objectives Some US states have mandated that women be informed when they have dense breasts; however, little is known about how general knowledge about breast density (BD) affects related health decision-making. We examined the effects of BD information and imaging technology information on 138 African–American (AA) and European–American (EA) women’s intentions to discuss breast cancer screening with their physicians. Methods Women were randomly assigned to receive BD information and/or imaging technology information via 2 by 2 factorial design, and completed planned behavior measures (e.g., attitudes, intentions) related to BC screening. Results Attitudes mediated the effects of BD information, and the mediation was stronger for AA women compared to EA women. Effects were more robust for BD information compared to imaging technology information. Results of moderator analyses revealed suppressor effects of injunctive norms that were moderated by imaging technology information. Conclusion Information about BD favorably influences women’s intentions to engage in relevant breast health behaviors. Stronger attitude mediated-effects for AA women suggest greater scrutiny of BD information. Practice implications Since BD information may influence women’s intentions to discuss BC screening, strategies to effectively present BD information to AA women should be investigated given the likelihood of their increased scrutiny of BD information. PMID:26847421

Waveform inversion with source encoding for breast sound speed reconstruction in ultrasound computed tomography.

PubMed

Wang, Kun; Matthews, Thomas; Anis, Fatima; Li, Cuiping; Duric, Neb; Anastasio, Mark A

2015-03-01

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the sound speed distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Both computer simulation and experimental phantom studies are conducted to demonstrate the use of the WISE method. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

Research on the lesion segmentation of breast tumor MR images based on FCM-DS theory

NASA Astrophysics Data System (ADS)

Zhang, Liangbin; Ma, Wenjun; Shen, Xing; Li, Yuehua; Zhu, Yuemin; Chen, Li; Zhang, Su

2017-03-01

Magnetic resonance imaging (MRI) plays an important role in the treatment of breast tumor by high intensity focused ultrasound (HIFU). The doctors evaluate the scale, distribution and the statement of benign or malignancy of breast tumor by analyzing variety modalities of MRI, such as the T2, DWI and DCE images for making accurate preoperative treatment plan and evaluating the effect of the operation. This paper presents a method of lesion segmentation of breast tumor based on FCM-DS theory. Fuzzy c-means clustering (FCM) algorithm combined with Dempster-Shafer (DS) theory is used to process the uncertainty of information, segmenting the lesion areas on DWI and DCE modalities of MRI and reducing the scale of the uncertain parts. Experiment results show that FCM-DS can fuse the DWI and DCE images to achieve accurate segmentation and display the statement of benign or malignancy of lesion area by Time-Intensity Curve (TIC), which could be beneficial in making preoperative treatment plan and evaluating the effect of the therapy.

Quantitative breast density analysis using tomosynthesis and comparison with MRI and digital mammography.

PubMed

Moon, Woo Kyung; Chang, Jie-Fan; Lo, Chung-Ming; Chang, Jung Min; Lee, Su Hyun; Shin, Sung Ui; Huang, Chiun-Sheng; Chang, Ruey-Feng

2018-02-01

Breast density at mammography has been used as markers of breast cancer risk. However, newly introduced tomosynthesis and computer-aided quantitative method could provide more reliable breast density evaluation. In the experiment, 98 tomosynthesis image volumes were obtained from 98 women. For each case, an automatic skin removal was used and followed by a fuzzy c-mean (FCM) classifier which separated the fibroglandular tissues from other tissues in breast area. Finally, percent of breast density and breast volume were calculated and the results were compared with MRI. In addition, the percent of breast density and breast area of digital mammography calculated using the software Cumulus (University of Toronto, Toronto, ON, Canada.) were also compared with 3-D modalities. Percent of breast density and breast volume, which were computed from tomosynthesis, MRI and digital mammography were 17.37% ± 4.39% and 607.12 cm 3  ± 323.01 cm 3 , 20.3% ± 8.6% and 537.59 cm 3  ± 287.74 cm 3 , and 12.03% ± 4.08%, respectively. There were significant correlations on breast density as well as volume between tomosynthesis and MRI (R = 0.482 and R = 0.805), tomosynthesis and breast density with breast area of digital mammography (R = 0.789 and R = 0.877), and MRI and breast density with breast area of digital mammography (R = 0.482 and R = 0.857) (all P values < .001). Breast density and breast volume evaluated from tomosynthesis, MRI and breast density and breast area of digital mammographic images have significant correlations and indicate that tomosynthesis could provide useful 3-D information on breast density through proposed method. Copyright © 2017 Elsevier B.V. All rights reserved.

Rapid virtual H&E histology of breast tissue specimens using a compact fluorescence nonlinear microscope

PubMed Central

Cahill, Lucas C.; Giacomelli, Michael G.; Yoshitake, Tadayuki; Vardeh, Hilde; Faulkner-Jones, Beverly E.; Connolly, James L.; Sun, Chi-Kuang; Fujimoto, James G.

2017-01-01

Up to 40% of patients undergoing breast conserving surgery for breast cancer require repeat surgeries due to close to or positive margins. The lengthy processing required for evaluating surgical margins by standard paraffin embedded histology precludes its use during surgery and therefore, technologies for rapid evaluation of surgical pathology could improve the treatment of breast cancer by reducing the number of surgeries required. We demonstrate real-time histological evaluation of breast cancer surgical specimens by staining specimens with acridine orange (AO) and sulforhodamine 101 (SR101) analogously to hematoxylin and eosin (H&E) and then imaging the specimens with fluorescence nonlinear microscopy (NLM) using a compact femtosecond fiber laser. A video-rate computational light absorption model was used to produce realistic virtual H&E images of tissue in real time and in three dimensions. NLM imaging could be performed to depths of 100 µm below the tissue surface, which is important since many surgical specimens require subsurface evaluation due to artifacts on the tissue surface from electrocautery, surgical ink or debris from specimen handling. We validate this method by expert review of NLM images compared to formalin fixed, paraffin embedded (FFPE) H&E histology. Diagnostically important features such as normal terminal ductal lobular units, fibrous and adipose stromal parenchyma, inflammation, invasive carcinoma, and in-situ lobular and ductal carcinoma were present in NLM images associated with pathologies identified on standard FFPE H&E histology. We demonstrate that AO and SR101 were extracted to undetectable levels after FFPE processing and fluorescence in situ hybridization (FISH) HER2 amplification status was unaffected by the NLM imaging protocol. This method potentially enables cost-effective, real-time histological guidance of surgical resections. PMID:29131161

A review of setup error in supine breast radiotherapy using cone-beam computed tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Batumalai, Vikneswary, E-mail: Vikneswary.batumalai@sswahs.nsw.gov.au; Liverpool and Macarthur Cancer Therapy Centres, New South Wales; Ingham Institute of Applied Medical Research, Sydney, New South Wales

2016-10-01

Setup error in breast radiotherapy (RT) measured with 3-dimensional cone-beam computed tomography (CBCT) is becoming more common. The purpose of this study is to review the literature relating to the magnitude of setup error in breast RT measured with CBCT. The different methods of image registration between CBCT and planning computed tomography (CT) scan were also explored. A literature search, not limited by date, was conducted using Medline and Google Scholar with the following key words: breast cancer, RT, setup error, and CBCT. This review includes studies that reported on systematic and random errors, and the methods used when registeringmore » CBCT scans with planning CT scan. A total of 11 relevant studies were identified for inclusion in this review. The average magnitude of error is generally less than 5 mm across a number of studies reviewed. The common registration methods used when registering CBCT scans with planning CT scan are based on bony anatomy, soft tissue, and surgical clips. No clear relationships between the setup errors detected and methods of registration were observed from this review. Further studies are needed to assess the benefit of CBCT over electronic portal image, as CBCT remains unproven to be of wide benefit in breast RT.« less

Compositional breast imaging using a dual-energy mammography protocol

PubMed Central

Laidevant, Aurelie D.; Malkov, Serghei; Flowers, Chris I.; Kerlikowske, Karla; Shepherd, John A.

2010-01-01

Purpose: Mammography has a low sensitivity in dense breasts due to low contrast between malignant and normal tissue confounded by the predominant water density of the breast. Water is found in both adipose and fibroglandular tissue and constitutes most of the mass of a breast. However, significant protein mass is mainly found in the fibroglandular tissue where most cancers originate. If the protein compartment in a mammogram could be imaged without the influence of water, the sensitivity and specificity of the mammogram may be improved. This article describes a novel approach to dual-energy mammography, full-field digital compositional mammography (FFDCM), which can independently image the three compositional components of breast tissue: water, lipid, and protein. Methods: Dual-energy attenuation and breast shape measures are used together to solve for the three compositional thicknesses. Dual-energy measurements were performed on breast-mimicking phantoms using a full-field digital mammography unit. The phantoms were made of materials shown to have similar x-ray attenuation properties of the compositional compartments. They were made of two main stacks of thicknesses around 2 and 4 cm. Twenty-six thickness and composition combinations were used to derive the compositional calibration using a least-squares fitting approach. Results: Very high accuracy was achieved with a simple cubic fitting function with root mean square errors of 0.023, 0.011, and 0.012 cm for the water, lipid, and protein thicknesses, respectively. The repeatability (percent coefficient of variation) of these measures was tested using sequential images and was found to be 0.5%, 0.5%, and 3.3% for water, lipid, and protein, respectively. However, swapping the location of the two stacks of the phantom on the imaging plate introduced further errors showing the need for more complete system uniformity corrections. Finally, a preliminary breast image is presented of each of the compositional compartments separately. Conclusions: FFDCM has been derived and exhibited good compositional thickness accuracy on phantoms. Preliminary breast images demonstrated the feasibility of creating individual compositional diagnostic images in a clinical environment. PMID:20175478

Development of a phantom to test fully automated breast density software - A work in progress.

PubMed

Waade, G G; Hofvind, S; Thompson, J D; Highnam, R; Hogg, P

2017-02-01

Mammographic density (MD) is an independent risk factor for breast cancer and may have a future role for stratified screening. Automated software can estimate MD but the relationship between breast thickness reduction and MD is not fully understood. Our aim is to develop a deformable breast phantom to assess automated density software and the impact of breast thickness reduction on MD. Several different configurations of poly vinyl alcohol (PVAL) phantoms were created. Three methods were used to estimate their density. Raw image data of mammographic images were processed using Volpara to estimate volumetric breast density (VBD%); Hounsfield units (HU) were measured on CT images; and physical density (g/cm 3 ) was calculated using a formula involving mass and volume. Phantom volume versus contact area and phantom volume versus phantom thickness was compared to values of real breasts. Volpara recognized all deformable phantoms as female breasts. However, reducing the phantom thickness caused a change in phantom density and the phantoms were not able to tolerate same level of compression and thickness reduction experienced by female breasts during mammography. Our results are promising as all phantoms resulted in valid data for automated breast density measurement. Further work should be conducted on PVAL and other materials to produce deformable phantoms that mimic female breast structure and density with the ability of being compressed to the same level as female breasts. We are the first group to have produced deformable phantoms that are recognized as breasts by Volpara software. Copyright © 2016 The College of Radiographers. All rights reserved.

Improved Hardware for Higher Spatial Resolution Strain-ENCoded (SENC) Breast MRI for Strain Measurements

PubMed Central

Harouni, Ahmed A.; Hossain, Jakir; Jacobs, Michael A.; Osman, Nael F.

2012-01-01

Introduction Early detection of breast lesions using mammography has resulted in lower mortality-rates. However, some breast lesions are mammography occult and magnetic resonance imaging (MRI) is recommended, but has lower specificity. It is possible to achieve higher specificity by using Strain-ENCoded (SENC) MRI and/or magnetic resonance elastography(MRE). SENC breast MRI can measure the strain properties of breast tissue. Similarly, MRE is used to measure elasticity (i.e., shear stiffness) of different tissue compositions interrogating the tissue mechanical properties. Reports have shown that malignant tumors are 3–13 times stiffer than normal tissue and benign tumors. Methods We have developed a Strain-ENCoded (SENC) breast hardware device capable of periodically compressing the breast, thus allowing for longer scanning time and measuring the strain characteristics of breast tissue. This hardware enabled us to use SENC MRI with high spatial resolution (1×1×5mm3) instead of Fast SENC(FSENC). Simple controls and multiple safety measures were added to ensure accurate, repeatable and safe in-vivo experiments. Results Phantom experiments showed that SENC breast MRI has higher SNR and CNR than FSENC under different scanning resolutions. Finally, the SENC breast device reproducibility measurements resulted in a difference of less than one mm with a 1% strain difference. Conclusion SENC breast MR images have higher SNR and CNR than FSENC images. Thus, combining SENC breast strain measurements with diagnostic breast MRI to differentiate benign from malignant lesions could potentially increase the specificity of diagnosis in the clinical setting. PMID:21440464

Breast Cancer Treatment in the Era of Molecular Imaging

PubMed Central

Edelhauser, Gundula; Funovics, Martin

2008-01-01

Summary Molecular imaging employs molecularly targeted probes to visualize and often quantify distinct disease-specific markers and pathways. Modalities like intravital confocal or multiphoton microscopy, near-infrared fluorescence combined with endoscopy, surface reflectance imaging, or fluorescence-mediated tomography, and radionuclide imaging with positron emission tomography (PET) and single-photon emission computed tomography (SPECT) are increasingly used for small animal high-throughput screening, drug development and testing, and monitoring gene therapy experiments. In the clinical treatment of breast cancer, PET and SPECT as well as magnetic resonance-based molecular imaging are already established for the staging of distant disease and intrathoracic nodal status, for patient selection regarding receptor-directed treatments, and to gain early information about treatment efficacy. In the near future, reporter gene imaging during gene therapy and further spatial and qualitative characterization of the disease can become clinically possible with radionuclide and optical methods. Ultimately, it may be expected that every level of breast cancer treatment will be affected by molecular imaging, including screening. PMID:21048912

Evaluation of the Utility of Screening Mammography for High-Risk Women Undergoing Screening Breast MR Imaging.

PubMed

Lo, Glen; Scaranelo, Anabel M; Aboras, Hana; Ghai, Sandeep; Kulkarni, Supriya; Fleming, Rachel; Bukhanov, Karina; Crystal, Pavel

2017-10-01

Purpose To evaluate the value of mammography in detecting breast cancer in high-risk women undergoing screening breast magnetic resonance (MR) imaging. Materials and Methods An ethics-approved, retrospective review of prospective databases was performed to identify outcomes of 3934 screening studies (1977 screening MR imaging examinations and 1957 screening mammograms) performed between January 2012 and July 2014 in 1249 high-risk women. Performance measures including recall and cancer detection rates, sensitivity, specificity, and positive predictive values were calculated for both mammography and MR imaging. Results A total of 45 cancers (33 invasive and 12 ductal carcinomas in situ) were diagnosed, 43 were seen with MR imaging and 14 with both mammography and MR imaging. Additional tests (further imaging and/or biopsy) were recommended in 461 screening MR imaging studies (recall rate, 23.3%; 95% confidence interval [CI]: 21.5%, 25.2%), and mammography recalled 217 (recall rate, 11.1%; 95% CI: 9.7%, 12.6%). The cancer detection rate for MR imaging was 21.8 cancers per 1000 examinations (95% CI: 15.78, 29.19) and that for mammography was 7.2 cancers per 1000 examinations (95% CI: 3.92, 11.97; P < .001). Sensitivity and specificity of MR imaging were 96% and 78% respectively, and those of mammography were 31% and 89%, respectively (P < .001). Positive predictive value for MR imaging recalls was 9.3% (95% CI: 6.83%, 12.36%) and that for mammography recalls was 6.5% (95% CI: 3.57%, 10.59%). Conclusion Contemporaneous screening mammography did not have added value in detection of breast cancer for women who undergo screening MR imaging. Routine use of screening mammography in women undergoing screening breast MR imaging warrants reconsideration. © RSNA, 2017 Online supplemental material is available for this article.

MO-DE-210-06: Development of a Supercompounded 3D Volumetric Ultrasound Image Guidance System for Prone Accelerated Partial Breast Irradiation (APBI)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiu, T; Hrycushko, B; Zhao, B

2015-06-15

Purpose: For early-stage breast cancer, accelerated partial breast irradiation (APBI) is a cost-effective breast-conserving treatment. Irradiation in a prone position can mitigate respiratory induced breast movement and achieve maximal sparing of heart and lung tissues. However, accurate dose delivery is challenging due to breast deformation and lumpectomy cavity shrinkage. We propose a 3D volumetric ultrasound (US) image guidance system for accurate prone APBI Methods: The designed system, set beneath the prone breast board, consists of a water container, an US scanner, and a two-layer breast immobilization cup. The outer layer of the breast cup forms the inner wall of watermore » container while the inner layer is attached to patient breast directly to immobilization. The US transducer scans is attached to the outer-layer of breast cup at the dent of water container. Rotational US scans in a transverse plane are achieved by simultaneously rotating water container and transducer, and multiple transverse scanning forms a 3D scan. A supercompounding-technique-based volumetric US reconstruction algorithm is developed for 3D image reconstruction. The performance of the designed system is evaluated with two custom-made gelatin phantoms containing several cylindrical inserts filled in with water (11% reflection coefficient between materials). One phantom is designed for positioning evaluation while the other is for scaling assessment. Results: In the positioning evaluation phantom, the central distances between the inserts are 15, 20, 30 and 40 mm. The distances on reconstructed images differ by −0.19, −0.65, −0.11 and −1.67 mm, respectively. In the scaling evaluation phantom, inserts are 12.7, 19.05, 25.40 and 31.75 mm in diameter. Measured inserts’ sizes on images differed by 0.23, 0.19, −0.1 and 0.22 mm, respectively. Conclusion: The phantom evaluation results show that the developed 3D volumetric US system can accurately localize target position and determine target volume, and is a promising image-guidance tool for prone APBI.« less

Optimization of a dual-energy contrast-enhanced technique for a photon-counting digital breast tomosynthesis system: I. A theoretical model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carton, Ann-Katherine; Ullberg, Christer; Lindman, Karin

2010-11-15

Purpose: Dual-energy (DE) iodine contrast-enhanced x-ray imaging of the breast has been shown to identify cancers that would otherwise be mammographically occult. In this article, theoretical modeling was performed to obtain optimally enhanced iodine images for a photon-counting digital breast tomosynthesis (DBT) system using a DE acquisition technique. Methods: In the system examined, the breast is scanned with a multislit prepatient collimator aligned with a multidetector camera. Each detector collects a projection image at a unique angle during the scan. Low-energy (LE) and high-energy (HE) projection images are acquired simultaneously in a single scan by covering alternate collimator slits withmore » Sn and Cu filters, respectively. Sn filters ranging from 0.08 to 0.22 mm thickness and Cu filters from 0.11 to 0.27 mm thickness were investigated. A tube voltage of 49 kV was selected. Tomographic images, hereafter referred to as DBT images, were reconstructed using a shift-and-add algorithm. Iodine-enhanced DBT images were acquired by performing a weighted logarithmic subtraction of the HE and LE DBT images. The DE technique was evaluated for 20-80 mm thick breasts. Weighting factors, w{sub t}, that optimally cancel breast tissue were computed. Signal-difference-to-noise ratios (SDNRs) between iodine-enhanced and nonenhanced breast tissue normalized to the square root of the mean glandular dose (MGD) were computed as a function of the fraction of the MGD allocated to the HE images. Peak SDNR/{radical}(MGD) and optimal dose allocations were identified. SDNR/{radical}(MGD) and dose allocations were computed for several practical feasible system configurations (i.e., determined by the number of collimator slits covered by Sn and Cu). A practical system configuration and Sn-Cu filter pair that accounts for the trade-off between SDNR, tube-output, and MGD were selected. Results: w{sub t} depends on the Sn-Cu filter combination used, as well as on the breast thickness; to optimally cancel 0% with 50% glandular breast tissue, w{sub t} values were found to range from 0.46 to 0.72 for all breast thicknesses and Sn-Cu filter pairs studied. The optimal w{sub t} values needed to cancel all possible breast tissue glandularites vary by less than 1% for 20 mm thick breasts and 18% for 80 mm breasts. The system configuration where one collimator slit covered by Sn is alternated with two collimator slits covered by Cu delivers SDNR/{radical}(MGD) nearest to the peak value. A reasonable compromise is a 0.16 mm Sn-0.23 mm Cu filter pair, resulting in SDNR values between 1.64 and 0.61 and MGD between 0.70 and 0.53 mGy for 20-80 mm thick breasts at the maximum tube current. Conclusions: A DE acquisition technique for a photon-counting DBT imaging system has been developed and optimized.« less

Shear wave induced resonance elastography of spherical masses with polarized torsional waves

NASA Astrophysics Data System (ADS)

Hadj Henni, Anis; Schmitt, Cédric; Trop, Isabelle; Cloutier, Guy

2012-03-01

Shear wave induced resonance (SWIR) is a technique for dynamic ultrasound elastography of confined mechanical inclusions. It was developed for breast tumor imaging and tissue characterization. This method relies on the polarization of torsional shear waves modeled with the Helmholtz equation in spherical coordinates. To validate modeling, an invitro set-up was used to measure and image the first three eigenfrequencies and eigenmodes of a soft sphere. A preliminary invivo SWIR measurement on a breast fibroadenoma is also reported. Results revealed the potential of SWIR elastography to detect and mechanically characterize breast lesions for early cancer detection.

Shear wave induced resonance elastography of spherical masses with polarized torsional waves.

PubMed

Henni, Anis Hadj; Schmitt, Cédric; Trop, Isabelle; Cloutier, Guy

2012-03-26

Shear Wave Induced Resonance (SWIR) is a technique for dynamic ultrasound elastography of confined mechanical inclusions. It was developed for breast tumor imaging and tissue characterization. This method relies on the polarization of torsional shear waves modeled with the Helmholtz equation in spherical coordinates. To validate modeling, an in vitro set-up was used to measure and image the first three eigenfrequencies and eigenmodes of a soft sphere. A preliminary in vivo SWIR measurement on a breast fibroadenoma is also reported. Results revealed the potential of SWIR elastography to detect and mechanically characterize breast lesions for early cancer detection.

Imaging dose in breast radiotherapy: does breast size affect the dose to the organs at risk and the risk of secondary cancer to the contralateral breast?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Batumalai, Vikneswary, E-mail: vikneswary.batumalai@sswahs.nsw.gov.au; South Western Clinical School, University of New South Wales, Sydney, New South Wales; Quinn, Alexandra

Correct target positioning is crucial for accurate dose delivery in breast radiotherapy resulting in utilisation of daily imaging. However, the radiation dose from daily imaging is associated with increased probability of secondary induced cancer. The aim of this study was to quantify doses associated with three imaging modalities and investigate the correlation of dose and varying breast size in breast radiotherapy. Planning computed tomography (CT) data sets of 30 breast cancer patients were utilised to simulate the dose received by various organs from a megavoltage computed tomography (MV-CT), megavoltage electronic portal image (MV-EPI) and megavoltage cone-beam computed tomography (MV-CBCT). Themore » mean dose to organs adjacent to the target volume (contralateral breast, lungs, spinal cord and heart) were analysed. Pearson correlation analysis was performed to determine the relationship between imaging dose and primary breast volume and the lifetime attributable risk (LAR) of induced secondary cancer was calculated for the contralateral breast. The highest contralateral breast mean dose was from the MV-CBCT (1.79 Gy), followed by MV-EPI (0.22 Gy) and MV-CT (0.11 Gy). A similar trend was found for all organs at risk (OAR) analysed. The primary breast volume inversely correlated with the contralateral breast dose for all three imaging modalities. As the primary breast volume increases, the likelihood of a patient developing a radiation-induced secondary cancer to the contralateral breast decreases. MV-CBCT showed a stronger relationship between breast size and LAR of developing a radiation-induced contralateral breast cancer in comparison with the MV-CT and MV-EPI. For breast patients, imaging dose to OAR depends on imaging modality and treated breast size. When considering the use of imaging during breast radiotherapy, the patient's breast size and contralateral breast dose should be taken into account.« less

Discriminating between benign and malignant breast tumors using 3D convolutional neural network in dynamic contrast enhanced-MR images

NASA Astrophysics Data System (ADS)

Li, Jing; Fan, Ming; Zhang, Juan; Li, Lihua

2017-03-01

Convolutional neural networks (CNNs) are the state-of-the-art deep learning network architectures that can be used in a range of applications, including computer vision and medical image analysis. It exhibits a powerful representation learning mechanism with an automated design to learn features directly from the data. However, the common 2D CNNs only use the two dimension spatial information without evaluating the correlation between the adjoin slices. In this study, we established a method of 3D CNNs to discriminate between malignant and benign breast tumors. To this end, 143 patients were enrolled which include 66 benign and 77 malignant instances. The MRI images were pre-processed for noise reduction and breast tumor region segmentation. Data augmentation by spatial translating, rotating and vertical and horizontal flipping is applied to the cases to reduce possible over-fitting. A region-of-interest (ROI) and a volume-of-interest (VOI) were segmented in 2D and 3D DCE-MRI, respectively. The enhancement ratio for each MR series was calculated for the 2D and 3D images. The results for the enhancement ratio images in the two series are integrated for classification. The results of the area under the ROC curve(AUC) values are 0.739 and 0.801 for 2D and 3D methods, respectively. The results for 3D CNN which combined 5 slices for each enhancement ratio images achieved a high accuracy(Acc), sensitivity(Sens) and specificity(Spec) of 0.781, 0.744 and 0.823, respectively. This study indicates that 3D CNN deep learning methods can be a promising technology for breast tumor classification without manual feature extraction.

WE-DE-207B-10: Library-Based X-Ray Scatter Correction for Dedicated Cone-Beam Breast CT: Clinical Validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, L; Zhu, L; Vedantham, S

Purpose: Scatter contamination is detrimental to image quality in dedicated cone-beam breast CT (CBBCT), resulting in cupping artifacts and loss of contrast in reconstructed images. Such effects impede visualization of breast lesions and the quantitative accuracy. Previously, we proposed a library-based software approach to suppress scatter on CBBCT images. In this work, we quantify the efficacy and stability of this approach using datasets from 15 human subjects. Methods: A pre-computed scatter library is generated using Monte Carlo simulations for semi-ellipsoid breast models and homogeneous fibroglandular/adipose tissue mixture encompassing the range reported in literature. Projection datasets from 15 human subjects thatmore » cover 95 percentile of breast dimensions and fibroglandular volume fraction were included in the analysis. Our investigations indicate that it is sufficient to consider the breast dimensions alone and variation in fibroglandular fraction does not significantly affect the scatter-to-primary ratio. The breast diameter is measured from a first-pass reconstruction; the appropriate scatter distribution is selected from the library; and, deformed by considering the discrepancy in total projection intensity between the clinical dataset and the simulated semi-ellipsoidal breast. The deformed scatter-distribution is subtracted from the measured projections for scatter correction. Spatial non-uniformity (SNU) and contrast-to-noise ratio (CNR) were used as quantitative metrics to evaluate the results. Results: On the 15 patient cases, our method reduced the overall image spatial non-uniformity (SNU) from 7.14%±2.94% (mean ± standard deviation) to 2.47%±0.68% in coronal view and from 10.14%±4.1% to 3.02% ±1.26% in sagittal view. The average contrast to noise ratio (CNR) improved by a factor of 1.49±0.40 in coronal view and by 2.12±1.54 in sagittal view. Conclusion: We demonstrate the robustness and effectiveness of a library-based scatter correction method using patient datasets with large variability in breast dimensions and composition. The high computational efficiency and simplicity in implementation make this attractive for clinical implementation. Supported partly by NIH R21EB019597, R21CA134128 and R01CA195512.The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.« less

Automated 3D ultrasound image segmentation for assistant diagnosis of breast cancer

NASA Astrophysics Data System (ADS)

Wang, Yuxin; Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A.; Du, Sidan; Yuan, Jie; Wang, Xueding; Carson, Paul L.

2016-04-01

Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.

TU-CD-207-01: Characterization of Breast Tissue Composition Using Spectral Mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, H; Cho, H; Kumar, N

Purpose: To investigate the feasibility of characterizing the chemical composition of breast tissue, in terms of water and lipid, by using spectral mammography in simulation and postmortem studies. Methods: Analytical simulations were performed to obtain low- and high-energy signals of breast tissue based on previously reported water, lipid, and protein contents. Dual-energy decomposition was used to characterize the simulated breast tissue into water and lipid basis materials and the measured water density was compared to the known value. In experimental studies, postmortem breasts were imaged with a spectral mammography system based on a scanning multi-slit Si strip photon-counting detector. Low-more » and high-energy images were acquired simultaneously from a single exposure by sorting the recorded photons into the corresponding energy bins. Dual-energy material decomposition of the low- and high-energy images yielded individual pixel measurements of breast tissue composition in terms of water and lipid thicknesses. After imaging, each postmortem breast was chemically decomposed into water, lipid and protein. The water density calculated from chemical analysis was used as the reference gold standard. Correlation of the water density measurements between spectral mammography and chemical analysis was analyzed using linear regression. Results: Both simulation and postmortem studies showed good linear correlation between the decomposed water thickness using spectral mammography and chemical analysis. The slope of the linear fitting function in the simulation and postmortem studies were 1.15 and 1.21, respectively. Conclusion: The results indicate that breast tissue composition, in terms of water and lipid, can be accurately measured using spectral mammography. Quantitative breast tissue composition can potentially be used to stratify patients according to their breast cancer risk.« less

Assessment of breast pathologies using nonlinear microscopy

PubMed Central

Tao, Yuankai K.; Shen, Dejun; Sheikine, Yuri; Ahsen, Osman O.; Wang, Helen H.; Schmolze, Daniel B.; Johnson, Nicole B.; Brooker, Jeffrey S.; Cable, Alex E.; Connolly, James L.; Fujimoto, James G.

