Optimization of the scan protocols for CT-based material extraction in small animal PET/CT studies
NASA Astrophysics Data System (ADS)
Yang, Ching-Ching; Yu, Jhih-An; Yang, Bang-Hung; Wu, Tung-Hsin
2013-12-01
We investigated the effects of scan protocols on CT-based material extraction to minimize radiation dose while maintaining sufficient image information in small animal studies. The phantom simulation experiments were performed with the high dose (HD), medium dose (MD) and low dose (LD) protocols at 50, 70 and 80 kVp with varying mA s. The reconstructed CT images were segmented based on Hounsfield unit (HU)-physical density (ρ) calibration curves and the dual-energy CT-based (DECT) method. Compared to the (HU;ρ) method performed on CT images acquired with the 80 kVp HD protocol, a 2-fold improvement in segmentation accuracy and a 7.5-fold reduction in radiation dose were observed when the DECT method was performed on CT images acquired with the 50/80 kVp LD protocol, showing the possibility to reduce radiation dose while achieving high segmentation accuracy.
Mestieri, Leticia Boldrin; Gomes-Cornélio, Ana Lívia; Rodrigues, Elisandra Márcia; Salles, Loise Pedrosa; Bosso-Martelo, Roberta; Guerreiro-Tanomaru, Juliane Maria; Tanomaru-Filho, Mário
2015-10-01
Mineral Trioxide Aggregate (MTA) is a calcium silicate-based material. New sealers have been developed based on calcium silicate as MTA Fillapex and MTA Plus. The aim of this study was to evaluate biocompatibility and bioactivity of these two calcium silicate-based sealers in culture of human dental pulp cells (hDPCs). The cells were isolated from third molars extracted from a 16-year-old patient. Pulp tissue was sectioned into fragments with approximately 1 mm3 and kept in supplemented medium to obtain hDPCs adherent cultures. Cell characterization assays were performed to prove the osteogenic potential. The evaluated materials were: MTA Plus (MTAP); MTA Fillapex (MTAF) and FillCanal (FC). Biocompatibility was evaluated with MTT and Neutral Red (NR) assays, after hDPCs exposure for 24 h to different dilutions of each sealer extract (1:2, 1:3 and 1:4). Unexposed cells were the positive control (CT). Bioactivity was assessed by alkaline phosphatase (ALP) enzymatic assay in cells exposed for one and three days to sealer extracts (1:4 dilution). All data were analyzed by ANOVA and Tukey post-test (p≤0.05%). MTT and NR results showed suitable cell viability rates for MTAP at all dilutions (90-135%). Cells exposed to MTAF and FC (1:2 and 1:4 dilutions) showed significant low viability rate when compared to CT in MTT. The NR results demonstrated cell viability for all materials tested. In MTAP group, the cells ALP activity was similar to CT in one and three days of exposure to the material. MTAF and FC groups demonstrated a decrease in ALP activity when compared to CT at both periods of cell exposure. The hDPCs were suitable for the evaluation of new endodontic materialsin vitro. MTAP may be considered a promising material for endodontic treatments.
[Study on extraction process of available components of tea].
Bai, Qing-Qing; Liu, Yong-Feng; Guo, Mei; Zhao, Jian-Xi; Zhang, Tian-Cai; Di, Duo-Long
2011-09-01
To investigate the optimum ethanol extraction process conditions for the available components in the tea - Catechines (CT) including Epigallo catechin gallate (EGCG) and Caffeine (CF). The content of EGCG, CT and CF, extraction rate, DPPH * Free radical scavenging capacity were chosen as the assessment indexes. With the alcohol ratio (A), solid-liquid ratio (B) and reflux time (C) as investigation factors, the optimum ethanol extraction process of the available components from tea was determined by L9 (3(4)) orthogonal experimental design. It would obtain different extraction conditions to analyze the assessment indexes depending on the different extraction purposes. For the purpose of CT, the contents of EGCG and CT, extraction rate and DPPH * Free radical scavenging capacity were chosen as the assessment indexes, the optimum extraction conditions were selected as follows: the ratio of raw material to 75% alcohol was 1: 12, the reflux time was 30 minutes and extraction times were three; For the purpose of CF, the content of CF and extraction rate were chosen as the assessment indexes, the optimum extraction conditions were selected as follows: the ratio of raw material to 60% alcohol was 1: 12, the reflux time was 30 minutes and extraction times were three; For the purpose of integrated extraction, the contents of CT and CF, extraction rate and DPPH * Free radical scavenging capacity were chosen as the assessment indexes, the optimum extraction conditions were selected as follows: the ratio of raw material to 60% alcohol was 1: 8, the reflux time was 30 minutes and extraction times were three. The optimum extraction process in order to attain different purposes can give a reference to the research of a new medicine and industry production.
USDA-ARS?s Scientific Manuscript database
The butanol-HCl spectrophotometric assay is widely used for quantifying extractable and insoluble condensed tannins (CT, syn. proanthocyanidins) in foods, feeds, and foliage of herbaceous and woody plants, but the method underestimates total CT content when applied directly to plant material. To imp...
An image-domain, contrast material extraction method for Dual-Energy CT
Lambert, Jack W.; Sun, Yuxin; Gould, Robert G.; Ohliger, Michael A.; Li, Zhixi; Yeh, Benjamin M.
2016-01-01
Objectives Conventional material decomposition techniques for dual-energy CT (DECT) assume mass or volume conservation, where the CT number of each voxel is fully assigned to predefined materials. We present an image-domain contrast material extraction process (CMEP) method that preferentially extracts contrast-producing materials while leaving the remaining image intact. Materials and Methods Image processing freeware (Fiji) is used to perform consecutive arithmetic operations on a dual-energy ratio map to generate masks, which are then applied to the original images to generate material-specific images. First, a low-energy image is divided by a high-energy image to generate a ratio map. The ratio map is then split into material-specific masks. Ratio intervals known to correspond to particular materials (e.g. iodine, calcium) are assigned a multiplier of 1, while ratio values in between these intervals are assigned linear gradients from 0 to 1. The masks are then multiplied by an original CT image to produce material-specific images. The method was tested quantitatively at Dual-Source (DSCT) and Rapid kVp-Switching CT (RSCT) with phantoms using pure and mixed formulations of tungsten, calcium and iodine. Errors were evaluated by comparing the known material concentrations with those derived from the CMEP material-specific images. Further qualitative evaluation was performed in vivo at RSCT with a rabbit model using identical CMEP parameters to the phantom. Orally administered tungsten, vascularly administered iodine, and skeletal calcium were used as the three contrast materials. Results All five material combinations; tungsten, iodine and calcium, and mixtures of tungsten-calcium and iodine-calcium, showed distinct dual-energy ratios, largely independent of material concentration at both DSCT and RSCT. The CMEP was successful in both phantoms and in vivo. For pure contrast materials in the phantom, the maximum error between the known and CMEP-derived material concentrations was 0.9 mg/mL, 24.9 mg/mL and 0.4 mg/mL for iodine, calcium and tungsten respectively. Mixtures of iodine and calcium showed the highest discrepancies, which reflected the sensitivity of iodine to the image-type chosen for the extraction of the final material-specific image. The rabbit model was able to clearly show the three extracted material phases, vascular iodine, oral tungsten and skeletal calcium. Some skeletal calcium was misassigned to the extracted iodine image, however this did not impede the depiction of the vasculature. Conclusions The CMEP is a straightforward, image domain approach to extract material signal at dual-energy CT. It has particular value for separation of experimental high-Z contrast elements from conventional iodine contrast or calcium, even when the exact attenuation coefficient profiles of desired contrast materials may be unknown. The CMEP is readily implemented in the image-domain within freeware, and can be adapted for use with images from multiple vendors. PMID:27875338
Usability-driven pruning of large ontologies: the case of SNOMED CT
Boeker, Martin; Illarramendi, Arantza; Schulz, Stefan
2012-01-01
Objectives To study ontology modularization techniques when applied to SNOMED CT in a scenario in which no previous corpus of information exists and to examine if frequency-based filtering using MEDLINE can reduce subset size without discarding relevant concepts. Materials and Methods Subsets were first extracted using four graph-traversal heuristics and one logic-based technique, and were subsequently filtered with frequency information from MEDLINE. Twenty manually coded discharge summaries from cardiology patients were used as signatures and test sets. The coverage, size, and precision of extracted subsets were measured. Results Graph-traversal heuristics provided high coverage (71–96% of terms in the test sets of discharge summaries) at the expense of subset size (17–51% of the size of SNOMED CT). Pre-computed subsets and logic-based techniques extracted small subsets (1%), but coverage was limited (24–55%). Filtering reduced the size of large subsets to 10% while still providing 80% coverage. Discussion Extracting subsets to annotate discharge summaries is challenging when no previous corpus exists. Ontology modularization provides valuable techniques, but the resulting modules grow as signatures spread across subhierarchies, yielding a very low precision. Conclusion Graph-traversal strategies and frequency data from an authoritative source can prune large biomedical ontologies and produce useful subsets that still exhibit acceptable coverage. However, a clinical corpus closer to the specific use case is preferred when available. PMID:22268217
Condensed tannins in extracts from European medicinal plants and herbal products.
Ropiak, Honorata M; Ramsay, Aina; Mueller-Harvey, Irene
2016-03-20
Medicinal plant materials are not usually analysed for condensed tannins (CT). Thirty commercially available European medicinal plants and herbal products were screened for CT and fourteen CT samples were analysed in detail. This is also the first comprehensive CT analysis of pine buds, walnut leaves, heather flowers and great water dock roots. Acetone/water extracts contained between 3.2 and 25.9 g CT/100g of extract, had CT with mean degrees of polymerisation of 2.9 to 13.3, procyanidin/prodelphinidin ratios of 1.6/98.4 to 100/0 and cis/trans flavan-3-ol ratios of 17.7/82.3 to 97.3/2.7. The majority of samples contained procyanidins, four contained A-type linkages (blackthorn flowers, heather flowers, bilberry leaves and cowberry leaves) and one sample also had galloylated procyanidins (great water dock roots). Copyright © 2015 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fried, David V.; Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas; Tucker, Susan L.
2014-11-15
Purpose: To determine whether pretreatment CT texture features can improve patient risk stratification beyond conventional prognostic factors (CPFs) in stage III non-small cell lung cancer (NSCLC). Methods and Materials: We retrospectively reviewed 91 cases with stage III NSCLC treated with definitive chemoradiation therapy. All patients underwent pretreatment diagnostic contrast enhanced computed tomography (CE-CT) followed by 4-dimensional CT (4D-CT) for treatment simulation. We used the average-CT and expiratory (T50-CT) images from the 4D-CT along with the CE-CT for texture extraction. Histogram, gradient, co-occurrence, gray tone difference, and filtration-based techniques were used for texture feature extraction. Penalized Cox regression implementing cross-validation wasmore » used for covariate selection and modeling. Models incorporating texture features from the 33 image types and CPFs were compared to those with models incorporating CPFs alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Patients were stratified based on whether their predicted outcome was above or below the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients and quantified using concordance correlation coefficients (CCC). We compared models incorporating the reproducibility seen on test-retest scans to our original models and determined the classification reproducibility. Results: Models incorporating both texture features and CPFs demonstrated a significant improvement in risk stratification compared to models using CPFs alone for OS (P=.046), LRC (P=.01), and FFDM (P=.005). The average CCCs were 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility within our models yielded 80.4% (±3.7% SD), 78.3% (±4.0% SD), and 78.8% (±3.9% SD) classification reproducibility in terms of OS, LRC, and FFDM, respectively. Conclusions: Pretreatment tumor texture may provide prognostic information beyond that obtained from CPFs. Models incorporating feature reproducibility achieved classification rates of ∼80%. External validation would be required to establish texture as a prognostic factor.« less
A unified material decomposition framework for quantitative dual- and triple-energy CT imaging.
Zhao, Wei; Vernekohl, Don; Han, Fei; Han, Bin; Peng, Hao; Yang, Yong; Xing, Lei; Min, James K
2018-04-21
Many clinical applications depend critically on the accurate differentiation and classification of different types of materials in patient anatomy. This work introduces a unified framework for accurate nonlinear material decomposition and applies it, for the first time, in the concept of triple-energy CT (TECT) for enhanced material differentiation and classification as well as dual-energy CT (DECT). We express polychromatic projection into a linear combination of line integrals of material-selective images. The material decomposition is then turned into a problem of minimizing the least-squares difference between measured and estimated CT projections. The optimization problem is solved iteratively by updating the line integrals. The proposed technique is evaluated by using several numerical phantom measurements under different scanning protocols. The triple-energy data acquisition is implemented at the scales of micro-CT and clinical CT imaging with commercial "TwinBeam" dual-source DECT configuration and a fast kV switching DECT configuration. Material decomposition and quantitative comparison with a photon counting detector and with the presence of a bow-tie filter are also performed. The proposed method provides quantitative material- and energy-selective images examining realistic configurations for both DECT and TECT measurements. Compared to the polychromatic kV CT images, virtual monochromatic images show superior image quality. For the mouse phantom, quantitative measurements show that the differences between gadodiamide and iodine concentrations obtained using TECT and idealized photon counting CT (PCCT) are smaller than 8 and 1 mg/mL, respectively. TECT outperforms DECT for multicontrast CT imaging and is robust with respect to spectrum estimation. For the thorax phantom, the differences between the concentrations of the contrast map and the corresponding true reference values are smaller than 7 mg/mL for all of the realistic configurations. A unified framework for both DECT and TECT imaging has been established for the accurate extraction of material compositions using currently available commercial DECT configurations. The novel technique is promising to provide an urgently needed solution for several CT-based diagnostic and therapy applications, especially for the diagnosis of cardiovascular and abdominal diseases where multicontrast imaging is involved. © 2018 American Association of Physicists in Medicine.
Energy-Discriminative Performance of a Spectral Micro-CT System
He, Peng; Yu, Hengyong; Bennett, James; Ronaldson, Paul; Zainon, Rafidah; Butler, Anthony; Butler, Phil; Wei, Biao; Wang, Ge
2013-01-01
Experiments were performed to evaluate the energy-discriminative performance of a spectral (multi-energy) micro-CT system. The system, designed by MARS (Medipix All Resolution System) Bio-Imaging Ltd. (Christchurch, New Zealand), employs a photon-counting energy-discriminative detector technology developed by CERN (European Organization for Nuclear Research). We used the K-edge attenuation characteristic of some known materials to calibrate the detector’s photon energy discrimination. For tomographic analysis, we used the compressed sensing (CS) based ordered-subset simultaneous algebraic reconstruction techniques (OS-SART) to reconstruct sample images, which is effective to reduce noise and suppress artifacts. Unlike conventional CT, the principal component analysis (PCA) method can be applied to extract and quantify additional attenuation information from a spectral CT dataset. Our results show that the spectral CT has a good energy-discriminative performance and provides more attenuation information than the conventional CT. PMID:24004864
NASA Astrophysics Data System (ADS)
Koga, Kusuto; Hayashi, Yuichiro; Hirose, Tomoaki; Oda, Masahiro; Kitasaka, Takayuki; Igami, Tsuyoshi; Nagino, Masato; Mori, Kensaku
2014-03-01
In this paper, we propose an automated biliary tract extraction method from abdominal CT volumes. The biliary tract is the path by which bile is transported from liver to the duodenum. No extraction method have been reported for the automated extraction of the biliary tract from common contrast CT volumes. Our method consists of three steps including: (1) extraction of extrahepatic bile duct (EHBD) candidate regions, (2) extraction of intrahepatic bile duct (IHBD) candidate regions, and (3) combination of these candidate regions. The IHBD has linear structures and intensities of the IHBD are low in CT volumes. We use a dark linear structure enhancement (DLSE) filter based on a local intensity structure analysis method using the eigenvalues of the Hessian matrix for the IHBD candidate region extraction. The EHBD region is extracted using a thresholding process and a connected component analysis. In the combination process, we connect the IHBD candidate regions to each EHBD candidate region and select a bile duct region from the connected candidate regions. We applied the proposed method to 22 cases of CT volumes. An average Dice coefficient of extraction result was 66.7%.