2014-01-01

Rapid intraoperative assessment of breast excision specimens is clinically important because up to 40% of patients undergoing breast-conserving cancer surgery require reexcision for positive or close margins. We demonstrate nonlinear microscopy (NLM) for the assessment of benign and malignant breast pathologies in fresh surgical specimens. A total of 179 specimens from 50 patients was imaged with NLM using rapid extrinsic nuclear staining with acridine orange and intrinsic second harmonic contrast generation from collagen. Imaging was performed on fresh, intact specimens without the need for fixation, embedding, and sectioning required for conventional histopathology. A visualization method to aid pathological interpretation is presented that maps NLM contrast from two-photon fluorescence and second harmonic signals to features closely resembling histopathology using hematoxylin and eosin staining. Mosaicking is used to overcome trade-offs between resolution and field of view, enabling imaging of subcellular features over square-centimeter specimens. After NLM examination, specimens were processed for standard paraffin-embedded histology using a protocol that coregistered histological sections to NLM images for paired assessment. Blinded NLM reading by three pathologists achieved 95.4% sensitivity and 93.3% specificity, compared with paraffin-embedded histology, for identifying invasive cancer and ductal carcinoma in situ versus benign breast tissue. Interobserver agreement was κ = 0.88 for NLM and κ = 0.89 for histology. These results show that NLM achieves high diagnostic accuracy, can be rapidly performed on unfixed specimens, and is a promising method for intraoperative margin assessment. PMID:25313045

Biomechanical modelling for breast image registration

NASA Astrophysics Data System (ADS)

Lee, Angela; Rajagopal, Vijay; Chung, Jae-Hoon; Bier, Peter; Nielsen, Poul M. F.; Nash, Martyn P.

2008-03-01

Breast cancer is a leading cause of death in women. Tumours are usually detected by palpation or X-ray mammography followed by further imaging, such as magnetic resonance imaging (MRI) or ultrasound. The aim of this research is to develop a biophysically-based computational tool that will allow accurate collocation of features (such as suspicious lesions) across multiple imaging views and modalities in order to improve clinicians' diagnosis of breast cancer. We have developed a computational framework for generating individual-specific, 3D finite element models of the breast. MR images were obtained of the breast under gravity loading and neutrally buoyant conditions. Neutrally buoyant breast images, obtained whilst immersing the breast in water, were used to estimate the unloaded geometry of the breast (for present purposes, we have assumed that the densities of water and breast tissue are equal). These images were segmented to isolate the breast tissues, and a tricubic Hermite finite element mesh was fitted to the digitised data points in order to produce a customized breast model. The model was deformed, in accordance with finite deformation elasticity theory, to predict the gravity loaded state of the breast in the prone position. The unloaded breast images were embedded into the reference model and warped based on the predicted deformation. In order to analyse the accuracy of the model predictions, the cross-correlation image comparison metric was used to compare the warped, resampled images with the clinical images of the prone gravity loaded state. We believe that a biomechanical image registration tool of this kind will aid radiologists to provide more reliable diagnosis and localisation of breast cancer.

A Metric for Reducing False Positives in the Computer-Aided Detection of Breast Cancer from Dynamic Contrast-Enhanced Magnetic Resonance Imaging Based Screening Examinations of High-Risk Women.

PubMed

Levman, Jacob E D; Gallego-Ortiz, Cristina; Warner, Ellen; Causer, Petrina; Martel, Anne L

2016-02-01

Magnetic resonance imaging (MRI)-enabled cancer screening has been shown to be a highly sensitive method for the early detection of breast cancer. Computer-aided detection systems have the potential to improve the screening process by standardizing radiologists to a high level of diagnostic accuracy. This retrospective study was approved by the institutional review board of Sunnybrook Health Sciences Centre. This study compares the performance of a proposed method for computer-aided detection (based on the second-order spatial derivative of the relative signal intensity) with the signal enhancement ratio (SER) on MRI-based breast screening examinations. Comparison is performed using receiver operating characteristic (ROC) curve analysis as well as free-response receiver operating characteristic (FROC) curve analysis. A modified computer-aided detection system combining the proposed approach with the SER method is also presented. The proposed method provides improvements in the rates of false positive markings over the SER method in the detection of breast cancer (as assessed by FROC analysis). The modified computer-aided detection system that incorporates both the proposed method and the SER method yields ROC results equal to that produced by SER while simultaneously providing improvements over the SER method in terms of false positives per noncancerous exam. The proposed method for identifying malignancies outperforms the SER method in terms of false positives on a challenging dataset containing many small lesions and may play a useful role in breast cancer screening by MRI as part of a computer-aided detection system.

Gold silver alloy nanoparticles (GSAN): an imaging probe for breast cancer screening with dual-energy mammography or computed tomography

NASA Astrophysics Data System (ADS)

Naha, Pratap C.; Lau, Kristen C.; Hsu, Jessica C.; Hajfathalian, Maryam; Mian, Shaameen; Chhour, Peter; Uppuluri, Lahari; McDonald, Elizabeth S.; Maidment, Andrew D. A.; Cormode, David P.

2016-07-01

Earlier detection of breast cancer reduces mortality from this disease. As a result, the development of better screening techniques is a topic of intense interest. Contrast-enhanced dual-energy mammography (DEM) is a novel technique that has improved sensitivity for cancer detection. However, the development of contrast agents for this technique is in its infancy. We herein report gold-silver alloy nanoparticles (GSAN) that have potent DEM contrast properties and improved biocompatibility. GSAN formulations containing a range of gold : silver ratios and capped with m-PEG were synthesized and characterized using various analytical methods. DEM and computed tomography (CT) phantom imaging showed that GSAN produced robust contrast that was comparable to silver alone. Cell viability, reactive oxygen species generation and DNA damage results revealed that the formulations with 30% or higher gold content are cytocompatible to Hep G2 and J774A.1 cells. In vivo imaging was performed in mice with and without breast tumors. The results showed that GSAN produce strong DEM and CT contrast and accumulated in tumors. Furthermore, both in vivo imaging and ex vivo analysis indicated the excretion of GSAN via both urine and feces. In summary, GSAN produce strong DEM and CT contrast, and has potential for both blood pool imaging and for breast cancer screening.Earlier detection of breast cancer reduces mortality from this disease. As a result, the development of better screening techniques is a topic of intense interest. Contrast-enhanced dual-energy mammography (DEM) is a novel technique that has improved sensitivity for cancer detection. However, the development of contrast agents for this technique is in its infancy. We herein report gold-silver alloy nanoparticles (GSAN) that have potent DEM contrast properties and improved biocompatibility. GSAN formulations containing a range of gold : silver ratios and capped with m-PEG were synthesized and characterized using various analytical methods. DEM and computed tomography (CT) phantom imaging showed that GSAN produced robust contrast that was comparable to silver alone. Cell viability, reactive oxygen species generation and DNA damage results revealed that the formulations with 30% or higher gold content are cytocompatible to Hep G2 and J774A.1 cells. In vivo imaging was performed in mice with and without breast tumors. The results showed that GSAN produce strong DEM and CT contrast and accumulated in tumors. Furthermore, both in vivo imaging and ex vivo analysis indicated the excretion of GSAN via both urine and feces. In summary, GSAN produce strong DEM and CT contrast, and has potential for both blood pool imaging and for breast cancer screening. Electronic supplementary information (ESI) available: Reactive oxygen species generation and DNA damage methods, stability of GSAN in PBS, step phantom images and a DEM image of a gold nanoparticle phantom, GSAN CT phantom results. See DOI: 10.1039/c6nr02618d

WE-DE-207B-11: Implementation of Size-Specific 3D Beam Modulation Filters On a Dedicated Breast CT Platform Using Breast Immobilization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hernandez, A; Boone, J

Purpose: To implement a 3D beam modulation filter (3D-BMF) in dedicated breast CT (bCT) and develop a method for conforming the patient’s breast to a pre-defined shape, optimizing the effects of the filter. This work expands on previous work reporting the methodology for designing a 3D-BMF that can spare unnecessary dose and improve signal equalization at the detector by preferentially filtering the beam in the thinner anterior and peripheral breast regions. Methods: Effective diameter profiles were measured for 219 segmented bCT images, grouped into volume quintiles, and averaged within each group to represent the range of breast sizes found clinically.more » These profiles were then used to generate five size-specific computational phantoms and fabricate five size-specific UHMW phantoms. Each computational phantom was utilized for designing a size-specific 3D-BMF using previously reported methods. Glandular dose values and projection images were simulated in MCNP6 with and without the 3DBMF using the system specifications of our prototype bCT scanner “Doheny”. Lastly, thermoplastic was molded around each of the five phantom sizes and used to produce a series of breast immobilizers for use in conforming the patient’s breast during bCT acquisition. Results: After incorporating the 3D-BMF, MC simulations estimated an 80% average reduction in the detector dynamic range requirements across all phantom sizes. The glandular dose was reduced on average 57% after normalizing by the number of quanta reaching the detector under the thickest region of the breast. Conclusion: A series of bCT-derived breast phantoms were used to design size-specific 3D-BMFs and breast immobilizers that can be used on the bCT platform to conform the patient’s breast and therefore optimally exploit the benefits of the 3D-BMF. Current efforts are focused on fabricating several prototype 3D-BMFs and performing phantom scans on Doheny for MC simulation validation and image quality analysis. Research reported in this paper was supported in part by the National Cancer Institute of the National Institutes of Health under award R01CA181081. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institue of Health.« less

Comparison of Background Parenchymal Enhancement at Contrast-enhanced Spectral Mammography and Breast MR Imaging.

PubMed

Sogani, Julie; Morris, Elizabeth A; Kaplan, Jennifer B; D'Alessio, Donna; Goldman, Debra; Moskowitz, Chaya S; Jochelson, Maxine S

2017-01-01

Purpose To assess the extent of background parenchymal enhancement (BPE) at contrast material-enhanced (CE) spectral mammography and breast magnetic resonance (MR) imaging, to evaluate interreader agreement in BPE assessment, and to examine the relationships between clinical factors and BPE. Materials and Methods This was a retrospective, institutional review board-approved, HIPAA-compliant study. Two hundred seventy-eight women from 25 to 76 years of age with increased breast cancer risk who underwent CE spectral mammography and MR imaging for screening or staging from 2010 through 2014 were included. Three readers independently rated BPE on CE spectral mammographic and MR images with the ordinal scale: minimal, mild, moderate, or marked. To assess pairwise agreement between BPE levels on CE spectral mammographic and MR images and among readers, weighted κ coefficients with quadratic weights were calculated. For overall agreement, mean κ values and bootstrapped 95% confidence intervals were calculated. The univariate and multivariate associations between BPE and clinical factors were examined by using generalized estimating equations separately for CE spectral mammography and MR imaging. Results Most women had minimal or mild BPE at both CE spectral mammography (68%-76%) and MR imaging (69%-76%). Between CE spectral mammography and MR imaging, the intrareader agreement ranged from moderate to substantial (κ = 0.55-0.67). Overall agreement on BPE levels between CE spectral mammography and MR imaging and among readers was substantial (κ = 0.66; 95% confidence interval: 0.61, 0.70). With both modalities, BPE demonstrated significant association with menopausal status, prior breast radiation therapy, hormonal treatment, breast density on CE spectral mammographic images, and amount of fibroglandular tissue on MR images (P < .001 for all). Conclusion There was substantial agreement between readers for BPE detected on CE spectral mammographic and MR images. © RSNA, 2016.

Identification of residual breast carcinoma following neoadjuvant chemotherapy: diffusion-weighted imaging--comparison with contrast-enhanced MR imaging and pathologic findings.

PubMed

Woodhams, Reiko; Kakita, Satoko; Hata, Hirofumi; Iwabuchi, Keiichi; Kuranami, Masaru; Gautam, Shiva; Hatabu, Hiroto; Kan, Shinichi; Mountford, Carolyn

2010-02-01

To compare the capability of diffusion-weighted (DW) and contrast material-enhanced magnetic resonance (MR) imaging to provide diagnostic information on residual breast cancers following neoadjuvant chemotherapy and to assess apparent diffusion coefficients (ADCs) of the carcinoma prior to neoadjuvant chemotherapy to determine if the method could help predict response to chemotherapy. Institutional review board approval and informed consent were obtained. Three hundred ninety-eight patients underwent MR imaging of the breast, including DW MR (b values, 0 and 1500 sec/mm(2)) and contrast-enhanced MR imaging. Of these, the contralateral breast in 73 women was used as a control. Seventy-two patients with 73 lesions with malignant disease were treated by using neoadjuvant chemotherapy and were examined for residual disease following therapy. Three were excluded because of prolonged intervals between final MR imaging and surgery. Thus, 69 patients (70 lesions) with DW and contrast-enhanced MR imaging results were compared with postoperative histopathologic findings. The ADCs of the carcinoma prior to neoadjuvant chemotherapy were calculated for each patient, and those with complete response and residual disease were compared. The accuracy for depicting residual tumor was 96% for DW MR imaging, compared with an accuracy of 89% for contrast-enhanced MR imaging (P = .06). There was no significant difference in prechemotherapy ADCs between pathologic complete response cases and those with residual disease. DW MR imaging had at least as good of accuracy as did contrast-enhanced MR imaging for monitoring neoadjuvant chemotherapy. The ADCs prior to chemotherapy did not predict response to chemotherapy. The use of DW imaging to visualize residual breast cancer without the need for contrast medium could be advantageous in women with impaired renal function. (c) RSNA, 2010

Breast ultrasound tomography with two parallel transducer arrays

NASA Astrophysics Data System (ADS)

Huang, Lianjie; Shin, Junseob; Chen, Ting; Lin, Youzuo; Gao, Kai; Intrator, Miranda; Hanson, Kenneth

2016-03-01

Breast ultrasound tomography is an emerging imaging modality to reconstruct the sound speed, density, and ultrasound attenuation of the breast in addition to ultrasound reflection/beamforming images for breast cancer detection and characterization. We recently designed and manufactured a new synthetic-aperture breast ultrasound tomography prototype with two parallel transducer arrays consisting of a total of 768 transducer elements. The transducer arrays are translated vertically to scan the breast in a warm water tank from the chest wall/axillary region to the nipple region to acquire ultrasound transmission and reflection data for whole-breast ultrasound tomography imaging. The distance of these two ultrasound transducer arrays is adjustable for scanning breasts with different sizes. We use our breast ultrasound tomography prototype to acquire phantom and in vivo patient ultrasound data to study its feasibility for breast imaging. We apply our recently developed ultrasound imaging and tomography algorithms to ultrasound data acquired using our breast ultrasound tomography system. Our in vivo patient imaging results demonstrate that our breast ultrasound tomography can detect breast lesions shown on clinical ultrasound and mammographic images.

A fast alignment method for breast MRI follow-up studies using automated breast segmentation and current-prior registration

NASA Astrophysics Data System (ADS)

Wang, Lei; Strehlow, Jan; Rühaak, Jan; Weiler, Florian; Diez, Yago; Gubern-Merida, Albert; Diekmann, Susanne; Laue, Hendrik; Hahn, Horst K.

2015-03-01

In breast cancer screening for high-risk women, follow-up magnetic resonance images (MRI) are acquired with a time interval ranging from several months up to a few years. Prior MRI studies may provide additional clinical value when examining the current one and thus have the potential to increase sensitivity and specificity of screening. To build a spatial correlation between suspicious findings in both current and prior studies, a reliable alignment method between follow-up studies is desirable. However, long time interval, different scanners and imaging protocols, and varying breast compression can result in a large deformation, which challenges the registration process. In this work, we present a fast and robust spatial alignment framework, which combines automated breast segmentation and current-prior registration techniques in a multi-level fashion. First, fully automatic breast segmentation is applied to extract the breast masks that are used to obtain an initial affine transform. Then, a non-rigid registration algorithm using normalized gradient fields as similarity measure together with curvature regularization is applied. A total of 29 subjects and 58 breast MR images were collected for performance assessment. To evaluate the global registration accuracy, the volume overlap and boundary surface distance metrics are calculated, resulting in an average Dice Similarity Coefficient (DSC) of 0.96 and root mean square distance (RMSD) of 1.64 mm. In addition, to measure local registration accuracy, for each subject a radiologist annotated 10 pairs of markers in the current and prior studies representing corresponding anatomical locations. The average distance error of marker pairs dropped from 67.37 mm to 10.86 mm after applying registration.

Breast cancer early detection via tracking of skin back-scattered secondary speckle patterns

NASA Astrophysics Data System (ADS)

Bennett, Aviya; Sirkis, Talia; Beiderman, Yevgeny; Agdarov, Sergey; Beiderman, Yafim; Zalevsky, Zeev

2018-02-01

Breast cancer has become a major cause of death among women. The lifetime risk of a woman developing this disease has been established as one in eight. The most useful way to reduce breast cancer death is to treat the disease as early as possible. The existing methods of early diagnostics of breast cancer are mainly based on screening mammography or Magnetic Resonance Imaging (MRI) periodically conducted at medical facilities. In this paper the authors proposing a new approach for simple breast cancer detection. It is based on skin stimulation by sound waves, illuminating it by laser beam and tracking the reflected secondary speckle patterns. As first approach, plastic balls of different sizes were placed under the skin of chicken breast and detected by the proposed method.

MO-E-BRD-01: Is Non-Invasive Image-Guided Breast Brachytherapy Good?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hiatt, J.

2015-06-15

Is Non-invasive Image-Guided Breast Brachytherapy Good? – Jess Hiatt, MS Non-invasive Image-Guided Breast Brachytherapy (NIBB) is an emerging therapy for breast boost treatments as well as Accelerated Partial Breast Irradiation (APBI) using HDR surface breast brachytherapy. NIBB allows for smaller treatment volumes while maintaining optimal target coverage. Considering the real-time image-guidance and immobilization provided by the NIBB modality, minimal margins around the target tissue are necessary. Accelerated Partial Breast Irradiation in brachytherapy: is shorter better? - Dorin Todor, PhD VCU A review of balloon and strut devices will be provided together with the origins of APBI: the interstitial multi-catheter implant.more » A dosimetric and radiobiological perspective will help point out the evolution in breast brachytherapy, both in terms of devices and the protocols/clinical trials under which these devices are used. Improvements in imaging, delivery modalities and convenience are among the factors driving the ultrashort fractionation schedules but our understanding of both local control and toxicities associated with various treatments is lagging. A comparison between various schedules, from a radiobiological perspective, will be given together with a critical analysis of the issues. to review and understand the evolution and development of APBI using brachytherapy methods to understand the basis and limitations of radio-biological ‘equivalence’ between fractionation schedules to review commonly used and proposed fractionation schedules Intra-operative breast brachytherapy: Is one stop shopping best?- Bruce Libby, PhD. University of Virginia A review of intraoperative breast brachytherapy will be presented, including the Targit-A and other trials that have used electronic brachytherapy. More modern approaches, in which the lumpectomy procedure is integrated into an APBI workflow, will also be discussed. Learning Objectives: To review past and current clinical trials for IORT To discuss lumpectomy-scan-plan-treat workflow for IORT.« less

New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis

NASA Astrophysics Data System (ADS)

Chaudhury, Baishali; Hall, Lawrence O.; Goldgof, Dmitry B.; Gatenby, Robert A.; Gillies, Robert; Drukteinis, Jennifer S.

2014-03-01

Magnetic Resonance Imaging (MRI) of breast cancer typically shows that tumors are heterogeneous with spatial variations in blood flow and cell density. Here, we examine the potential link between clinical tumor imaging and the underlying evolutionary dynamics behind heterogeneity in the cellular expression of estrogen receptors (ER) in breast cancer. We assume, in an evolutionary environment, that ER expression will only occur in the presence of significant concentrations of estrogen, which is delivered via the blood stream. Thus, we hypothesize, the expression of ER in breast cancer cells will correlate with blood flow on gadolinium enhanced breast MRI. To test this hypothesis, we performed quantitative analysis of blood flow on dynamic contrast enhanced MRI (DCE-MRI) and correlated it with the ER status of the tumor. Here we present our analytic methods, which utilize a novel algorithm to analyze 20 volumetric DCE-MRI breast cancer tumors. The algorithm generates post initial enhancement (PIE) maps from DCE-MRI and then performs texture features extraction from the PIE map, feature selection, and finally classification of tumors into ER positive and ER negative status. The combined gray level co-occurrence matrices, gray level run length matrices and local binary pattern histogram features allow quantification of breast tumor heterogeneity. The algorithm predicted ER expression with an accuracy of 85% using a Naive Bayes classifier in leave-one-out cross-validation. Hence, we conclude that our data supports the hypothesis that imaging characteristics can, through application of evolutionary principles, provide insights into the cellular and molecular properties of cancer cells.

Classification of breast abnormalities using artificial neural network

NASA Astrophysics Data System (ADS)

Zaman, Nur Atiqah Kamarul; Rahman, Wan Eny Zarina Wan Abdul; Jumaat, Abdul Kadir; Yasiran, Siti Salmah

2015-05-01

Classification is the process of recognition, differentiation and categorizing objects into groups. Breast abnormalities are calcifications which are tumor markers that indicate the presence of cancer in the breast. The aims of this research are to classify the types of breast abnormalities using artificial neural network (ANN) classifier and to evaluate the accuracy performance using receiver operating characteristics (ROC) curve. The methods used in this research are ANN for breast abnormalities classifications and Canny edge detector as a feature extraction method. Previously the ANN classifier provides only the number of benign and malignant cases without providing information for specific cases. However in this research, the type of abnormality for each image can be obtained. The existing MIAS MiniMammographic database classified the mammogram images into three features only namely characteristic of background tissues, class of abnormality and radius of abnormality. However, in this research three other features are added-in. These three features are number of spots, area and shape of abnormalities. Lastly the performance of the ANN classifier is evaluated using ROC curve. It is found that ANN has an accuracy of 97.9% which is considered acceptable.

MO-A-BRD-01: An Investigation of the Dynamic Response of a Novel Acousto-Optic Liquid Crystal Detector for Full-Field Transmission Ultrasound Breast Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosenfield, J.R.; La Riviere, P.J.; Sandhu, J.S.

Purpose: To characterize the dynamic response of a novel acousto-optic (AO) liquid crystal detector for high-resolution transmission ultrasound breast imaging. Transient and steady-state lesion contrast were investigated to identify optimal transducer settings for our prototype imaging system consistent with the FDA limits of 1 W/cm{sup 2} and 50 J/cm{sup 2} on the incident acoustic intensity and the transmitted acoustic energy flux density. Methods: We have developed a full-field transmission ultrasound breast imaging system that uses monochromatic plane-wave illumination to acquire projection images of the compressed breast. The acoustic intensity transmitted through the breast is converted into a visual image bymore » a proprietary liquid crystal detector operating on the basis of the AO effect. The dynamic response of the AO detector in the absence of an imaged breast was recorded by a CCD camera as a function of the acoustic field intensity and the detector exposure time. Additionally, a stereotactic needle biopsy breast phantom was used to investigate the change in opaque lesion contrast with increasing exposure time for a range of incident acoustic field intensities. Results: Using transducer voltages between 0.3 V and 0.8 V and exposure times of 3 minutes, a unique one-to-one mapping of incident acoustic intensity to steady-state optical brightness in the AO detector was observed. A transfer curve mapping acoustic intensity to steady-state optical brightness shows a high-contrast region analogous to the linear portion of the Hurter-Driffield curves of radiography. Using transducer voltages between 1 V and 1.75 V and exposure times of 90 s, the lesion contrast study demonstrated increasing lesion contrast with increasing breast exposure time and acoustic field intensity. Lesion-to-background contrast on the order of 0.80 was observed. Conclusion: Maximal lesion contrast in our prototype system can be obtained using the highest acoustic field intensity and the longest breast exposure time allowable under FDA standards. Department of Defense (DOD) Breast Cancer Research Program IDEA Award W81XWH-11-1-0332; National Institutes of Health (NIH) Grant T32 EB002103-21 from the National Institute of Biomedical Imaging and Bioengineering (NIBIB)« less

How Important Is a Reproducible Breath Hold for Deep Inspiration Breath Hold Breast Radiation Therapy?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wiant, David, E-mail: David.wiant@conehealth.com; Wentworth, Stacy; Liu, Han

Purpose: Deep inspiration breath hold (DIBH) for left-sided breast cancer has been shown to reduce heart dose. Surface imaging helps to ensure accurate breast positioning, but it does not guarantee a reproducible breath hold (BH) at DIBH treatments. We examine the effects of variable BH positions for DIBH treatments. Methods and Materials: Twenty-five patients who underwent free breathing (FB) and DIBH scans were reviewed. Four plans were created for each patient: FB, DIBH, FB-DIBH (the DIBH plans were copied to the FB images and recalculated, and image registration was based on breast tissue), and P-DIBH (a partial BH with themore » heart shifted midway between the FB and DIBH positions). The FB-DIBH plans give a “worst-case” scenario for surface imaging DIBH, where the breast is aligned by surface imaging but the patient is not holding their breath. Kolmogorov-Smirnov tests were used to compare the dose metrics. Results: The DIBH plans gave lower heart dose and comparable breast coverage versus FB in all cases. The FB-DIBH plans showed no significant difference versus FB plans for breast coverage, mean heart dose, or maximum heart dose (P≥.10). The mean heart dose differed between FB-DIBH and FB by <2 Gy for all cases, and the maximum heart dose differed by <2 Gy for 21 cases. The P-DIBH plans showed significantly lower mean heart dose than FB (P<.01). The mean heart doses for the P-DIBH plans were« less

Automated segmentation of ultrasonic breast lesions using statistical texture classification and active contour based on probability distance.

PubMed

Liu, Bo; Cheng, H D; Huang, Jianhua; Tian, Jiawei; Liu, Jiafeng; Tang, Xianglong

2009-08-01

Because of its complicated structure, low signal/noise ratio, low contrast and blurry boundaries, fully automated segmentation of a breast ultrasound (BUS) image is a difficult task. In this paper, a novel segmentation method for BUS images without human intervention is proposed. Unlike most published approaches, the proposed method handles the segmentation problem by using a two-step strategy: ROI generation and ROI segmentation. First, a well-trained texture classifier categorizes the tissues into different classes, and the background knowledge rules are used for selecting the regions of interest (ROIs) from them. Second, a novel probability distance-based active contour model is applied for segmenting the ROIs and finding the accurate positions of the breast tumors. The active contour model combines both global statistical information and local edge information, using a level set approach. The proposed segmentation method was performed on 103 BUS images (48 benign and 55 malignant). To validate the performance, the results were compared with the corresponding tumor regions marked by an experienced radiologist. Three error metrics, true-positive ratio (TP), false-negative ratio (FN) and false-positive ratio (FP) were used for measuring the performance of the proposed method. The final results (TP = 91.31%, FN = 8.69% and FP = 7.26%) demonstrate that the proposed method can segment BUS images efficiently, quickly and automatically.

Independent value of image fusion in unenhanced breast MRI using diffusion-weighted and morphological T2-weighted images for lesion characterization in patients with recently detected BI-RADS 4/5 x-ray mammography findings.

PubMed

Bickelhaupt, Sebastian; Tesdorff, Jana; Laun, Frederik Bernd; Kuder, Tristan Anselm; Lederer, Wolfgang; Teiner, Susanne; Maier-Hein, Klaus; Daniel, Heidi; Stieber, Anne; Delorme, Stefan; Schlemmer, Heinz-Peter

2017-02-01

The aim of this study was to evaluate the accuracy and applicability of solitarily reading fused image series of T2-weighted and high-b-value diffusion-weighted sequences for lesion characterization as compared to sequential or combined image analysis of these unenhanced sequences and to contrast- enhanced breast MRI. This IRB-approved study included 50 female participants with suspicious breast lesions detected in screening X-ray mammograms, all of which provided written informed consent. Prior to biopsy, all women underwent MRI including diffusion-weighted imaging (DWIBS, b = 1500s/mm 2 ). Images were analyzed as follows: prospective image fusion of DWIBS and T2-weighted images (FU), side-by-side analysis of DWIBS and T2-weighted series (CO), combination of the first two methods (CO+FU), and full contrast-enhanced diagnostic protocol (FDP). Diagnostic indices, confidence, and image quality of the protocols were compared by two blinded readers. Reading the CO+FU (accuracy 0.92; NPV 96.1 %; PPV 87.6 %) and the CO series (0.90; 96.1 %; 83.7 %) provided a diagnostic performance similar to the FDP (0.95; 96.1 %; 91.3 %; p > 0.05). FU reading alone significantly reduced the diagnostic accuracy (0.82; 93.3 %; 73.4 %; p = 0.023). MR evaluation of suspicious BI-RADS 4 and 5 lesions detected on mammography by using a non-contrast-enhanced T2-weighted and DWIBS sequence protocol is most accurate if MR images were read using the CO+FU protocol. • Unenhanced breast MRI with additional DWIBS/T2w-image fusion allows reliable lesion characterization. • Abbreviated reading of fused DWIBS/T2w-images alone decreases diagnostic confidence and accuracy. • Reading fused DWIBS/T2w-images as the sole diagnostic method should be avoided.

Implementation of several mathematical algorithms to breast tissue density classification

NASA Astrophysics Data System (ADS)

Quintana, C.; Redondo, M.; Tirao, G.

2014-02-01

The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories.

Registration of 3D ultrasound computer tomography and MRI for evaluation of tissue correspondences

NASA Astrophysics Data System (ADS)

Hopp, T.; Dapp, R.; Zapf, M.; Kretzek, E.; Gemmeke, H.; Ruiter, N. V.

2015-03-01

3D Ultrasound Computer Tomography (USCT) is a new imaging method for breast cancer diagnosis. In the current state of development it is essential to correlate USCT with a known imaging modality like MRI to evaluate how different tissue types are depicted. Due to different imaging conditions, e.g. with the breast subject to buoyancy in USCT, a direct correlation is demanding. We present a 3D image registration method to reduce positioning differences and allow direct side-by-side comparison of USCT and MRI volumes. It is based on a two-step approach including a buoyancy simulation with a biomechanical model and free form deformations using cubic B-Splines for a surface refinement. Simulation parameters are optimized patient-specifically in a simulated annealing scheme. The method was evaluated with in-vivo datasets resulting in an average registration error below 5mm. Correlating tissue structures can thereby be located in the same or nearby slices in both modalities and three-dimensional non-linear deformations due to the buoyancy are reduced. Image fusion of MRI volumes and USCT sound speed volumes was performed for intuitive display. By applying the registration to data of our first in-vivo study with the KIT 3D USCT, we could correlate several tissue structures in MRI and USCT images and learn how connective tissue, carcinomas and breast implants observed in the MRI are depicted in the USCT imaging modes.

Automatic quantification of mammary glands on non-contrast x-ray CT by using a novel segmentation approach

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Kano, Takuya; Cai, Yunliang; Li, Shuo; Zhou, Xinxin; Hara, Takeshi; Yokoyama, Ryujiro; Fujita, Hiroshi

2016-03-01

This paper describes a brand new automatic segmentation method for quantifying volume and density of mammary gland regions on non-contrast CT images. The proposed method uses two processing steps: (1) breast region localization, and (2) breast region decomposition to accomplish a robust mammary gland segmentation task on CT images. The first step detects two minimum bounding boxes of left and right breast regions, respectively, based on a machine-learning approach that adapts to a large variance of the breast appearances on different age levels. The second step divides the whole breast region in each side into mammary gland, fat tissue, and other regions by using spectral clustering technique that focuses on intra-region similarities of each patient and aims to overcome the image variance caused by different scan-parameters. The whole approach is designed as a simple structure with very minimum number of parameters to gain a superior robustness and computational efficiency for real clinical setting. We applied this approach to a dataset of 300 CT scans, which are sampled with the equal number from 30 to 50 years-old-women. Comparing to human annotations, the proposed approach can measure volume and quantify distributions of the CT numbers of mammary gland regions successfully. The experimental results demonstrated that the proposed approach achieves results consistent with manual annotations. Through our proposed framework, an efficient and effective low cost clinical screening scheme may be easily implemented to predict breast cancer risk, especially on those already acquired scans.

Contrast Enhancement for Thermal Acoustic Breast Cancer Imaging via Resonant Stimulation

DTIC Science & Technology

2009-03-01

structures,” Appl . Opt., vol. 39, no. 31, pp. 5872–5883, 2000. [12] D. Feng, Y. Xu, G. Ku, and L. V. Wang, “Microwave-induced thermoa- coustic tomography...image recon- struction,” Appl . Opt., vol. 39, no. 32, pp. 5971–5977, 2000. [14] G. Kossoff, E. K. Fry, and J. Jellins, “Average velocity of ultrasound...P. Stoica, and R. Wu, “Microwave imaging via adaptive beamforming methods for breast cancer detection,” J. Electro- magn. Waves Appl ., vol. 20, no. 1

MPGD for breast cancer prevention: a high resolution and low dose radiation medical imaging

NASA Astrophysics Data System (ADS)

Gutierrez, R. M.; Cerquera, E. A.; Mañana, G.

2012-07-01

Early detection of small calcifications in mammograms is considered the best preventive tool of breast cancer. However, existing digital mammography with relatively low radiation skin exposure has limited accessibility and insufficient spatial resolution for small calcification detection. Micro Pattern Gaseous Detectors (MPGD) and associated technologies, increasingly provide new information useful to generate images of microscopic structures and make more accessible cutting edge technology for medical imaging and many other applications. In this work we foresee and develop an application for the new information provided by a MPGD camera in the form of highly controlled images with high dynamical resolution. We present a new Super Detail Image (S-DI) that efficiently profits of this new information provided by the MPGD camera to obtain very high spatial resolution images. Therefore, the method presented in this work shows that the MPGD camera with SD-I, can produce mammograms with the necessary spatial resolution to detect microcalcifications. It would substantially increase efficiency and accessibility of screening mammography to highly improve breast cancer prevention.

Breast volume assessment: comparing five different techniques.

PubMed

Bulstrode, N; Bellamy, E; Shrotria, S

2001-04-01

Breast volume assessment is not routinely performed pre-operatively because as yet there is no accepted technique. There have been a variety of methods published, but this is the first study to compare these techniques. We compared volume measurements obtained from mammograms (previously compared to mastectomy specimens) with estimates of volume obtained from four other techniques: thermoplastic moulding, magnetic resonance imaging, Archimedes principle and anatomical measurements. We also assessed the acceptability of each method to the patient. Measurements were performed on 10 women, which produced results for 20 breasts. We were able to calculate regression lines between volume measurements obtained from mammography to the other four methods: (1) magnetic resonance imaging (MRI), 379+(0.75 MRI) [r=0.48], (2) Thermoplastic moulding, 132+(1.46 Thermoplastic moulding) [r=0.82], (3) Anatomical measurements, 168+(1.55 Anatomical measurements) [r=0.83]. (4) Archimedes principle, 359+(0.6 Archimedes principle) [r=0.61] all units in cc. The regression curves for the different techniques are variable and it is difficult to reliably compare results. A standard method of volume measurement should be used when comparing volumes before and after intervention or between individual patients, and it is unreliable to compare volume measurements using different methods. Calculating the breast volume from mammography has previously been compared to mastectomy samples and shown to be reasonably accurate. However we feel thermoplastic moulding shows promise and should be further investigated as it gives not only a volume assessment but a three-dimensional impression of the breast shape, which may be valuable in assessing cosmesis following breast-conserving-surgery.

PIP breast implants: rupture rate and correlation with breast cancer

PubMed Central

MOSCHETTA, M.; TELEGRAFO, M.; CORNACCHIA, I.; VINCENTI, L.; RANIERI, V.; CIRILLI, A.; RELLA, L.; IANORA, A.A. STABILE; ANGELELLI, G.

2014-01-01

Aim To evaluate the incidence of Poly Implant Prosthése (PIP) rupture as assessed by magnetic resonance imaging (MRI), the prevalence of the detected signs and the potential correlation with breast carcinoma. Patients and methods 67 patients with silicone breast implants and clinical indications for breast MRI were evaluated for a total of 125 implants: 40 (32%) PIP in 21 patients and 85 non-PIP in 46 patients (68%), the latest considered as control group. A 1.5-T MR imaging device was used in order to assess implant integrity with dedicated sequences and in 6 cases a dynamic study was performed for characterizing breast lesions. Two radiologists with more than 5 years’ experience in the field of MRI evaluated in consensus all MR images searching for the presence of clear signs of intra or extra-capsular implant rupture. Results 20/40 (50%) PIP implants presented signs of intra-capsular rupture: linguine sign in 20 cases (100%), tear-drop sign in 6 (30%). In 12/20 cases (60%), MRI signs of extra-capsular rupture were detected. In the control group, an intra-capsular rupture was diagnosed in 12/85 cases (14%) associated with extra-capsular one in 5/12 cases (42%). Among the six cases with suspected breast lesions, in 2/21 patients with PIP implants (10%) a breast carcinoma was diagnosed (mucinous carcinoma, n=1; invasive ductal carcinoma, n=1). In 4/46 patients (9%) with non-PIP implants, an invasive ductal carcinoma was diagnosed. Conclusion The rupture rate of PIP breast implants is significantly higher than non-PIP (50% vs 14%). MRI represents the most accurate imaging tool for evaluating breast prostheses and the linguine sign is the most common MRI sign to be searched. The incidence of breast carcinoma does not significantly differ between the PIP and non-PIP implants and a direct correlation with breast cancer can not been demonstrated. PMID:25644728

Comparison between Breast MRI and Contrast-Enhanced Spectral Mammography

PubMed Central

Łuczyńska, Elżbieta; Heinze-Paluchowska, Sylwia; Hendrick, Edward; Dyczek, Sonia; Ryś, Janusz; Herman, Krzysztof; Blecharz, Paweł; Jakubowicz, Jerzy

2015-01-01

Background The main goal of this study was to compare contrast-enhanced spectral mammography (CESM) and breast magnetic resonance imaging (MRI) with histopathological results and to compare the sensitivity, accuracy, and positive and negative predictive values for both imaging modalities. Material/Methods After ethics approval, CESM and MRI examinations were performed in 102 patients who had suspicious lesions described in conventional mammography. All visible lesions were evaluated independently by 2 experienced radiologists using BI-RADS classifications (scale 1–5). Dimensions of lesions measured with each modality were compared to postoperative histopathology results. Results There were 102 patients entered into CESM/MRI studies and 118 lesions were identified by the combination of CESM and breast MRI. Histopathology confirmed that 81 of 118 lesions were malignant and 37 were benign. Of the 81 malignant lesions, 72 were invasive cancers and 9 were in situ cancers. Sensitivity was 100% with CESM and 93% with breast MRI. Accuracy was 79% with CESM and 73% with breast MRI. ROC curve areas based on BI-RADS were 0.83 for CESM and 0.84 for breast MRI. Lesion size estimates on CESM and breast MRI were similar, both slightly larger than those from histopathology. Conclusions Our results indicate that CESM has the potential to be a valuable diagnostic method that enables accurate detection of malignant breast lesions, has high negative predictive value, and a false-positive rate similar to that of breast MRI. PMID:25963880

Conventional and phase contrast x-ray imaging techniques and ultrasound imaging method in breast tumor detection: initial comparison studies using phantom

NASA Astrophysics Data System (ADS)

Guo, Yuran; Wu, Di; Omoumi, Farid H.; Li, Yuhua; Wong, Molly Donovan; Ghani, Muhammad U.; Zheng, Bin; Liu, Hong

2018-02-01

The objective of this study was to demonstrate the capability of the high-energy in-line phase contrast imaging in detecting the breast tumors which are undetectable by conventional x-ray imaging but detectable by ultrasound. Experimentally, a CIRS multipurpose breast phantom with heterogeneous 50% glandular and 50% adipose breast tissue was imaged by high-energy in-line phase contrast system, conventional x-ray system and ultrasonography machine. The high-energy in-line phase contrast projection was acquired at 120 kVp, 0.3 mAs with the focal spot size of 18.3 μm. The conventional x-ray projection was acquired at 40 kVp, 3.3 mAs with the focal spot size of 22.26 μm. Both of the x-ray imaging acquisitions were conducted with a unique mean glandular dose of 0.08 mGy. As the result, the high-energy in-line phase contrast system was able to detect one lesion-like object which was also detected by the ultrasonography. This object was spherical shape with the length of about 12.28 mm. Also, the conventional x-ray system was not able to detect any objects. This result indicated the advantages provided by high-energy in-line phase contrast over conventional x-ray system in detecting lesion-like object under the same radiation dose. To meet the needs of current clinical strategies for high-density breasts screening, breast phantoms with higher glandular densities will be employed in future studies.

Raman imaging at biological interfaces: applications in breast cancer diagnosis

PubMed Central

2013-01-01

Background One of the most important areas of Raman medical diagnostics is identification and characterization of cancerous and noncancerous tissues. The methods based on Raman scattering has shown significant potential for probing human breast tissue to provide valuable information for early diagnosis of breast cancer. A vibrational fingerprint from the biological tissue provides information which can be used to identify, characterize and discriminate structures in breast tissue, both in the normal and cancerous environment. Results The paper reviews recent progress in understanding structure and interactions at biological interfaces of the human tissue by using confocal Raman imaging and IR spectroscopy. The important differences between the noncancerous and cancerous human breast tissues were found in regions characteristic for vibrations of carotenoids, fatty acids, proteins, and interfacial water. Particular attention was paid to the role played by unsaturated fatty acids and their derivatives as well as carotenoids and interfacial water. Conclusions We demonstrate that Raman imaging has reached a clinically relevant level in regard to breast cancer diagnosis applications. The results presented in the paper may have serious implications on understanding mechanisms of interactions in living cells under realistically crowded conditions of biological tissue. PMID:23705882

A Comparison of Ultrasound Tomography Methods in Circular Geometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leach, R R; Azevedo, S G; Berryman, J G

2002-01-24

Extremely high quality data was acquired using an experimental ultrasound scanner developed at Lawrence Livermore National Laboratory using a 2D ring geometry with up to 720 transmitter/receiver transducer positions. This unique geometry allows reflection and transmission modes and transmission imaging and quantification of a 3D volume using 2D slice data. Standard image reconstruction methods were applied to the data including straight-ray filtered back projection, reflection tomography, and diffraction tomography. Newer approaches were also tested such as full wave, full wave adjoint method, bent-ray filtered back projection, and full-aperture tomography. A variety of data sets were collected including a formalin-fixed humanmore » breast tissue sample, a commercial ultrasound complex breast phantom, and cylindrical objects with and without inclusions. The resulting reconstruction quality of the images ranges from poor to excellent. The method and results of this study are described including like-data reconstructions produced by different algorithms with side-by-side image comparisons. Comparisons to medical B-scan and x-ray CT scan images are also shown. Reconstruction methods with respect to image quality using resolution, noise, and quantitative accuracy, and computational efficiency metrics will also be discussed.« less

Foundation and methodologies in computer-aided diagnosis systems for breast cancer detection.

PubMed

Jalalian, Afsaneh; Mashohor, Syamsiah; Mahmud, Rozi; Karasfi, Babak; Saripan, M Iqbal B; Ramli, Abdul Rahman B

2017-01-01

Breast cancer is the most prevalent cancer that affects women all over the world. Early detection and treatment of breast cancer could decline the mortality rate. Some issues such as technical reasons, which related to imaging quality and human error, increase misdiagnosis of breast cancer by radiologists. Computer-aided detection systems (CADs) are developed to overcome these restrictions and have been studied in many imaging modalities for breast cancer detection in recent years. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist. In this study, the recent CAD systems for breast cancer detection on different modalities such as mammography, ultrasound, MRI, and biopsy histopathological images are introduced. The foundation of CAD systems generally consist of four stages: Pre-processing, Segmentation, Feature extraction, and Classification. The approaches which applied to design different stages of CAD system are summarised. Advantages and disadvantages of different segmentation, feature extraction and classification techniques are listed. In addition, the impact of imbalanced datasets in classification outcomes and appropriate methods to solve these issues are discussed. As well as, performance evaluation metrics for various stages of breast cancer detection CAD systems are reviewed.

Foundation and methodologies in computer-aided diagnosis systems for breast cancer detection

PubMed Central

Jalalian, Afsaneh; Mashohor, Syamsiah; Mahmud, Rozi; Karasfi, Babak; Saripan, M. Iqbal B.; Ramli, Abdul Rahman B.

2017-01-01

Breast cancer is the most prevalent cancer that affects women all over the world. Early detection and treatment of breast cancer could decline the mortality rate. Some issues such as technical reasons, which related to imaging quality and human error, increase misdiagnosis of breast cancer by radiologists. Computer-aided detection systems (CADs) are developed to overcome these restrictions and have been studied in many imaging modalities for breast cancer detection in recent years. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist. In this study, the recent CAD systems for breast cancer detection on different modalities such as mammography, ultrasound, MRI, and biopsy histopathological images are introduced. The foundation of CAD systems generally consist of four stages: Pre-processing, Segmentation, Feature extraction, and Classification. The approaches which applied to design different stages of CAD system are summarised. Advantages and disadvantages of different segmentation, feature extraction and classification techniques are listed. In addition, the impact of imbalanced datasets in classification outcomes and appropriate methods to solve these issues are discussed. As well as, performance evaluation metrics for various stages of breast cancer detection CAD systems are reviewed. PMID:28435432

Molecular Imaging of Breast Cancer: Present and future directions

NASA Astrophysics Data System (ADS)

Alcantara, David; Pernia Leal, Manuel; Garcia, Irene; Garcia-Martin, Maria Luisa

2014-12-01

Medical imaging technologies have undergone explosive growth over the past few decades and now play a central role in clinical oncology. But the truly transformative power of imaging in the clinical management of cancer patients lies ahead. Today, imaging is at a crossroads, with molecularly targeted imaging agents expected to broadly expand the capabilities of conventional anatomical imaging methods. Molecular imaging will allow clinicians to not only see where a tumour is located in the body, but also to visualize the expression and activity of specific molecules (e.g. proteases and protein kinases) and biological processes (e.g. apoptosis, angiogenesis, and metastasis) that influence tumour behavior and/or response to therapy. Breast cancer, the most common cancer among women and a research area where our group is actively involved, is a very heterogeneous disease with diverse patterns of development and response to treatment. Hence, molecular imaging is expected to have a major impact on this type of cancer, leading to important improvements in diagnosis, individualized treatment, and drug development, as well as our understanding of how breast cancer arises.

Computation of breast ptosis from 3D surface scans of the female torso

PubMed Central

Li, Danni; Cheong, Audrey; Reece, Gregory P.; Crosby, Melissa A.; Fingeret, Michelle C.; Merchant, Fatima A.

2016-01-01

Stereophotography is now finding a niche in clinical breast surgery, and several methods for quantitatively measuring breast morphology from 3D surface images have been developed. Breast ptosis (sagging of the breast), which refers to the extent by which the nipple is lower than the inframammary fold (the contour along which the inferior part of the breast attaches to the chest wall), is an important morphological parameter that is frequently used for assessing the outcome of breast surgery. This study presents a novel algorithm that utilizes three-dimensional (3D) features such as surface curvature and orientation for the assessment of breast ptosis from 3D scans of the female torso. The performance of the computational approach proposed was compared against the consensus of manual ptosis ratings by nine plastic surgeons, and that of current 2D photogrammetric methods. Compared to the 2D methods, the average accuracy for 3D features was ~13% higher, with an increase in precision, recall, and F-score of 37%, 29%, and 33%, respectively. The computational approach proposed provides an improved and unbiased objective method for rating ptosis when compared to qualitative visualization by observers, and distance based 2D photogrammetry approaches. PMID:27643463

Body image dissatisfaction in patients undergoing breast reconstruction: Examining the roles of breast symmetry and appearance investment.

PubMed

Teo, Irene; Reece, Gregory P; Huang, Sheng-Cheng; Mahajan, Kanika; Andon, Johnny; Khanal, Pujjal; Sun, Clement; Nicklaus, Krista; Merchant, Fatima; Markey, Mia K; Fingeret, Michelle Cororve

2018-03-01

Reconstruction as part of treatment for breast cancer is aimed at mitigating body image concerns after mastectomy. Although algorithms have been developed to objectively assess breast reconstruction outcomes, associations between objectively quantified breast aesthetic appearance and patient-reported body image outcomes have not been examined. Further, the role of appearance investment in explaining a patient's body image is not well understood. We investigated the extent to which objectively quantified breast symmetry and patient-reported appearance investment were associated with body image dissatisfaction in patients undergoing cancer-related breast reconstruction. Breast cancer patients in different stages of reconstruction (n = 190) completed self-report measures of appearance investment and body image dissatisfaction. Vertical extent and horizontal extent symmetry values, which are indicators of breast symmetry, were calculated from clinical photographs. Associations among breast symmetry, appearance investment, body image dissatisfaction, and patient clinical factors were examined. Multi-variable regression was used to evaluate the extent to which symmetry and appearance investment were associated with body image dissatisfaction. Vertical extent symmetry, but not horizontal extent symmetry, was associated with body image dissatisfaction. Decreased vertical extent symmetry (β = -.19, P < .05) and increased appearance investment (β = .45, P < .001) were significantly associated with greater body image dissatisfaction while controlling for clinical factors. Breast symmetry and patient appearance investment both significantly contribute to an understanding of patient-reported body image satisfaction during breast reconstruction treatment. Copyright © 2017 John Wiley & Sons, Ltd.

SU-E-T-450: How Important Is a Reproducible Breath Hold for DIBH Breast Radiotherapy?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, H; Wentworth, S; Sintay, B

Purpose: Deep inspiration breath hold (DIBH) for left-sided breast cancer has been shown to reduce heart dose. Surface imaging helps to ensure accurate breast positioning, but does not guarantee a reproducible breath hold (BH) at DIBH treatments. We examine the effects of variable BH positions for DIBH treatments. Methods: Twenty-Five patients with free breathing (FB) and DIBH scans were reviewed. Four plans were created for each patient: 1) FB, 2) DIBH, 3) FB-DIBH – the DIBH plans were copied to the FB images and recalculated (image registration was based on breast tissue), and 4) P-DIBH – a partial BH withmore » the heart shifted midway between the FB and DIBH positions. The FB-DIBH plans give “worst case” scenarios for surface imaging DIBH, where the breast is aligned by surface imaging but the patient is not holding their breath. Students t-tests were used to compare dose metrics. Results: The DIBH plans gave lower heart dose and comparable breast coverage versus FB in all cases. The FB-DIBH plans showed no significant difference versus FB plans for breast coverage, mean heart dose, or maximum heart dose (p >= 0.10). The mean heart dose differed between FB-DIBH and FB by < 2 Gy for all cases, the maximum heart dose differed by < 2 Gy for 21 cases. The P-DIBH plans showed significantly lower mean heart dose than FB (p = 0.01). The mean heart doses for the P-DIBH plans were < FB for 22 cases, the maximum dose < FB for 18 cases. Conclusions: A DIBH plan delivered to a FB patient set-up with surface imaging will yield similar dosimetry to a plan created and delivered FB. A DIBH plan delivered with even a partial BH can give reduced heart dose compared to FB techniques when the breast tissue is well aligned.« less

Quantitative shear wave ultrasound elastography: initial experience in solid breast masses

PubMed Central

2010-01-01

Introduction Shear wave elastography is a new method of obtaining quantitative tissue elasticity data during breast ultrasound examinations. The aims of this study were (1) to determine the reproducibility of shear wave elastography (2) to correlate the elasticity values of a series of solid breast masses with histological findings and (3) to compare shear wave elastography with greyscale ultrasound for benign/malignant classification. Methods Using the Aixplorer® ultrasound system (SuperSonic Imagine, Aix en Provence, France), 53 solid breast lesions were identified in 52 consecutive patients. Two orthogonal elastography images were obtained of each lesion. Observers noted the mean elasticity values in regions of interest (ROI) placed over the stiffest areas on the two elastography images and a mean value was calculated for each lesion. A sub-set of 15 patients had two elastography images obtained by an additional operator. Reproducibility of observations was assessed between (1) two observers analysing the same pair of images and (2) findings from two pairs of images of the same lesion taken by two different operators. All lesions were subjected to percutaneous biopsy. Elastography measurements were correlated with histology results. After preliminary experience with 10 patients a mean elasticity cut off value of 50 kilopascals (kPa) was selected for benign/malignant differentiation. Greyscale images were classified according to the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS). BI-RADS categories 1-3 were taken as benign while BI-RADS categories 4 and 5 were classified as malignant. Results Twenty-three benign lesions and 30 cancers were diagnosed on histology. Measurement of mean elasticity yielded an intraclass correlation coefficient of 0.99 for two observers assessing the same pairs of elastography images. Analysis of images taken by two independent operators gave an intraclass correlation coefficient of 0.80. Shear wave elastography versus greyscale BI-RADS performance figures were sensitivity: 97% vs 87%, specificity: 83% vs 78%, positive predictive value (PPV): 88% vs 84%, negative predictive value (NPV): 95% vs 82% and accuracy: 91% vs 83% respectively. These differences were not statistically significant. Conclusions Shear wave elastography gives quantitative and reproducible information on solid breast lesions with diagnostic accuracy at least as good as greyscale ultrasound with BI-RADS classification. PMID:21122101

Correlation of breast image alignment using biomechanical modelling

NASA Astrophysics Data System (ADS)

Lee, Angela; Rajagopal, Vijay; Bier, Peter; Nielsen, Poul M. F.; Nash, Martyn P.

2009-02-01

Breast cancer is one of the most common causes of cancer death among women around the world. Researchers have found that a combination of imaging modalities (such as x-ray mammography, magnetic resonance, and ultrasound) leads to more effective diagnosis and management of breast cancers because each imaging modality displays different information about the breast tissues. In order to aid clinicians in interpreting the breast images from different modalities, we have developed a computational framework for generating individual-specific, 3D, finite element (FE) models of the breast. Medical images are embedded into this model, which is subsequently used to simulate the large deformations that the breasts undergo during different imaging procedures, thus warping the medical images to the deformed views of the breast in the different modalities. In this way, medical images of the breast taken in different geometric configurations (compression, gravity, etc.) can be aligned according to physically feasible transformations. In order to analyse the accuracy of the biomechanical model predictions, squared normalised cross correlation (NCC2) was used to provide both local and global comparisons of the model-warped images with clinical images of the breast subject to different gravity loaded states. The local comparison results were helpful in indicating the areas for improvement in the biomechanical model. To improve the modelling accuracy, we will need to investigate the incorporation of breast tissue heterogeneity into the model and altering the boundary conditions for the breast model. A biomechanical image registration tool of this kind will help radiologists to provide more reliable diagnosis and localisation of breast cancer.

Using computer assisted image analysis to determine the optimal Ki67 threshold for predicting outcome of invasive breast cancer

PubMed Central

Tay, Timothy Kwang Yong; Thike, Aye Aye; Pathmanathan, Nirmala; Jara-Lazaro, Ana Richelia; Iqbal, Jabed; Sng, Adeline Shi Hui; Ye, Heng Seow; Lim, Jeffrey Chun Tatt; Koh, Valerie Cui Yun; Tan, Jane Sie Yong; Yeong, Joe Poh Sheng; Chow, Zi Long; Li, Hui Hua; Cheng, Chee Leong; Tan, Puay Hoon

2018-01-01

Background Ki67 positivity in invasive breast cancers has an inverse correlation with survival outcomes and serves as an immunohistochemical surrogate for molecular subtyping of breast cancer, particularly ER positive breast cancer. The optimal threshold of Ki67 in both settings, however, remains elusive. We use computer assisted image analysis (CAIA) to determine the optimal threshold for Ki67 in predicting survival outcomes and differentiating luminal B from luminal A breast cancers. Methods Quantitative scoring of Ki67 on tissue microarray (TMA) sections of 440 invasive breast cancers was performed using Aperio ePathology ImmunoHistochemistry Nuclear Image Analysis algorithm, with TMA slides digitally scanned via Aperio ScanScope XT System. Results On multivariate analysis, tumours with Ki67 ≥14% had an increased likelihood of recurrence (HR 1.941, p=0.021) and shorter overall survival (HR 2.201, p=0.016). Similar findings were observed in the subset of 343 ER positive breast cancers (HR 2.409, p=0.012 and HR 2.787, p=0.012 respectively). The value of Ki67 associated with ER+HER2-PR<20% tumours (Luminal B subtype) was found to be <17%. Conclusion Using CAIA, we found optimal thresholds for Ki67 that predict a poorer prognosis and an association with the Luminal B subtype of breast cancer. Further investigation and validation of these thresholds are recommended. PMID:29545924

Objective breast tissue image classification using Quantitative Transmission ultrasound tomography

NASA Astrophysics Data System (ADS)

Malik, Bilal; Klock, John; Wiskin, James; Lenox, Mark

2016-12-01

Quantitative Transmission Ultrasound (QT) is a powerful and emerging imaging paradigm which has the potential to perform true three-dimensional image reconstruction of biological tissue. Breast imaging is an important application of QT and allows non-invasive, non-ionizing imaging of whole breasts in vivo. Here, we report the first demonstration of breast tissue image classification in QT imaging. We systematically assess the ability of the QT images’ features to differentiate between normal breast tissue types. The three QT features were used in Support Vector Machines (SVM) classifiers, and classification of breast tissue as either skin, fat, glands, ducts or connective tissue was demonstrated with an overall accuracy of greater than 90%. Finally, the classifier was validated on whole breast image volumes to provide a color-coded breast tissue volume. This study serves as a first step towards a computer-aided detection/diagnosis platform for QT.

Personalized estimates of radiation dose from dedicated breast CT in a diagnostic population and comparison with diagnostic mammography

PubMed Central

Vedantham, Srinivasan; Shi, Linxi; Karellas, Andrew; O’Connell, Avice M.; Conover, David L.