NASA Astrophysics Data System (ADS)
Xu, Xiaofei; Xing, Yuxiang; Wang, Sen; Zhang, Li
2018-06-01
X-ray liquid security inspection system plays an important role in homeland security, while the conventional dual-energy CT (DECT) system may have a big deviation in extracting the atomic number and the electron density of materials in various conditions. Photon counting detectors (PCDs) have the capability of discriminating the incident photons of different energy. The technique becomes more and more mature in nowadays. In this work, we explore the performance of a multi-energy CT imaging system with a PCD for liquid security inspection in material discrimination. We used a maximum-likelihood (ML) decomposition method with scatter correction based on a cross-energy response model (CERM) for PCDs so that to improve the accuracy of atomic number and electronic density imaging. Experimental study was carried to examine the effectiveness and robustness of the proposed system. Our results show that the concentration of different solutions in physical phantoms can be reconstructed accurately, which could improve the material identification compared to current available dual-energy liquid security inspection systems. The CERM-base decomposition and reconstruction method can be easily used to different applications such as medical diagnosis.
Tensor-based Dictionary Learning for Spectral CT Reconstruction
Zhang, Yanbo; Wang, Ge
2016-01-01
Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628
X-ray phase contrast tomography by tracking near field speckle
Wang, Hongchang; Berujon, Sebastien; Herzen, Julia; Atwood, Robert; Laundy, David; Hipp, Alexander; Sawhney, Kawal
2015-01-01
X-ray imaging techniques that capture variations in the x-ray phase can yield higher contrast images with lower x-ray dose than is possible with conventional absorption radiography. However, the extraction of phase information is often more difficult than the extraction of absorption information and requires a more sophisticated experimental arrangement. We here report a method for three-dimensional (3D) X-ray phase contrast computed tomography (CT) which gives quantitative volumetric information on the real part of the refractive index. The method is based on the recently developed X-ray speckle tracking technique in which the displacement of near field speckle is tracked using a digital image correlation algorithm. In addition to differential phase contrast projection images, the method allows the dark-field images to be simultaneously extracted. After reconstruction, compared to conventional absorption CT images, the 3D phase CT images show greatly enhanced contrast. This new imaging method has advantages compared to other X-ray imaging methods in simplicity of experimental arrangement, speed of measurement and relative insensitivity to beam movements. These features make the technique an attractive candidate for material imaging such as in-vivo imaging of biological systems containing soft tissue. PMID:25735237
Extraction and classification of 3D objects from volumetric CT data
NASA Astrophysics Data System (ADS)
Song, Samuel M.; Kwon, Junghyun; Ely, Austin; Enyeart, John; Johnson, Chad; Lee, Jongkyu; Kim, Namho; Boyd, Douglas P.
2016-05-01
We propose an Automatic Threat Detection (ATD) algorithm for Explosive Detection System (EDS) using our multistage Segmentation Carving (SC) followed by Support Vector Machine (SVM) classifier. The multi-stage Segmentation and Carving (SC) step extracts all suspect 3-D objects. The feature vector is then constructed for all extracted objects and the feature vector is classified by the Support Vector Machine (SVM) previously learned using a set of ground truth threat and benign objects. The learned SVM classifier has shown to be effective in classification of different types of threat materials. The proposed ATD algorithm robustly deals with CT data that are prone to artifacts due to scatter, beam hardening as well as other systematic idiosyncrasies of the CT data. Furthermore, the proposed ATD algorithm is amenable for including newly emerging threat materials as well as for accommodating data from newly developing sensor technologies. Efficacy of the proposed ATD algorithm with the SVM classifier is demonstrated by the Receiver Operating Characteristics (ROC) curve that relates Probability of Detection (PD) as a function of Probability of False Alarm (PFA). The tests performed using CT data of passenger bags shows excellent performance characteristics.
In-line phase contrast micro-CT reconstruction for biomedical specimens.
Fu, Jian; Tan, Renbo
2014-01-01
X-ray phase contrast micro computed tomography (micro-CT) can non-destructively provide the internal structure information of soft tissues and low atomic number materials. It has become an invaluable analysis tool for biomedical specimens. Here an in-line phase contrast micro-CT reconstruction technique is reported, which consists of a projection extraction method and the conventional filter back-projection (FBP) reconstruction algorithm. The projection extraction is implemented by applying the Fourier transform to the forward projections of in-line phase contrast micro-CT. This work comprises a numerical study of the method and its experimental verification using a biomedical specimen dataset measured at an X-ray tube source micro-CT setup. The numerical and experimental results demonstrate that the presented technique can improve the imaging contrast of biomedical specimens. It will be of interest for a wide range of in-line phase contrast micro-CT applications in medicine and biology.
Extraction of CT dose information from DICOM metadata: automated Matlab-based approach.
Dave, Jaydev K; Gingold, Eric L
2013-01-01
The purpose of this study was to extract exposure parameters and dose-relevant indexes of CT examinations from information embedded in DICOM metadata. DICOM dose report files were identified and retrieved from a PACS. An automated software program was used to extract from these files information from the structured elements in the DICOM metadata relevant to exposure. Extracting information from DICOM metadata eliminated potential errors inherent in techniques based on optical character recognition, yielding 100% accuracy.
The segmentation of bones in pelvic CT images based on extraction of key frames.
Yu, Hui; Wang, Haijun; Shi, Yao; Xu, Ke; Yu, Xuyao; Cao, Yuzhen
2018-05-22
Bone segmentation is important in computed tomography (CT) imaging of the pelvis, which assists physicians in the early diagnosis of pelvic injury, in planning operations, and in evaluating the effects of surgical treatment. This study developed a new algorithm for the accurate, fast, and efficient segmentation of the pelvis. The proposed method consists of two main parts: the extraction of key frames and the segmentation of pelvic CT images. Key frames were extracted based on pixel difference, mutual information and normalized correlation coefficient. In the pelvis segmentation phase, skeleton extraction from CT images and a marker-based watershed algorithm were combined to segment the pelvis. To meet the requirements of clinical application, physician's judgment is needed. Therefore the proposed methodology is semi-automated. In this paper, 5 sets of CT data were used to test the overlapping area, and 15 CT images were used to determine the average deviation distance. The average overlapping area of the 5 sets was greater than 94%, and the minimum average deviation distance was approximately 0.58 pixels. In addition, the key frame extraction efficiency and the running time of the proposed method were evaluated on 20 sets of CT data. For each set, approximately 13% of the images were selected as key frames, and the average processing time was approximately 2 min (the time for manual marking was not included). The proposed method is able to achieve accurate, fast, and efficient segmentation of pelvic CT image sequences. Segmentation results not only provide an important reference for early diagnosis and decisions regarding surgical procedures, they also offer more accurate data for medical image registration, recognition and 3D reconstruction.
X-ray physico-chemical imaging during activation of cobalt-based Fischer-Tropsch synthesis catalysts
NASA Astrophysics Data System (ADS)
Beale, Andrew M.; Jacques, Simon D. M.; Di Michiel, Marco; Mosselmans, J. Frederick W.; Price, Stephen W. T.; Senecal, Pierre; Vamvakeros, Antonios; Paterson, James
2017-11-01
The imaging of catalysts and other functional materials under reaction conditions has advanced significantly in recent years. The combination of the computed tomography (CT) approach with methods such as X-ray diffraction (XRD), X-ray fluorescence (XRF) and X-ray absorption near-edge spectroscopy (XANES) now enables local chemical and physical state information to be extracted from within the interiors of intact materials which are, by accident or design, inhomogeneous. In this work, we follow the phase evolution during the initial reduction step(s) to form Co metal, for Co-containing particles employed as Fischer-Tropsch synthesis (FTS) catalysts; firstly, working at small length scales (approx. micrometre spatial resolution), a combination of sample size and density allows for transmission of comparatively low energy signals enabling the recording of `multimodal' tomography, i.e. simultaneous XRF-CT, XANES-CT and XRD-CT. Subsequently, we show high-energy XRD-CT can be employed to reveal extent of reduction and uniformity of crystallite size on millimetre-sized TiO2 trilobes. In both studies, the CoO phase is seen to persist or else evolve under particular operating conditions and we speculate as to why this is observed. This article is part of a discussion meeting issue 'Providing sustainable catalytic solutions for a rapidly changing world'.
NASA Astrophysics Data System (ADS)
Hayashi, Tatsuro; Zhou, Xiangrong; Chen, Huayue; Hara, Takeshi; Miyamoto, Kei; Kobayashi, Tatsunori; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi
2010-03-01
X-ray CT images have been widely used in clinical routine in recent years. CT images scanned by a modern CT scanner can show the details of various organs and tissues. This means various organs and tissues can be simultaneously interpreted on CT images. However, CT image interpretation requires a lot of time and energy. Therefore, support for interpreting CT images based on image-processing techniques is expected. The interpretation of the spinal curvature is important for clinicians because spinal curvature is associated with various spinal disorders. We propose a quantification scheme of the spinal curvature based on the center line of spinal canal on CT images. The proposed scheme consists of four steps: (1) Automated extraction of the skeletal region based on CT number thresholding. (2) Automated extraction of the center line of spinal canal. (3) Generation of the median plane image of spine, which is reformatted based on the spinal canal. (4) Quantification of the spinal curvature. The proposed scheme was applied to 10 cases, and compared with the Cobb angle that is commonly used by clinicians. We found that a high-correlation (for the 95% confidence interval, lumbar lordosis: 0.81-0.99) between values obtained by the proposed (vector) method and Cobb angle. Also, the proposed method can provide the reproducible result (inter- and intra-observer variability: within 2°). These experimental results suggested a possibility that the proposed method was efficient for quantifying the spinal curvature on CT images.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ali, I; Ahmad, S; Alsbou, N
Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embeddedmore » into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract actual length, size and CT-numbers distorted by motion in CBCT imaging. The model provides further information about motion of the target.« less
Montero, Olimpio; Macías-Sánchez, Maria Dolores; Lama, Carmen M; Lubián, Luis M; Mantell, Casimiro; Rodríguez, Miguel; de la Ossa, Enrique M
2005-12-14
Dynamic extraction of carotenoids from a marine strain of Synechococcus sp. (Cyanophyceae) with supercritical CO2 (SC-CO2) was investigated with regard to operation pressure and temperature effects on extraction efficiency. Extraction yield (milligrams of pigment per gram of dry weight) for SC-CO2) was compared with the extraction yield for dimethylformamide (DMF). Carotenoids extracted with SC-CO2 were beta-carotene (Ct), zeaxanthin (Z), beta-cryptoxanthin (Cr), and equinenone; chlorophyll a was poorly extracted, whereas myxoxanthophyll, another major carotenoid, was not extracted under any experimental condition. The highest relative yield, which is defined here as y(r) = [(mg of pigment(SC-CO2)/mg of pigment(DMF))] x 100, was 76.1 +/- 8.6% for Ct, but it rose to 87.0 +/- 3.4% when 15% ethanol was used as cosolvent. The pressure effect on y(r) was found to be significant (p < 0.05) for both Cr and Z, along with total carotenoids, whereas the effect of square T (TT) was significant for only Ct. From empirical correlations, pairwise pressure (bar) and temperature (degrees C), respectively, for optimal extraction were determined to be (358, 50) for Ct, (454, 59) for Cr, and (500, 60) for Z. Cell disruption by sonication or detergent treatment of the biomass did not improve the extraction efficiency. Matrix structure together with material state could explain the low carotenoid extraction yield obtained with SC-CO2 as compared to DMF in Synechococcus sp. However, the process can be applied to selective extraction of different carotenoids.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Epting, William K.; Mansley, Zachary; Menasche, David B.
2017-03-03
The electrodes in solid oxide fuel cells (SOFCs) consist of three phases interconnected in three dimensions. The volume needed to describe quantitatively such microstructures depends on several lengths scales, which are functions of materials properties and fabrication methods. This work focuses on quantifying the volume needed to represent “intermediate frequency” heterogeneities in electrodes of a commercial SOFC using X-ray computed tomography (CT) over two different length scales. Electrode volumes of 150 x 150 x 9 μm 3 were extracted from a synchrotron-based micro-CT data set, with 13 μm 3 voxels. 13.6 x 19.8 x 19.4 μm 3 of the cathodemore » and 26.3 x 24.8 x 15.7 μm 3 of the anode were extracted from laboratory nano-CT data sets, both with 65 3 nm 3 voxels. After comparing the variation across sub-regions for the greyscale values from the micro-CT, and for the phase fractions and triple phase boundary densities from the nano-CT, it was found that the sub-region length scales needed to yield statistically similar average values were an order of magnitude larger than those expected to capture the “high frequency” heterogeneity related to the discrete nature of the three phases in electrodes. In conclusion, the challenge of quantifying such electrodes using available experimental methods is discussed.« less
Parametric boundary reconstruction algorithm for industrial CT metrology application.
Yin, Zhye; Khare, Kedar; De Man, Bruno
2009-01-01
High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object. In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly incorporated as prior knowledge to improve the convergence of an iterative approach. In this paper, the feasibility of parametric boundary reconstruction algorithm is demonstrated with both simple and complex simulated objects. Finally, the proposed algorithm is applied to the experimental industrial CT system data.
Template-based automatic extraction of the joint space of foot bones from CT scan
NASA Astrophysics Data System (ADS)
Park, Eunbi; Kim, Taeho; Park, Jinah
2016-03-01
Clean bone segmentation is critical in studying the joint anatomy for measuring the spacing between the bones. However, separation of the coupled bones in CT images is sometimes difficult due to ambiguous gray values coming from the noise and the heterogeneity of bone materials as well as narrowing of the joint space. For fine reconstruction of the individual local boundaries, manual operation is a common practice where the segmentation remains to be a bottleneck. In this paper, we present an automatic method for extracting the joint space by applying graph cut on Markov random field model to the region of interest (ROI) which is identified by a template of 3D bone structures. The template includes encoded articular surface which identifies the tight region of the high-intensity bone boundaries together with the fuzzy joint area of interest. The localized shape information from the template model within the ROI effectively separates the bones nearby. By narrowing the ROI down to the region including two types of tissue, the object extraction problem was reduced to binary segmentation and solved via graph cut. Based on the shape of a joint space marked by the template, the hard constraint was set by the initial seeds which were automatically generated from thresholding and morphological operations. The performance and the robustness of the proposed method are evaluated on 12 volumes of ankle CT data, where each volume includes a set of 4 tarsal bones (calcaneus, talus, navicular and cuboid).
NASA Astrophysics Data System (ADS)
Kitagawa, Teruhiko; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Kanematsu, Masayuki; Hoshi, Hiroaki
2008-03-01
In order to support the diagnosis of hepatic diseases, understanding the anatomical structures of hepatic lobes and hepatic vessels is necessary. Although viewing and understanding the hepatic vessels in contrast media-enhanced CT images is easy, the observation of the hepatic vessels in non-contrast X-ray CT images that are widely used for the screening purpose is difficult. We are developing a computer-aided diagnosis (CAD) system to support the liver diagnosis based on non-contrast X-ray CT images. This paper proposes a new approach to segment the middle hepatic vein (MHV), a key structure (landmark) for separating the liver region into left and right lobes. Extraction and classification of hepatic vessels are difficult in non-contrast X-ray CT images because the contrast between hepatic vessels and other liver tissues is low. Our approach uses an atlas-driven method by the following three stages. (1) Construction of liver atlases of left and right hepatic lobes using a learning datasets. (2) Fully-automated enhancement and extraction of hepatic vessels in liver regions. (3) Extraction of MHV based on the results of (1) and (2). The proposed approach was applied to 22 normal liver cases of non-contrast X-ray CT images. The preliminary results show that the proposed approach achieves the success in 14 cases for MHV extraction.
Mori, Kensaku; Ota, Shunsuke; Deguchi, Daisuke; Kitasaka, Takayuki; Suenaga, Yasuhito; Iwano, Shingo; Hasegawa, Yosihnori; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi
2009-01-01
This paper presents a method for the automated anatomical labeling of bronchial branches extracted from 3D CT images based on machine learning and combination optimization. We also show applications of anatomical labeling on a bronchoscopy guidance system. This paper performs automated labeling by using machine learning and combination optimization. The actual procedure consists of four steps: (a) extraction of tree structures of the bronchus regions extracted from CT images, (b) construction of AdaBoost classifiers, (c) computation of candidate names for all branches by using the classifiers, (d) selection of best combination of anatomical names. We applied the proposed method to 90 cases of 3D CT datasets. The experimental results showed that the proposed method can assign correct anatomical names to 86.9% of the bronchial branches up to the sub-segmental lobe branches. Also, we overlaid the anatomical names of bronchial branches on real bronchoscopic views to guide real bronchoscopy.
NASA Astrophysics Data System (ADS)
Ishimori, Hiroyuki; Kawata, Yoshiki; Niki, Noboru; Nakaya, Yoshihiro; Ohmatsu, Hironobu; Matsui, Eisuke; Fujii, Masashi; Moriyama, Noriyuki
2007-03-01
We have developed a Micro CT system for understanding lung function at a high resolution of the micrometer order (up to 5µm in spatial resolution). Micro CT system enables the removal specimen of lungs to be observed at micro level, has expected a big contribution for micro internal organs morphology and the image diagnosis study. In this research, we develop system to visualize lung microstructures in three dimensions from micro CT images and analyze them. They characterize in that high CT value of the noise area is, and the difficulty of only using threshold processing to extract the alveolar wall of micro CT images. Thus, we are developing a method of extracting the alveolar wall with surface thinning algorithm. In this report, we propose the method which reduces the excessive degeneracy of figure which caused by surface thinning process. And, we apply this algorithm to the micro CT image of the actual pulmonary specimen. It is shown that the extraction of the alveolus wall becomes possible in the high precision.
Non-medical Uses of Computed Tomography (CT) and Nuclear Magnetic Resonance
Finding Aids dropdown arrow Site Map A-Z Index Menu Synopsis Non-medical Uses of Computed Tomography (CT materials characterizations, and to provide non-destructive evaluations for discovering flaws in parts presence and facilitate the recovery/extraction of oil, water, coal, and/or gas; and to provide non
Warden, Graham I.; Farkas, Cameron E.; Ikuta, Ichiro; Prevedello, Luciano M.; Andriole, Katherine P.; Khorasani, Ramin
2012-01-01
Purpose: To develop and validate an informatics toolkit that extracts anatomy-specific computed tomography (CT) radiation exposure metrics (volume CT dose index and dose-length product) from existing digital image archives through optical character recognition of CT dose report screen captures (dose screens) combined with Digital Imaging and Communications in Medicine attributes. Materials and Methods: This institutional review board–approved HIPAA-compliant study was performed in a large urban health care delivery network. Data were drawn from a random sample of CT encounters that occurred between 2000 and 2010; images from these encounters were contained within the enterprise image archive, which encompassed images obtained at an adult academic tertiary referral hospital and its affiliated sites, including a cancer center, a community hospital, and outpatient imaging centers, as well as images imported from other facilities. Software was validated by using 150 randomly selected encounters for each major CT scanner manufacturer, with outcome measures of dose screen retrieval rate (proportion of correctly located dose screens) and anatomic assignment precision (proportion of extracted exposure data with correctly assigned anatomic region, such as head, chest, or abdomen and pelvis). The 95% binomial confidence intervals (CIs) were calculated for discrete proportions, and CIs were derived from the standard error of the mean for continuous variables. After validation, the informatics toolkit was used to populate an exposure repository from a cohort of 54 549 CT encounters; of which 29 948 had available dose screens. Results: Validation yielded a dose screen retrieval rate of 99% (597 of 605 CT encounters; 95% CI: 98%, 100%) and an anatomic assignment precision of 94% (summed DLP fraction correct 563 in 600 CT encounters; 95% CI: 92%, 96%). Patient safety applications of the resulting data repository include benchmarking between institutions, CT protocol quality control and optimization, and cumulative patient- and anatomy-specific radiation exposure monitoring. Conclusion: Large-scale anatomy-specific radiation exposure data repositories can be created with high fidelity from existing digital image archives by using open-source informatics tools. ©RSNA, 2012 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12111822/-/DC1 PMID:22668563
TU-F-18A-06: Dual Energy CT Using One Full Scan and a Second Scan with Very Few Projections
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, T; Zhu, L
Purpose: The conventional dual energy CT (DECT) requires two full CT scans at different energy levels, resulting in dose increase as well as imaging errors from patient motion between the two scans. To shorten the scan time of DECT and thus overcome these drawbacks, we propose a new DECT algorithm using one full scan and a second scan with very few projections by preserving structural information. Methods: We first reconstruct a CT image on the full scan using a standard filtered-backprojection (FBP) algorithm. We then use a compressed sensing (CS) based iterative algorithm on the second scan for reconstruction frommore » very few projections. The edges extracted from the first scan are used as weights in the Objectives: function of the CS-based reconstruction to substantially improve the image quality of CT reconstruction. The basis material images are then obtained by an iterative image-domain decomposition method and an electron density map is finally calculated. The proposed method is evaluated on phantoms. Results: On the Catphan 600 phantom, the CT reconstruction mean error using the proposed method on 20 and 5 projections are 4.76% and 5.02%, respectively. Compared with conventional iterative reconstruction, the proposed edge weighting preserves object structures and achieves a better spatial resolution. With basis materials of Iodine and Teflon, our method on 20 projections obtains similar quality of decomposed material images compared with FBP on a full scan and the mean error of electron density in the selected regions of interest is 0.29%. Conclusion: We propose an effective method for reducing projections and therefore scan time in DECT. We show that a full scan plus a 20-projection scan are sufficient to provide DECT images and electron density with similar quality compared with two full scans. Our future work includes more phantom studies to validate the performance of our method.« less
Investigation of Carbon Fiber Architecture in Braided Composites Using X-Ray CT Inspection
NASA Technical Reports Server (NTRS)
Rhoads, Daniel J.; Miller, Sandi G.; Roberts, Gary D.; Rauser, Richard W.; Golovaty, Dmitry; Wilber, J. Patrick; Espanol, Malena I.
2017-01-01
During the fabrication of braided carbon fiber composite materials, process variations occur which affect the fiber architecture. Quantitative measurements of local and global fiber architecture variations are needed to determine the potential effect of process variations on mechanical properties of the cured composite. Although non-destructive inspection via X-ray CT imaging is a promising approach, difficulties in quantitative analysis of the data arise due to the similar densities of the material constituents. In an effort to gain more quantitative information about features related to fiber architecture, methods have been explored to improve the details that can be captured by X-ray CT imaging. Metal-coated fibers and thin veils are used as inserts to extract detailed information about fiber orientations and inter-ply behavior from X-ray CT images.
Component extraction on CT volumes of assembled products using geometric template matching
NASA Astrophysics Data System (ADS)
Muramatsu, Katsutoshi; Ohtake, Yutaka; Suzuki, Hiromasa; Nagai, Yukie
2017-03-01
As a method of non-destructive internal inspection, X-ray computed tomography (CT) is used not only in medical applications but also for product inspection. Some assembled products can be divided into separate components based on density, which is known to be approximately proportional to CT values. However, components whose densities are similar cannot be distinguished using the CT value driven approach. In this study, we proposed a new component extraction algorithm from the CT volume, using a set of voxels with an assigned CT value with the surface mesh as the template rather than the density. The method has two main stages: rough matching and fine matching. At the rough matching stage, the position of candidate targets is identified roughly from the CT volume, using the template of the target component. At the fine matching stage, these candidates are precisely matched with the templates, allowing the correct position of the components to be detected from the CT volume. The results of two computational experiments showed that the proposed algorithm is able to extract components with similar density within the assembled products on CT volumes.
Quantitative Probes of Electron-Phonon Coupling in an Organic Charge-Transfer Material
NASA Astrophysics Data System (ADS)
Rury, Aaron; Sorenson, Shayne; Driscoll, Eric; Dawlaty, Jahan
While organic charge transfer (CT) materials may provide alternatives to inorganic materials in electronics and photonics applications, properties central to applications remain understudied in these organic materials. Specifically, electron-phonon coupling plays a pivotal role in electronic applications yet this coupling in CT materials remains difficult to directly characterize. To better understand the suitability of organic CT materials for electronic applications, we have devised an experimental technique that can directly assess electron-phonon coupling in a model organic CT material. Upon non-resonant interaction with an ultrafast laser pulse, we show that coherent excitation of Raman-active lattice vibrations of quinhydrone, a 1:1 co-crystal of the hydroquinone and p-benzoquinone, modulates the energies of electronic transitions probed by a white light pulse. Using a well-established theoretical framework of vibrational quantum beat spectra across the probe bandwidth, we quantitatively extract the parameters describing these electronic transitions to characterize electron-phonon coupling in this material. In conjunction with temperature-dependent resonance Raman measurements, we assess the hypothesis that several sharp transitions in the near-IR correspond to previously unknown excitonic states of this material. These results and their interpretation set the foundation for further elucidation of the one of the most important parameters in the application of organic charge-transfer materials to electronics and photonics.
Newell, John D; Fuld, Matthew K; Allmendinger, Thomas; Sieren, Jered P; Chan, Kung-Sik; Guo, Junfeng; Hoffman, Eric A
2015-01-01
The purpose of this study was to evaluate the impact of ultralow radiation dose single-energy computed tomographic (CT) acquisitions with Sn prefiltration and third-generation iterative reconstruction on density-based quantitative measures of growing interest in phenotyping pulmonary disease. The effects of both decreasing dose and different body habitus on the accuracy of the mean CT attenuation measurements and the level of image noise (SD) were evaluated using the COPDGene 2 test object, containing 8 different materials of interest ranging from air to acrylic and including various density foams. A third-generation dual-source multidetector CT scanner (Siemens SOMATOM FORCE; Siemens Healthcare AG, Erlangen, Germany) running advanced modeled iterative reconstruction (ADMIRE) software (Siemens Healthcare AG) was used.We used normal and very large body habitus rings at dose levels varying from 1.5 to 0.15 mGy using a spectral-shaped (0.6-mm Sn) tube output of 100 kV(p). Three CT scans were obtained at each dose level using both rings. Regions of interest for each material in the test object scans were automatically extracted. The Hounsfield unit values of each material using weighted filtered back projection (WFBP) at 1.5 mGy was used as the reference value to evaluate shifts in CT attenuation at lower dose levels using either WFBP or ADMIRE. Statistical analysis included basic statistics, Welch t tests, multivariable covariant model using the F test to assess the significance of the explanatory (independent) variables on the response (dependent) variable, and CT mean attenuation, in the multivariable covariant model including reconstruction method. Multivariable regression analysis of the mean CT attenuation values showed a significant difference with decreasing dose between ADMIRE and WFBP. The ADMIRE has reduced noise and more stable CT attenuation compared with WFBP. There was a strong effect on the mean CT attenuation values of the scanned materials for ring size (P < 0.0001) and dose level (P < 0.0001). The number of voxels in the region of interest for the particular material studied did not demonstrate a significant effect (P > 0.05). The SD was lower with ADMIRE compared with WFBP at all dose levels and ring sizes (P < 0.05). The third-generation dual-source CT scanners using third-generation iterative reconstruction methods can acquire accurate quantitative CT images with acceptable image noise at very low-dose levels (0.15 mGy). This opens up new diagnostic and research opportunities in CT phenotyping of the lung for developing new treatments and increased understanding of pulmonary disease.
Dall'Agnol, Cristina; Hartmann, Mateus Silveira Martins; Barletta, Fernando Branco
2008-01-01
This study evaluated the efficiency of different techniques for removal of filling material from root canals, using computed tomography (CT). Sixty mesial roots from extracted human mandibular molars were used. Root canals were filled and, after 6 months, the teeth were randomly assigned to 3 groups, according to the root-filling removal technique: Group A - hand instrumentation with K-type files; Group B - reciprocating instrumentation with engine-driven K-type files; and Group C rotary instrumentation with engine-driven ProTaper system. CT scans were used to assess the volume of filling material inside the root canals before and after the removal procedure. In both moments, the area of filling material was outlined by an experienced radiologist and the volume of filling material was automatically calculated by the CT software program. Based on the volume of initial and residual filling material of each specimen, the percentage of filling material removed from the root canals by the different techniques was calculated. Data were analyzed statistically by ANOVA and chi-square test for linear trend (?=0.05). No statistically significant difference (p=0.36) was found among the groups regarding the percent means of removed filling material. The analysis of the association between the percentage of filling material removal (high or low) and the proposed techniques by chi-square test showed statistically significant difference (p=0.015), as most cases in group B (reciprocating technique) presented less than 50% of filling material removed (low percent removal). In conclusion, none of the techniques evaluated in this study was effective in providing complete removal of filling material from the root canals.
A Hybrid Method for Pancreas Extraction from CT Image Based on Level Set Methods
Tan, Hanqing; Fujita, Hiroshi
2013-01-01
This paper proposes a novel semiautomatic method to extract the pancreas from abdominal CT images. Traditional level set and region growing methods that request locating initial contour near the final boundary of object have problem of leakage to nearby tissues of pancreas region. The proposed method consists of a customized fast-marching level set method which generates an optimal initial pancreas region to solve the problem that the level set method is sensitive to the initial contour location and a modified distance regularized level set method which extracts accurate pancreas. The novelty in our method is the proper selection and combination of level set methods, furthermore an energy-decrement algorithm and an energy-tune algorithm are proposed to reduce the negative impact of bonding force caused by connected tissue whose intensity is similar with pancreas. As a result, our method overcomes the shortages of oversegmentation at weak boundary and can accurately extract pancreas from CT images. The proposed method is compared to other five state-of-the-art medical image segmentation methods based on a CT image dataset which contains abdominal images from 10 patients. The evaluated results demonstrate that our method outperforms other methods by achieving higher accuracy and making less false segmentation in pancreas extraction. PMID:24066016
2014-01-01
Background Contrast-induced acute kidney injury is a common cause of iatrogenic acute kidney injury (AKI). Most of the published estimates of AKI after contrast use originate from the cardiac catheterization literature despite contrast-enhanced computed tomography (CT) scans being the more common setting for contrast use. This systematic review aims to summarize the current evidence about (1)the risk of AKI following intravenous (IV) contrast-enhanced CT scans and(2) the risk of clinical outcomes (i.e. death, hospitalization and need for renal replacement therapy) due to IV contrast-enhanced CT scans. Methods/Design A systematic literature search for published studies will be performed using MEDLINE, EMBASE and The COCHRANE Library databases. Unpublished studies will be identified by searching through grey literature. No language restriction will be applied. The review will consider all studies that have examined the association between IV contrast media and AKI. To be selected, the study should include two arms: one group of exposed patients who received IV contrast material before CT scans and one group of unexposed group who did not receive contrast material before CT scans. Two authors will independently screen titles and abstracts obtained from electronic databases, extract data and will assess the quality of the studies selected using the Cochrane's ‘Risk of Bias’ assessment tool for randomized trials and the Newcastle-Ottawa Scale for observational studies. A random-effects meta-analysis will be performed if there is no remarkable heterogeneity between studies. Discussion This systematic review will provide synthesis of current evidence around the effect of IV contrast material on AKI and other clinical outcomes. Results will be helpful for making evidence-based recommendations and guidelines for clinical and radiologic settings. Systematic review registration PROSPERO CRD42013003799. PMID:25148933
Engineered phage-based therapeutic materials inhibit Chlamydia trachomatis intracellular infection
Bhattarai, Shanta Raj; Yoo, So Young; Lee, Seung-Wuk; Dean, Deborah
2012-01-01
Developing materials that are effective against sexually transmitted pathogens such as Chlamydia trachomatis (Ct) and HIV-1 is challenging both in terms of material selection and improving bio-membrane and cellular permeability at desired mucosal sites. Here, we engineered the prokaryotic bacterial virus (M13 phage) carrying two functional peptides, integrin binding peptide (RGD) and a segment of the polymorphic membrane protein D (PmpD) from Ct, as a phage-based material that can ameliorate Ct infection. Ct is a globally prevalent human pathogen for which there are no effective vaccines or microbicides. We show that engineered phage stably express both RGD motifs and Ct peptides and traffic intracellularly and into the lumen of the inclusion in which the organism resides within the host cell. Engineered phage were able to significantly reduce Ct infection in both HeLa and primary endocervical cells compared with Ct infection alone. Polyclonal antibodies raised against PmpD and co-incubated with constructs prior to infection did not alter the course of infection, indicating that PmpD is responsible for the observed decrease in Ct infection. Our results suggest that phage-based design approaches to vector delivery that overcome mucosal cellular barriers may be effective in preventing Ct and other sexually transmitted pathogens. PMID:22494890
Stress and strain distribution in demineralized enamel: A micro-CT based finite element study.
Neves, Aline Almeida; Coutinho, Eduardo; Alves, Haimon Diniz Lopes; de Assis, Joaquim Teixeira
2015-10-01
Physiological oral mechanical forces may play a role on the progression of enamel carious lesions to cavitation. Thus, the aim of this study was to describe, by 3D finite element analysis, stress, and strain patterns in sound and carious enamel after a simulated occlusal load. Micro-CT based models were created and meshed with tetrahedral elements (based on an extracted third molar), namely: a sound (ST) and a carious tooth (CT). For the CT, enamel material properties were assigned according to the micro-CT gray values. Below the threshold corresponding to the enamel lesion (2.5 g/cm(3) ) lower and isotropic elastic modulus was assigned (E = 18 GPa against E1 = 80 GPa, E2 = E3 = 20 GPa for sound enamel). Both models were imported into a FE solver where boundary conditions were assigned and a pressure load (500 MPa) was applied at the occlusal surface. A linear static analysis was performed, considering anisotropy in sound enamel. ST showed a more efficient transfer of maximum principal stress from enamel to the dentin layer, while for the CT, enamel layer was subjected to higher and concentrated loads. Maximum principal strain distributions were seen at the carious enamel surface, especially at the central fossa, correlating to the enamel cavity seen at the original micro-CT model. It is possible to conclude that demineralized enamel compromises appropriate stress transfer from enamel to dentin, contributing to the odds of fracture and cavitation. Enamel fracture over a dentin lesion may happen as one of the normal pathways to caries progression and may act as a confounding factor during clinical diagnostic decisions. © 2015 Wiley Periodicals, Inc.