2013-01-01

This study retrospectively analyzed the mean glandular dose (MGD) to 133 breasts from 132 subjects, all women, who participated in a clinical trial evaluating dedicated breast CT in a diagnostic population. The clinical trial was conducted in adherence to a protocol approved by institutional review boards and the study participants provided written informed consent. Individual estimates of mean glandular dose to each breast from dedicated breast CT was obtained by combining x-ray beam characteristics with estimates of breast dimensions and fibroglandular fraction from volumetric breast CT images, and using normalized glandular dose coefficients. For each study participant and for the breast corresponding to that imaged with breast CT, an estimate of the MGD from diagnostic mammography (including supplemental views) was obtained from the DICOM image headers for comparison. This estimate uses normalized glandular dose coefficients corresponding to a breast with 50% fibroglandular weight fraction. The median fibroglandular weight fraction for the study cohort determined from volumetric breast CT images was 15%. Hence, the MGD from diagnostic mammography was corrected to be representative of the study cohort. Individualized estimates of MGD from breast CT ranged from 5.7 mGy to 27.8 mGy. Corresponding to the breasts imaged with breast CT, the MGD from diagnostic mammography ranged from 2.6 to 31.6 mGy. The mean (± inter-breast SD) and the median MGD (mGy) from dedicated breast CT exam were 13.9±4.6 and 12.6, respectively. For the corresponding breasts, the mean (± inter-breast SD) and the median MGD (mGy) from diagnostic mammography were 12.4±6.3 and 11.1, respectively. Statistical analysis indicated that at the 0.05 level, the distributions of MGD from dedicated breast CT and diagnostic mammography were significantly different (Wilcoxon signed ranks test, p = 0.007). While the interquartile range and the range (maximum-minimum) of MGD from dedicated breast CT was lower than diagnostic mammography, the median MGD from dedicated breast CT was approximately 13.5% higher than that from diagnostic mammography. The MGD for breast CT is based on a 1.45 mm skin layer and that for diagnostic mammography is based on a 4 mm skin layer; thus, favoring a lower estimate for MGD from diagnostic mammography. The median MGD from dedicated breast CT corresponds to the median MGD from 4 to 5 diagnostic mammography views. In comparison, for the same 133 breasts, the mean and the median number of views per breast during diagnostic mammography were 4.53 and 4, respectively. Paired analysis showed that there was approximately equal likelihood of receiving lower MGD from either breast CT or diagnostic mammography. Future work will investigate methods to reduce and optimize radiation dose from dedicated breast CT. PMID:24165162

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

Is Non-invasive Image-Guided Breast Brachytherapy Good? – Jess Hiatt, MS Non-invasive Image-Guided Breast Brachytherapy (NIBB) is an emerging therapy for breast boost treatments as well as Accelerated Partial Breast Irradiation (APBI) using HDR surface breast brachytherapy. NIBB allows for smaller treatment volumes while maintaining optimal target coverage. Considering the real-time image-guidance and immobilization provided by the NIBB modality, minimal margins around the target tissue are necessary. Accelerated Partial Breast Irradiation in brachytherapy: is shorter better? - Dorin Todor, PhD VCU A review of balloon and strut devices will be provided together with the origins of APBI: the interstitial multi-catheter implant.more » A dosimetric and radiobiological perspective will help point out the evolution in breast brachytherapy, both in terms of devices and the protocols/clinical trials under which these devices are used. Improvements in imaging, delivery modalities and convenience are among the factors driving the ultrashort fractionation schedules but our understanding of both local control and toxicities associated with various treatments is lagging. A comparison between various schedules, from a radiobiological perspective, will be given together with a critical analysis of the issues. to review and understand the evolution and development of APBI using brachytherapy methods to understand the basis and limitations of radio-biological ‘equivalence’ between fractionation schedules to review commonly used and proposed fractionation schedules Intra-operative breast brachytherapy: Is one stop shopping best?- Bruce Libby, PhD. University of Virginia A review of intraoperative breast brachytherapy will be presented, including the Targit-A and other trials that have used electronic brachytherapy. More modern approaches, in which the lumpectomy procedure is integrated into an APBI workflow, will also be discussed. Learning Objectives: To review past and current clinical trials for IORT To discuss lumpectomy-scan-plan-treat workflow for IORT.« less

TU-E-217BCD-09: The Feasibility of the Dual-Dictionary Method for Breast Computed Tomography Based on Photon-Counting Detectors.

PubMed

Zhao, B; Ding, H; Lu, Y; Wang, G; Zhao, J; Molloi, S

2012-06-01

To investigate the feasibility of an Iterative Reconstruction (IR) method utilizing the algebraic reconstruction technique coupled with dual-dictionary learning for the application of dedicated breast computed tomography (CT) based on a photon-counting detector. Postmortem breast samples were scanned in an experimental fan beam CT system based on a Cadmium-Zinc-Telluride (CZT) photon-counting detector. Images were reconstructed from various numbers of projections with both IR and Filtered-Back-Projection (FBP) methods. Contrast-to-Noise Ratio (CNR) between the glandular and adipose tissue of postmortem breast samples were calculated to evaluate the quality of images reconstructed from IR and FBP. In addition to CNR, the spatial resolution was also used as a metric to evaluate the quality of images reconstructed from the two methods. This is further studied with a high-resolution phantom consisting of a 14 cm diameter, 10 cm length polymethylmethacrylate (PMMA) cylinder. A 5 cm diameter coaxial volume of Interest insert that contains fine Aluminum wires of various diameters was used to determine spatial resolution. The spatial resolution and CNR were better when identical sinograms were reconstructed in IR as compared to FBP. In comparison with FBP reconstruction, a similar CNR was achieved using IR method with up to a factor of 5 fewer projections. The results of this study suggest that IR method can significantly reduce the required number of projections for a CT reconstruction compared to FBP method to achieve an equivalent CNR. Therefore, the scanning time of a CZT-based CT system using the IR method can potentially be reduced. © 2012 American Association of Physicists in Medicine.

Full Angle Spatial Compound of ARFI images for breast cancer detection.

PubMed

González-Salido, Nuria; Medina, Luis; Camacho, Jorge

2016-09-01

Automated ultrasound breast imaging would overcome most of the limitations that precludes conventional hand-held echography to be an effective screening method for breast cancer diagnosis. If a three dimensional (3D) ultrasound dataset is acquired without manual intervention of the technician, repeatability and patient follow-up could be improved. Furthermore, depending on the system configuration, resolution and contrast could be enhanced with regard to conventional echography, improving lesion detectability and evaluation. Having multiple modalities is another major advantage of these automated systems, currently under development by several research groups. Because of their circular structure, some of them include through-transmission measurements that allow constructing speed of sound and attenuation maps, which adds complementary information to the conventional reflectivity B-Mode image. This work addresses the implementation of the Acoustic Radiation Force Impulse (ARFI) imaging technique in a Full Angle Spatial Compound (FASC) automated breast imaging system. It is of particular interest because of the high specificity of ARFI for breast cancer diagnosis, by representing tissue elasticity differences rather than acoustic reflectivity. First, the image formation process is analyzed and a compounding strategy is proposed for ARFI-FASC. Then, experimental results with a prototype system and two gelatin phantoms are presented: Phantom A with a hard inclusion in a soft background, and phantom B with three soft inclusions in a hard background and with three steel needles. It is demonstrated that the full angle composition of ARFI images improves image quality, enhancing Contrast to Noise Ratio (CNR) from 4.9 to 20.6 and 3.6 to 13.5 in phantoms A and B respectively. Furthermore, this CNR increase improved detectability of small structures (needles) with regard to images obtained from a single location, in which image texture masked their presence. Copyright © 2016 Elsevier B.V. All rights reserved.

Visualization of microcalcifications using photoacoustic imaging: feasibility study

NASA Astrophysics Data System (ADS)

Hsiao, Tsai-Chu; Wang, Po-Hsun; Fan, Chih-Tai; Cheng, Yao-You; Li, Meng-Lin

2011-03-01

Recently, photoacoustic imaging has been intensively studied for blood vessel imaging, and shown its capability of revealing vascular features suggestive of malignancy of breast cancer. In this study, we explore the feasibility of visualization of micro-calcifications using photoacoustic imaging. Breast micro-calcification is also known as one of the most important indicators for early breast cancer detection. The non-ionizing radiation and speckle free nature of photoacoustic imaging overcomes the drawbacks of current diagnostic tools - X-ray mammography and ultrasound imaging, respectively. We employed a 10-MHz photoacoustic imaging system to verify our idea. A sliced chicken breast phantom with granulated calcium hydroxyapatite (HA) - major chemical composition of the breast calcification associated with malignant breast cancers - embedded was imaged. With the near infared (NIR) laser excitation, it is shown that the distribution of ~500 μm HAs can be clearly imaged. In addition, photoacoustic signals from HAs rivals those of blood given an optimal NIR wavelength. In summary, photoacoustic imaging shows its promise for breast micro-calcification detection. Moreover, fusion of the photoacoustic and ultrasound images can reveal the location and distribution of micro-calcifications within anatomical landmarks of the breast tissue, which is clinically useful for biopsy and diagnosis of breast cancer staging.

Comparison of breast percent density estimation from raw versus processed digital mammograms

NASA Astrophysics Data System (ADS)

Li, Diane; Gavenonis, Sara; Conant, Emily; Kontos, Despina

2011-03-01

We compared breast percent density (PD%) measures obtained from raw and post-processed digital mammographic (DM) images. Bilateral raw and post-processed medio-lateral oblique (MLO) images from 81 screening studies were retrospectively analyzed. Image acquisition was performed with a GE Healthcare DS full-field DM system. Image post-processing was performed using the PremiumViewTM algorithm (GE Healthcare). Area-based breast PD% was estimated by a radiologist using a semi-automated image thresholding technique (Cumulus, Univ. Toronto). Comparison of breast PD% between raw and post-processed DM images was performed using the Pearson correlation (r), linear regression, and Student's t-test. Intra-reader variability was assessed with a repeat read on the same data-set. Our results show that breast PD% measurements from raw and post-processed DM images have a high correlation (r=0.98, R2=0.95, p<0.001). Paired t-test comparison of breast PD% between the raw and the post-processed images showed a statistically significant difference equal to 1.2% (p = 0.006). Our results suggest that the relatively small magnitude of the absolute difference in PD% between raw and post-processed DM images is unlikely to be clinically significant in breast cancer risk stratification. Therefore, it may be feasible to use post-processed DM images for breast PD% estimation in clinical settings. Since most breast imaging clinics routinely use and store only the post-processed DM images, breast PD% estimation from post-processed data may accelerate the integration of breast density in breast cancer risk assessment models used in clinical practice.

TU-AB-207-01: Introduction to Tomosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sechopoulos, I.

2015-06-15

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact,more » the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. To learn how to test the performance of tomosynthesis imaging systems. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.« less

TU-AB-207-03: Tomosynthesis: Clinical Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maidment, A.

2015-06-15

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact,more » the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. To learn how to test the performance of tomosynthesis imaging systems. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.« less

TU-AB-207-00: Digital Tomosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

2015-06-15

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact,more » the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. To learn how to test the performance of tomosynthesis imaging systems. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.« less

Generation of a suite of 3D computer-generated breast phantoms from a limited set of human subject data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hsu, Christina M. L.; Palmeri, Mark L.; Department of Anesthesiology, Duke University Medical Center, Durham, North Carolina 27710

2013-04-15

Purpose: The authors previously reported on a three-dimensional computer-generated breast phantom, based on empirical human image data, including a realistic finite-element based compression model that was capable of simulating multimodality imaging data. The computerized breast phantoms are a hybrid of two phantom generation techniques, combining empirical breast CT (bCT) data with flexible computer graphics techniques. However, to date, these phantoms have been based on single human subjects. In this paper, the authors report on a new method to generate multiple phantoms, simulating additional subjects from the limited set of original dedicated breast CT data. The authors developed an image morphingmore » technique to construct new phantoms by gradually transitioning between two human subject datasets, with the potential to generate hundreds of additional pseudoindependent phantoms from the limited bCT cases. The authors conducted a preliminary subjective assessment with a limited number of observers (n= 4) to illustrate how realistic the simulated images generated with the pseudoindependent phantoms appeared. Methods: Several mesh-based geometric transformations were developed to generate distorted breast datasets from the original human subject data. Segmented bCT data from two different human subjects were used as the 'base' and 'target' for morphing. Several combinations of transformations were applied to morph between the 'base' and 'target' datasets such as changing the breast shape, rotating the glandular data, and changing the distribution of the glandular tissue. Following the morphing, regions of skin and fat were assigned to the morphed dataset in order to appropriately assign mechanical properties during the compression simulation. The resulting morphed breast was compressed using a finite element algorithm and simulated mammograms were generated using techniques described previously. Sixty-two simulated mammograms, generated from morphing three human subject datasets, were used in a preliminary observer evaluation where four board certified breast radiologists with varying amounts of experience ranked the level of realism (from 1 ='fake' to 10 ='real') of the simulated images. Results: The morphing technique was able to successfully generate new and unique morphed datasets from the original human subject data. The radiologists evaluated the realism of simulated mammograms generated from the morphed and unmorphed human subject datasets and scored the realism with an average ranking of 5.87 {+-} 1.99, confirming that overall the phantom image datasets appeared more 'real' than 'fake.' Moreover, there was not a significant difference (p > 0.1) between the realism of the unmorphed datasets (6.0 {+-} 1.95) compared to the morphed datasets (5.86 {+-} 1.99). Three of the four observers had overall average rankings of 6.89 {+-} 0.89, 6.9 {+-} 1.24, 6.76 {+-} 1.22, whereas the fourth observer ranked them noticeably lower at 2.94 {+-} 0.7. Conclusions: This work presents a technique that can be used to generate a suite of realistic computerized breast phantoms from a limited number of human subjects. This suite of flexible breast phantoms can be used for multimodality imaging research to provide a known truth while concurrently producing realistic simulated imaging data.« less

Breast imaging. A practical look at its capabilities and its limitations.

PubMed

Clark, R; Nemec, L; Love, N

1992-10-01

The film-screen technique is evolving as the standard for mammography. Sonography is the only other method that currently has a defined role in breast imaging. Mammography should be performed at facilities that have received American College of Radiology accreditation or its equivalent, because technical quality assurance is an important part of mammographic practice. Interpretive quality may be assured by outcome audits performed by mammography facilities. Primary care physicians are best suited to encouraging eligible women to undergo screening studies and should consider these recommendations: Refer patients for screening mammography to accredited facilities according to established guidelines. Educate patients about the need for regular screening. Provide annual breast physical examination. Refresh your knowledge on breast health and the techniques of physical examination if necessary. Teach patients breast self-examination techniques. Demand low-cost, high-quality screening mammography; be aware of local variability of charges and quality.

Breast ultrasound computed tomography using waveform inversion with source encoding

NASA Astrophysics Data System (ADS)

Wang, Kun; Matthews, Thomas; Anis, Fatima; Li, Cuiping; Duric, Neb; Anastasio, Mark A.

2015-03-01

Ultrasound computed tomography (USCT) holds great promise for improving the detection and management of breast cancer. Because they are based on the acoustic wave equation, waveform inversion-based reconstruction methods can produce images that possess improved spatial resolution properties over those produced by ray-based methods. However, waveform inversion methods are computationally demanding and have not been applied widely in USCT breast imaging. In this work, source encoding concepts are employed to develop an accelerated USCT reconstruction method that circumvents the large computational burden of conventional waveform inversion methods. This method, referred to as the waveform inversion with source encoding (WISE) method, encodes the measurement data using a random encoding vector and determines an estimate of the speed-of-sound distribution by solving a stochastic optimization problem by use of a stochastic gradient descent algorithm. Computer-simulation studies are conducted to demonstrate the use of the WISE method. Using a single graphics processing unit card, each iteration can be completed within 25 seconds for a 128 × 128 mm2 reconstruction region. The results suggest that the WISE method maintains the high spatial resolution of waveform inversion methods while significantly reducing the computational burden.

Breast tumor segmentation in DCE-MRI using fully convolutional networks with an application in radiogenomics

NASA Astrophysics Data System (ADS)

Zhang, Jun; Saha, Ashirbani; Zhu, Zhe; Mazurowski, Maciej A.

2018-02-01

Breast tumor segmentation based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) remains an active as well as a challenging problem. Previous studies often rely on manual annotation for tumor regions, which is not only time-consuming but also error-prone. Recent studies have shown high promise of deep learning-based methods in various segmentation problems. However, these methods are usually faced with the challenge of limited number (e.g., tens or hundreds) of medical images for training, leading to sub-optimal segmentation performance. Also, previous methods cannot efficiently deal with prevalent class-imbalance problems in tumor segmentation, where the number of voxels in tumor regions is much lower than that in the background area. To address these issues, in this study, we propose a mask-guided hierarchical learning (MHL) framework for breast tumor segmentation via fully convolutional networks (FCN). Our strategy is first decomposing the original difficult problem into several sub-problems and then solving these relatively simpler sub-problems in a hierarchical manner. To precisely identify locations of tumors that underwent a biopsy, we further propose an FCN model to detect two landmarks defined on nipples. Finally, based on both segmentation probability maps and our identified landmarks, we proposed to select biopsied tumors from all detected tumors via a tumor selection strategy using the pathology location. We validate our MHL method using data for 272 patients, and achieve a mean Dice similarity coefficient (DSC) of 0.72 in breast tumor segmentation. Finally, in a radiogenomic analysis, we show that a previously developed image features show a comparable performance for identifying luminal A subtype when applied to the automatic segmentation and a semi-manual segmentation demonstrating a high promise for fully automated radiogenomic analysis in breast cancer.

Multi-axis dose accumulation of noninvasive image-guided breast brachytherapy through biomechanical modeling of tissue deformation using the finite element method

PubMed Central

Ghadyani, Hamid R.; Bastien, Adam D.; Lutz, Nicholas N.; Hepel, Jaroslaw T.

2015-01-01

Purpose Noninvasive image-guided breast brachytherapy delivers conformal HDR 192Ir brachytherapy treatments with the breast compressed, and treated in the cranial-caudal and medial-lateral directions. This technique subjects breast tissue to extreme deformations not observed for other disease sites. Given that, commercially-available software for deformable image registration cannot accurately co-register image sets obtained in these two states, a finite element analysis based on a biomechanical model was developed to deform dose distributions for each compression circumstance for dose summation. Material and methods The model assumed the breast was under planar stress with values of 30 kPa for Young's modulus and 0.3 for Poisson's ratio. Dose distributions from round and skin-dose optimized applicators in cranial-caudal and medial-lateral compressions were deformed using 0.1 cm planar resolution. Dose distributions, skin doses, and dose-volume histograms were generated. Results were examined as a function of breast thickness, applicator size, target size, and offset distance from the center. Results Over the range of examined thicknesses, target size increased several millimeters as compression thickness decreased. This trend increased with increasing offset distances. Applicator size minimally affected target coverage, until applicator size was less than the compressed target size. In all cases, with an applicator larger or equal to the compressed target size, > 90% of the target covered by > 90% of the prescription dose. In all cases, dose coverage became less uniform as offset distance increased and average dose increased. This effect was more pronounced for smaller target–applicator combinations. Conclusions The model exhibited skin dose trends that matched MC-generated benchmarking results within 2% and clinical observations over a similar range of breast thicknesses and target sizes. The model provided quantitative insight on dosimetric treatment variables over a range of clinical circumstances. These findings highlight the need for careful target localization and accurate identification of compression thickness and target offset. PMID:25829938

Radiotherapy setup displacements in breast cancer patients: 3D surface imaging experience.

PubMed

Cravo Sá, Ana; Fermento, Ana; Neves, Dalila; Ferreira, Sara; Silva, Teresa; Marques Coelho, Carina; Vaandering, Aude; Roma, Ana; Quaresma, Sérgio; Bonnarens, Emmanuel

2018-01-01

In this study, we intend to compare two different setup procedures for female breast cancer patients. Imaging in radiotherapy provides a precise localization of the tumour, increasing the accuracy of the treatment delivery in breast cancer. Twenty breast cancer patients who underwent whole breast radiotherapy (WBRT) were selected for this study. Patients were divided into two groups of ten. Group one (G1) was positioned by tattoos and then the patient positioning was adjusted with the aid of AlignRT (Vision RT, London, UK). In group two (G2), patients were positioned only by tattoos. For both groups, the first 15 fractions were analyzed, a daily kilovoltage (kV) cone beam computed tomography (CBCT) image was made and then the rotational and translational displacements and, posteriorly, the systematic ( Σ ) and random ( σ ) errors were analyzed. The comparison of CBCT displacements for the two groups showed a statistically significant difference in the translational left-right (LR) direction ( ρ  = 0.03), considering that the procedure with AlignRT system has smaller lateral displacements. The results of systematic ( Σ ) and random ( σ ) errors showed that for translational displacements the group positioned only by tattoos (G2) demonstrated higher values of errors when compared with the group positioned with the aid of AlignRT (G1). AlignRT could help the positioning of breast cancer patients; however, it should be used with another imaging method.

Intraoperative Evaluation of Breast Tumor Margins with Optical Coherence Tomography

PubMed Central

Nguyen, Freddy T.; Zysk, Adam M.; Chaney, Eric J.; Kotynek, Jan G.; Oliphant, Uretz J.; Bellafiore, Frank J.; Rowland, Kendrith M.; Johnson, Patricia A.; Boppart, Stephen A.

2009-01-01

As breast cancer screening rates increase, smaller and more numerous lesions are being identified earlier, leading to more breast-conserving surgical procedures. Achieving a clean surgical margin represents a technical challenge with important clinical implications. Optical coherence tomography (OCT) is introduced as an intraoperative high-resolution imaging technique that assesses surgical breast tumor margins by providing real-time microscopic images up to 2 mm beneath the tissue surface. In a study of 37 patients split between training and study groups, OCT images covering 1 cm2 regions were acquired from surgical margins of lumpectomy specimens, registered with ink, and correlated with corresponding histological sections. A 17 patient training set used to establish standard imaging protocols and OCT evaluation criteria demonstrated that areas of higher scattering tissue with a heterogeneous pattern were indicative of tumor cells and tumor tissue, in contrast to lower scattering adipocytes found in normal breast tissue. The remaining 20 patients were enrolled into the feasibility study. Of these lumpectomy specimens, 11 were identified with a positive or close surgical margin and 9 were identified with a negative margin under OCT. Based on histological findings, 9 true positives, 9 true negatives, 2 false positives, and 0 false negatives were found, yielding a sensitivity of 100% and specificity of 82%. These results demonstrate the potential of OCT as a real-time method for intraoperative margin assessment in breast conserving surgeries. PMID:19910294

Breast Tissue Characterization with Photon-counting Spectral CT Imaging: A Postmortem Breast Study

PubMed Central

Ding, Huanjun; Klopfer, Michael J.; Ducote, Justin L.; Masaki, Fumitaro

2014-01-01

Purpose To investigate the feasibility of breast tissue characterization in terms of water, lipid, and protein contents with a spectral computed tomographic (CT) system based on a cadmium zinc telluride (CZT) photon-counting detector by using postmortem breasts. Materials and Methods Nineteen pairs of postmortem breasts were imaged with a CZT-based photon-counting spectral CT system with beam energy of 100 kVp. The mean glandular dose was estimated to be in the range of 1.8–2.2 mGy. The images were corrected for pulse pile-up and other artifacts by using spectral distortion corrections. Dual-energy decomposition was then applied to characterize each breast into water, lipid, and protein contents. The precision of the three-compartment characterization was evaluated by comparing the composition of right and left breasts, where the standard error of the estimations was determined. The results of dual-energy decomposition were compared by using averaged root mean square to chemical analysis, which was used as the reference standard. Results The standard errors of the estimations of the right-left correlations obtained from spectral CT were 7.4%, 6.7%, and 3.2% for water, lipid, and protein contents, respectively. Compared with the reference standard, the average root mean square error in breast tissue composition was 2.8%. Conclusion Spectral CT can be used to accurately quantify the water, lipid, and protein contents in breast tissue in a laboratory study by using postmortem specimens. © RSNA, 2014 PMID:24814180

Detection of the nipple in automated 3D breast ultrasound using coronal slab-average-projection and cumulative probability map

NASA Astrophysics Data System (ADS)

Kim, Hannah; Hong, Helen

2014-03-01

We propose an automatic method for nipple detection on 3D automated breast ultrasound (3D ABUS) images using coronal slab-average-projection and cumulative probability map. First, to identify coronal images that appeared remarkable distinction between nipple-areola region and skin, skewness of each coronal image is measured and the negatively skewed images are selected. Then, coronal slab-average-projection image is reformatted from selected images. Second, to localize nipple-areola region, elliptical ROI covering nipple-areola region is detected using Hough ellipse transform in coronal slab-average-projection image. Finally, to separate the nipple from areola region, 3D Otsu's thresholding is applied to the elliptical ROI and cumulative probability map in the elliptical ROI is generated by assigning high probability to low intensity region. False detected small components are eliminated using morphological opening and the center point of detected nipple region is calculated. Experimental results show that our method provides 94.4% nipple detection rate.

Internet Pornography Use and Sexual Body Image in a Dutch Sample

PubMed Central

Cranney, Stephen

2016-01-01

Objectives A commonly attributed cause of sexual body image dissatisfaction is pornography use. This relationship has received little verification. Methods The relationship between sexual body image dissatisfaction and Internet pornography use was tested using a large-N sample of Dutch respondents. Results/Conclusion Penis size dissatisfaction is associated with pornography use. The relationship between pornography use and breast size dissatisfaction is null. These results support prior speculation and self-reports about the relationship between pornography use and sexual body image among men. These results also support a prior null finding of the relationship between breast size satisfaction for women and pornography use. PMID:26918066

Quantification of breast density with dual energy mammography: A simulation study

PubMed Central

Ducote, Justin L.; Molloi, Sabee

2008-01-01

Breast density, the percentage of glandular breast tissue, has been identified as an important yet underutilized risk factor in the development of breast cancer. A quantitative method to measure breast density with dual energy imaging was investigated using a computer simulation model. Two configurations to measure breast density were evaluated: the usage of monoenergetic beams and an ideal detector, and the usage of polyenergetic beams with spectra from a tungsten anode x-ray tube with a detector modeled after a digital mammography system. The simulation model calculated the mean glandular dose necessary to quantify the variability of breast density to within 1∕3%. The breast was modeled as a semicircle 10 cm in radius with equal homogenous thicknesses of adipose and glandular tissues. Breast thicknesses were considered in the range of 2–10 cm and energies in the range of 10–150 keV for the two monoenergetic beams, and 20–150 kVp for spectra with a tungsten anode x-ray tube. For a 4.2 cm breast thickness, the required mean glandular doses were 0.183 μGy for two monoenergetic beams at 19 and 71 keV, and 9.85 μGy for two polyenergetic spectra from a tungsten anode at 32 and 96 kVp with beam filtrations of 50 μm Rh and 300 μm Cu for the low and high energy beams, respectively. The results suggest that for either configuration, breast density can be precisely measured with dual energy imaging requiring only a small amount of additional dose to the breast. The possibility of using a standard screening mammogram as the low energy image is also discussed. PMID:19175100

Improved Ultrasonic Imaging of the Breast

DTIC Science & Technology

2003-08-01

benign and malignant masses often exhibit only subtle image differences. We have invented a new technique that uses modified ultrasound equipment to form images of ultrasonic angular scatter. This method provides a new source of image contrast and should enhance the detectability of MCs and improve the differentiation of benign and malignant lesions. This method yields high resolution images with minimal statistical variability. In this first year 0 funding, we have formed images in tissue mimicking phantoms and found that

A novel ultrasonic method for measuring breast density and breast cancer risk

NASA Astrophysics Data System (ADS)

Glide-Hurst, Carri K.; Duric, Neb; Littrup, Peter J.

2008-03-01

Women with high mammographic breast density are at 4- to 6-fold increased risk of developing breast cancer compared to women with fatty breasts. However, current breast density estimations rely on mammography, which cannot provide accurate volumetric breast representation. Therefore, we explored two techniques of breast density evaluation via ultrasound tomography. A sample of 93 patients was imaged with our clinical prototype; each dataset contained 45-75 tomograms ranging from near the chest wall through the nipple. Whole breast acoustic velocity was determined by creating image stacks and evaluating the sound speed frequency distribution. Ultrasound percent density (USPD) was determined by segmenting high sound speed areas from each tomogram using k-means clustering, integrating over the entire breast, and dividing by total breast area. Both techniques were independently evaluated using two mammographic density measures: (1) qualitative, determined by a radiologist's visual assessment using BI-RADS Categories, and (2) quantitative, via semi-automatic segmentation to calculate mammographic percent density (MPD) for craniocaudal and medio-lateral oblique mammograms. ~140 m/s difference in acoustic velocity was observed between fatty and dense BI-RADS Categories. Increased sound speed was found with increased BI-RADS Category and quantitative MPD. Furthermore, strong positive associations between USPD, BI-RADS Category, and calculated MPD were observed. These results confirm that utilizing sound speed, both for whole-breast evaluation and segmenting locally, can be implemented to evaluate breast density.

Abnormality detection of mammograms by discriminative dictionary learning on DSIFT descriptors.

PubMed

Tavakoli, Nasrin; Karimi, Maryam; Nejati, Mansour; Karimi, Nader; Reza Soroushmehr, S M; Samavi, Shadrokh; Najarian, Kayvan

2017-07-01

Detection and classification of breast lesions using mammographic images are one of the most difficult studies in medical image processing. A number of learning and non-learning methods have been proposed for detecting and classifying these lesions. However, the accuracy of the detection/classification still needs improvement. In this paper we propose a powerful classification method based on sparse learning to diagnose breast cancer in mammograms. For this purpose, a supervised discriminative dictionary learning approach is applied on dense scale invariant feature transform (DSIFT) features. A linear classifier is also simultaneously learned with the dictionary which can effectively classify the sparse representations. Our experimental results show the superior performance of our method compared to existing approaches.