Baharara, Javad; Amini, Elaheh; Afzali, Mahbubeh; Nikdel, Najme; Mostafapour, Asma; Kerachian, Mohammad Amin
2016-01-01
Objective(s): Sea cucumber is one of the classes of echinoderms, which is considered as a health marine product and possess various biological characteristics with therapeutic application. The present investigation attempted to evaluate the potential of anti-cancer Persian Gulf sea cucumber species Holothuria arenicola (H. arenicola) aqueous extract on mice colon carcinoma cells in vitro and in vivo. Materials and Methods: The CT26 carcinoma cells were treated with various concentrations of extract in 24 and 48 hr, and then its anti-proliferative effect was measured by MTT assay and morphological observations. The apoptotic effect was examined by fluorescence microscopy (DNA fragmentation assay), Flow cytometry, caspase-3 and -9 colorimetric assays. The in vivo anti-tumor efficacy of sea cucumber extract on CT26 tumor cells transplanted in BALB/c mice was also investigated. Results: The results showed that the water extract of sea cucumber revealed remarkable anti-proliferative effect on CT26 tumor cells with IC50= 31 µg/ml with recruitment of intrinsic apoptotic pathway in vitro. In addition, the colon tumor volume in treated groups remarkably reduced in homozygous mice. Histopathological examination elucidated that sea cucumber extract attenuated tumor size and volume along with apoptosis characteristics. Moreover, RT-PCR analysis revealed that sea cucumber extract induced intrinsic apoptosis in vivo through suppression of Bcl-2 expression. Conclusion: Our data confirmed this notion that sea cucumber administrates anti-cancer effect that can be used as complementary in preclinical experiments, so further characterization are recommended for detection sea cucumber metabolites and clinical application. PMID:27279978
NASA Astrophysics Data System (ADS)
Govindappa, M.; Hemashekhar, B.; Arthikala, Manoj-Kumar; Ravishankar Rai, V.; Ramachandra, Y. L.
2018-06-01
The current research study is to develop an easy and eco-friendly method for the synthesis of AgNPs using aqueous leaf extract of Calophyllum tomentosum (CtAgNPs) and evaluated the extract to know the effects of anti-bacterial, antioxidant, anti-diabetic, anti-inflammatory and anti-tyrosinase activity. Using UV-vis spectrophotometer, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX) characterized the Calophyllum tomentosum mediated silver nanoparticles. The leaf extract of C. tomentosum yielded flavonoids, saponins, tannins, alkaloids, glycosides, phenols, terpenoids and coumarins. AgNPs formation was confirmed by UV-vis spectra at 438 nm. Crystalline structure with a face centered cubic (fcc) of AgNPs was observed in XRD. FTIR had shown that the phytochemicals were responsible for the reduction and capping material of silver nanoparticles. The size and shape of the AgNPs were determined using SEM. From EDX study analysed the strong absorption property of AgNPs. The CtAgNPs have showed significant antibacterial activity on multi drug resistance bacteria. The CtAgNPs had shown strong antioxidant (DPPH, H2O2 scavenging, nitric oxide scavenging power, reducing power) activities. The CtAgNPs had strongly inhibited the α-glucosidase and DPPIV compared to α-amylase. The CtAgNPs exhibited strong anti-inflammatory activity (albumin denaturation, membrane stabilization, heat haemolytic, protein inhibitory, lipoxygenase, xanthine oxidase) and tyrosinase inhibitory activity. To our best knowledge, this is the first attempt on the synthesis of silver nanoparticles using Calophyllum tomentosum leaves extract. Hence, to validate our results the in vivo studies at molecular level are needed to develop an antioxidant, anti-diabetic and anti-inflammatory agent.
Algorithm-enabled partial-angular-scan configurations for dual-energy CT.
Chen, Buxin; Zhang, Zheng; Xia, Dan; Sidky, Emil Y; Pan, Xiaochuan
2018-05-01
We seek to investigate an optimization-based one-step method for image reconstruction that explicitly compensates for nonlinear spectral response (i.e., the beam-hardening effect) in dual-energy CT, to investigate the feasibility of the one-step method for enabling two dual-energy partial-angular-scan configurations, referred to as the short- and half-scan configurations, on standard CT scanners without involving additional hardware, and to investigate the potential of the short- and half-scan configurations in reducing imaging dose and scan time in a single-kVp-switch full-scan configuration in which two full rotations are made for collection of dual-energy data. We use the one-step method to reconstruct images directly from dual-energy data through solving a nonconvex optimization program that specifies the images to be reconstructed in dual-energy CT. Dual-energy full-scan data are generated from numerical phantoms and collected from physical phantoms with the standard single-kVp-switch full-scan configuration, whereas dual-energy short- and half-scan data are extracted from the corresponding full-scan data. Besides visual inspection and profile-plot comparison, the reconstructed images are analyzed also in quantitative studies based upon tasks of linear-attenuation-coefficient and material-concentration estimation and of material differentiation. Following the performance of a computer-simulation study to verify that the one-step method can reconstruct numerically accurately basis and monochromatic images of numerical phantoms, we reconstruct basis and monochromatic images by using the one-step method from real data of physical phantoms collected with the full-, short-, and half-scan configurations. Subjective inspection based upon visualization and profile-plot comparison reveals that monochromatic images, which are used often in practical applications, reconstructed from the full-, short-, and half-scan data are largely visually comparable except for some differences in texture details. Moreover, quantitative studies based upon tasks of linear-attenuation-coefficient and material-concentration estimation and of material differentiation indicate that the short- and half-scan configurations yield results in close agreement with the ground-truth information and that of the full-scan configuration. The one-step method considered can compensate effectively for the nonlinear spectral response in full- and partial-angular-scan dual-energy CT. It can be exploited for enabling partial-angular-scan configurations on standard CT scanner without involving additional hardware. Visual inspection and quantitative studies reveal that, with the one-step method, partial-angular-scan configurations considered can perform at a level comparable to that of the full-scan configuration, thus suggesting the potential of the two partial-angular-scan configurations in reducing imaging dose and scan time in the standard single-kVp-switch full-scan CT in which two full rotations are performed. The work also yields insights into the investigation and design of other nonstandard scan configurations of potential practical significance in dual-energy CT. © 2018 American Association of Physicists in Medicine.
Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan
2010-01-01
Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.
Material Separation Using Dual-Energy CT: Current and Emerging Applications.
Patino, Manuel; Prochowski, Andrea; Agrawal, Mukta D; Simeone, Frank J; Gupta, Rajiv; Hahn, Peter F; Sahani, Dushyant V
2016-01-01
Dual-energy (DE) computed tomography (CT) offers the opportunity to generate material-specific images on the basis of the atomic number Z and the unique mass attenuation coefficient of a particular material at different x-ray energies. Material-specific images provide qualitative and quantitative information about tissue composition and contrast media distribution. The most significant contribution of DE CT-based material characterization comes from the capability to assess iodine distribution through the creation of an image that exclusively shows iodine. These iodine-specific images increase tissue contrast and amplify subtle differences in attenuation between normal and abnormal tissues, improving lesion detection and characterization in the abdomen. In addition, DE CT enables computational removal of iodine influence from a CT image, generating virtual noncontrast images. Several additional materials, including calcium, fat, and uric acid, can be separated, permitting imaging assessment of metabolic imbalances, elemental deficiencies, and abnormal deposition of materials within tissues. The ability to obtain material-specific images from a single, contrast-enhanced CT acquisition can complement the anatomic knowledge with functional information, and may be used to reduce the radiation dose by decreasing the number of phases in a multiphasic CT examination. DE CT also enables generation of energy-specific and virtual monochromatic images. Clinical applications of DE CT leverage both material-specific images and virtual monochromatic images to expand the current role of CT and overcome several limitations of single-energy CT. (©)RSNA, 2016.
A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images
Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu
2017-01-01
The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979
Variability sensitivity of dynamic texture based recognition in clinical CT data
NASA Astrophysics Data System (ADS)
Kwitt, Roland; Razzaque, Sharif; Lowell, Jeffrey; Aylward, Stephen
2014-03-01
Dynamic texture recognition using a database of template models has recently shown promising results for the task of localizing anatomical structures in Ultrasound video. In order to understand its clinical value, it is imperative to study the sensitivity with respect to inter-patient variability as well as sensitivity to acquisition parameters such as Ultrasound probe angle. Fully addressing patient and acquisition variability issues, however, would require a large database of clinical Ultrasound from many patients, acquired in a multitude of controlled conditions, e.g., using a tracked transducer. Since such data is not readily attainable, we advocate an alternative evaluation strategy using abdominal CT data as a surrogate. In this paper, we describe how to replicate Ultrasound variabilities by extracting subvolumes from CT and interpreting the image material as an ordered sequence of video frames. Utilizing this technique, and based on a database of abdominal CT from 45 patients, we report recognition results on an organ (kidney) recognition task, where we try to discriminate kidney subvolumes/videos from a collection of randomly sampled negative instances. We demonstrate that (1) dynamic texture recognition is relatively insensitive to inter-patient variation while (2) viewing angle variability needs to be accounted for in the template database. Since naively extending the template database to counteract variability issues can lead to impractical database sizes, we propose an alternative strategy based on automated identification of a small set of representative models.
Cook, Tessa S; Zimmerman, Stefan L; Steingall, Scott R; Maidment, Andrew D A; Kim, Woojin; Boonn, William W
2011-01-01
There is growing interest in the ability to monitor, track, and report exposure to radiation from medical imaging. Historically, however, dose information has been stored on an image-based dose sheet, an arrangement that precludes widespread indexing. Although scanner manufacturers are beginning to include dose-related parameters in the Digital Imaging and Communications in Medicine (DICOM) headers of imaging studies, there remains a vast repository of retrospective computed tomographic (CT) data with image-based dose sheets. Consequently, it is difficult for imaging centers to monitor their dose estimates or participate in the American College of Radiology (ACR) Dose Index Registry. An automated extraction software pipeline known as Radiation Dose Intelligent Analytics for CT Examinations (RADIANCE) has been designed that quickly and accurately parses CT dose sheets to extract and archive dose-related parameters. Optical character recognition of information in the dose sheet leads to creation of a text file, which along with the DICOM study header is parsed to extract dose-related data. The data are then stored in a relational database that can be queried for dose monitoring and report creation. RADIANCE allows efficient dose analysis of CT examinations and more effective education of technologists, radiologists, and referring physicians regarding patient exposure to radiation at CT. RADIANCE also allows compliance with the ACR's dose reporting guidelines and greater awareness of patient radiation dose, ultimately resulting in improved patient care and treatment.
Multienergy CT acquisition and reconstruction with a stepped tube potential scan
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shen, Le; Xing, Yuxiang, E-mail: xingyx@mail.tsinghua.edu.cn
Purpose: Based on an energy-dependent property of matter, one may obtain a pseudomonochromatic attenuation map, a material composition image, an electron-density distribution, and an atomic number image using a dual- or multienergy computed tomography (CT) scan. Dual- and multienergy CT scans broaden the potential of x-ray CT imaging. The development of such systems is very useful in both medical and industrial investigations. In this paper, the authors propose a new dual- and multienergy CT system design (segmental multienergy CT, SegMECT) using an innovative scanning scheme that is conveniently implemented on a conventional single-energy CT system. The two-step-energy dual-energy CT canmore » be regarded as a special case of SegMECT. A special reconstruction method is proposed to support SegMECT. Methods: In their SegMECT, a circular trajectory in a CT scan is angularly divided into several arcs. The x-ray source is set to a different tube voltage for each arc of the trajectory. Thus, the authors only need to make a few step changes to the x-ray energy during the scan to complete a multienergy data acquisition. With such a data set, the image reconstruction might suffer from severe limited-angle artifacts if using conventional reconstruction methods. To solve the problem, they present a new prior-image-based reconstruction technique using a total variance norm of a quotient image constraint. On the one hand, the prior extracts structural information from all of the projection data. On the other hand, the effect from a possibly imprecise intensity level of the prior can be mitigated by minimizing the total variance of a quotient image. Results: The authors present a new scheme for a SegMECT configuration and establish a reconstruction method for such a system. Both numerical simulation and a practical phantom experiment are conducted to validate the proposed reconstruction method and the effectiveness of the system design. The results demonstrate that the proposed SegMECT can provide both attenuation images and material decomposition images of reasonable image quality. Compared to existing methods, the new system configuration demonstrates advantages in simplicity of implementation, system cost, and dose control. Conclusions: This proposed SegMECT imaging approach has great potential for practical applications. It can be readily realized on a conventional CT system.« less
Zhang, Pin; Liang, Yanmei; Chang, Shengjiang; Fan, Hailun
2013-08-01
Accurate segmentation of renal tissues in abdominal computed tomography (CT) image sequences is an indispensable step for computer-aided diagnosis and pathology detection in clinical applications. In this study, the goal is to develop a radiology tool to extract renal tissues in CT sequences for the management of renal diagnosis and treatments. In this paper, the authors propose a new graph-cuts-based active contours model with an adaptive width of narrow band for kidney extraction in CT image sequences. Based on graph cuts and contextual continuity, the segmentation is carried out slice-by-slice. In the first stage, the middle two adjacent slices in a CT sequence are segmented interactively based on the graph cuts approach. Subsequently, the deformable contour evolves toward the renal boundaries by the proposed model for the kidney extraction of the remaining slices. In this model, the energy function combining boundary with regional information is optimized in the constructed graph and the adaptive search range is determined by contextual continuity and the object size. In addition, in order to reduce the complexity of the min-cut computation, the nodes in the graph only have n-links for fewer edges. The total 30 CT images sequences with normal and pathological renal tissues are used to evaluate the accuracy and effectiveness of our method. The experimental results reveal that the average dice similarity coefficient of these image sequences is from 92.37% to 95.71% and the corresponding standard deviation for each dataset is from 2.18% to 3.87%. In addition, the average automatic segmentation time for one kidney in each slice is about 0.36 s. Integrating the graph-cuts-based active contours model with contextual continuity, the algorithm takes advantages of energy minimization and the characteristics of image sequences. The proposed method achieves effective results for kidney segmentation in CT sequences.
Performance estimation for threat detection in CT systems
NASA Astrophysics Data System (ADS)
Montgomery, Trent; Karl, W. Clem; Castañón, David A.
2017-05-01
Detecting the presence of hazardous materials in suitcases and carry-on luggage is an important problem in aviation security. As the set of threats is expanding, there is a corresponding need to increase the capabilities of explosive detection systems to address these threats. However, there is a lack of principled tools for predicting the performance of alternative designs for detection systems. In this paper, we describe an approach for computing bounds on the achievable classification performance of material discrimination systems based on empirical statistics that estimate the f-divergence of the underlying features. Our approach can be used to examine alternative physical observation modalities and measurement configurations, as well as variations in reconstruction and feature extraction algorithms.
Hepatic CT image query using Gabor features
NASA Astrophysics Data System (ADS)
Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange
2004-07-01
A retrieval scheme for liver computerize tomography (CT) images based on Gabor texture is presented. For each hepatic CT image, we manually delineate abnormal regions within liver area. Then, a continuous Gabor transform is utilized to analyze the texture of the pathology bearing region and extract the corresponding feature vectors. For a given sample image, we compare its feature vector with those of other images. Similar images with the highest rank are retrieved. In experiments, 45 liver CT images are collected, and the effectiveness of Gabor texture for content based retrieval is verified.
Cyst-based measurements for assessing lymphangioleiomyomatosis in computed tomography
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lo, P., E-mail: pechinlo@mednet.edu.ucla; Brown, M. S.; Kim, H.
Purpose: To investigate the efficacy of a new family of measurements made on individual pulmonary cysts extracted from computed tomography (CT) for assessing the severity of lymphangioleiomyomatosis (LAM). Methods: CT images were analyzed using thresholding to identify a cystic region of interest from chest CT of LAM patients. Individual cysts were then extracted from the cystic region by the watershed algorithm, which separates individual cysts based on subtle edges within the cystic regions. A family of measurements were then computed, which quantify the amount, distribution, and boundary appearance of the cysts. Sequential floating feature selection was used to select amore » small subset of features for quantification of the severity of LAM. Adjusted R{sup 2} from multiple linear regression and R{sup 2} from linear regression against measurements from spirometry were used to compare the performance of our proposed measurements with currently used density based CT measurements in the literature, namely, the relative area measure and the D measure. Results: Volumetric CT data, performed at total lung capacity and residual volume, from a total of 49 subjects enrolled in the MILES trial were used in our study. Our proposed measures had adjusted R{sup 2} ranging from 0.42 to 0.59 when regressing against the spirometry measures, with p < 0.05. For previously used density based CT measurements in the literature, the best R{sup 2} was 0.46 (for only one instance), with the majority being lower than 0.3 or p > 0.05. Conclusions: The proposed family of CT-based cyst measurements have better correlation with spirometric measures than previously used density based CT measurements. They show potential as a sensitive tool for quantitatively assessing the severity of LAM.« less
NASA Astrophysics Data System (ADS)
Wu, T. Y.; Lin, S. F.
2013-10-01
Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.
WE-E-18C-01: Multi-Energy CT: Current Status and Recent Innovations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pelc, N; McCollough, C; Yu, L
2014-06-15
Conventional computed tomography (CT) uses a single polychromatic x-ray spectrum and energy integrating detectors, and produces images whose contrast depends on the effective attenuation coefficient of the broad spectrum beam. This can introduce errors from beam hardening and does not produce the optimal contrast-to-noise ratio. In addition, multiple materials can have the same effective attenuation coefficient, causing different materials to be indistinguishable in conventional CT images. If transmission measurements at two or more energies are obtained, even with polychromatic beams, more specific information about the object can be obtained. If the object does not contain materials with k-edges in themore » spectrum, the x-ray attenuation can be well-approximated by a linear combination of two processes (photoelectric absorption and Compton scattering) or, equivalently, two basis materials. For such cases, two spectral measurements suffice, although additional measurements can provide higher precision. If K-edge materials are present, additional spectral measurements can allow these materials to be isolated. Current commercial implementations use varied approaches, including two sources operating a different kVp, one source whose kVp is rapidly switched in a single scan, and a dual layer detector that can provide spectral information in every reading. Processing of the spectral information can be performed in the raw data domain or in the image domain. The process of calculating the amount of the two basis functions implicitly corrects for beam hardening and therefore can lead to improvements in quantitative accuracy. Information can be extracted to provide material specific information beyond that of conventional CT. This additional information has been shown to be important in several clinical applications, and can also lead to more efficient clinical protocols. Recent innovations in x-ray sources, detectors, and systems have made multi-energy CT much more practical and improved its performance. In addition, this is a very active area of research and further improvements are expected through further technological improvements. Learning Objectives: Basic principles of multi-energy CT Current implementations of mutli-energy CT Data and image analysis methods in multi-energy CT Current clinical applications of dual energy CT5. recent innovations and anticipated advances in multi-energy CT.« less
Casey, M B; Pearson, G R; Perkins, J D; Tremaine, W H
2015-09-01
The most prevalent type of equine dental pulpitis due to apical infection is not associated with coronal fractures or periodontal disease. The pathogenesis of this type of pulpitis is not fully understood. Computed tomography (CT) is increasingly used to investigate equine dental disorders. However, gross, tomographic and histopathological changes in equine dental pulpitis have not been compared previously. To compare gross, CT and histological appearances of sectioned mandibular cheek teeth extracted from horses with clinical signs of pulpitis without coronal fractures or periodontal disease. To contribute to understanding the pathogenesis of equine dental pulpitis. Descriptive study using diseased and healthy teeth. Mandibular cheek teeth extracted from horses with clinical signs of pulpitis (cases), and from cadavers with no history of dental disease (controls), were compared using CT in the transverse plane at 1 mm intervals. Teeth were then sectioned transversely, photographed and processed for histopathological examination. Tomographs were compared with corresponding gross and histological sections. Cement, dentine and bone had similar ranges of attenuation (550-2000 Hounsfield Units, HU) in tomographs but could be differentiated from pulp (-400 to 500 HU) and enamel (> 2500 HU). Twelve discrete dental lesions were identified grossly, 10 of which were characterised histologically. Reactive and reparative dentinogenesis and extensive pulpar mineralisation, previously undescribed, were identified. Pulpar oedema, neutrophilic inflammation, cement and enamel defects, and reactive cemental deposition were also observed. The CT and pathological findings corresponded well where there was mineralised tissue deposited, defects in mineralised tissue, or food material in the pulpar area. Pulpar and dentinal necrosis and cement destruction, evident grossly and histologically, did not correspond to CT changes. Computed tomography is useful for identifying deposition and defects of mineralised material but less useful for identifying inflammation and tissue destruction. The equine dentine-pulp complex responds to insult with reactive and reparative changes. © 2014 EVJ Ltd.
Can SNOMED CT be squeezed without losing its shape?
López-García, Pablo; Schulz, Stefan
2016-09-21
In biomedical applications where the size and complexity of SNOMED CT become problematic, using a smaller subset that can act as a reasonable substitute is usually preferred. In a special class of use cases-like ontology-based quality assurance, or when performing scaling experiments for real-time performance-it is essential that modules show a similar shape than SNOMED CT in terms of concept distribution per sub-hierarchy. Exactly how to extract such balanced modules remains unclear, as most previous work on ontology modularization has focused on other problems. In this study, we investigate to what extent extracting balanced modules that preserve the original shape of SNOMED CT is possible, by presenting and evaluating an iterative algorithm. We used a graph-traversal modularization approach based on an input signature. To conform to our definition of a balanced module, we implemented an iterative algorithm that carefully bootstraped and dynamically adjusted the signature at each step. We measured the error for each sub-hierarchy and defined convergence as a residual sum of squares <1. Using 2000 concepts as an initial signature, our algorithm converged after seven iterations and extracted a module 4.7 % the size of SNOMED CT. Seven sub-hierarhies were either over or under-represented within a range of 1-8 %. Our study shows that balanced modules from large terminologies can be extracted using ontology graph-traversal modularization techniques under certain conditions: that the process is repeated a number of times, the input signature is dynamically adjusted in each iteration, and a moderate under/over-representation of some hierarchies is tolerated. In the case of SNOMED CT, our results conclusively show that it can be squeezed to less than 5 % of its size without any sub-hierarchy losing its shape more than 8 %, which is likely sufficient in most use cases.
Niu, Qiang; Chi, Xiaoyi; Leu, Ming C; Ochoa, Jorge
2008-01-01
This paper describes image processing, geometric modeling and data management techniques for the development of a virtual bone surgery system. Image segmentation is used to divide CT scan data into different segments representing various regions of the bone. A region-growing algorithm is used to extract cortical bone and trabecular bone structures systematically and efficiently. Volume modeling is then used to represent the bone geometry based on the CT scan data. Material removal simulation is achieved by continuously performing Boolean subtraction of the surgical tool model from the bone model. A quadtree-based adaptive subdivision technique is developed to handle the large set of data in order to achieve the real-time simulation and visualization required for virtual bone surgery. A Marching Cubes algorithm is used to generate polygonal faces from the volumetric data. Rendering of the generated polygons is performed with the publicly available VTK (Visualization Tool Kit) software. Implementation of the developed techniques consists of developing a virtual bone-drilling software program, which allows the user to manipulate a virtual drill to make holes with the use of a PHANToM device on a bone model derived from real CT scan data.
A New Approach to Automated Labeling of Internal Features of Hardwood Logs Using CT Images
Daniel L. Schmoldt; Pei Li; A. Lynn Abbott
1996-01-01
The feasibility of automatically identifying internal features of hardwood logs using CT imagery has been established previously. Features of primary interest are bark, knots, voids, decay, and clear wood. Our previous approach: filtered original CT images, applied histogram segmentation, grew volumes to extract 3-d regions, and applied a rule base, with Dempster-...
A limited-angle CT reconstruction method based on anisotropic TV minimization.
Chen, Zhiqiang; Jin, Xin; Li, Liang; Wang, Ge
2013-04-07
This paper presents a compressed sensing (CS)-inspired reconstruction method for limited-angle computed tomography (CT). Currently, CS-inspired CT reconstructions are often performed by minimizing the total variation (TV) of a CT image subject to data consistency. A key to obtaining high image quality is to optimize the balance between TV-based smoothing and data fidelity. In the case of the limited-angle CT problem, the strength of data consistency is angularly varying. For example, given a parallel beam of x-rays, information extracted in the Fourier domain is mostly orthogonal to the direction of x-rays, while little is probed otherwise. However, the TV minimization process is isotropic, suggesting that it is unfit for limited-angle CT. Here we introduce an anisotropic TV minimization method to address this challenge. The advantage of our approach is demonstrated in numerical simulation with both phantom and real CT images, relative to the TV-based reconstruction.
ExaCT: automatic extraction of clinical trial characteristics from journal publications
2010-01-01
Background Clinical trials are one of the most important sources of evidence for guiding evidence-based practice and the design of new trials. However, most of this information is available only in free text - e.g., in journal publications - which is labour intensive to process for systematic reviews, meta-analyses, and other evidence synthesis studies. This paper presents an automatic information extraction system, called ExaCT, that assists users with locating and extracting key trial characteristics (e.g., eligibility criteria, sample size, drug dosage, primary outcomes) from full-text journal articles reporting on randomized controlled trials (RCTs). Methods ExaCT consists of two parts: an information extraction (IE) engine that searches the article for text fragments that best describe the trial characteristics, and a web browser-based user interface that allows human reviewers to assess and modify the suggested selections. The IE engine uses a statistical text classifier to locate those sentences that have the highest probability of describing a trial characteristic. Then, the IE engine's second stage applies simple rules to these sentences to extract text fragments containing the target answer. The same approach is used for all 21 trial characteristics selected for this study. Results We evaluated ExaCT using 50 previously unseen articles describing RCTs. The text classifier (first stage) was able to recover 88% of relevant sentences among its top five candidates (top5 recall) with the topmost candidate being relevant in 80% of cases (top1 precision). Precision and recall of the extraction rules (second stage) were 93% and 91%, respectively. Together, the two stages of the extraction engine were able to provide (partially) correct solutions in 992 out of 1050 test tasks (94%), with a majority of these (696) representing fully correct and complete answers. Conclusions Our experiments confirmed the applicability and efficacy of ExaCT. Furthermore, they demonstrated that combining a statistical method with 'weak' extraction rules can identify a variety of study characteristics. The system is flexible and can be extended to handle other characteristics and document types (e.g., study protocols). PMID:20920176
Pseudo CT estimation from MRI using patch-based random forest
NASA Astrophysics Data System (ADS)
Yang, Xiaofeng; Lei, Yang; Shu, Hui-Kuo; Rossi, Peter; Mao, Hui; Shim, Hyunsuk; Curran, Walter J.; Liu, Tian
2017-02-01
Recently, MR simulators gain popularity because of unnecessary radiation exposure of CT simulators being used in radiation therapy planning. We propose a method for pseudo CT estimation from MR images based on a patch-based random forest. Patient-specific anatomical features are extracted from the aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified using feature selection to train the random forest. The well-trained random forest is used to predict the pseudo CT of a new patient. This prediction technique was tested with human brain images and the prediction accuracy was assessed using the original CT images. Peak signal-to-noise ratio (PSNR) and feature similarity (FSIM) indexes were used to quantify the differences between the pseudo and original CT images. The experimental results showed the proposed method could accurately generate pseudo CT images from MR images. In summary, we have developed a new pseudo CT prediction method based on patch-based random forest, demonstrated its clinical feasibility, and validated its prediction accuracy. This pseudo CT prediction technique could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.
Hasturk, Hatice; Kantarci, Alpdogan; Ghattas, Mazen; Dangaria, Smit J.; Abdallah, Rima; Morgan, Elise F.; Diekwisch, Thomas G.H.; Ashman, Arthur; Van Dyke, Thomas
2015-01-01
Background This report is the second part of the previously published study on the impact of light/chemical hardening technology and a newly formulated composite graft material for crestal augmentation during immediate implant placement. Methods A total of 48 implants were placed into the sockets of the mesial roots of freshly extracted mandibular premolar teeth in three minipigs. Crestal areas and intrabony spaces were randomly augmented with light-hardened graft materials including a composite graft consisting of polymethylmethacrylate, polyhydroxylethylmethacrylate, and calcium hydroxide (PPCH) plus polyanhydride (PA); PPCH graft; and PA graft, or left untreated. Distal sockets not receiving implants and the sockets of first molars (n = 60) were randomly treated with one of the graft materials or left empty. In addition, two molar sockets were treated with the original PPCH graft material. Quantitative microcomputed tomography (micro-CT) was used to assess alveolar bone structure and tissue compositions. Histologic evaluations included descriptive histology to assess the peri-implant wound healing, as well as histomorphometric measurements to determine bone-to-implant contact (BIC). Results Both trabecular and cortical bone measurements by micro-CT did not reveal any significant differences among the groups. Sites augmented with PPCH+PA resulted in significantly greater BIC surface than PPCH alone and no-graft-treated implants (P <0.05) histologically. Stained ground sections showed complete bone formation between bone and implant surface in the PPCH+PA group, whereas sites without augmentation showed large gaps between bone and implant surfaces, indicating a slower bone apposition and less BIC surface compared to all other groups. Similar to implant sections, all materials showed positive outcome on trabecular and cortical bone formation in extraction sockets with an intact crestal cortical bone. Conclusion Histologic evaluations supported the previous findings on implant stability and function and confirmed that PPCH+PA provides a greater BIC with a well-organized implant–bone interface and is useful in crestal augmentation during immediate implant placement. PMID:24502615
Hasturk, Hatice; Kantarci, Alpdogan; Ghattas, Mazen; Dangaria, Smit J; Abdallah, Rima; Morgan, Elise F; Diekwisch, Thomas G H; Ashman, Arthur; Van Dyke, Thomas
2014-09-01
This report is the second part of the previously published study on the impact of light/chemical hardening technology and a newly formulated composite graft material for crestal augmentation during immediate implant placement. A total of 48 implants were placed into the sockets of the mesial roots of freshly extracted mandibular premolar teeth in three minipigs. Crestal areas and intrabony spaces were randomly augmented with light-hardened graft materials including a composite graft consisting of polymethylmethacrylate, polyhydroxylethylmethacrylate, and calcium hydroxide (PPCH) plus polyanhydride (PA); PPCH graft; and PA graft, or left untreated. Distal sockets not receiving implants and the sockets of first molars (n = 60) were randomly treated with one of the graft materials or left empty. In addition, two molar sockets were treated with the original PPCH graft material. Quantitative microcomputed tomography (micro-CT) was used to assess alveolar bone structure and tissue compositions. Histologic evaluations included descriptive histology to assess the peri-implant wound healing, as well as histomorphometric measurements to determine bone-to-implant contact (BIC). Both trabecular and cortical bone measurements by micro-CT did not reveal any significant differences among the groups. Sites augmented with PPCH+PA resulted in significantly greater BIC surface than PPCH alone and no-graft-treated implants (P <0.05) histologically. Stained ground sections showed complete bone formation between bone and implant surface in the PPCH+PA group, whereas sites without augmentation showed large gaps between bone and implant surfaces, indicating a slower bone apposition and less BIC surface compared to all other groups. Similar to implant sections, all materials showed positive outcome on trabecular and cortical bone formation in extraction sockets with an intact crestal cortical bone. Histologic evaluations supported the previous findings on implant stability and function and confirmed that PPCH+PA provides a greater BIC with a well-organized implant-bone interface and is useful in crestal augmentation during immediate implant placement.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fave, X; Fried, D; UT Health Science Center Graduate School of Biomedical Sciences, Houston, TX
2015-06-15
Purpose: Several studies have demonstrated the prognostic potential for texture features extracted from CT images of non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine if these features could be extracted with high reproducibility from cone-beam CT (CBCT) images in order for features to be easily tracked throughout a patient’s treatment. Methods: Two materials in a radiomics phantom, designed to approximate NSCLC tumor texture, were used to assess the reproducibility of 26 features. This phantom was imaged on 9 CBCT scanners, including Elekta and Varian machines. Thoracic and head imaging protocols were acquired on eachmore » machine. CBCT images from 27 NSCLC patients imaged using the thoracic protocol on Varian machines were obtained for comparison. The variance for each texture measured from these patients was compared to the variance in phantom values for different manufacturer/protocol subsets. Levene’s test was used to identify features which had a significantly smaller variance in the phantom scans versus the patient data. Results: Approximately half of the features (13/26 for material1 and 15/26 for material2) had a significantly smaller variance (p<0.05) between Varian thoracic scans of the phantom compared to patient scans. Many of these same features remained significant for the head scans on Varian (12/26 and 8/26). However, when thoracic scans from Elekta and Varian were combined, only a few features were still significant (4/26 and 5/26). Three features (skewness, coarsely filtered mean and standard deviation) were significant in almost all manufacturer/protocol subsets. Conclusion: Texture features extracted from CBCT images of a radiomics phantom are reproducible and show significantly less variation than the same features measured from patient images when images from the same manufacturer or with similar parameters are used. Reproducibility between CBCT scanners may be high enough to allow the extraction of meaningful texture values for patients. This project was funded in part by the Cancer Prevention Research Institute of Texas (CPRIT). Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.« less
Usability-driven pruning of large ontologies: the case of SNOMED CT.