Three dimensional reconstruction of a human breast carcinoma using routine laboratory equipment and immunohistochemistry

PubMed Central

Kurien, T; Boyce, R W G; Paish, E C; Ronan, J; Maddison, J; Rakha, E A; Green, A R; Ellis, I O

2005-01-01

Aims: To establish a three dimensional reconstruction of an invasive breast carcinoma using basic laboratory equipment to evaluate and characterise the spatial arrangement of the parenchymal cells of the breast. Methods: One hundred and twenty eight sequential 4 μm sections (20 μm apart) of the tumour were stained immunohistochemically with an epithelial specific marker (AE1/AE3) or tumour specific marker (c-erbB-2) to reconstruct two different three dimensional images of the normal and malignant parenchymal cells. Sections were digitally imaged using a microscope, scanner, and digital camera linked to a conventional personal computer. Accurate alignment of the digitalised images was carried out using a semiautomatic graphical method of manual interaction, using the cross correlation coefficient as a goodness of fit measure, and an automatic search algorithm using the Fibonacci search algorithm for automatic alignment. The volume was reconstructed using maximum, minimum point projection and “back to front” opacity blending. Results: The quality of the reconstructed images was distinct and perfect, providing a comprehensive and explicit view of the normal and malignant parenchymal tissues of the breast that is not possible by viewing two dimensional histological sections. Specifically, this approach showed the spatial arrangement of the tumour cells and their relation to the surrounding tissues at a high resolution. Conclusion: This simple and reproducible approach enables the spread and infiltration of invasive carcinoma to be understood and could also be used to analyse the spatial relation between atypical hyperplastic and malignant in situ lesions of the breast. PMID:16126880

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drukker, Karen, E-mail: kdrukker@uchicago.edu; Sennett, Charlene A.; Giger, Maryellen L.

Purpose: Develop a computer-aided detection method and investigate its feasibility for detection of breast cancer in automated 3D ultrasound images of women with dense breasts. Methods: The HIPAA compliant study involved a dataset of volumetric ultrasound image data, “views,” acquired with an automated U-Systems Somo•V{sup ®} ABUS system for 185 asymptomatic women with dense breasts (BI-RADS Composition/Density 3 or 4). For each patient, three whole-breast views (3D image volumes) per breast were acquired. A total of 52 patients had breast cancer (61 cancers), diagnosed through any follow-up at most 365 days after the original screening mammogram. Thirty-one of these patientsmore » (32 cancers) had a screening-mammogram with a clinically assigned BI-RADS Assessment Category 1 or 2, i.e., were mammographically negative. All software used for analysis was developed in-house and involved 3 steps: (1) detection of initial tumor candidates, (2) characterization of candidates, and (3) elimination of false-positive candidates. Performance was assessed by calculating the cancer detection sensitivity as a function of the number of “marks” (detections) per view. Results: At a single mark per view, i.e., six marks per patient, the median detection sensitivity by cancer was 50.0% (16/32) ± 6% for patients with a screening mammogram-assigned BI-RADS category 1 or 2—similar to radiologists’ performance sensitivity (49.9%) for this dataset from a prior reader study—and 45.9% (28/61) ± 4% for all patients. Conclusions: Promising detection sensitivity was obtained for the computer on a 3D ultrasound dataset of women with dense breasts at a rate of false-positive detections that may be acceptable for clinical implementation.« less

Dual-energy contrast-enhanced digital mammography (DE-CEDM): optimization on digital subtraction with practical x-ray low/high-energy spectra

NASA Astrophysics Data System (ADS)

Chen, Biao; Jing, Zhenxue; Smith, Andrew P.; Parikh, Samir; Parisky, Yuri

2006-03-01

Dual-energy contrast enhanced digital mammography (DE-CEDM), which is based upon the digital subtraction of low/high-energy image pairs acquired before/after the administration of contrast agents, may provide physicians physiologic and morphologic information of breast lesions and help characterize their probability of malignancy. This paper proposes to use only one pair of post-contrast low / high-energy images to obtain digitally subtracted dual-energy contrast-enhanced images with an optimal weighting factor deduced from simulated characteristics of the imaging chain. Based upon our previous CEDM framework, quantitative characteristics of the materials and imaging components in the x-ray imaging chain, including x-ray tube (tungsten) spectrum, filters, breast tissues / lesions, contrast agents (non-ionized iodine solution), and selenium detector, were systemically modeled. Using the base-material (polyethylene-PMMA) decomposition method based on entrance low / high-energy x-ray spectra and breast thickness, the optimal weighting factor was calculated to cancel the contrast between fatty and glandular tissues while enhancing the contrast of iodized lesions. By contrast, previous work determined the optimal weighting factor through either a calibration step or through acquisition of a pre-contrast low/high-energy image pair. Computer simulations were conducted to determine weighting factors, lesions' contrast signal values, and dose levels as functions of x-ray techniques and breast thicknesses. Phantom and clinical feasibility studies were performed on a modified Selenia full field digital mammography system to verify the proposed method and computer-simulated results. The resultant conclusions from the computer simulations and phantom/clinical feasibility studies will be used in the upcoming clinical study.

Computer-assisted assessment of ultrasound real-time elastography: initial experience in 145 breast lesions.

PubMed

Zhang, Xue; Xiao, Yang; Zeng, Jie; Qiu, Weibao; Qian, Ming; Wang, Congzhi; Zheng, Rongqin; Zheng, Hairong

2014-01-01

To develop and evaluate a computer-assisted method of quantifying five-point elasticity scoring system based on ultrasound real-time elastography (RTE), for classifying benign and malignant breast lesions, with pathologic results as the reference standard. Conventional ultrasonography (US) and RTE images of 145 breast lesions (67 malignant, 78 benign) were performed in this study. Each lesion was automatically contoured on the B-mode image by the level set method and mapped on the RTE image. The relative elasticity value of each pixel was reconstructed and classified into hard or soft by the fuzzy c-means clustering method. According to the hardness degree inside lesion and its surrounding tissue, the elasticity score of the RTE image was computed in an automatic way. Visual assessments of the radiologists were used for comparing the diagnostic performance. Histopathologic examination was used as the reference standard. The Student's t test and receiver operating characteristic (ROC) curve analysis were performed for statistical analysis. Considering score 4 or higher as test positive for malignancy, the diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 93.8% (136/145), 92.5% (62/67), 94.9% (74/78), 93.9% (62/66), and 93.7% (74/79) for the computer-assisted scheme, and 89.7% (130/145), 85.1% (57/67), 93.6% (73/78), 92.0% (57/62), and 88.0% (73/83) for manual assessment. Area under ROC curve (Az value) for the proposed method was higher than the Az value for visual assessment (0.96 vs. 0.93). Computer-assisted quantification of classical five-point scoring system can significantly eliminate the interobserver variability and thereby improve the diagnostic confidence of classifying the breast lesions to avoid unnecessary biopsy. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Mammogram image quality as a potential contributor to disparities in breast cancer stage at diagnosis: an observational study

PubMed Central

2013-01-01

Background In an ongoing study of racial/ethnic disparities in breast cancer stage at diagnosis, we consented patients to allow us to review their mammogram images, in order to examine the potential role of mammogram image quality on this disparity. Methods In a population-based study of urban breast cancer patients, a single breast imaging specialist (EC) performed a blinded review of the index mammogram that prompted diagnostic follow-up, as well as recent prior mammograms performed approximately one or two years prior to the index mammogram. Seven indicators of image quality were assessed on a five-point Likert scale, where 4 and 5 represented good and excellent quality. These included 3 technologist-associated image quality (TAIQ) indicators (positioning, compression, sharpness), and 4 machine associated image quality (MAIQ) indicators (contrast, exposure, noise and artifacts). Results are based on 494 images examined for 268 patients, including 225 prior images. Results Whereas MAIQ was generally high, TAIQ was more variable. In multivariable models of sociodemographic predictors of TAIQ, less income was associated with lower TAIQ (p < 0.05). Among prior mammograms, lower TAIQ was subsequently associated with later stage at diagnosis, even after adjusting for multiple patient and practice factors (OR = 0.80, 95% CI: 0.65, 0.99). Conclusions Considerable gains could be made in terms of increasing image quality through better positioning, compression and sharpness, gains that could impact subsequent stage at diagnosis. PMID:23621946

Clinical and ultrasonographic features of male breast tumors: A retrospective analysis

PubMed Central

Li, Anna Fen-Yau; Chou, Yi-Hong; Hsu, Hui-Chen; Chen, Ying-Yuan

2018-01-01

Objective The purpose of this study was to determine clinical and ultrasonographic characteristics of male breast tumors. Methods The medical records of male patients with breast lesions were retrieved from an electronic medical record database and a pathology database and retrospectively reviewed. A total of 112 men (125 breast masses) with preoperative breast ultrasonography (US) were included (median age, 59.50 years; age range, 15–96 years). Data extracted included patient age, if the lesions were bilateral, palpable, and tender, and the presence of nipple discharge. Breast lesion features on static US images were reviewed by three experienced radiologists without knowledge of physical examination or pathology results, original breast US image interpretations, or surgical outcomes. The US features were documented according to the BI-RADS (Breast Imaging-Reporting and Data System) US lexicons. A forth radiologist compiled the data for analysis. Results Of the 125 breast masses, palpable tender lumps and bilateral synchronous masses were more likely to be benign than malignant (both, 100% vs 0%, P < 0.05). Advanced age and bloody discharge from nipples were common in malignant lesions (P <0.05). A mass eccentric to a nipple, irregular shape, the presence of an echogenic halo, predominantly internal vascularity, and rich color flow signal on color Doppler ultrasound were significantly related to malignancy (all, P < 0.05). An echogenic halo and the presence of rich color flow signal were independent predictors of malignancy. Conclusion Specific clinical and US characteristics of male breast tumors may help guide treatment, and determine if surgery or conservative treatment is preferable. PMID:29558507

Role of Nuclear Morphometry in Breast Cancer and its Correlation with Cytomorphological Grading of Breast Cancer: A Study of 64 Cases

PubMed Central

Kashyap, Anamika; Jain, Manjula; Shukla, Shailaja; Andley, Manoj

2018-01-01

Background: Fine needle aspiration cytology (FNAC) is a simple, rapid, inexpensive, and reliable method of diagnosis of breast mass. Cytoprognostic grading in breast cancers is important to identify high-grade tumors. Computer-assisted image morphometric analysis has been developed to quantitate as well as standardize various grading systems. Aims: To apply nuclear morphometry on cytological aspirates of breast cancer and evaluate its correlation with cytomorphological grading with derivation of suitable cutoff values between various grades. Settings and Designs: Descriptive cross-sectional hospital-based study. Materials and Methods: This study included 64 breast cancer cases (29 of grade 1, 22 of grade 2, and 13 of grade 3). Image analysis was performed on Papanicolaou stained FNAC slides by NIS –Elements Advanced Research software (Ver 4.00). Nuclear morphometric parameters analyzed included 5 nuclear size, 2 shape, 4 texture, and 2 density parameters. Results: Nuclear size parameters showed an increase in values with increasing cytological grades of carcinoma. Nuclear shape parameters were not found to be significantly different between the three grades. Among nuclear texture parameters, sum intensity, and sum brightness were found to be different between the three grades. Conclusion: Nuclear morphometry can be applied to augment the cytology grading of breast cancer and thus help in classifying patients into low and high-risk groups. PMID:29403169

Diffuse Optical Imaging and Spectroscopy of the Human Breast for Quantitative Oximetry with Depth Resolution

NASA Astrophysics Data System (ADS)

Yu, Yang

Near-infrared spectral imaging for breast cancer diagnostics and monitoring has been a hot research topic for the past decade. Here we present instrumentation for diffuse optical imaging of breast tissue with tandem scan of a single source-detector pair with broadband light in transmission geometry for tissue oximetry. The efforts to develop the continuous-wave (CW) domain instrument have been described, and a frequency-domain (FD) system is also used to measure the bulk tissue optical properties and the breast thickness distribution. We also describe the efforts to improve the data processing codes in the 2D spatial domain for better noise suppression, contrast enhancement, and spectral analysis. We developed a paired-wavelength approach, which is based on finding pairs of wavelength that feature the same optical contrast, to quantify the tissue oxygenation for the absorption structures detected in the 2D structural image. A total of eighteen subjects, two of whom were bearing breast cancer on their right breasts, were measured with this hybrid CW/FD instrument and processed with the improved algorithms. We obtained an average tissue oxygenation value of 87% +/- 6% from the healthy breasts, significantly higher than that measured in the diseased breasts (69% +/- 14%) (p < 0.01). For the two diseased breasts, the tumor areas bear hypoxia signatures versus the remainder of the breast, with oxygenation values of 49 +/- 11% (diseased region) vs. 61 +/- 16% (healthy regions) for the breast with invasive ductal carcinoma, and 58 +/- 8% (diseased region) vs 77 +/- 11% (healthy regions) for ductal carcinoma in situ. Our subjects came from various ethnical/racial backgrounds, and two-thirds of our subjects were less than thirty years old, indicating a potential to apply the optical mammography to a broad population. The second part of this thesis covers the topic of depth discrimination, which is lacking with our single source-detector scan system. Based on an off-axis detection method, we incorporated an additional detector to acquire a second set of image independently. We then proposed an inner-product approach to associate absorption structures detected in the on-axis image with those detected in the off-axis image. The spatial coordinate difference for the same structure between the two images is directly related to the depth of the corresponding structure, and the monotonic dependence can be quantified by perturbation theory of the diffusion equation. A preliminary phantom study shows good agreement between the measured and the actual depth of embedded structures, and human measurements show the capability to assign a depth coordinate to the more complex absorption structures inside the breast.

Contrast enhanced imaging with a stationary digital breast tomosynthesis system

NASA Astrophysics Data System (ADS)

Puett, Connor; Calliste, Jabari; Wu, Gongting; Inscoe, Christina R.; Lee, Yueh Z.; Zhou, Otto; Lu, Jianping

2017-03-01

Digital breast tomosynthesis (DBT) captures some depth information and thereby improves the conspicuity of breast lesions, compared to standard mammography. Using contrast during DBT may also help distinguish malignant from benign sites. However, adequate visualization of the low iodine signal requires a subtraction step to remove background signal and increase lesion contrast. Additionally, attention to factors that limit contrast, including scatter, noise, and artifact, are important during the image acquisition and post-acquisition processing steps. Stationary DBT (sDBT) is an emerging technology that offers a higher spatial and temporal resolution than conventional DBT. This phantom-based study explored contrast-enhanced sDBT (CE sDBT) across a range of clinically-appropriate iodine concentrations, lesion sizes, and breast thicknesses. The protocol included an effective scatter correction method and an iterative reconstruction technique that is unique to the sDBT system. The study demonstrated the ability of this CE sDBT system to collect projection images adequate for both temporal subtraction (TS) and dual-energy subtraction (DES). Additionally, the reconstruction approach preserved the improved contrast-to-noise ratio (CNR) achieved in the subtraction step. Finally, scatter correction increased the iodine signal and CNR of iodine-containing regions in projection views and reconstructed image slices during both TS and DES. These findings support the ongoing study of sDBT as a potentially useful tool for contrast-enhanced breast imaging and also highlight the significant effect that scatter has on image quality during DBT.

A Standard Mammography Unit - Standard 3D Ultrasound Probe Fusion Prototype: First Results.

PubMed

Schulz-Wendtland, Rüdiger; Jud, Sebastian M; Fasching, Peter A; Hartmann, Arndt; Radicke, Marcus; Rauh, Claudia; Uder, Michael; Wunderle, Marius; Gass, Paul; Langemann, Hanna; Beckmann, Matthias W; Emons, Julius

2017-06-01

The combination of different imaging modalities through the use of fusion devices promises significant diagnostic improvement for breast pathology. The aim of this study was to evaluate image quality and clinical feasibility of a prototype fusion device (fusion prototype) constructed from a standard tomosynthesis mammography unit and a standard 3D ultrasound probe using a new method of breast compression. Imaging was performed on 5 mastectomy specimens from patients with confirmed DCIS or invasive carcinoma (BI-RADS ™ 6). For the preclinical fusion prototype an ABVS system ultrasound probe from an Acuson S2000 was integrated into a MAMMOMAT Inspiration (both Siemens Healthcare Ltd) and, with the aid of a newly developed compression plate, digital mammogram and automated 3D ultrasound images were obtained. The quality of digital mammogram images produced by the fusion prototype was comparable to those produced using conventional compression. The newly developed compression plate did not influence the applied x-ray dose. The method was not more labour intensive or time-consuming than conventional mammography. From the technical perspective, fusion of the two modalities was achievable. In this study, using only a few mastectomy specimens, the fusion of an automated 3D ultrasound machine with a standard mammography unit delivered images of comparable quality to conventional mammography. The device allows simultaneous ultrasound - the second important imaging modality in complementary breast diagnostics - without increasing examination time or requiring additional staff.

Imaging of common breast implants and implant-related complications: A pictorial essay

PubMed Central

Shah, Amisha T; Jankharia, Bijal B

2016-01-01

The number of women undergoing breast implant procedures is increasing exponentially. It is, therefore, imperative for a radiologist to be familiar with the normal and abnormal imaging appearances of common breast implants. Diagnostic imaging studies such as mammography, ultrasonography, and magnetic resonance imaging are used to evaluate implant integrity, detect abnormalities of the implant and its surrounding capsule, and detect breast conditions unrelated to implants. Magnetic resonance imaging of silicone breast implants, with its high sensitivity and specificity for detecting implant rupture, is the most reliable modality to asses implant integrity. Whichever imaging modality is used, the overall aim of imaging breast implants is to provide the pertinent information about implant integrity, detect implant failures, and to detect breast conditions unrelated to the implants, such as cancer. PMID:27413269

Imaging of common breast implants and implant-related complications: A pictorial essay.

PubMed

Shah, Amisha T; Jankharia, Bijal B

2016-01-01

The number of women undergoing breast implant procedures is increasing exponentially. It is, therefore, imperative for a radiologist to be familiar with the normal and abnormal imaging appearances of common breast implants. Diagnostic imaging studies such as mammography, ultrasonography, and magnetic resonance imaging are used to evaluate implant integrity, detect abnormalities of the implant and its surrounding capsule, and detect breast conditions unrelated to implants. Magnetic resonance imaging of silicone breast implants, with its high sensitivity and specificity for detecting implant rupture, is the most reliable modality to asses implant integrity. Whichever imaging modality is used, the overall aim of imaging breast implants is to provide the pertinent information about implant integrity, detect implant failures, and to detect breast conditions unrelated to the implants, such as cancer.

Wavelet-based multifractal analysis of dynamic infrared thermograms to assist in early breast cancer diagnosis

PubMed Central

Gerasimova, Evgeniya; Audit, Benjamin; Roux, Stephane G.; Khalil, André; Gileva, Olga; Argoul, Françoise; Naimark, Oleg; Arneodo, Alain

2014-01-01

Breast cancer is the most common type of cancer among women and despite recent advances in the medical field, there are still some inherent limitations in the currently used screening techniques. The radiological interpretation of screening X-ray mammograms often leads to over-diagnosis and, as a consequence, to unnecessary traumatic and painful biopsies. Here we propose a computer-aided multifractal analysis of dynamic infrared (IR) imaging as an efficient method for identifying women with risk of breast cancer. Using a wavelet-based multi-scale method to analyze the temporal fluctuations of breast skin temperature collected from a panel of patients with diagnosed breast cancer and some female volunteers with healthy breasts, we show that the multifractal complexity of temperature fluctuations observed in healthy breasts is lost in mammary glands with malignant tumor. Besides potential clinical impact, these results open new perspectives in the investigation of physiological changes that may precede anatomical alterations in breast cancer development. PMID:24860510

[Digital breast tomosynthesis : technical principles, current clinical relevance and future perspectives].

PubMed

Hellerhoff, K

2010-11-01

In recent years digital full field mammography has increasingly replaced conventional film mammography. High quality imaging is guaranteed by high quantum efficiency and very good contrast resolution with optimized dosing even for women with dense glandular tissue. However, digital mammography remains a projection procedure by which overlapping tissue limits the detectability of subtle alterations. Tomosynthesis is a procedure developed from digital mammography for slice examination of breasts which eliminates the effects of overlapping tissue and allows 3D imaging of breasts. A curved movement of the X-ray tube during scanning allows the acquisition of many 2D images from different angles. Subseqently, reconstruction algorithms employing a shift and add method improve the recognition of details at a defined level and at the same time eliminate smear artefacts due to overlapping structures. The total dose corresponds to that of conventional mammography imaging. The technical procedure, including the number of levels, suitable anodes/filter combinations, angle regions of images and selection of reconstruction algorithms, is presently undergoing optimization. Previous studies on the clinical value of tomosynthesis have examined screening parameters, such as recall rate and detection rate as well as information on tumor extent for histologically proven breast tumors. More advanced techniques, such as contrast medium-enhanced tomosynthesis, are presently under development and dual-energy imaging is of particular importance.

Multiscale nonlinear microscopy and widefield white light imaging enables rapid histological imaging of surgical specimen margins

PubMed Central

Giacomelli, Michael G.; Yoshitake, Tadayuki; Cahill, Lucas C.; Vardeh, Hilde; Quintana, Liza M.; Faulkner-Jones, Beverly E.; Brooker, Jeff; Connolly, James L.; Fujimoto, James G.

2018-01-01

The ability to histologically assess surgical specimens in real-time is a long-standing challenge in cancer surgery, including applications such as breast conserving therapy (BCT). Up to 40% of women treated with BCT for breast cancer require a repeat surgery due to postoperative histological findings of close or positive surgical margins using conventional formalin fixed paraffin embedded histology. Imaging technologies such as nonlinear microscopy (NLM), combined with exogenous fluorophores can rapidly provide virtual H&E imaging of surgical specimens without requiring microtome sectioning, facilitating intraoperative assessment of margin status. However, the large volume of typical surgical excisions combined with the need for rapid assessment, make comprehensive cellular resolution margin assessment during surgery challenging. To address this limitation, we developed a multiscale, real-time microscope with variable magnification NLM and real-time, co-registered position display using a widefield white light imaging system. Margin assessment can be performed rapidly under operator guidance to image specific regions of interest located using widefield imaging. Using simulated surgical margins dissected from human breast excisions, we demonstrate that multi-centimeter margins can be comprehensively imaged at cellular resolution, enabling intraoperative margin assessment. These methods are consistent with pathology assessment performed using frozen section analysis (FSA), however NLM enables faster and more comprehensive assessment of surgical specimens because imaging can be performed without freezing and cryo-sectioning. Therefore, NLM methods have the potential to be applied to a wide range of intra-operative applications. PMID:29761001

Ultrashort Microwave-Pumped Real-Time Thermoacoustic Breast Tumor Imaging System.

PubMed

Ye, Fanghao; Ji, Zhong; Ding, Wenzheng; Lou, Cunguang; Yang, Sihua; Xing, Da

2016-03-01

We report the design of a real-time thermoacoustic (TA) scanner dedicated to imaging deep breast tumors and investigate its imaging performance. The TA imaging system is composed of an ultrashort microwave pulse generator and a ring transducer array with 384 elements. By vertically scanning the transducer array that encircles the breast phantom, we achieve real-time, 3D thermoacoustic imaging (TAI) with an imaging speed of 16.7 frames per second. The stability of the microwave energy and its distribution in the cling-skin acoustic coupling cup are measured. The results indicate that there is a nearly uniform electromagnetic field in each XY-imaging plane. Three plastic tubes filled with salt water are imaged dynamically to evaluate the real-time performance of our system, followed by 3D imaging of an excised breast tumor embedded in a breast phantom. Finally, to demonstrate the potential for clinical applications, the excised breast of a ewe embedded with an ex vivo human breast tumor is imaged clearly with a contrast of about 1:2.8. The high imaging speed, large field of view, and 3D imaging performance of our dedicated TAI system provide the potential for clinical routine breast screening.

Semi-automated delineation of breast cancer tumors and subsequent materialization using three-dimensional printing (rapid prototyping).

PubMed

Schulz-Wendtland, Rüdiger; Harz, Markus; Meier-Meitinger, Martina; Brehm, Barbara; Wacker, Till; Hahn, Horst K; Wagner, Florian; Wittenberg, Thomas; Beckmann, Matthias W; Uder, Michael; Fasching, Peter A; Emons, Julius

2017-03-01

Three-dimensional (3D) printing has become widely available, and a few cases of its use in clinical practice have been described. The aim of this study was to explore facilities for the semi-automated delineation of breast cancer tumors and to assess the feasibility of 3D printing of breast cancer tumors. In a case series of five patients, different 3D imaging methods-magnetic resonance imaging (MRI), digital breast tomosynthesis (DBT), and 3D ultrasound-were used to capture 3D data for breast cancer tumors. The volumes of the breast tumors were calculated to assess the comparability of the breast tumor models, and the MRI information was used to render models on a commercially available 3D printer to materialize the tumors. The tumor volumes calculated from the different 3D methods appeared to be comparable. Tumor models with volumes between 325 mm 3 and 7,770 mm 3 were printed and compared with the models rendered from MRI. The materialization of the tumors reflected the computer models of them. 3D printing (rapid prototyping) appears to be feasible. Scenarios for the clinical use of the technology might include presenting the model to the surgeon to provide a better understanding of the tumor's spatial characteristics in the breast, in order to improve decision-making in relation to neoadjuvant chemotherapy or surgical approaches. J. Surg. Oncol. 2017;115:238-242. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Regret associated with the decision for breast reconstruction: the association of negative body image, distress and surgery characteristics with decision regret.

PubMed

Sheehan, Joanne; Sherman, Kerry A; Lam, Thomas; Boyages, John

2008-01-01

This study investigated the influence of psychosocial and surgical factors on decision regret among 123 women diagnosed with breast cancer who had undergone immediate (58%) or delayed (42%) breast reconstruction following mastectomy. The majority of participants (52.8%, n = 65) experienced no decision regret, 27.6% experienced mild regret and 19.5% moderate to strong regret. Bivariate analyses indicated that decision regret was associated with negative body image and psychological distress - intrusion and avoidance. There were no differences in decision regret either with respect to methods or timing patterns of reconstructive surgery. Multinominal logistic regression analysis showed that, when controlling for mood state and time since last reconstructive procedure, increases in negative body image were associated with increased likelihood of experiencing decision regret. These findings highlight the need for optimal input from surgeons and therapists in order to promote realistic expectations regarding the outcome of breast reconstruction and to reduce the likelihood of women experiencing decision regret.

Automated detection of breast cancer in resected specimens with fluorescence lifetime imaging

NASA Astrophysics Data System (ADS)

Phipps, Jennifer E.; Gorpas, Dimitris; Unger, Jakob; Darrow, Morgan; Bold, Richard J.; Marcu, Laura

2018-01-01

Re-excision rates for breast cancer lumpectomy procedures are currently nearly 25% due to surgeons relying on inaccurate or incomplete methods of evaluating specimen margins. The objective of this study was to determine if cancer could be automatically detected in breast specimens from mastectomy and lumpectomy procedures by a classification algorithm that incorporated parameters derived from fluorescence lifetime imaging (FLIm). This study generated a database of co-registered histologic sections and FLIm data from breast cancer specimens (N  =  20) and a support vector machine (SVM) classification algorithm able to automatically detect cancerous, fibrous, and adipose breast tissue. Classification accuracies were greater than 97% for automated detection of cancerous, fibrous, and adipose tissue from breast cancer specimens. The classification worked equally well for specimens scanned by hand or with a mechanical stage, demonstrating that the system could be used during surgery or on excised specimens. The ability of this technique to simply discriminate between cancerous and normal breast tissue, in particular to distinguish fibrous breast tissue from tumor, which is notoriously challenging for optical techniques, leads to the conclusion that FLIm has great potential to assess breast cancer margins. Identification of positive margins before waiting for complete histologic analysis could significantly reduce breast cancer re-excision rates.

Imaging characteristics of scintimammography using parallel-hole and pinhole collimators

NASA Astrophysics Data System (ADS)

Tsui, B. M. W.; Wessell, D. E.; Zhao, X. D.; Wang, W. T.; Lewis, D. P.; Frey, E. C.

1998-08-01

The purpose of the study is to investigate the imaging characteristics of scintimammography (SM) using parallel-hole (PR) and pinhole (PN) collimators in a clinical setting. Experimental data were acquired from a phantom that models the breast with small lesions using a low energy high resolution (LEHR) PR and a PN collimator. At close distances, the PN collimator provides better spatial resolution and higher detection efficiency than the PR collimator, at the expense of a smaller field-of-view (FOV). Detection of small breast lesions can be further enhanced by noise smoothing, field uniformity correction, scatter subtraction and resolution recovery filtering. Monte Carlo (MC) simulation data were generated from the 3D MCAT phantom that realistically models the Tc-99m sestamibi uptake and attenuation distributions in an average female patient. For both PR and PN collimation, the scatter to primary ratio (S/P) decreases from the base of the breast to the nipple and is higher in the left than right breast due to scatter of photons from the heart. Results from the study add to understanding of the imaging characteristics of SM using PR and PN collimators and assist in the design of data acquisition and image processing methods to enhance the detection of breast lesions using SM.

Breast density characterization using texton distributions.