López-García, Pablo; Boeker, Martin; Illarramendi, Arantza; Schulz, Stefan
2012-06-01
To study ontology modularization techniques when applied to SNOMED CT in a scenario in which no previous corpus of information exists and to examine if frequency-based filtering using MEDLINE can reduce subset size without discarding relevant concepts. Subsets were first extracted using four graph-traversal heuristics and one logic-based technique, and were subsequently filtered with frequency information from MEDLINE. Twenty manually coded discharge summaries from cardiology patients were used as signatures and test sets. The coverage, size, and precision of extracted subsets were measured. Graph-traversal heuristics provided high coverage (71-96% of terms in the test sets of discharge summaries) at the expense of subset size (17-51% of the size of SNOMED CT). Pre-computed subsets and logic-based techniques extracted small subsets (1%), but coverage was limited (24-55%). Filtering reduced the size of large subsets to 10% while still providing 80% coverage. Extracting subsets to annotate discharge summaries is challenging when no previous corpus exists. Ontology modularization provides valuable techniques, but the resulting modules grow as signatures spread across subhierarchies, yielding a very low precision. Graph-traversal strategies and frequency data from an authoritative source can prune large biomedical ontologies and produce useful subsets that still exhibit acceptable coverage. However, a clinical corpus closer to the specific use case is preferred when available.
LETTER TO THE EDITOR: Free-response operator characteristic models for visual search
NASA Astrophysics Data System (ADS)
Hutchinson, T. P.
2007-05-01
Computed tomography of diffraction enhanced imaging (DEI-CT) is a novel x-ray phase-contrast computed tomography which is applied to inspect weakly absorbing low-Z samples. Refraction-angle images which are extracted from a series of raw DEI images measured in different positions of the rocking curve of the analyser can be regarded as projections of DEI-CT. Based on them, the distribution of refractive index decrement in the sample can be reconstructed according to the principles of CT. How to combine extraction methods and reconstruction algorithms to obtain the most accurate reconstructed results is investigated in detail in this paper. Two kinds of comparison, the comparison of different extraction methods and the comparison between 'two-step' algorithms and the Hilbert filtered backprojection (HFBP) algorithm, draw the conclusion that the HFBP algorithm based on the maximum refraction-angle (MRA) method may be the best combination at present. Though all current extraction methods including the MRA method are approximate methods and cannot calculate very large refraction-angle values, the HFBP algorithm based on the MRA method is able to provide quite acceptable estimations of the distribution of refractive index decrement of the sample. The conclusion is proved by the experimental results at the Beijing Synchrotron Radiation Facility.
Yoshino, Naoto; Fujihashi, Kohtaro; Hagiwara, Yukari; Kanno, Hiroyuki; Takahashi, Kiyomi; Kobayashi, Ryoki; Inaba, Noriyuki; Noda, Masatoshi; Sato, Shigehiro
2009-07-30
Although native cholera toxin (CT) is an extremely effective adjuvant, its toxicity prevents its use in humans. We report here that apple polyphenol extract (APE), obtained from unripe apples, reduces CT-induced morphological changes and cAMP accumulation. Based upon this finding, we have attempted to design a novel, effective and safe mucosal vaccine by using CT with several dosages of APE as nasal adjuvants. Mice nasally immunized with OVA plus CT and an optimal dosage of APE showed significantly reduced levels of inflammatory responses as well as total and OVA-specific IgE antibodies when compared with mice given without APE. However, levels of both mucosal and systemic OVA-specific antibody responses were maintained. Further, APE significantly down-regulated accumulation of CT in the olfactory nerves and epithelium. In summary, an optimal dosage of APE would take full advantage of mucosal adjuvanticity of native CT without any toxicity for application in humans.
Automated extraction of radiation dose information for CT examinations.
Cook, Tessa S; Zimmerman, Stefan; Maidment, Andrew D A; Kim, Woojin; Boonn, William W
2010-11-01
Exposure to radiation as a result of medical imaging is currently in the spotlight, receiving attention from Congress as well as the lay press. Although scanner manufacturers are moving toward including effective dose information in the Digital Imaging and Communications in Medicine headers of imaging studies, there is a vast repository of retrospective CT data at every imaging center that stores dose information in an image-based dose sheet. As such, it is difficult for imaging centers to participate in the ACR's Dose Index Registry. The authors have designed an automated extraction system to query their PACS archive and parse CT examinations to extract the dose information stored in each dose sheet. First, an open-source optical character recognition program processes each dose sheet and converts the information to American Standard Code for Information Interchange (ASCII) text. Each text file is parsed, and radiation dose information is extracted and stored in a database which can be queried using an existing pathology and radiology enterprise search tool. Using this automated extraction pipeline, it is possible to perform dose analysis on the >800,000 CT examinations in the PACS archive and generate dose reports for all of these patients. It is also possible to more effectively educate technologists, radiologists, and referring physicians about exposure to radiation from CT by generating report cards for interpreted and performed studies. The automated extraction pipeline enables compliance with the ACR's reporting guidelines and greater awareness of radiation dose to patients, thus resulting in improved patient care and management. Copyright © 2010 American College of Radiology. Published by Elsevier Inc. All rights reserved.
Automated extraction of pleural effusion in three-dimensional thoracic CT images
NASA Astrophysics Data System (ADS)
Kido, Shoji; Tsunomori, Akinori
2009-02-01
It is important for diagnosis of pulmonary diseases to measure volume of accumulating pleural effusion in threedimensional thoracic CT images quantitatively. However, automated extraction of pulmonary effusion correctly is difficult. Conventional extraction algorithm using a gray-level based threshold can not extract pleural effusion from thoracic wall or mediastinum correctly, because density of pleural effusion in CT images is similar to those of thoracic wall or mediastinum. So, we have developed an automated extraction method of pulmonary effusion by use of extracting lung area with pleural effusion. Our method used a template of lung obtained from a normal lung for segmentation of lungs with pleural effusions. Registration process consisted of two steps. First step was a global matching processing between normal and abnormal lungs of organs such as bronchi, bones (ribs, sternum and vertebrae) and upper surfaces of livers which were extracted using a region-growing algorithm. Second step was a local matching processing between normal and abnormal lungs which were deformed by the parameter obtained from the global matching processing. Finally, we segmented a lung with pleural effusion by use of the template which was deformed by two parameters obtained from the global matching processing and the local matching processing. We compared our method with a conventional extraction method using a gray-level based threshold and two published methods. The extraction rates of pleural effusions obtained from our method were much higher than those obtained from other methods. Automated extraction method of pulmonary effusion by use of extracting lung area with pleural effusion is promising for diagnosis of pulmonary diseases by providing quantitative volume of accumulating pleural effusion.
NASA Astrophysics Data System (ADS)
Meng, Qier; Kitasaka, Takayuki; Oda, Masahiro; Mori, Kensaku
2017-03-01
Airway segmentation is an important step in analyzing chest CT volumes for computerized lung cancer detection, emphysema diagnosis, asthma diagnosis, and pre- and intra-operative bronchoscope navigation. However, obtaining an integrated 3-D airway tree structure from a CT volume is a quite challenging task. This paper presents a novel airway segmentation method based on intensity structure analysis and bronchi shape structure analysis in volume of interest (VOI). This method segments the bronchial regions by applying the cavity enhancement filter (CEF) to trace the bronchial tree structure from the trachea. It uses the CEF in each VOI to segment each branch and to predict the positions of VOIs which envelope the bronchial regions in next level. At the same time, a leakage detection is performed to avoid the leakage by analysing the pixel information and the shape information of airway candidate regions extracted in the VOI. Bronchial regions are finally obtained by unifying the extracted airway regions. The experiments results showed that the proposed method can extract most of the bronchial region in each VOI and led good results of the airway segmentation.
Pelvic artery calcification detection on CT scans using convolutional neural networks
NASA Astrophysics Data System (ADS)
Liu, Jiamin; Lu, Le; Yao, Jianhua; Bagheri, Mohammadhadi; Summers, Ronald M.
2017-03-01
Artery calcification is observed commonly in elderly patients, especially in patients with chronic kidney disease, and may affect coronary, carotid and peripheral arteries. Vascular calcification has been associated with many clinical outcomes. Manual identification of calcification in CT scans requires substantial expert interaction, which makes it time-consuming and infeasible for large-scale studies. Many works have been proposed for coronary artery calcification detection in cardiac CT scans. In these works, coronary artery extraction is commonly required for calcification detection. However, there are few works about abdominal or pelvic artery calcification detection. In this work, we present a method for automatic pelvic artery calcification detection on CT scan. This method uses the recent advanced faster region-based convolutional neural network (R-CNN) to directly identify artery calcification without a need for artery extraction since pelvic artery extraction itself is challenging. Our method first generates category-independent region proposals for each slice of the input CT scan using region proposal networks (RPN). Then, each region proposal is jointly classified and refined by softmax classifier and bounding box regressor. We applied the detection method to 500 images from 20 CT scans of patients for evaluation. The detection system achieved a 77.4% average precision and a 85% sensitivity at 1 false positive per image.
Assessment of an Optical Flow Field-Based Polyp Detector for CT Colonography
2001-10-25
sort true polyps from false positives based on features extracted from the computed OFFs. II. METHODOLOGY A. Pre-processing The 3D CT data was...subvolume and scrolling direction, as follows: = ∑ Z ZD y)x,( Smoothy )x,( vv (2) The smoothing filter used is a 3×3 rectangular
3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxels
NASA Astrophysics Data System (ADS)
Huang, Shan; Liu, Xiabi; Han, Guanghui; Zhao, Xinming; Zhao, Yanfeng; Zhou, Chunwu
2018-02-01
The earlier detection of ground glass opacity (GGO) is of great importance since GGOs are more likely to be malignant than solid nodules. However, the detection of GGO is a difficult task in lung cancer screening. This paper proposes a novel GGO candidate extraction method, which performs multilevel thresholding on supervoxels in 3D lung CT images. Firstly, we segment the lung parenchyma based on Otsu algorithm. Secondly, the voxels which are adjacent in 3D discrete space and sharing similar grayscale are clustered into supervoxels. This procedure is used to enhance GGOs and reduce computational complexity. Thirdly, Hessian matrix is used to emphasize focal GGO candidates. Lastly, an improved adaptive multilevel thresholding method is applied on segmented clusters to extract GGO candidates. The proposed method was evaluated on a set of 19 lung CT scans containing 166 GGO lesions from the Lung CT Imaging Signs (LISS) database. The experimental results show that our proposed GGO candidate extraction method is effective, with a sensitivity of 100% and 26.3 of false positives per scan (665 GGO candidates, 499 non-GGO regions and 166 GGO regions). It can handle both focal GGOs and diffuse GGOs.
Katiki, Luciana M; Ferreira, Jorge F S; Gonzalez, Javier M; Zajac, Anne M; Lindsay, David S; Chagas, Ana Carolina S; Amarante, Alessandro F T
2013-02-18
Although tannin-rich forages are known to increase protein uptake and to reduce gastrointestinal nematode infections in grazing ruminants, most published research involves forages with condensed tannins (CT), while published literature lacks information on the anthelmintic capacity, nutritional benefits, and antioxidant capacity of alternative forages containing hydrolyzable tannins (HT). We evaluated the anthelmintic activity and the antioxidant capacity of plant extracts containing either mostly CT, mostly HT, or both CT and HT. Extracts were prepared with 70% acetone, lyophilized, redissolved to doses ranging from 1.0mg/mL to 25mg/mL, and tested against adult Caenorhabditis elegans as a test model. The extract concentrations that killed 50% (LC(50)) or 90% (LC(90)) of the nematodes in 24h were determined and compared to the veterinary anthelmintic levamisole (8 mg/mL). Extracts were quantified for CT by the acid butanol assay, for HT (based on gallic acid and ellagic acid) by high-performance liquid chromatography (HPLC) and total phenolics, and for their antioxidant activity by the oxygen radical absorbance capacity (ORAC) assay. Extracts with mostly CT were Lespedeza cuneata, Salix X sepulcralis, and Robinia pseudoacacia. Extracts rich in HT were Acer rubrum, Rosa multiflora, and Quercus alba, while Rhus typhina had both HT and CT. The extracts with the lowest LC(50) and LC(90) concentrations, respectively, in the C. elegans assay were Q. alba (0.75 and 1.06 mg/mL), R. typhina collected in 2007 (0.65 and 2.74 mg/mL), A. rubrum (1.03 and 5.54 mg/mL), and R. multiflora (2.14 and 8.70 mg/mL). At the doses of 20 and 25mg/mL, HT-rich, or both CT- and HT-rich, extracts were significantly more lethal to adult C. elegans than extracts containing only CT. All extracts were high in antioxidant capacity, with ORAC values ranging from 1800 μmoles to 4651 μmoles of trolox equivalents/g, but ORAC did not correlate with anthelmintic activity. The total phenolics test had a positive and highly significant (r=0.826, p ≤ 0.01) correlation with total hydrolyzable tannins. Plants used in this research are naturalized to the Appalachian edaphoclimatic conditions, but occur in temperate climate areas worldwide. They represent a rich, renewable, and unexplored source of tannins and antioxidants for grazing ruminants, whereas conventional CT-rich forages, such as L. cuneata, may be hard to establish and adapt to areas with temperate climate. Due to their high in vitro anthelmintic activity, antioxidant capacity, and their adaptability to non-arable lands, Q. alba, R. typhina, A. rubrum, and R. multiflora have a high potential to improve the health of grazing animals and must have their anthelmintic effects confirmed in vivo in both sheep and goats. Published by Elsevier B.V.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, J; Gao, H
2016-06-15
Purpose: Different from the conventional computed tomography (CT), spectral CT based on energy-resolved photon-counting detectors is able to provide the unprecedented material composition. However, an important missing piece for accurate spectral CT is to incorporate the detector response function (DRF), which is distorted by factors such as pulse pileup and charge-sharing. In this work, we propose material reconstruction methods for spectral CT with DRF. Methods: The polyenergetic X-ray forward model takes the DRF into account for accurate material reconstruction. Two image reconstruction methods are proposed: a direct method based on the nonlinear data fidelity from DRF-based forward model; a linear-data-fidelitymore » based method that relies on the spectral rebinning so that the corresponding DRF matrix is invertible. Then the image reconstruction problem is regularized with the isotropic TV term and solved by alternating direction method of multipliers. Results: The simulation results suggest that the proposed methods provided more accurate material compositions than the standard method without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Conclusion: We have proposed material reconstruction methods for spectral CT with DRF, whichprovided more accurate material compositions than the standard methods without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Jiulong Liu and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).« less
Iamsaard, Sitthichai; Burawat, Jaturon; Kanla, Pipatpong; Arun, Supatcharee; Sukhorum, Wannisa; Sripanidkulchai, Bungorn; Uabundit, Nongnut; Wattathorn, Jintanaporn; Hipkaeo, Wiphawi; Fongmoon, Duriya; Kondo, Hisatake
2014-06-01
Ketoconazole (KET), an antifungal drug, has adverse effects on the male reproductive system. Pre-treatments with antioxidant plant against testicular damage induced by KET are required. The flowers of Clitoria ternatea (CT) are proven to have hepatoprotective potential. However, the protective effect on KET-induced testicular damage has not been reported. To investigate the protective effect of CT flower extracts with antioxidant activity on male reproductive parameters including sperm concentration, serum testosterone level, histopathology of the testis, and testicular tyrosine phosphorylation levels in rats induced with KET. The antioxidant activity of CT flower extracts was determined using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays. Male rats were treated with CT flower extracts (10, 50, or 100 mg/kg BW) or distilled water via a gastric tube for 28 d (preventive period: Days 1-21) and induced by KET (100 mg/kg BW) via intraperitoneal injection for 7 d (induction period: Days 22-28). After the experiment, all animals were examined for the weights of the testis, epididymis plus vas deferens and seminal vesicle, serum testosterone levels, sperm concentration, histological structures and diameter of testis, and testicular tyrosine phosphorylation levels by immunoblotting. The CT flower extracts had capabilities for DPPH scavenging and high reducing power. At 100 mg/kg BW, the extract had no toxic effects on the male reproductive system. Significantly, in CT+KET groups, CT flower extracts (50 and 100 mg/kg BW) alleviated the reduction of reproductive organ weight parameters, testosterone levels, and sperm concentration. In addition, CT flower extracts gave protection from testicular damage in KET-induced rats. Moreover, in the CT100+KET group, CT flower extracts significantly enhanced the expression of a testicular 50-kDa tyrosine phosphorylated protein compared with that of other groups. C. ternatea flower extracts possessing antioxidant activity are not harmful to the male reproductive system and can protect against testicular damage in KET-induced rats.
Gordaliza, P M; Muñoz-Barrutia, A; Via, L E; Sharpe, S; Desco, M; Vaquero, J J
2018-05-29
Computed tomography (CT) images enable capturing specific manifestations of tuberculosis (TB) that are undetectable using common diagnostic tests, which suffer from limited specificity. In this study, we aimed to automatically quantify the burden of Mycobacterium tuberculosis (Mtb) using biomarkers extracted from x-ray CT images. Nine macaques were aerosol-infected with Mtb and treated with various antibiotic cocktails. Chest CT scans were acquired in all animals at specific times independently of disease progression. First, a fully automatic segmentation of the healthy lungs from the acquired chest CT volumes was performed and air-like structures were extracted. Next, unsegmented pulmonary regions corresponding to damaged parenchymal tissue and TB lesions were included. CT biomarkers were extracted by classification of the probability distribution of the intensity of the segmented images into three tissue types: (1) Healthy tissue, parenchyma free from infection; (2) soft diseased tissue, and (3) hard diseased tissue. The probability distribution of tissue intensities was assumed to follow a Gaussian mixture model. The thresholds identifying each region were automatically computed using an expectation-maximization algorithm. The estimated longitudinal course of TB infection shows that subjects that have followed the same antibiotic treatment present a similar response (relative change in the diseased volume) with respect to baseline. More interestingly, the correlation between the diseased volume (soft tissue + hard tissue), which was manually delineated by an expert, and the automatically extracted volume with the proposed method was very strong (R 2 ≈ 0.8). We present a methodology that is suitable for automatic extraction of a radiological biomarker from CT images for TB disease burden. The method could be used to describe the longitudinal evolution of Mtb infection in a clinical trial devoted to the design of new drugs.
Upadhyay, Gayaprasad; Khoshla, Sarvesh; Kosuru, Ramoji; Singh, Sanjay
2016-01-01
Objective: The current study was designed to explore anxiolytic, antidepressant, and antistress actions of Cinnamomum tamala (CT) leaves (aqueous extract) in rats. Materials and Methods: Behavioral procedures of anxiety, depression, and stress were assessed in rats. CT (100, 200, and 400 mg/kg) was given once a daily for 7 days via oral route and the efficacy was matched by those elicited by lorazepam (1 mg/kg, p.o.), imipramine (10 mg/kg, p.o.), and Withania somnifera (100 mg/kg, p.o.) for anxiolytic, antidepressant, and antistress studies, respectively. Standard drugs were given 1 time, 30 min preceding the behavioral trials. Results: One-way analysis of variance followed by Newman–Keuls multiple comparison test was employed to analyze the results. P < 0.05 was considered statistically significant as compared to control. CT at 400 mg/kg produced an antianxiety effect equivalent to lorazepam, in the elevated plus maze, open field, and social interaction tests among selected doses of the CT. CT at 400 mg/kg also induced an antidepressant activity similar to imipramine, in the behavioral despair, learned helplessness test, and tail suspension among selected doses of the CT. Moreover, CT at 400 mg/kg produced a significant antistress effect comparable to W. somnifera in water immersion-restraint stress by decreasing ulcer index, adrenal gland weight, and by normalizing the plasma levels of corticosterone, glucose, cholesterol, and triglyceride levels when related to stress control. Conclusion: The study shows that among the different CT doses, CT at 400 mg/kg possesses significant anxiolytic, antidepressant, and anti-stress effects and has therapeutic beneficial for the management of psychological ailments. PMID:27721543
Abbasi-Maleki, Saeid; Mousavi, Zahra
2017-09-01
Studies indicate that major deficiency in the levels of monoaminergic transmitters is a reason for severe depression. On the other hand, it is shown that Carthamus tinctorius L. (CT) may improve neuropsychological injuries by regulation of the monoamine transporter action. Hence, the present study was undertaken to evaluate the involvement of monoaminergic systems in antidepressant-like effect of CT extract in the tail suspension test (TST) in mice. The mice were intraperitoneally (IP) treated with CT extract (100-400 mg/kg) 1 hr before the TST. To investigate the involvement of monoaminergic systems in antidepressant-like effect, the mice were treated with receptor antagonists 15 min before CT extract treatment (400 mg/kg, IP) and 1 hr before the TST. Findings showed that CT extract (100-400 mg/kg, IP), dose-dependently induced antidepressant-like effect ( P <0.001), but it was not accompanied by alterations in spontaneous locomotor activity in the open-field test. Pretreatment of mice with SCH23390, sulpiride, haloperidol, WAY100135, cyproheptadine, ketanserin and p-chlorophenylalanine (PCPA) inhibited the antidepressant-like effect of CT extract (400 mg/kg, IP), but not with prazosin and yohimbine. Co-administration of CT extract (100 mg/kg, IP) with sub-effective doses of fluoxetine (5 mg/kg, IP) or imipramine (5 mg/kg, IP) increased their antidepressant-like response. Our findings firstly showed that components (especially N-Hexadecanoic acid) of CT extract induce antidepressant-like effects by interaction with dopaminergic (D1 and D2) and serotonergic (5HT1A, 5-HT2A receptors) systems. These findings validate the folk use of CT extract for the management of depression.
Four-Dimensional Dose Reconstruction for Scanned Proton Therapy Using Liver 4DCT-MRI
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bernatowicz, Kinga, E-mail: kinga.bernatowicz@psi.ch; Proton Therapy Center, Paul Scherrer Institute, PSI Villigen; Peroni, Marta
Purpose: Four-dimensional computed tomography-magnetic resonance imaging (4DCT-MRI) is an image-processing technique for simulating many 4DCT data sets from a static reference CT and motions extracted from 4DMRI studies performed using either volunteers or patients. In this work, different motion extraction approaches were tested using 6 liver cases, and a detailed comparison between 4DCT-MRI and 4DCT was performed. Methods and Materials: 4DCT-MRI has been generated using 2 approaches. The first approach used motion extracted from 4DMRI as being “most similar” to that of 4DCT from the same patient (subject-specific), and the second approach used the most similar motion obtained from amore » motion library derived from 4DMRI liver studies of 13 healthy volunteers (population-based). The resulting 4DCT-MRI and 4DCTs were compared using scanned proton 4D dose calculations (4DDC). Results: Dosimetric analysis showed that 93% ± 8% of points inside the clinical target volume (CTV) agreed between 4DCT and subject-specific 4DCT-MRI (gamma analysis: 3%/3 mm). The population-based approach however showed lower dosimetric agreement with only 79% ± 14% points in the CTV reaching the 3%/3 mm criteria. Conclusions: 4D CT-MRI extends the capabilities of motion modeling for dose calculations by accounting for realistic and variable motion patterns, which can be directly employed in clinical research studies. We have found that the subject-specific liver modeling appears more accurate than the population-based approach. The former is particularly interesting for clinical applications, such as improved target delineation and 4D dose reconstruction for patient-specific QA to allow for inter- and/or intra-fractional plan corrections.« less
A practical material decomposition method for x-ray dual spectral computed tomography.
Hu, Jingjing; Zhao, Xing
2016-03-17
X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today's clinical dual energy CT scanners usually measure different rays for different energy spectra and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.
Zou, Yunlong; Holmes, Russell J
2015-08-26
In order to further improve the performance of organic photovoltaic cells (OPVs), it is essential to better understand the factors that limit the open-circuit voltage (VOC). Previous work has sought to correlate the value of VOC in donor-acceptor (D-A) OPVs to the interface energy level offset (EDA). In this work, measurements of electroluminescence are used to extract the charge transfer (CT) state energy for multiple small molecule D-A pairings. The CT state as measured from electroluminescence is found to show better correlation to the maximum VOC than EDA. The difference between EDA and the CT state energy is attributed to the Coulombic binding energy of the CT state. This correlation is demonstrated explicitly by inserting an insulating spacer layer between the donor and acceptor materials, reducing the binding energy of the CT state and increasing the measured VOC. These results demonstrate a direct correlation between maximum VOC and CT state energy.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, S; Le, Q; Mutaf, Y
2015-06-15
Purpose: To assess dose calculation accuracy of cone-beam CT (CBCT) based treatment plans using a patient-specific stepwise CT-density conversion table in comparison to conventional CT-based treatment plans. Methods: Unlike CT-based treatment planning which use fixed CT-density table, this study used patient-specific CT-density table to minimize the errors in reconstructed mass densities due to the effects of CBCT Hounsfield unit (HU) uncertainties. The patient-specific CT-density table was a stepwise function which maps HUs to only 6 classes of materials with different mass densities: air (0.00121g/cm3), lung (0.26g/cm3), adipose (0.95g/cm3), tissue (1.05 g/cm3), cartilage/bone (1.6g/cm3), and other (3g/cm3). HU thresholds to definemore » different materials were adjusted for each CBCT via best match with the known tissue types in these images. Dose distributions were compared between CT-based plans and CBCT-based plans (IMRT/VMAT) for four types of treatment sites: head and neck (HN), lung, pancreas, and pelvis. For dosimetric comparison, PTV mean dose in both plans were compared. A gamma analysis was also performed to directly compare dosimetry in the two plans. Results: Compared to CT-based plans, the differences for PTV mean dose were 0.1% for pelvis, 1.1% for pancreas, 1.8% for lung, and −2.5% for HN in CBCT-based plans. The gamma passing rate was 99.8% for pelvis, 99.6% for pancreas, and 99.3% for lung with 3%/3mm criteria, and 80.5% for head and neck with 5%/3mm criteria. Different dosimetry accuracy level was observed: 1% for pelvis, 3% for lung and pancreas, and 5% for head and neck. Conclusion: By converting CBCT data to 6 classes of materials for dose calculation, 3% of dose calculation accuracy can be achieved for anatomical sites studied here, except HN which had a 5% accuracy. CBCT-based treatment planning using a patient-specific stepwise CT-density table can facilitate the evaluation of dosimetry changes resulting from variation in patient anatomy.« less
[Imaging analysis of jaw defects reparation with antigen-extracted porcine cancellous bone].
Chen, Xufeng; Lu, Lihong; Feng, Zhiqiang; Yin, Zhongda; Lai, Renfa
2017-12-01
At present, most of the bone xenograft for clinical application comes from bovine. In recent years, many studies have been done on the clinical application of porcine xenograft bone. The goal of this study was to evaluate the effect of canine mandibular defects reparation with antigen-extracted porcine cancellous bone by imaging examination. Four dogs' bilateral mandibular defects were created, with one side repaired with autologous bone (set as control group) while the other side repaired with antigen-extracted porcine cancellous bone (set as experimental group). Titanium plates and titanium screws were used for fixation. Cone beam computed tomography (CBCT), computed tomography (CT), single-photon emission computed tomography (SPECT) were undertaken at week 12 and 24 postoperatively, and SPECT and CT images were fused. The results demonstrated that the remodeling of antigen-extracted porcine cancellous bone was slower than that of autologous bone, but it can still be used as scaffold for jaw defects. The results in this study provide a new choice for materials required for clinical reparation of jaw defects.
A neural network-based method for spectral distortion correction in photon counting x-ray CT
NASA Astrophysics Data System (ADS)
Touch, Mengheng; Clark, Darin P.; Barber, William; Badea, Cristian T.
2016-08-01
Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables both 4 energy bins acquisition, as well as full-spectrum mode in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical effects in the detector and can be very noisy due to photon starvation in narrow energy bins. To address spectral distortions, we propose and demonstrate a novel artificial neural network (ANN)-based spectral distortion correction mechanism, which learns to undo the distortion in spectral CT, resulting in improved material decomposition accuracy. To address noise, post-reconstruction denoising based on bilateral filtration, which jointly enforces intensity gradient sparsity between spectral samples, is used to further improve the robustness of ANN training and material decomposition accuracy. Our ANN-based distortion correction method is calibrated using 3D-printed phantoms and a model of our spectral CT system. To enable realistic simulations and validation of our method, we first modeled the spectral distortions using experimental data acquired from 109Cd and 133Ba radioactive sources measured with our PCXD. Next, we trained an ANN to learn the relationship between the distorted spectral CT projections and the ideal, distortion-free projections in a calibration step. This required knowledge of the ground truth, distortion-free spectral CT projections, which were obtained by simulating a spectral CT scan of the digital version of a 3D-printed phantom. Once the training was completed, the trained ANN was used to perform distortion correction on any subsequent scans of the same system with the same parameters. We used joint bilateral filtration to perform noise reduction by jointly enforcing intensity gradient sparsity between the reconstructed images for each energy bin. Following reconstruction and denoising, the CT data was spectrally decomposed using the photoelectric effect, Compton scattering, and a K-edge material (i.e. iodine). The ANN-based distortion correction approach was tested using both simulations and experimental data acquired in phantoms and a mouse with our PCXD-based micro-CT system for 4 bins and full-spectrum acquisition modes. The iodine detectability and decomposition accuracy were assessed using the contrast-to-noise ratio and relative error in iodine concentration estimation metrics in images with and without distortion correction. In simulation, the material decomposition accuracy in the reconstructed data was vastly improved following distortion correction and denoising, with 50% and 20% reductions in material concentration measurement error in full-spectrum and 4 energy bins cases, respectively. Overall, experimental data confirms that full-spectrum mode provides superior results to 4-energy mode when the distortion corrections are applied. The material decomposition accuracy in the reconstructed data was vastly improved following distortion correction and denoising, with as much as a 41% reduction in material concentration measurement error for full-spectrum mode, while also bringing the iodine detectability to 4-6 mg ml-1. Distortion correction also improved the 4 bins mode data, but to a lesser extent. The results demonstrate the experimental feasibility and potential advantages of ANN-based distortion correction and joint bilateral filtration-based denoising for accurate K-edge imaging with a PCXD. Given the computational efficiency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.
NASA Astrophysics Data System (ADS)
Hofmann, Philipp; Sedlmair, Martin; Krauss, Bernhard; Wichmann, Julian L.; Bauer, Ralf W.; Flohr, Thomas G.; Mahnken, Andreas H.
2016-03-01
Osteoporosis is a degenerative bone disease usually diagnosed at the manifestation of fragility fractures, which severely endanger the health of especially the elderly. To ensure timely therapeutic countermeasures, noninvasive and widely applicable diagnostic methods are required. Currently the primary quantifiable indicator for bone stability, bone mineral density (BMD), is obtained either by DEXA (Dual-energy X-ray absorptiometry) or qCT (quantitative CT). Both have respective advantages and disadvantages, with DEXA being considered as gold standard. For timely diagnosis of osteoporosis, another CT-based method is presented. A Dual Energy CT reconstruction workflow is being developed to evaluate BMD by evaluating lumbar spine (L1-L4) DE-CT images. The workflow is ROI-based and automated for practical use. A dual energy 3-material decomposition algorithm is used to differentiate bone from soft tissue and fat attenuation. The algorithm uses material attenuation coefficients on different beam energy levels. The bone fraction of the three different tissues is used to calculate the amount of hydroxylapatite in the trabecular bone of the corpus vertebrae inside a predefined ROI. Calibrations have been performed to obtain volumetric bone mineral density (vBMD) without having to add a calibration phantom or to use special scan protocols or hardware. Accuracy and precision are dependent on image noise and comparable to qCT images. Clinical indications are in accordance with the DEXA gold standard. The decomposition-based workflow shows bone degradation effects normally not visible on standard CT images which would induce errors in normal qCT results.
Histologic evaluation of autogenous connective tissue and acellular dermal matrix grafts in humans.