PubMed

Petroudi, Styliani; Brady, Michael

2011-01-01

Breast density has been shown to be one of the most significant risks for developing breast cancer, with women with dense breasts at four to six times higher risk. The Breast Imaging Reporting and Data System (BI-RADS) has a four class classification scheme that describes the different breast densities. However, there is great inter and intra observer variability among clinicians in reporting a mammogram's density class. This work presents a novel texture classification method and its application for the development of a completely automated breast density classification system. The new method represents the mammogram using textons, which can be thought of as the building blocks of texture under the operational definition of Leung and Malik as clustered filter responses. The new proposed method characterizes the mammographic appearance of the different density patterns by evaluating the texton spatial dependence matrix (TDSM) in the breast region's corresponding texton map. The TSDM is a texture model that captures both statistical and structural texture characteristics. The normalized TSDM matrices are evaluated for mammograms from the different density classes and corresponding texture models are established. Classification is achieved using a chi-square distance measure. The fully automated TSDM breast density classification method is quantitatively evaluated on mammograms from all density classes from the Oxford Mammogram Database. The incorporation of texton spatial dependencies allows for classification accuracy reaching over 82%. The breast density classification accuracy is better using texton TSDM compared to simple texton histograms.

TU-CD-207-12: Impact of Anatomical Noise On Detection Performance of Microcalcifications in Multi-Contrast Breast Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garrett, J; Ge, Y; Li, K

2015-06-15

Purpose: The anatomical noise power spectra (NPS) for differential phase contrast (DPC) and dark field (DF) imaging have recently been characterized using a power-law model with two parameters, alpha and beta, an innovative extension to the methodology used in x-ray attenuation based breast imaging such as mammography, DBT, or cone-beam CT. Beta values of 3.6, 2.6, and 1.3 have been measured for absorption, DPC, and DF respectively for cadaver breasts imaged in the coronal plane; these dramatic differences should be reflected in their detection performance. The purpose of this study was to determine the impact of anatomical noise on breastmore » calcification detection and compare the detection performance of the three contrast mechanisms of a multi-contrast x-ray imaging system. Methods: In our studies, a calcification image object was segmented out of the multi-contrast images of a cadaver breast specimen. 50 measured total NPS were measured from breast cadavers directly. The ideal model observer detectability was calculated for a range of doses (5–100%) and a range of calcification sizes (diameter = 0.25–2.5 mm). Results: Overall we found the highest average detectability corresponded to DPC imaging (7.4 for 1 mm calc.), with DF the next highest (3.8 for 1 mm calc.), and absorption the lowest (3.2 for 1 mm calc.). However, absorption imaging also showed the slowest dependence on dose of the three modalities due to the significant anatomical noise. DPC showed a peak detectability for calcifications ∼1.25 mm in diameter, DF showed a peak for calcifications around 0.75 mm in diameter, and absorption imaging had no such peak in the range explored. Conclusion: Understanding imaging performance for DPC and DF is critical to transition these modalities to the clinic. The results presented here offer new insight into how these modalities complement absorption imaging to maximize the likelihood of detecting early breast cancers. J. Garrett, Y. Ge, K. Li: Nothing to disclose. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.« less

Delineating Extramammary Findings at Breast MR Imaging.

PubMed

Gao, Yiming; Ibidapo, Opeyemi; Toth, Hildegard K; Moy, Linda

2017-01-01

Breast magnetic resonance (MR) imaging is the only breast imaging modality that consistently encompasses extramammary structures in the thorax and upper abdomen. Incidental extramammary findings on breast MR images of patients with a history of breast cancer or other malignancies are significantly more likely to be malignant and may affect staging and treatment. An understanding of the frequency, distribution, and context of extramammary findings on breast MR images and a familiarity with common and uncommon sites of breast cancer metastasis inform the differential diagnosis and prompt the appropriate diagnostic next step, to differentiate benign from malignant findings. High-yield organ systems on breast MR images, as reflected by a high positive predictive value for malignancy, are correlated with known distant sites of breast cancer metastasis in the bone, lung, liver, and lymph nodes. Staging is considered when disease involves the skin and chest wall. Unusual sites of breast cancer metastasis from invasive lobular carcinoma are discussed, including the gastrointestinal tract, peritoneum, and adrenal glands. Nonmalignant clinically important findings involving the cardiovascular and gastrointestinal systems are reviewed, and potential pitfalls in diagnosis and interpretation are highlighted. A consistently systematic diagnostic approach is emphasized for identifying extramammary abnormalities on breast MR images. All things considered, the radiologist should be able to improve diagnostic sensitivity and specificity while interpreting extramammary findings on breast MR images. © RSNA, 2017.

Volume and tissue composition preserving deformation of breast CT images to simulate breast compression in mammographic imaging

NASA Astrophysics Data System (ADS)

Han, Tao; Chen, Lingyun; Lai, Chao-Jen; Liu, Xinming; Shen, Youtao; Zhong, Yuncheng; Ge, Shuaiping; Yi, Ying; Wang, Tianpeng; Shaw, Chris C.

2009-02-01

Images of mastectomy breast specimens have been acquired with a bench top experimental Cone beam CT (CBCT) system. The resulting images have been segmented to model an uncompressed breast for simulation of various CBCT techniques. To further simulate conventional or tomosynthesis mammographic imaging for comparison with the CBCT technique, a deformation technique was developed to convert the CT data for an uncompressed breast to a compressed breast without altering the breast volume or regional breast density. With this technique, 3D breast deformation is separated into two 2D deformations in coronal and axial views. To preserve the total breast volume and regional tissue composition, each 2D deformation step was achieved by altering the square pixels into rectangular ones with the pixel areas unchanged and resampling with the original square pixels using bilinear interpolation. The compression was modeled by first stretching the breast in the superior-inferior direction in the coronal view. The image data were first deformed by distorting the voxels with a uniform distortion ratio. These deformed data were then deformed again using distortion ratios varying with the breast thickness and re-sampled. The deformation procedures were applied in the axial view to stretch the breast in the chest wall to nipple direction while shrinking it in the mediolateral to lateral direction re-sampled and converted into data for uniform cubic voxels. Threshold segmentation was applied to the final deformed image data to obtain the 3D compressed breast model. Our results show that the original segmented CBCT image data were successfully converted into those for a compressed breast with the same volume and regional density preserved. Using this compressed breast model, conventional and tomosynthesis mammograms were simulated for comparison with CBCT.

ACR Appropriateness Criteria® Stage I Breast Cancer: Initial Workup and Surveillance for Local Recurrence and Distant Metastases in Asymptomatic Women.

PubMed

Moy, Linda; Bailey, Lisa; D'Orsi, Carl; Green, Edward D; Holbrook, Anna I; Lee, Su-Ju; Lourenco, Ana P; Mainiero, Martha B; Sepulveda, Karla A; Slanetz, Priscilla J; Trikha, Sunita; Yepes, Monica M; Newell, Mary S

2017-05-01

Women and health care professionals generally prefer intensive follow-up after a diagnosis of breast cancer. However, there are no survival differences between women who obtain intensive surveillance with imaging and laboratory studies compared with women who only undergo testing because of the development of symptoms or findings on clinical examinations. American Society of Clinical Oncology and National Comprehensive Cancer Network guidelines state that annual mammography is the only imaging examination that should be performed to detect a localized breast recurrence in asymptomatic patients; more imaging may be needed if the patient has locoregional symptoms (eg, palpable abnormality). Women with other risk factors that increase their lifetime risk for breast cancer may warrant evaluation with breast MRI. Furthermore, the quality of life is similar for women who undergo intensive surveillance compared with those who do not. There is little justification for imaging to detect or rule out metastasis in asymptomatic women with newly diagnosed stage I breast cancer. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Differentiating malignant from benign breast tumors on acoustic radiation force impulse imaging using fuzzy-based neural networks with principle component analysis

NASA Astrophysics Data System (ADS)

Liu, Hsiao-Chuan; Chou, Yi-Hong; Tiu, Chui-Mei; Hsieh, Chi-Wen; Liu, Brent; Shung, K. Kirk

2017-03-01

Many modalities have been developed as screening tools for breast cancer. A new screening method called acoustic radiation force impulse (ARFI) imaging was created for distinguishing breast lesions based on localized tissue displacement. This displacement was quantitated by virtual touch tissue imaging (VTI). However, VTIs sometimes express reverse results to intensity information in clinical observation. In the study, a fuzzy-based neural network with principle component analysis (PCA) was proposed to differentiate texture patterns of malignant breast from benign tumors. Eighty VTIs were randomly retrospected. Thirty four patients were determined as BI-RADS category 2 or 3, and the rest of them were determined as BI-RADS category 4 or 5 by two leading radiologists. Morphological method and Boolean algebra were performed as the image preprocessing to acquire region of interests (ROIs) on VTIs. Twenty four quantitative parameters deriving from first-order statistics (FOS), fractal dimension and gray level co-occurrence matrix (GLCM) were utilized to analyze the texture pattern of breast tumors on VTIs. PCA was employed to reduce the dimension of features. Fuzzy-based neural network as a classifier to differentiate malignant from benign breast tumors. Independent samples test was used to examine the significance of the difference between benign and malignant breast tumors. The area Az under the receiver operator characteristic (ROC) curve, sensitivity, specificity and accuracy were calculated to evaluate the performance of the system. Most all of texture parameters present significant difference between malignant and benign tumors with p-value of less than 0.05 except the average of fractal dimension. For all features classified by fuzzy-based neural network, the sensitivity, specificity, accuracy and Az were 95.7%, 97.1%, 95% and 0.964, respectively. However, the sensitivity, specificity, accuracy and Az can be increased to 100%, 97.1%, 98.8% and 0.985, respectively if PCA was performed to reduce the dimension of features. Patterns of breast tumors on VTIs can effectively be recognized by quantitative texture parameters, and differentiated malignant from benign lesions by fuzzy-based neural network with PCA.

Method and system of Jones-matrix mapping of blood plasma films with "fuzzy" analysis in differentiation of breast pathology changes

NASA Astrophysics Data System (ADS)

Zabolotna, Natalia I.; Radchenko, Kostiantyn O.; Karas, Oleksandr V.

2018-01-01

A fibroadenoma diagnosing of breast using statistical analysis (determination and analysis of statistical moments of the 1st-4th order) of the obtained polarization images of Jones matrix imaginary elements of the optically thin (attenuation coefficient τ <= 0,1 ) blood plasma films with further intellectual differentiation based on the method of "fuzzy" logic and discriminant analysis were proposed. The accuracy of the intellectual differentiation of blood plasma samples to the "norm" and "fibroadenoma" of breast was 82.7% by the method of linear discriminant analysis, and by the "fuzzy" logic method is 95.3%. The obtained results allow to confirm the potentially high level of reliability of the method of differentiation by "fuzzy" analysis.

Breast imaging with the SoftVue imaging system: first results

NASA Astrophysics Data System (ADS)

Duric, Neb; Littrup, Peter; Schmidt, Steven; Li, Cuiping; Roy, Olivier; Bey-Knight, Lisa; Janer, Roman; Kunz, Dave; Chen, Xiaoyang; Goll, Jeffrey; Wallen, Andrea; Zafar, Fouzaan; Allada, Veerendra; West, Erik; Jovanovic, Ivana; Li, Kuo; Greenway, William

2013-03-01

For women with dense breast tissue, who are at much higher risk for developing breast cancer, the performance of mammography is at its worst. Consequently, many early cancers go undetected when they are the most treatable. Improved cancer detection for women with dense breasts would decrease the proportion of breast cancers diagnosed at later stages, which would significantly lower the mortality rate. The emergence of whole breast ultrasound provides good performance for women with dense breast tissue, and may eliminate the current trade-off between the cost effectiveness of mammography and the imaging performance of more expensive systems such as magnetic resonance imaging. We report on the performance of SoftVue, a whole breast ultrasound imaging system, based on the principles of ultrasound tomography. SoftVue was developed by Delphinus Medical Technologies and builds on an early prototype developed at the Karmanos Cancer Institute. We present results from preliminary testing of the SoftVue system, performed both in the lab and in the clinic. These tests aimed to validate the expected improvements in image performance. Initial qualitative analyses showed major improvements in image quality, thereby validating the new imaging system design. Specifically, SoftVue's imaging performance was consistent across all breast density categories and had much better resolution and contrast. The implications of these results for clinical breast imaging are discussed and future work is described.

The role of lipid droplets and adipocytes in cancer. Raman imaging of cell cultures: MCF10A, MCF7, and MDA-MB-231 compared to adipocytes in cancerous human breast tissue.

PubMed

Abramczyk, Halina; Surmacki, Jakub; Kopeć, Monika; Olejnik, Alicja Klaudia; Lubecka-Pietruszewska, Katarzyna; Fabianowska-Majewska, Krystyna

2015-04-07

We have studied live non-malignant (MCF10A), mildly malignant (MCF7) and malignant (MDA-MB-231) breast cancer cells and human breast cancer tissue. We demonstrate the first application of Raman imaging and spectroscopy in diagnosing the role of lipid droplets in cell line cultures that closely mimic an in vivo environment of various stages in human breast cancer tissue. We have analyzed the composition of the lipid droplets in non-malignant and malignant human breast epithelial cell lines and discussed the potential of lipid droplets as a prognostic marker in breast cancer. To identify any difference in the lipid droplet-associated biochemistry and to correlate it with different stages of breast cancer, the PCA method was employed. The chemical composition of lipids and proteins, both in the cell line models and in human breast tissue has been analyzed. The paper shows the alterations in lipid metabolism that have been reported in cancer, at both the cellular and tissue levels, and discusses how they contribute to the different aspects of tumourigenesis.

The Use of Mouse Models of Breast Cancer and Quantitative Image Analysis to Evaluate Hormone Receptor Antigenicity after Microwave-assisted Formalin Fixation

PubMed Central

Engelberg, Jesse A.; Giberson, Richard T.; Young, Lawrence J.T.; Hubbard, Neil E.

2014-01-01

Microwave methods of fixation can dramatically shorten fixation times while preserving tissue structure; however, it remains unclear if adequate tissue antigenicity is preserved. To assess and validate antigenicity, robust quantitative methods and animal disease models are needed. We used two mouse mammary models of human breast cancer to evaluate microwave-assisted and standard 24-hr formalin fixation. The mouse models expressed four antigens prognostic for breast cancer outcome: estrogen receptor, progesterone receptor, Ki67, and human epidermal growth factor receptor 2. Using pathologist evaluation and novel methods of quantitative image analysis, we measured and compared the quality of antigen preservation, percentage of positive cells, and line plots of cell intensity. Visual evaluations by pathologists established that the amounts and patterns of staining were similar in tissues fixed by the different methods. The results of the quantitative image analysis provided a fine-grained evaluation, demonstrating that tissue antigenicity is preserved in tissues fixed using microwave methods. Evaluation of the results demonstrated that a 1-hr, 150-W fixation is better than a 45-min, 150-W fixation followed by a 15-min, 650-W fixation. The results demonstrated that microwave-assisted formalin fixation can standardize fixation times to 1 hr and produce immunohistochemistry that is in every way commensurate with longer conventional fixation methods. PMID:24682322

Effects of exposure equalization on image signal-to-noise ratios in digital mammography: A simulation study with an anthropomorphic breast phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu Xinming; Lai Chaojen; Whitman, Gary J.

Purpose: The scan equalization digital mammography (SEDM) technique combines slot scanning and exposure equalization to improve low-contrast performance of digital mammography in dense tissue areas. In this study, full-field digital mammography (FFDM) images of an anthropomorphic breast phantom acquired with an anti-scatter grid at various exposure levels were superimposed to simulate SEDM images and investigate the improvement of low-contrast performance as quantified by primary signal-to-noise ratios (PSNRs). Methods: We imaged an anthropomorphic breast phantom (Gammex 169 ''Rachel,'' Gammex RMI, Middleton, WI) at various exposure levels using a FFDM system (Senographe 2000D, GE Medical Systems, Milwaukee, WI). The exposure equalization factorsmore » were computed based on a standard FFDM image acquired in the automatic exposure control (AEC) mode. The equalized image was simulated and constructed by superimposing a selected set of FFDM images acquired at 2, 1, 1/2, 1/4, 1/8, 1/16, and 1/32 times of exposure levels to the standard AEC timed technique (125 mAs) using the equalization factors computed for each region. Finally, the equalized image was renormalized regionally with the exposure equalization factors to result in an appearance similar to that with standard digital mammography. Two sets of FFDM images were acquired to allow for two identically, but independently, formed equalized images to be subtracted from each other to estimate the noise levels. Similarly, two identically but independently acquired standard FFDM images were subtracted to estimate the noise levels. Corrections were applied to remove the excess system noise accumulated during image superimposition in forming the equalized image. PSNRs over the compressed area of breast phantom were computed and used to quantitatively study the effects of exposure equalization on low-contrast performance in digital mammography. Results: We found that the highest achievable PSNR improvement factor was 1.89 for the anthropomorphic breast phantom used in this study. The overall PSNRs were measured to be 79.6 for the FFDM imaging and 107.6 for the simulated SEDM imaging on average in the compressed area of breast phantom, resulting in an average improvement of PSNR by {approx}35% with exposure equalization. We also found that the PSNRs appeared to be largely uniform with exposure equalization, and the standard deviations of PSNRs were estimated to be 10.3 and 7.9 for the FFDM imaging and the simulated SEDM imaging, respectively. The average glandular dose for SEDM was estimated to be 212.5 mrad, {approx}34% lower than that of standard AEC-timed FFDM (323.8 mrad) as a result of exposure equalization for the entire breast phantom. Conclusions: Exposure equalization was found to substantially improve image PSNRs in dense tissue regions and result in more uniform image PSNRs. This improvement may lead to better low-contrast performance in detecting and visualizing soft tissue masses and micro-calcifications in dense tissue areas for breast imaging tasks.« less

3D silicon breast surface mapping via structured light profilometry

NASA Astrophysics Data System (ADS)

Vairavan, R.; Ong, N. R.; Sauli, Z.; Kirtsaeng, S.; Sakuntasathien, S.; Shahimin, M. M.; Alcain, J. B.; Lai, S. L.; Paitong, P.; Retnasamy, V.

2017-09-01

Digital fringe projection technique is one of the promising optical methods for 3D surface imaging as it demonstrates non contact and non invasive characteristics. The potential of this technique matches the requirement for human body evaluation, as it is vital for disease diagnosis and for treatment option selection. Thus, the digital fringe projection has addressed this requirement with its wide clinical related application and studies. However, the application of this technique for 3D surface mapping of the breast is very minimal. Hence, in this work, the application of digital fringe projection for 3D breast surface mapping is reported. Phase shift fringe projection technique was utilized to perform the 3D breast surface mapping. Maiden results have confirmed the feasibility of using the digital fringe projection method for 3D surface mapping of the breast and it can be extended for breast cancer detection.

Breast cancer screening controversies: who, when, why, and how?

PubMed

Chetlen, Alison; Mack, Julie; Chan, Tiffany

2016-01-01

Mammographic screening is effective in reducing mortality from breast cancer. The issue is not whether mammography is effective, but whether the false positive rate and false negative rates can be reduced. This review will discuss controversies including the reduction in breast cancer mortality, overdiagnosis, the ideal screening candidate, and the optimal imaging modality for breast cancer screening. The article will compare and contrast screening mammography, tomosynthesis, whole-breast screening ultrasound, magnetic resonance imaging, and molecular breast imaging. Though supplemental imaging modalities are being utilized to improve breast cancer diagnosis, mammography still remains the gold standard for breast cancer screening. Copyright © 2015 Elsevier Inc. All rights reserved.

MO-E-BRD-02: Accelerated Partial Breast Irradiation in Brachytherapy: Is Shorter Better?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Todor, D.

2015-06-15

Is Non-invasive Image-Guided Breast Brachytherapy Good? – Jess Hiatt, MS Non-invasive Image-Guided Breast Brachytherapy (NIBB) is an emerging therapy for breast boost treatments as well as Accelerated Partial Breast Irradiation (APBI) using HDR surface breast brachytherapy. NIBB allows for smaller treatment volumes while maintaining optimal target coverage. Considering the real-time image-guidance and immobilization provided by the NIBB modality, minimal margins around the target tissue are necessary. Accelerated Partial Breast Irradiation in brachytherapy: is shorter better? - Dorin Todor, PhD VCU A review of balloon and strut devices will be provided together with the origins of APBI: the interstitial multi-catheter implant.more » A dosimetric and radiobiological perspective will help point out the evolution in breast brachytherapy, both in terms of devices and the protocols/clinical trials under which these devices are used. Improvements in imaging, delivery modalities and convenience are among the factors driving the ultrashort fractionation schedules but our understanding of both local control and toxicities associated with various treatments is lagging. A comparison between various schedules, from a radiobiological perspective, will be given together with a critical analysis of the issues. to review and understand the evolution and development of APBI using brachytherapy methods to understand the basis and limitations of radio-biological ‘equivalence’ between fractionation schedules to review commonly used and proposed fractionation schedules Intra-operative breast brachytherapy: Is one stop shopping best?- Bruce Libby, PhD. University of Virginia A review of intraoperative breast brachytherapy will be presented, including the Targit-A and other trials that have used electronic brachytherapy. More modern approaches, in which the lumpectomy procedure is integrated into an APBI workflow, will also be discussed. Learning Objectives: To review past and current clinical trials for IORT To discuss lumpectomy-scan-plan-treat workflow for IORT.« less

Diffuse optical tomography and spectroscopy of breast cancer and fetal brain

NASA Astrophysics Data System (ADS)

Choe, Regine

Diffuse optical techniques utilize light in the near infrared spectral range to measure tissue physiology non-invasively. Based on these measurements, either on average or a three-dimensional spatial map of tissue properties such as total hemoglobin concentration, blood oxygen saturation and scattering can be obtained using model-based reconstruction algorithms. In this thesis, diffuse optical techniques were applied for in vivo breast cancer imaging and trans-abdominal fetal brain oxygenation monitoring. For in vivo breast cancer imaging, clinical diffuse optical tomography and related instrumentation was developed and used in several contexts. Bulk physiological properties were quantified for fifty-two healthy subjects in the parallel-plate transmission geometry. Three-dimensional images of breast were reconstructed for subjects with breast tumors and, tumor contrast with respect to normal tissue was found in total hemoglobin concentration and scattering and was quantified for twenty-two breast carcinomas. Tumor contrast and tumor volume changes during neoadjuvant chemotherapy were tracked for one subject and compared to the dynamic contrast-enhanced MRI. Finally, the feasibility for measuring blood flow of breast tumors using optical methods was demonstrated for seven subjects. In a qualitatively different set of experiments, the feasibility for trans-abdominal fetal brain oxygenation monitoring was demonstrated on pregnant ewes with induced fetal hypoxia. Preliminary clinical experiences were discussed to identify future directions. In total, this research has translated diffuse optical tomography techniques into clinical research environment.

Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction

NASA Astrophysics Data System (ADS)

Lu, Yao; Chan, Heang-Ping; Wei, Jun; Hadjiiski, Lubomir M.; Samala, Ravi K.

2017-10-01

In digital breast tomosynthesis (DBT), the high-attenuation metallic clips marking a previous biopsy site in the breast cause errors in the estimation of attenuation along the ray paths intersecting the markers during reconstruction, which result in interplane and inplane artifacts obscuring the visibility of subtle lesions. We proposed a new metal artifact reduction (MAR) method to improve image quality. Our method uses automatic detection and segmentation to generate a marker location map for each projection (PV). A voting technique based on the geometric correlation among different PVs is designed to reduce false positives (FPs) and to label the pixels on the PVs and the voxels in the imaged volume that represent the location and shape of the markers. An iterative diffusion method replaces the labeled pixels on the PVs with estimated tissue intensity from the neighboring regions while preserving the original pixel values in the neighboring regions. The inpainted PVs are then used for DBT reconstruction. The markers are repainted on the reconstructed DBT slices for radiologists’ information. The MAR method is independent of reconstruction techniques or acquisition geometry. For the training set, the method achieved 100% success rate with one FP in 19 views. For the test set, the success rate by view was 97.2% for core biopsy microclips and 66.7% for clusters of large post-lumpectomy markers with a total of 10 FPs in 58 views. All FPs were large dense benign calcifications that also generated artifacts if they were not corrected by MAR. For the views with successful detection, the metal artifacts were reduced to a level that was not visually apparent in the reconstructed slices. The visibility of breast lesions obscured by the reconstruction artifacts from the metallic markers was restored.

Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review.

PubMed

Chen, Jia-Mei; Li, Yan; Xu, Jun; Gong, Lei; Wang, Lin-Wei; Liu, Wen-Lou; Liu, Juan

2017-03-01

With the advance of digital pathology, image analysis has begun to show its advantages in information analysis of hematoxylin and eosin histopathology images. Generally, histological features in hematoxylin and eosin images are measured to evaluate tumor grade and prognosis for breast cancer. This review summarized recent works in image analysis of hematoxylin and eosin histopathology images for breast cancer prognosis. First, prognostic factors for breast cancer based on hematoxylin and eosin histopathology images were summarized. Then, usual procedures of image analysis for breast cancer prognosis were systematically reviewed, including image acquisition, image preprocessing, image detection and segmentation, and feature extraction. Finally, the prognostic value of image features and image feature-based prognostic models was evaluated. Moreover, we discussed the issues of current analysis, and some directions for future research.

Detection of breast cancer in automated 3D breast ultrasound

NASA Astrophysics Data System (ADS)

Tan, Tao; Platel, Bram; Mus, Roel; Karssemeijer, Nico

2012-03-01

Automated 3D breast ultrasound (ABUS) is a novel imaging modality, in which motorized scans of the breasts are made with a wide transducer through a membrane under modest compression. The technology has gained high interest and may become widely used in screening of dense breasts, where sensitivity of mammography is poor. ABUS has a high sensitivity for detecting solid breast lesions. However, reading ABUS images is time consuming, and subtle abnormalities may be missed. Therefore, we are developing a computer aided detection (CAD) system to help reduce reading time and errors. In the multi-stage system we propose, segmentations of the breast and nipple are performed, providing landmarks for the detection algorithm. Subsequently, voxel features characterizing coronal spiculation patterns, blobness, contrast, and locations with respect to landmarks are extracted. Using an ensemble of classifiers, a likelihood map indicating potential malignancies is computed. Local maxima in the likelihood map are determined using a local maxima detector and form a set of candidate lesions in each view. These candidates are further processed in a second detection stage, which includes region segmentation, feature extraction and a final classification. Region segmentation is performed using a 3D spiral-scanning dynamic programming method. Region features include descriptors of shape, acoustic behavior and texture. Performance was determined using a 78-patient dataset with 93 images, including 50 malignant lesions. We used 10-fold cross-validation. Using FROC analysis we found that the system obtains a lesion sensitivity of 60% and 70% at 2 and 4 false positives per image respectively.

MR-Guided Near Infrared Spectroscopy for Reducing Breast Cancer False Positives

DTIC Science & Technology

2009-09-01

an Invivo breast coil in a (b) Philips scanner , and (b) a USA Instruments coil in a (d) GE scanner . 8 Quantitative accuracy in optical imaging...reconstruction [7], which includes a weighting term to account for the accuracy of the MR scanner in determining water and fat images. The advantage of... scanner used in this study. These methods were tested in a 86mm diameter gelatin phantom, shown in Figure 6, with porcine blood added to mimic the

Body Image and Sexuality in Women Survivors of Breast Cancer in India: Qualitative Findings

PubMed Central

Barthakur, Michelle S; Sharma, Mahendra P; Chaturvedi, Santosh K; Manjunath, Suraj K

2017-01-01

Objectives: With increasing rates of breast cancer survivors, psychosocial issues surrounding cancer survivorship have been gaining prominence. The following article reports on body image and sexuality-related issues in aftermath of the diagnosis and its treatment in the Indian context. Materials and Methods: Research design was mixed method, cross–sectional, and exploratory in nature. Quantitative sample consisted of fifty survivors while the qualitative sample size included 15 out of the 50 total breast cancer survivors who were recruited from hospitals, nongovernmental organization, and through word-of-mouth. Data was collected using quantitative measures, and in-depth interviews were done using semi-structured interview schedule that was developed for the study. Qualitative data were analyzed using descriptive phenomenological approach. Results: In body image, emerging themes were about identity (womanhood, motherhood, and attractiveness), impact of surgery, hair loss, clothes, and uncomfortable situations. In sexuality, barriers were faced due to difficulty in disclosure and themes were about adjustments made by spouses, role of age, and sexual difficulties due to treatment. Conclusions: Findings imply need to address the issues of body image and sexuality as it impacts quality of life of survivors. PMID:28216857

Radiologic and histopathologic review of rare benign and malignant breast diseases

PubMed Central

Dağıstan, Emine; Kızıldağ, Betül; Gürel, Safiye; Barut, Yüksel; Paşaoğlu, Esra

2017-01-01

High social awareness of breast diseases and the rise in breast imaging facilities have led to an increase in the detection of even rare benign and malignant breast lesions. Breast lesions are associated with a broad spectrum of imaging characteristics, and each radiologic imaging technique reflects different characteristics of them. We aimed to increase familiarity of the radiologist with these uncommon lesions as well as correlate histopathologic findings with the radiologic imaging features of the tumors. Histopathologic examination is necessary in the evaluation of such breast lesions, particularly when radiologic images are not definitive for a specific diagnosis. PMID:28508760

TH-AB-209-10: Breast Cancer Identification Through X-Ray Coherent Scatter Spectral Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kapadia, A; Morris, R; Albanese, K

Purpose: We have previously described the development and testing of a coherent-scatter spectral imaging system for identification of cancer. Our prior evaluations were performed using either tissue surrogate phantoms or formalin-fixed tissue obtained from pathology. Here we present the first results from a scatter imaging study using fresh breast tumor tissues obtained through surgical excision. Methods: A coherent-scatter imaging system was built using a clinical X-ray tube, photon counting detectors, and custom-designed coded-apertures. System performance was characterized using calibration phantoms of biological materials. Fresh breast tumors were obtained from patients undergoing mastectomy and lumpectomy surgeries for breast cancer. Each specimenmore » was vacuum-sealed, scanned using the scatter imaging system, and then sent to pathology for histological workup. Scatter images were generated separately for each tissue specimen and analyzed to identify voxels containing malignant tissue. The images were compared against histological analysis (H&E + pathologist identification of tumors) to assess the match between scatter-based and histological diagnosis. Results: In all specimens scanned, the scatter images showed the location of cancerous regions within the specimen. The detection and classification was performed through automated spectral matching without the need for manual intervention. The scatter spectra corresponding to cancer tissue were found to be in agreement with those reported in literature. Inter-patient variability was found to be within limits reported in literature. The scatter images showed agreement with pathologist-identified regions of cancer. Spatial resolution for this configuration of the scanner was determined to be 2–3 mm, and the total scan time for each specimen was under 15 minutes. Conclusion: This work demonstrates the utility of coherent scatter imaging in identifying cancer based on the scatter properties of the tissue. It presents the first results from coherent scatter imaging of fresh (unfixed) breast tissue using our coded-aperture scatter imaging approach for cancer identification.« less

Comparison of Background Parenchymal Enhancement at Contrast-enhanced Spectral Mammography and Breast MR Imaging

PubMed Central

Morris, Elizabeth A.; Kaplan, Jennifer B.; D’Alessio, Donna; Goldman, Debra; Moskowitz, Chaya S.

2017-01-01

Purpose To assess the extent of background parenchymal enhancement (BPE) at contrast material–enhanced (CE) spectral mammography and breast magnetic resonance (MR) imaging, to evaluate interreader agreement in BPE assessment, and to examine the relationships between clinical factors and BPE. Materials and Methods This was a retrospective, institutional review board–approved, HIPAA-compliant study. Two hundred seventy-eight women from 25 to 76 years of age with increased breast cancer risk who underwent CE spectral mammography and MR imaging for screening or staging from 2010 through 2014 were included. Three readers independently rated BPE on CE spectral mammographic and MR images with the ordinal scale: minimal, mild, moderate, or marked. To assess pairwise agreement between BPE levels on CE spectral mammographic and MR images and among readers, weighted κ coefficients with quadratic weights were calculated. For overall agreement, mean κ values and bootstrapped 95% confidence intervals were calculated. The univariate and multivariate associations between BPE and clinical factors were examined by using generalized estimating equations separately for CE spectral mammography and MR imaging. Results Most women had minimal or mild BPE at both CE spectral mammography (68%–76%) and MR imaging (69%–76%). Between CE spectral mammography and MR imaging, the intrareader agreement ranged from moderate to substantial (κ = 0.55–0.67). Overall agreement on BPE levels between CE spectral mammography and MR imaging and among readers was substantial (κ = 0.66; 95% confidence interval: 0.61, 0.70). With both modalities, BPE demonstrated significant association with menopausal status, prior breast radiation therapy, hormonal treatment, breast density on CE spectral mammographic images, and amount of fibroglandular tissue on MR images (P < .001 for all). Conclusion There was substantial agreement between readers for BPE detected on CE spectral mammographic and MR images. © RSNA, 2016 PMID:27379544

Computation of breast ptosis from 3D surface scans of the female torso.

PubMed

Li, Danni; Cheong, Audrey; Reece, Gregory P; Crosby, Melissa A; Fingeret, Michelle C; Merchant, Fatima A

2016-11-01

Stereophotography is now finding a niche in clinical breast surgery, and several methods for quantitatively measuring breast morphology from 3D surface images have been developed. Breast ptosis (sagging of the breast), which refers to the extent by which the nipple is lower than the inframammary fold (the contour along which the inferior part of the breast attaches to the chest wall), is an important morphological parameter that is frequently used for assessing the outcome of breast surgery. This study presents a novel algorithm that utilizes three-dimensional (3D) features such as surface curvature and orientation for the assessment of breast ptosis from 3D scans of the female torso. The performance of the computational approach proposed was compared against the consensus of manual ptosis ratings by nine plastic surgeons, and that of current 2D photogrammetric methods. Compared to the 2D methods, the average accuracy for 3D features was ~13% higher, with an increase in precision, recall, and F-score of 37%, 29%, and 33%, respectively. The computational approach proposed provides an improved and unbiased objective method for rating ptosis when compared to qualitative visualization by observers, and distance based 2D photogrammetry approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Computer-extracted Image Phenotypes from Tumors on Breast MRI to Predict Breast Cancer Pathologic Stage

PubMed Central

Burnside, Elizabeth S.; Drukker, Karen; Li, Hui; Bonaccio, Ermelinda; Zuley, Margarita; Ganott, Marie; Net, Jose M.; Sutton, Elizabeth; Brandt, Kathleen R.; Whitman, Gary; Conzen, Suzanne; Lan, Li; Ji, Yuan; Zhu, Yitan; Jaffe, Carl; Huang, Erich; Freymann, John; Kirby, Justin; Morris, Elizabeth; Giger, Maryellen

2015-01-01

Background To demonstrate that computer-extracted image phenotypes (CEIPs) of biopsy-proven breast cancer on MRI can accurately predict pathologic stage. Methods We used a dataset of de-identified breast MRIs organized by the National Cancer Institute in The Cancer Imaging Archive. We analyzed 91 biopsy-proven breast cancer cases with pathologic stage (stage I = 22; stage II = 58; stage III = 11) and surgically proven nodal status (negative nodes = 46, ≥ 1 positive node = 44, no nodes examined = 1). We characterized tumors by (a) radiologist measured size, and (b) CEIP. We built models combining two CEIPs to predict tumor pathologic stage and lymph node involvement, evaluated them in leave-one-out cross-validation with area under the ROC curve (AUC) as figure of merit. Results Tumor size was the most powerful predictor of pathologic stage but CEIPs capturing biologic behavior also emerged as predictive (e.g. stage I+II vs. III demonstrated AUC = 0.83). No size measure was successful in the prediction of positive lymph nodes but adding a CEIP describing tumor “homogeneity,” significantly improved this discrimination (AUC = 0.62, p=.003) over chance. Conclusions Our results indicate that MRI phenotypes show promise for predicting breast cancer pathologic stage and lymph node status. PMID:26619259

Automated modification and fusion of voxel models to construct body phantoms with heterogeneous breast tissue: Application to MRI simulations

PubMed Central

Rispoli, Joseph V.; Wright, Steven M.; Malloy, Craig R.; McDougall, Mary P.

2017-01-01

Background Human voxel models incorporating detailed anatomical features are vital tools for the computational evaluation of electromagnetic (EM) fields within the body. Besides whole-body human voxel models, phantoms representing smaller heterogeneous anatomical features are often employed; for example, localized breast voxel models incorporating fatty and fibroglandular tissues have been developed for a variety of EM applications including mammography simulation and dosimetry, magnetic resonance imaging (MRI), and ultra-wideband microwave imaging. However, considering wavelength effects, electromagnetic modeling of the breast at sub-microwave frequencies necessitates detailed breast phantoms in conjunction with whole-body voxel models. Methods Heterogeneous breast phantoms are sized to fit within radiofrequency coil hardware, modified by voxel-wise extrusion, and fused to whole-body models using voxel-wise, tissue-dependent logical operators. To illustrate the utility of this method, finite-difference time-domain simulations are performed using a whole-body model integrated with a variety of available breast phantoms spanning the standard four tissue density classifications representing the majority of the population. Results The software library uses a combination of voxel operations to seamlessly size, modify, and fuse eleven breast phantoms to whole-body voxel models. The software is publicly available on GitHub and is linked to the file exchange at MATLAB® Central. Simulations confirm the proportions of fatty and fibroglandular tissues in breast phantoms have significant yet predictable implications on projected power deposition in tissue. Conclusions Breast phantoms may be modified and fused to whole-body voxel models using the software presented in this work; user considerations for the open-source software and resultant phantoms are discussed. Furthermore, results indicate simulating breast models as predominantly fatty tissue can considerably underestimate the potential for tissue heating in women with substantial fibroglandular tissue. PMID:28798837

Imaging in the evaluation and follow-up of early and advanced breast cancer: When, why, and how often?

PubMed

Bychkovsky, Brittany L; Lin, Nancy U

2017-02-01

Imaging in the evaluation and follow-up of patients with early or advanced breast cancer is an important aspect of cancer care. The role of imaging in breast cancer depends on the goal and should only be performed to guide clinical decisions. Imaging is valuable if a finding will change the course of treatment and improve outcomes, whether this is disease-free survival, overall survival or quality-of-life. In the last decade, imaging is often overused in oncology and contributes to rising healthcare costs. In this context, we review the data that supports the appropriate use of imaging for breast cancer patients. We will discuss: 1) the optimal use of staging imaging in both early (Stage 0-II) and locally advanced (Stage III) breast cancer, 2) the role of surveillance imaging to detect recurrent disease in Stage 0-III breast cancer and 3) how patients with metastatic breast cancer should be followed with advanced imaging. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dual-Energy Contrast-Enhanced Breast Tomosynthesis: Optimization of Beam Quality for Dose and Image Quality

PubMed Central

Samei, Ehsan; Saunders, Robert S.

2014-01-01

Dual-energy contrast-enhanced breast tomosynthesis is a promising technique to obtain three-dimensional functional information from the breast with high resolution and speed. To optimize this new method, this study searched for the beam quality that maximized image quality in terms of mass detection performance. A digital tomosynthesis system was modeled using a fast ray-tracing algorithm, which created simulated projection images by tracking photons through a voxelized anatomical breast phantom containing iodinated lesions. The single-energy images were combined into dual-energy images through a weighted log subtraction process. The weighting factor was optimized to minimize anatomical noise, while the dose distribution was chosen to minimize quantum noise. The dual-energy images were analyzed for the signal difference to noise ratio (SdNR) of iodinated masses. The fast ray-tracing explored 523,776 dual-energy combinations to identify which yields optimum mass SdNR. The ray-tracing results were verified using a Monte Carlo model for a breast tomosynthesis system with a selenium-based flat-panel detector. The projection images from our voxelized breast phantom were obtained at a constant total glandular dose. The projections were combined using weighted log subtraction and reconstructed using commercial reconstruction software. The lesion SdNR was measured in the central reconstructed slice. The SdNR performance varied markedly across the kVp and filtration space. Ray-tracing results indicated that the mass SdNR was maximized with a high-energy tungsten beam at 49 kVp with 92.5 μm of copper filtration and a low-energy tungsten beam at 49 kVp with 95 μm of tin filtration. This result was consistent with Monte Carlo findings. This mammographic technique led to a mass SdNR of 0.92 ± 0.03 in the projections and 3.68 ± 0.19 in the reconstructed slices. These values were markedly higher than those for non-optimized techniques. Our findings indicate that dual-energy breast tomosynthesis can be performed optimally at 49 kVp with alternative copper and tin filters, with reconstruction following weighted subtraction. The optimum technique provides best visibility of iodine against structured breast background in dual-energy contrast-enhanced breast tomosynthesis. PMID:21908902

Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks.

PubMed

Bandeira Diniz, João Otávio; Bandeira Diniz, Pedro Henrique; Azevedo Valente, Thales Levi; Corrêa Silva, Aristófanes; de Paiva, Anselmo Cardoso; Gattass, Marcelo

2018-03-01

The processing of medical image is an important tool to assist in minimizing the degree of uncertainty of the specialist, while providing specialists with an additional source of detect and diagnosis information. Breast cancer is the most common type of cancer that affects the female population around the world. It is also the most deadly type of cancer among women. It is the second most common type of cancer among all others. The most common examination to diagnose breast cancer early is mammography. In the last decades, computational techniques have been developed with the purpose of automatically detecting structures that maybe associated with tumors in mammography examination. This work presents a computational methodology to automatically detection of mass regions in mammography by using a convolutional neural network. The materials used in this work is the DDSM database. The method proposed consists of two phases: training phase and test phase. The training phase has 2 main steps: (1) create a model to classify breast tissue into dense and non-dense (2) create a model to classify regions of breast into mass and non-mass. The test phase has 7 step: (1) preprocessing; (2) registration; (3) segmentation; (4) first reduction of false positives; (5) preprocessing of regions segmented; (6) density tissue classification (7) second reduction of false positives where regions will be classified into mass and non-mass. The proposed method achieved 95.6% of accuracy in classify non-dense breasts tissue and 97,72% accuracy in classify dense breasts. To detect regions of mass in non-dense breast, the method achieved a sensitivity value of 91.5%, and specificity value of 90.7%, with 91% accuracy. To detect regions in dense breasts, our method achieved 90.4% of sensitivity and 96.4% of specificity, with accuracy of 94.8%. According to the results achieved by CNN, we demonstrate the feasibility of using convolutional neural networks on medical image processing techniques for classification of breast tissue and mass detection. Copyright © 2018 Elsevier B.V. All rights reserved.

Statistical analysis to assess automated level of suspicion scoring methods in breast ultrasound

NASA Astrophysics Data System (ADS)

Galperin, Michael

2003-05-01

A well-defined rule-based system has been developed for scoring 0-5 the Level of Suspicion (LOS) based on qualitative lexicon describing the ultrasound appearance of breast lesion. The purposes of the research are to asses and select one of the automated LOS scoring quantitative methods developed during preliminary studies in benign biopsies reduction. The study has used Computer Aided Imaging System (CAIS) to improve the uniformity and accuracy of applying the LOS scheme by automatically detecting, analyzing and comparing breast masses. The overall goal is to reduce biopsies on the masses with lower levels of suspicion, rather that increasing the accuracy of diagnosis of cancers (will require biopsy anyway). On complex cysts and fibroadenoma cases experienced radiologists were up to 50% less certain in true negatives than CAIS. Full correlation analysis was applied to determine which of the proposed LOS quantification methods serves CAIS accuracy the best. This paper presents current results of applying statistical analysis for automated LOS scoring quantification for breast masses with known biopsy results. It was found that First Order Ranking method yielded most the accurate results. The CAIS system (Image Companion, Data Companion software) is developed by Almen Laboratories and was used to achieve the results.

Combined magnetic resonance, fluorescence, and histology imaging strategy in a human breast tumor xenograft model

PubMed Central

Jiang, Lu; Greenwood, Tiffany R.; Amstalden van Hove, Erika R.; Chughtai, Kamila; Raman, Venu; Winnard, Paul T.; Heeren, Ron; Artemov, Dmitri; Glunde, Kristine

2014-01-01

Applications of molecular imaging in cancer and other diseases frequently require combining in vivo imaging modalities, such as magnetic resonance and optical imaging, with ex vivo optical, fluorescence, histology, and immunohistochemical (IHC) imaging, to investigate and relate molecular and biological processes to imaging parameters within the same region of interest. We have developed a multimodal image reconstruction and fusion framework that accurately combines in vivo magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI), ex vivo brightfield and fluorescence microscopic imaging, and ex vivo histology imaging. Ex vivo brightfield microscopic imaging was used as an intermediate modality to facilitate the ultimate link between ex vivo histology and in vivo MRI/MRSI. Tissue sectioning necessary for optical and histology imaging required generation of a three-dimensional (3D) reconstruction module for 2D ex vivo optical and histology imaging data. We developed an external fiducial marker based 3D reconstruction method, which was able to fuse optical brightfield and fluorescence with histology imaging data. Registration of 3D tumor shape was pursued to combine in vivo MRI/MRSI and ex vivo optical brightfield and fluorescence imaging data. This registration strategy was applied to in vivo MRI/MRSI, ex vivo optical brightfield/fluorescence, as well as histology imaging data sets obtained from human breast tumor models. 3D human breast tumor data sets were successfully reconstructed and fused with this platform. PMID:22945331

The Impact of Acquisition Dose on Quantitative Breast Density Estimation with Digital Mammography: Results from ACRIN PA 4006.

PubMed

Chen, Lin; Ray, Shonket; Keller, Brad M; Pertuz, Said; McDonald, Elizabeth S; Conant, Emily F; Kontos, Despina

2016-09-01

Purpose To investigate the impact of radiation dose on breast density estimation in digital mammography. Materials and Methods With institutional review board approval and Health Insurance Portability and Accountability Act compliance under waiver of consent, a cohort of women from the American College of Radiology Imaging Network Pennsylvania 4006 trial was retrospectively analyzed. All patients underwent breast screening with a combination of dose protocols, including standard full-field digital mammography, low-dose digital mammography, and digital breast tomosynthesis. A total of 5832 images from 486 women were analyzed with previously validated, fully automated software for quantitative estimation of density. Clinical Breast Imaging Reporting and Data System (BI-RADS) density assessment results were also available from the trial reports. The influence of image acquisition radiation dose on quantitative breast density estimation was investigated with analysis of variance and linear regression. Pairwise comparisons of density estimations at different dose levels were performed with Student t test. Agreement of estimation was evaluated with quartile-weighted Cohen kappa values and Bland-Altman limits of agreement. Results Radiation dose of image acquisition did not significantly affect quantitative density measurements (analysis of variance, P = .37 to P = .75), with percent density demonstrating a high overall correlation between protocols (r = 0.88-0.95; weighted κ = 0.83-0.90). However, differences in breast percent density (1.04% and 3.84%, P < .05) were observed within high BI-RADS density categories, although they were significantly correlated across the different acquisition dose levels (r = 0.76-0.92, P < .05). Conclusion Precision and reproducibility of automated breast density measurements with digital mammography are not substantially affected by variations in radiation dose; thus, the use of low-dose techniques for the purpose of density estimation may be feasible. (©) RSNA, 2016 Online supplemental material is available for this article.

The Impact of Acquisition Dose on Quantitative Breast Density Estimation with Digital Mammography: Results from ACRIN PA 4006

PubMed Central

Chen, Lin; Ray, Shonket; Keller, Brad M.; Pertuz, Said; McDonald, Elizabeth S.; Conant, Emily F.

2016-01-01

Purpose To investigate the impact of radiation dose on breast density estimation in digital mammography. Materials and Methods With institutional review board approval and Health Insurance Portability and Accountability Act compliance under waiver of consent, a cohort of women from the American College of Radiology Imaging Network Pennsylvania 4006 trial was retrospectively analyzed. All patients underwent breast screening with a combination of dose protocols, including standard full-field digital mammography, low-dose digital mammography, and digital breast tomosynthesis. A total of 5832 images from 486 women were analyzed with previously validated, fully automated software for quantitative estimation of density. Clinical Breast Imaging Reporting and Data System (BI-RADS) density assessment results were also available from the trial reports. The influence of image acquisition radiation dose on quantitative breast density estimation was investigated with analysis of variance and linear regression. Pairwise comparisons of density estimations at different dose levels were performed with Student t test. Agreement of estimation was evaluated with quartile-weighted Cohen kappa values and Bland-Altman limits of agreement. Results Radiation dose of image acquisition did not significantly affect quantitative density measurements (analysis of variance, P = .37 to P = .75), with percent density demonstrating a high overall correlation between protocols (r = 0.88–0.95; weighted κ = 0.83–0.90). However, differences in breast percent density (1.04% and 3.84%, P < .05) were observed within high BI-RADS density categories, although they were significantly correlated across the different acquisition dose levels (r = 0.76–0.92, P < .05). Conclusion Precision and reproducibility of automated breast density measurements with digital mammography are not substantially affected by variations in radiation dose; thus, the use of low-dose techniques for the purpose of density estimation may be feasible. © RSNA, 2016 Online supplemental material is available for this article. PMID:27002418

Dual Energy Method for Breast Imaging: A Simulation Study.

PubMed

Koukou, V; Martini, N; Michail, C; Sotiropoulou, P; Fountzoula, C; Kalyvas, N; Kandarakis, I; Nikiforidis, G; Fountos, G

2015-01-01

Dual energy methods can suppress the contrast between adipose and glandular tissues in the breast and therefore enhance the visibility of calcifications. In this study, a dual energy method based on analytical modeling was developed for the detection of minimum microcalcification thickness. To this aim, a modified radiographic X-ray unit was considered, in order to overcome the limited kVp range of mammographic units used in previous DE studies, combined with a high resolution CMOS sensor (pixel size of 22.5 μm) for improved resolution. Various filter materials were examined based on their K-absorption edge. Hydroxyapatite (HAp) was used to simulate microcalcifications. The contrast to noise ratio (CNR tc ) of the subtracted images was calculated for both monoenergetic and polyenergetic X-ray beams. The optimum monoenergetic pair was 23/58 keV for the low and high energy, respectively, resulting in a minimum detectable microcalcification thickness of 100 μm. In the polyenergetic X-ray study, the optimal spectral combination was 40/70 kVp filtered with 100 μm cadmium and 1000 μm copper, respectively. In this case, the minimum detectable microcalcification thickness was 150 μm. The proposed dual energy method provides improved microcalcification detectability in breast imaging with mean glandular dose values within acceptable levels.

Dual Energy Method for Breast Imaging: A Simulation Study

PubMed Central

2015-01-01

Dual energy methods can suppress the contrast between adipose and glandular tissues in the breast and therefore enhance the visibility of calcifications. In this study, a dual energy method based on analytical modeling was developed for the detection of minimum microcalcification thickness. To this aim, a modified radiographic X-ray unit was considered, in order to overcome the limited kVp range of mammographic units used in previous DE studies, combined with a high resolution CMOS sensor (pixel size of 22.5 μm) for improved resolution. Various filter materials were examined based on their K-absorption edge. Hydroxyapatite (HAp) was used to simulate microcalcifications. The contrast to noise ratio (CNRtc) of the subtracted images was calculated for both monoenergetic and polyenergetic X-ray beams. The optimum monoenergetic pair was 23/58 keV for the low and high energy, respectively, resulting in a minimum detectable microcalcification thickness of 100 μm. In the polyenergetic X-ray study, the optimal spectral combination was 40/70 kVp filtered with 100 μm cadmium and 1000 μm copper, respectively. In this case, the minimum detectable microcalcification thickness was 150 μm. The proposed dual energy method provides improved microcalcification detectability in breast imaging with mean glandular dose values within acceptable levels. PMID:26246848

Breast Cancer Risk and Mammographic Density Assessed with Semiautomated and Fully Automated Methods and BI-RADS.

PubMed

Jeffers, Abra M; Sieh, Weiva; Lipson, Jafi A; Rothstein, Joseph H; McGuire, Valerie; Whittemore, Alice S; Rubin, Daniel L

2017-02-01

Purpose To compare three metrics of breast density on full-field digital mammographic (FFDM) images as predictors of future breast cancer risk. Materials and Methods This institutional review board-approved study included 125 women with invasive breast cancer and 274 age- and race-matched control subjects who underwent screening FFDM during 2004-2013 and provided informed consent. The percentage of density and dense area were assessed semiautomatically with software (Cumulus 4.0; University of Toronto, Toronto, Canada), and volumetric percentage of density and dense volume were assessed automatically with software (Volpara; Volpara Solutions, Wellington, New Zealand). Clinical Breast Imaging Reporting and Data System (BI-RADS) classifications of breast density were extracted from mammography reports. Odds ratios and 95% confidence intervals (CIs) were estimated by using conditional logistic regression stratified according to age and race and adjusted for body mass index, parity, and menopausal status, and the area under the receiver operating characteristic curve (AUC) was computed. Results The adjusted odds ratios and 95% CIs for each standard deviation increment of the percentage of density, dense area, volumetric percentage of density, and dense volume were 1.61 (95% CI: 1.19, 2.19), 1.49 (95% CI: 1.15, 1.92), 1.54 (95% CI: 1.12, 2.10), and 1.41 (95% CI: 1.11, 1.80), respectively. Odds ratios for women with extremely dense breasts compared with those with scattered areas of fibroglandular density were 2.06 (95% CI: 0.85, 4.97) and 2.05 (95% CI: 0.90, 4.64) for BI-RADS and Volpara density classifications, respectively. Clinical BI-RADS was more accurate (AUC, 0.68; 95% CI: 0.63, 0.74) than Volpara (AUC, 0.64; 95% CI: 0.58, 0.70) and continuous measures of percentage of density (AUC, 0.66; 95% CI: 0.60, 0.72), dense area (AUC, 0.66; 95% CI: 0.60, 0.72), volumetric percentage of density (AUC, 0.64; 95% CI: 0.58, 0.70), and density volume (AUC, 0.65; 95% CI: 0.59, 0.71), although the AUC differences were not statistically significant. Conclusion Mammographic density on FFDM images was positively associated with breast cancer risk by using the computer assisted methods and BI-RADS. BI-RADS classification was as accurate as computer-assisted methods for discrimination of patients from control subjects. © RSNA, 2016.

Multiphoton microscopic imaging of fibrotic focus in invasive ductal carcinoma of the breast

NASA Astrophysics Data System (ADS)

Chen, Sijia; Nie, Yuting; Lian, Yuane; Wu, Yan; Fu, Fangmeng; Wang, Chuan; Zhuo, Shuangmu; Chen, Jianxin

2014-11-01

During the proliferation of breast cancer, the desmoplastic can evoke a fibrosis response by invading healthy tissue. Fibrotic focus (FF) in invasive ductal carcinoma (IDC) of the breast had been reported to be associated with significantly poorer survival rate than IDC without FF. As an important prognosis indicator, it's difficult to obtain the exact fibrotic information from traditional detection method such as mammography. Multiphoton imaging based on two-photon excited fluorescence (TPEF) and second-harmonic generation (SHG) has been recently employed for microscopic examination of unstained tissue. In this study, multiphoton microscopy (MPM) was used to image the fibrotic focus in invasive ductal carcinoma tissue. The morphology and distribution of collagen in fibrotic focus can be demonstrated by the SHG signal. Variation of collagen between IDC with and without FF will be examined and further characterized, which may be greatly related to the metastasis of breast cancer. Our result suggested that the MPM can be efficient in identifying and locating the fibrotic focus in IDC. Combining with the pathology analysis and other detecting methods, MPM owns potential in becoming an advanced histological tool for detecting the fibrotic focus in IDC and collecting prognosis information, which may guide the subsequent surgery option and therapy procedure for patients.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Xiu-Li, E-mail: usually.158@163.com; Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, No 169 Donghu Road, Wuchang District, Wuhan 430071; Peng, Chun-Wei, E-mail: pqc278@163.com

Highlights: {yields} HER2 level is closely related to the biologic behaviors of breast cancer cells. {yields} A new method to simultaneously image HER2 and type IV collagen was established. {yields} HER2 status and type IV collagen degradation predict breast cancer invasion. {yields} The complex interactions between tumor and its environment were revealed. -- Abstract: It has been well recognized that human epidermal growth factor receptor 2 (HER2) level in breast cancer (BC) is closely related to the malignant biologic behaviors of the tumor, including invasion and metastasis. Yet, there has been a lack of directly observable evidence to support suchmore » notion. Here we report a quantum dots (QDs)-based double-color imaging technique to simultaneously show the HER2 level on BC cells and the type IV collagen in the tumor matrix. In benign breast tumor, the type IV collagen was intact. With the increasing of HER2 expression level, there has been a progressive decrease in type IV collagen around the cancer nest. At HER2 (3+) expression level, there has virtually been a total destruction of type IV collagen. Moreover, HER2 (3+) BC cells also show direct invasion into the blood vessels. This novel imaging method provides direct observable evidence to support the theory that the HER2 expression level is directly related to BC invasion.« less

Optical imaging for breast cancer prescreening

PubMed Central

Godavarty, Anuradha; Rodriguez, Suset; Jung, Young-Jin; Gonzalez, Stephanie

2015-01-01

Breast cancer prescreening is carried out prior to the gold standard screening using X-ray mammography and/or ultrasound. Prescreening is typically carried out using clinical breast examination (CBE) or self-breast examinations (SBEs). Since CBE and SBE have high false-positive rates, there is a need for a low-cost, noninvasive, non-radiative, and portable imaging modality that can be used as a prescreening tool to complement CBE/SBE. This review focuses on the various hand-held optical imaging devices that have been developed and applied toward early-stage breast cancer detection or as a prescreening tool via phantom, in vivo, and breast cancer imaging studies. Apart from the various optical devices developed by different research groups, a wide-field fiber-free near-infrared optical scanner has been developed for transillumination-based breast imaging in our Optical Imaging Laboratory. Preliminary in vivo studies on normal breast tissues, with absorption-contrasted targets placed in the intramammary fold, detected targets as deep as 8.8 cm. Future work involves in vivo imaging studies on breast cancer subjects and comparison with the gold standard X-ray mammography approach. PMID:26229503

Paradigm Shifts in Breast Care Delivery: Impact of Imaging in a Multidisciplinary Environment.

PubMed

Krishnamurthy, Savitri; Bevers, Therese; Kuerer, Henry M; Smith, Benjamin; Yang, Wei Tse

2017-02-01

The practice of breast imaging in a collaborative multidisciplinary environment adds significant value to outcomes in women's health care. In this article, we describe multidisciplinary considerations in breast cancer screening and early detection, the impact of imaging and histopathologic findings in the diagnostic evaluation and management of breast abnormalities, and the contribution of imaging to surgical and radiation therapy planning for the breast cancer patient. The multidisciplinary delivery of breast care for women that incorporates screening, diagnosis of borderline and high-risk lesions, and management of the breast cancer patient adds considerable value to outcomes in health care.

Integrating prior information into microwave tomography Part 1: Impact of detail on image quality.

PubMed

Kurrant, Douglas; Baran, Anastasia; LoVetri, Joe; Fear, Elise

2017-12-01

The authors investigate the impact that incremental increases in the level of detail of patient-specific prior information have on image quality and the convergence behavior of an inversion algorithm in the context of near-field microwave breast imaging. A methodology is presented that uses image quality measures to characterize the ability of the algorithm to reconstruct both internal structures and lesions embedded in fibroglandular tissue. The approach permits key aspects that impact the quality of reconstruction of these structures to be identified and quantified. This provides insight into opportunities to improve image reconstruction performance. Patient-specific information is acquired using radar-based methods that form a regional map of the breast. This map is then incorporated into a microwave tomography algorithm. Previous investigations have demonstrated the effectiveness of this approach to improve image quality when applied to data generated with two-dimensional (2D) numerical models. The present study extends this work by generating prior information that is customized to vary the degree of structural detail to facilitate the investigation of the role of prior information in image formation. Numerical 2D breast models constructed from magnetic resonance (MR) scans, and reconstructions formed with a three-dimensional (3D) numerical breast model are used to assess if trends observed for the 2D results can be extended to 3D scenarios. For the blind reconstruction scenario (i.e., no prior information), the breast surface is not accurately identified and internal structures are not clearly resolved. A substantial improvement in image quality is achieved by incorporating the skin surface map and constraining the imaging domain to the breast. Internal features within the breast appear in the reconstructed image. However, it is challenging to discriminate between adipose and glandular regions and there are inaccuracies in both the structural properties of the glandular region and the dielectric properties reconstructed within this structure. Using a regional map with a skin layer only marginally improves this situation. Increasing the structural detail in the prior information to include internal features leads to reconstructions for which the interface that delineates the fat and gland regions can be inferred. Different features within the glandular region corresponding to tissues with varying relative permittivity values, such as a lesion embedded within glandular structure, emerge in the reconstructed images. Including knowledge of the breast surface and skin layer leads to a substantial improvement in image quality compared to the blind case, but the images have limited diagnostic utility for applications such as tumor response tracking. The diagnostic utility of the reconstruction technique is improved considerably when patient-specific structural information is used. This qualitative observation is supported quantitatively with image metrics. © 2017 American Association of Physicists in Medicine.

Automation and Preclinical Evaluation of a Dedicated Emission Mammotomography System for Fully 3-D Molecular Breast Imaging

DTIC Science & Technology

2009-10-01

molecular breast imaging, with the ability to dynamically contour any sized breast, will improve detection and potentially in vivo characterization of...Having flexible 3D positioning about the breast yielded minimal RMSD differences, which is important for high resolution molecular emission imaging. This...TITLE: Automation and Preclinical Evaluation of a Dedicated Emission Mammotomography System for Fully 3-D Molecular Breast Imaging PRINCIPAL

Segmentation of the whole breast from low-dose chest CT images

NASA Astrophysics Data System (ADS)

Liu, Shuang; Salvatore, Mary; Yankelevitz, David F.; Henschke, Claudia I.; Reeves, Anthony P.

2015-03-01

The segmentation of whole breast serves as the first step towards automated breast lesion detection. It is also necessary for automatically assessing the breast density, which is considered to be an important risk factor for breast cancer. In this paper we present a fully automated algorithm to segment the whole breast in low-dose chest CT images (LDCT), which has been recommended as an annual lung cancer screening test. The automated whole breast segmentation and potential breast density readings as well as lesion detection in LDCT will provide useful information for women who have received LDCT screening, especially the ones who have not undergone mammographic screening, by providing them additional risk indicators for breast cancer with no additional radiation exposure. The two main challenges to be addressed are significant range of variations in terms of the shape and location of the breast in LDCT and the separation of pectoral muscles from the glandular tissues. The presented algorithm achieves robust whole breast segmentation using an anatomy directed rule-based method. The evaluation is performed on 20 LDCT scans by comparing the segmentation with ground truth manually annotated by a radiologist on one axial slice and two sagittal slices for each scan. The resulting average Dice coefficient is 0.880 with a standard deviation of 0.058, demonstrating that the automated segmentation algorithm achieves results consistent with manual annotations of a radiologist.

Molecular breast imaging using a dedicated high-performance instrument

NASA Astrophysics Data System (ADS)

O'Connor, Michael K.; Wagenaar, Douglas; Hruska, Carrie B.; Phillips, Stephen; Caravaglia, Gina; Rhodes, Deborah

2006-08-01

In women with radiographically dense breasts, the sensitivity of mammography is less than 50%. With the increase in the percent of women with dense breasts, it is important to look at alternative screening techniques for this population. This article reviews the strengths and weaknesses of current imaging techniques and focuses on recent developments in semiconductor-based gamma camera systems that offer significant improvements in image quality over that achievable with single-crystal sodium iodide systems. We have developed a technique known as Molecular Breast Imaging (MBI) using small field of view Cadmium Zinc Telluride (CZT) gamma cameras that permits the breast to be imaged in a similar manner to mammography, using light pain-free compression. Computer simulations and experimental studies have shown that use of low-energy high sensitivity collimation coupled with the excellent energy resolution and intrinsic spatial resolution of CZT detectors provides optimum image quality for the detection of small breast lesions. Preliminary clinical studies with a prototype dual-detector system have demonstrated that Molecular Breast Imaging has a sensitivity of ~90% for the detection of breast tumors less than 10 mm in diameter. By comparison, conventional scintimammography only achieves a sensitivity of 50% in the detection of lesions < 10 mm. Because Molecular Breast Imaging is not affected by breast density, this technique may offer an important adjunct to mammography in the evaluation of women with dense breast parenchyma.

Population of 224 realistic human subject-based computational breast phantoms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erickson, David W.; Wells, Jered R., E-mail: jered.wells@duke.edu; Sturgeon, Gregory M.

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was thenmore » applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.« less

Population of 224 realistic human subject-based computational breast phantoms

PubMed Central

Erickson, David W.; Wells, Jered R.; Sturgeon, Gregory M.; Dobbins, James T.; Segars, W. Paul; Lo, Joseph Y.

2016-01-01

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns. PMID:26745896

Volumetric breast density evaluation by ultrasound tomography and magnetic resonance imaging: a preliminary comparative study

NASA Astrophysics Data System (ADS)

Myc, Lukasz; Duric, Neb; Littrup, Peter; Li, Cuiping; Ranger, Bryan; Lupinacci, Jessica; Schmidt, Steven; Rama, Olsi; Bey-Knight, Lisa

2010-03-01

Since a 1976 study by Wolfe, high breast density has gained recognition as a factor strongly correlating with an increased incidence of breast cancer. These observations have led to mammographic density being designated a "risk factor" for breast cancer. Clinically, the exclusive reliance on mammography for breast density measurement has forestalled the inclusion of breast density into statistical risk models. This exclusion has in large part been due to the ionizing radiation associated with the method. Additionally, the use of mammography as valid tool for measuring a three dimensional characteristic (breast density) has been criticized for its prima facie incongruity. These shortfalls have prompted MRI studies of breast density as an alternative three-dimensional method of assessing breast density. Although, MRI is safe and can be used to measure volumetric density, its cost has prohibited its use in screening. Here, we report that sound speed measurements using a prototype ultrasound tomography device have potential for use as surrogates for breast density measurement. Accordingly, we report a strong positive linear correlation between volume-averaged sound speed of the breast and percent glandular tissue volume as assessed by MR.

Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography.

PubMed

Kim, Sun Mi; Kim, Yongdai; Jeong, Kuhwan; Jeong, Heeyeong; Kim, Jiyoung

2018-01-01

The aim of this study was to compare the performance of image analysis for predicting breast cancer using two distinct regression models and to evaluate the usefulness of incorporating clinical and demographic data (CDD) into the image analysis in order to improve the diagnosis of breast cancer. This study included 139 solid masses from 139 patients who underwent a ultrasonography-guided core biopsy and had available CDD between June 2009 and April 2010. Three breast radiologists retrospectively reviewed 139 breast masses and described each lesion using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We applied and compared two regression methods-stepwise logistic (SL) regression and logistic least absolute shrinkage and selection operator (LASSO) regression-in which the BI-RADS descriptors and CDD were used as covariates. We investigated the performances of these regression methods and the agreement of radiologists in terms of test misclassification error and the area under the curve (AUC) of the tests. Logistic LASSO regression was superior (P<0.05) to SL regression, regardless of whether CDD was included in the covariates, in terms of test misclassification errors (0.234 vs. 0.253, without CDD; 0.196 vs. 0.258, with CDD) and AUC (0.785 vs. 0.759, without CDD; 0.873 vs. 0.735, with CDD). However, it was inferior (P<0.05) to the agreement of three radiologists in terms of test misclassification errors (0.234 vs. 0.168, without CDD; 0.196 vs. 0.088, with CDD) and the AUC without CDD (0.785 vs. 0.844, P<0.001), but was comparable to the AUC with CDD (0.873 vs. 0.880, P=0.141). Logistic LASSO regression based on BI-RADS descriptors and CDD showed better performance than SL in predicting the presence of breast cancer. The use of CDD as a supplement to the BI-RADS descriptors significantly improved the prediction of breast cancer using logistic LASSO regression.

iROLL: does 3-D radioguided occult lesion localization improve surgical management in early-stage breast cancer?

PubMed

Bluemel, Christina; Cramer, Andreas; Grossmann, Christoph; Kajdi, Georg W; Malzahn, Uwe; Lamp, Nora; Langen, Heinz-Jakob; Schmid, Jan; Buck, Andreas K; Grimminger, Hanns-Jörg; Herrmann, Ken

2015-10-01

To prospectively evaluate the feasibility of 3-D radioguided occult lesion localization (iROLL) and to compare iROLL with wire-guided localization (WGL) in patients with early-stage breast cancer undergoing breast-conserving surgery and sentinel lymph node biopsy (SLNB). WGL (standard procedure) and iROLL in combination with SLNB were performed in 31 women (mean age 65.1 ± 11.2 years) with early-stage breast cancer and clinically negative axillae. Patient comfort in respect of both methods was assessed using a ten point scale. SLNB and iROLL were guided by freehand SPECT (fhSPECT). The results of the novel 3-D image-based method were compared with those of WGL, ultrasound-based lesion localization, and histopathology. iROLL successfully detected the malignant primary and at least one sentinel lymph node in 97% of patients. In a single patient (3%), only iROLL, and not WGL, enabled lesion localization. The variability between fhSPECT and ultrasound-based depth localization of breast lesions was low (1.2 ± 1.4 mm). Clear margins were achieved in 81% of the patients; however, precise prediction of clear histopathological surgical margins was not feasible using iROLL. Patients rated iROLL as less painful than WGL with a pain score 0.8 ± 1.2 points (p < 0.01) lower than the score for iROLL. iROLL is a well-tolerated and feasible technique for localizing early-stage breast cancer in the course of breast-conserving surgery, and is a suitable replacement for WGL. As a single image-based procedure for localization of breast lesions and sentinel nodes, iROLL may improve the entire surgical procedure. However, no advantages of the image-guided procedure were found with regard to prediction of complete tumour resection.

Comparison of breast density measurements made using ultrasound tomography and mammography

NASA Astrophysics Data System (ADS)

Sak, Mark; Duric, Neb; Littrup, Peter; Bey-Knight, Lisa; Krycia, Mark; Sherman, Mark E.; Boyd, Norman; Gierach, Gretchen L.

2015-03-01

Women with elevated mammographic percent density, defined as the ratio of fibroglandular tissue area to total breast area on a mammogram are at an increased risk of developing breast cancer. Ultrasound tomography (UST) is an imaging modality that can create tomographic sound speed images of a patient's breast, which can then be used to measure breast density. These sound speed images are useful because physical tissue density is directly proportional to sound speed. The work presented here updates previous results that compared mammographic breast density measurements with UST breast density measurements within an ongoing study. The current analysis has been expanded to include 158 women with negative digital mammographic screens who then underwent a breast UST scan. Breast density was measured for both imaging modalities and preliminary analysis demonstrated strong and positive correlations (Spearman correlation coefficient rs = 0.703). Additional mammographic and UST related imaging characteristics were also analyzed and used to compare the behavior of both imaging modalities. Results suggest that UST can be used among women with negative mammographic screens as a quantitative marker of breast density that may avert shortcomings of mammography.

Breast cancer Ki67 expression preoperative discrimination by DCE-MRI radiomics features

NASA Astrophysics Data System (ADS)

Ma, Wenjuan; Ji, Yu; Qin, Zhuanping; Guo, Xinpeng; Jian, Xiqi; Liu, Peifang

2018-02-01

To investigate whether quantitative radiomics features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are associated with Ki67 expression of breast cancer. In this institutional review board approved retrospective study, we collected 377 cases Chinese women who were diagnosed with invasive breast cancer in 2015. This cohort included 53 low-Ki67 expression (Ki67 proliferation index less than 14%) and 324 cases with high-Ki67 expression (Ki67 proliferation index more than 14%). A binary-classification of low- vs. high- Ki67 expression was performed. A set of 52 quantitative radiomics features, including morphological, gray scale statistic, and texture features, were extracted from the segmented lesion area. Three most common machine learning classification methods, including Naive Bayes, k-Nearest Neighbor and support vector machine with Gaussian kernel, were employed for the classification and the least absolute shrink age and selection operator (LASSO) method was used to select most predictive features set for the classifiers. Classification performance was evaluated by the area under receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity. The model that used Naive Bayes classification method achieved the best performance than the other two methods, yielding 0.773 AUC value, 0.757 accuracy, 0.777 sensitivity and 0.769 specificity. Our study showed that quantitative radiomics imaging features of breast tumor extracted from DCE-MRI are associated with breast cancer Ki67 expression. Future larger studies are needed in order to further evaluate the findings.

Deep learning and three-compartment breast imaging in breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Drukker, Karen; Huynh, Benjamin Q.; Giger, Maryellen L.; Malkov, Serghei; Avila, Jesus I.; Fan, Bo; Joe, Bonnie; Kerlikowske, Karla; Drukteinis, Jennifer S.; Kazemi, Leila; Pereira, Malesa M.; Shepherd, John

2017-03-01

We investigated whether deep learning has potential to aid in the diagnosis of breast cancer when applied to mammograms and biologic tissue composition images derived from three-compartment (3CB) imaging. The dataset contained diagnostic mammograms and 3CB images (water, lipid, and protein content) of biopsy-sampled BIRADS 4 and 5 lesions in 195 patients. In 58 patients, the lesion manifested as a mass (13 malignant vs. 45 benign), in 87 as microcalcifications (19 vs. 68), and in 56 as (focal) asymmetry or architectural distortion (11 vs. 45). Six patients had both a mass and calcifications. For each mammogram and corresponding 3CB images, a 128x128 region of interest containing the lesion was selected by an expert radiologist and used directly as input to a deep learning method pretrained on a very large independent set of non-medical images. We used a nested leave-one-out-by-case (patient) model selection and classification protocol. The area under the ROC curve (AUC) for the task of distinguishing between benign and malignant lesions was used as performance metric. For the cases with mammographic masses, the AUC increased from 0.83 (mammograms alone) to 0.89 (mammograms+3CB, p=.162). For the microcalcification and asymmetry/architectural distortion cases the AUC increased from 0.84 to 0.91 (p=.116) and from 0.61 to 0.87 (p=.006), respectively. Our results indicate great potential for the application of deep learning methods in the diagnosis of breast cancer and additional knowledge of the biologic tissue composition appeared to improve performance, especially for lesions mammographically manifesting as asymmetries or architectural distortions.

Cell type classifiers for breast cancer microscopic images based on fractal dimension texture analysis of image color layers.

PubMed

Jitaree, Sirinapa; Phinyomark, Angkoon; Boonyaphiphat, Pleumjit; Phukpattaranont, Pornchai

2015-01-01

Having a classifier of cell types in a breast cancer microscopic image (BCMI), obtained with immunohistochemical staining, is required as part of a computer-aided system that counts the cancer cells in such BCMI. Such quantitation by cell counting is very useful in supporting decisions and planning of the medical treatment of breast cancer. This study proposes and evaluates features based on texture analysis by fractal dimension (FD), for the classification of histological structures in a BCMI into either cancer cells or non-cancer cells. The cancer cells include positive cells (PC) and negative cells (NC), while the normal cells comprise stromal cells (SC) and lymphocyte cells (LC). The FD feature values were calculated with the box-counting method from binarized images, obtained by automatic thresholding with Otsu's method of the grayscale images for various color channels. A total of 12 color channels from four color spaces (RGB, CIE-L*a*b*, HSV, and YCbCr) were investigated, and the FD feature values from them were used with decision tree classifiers. The BCMI data consisted of 1,400, 1,200, and 800 images with pixel resolutions 128 × 128, 192 × 192, and 256 × 256, respectively. The best cross-validated classification accuracy was 93.87%, for distinguishing between cancer and non-cancer cells, obtained using the Cr color channel with window size 256. The results indicate that the proposed algorithm, based on fractal dimension features extracted from a color channel, performs well in the automatic classification of the histology in a BCMI. This might support accurate automatic cell counting in a computer-assisted system for breast cancer diagnosis. © Wiley Periodicals, Inc.

TH-A-18A-01: Innovation in Clinical Breast Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, B; Yang, K; Yaffe, M

Several novel modalities have been or are on the verge of being introduced into the breast imaging clinic. These include tomosynthesis imaging, dedicated breast CT, contrast-enhanced digital mammography, and automated breast ultrasound, all of which are covered in this course. Tomosynthesis and dedicated breast CT address the problem of tissue superimposition that limits mammography screening performance, by improved or full resolution of the 3D breast morphology. Contrast-enhanced digital mammography provides functional information that allows for visualization of tumor angiogenesis. 3D breast ultrasound has high sensitivity for tumor detection in dense breasts, but the imaging exam was traditionally performed by radiologists.more » In automated breast ultrasound, the scan is performed in an automated fashion, making for a more practical imaging tool, that is now used as an adjunct to digital mammography in breast cancer screening. This course will provide medical physicists with an in-depth understanding of the imaging physics of each of these four novel imaging techniques, as well as the rationale and implementation of QC procedures. Further, basic clinical applications and work flow issues will be discussed. Learning Objectives: To be able to describe the underlying physical and physiological principles of each imaging technique, and to understand the corresponding imaging acquisition process. To be able to describe the critical system components and their performance requirements. To understand the rationale and implementation of quality control procedures, as well as regulatory requirements for systems with FDA approval. To learn about clinical applications and understand risks and benefits/strength and weakness of each modality in terms of clinical breast imaging.« less

Color-coded automated signal intensity curves for detection and characterization of breast lesions: preliminary evaluation of a new software package for integrated magnetic resonance-based breast imaging.

PubMed

Pediconi, Federica; Catalano, Carlo; Venditti, Fiammetta; Ercolani, Mauro; Carotenuto, Luigi; Padula, Simona; Moriconi, Enrica; Roselli, Antonella; Giacomelli, Laura; Kirchin, Miles A; Passariello, Roberto

2005-07-01

The objective of this study was to evaluate the value of a color-coded automated signal intensity curve software package for contrast-enhanced magnetic resonance mammography (CE-MRM) in patients with suspected breast cancer. Thirty-six women with suspected breast cancer based on mammographic and sonographic examinations were preoperatively evaluated on CE-MRM. CE-MRM was performed on a 1.5-T magnet using a 2D Flash dynamic T1-weighted sequence. A dosage of 0.1 mmol/kg of Gd-BOPTA was administered at a flow rate of 2 mL/s followed by 10 mL of saline. Images were analyzed with the new software package and separately with a standard display method. Statistical comparison was performed of the confidence for lesion detection and characterization with the 2 methods and of the diagnostic accuracy for characterization compared with histopathologic findings. At pathology, 54 malignant lesions and 14 benign lesions were evaluated. All 68 (100%) lesions were detected with both methods and good correlation with histopathologic specimens was obtained. Confidence for both detection and characterization was significantly (P < or = 0.025) better with the color-coded method, although no difference (P > 0.05) between the methods was noted in terms of the sensitivity, specificity, and overall accuracy for lesion characterization. Excellent agreement between the 2 methods was noted for both the determination of lesion size (kappa = 0.77) and determination of SI/T curves (kappa = 0.85). The novel color-coded signal intensity curve software allows lesions to be visualized as false color maps that correspond to conventional signal intensity time curves. Detection and characterization of breast lesions with this method is quick and easily interpretable.

A superpixel-based framework for automatic tumor segmentation on breast DCE-MRI

NASA Astrophysics Data System (ADS)

Yu, Ning; Wu, Jia; Weinstein, Susan P.; Gaonkar, Bilwaj; Keller, Brad M.; Ashraf, Ahmed B.; Jiang, YunQing; Davatzikos, Christos; Conant, Emily F.; Kontos, Despina

2015-03-01

Accurate and efficient automated tumor segmentation in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is highly desirable for computer-aided tumor diagnosis. We propose a novel automatic segmentation framework which incorporates mean-shift smoothing, superpixel-wise classification, pixel-wise graph-cuts partitioning, and morphological refinement. A set of 15 breast DCE-MR images, obtained from the American College of Radiology Imaging Network (ACRIN) 6657 I-SPY trial, were manually segmented to generate tumor masks (as ground truth) and breast masks (as regions of interest). Four state-of-the-art segmentation approaches based on diverse models were also utilized for comparison. Based on five standard evaluation metrics for segmentation, the proposed framework consistently outperformed all other approaches. The performance of the proposed framework was: 1) 0.83 for Dice similarity coefficient, 2) 0.96 for pixel-wise accuracy, 3) 0.72 for VOC score, 4) 0.79 mm for mean absolute difference, and 5) 11.71 mm for maximum Hausdorff distance, which surpassed the second best method (i.e., adaptive geodesic transformation), a semi-automatic algorithm depending on precise initialization. Our results suggest promising potential applications of our segmentation framework in assisting analysis of breast carcinomas.

Computation of mass-density images from x-ray refraction-angle images.

PubMed

Wernick, Miles N; Yang, Yongyi; Mondal, Indrasis; Chapman, Dean; Hasnah, Moumen; Parham, Christopher; Pisano, Etta; Zhong, Zhong

2006-04-07

In this paper, we investigate the possibility of computing quantitatively accurate images of mass density variations in soft tissue. This is a challenging task, because density variations in soft tissue, such as the breast, can be very subtle. Beginning from an image of refraction angle created by either diffraction-enhanced imaging (DEI) or multiple-image radiography (MIR), we estimate the mass-density image using a constrained least squares (CLS) method. The CLS algorithm yields accurate density estimates while effectively suppressing noise. Our method improves on an analytical method proposed by Hasnah et al (2005 Med. Phys. 32 549-52), which can produce significant artefacts when even a modest level of noise is present. We present a quantitative evaluation study to determine the accuracy with which mass density can be determined in the presence of noise. Based on computer simulations, we find that the mass-density estimation error can be as low as a few per cent for typical density variations found in the breast. Example images computed from less-noisy real data are also shown to illustrate the feasibility of the technique. We anticipate that density imaging may have application in assessment of water content of cartilage resulting from osteoarthritis, in evaluation of bone density, and in mammographic interpretation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, Y; Becker, S; Mutaf, Y

Purpose: The first GammaPod™ unit, a dedicated prone stereotactic treatment device for early stage breast cancer, has been installed and commissioned at University of Maryland School of Medicine. The objective of this study was to investigate potential dosimetric impact of inaccurate breast contour. Methods: In GammaPod treatments, patient’s beast is immobilized by a breast cup device (BCID) throughout the entire same-day imaging and treatment procedure. 28 different BICD sizes are available to accommodate patients with varying breast sizes. A mild suction helps breast tissue to conform to the shape of the cup with selected size. In treatment planning, dose calculationmore » utilizes previously calculated dose distributions for available cup geometry rather than the breast shape from CT image. Patient CT images with breast cups indicate minor geometric discrepancy between the matched shape of the cup and the breast contour, i.e., the contour size is larger or smaller. In order to investigate the dosimetric impact of these discrepancies, we simulated such discrepancies and reassessed the dose to target as well as skin. Results: In vicinity of skin, hot/cold spots were found when matched cup size was smaller/larger than patient’s breast after comparing the corrected dose profiles from Monte Carlo simulation with the planned dose from TPS. The overdosing/underdosing of target could yield point dose differences as large as 5% due to these setup errors (D95 changes within 2.5%). Maximal skin dose was overestimated/underestimated up to 25%/45% when matched cup size was larger/smaller than real breast contour. Conclusion: The dosimetric evaluation suggests substantial underdosing/overdosing with inaccurate cup geometry during planning, which is acceptable for current clinical trial. Further studies are needed to evaluate such impact to treating small volume close to skin.« less

Monte Carlo simulations to assess the effects of tube current modulation on breast dose for multidetector CT

NASA Astrophysics Data System (ADS)

Angel, Erin; Yaghmai, Nazanin; Matilda Jude, Cecilia; DeMarco, John J.; Cagnon, Christopher H.; Goldin, Jonathan G.; Primak, Andrew N.; Stevens, Donna M.; Cody, Dianna D.; McCollough, Cynthia H.; McNitt-Gray, Michael F.

2009-02-01

Tube current modulation was designed to reduce radiation dose in CT imaging while maintaining overall image quality. This study aims to develop a method for evaluating the effects of tube current modulation (TCM) on organ dose in CT exams of actual patient anatomy. This method was validated by simulating a TCM and a fixed tube current chest CT exam on 30 voxelized patient models and estimating the radiation dose to each patient's glandular breast tissue. This new method for estimating organ dose was compared with other conventional estimates of dose reduction. Thirty detailed voxelized models of patient anatomy were created based on image data from female patients who had previously undergone clinically indicated CT scans including the chest area. As an indicator of patient size, the perimeter of the patient was measured on the image containing at least one nipple using a semi-automated technique. The breasts were contoured on each image set by a radiologist and glandular tissue was semi-automatically segmented from this region. Previously validated Monte Carlo models of two multidetector CT scanners were used, taking into account details about the source spectra, filtration, collimation and geometry of the scanner. TCM data were obtained from each patient's clinical scan and factored into the model to simulate the effects of TCM. For each patient model, two exams were simulated: a fixed tube current chest CT and a tube current modulated chest CT. X-ray photons were transported through the anatomy of the voxelized patient models, and radiation dose was tallied in the glandular breast tissue. The resulting doses from the tube current modulated simulations were compared to the results obtained from simulations performed using a fixed mA value. The average radiation dose to the glandular breast tissue from a fixed tube current scan across all patient models was 19 mGy. The average reduction in breast dose using the tube current modulated scan was 17%. Results were size dependent with smaller patients getting better dose reduction (up to 64% reduction) and larger patients getting a smaller reduction, and in some cases the dose actually increased when using tube current modulation (up to 41% increase). The results indicate that radiation dose to glandular breast tissue generally decreases with the use of tube current modulated CT acquisition, but that patient size (and in some cases patient positioning) may affect dose reduction.

Multi-scales region segmentation for ROI separation in digital mammograms

NASA Astrophysics Data System (ADS)

Zhang, Dapeng; Zhang, Di; Li, Yue; Wang, Wei

2017-02-01

Mammography is currently the most effective imaging modality used by radiologists for the screening of breast cancer. Segmentation is one of the key steps in the process of developing anatomical models for calculation of safe medical dose of radiation. This paper explores the potential of the statistical region merging segmentation technique for Breast segmentation in digital mammograms. First, the mammograms are pre-processing for regions enhancement, then the enhanced images are segmented using SRM with multi scales, finally these segmentations are combined for region of interest (ROI) separation and edge detection. The proposed algorithm uses multi-scales region segmentation in order to: separate breast region from background region, region edge detection and ROIs separation. The experiments are performed using a data set of mammograms from different patients, demonstrating the validity of the proposed criterion. Results show that, the statistical region merging segmentation algorithm actually can work on the segmentation of medical image and more accurate than another methods. And the outcome shows that the technique has a great potential to become a method of choice for segmentation of mammograms.

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples

PubMed Central

Lakshmanan, Manu N.; Greenberg, Joel A.; Samei, Ehsan; Kapadia, Anuj J.

2016-01-01

Abstract. A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice. PMID:26962543

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples.

PubMed

Lakshmanan, Manu N; Greenberg, Joel A; Samei, Ehsan; Kapadia, Anuj J

2016-01-01

A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice.

Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study

NASA Astrophysics Data System (ADS)

Taroni, Paola; Paganoni, Anna Maria; Ieva, Francesca; Pifferi, Antonio; Quarto, Giovanna; Abbate, Francesca; Cassano, Enrico; Cubeddu, Rinaldo

2017-01-01

Several techniques are being investigated as a complement to screening mammography, to reduce its false-positive rate, but results are still insufficient to draw conclusions. This initial study explores time domain diffuse optical imaging as an adjunct method to classify non-invasively malignant vs benign breast lesions. We estimated differences in tissue composition (oxy- and deoxyhemoglobin, lipid, water, collagen) and absorption properties between lesion and average healthy tissue in the same breast applying a perturbative approach to optical images collected at 7 red-near infrared wavelengths (635-1060 nm) from subjects bearing breast lesions. The Discrete AdaBoost procedure, a machine-learning algorithm, was then exploited to classify lesions based on optically derived information (either tissue composition or absorption) and risk factors obtained from patient’s anamnesis (age, body mass index, familiarity, parity, use of oral contraceptives, and use of Tamoxifen). Collagen content, in particular, turned out to be the most important parameter for discrimination. Based on the initial results of this study the proposed method deserves further investigation.