Cummings, Lewis C; Kaldahl, Wayne B; Allen, Edward P
2005-02-01
The clinical success of root coverage with autogenous connective tissue (CT) or acellular dermal matrix (ADM) has been well documented. However, limited histological results of CT grafts have been reported, and a case report of a human block section has been published documenting an ADM graft. The purpose of this study is to document the histological results of CT grafts, ADM grafts, and coronally advanced flaps to cover denuded roots in humans. This study included four patients previously treatment planned for extractions of three or more anterior teeth. Three teeth in each patient were selected and randomly designated to receive either a CT or ADM graft beneath a coronally advanced flap (tests) or coronally advanced flap alone (control). Six months postoperatively block section extractions were performed and the teeth processed for histologic evaluation with hematoxylin-eosin and Verhoeff's stains. Histologically, both the CT and ADM were well incorporated within the recipient tissues. New fibroblasts, vascular elements, and collagen were present throughout the ADM, while retention of the transplanted elastic fibers was apparent. No effect on the keratinization or connective tissue organization of the overlying alveolar mucosa was evident with either graft. For both materials, areas of cemental deposition were present within the root notches, the alveolar bone was essentially unaffected, and the attachments to the root surfaces were similar. Although CT and ADM have a slightly different histological appearance, both can successfully be used to cover denuded roots with similar attachments and no adverse healing.
An application of Chan-Vese method used to determine the ROI area in CT lung screening
NASA Astrophysics Data System (ADS)
Prokop, Paweł; Surtel, Wojciech
2016-09-01
The article presents two approaches of determining the ROI area in CT lung screening. First approach is based on a classic method of framing the image in order to determine the ROI by using a MaZda tool. Second approach is based on segmentation of CT images of the lungs and reducing the redundant information from the image. Of the two approaches of an Active Contour, it was decided to choose the Chan-Vese method. In order to determine the effectiveness of the approach, it was performed an analysis of received ROI texture and extraction of textural features. In order to determine the effectiveness of the method, it was performed an analysis of the received ROI textures and extraction of the texture features, by using a Mazda tool. The results were compared and presented in the form of the radar graphs. The second approach proved to be effective and appropriate and consequently it is used for further analysis of CT images, in the computer-aided diagnosis of sarcoidosis.
Liuti, T; Smith, S; Dixon, P M
2018-01-01
Equine maxillary cheek teeth apical infections are a significant disorder because of frequent spread of infection to the supporting bones. The accuracy of computed tomographic imaging (CT) of this disorder has not been fully assessed. To compare the radiographic and CT findings in horses diagnosed with maxillary cheek teeth apical infections with pathological findings in the extracted teeth to assess the accuracy of these imaging techniques. Observational clinical study. Thirty-two maxillary cheek teeth (in 29 horses) diagnosed with apical infections by clinical, radiographic and principally by CT examinations, were extracted orally. The extracted teeth were subjected to further CT, gross pathological and histological examinations. Four normal teeth extracted from a cadaver served as controls. Pulpar and apical changes highly indicative of maxillary cheek teeth apical infection were present in all 32 teeth on CT, but in just 17/32 teeth (53%) radiographically. Gross pulpar/apical abnormalities and histological pulpar/periapical changes were present in 31/32 (97%) extracted teeth. On CT, one tooth contained small gas pockets in the apical aspect of one pulp and adjacent periodontal space, however no pathological changes were found following its extraction. The study is descriptive and is confined to a small number of cases. This study showed a 97% agreement between CT diagnosis of maxillary cheek teeth apical infection and the presence of pathological changes in the extracted teeth, confirming the diagnostic accuracy of CT compared with radiography for this disorder. © 2017 EVJ Ltd.
Mattar, Rejane; Basile-Filho, Anibal; Kemp, Rafael; Santos, José Sebastião dos
2013-01-01
To analyze the usefulness of Quick Lactose Intolerance Test in relation to the genetic test based on LCT-13910C>T genotypes, previously validated for clinical practice, for primary hypolactasia/lactase-persistence diagnosis. Thirty-two dyspeptic patients that underwent upper gastrointestinal endoscopy entered the study. Two postbulbar duodenal biopsies were taken for the Quick test, and gastric antral biopsy for DNA extraction and LCT-13910C>T polymorphism analysis. DNA was also extracted from biopsies after being used in the Quick Test that was kept frozen until extraction. Nine patients with lactase-persistence genotype (LCT-13910CT or LCT-13910TT) had normolactasia, eleven patients with hypolactasia genotype (LCT-13910CC) had severe hypolactasia, and among twelve with mild hypolactasia, except for one that had LCT-13910CT genotype, all the others had hypolactasia genotype. The agreement between genetic test and quick test was high (p<0.0001; Kappa Index 0.92). Most of the patients that reported symptoms with lactose-containing food ingestion had severe hypolactasia (p<0.05). Amplification with good quality PCR product was also obtained with DNA extracted from biopsies previously used in the Quick Test; thus, for the future studies antral gastric biopsies for genetic test would be unnecessary. Quick test is highly sensitive and specific for hypolactasia diagnosis and indicated those patients with symptoms of lactose intolerance.
Algorithm of pulmonary emphysema extraction using thoracic 3-D CT images
NASA Astrophysics Data System (ADS)
Saita, Shinsuke; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Nakano, Yasutaka; Ohmatsu, Hironobu; Tominaga, Keigo; Eguchi, Kenji; Moriyama, Noriyuki
2008-03-01
Emphysema patients have the tendency to increase due to aging and smoking. Emphysematous disease destroys alveolus and to repair is impossible, thus early detection is essential. CT value of lung tissue decreases due to the destruction of lung structure. This CT value becomes lower than the normal lung- low density absorption region or referred to as Low Attenuation Area (LAA). So far, the conventional way of extracting LAA by simple thresholding has been proposed. However, the CT value of CT image fluctuates due to the measurement conditions, with various bias components such as inspiration, expiration and congestion. It is therefore necessary to consider these bias components in the extraction of LAA. We removed these bias components and we proposed LAA extraction algorithm. This algorithm has been applied to the phantom image. Then, by using the low dose CT(normal: 30 cases, obstructive lung disease: 26 cases), we extracted early stage LAA and quantitatively analyzed lung lobes using lung structure.
A Flexible Method for Multi-Material Decomposition of Dual-Energy CT Images.
Mendonca, Paulo R S; Lamb, Peter; Sahani, Dushyant V
2014-01-01
The ability of dual-energy computed-tomographic (CT) systems to determine the concentration of constituent materials in a mixture, known as material decomposition, is the basis for many of dual-energy CT's clinical applications. However, the complex composition of tissues and organs in the human body poses a challenge for many material decomposition methods, which assume the presence of only two, or at most three, materials in the mixture. We developed a flexible, model-based method that extends dual-energy CT's core material decomposition capability to handle more complex situations, in which it is necessary to disambiguate among and quantify the concentration of a larger number of materials. The proposed method, named multi-material decomposition (MMD), was used to develop two image analysis algorithms. The first was virtual unenhancement (VUE), which digitally removes the effect of contrast agents from contrast-enhanced dual-energy CT exams. VUE has the ability to reduce patient dose and improve clinical workflow, and can be used in a number of clinical applications such as CT urography and CT angiography. The second algorithm developed was liver-fat quantification (LFQ), which accurately quantifies the fat concentration in the liver from dual-energy CT exams. LFQ can form the basis of a clinical application targeting the diagnosis and treatment of fatty liver disease. Using image data collected from a cohort consisting of 50 patients and from phantoms, the application of MMD to VUE and LFQ yielded quantitatively accurate results when compared against gold standards. Furthermore, consistent results were obtained across all phases of imaging (contrast-free and contrast-enhanced). This is of particular importance since most clinical protocols for abdominal imaging with CT call for multi-phase imaging. We conclude that MMD can successfully form the basis of a number of dual-energy CT image analysis algorithms, and has the potential to improve the clinical utility of dual-energy CT in disease management.
Maneesai, Putcharawipa; Prasarttong, Patoomporn; Bunbupha, Sarawoot; Kukongviriyapan, Upa; Kukongviriyapan, Veerapol; Tangsucharit, Panot; Prachaney, Parichat; Pakdeechote, Poungrat
2016-01-01
This study examined the effect of Carthamus tinctorius (CT) extract plus captopril treatment on blood pressure, vascular function, nitric oxide (NO) bioavailability, oxidative stress and renin-angiotensin system (RAS) in Nω-Nitro-l-arginine methyl ester (l-NAME)-induced hypertension. Rats were treated with l-NAME (40 mg/kg/day) for five weeks and given CT extract (75 or 150 or 300 or 500 mg/kg/day): captopril (5 mg/kg/day) or CT extract (300 mg/kg/day) plus captopril (5 mg/kg/day) for two consecutive weeks. CT extract reduced blood pressure dose-dependently, and the most effective dose was 300 mg/kg/day. l-NAME-induced hypertensive rats showed abnormalities including high blood pressure, high vascular resistance, impairment of acetylcholine-induced vasorelaxation in isolated aortic rings and mesenteric vascular beds, increased vascular superoxide production and plasma malondialdehyde levels, downregulation of eNOS, low level of plasma nitric oxide metabolites, upregulation of angiotensin II type 1 receptor and increased plasma angiotensin II. These abnormalities were alleviated by treatment with either CT extract or captopril. Combination treatment of CT extract and captopril normalized all the abnormalities found in hypertensive rats except endothelial dysfunction. These data indicate that there are synergistic antihypertensive effects of CT extract and captopril. These effects are likely mediated by their anti-oxidative properties and their inhibition of RAS. PMID:26938552
NASA Astrophysics Data System (ADS)
Emaminejad, Nastaran; Wahi-Anwar, Muhammad; Hoffman, John; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael
2018-02-01
Translation of radiomics into clinical practice requires confidence in its interpretations. This may be obtained via understanding and overcoming the limitations in current radiomic approaches. Currently there is a lack of standardization in radiomic feature extraction. In this study we examined a few factors that are potential sources of inconsistency in characterizing lung nodules, such as 1)different choices of parameters and algorithms in feature calculation, 2)two CT image dose levels, 3)different CT reconstruction algorithms (WFBP, denoised WFBP, and Iterative). We investigated the effect of variation of these factors on entropy textural feature of lung nodules. CT images of 19 lung nodules identified from our lung cancer screening program were identified by a CAD tool and contours provided. The radiomics features were extracted by calculating 36 GLCM based and 4 histogram based entropy features in addition to 2 intensity based features. A robustness index was calculated across different image acquisition parameters to illustrate the reproducibility of features. Most GLCM based and all histogram based entropy features were robust across two CT image dose levels. Denoising of images slightly improved robustness of some entropy features at WFBP. Iterative reconstruction resulted in improvement of robustness in a fewer times and caused more variation in entropy feature values and their robustness. Within different choices of parameters and algorithms texture features showed a wide range of variation, as much as 75% for individual nodules. Results indicate the need for harmonization of feature calculations and identification of optimum parameters and algorithms in a radiomics study.
Castañeda-Ramírez, G S; Torres-Acosta, J F J; Sandoval-Castro, C A; González-Pech, P G; Parra-Tabla, V P; Mathieu, C
2017-12-01
In vitro studies using plant extracts suggest a relationship between their polyphenol contents and their anthelmintic (AH) activity against Haemonchus contortus. High polyphenol content appears to increase the efficacy of plant extracts against H. contortus as assessed by the larval exsheathment inhibition assay (LEIA) while appearing to reduce the AH efficacy measured using the egg hatch assay (EHA). In addition, some plants lack AH activity. Therefore, the present study investigated the relationship between the contents of condensed tannins (CT), total phenols (TP), and total tannins (TT) in methanol:water extracts (70:30) obtained from ten tropical plant species consumed by small ruminants as well as their AH activity against H. contortus evaluated by LEIA and EHA. Extracts of Acacia collinsii, Lysiloma latisiliquum, Havardia albicans, Senegalia gaumeri, Mimosa bahamensis, Piscidia piscipula, Acacia pennatula, Gymnopodium floribundum, Leucaena leucocephala, and Bunchosia swartziana were examined. Positive correlations were found between the effective concentration 50% (EC 50 ) (EHA) of extracts and their CT (r = 0.6809, P < 0.05, n = 10) and TP (r = 0.9152, P < 0.05, n = 10) content, suggesting that their concentration negatively affected AH activity against eggs. Based on the LEIA, there was no significant association between the EC 50 and the CT, TP, or TT of all extracts evaluated. Thus, if sheep and goats consume a complex feed mixture with high amounts of CT, TP, and TT, it might be difficult to observe an AH effect against H. contortus egg hatching. However, the AH effect upon L 3 establishment might be feasible.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lalonde, A; Bouchard, H
Purpose: To develop a general method for human tissue characterization with dual-and multi-energy CT and evaluate its performance in determining elemental compositions and the associated proton stopping power relative to water (SPR) and photon mass absorption coefficients (EAC). Methods: Principal component analysis is used to extract an optimal basis of virtual materials from a reference dataset of tissues. These principal components (PC) are used to perform two-material decomposition using simulated DECT data. The elemental mass fraction and the electron density in each tissue is retrieved by measuring the fraction of each PC. A stoichiometric calibration method is adapted to themore » technique to make it suitable for clinical use. The present approach is compared with two others: parametrization and three-material decomposition using the water-lipid-protein (WLP) triplet. Results: Monte Carlo simulations using TOPAS for four reference tissues shows that characterizing them with only two PC is enough to get a submillimetric precision on proton range prediction. Based on the simulated DECT data of 43 references tissues, the proposed method is in agreement with theoretical values of protons SPR and low-kV EAC with a RMS error of 0.11% and 0.35%, respectively. In comparison, parametrization and WLP respectively yield RMS errors of 0.13% and 0.29% on SPR, and 2.72% and 2.19% on EAC. Furthermore, the proposed approach shows potential applications for spectral CT. Using five PC and five energy bins reduces the SPR RMS error to 0.03%. Conclusion: The proposed method shows good performance in determining elemental compositions from DECT data and physical quantities relevant to radiotherapy dose calculation and generally shows better accuracy and unbiased results compared to reference methods. The proposed method is particularly suitable for Monte Carlo calculations and shows promise in using more than two energies to characterize human tissue with CT.« less
Geometry-constraint-scan imaging for in-line phase contrast micro-CT.
Fu, Jian; Yu, Guangyuan; Fan, Dekai
2014-01-01
X-ray phase contrast computed tomography (CT) uses the phase shift that x-rays undergo when passing through matter, rather than their attenuation, as the imaging signal and may provide better image quality in soft-tissue and biomedical materials with low atomic number. Here a geometry-constraint-scan imaging technique for in-line phase contrast micro-CT is reported. It consists of two circular-trajectory scans with x-ray detector at different positions, the phase projection extraction method with the Fresnel free-propagation theory and the filter back-projection reconstruction algorithm. This method removes the contact-detector scan and the pure phase object assumption in classical in-line phase contrast Micro-CT. Consequently it relaxes the experimental conditions and improves the image contrast. This work comprises a numerical study of this technique and its experimental verification using a biomedical composite dataset measured at an x-ray tube source Micro-CT setup. The numerical and experimental results demonstrate the validity of the presented method. It will be of interest for a wide range of in-line phase contrast Micro-CT applications in biology and medicine.
Spectral CT metal artifact reduction with an optimization-based reconstruction algorithm
NASA Astrophysics Data System (ADS)
Gilat Schmidt, Taly; Barber, Rina F.; Sidky, Emil Y.
2017-03-01
Metal objects cause artifacts in computed tomography (CT) images. This work investigated the feasibility of a spectral CT method to reduce metal artifacts. Spectral CT acquisition combined with optimization-based reconstruction is proposed to reduce artifacts by modeling the physical effects that cause metal artifacts and by providing the flexibility to selectively remove corrupted spectral measurements in the spectral-sinogram space. The proposed Constrained `One-Step' Spectral CT Image Reconstruction (cOSSCIR) algorithm directly estimates the basis material maps while enforcing convex constraints. The incorporation of constraints on the reconstructed basis material maps is expected to mitigate undersampling effects that occur when corrupted data is excluded from reconstruction. The feasibility of the cOSSCIR algorithm to reduce metal artifacts was investigated through simulations of a pelvis phantom. The cOSSCIR algorithm was investigated with and without the use of a third basis material representing metal. The effects of excluding data corrupted by metal were also investigated. The results demonstrated that the proposed cOSSCIR algorithm reduced metal artifacts and improved CT number accuracy. For example, CT number error in a bright shading artifact region was reduced from 403 HU in the reference filtered backprojection reconstruction to 33 HU using the proposed algorithm in simulation. In the dark shading regions, the error was reduced from 1141 HU to 25 HU. Of the investigated approaches, decomposing the data into three basis material maps and excluding the corrupted data demonstrated the greatest reduction in metal artifacts.
Informatics in Radiology: Dual-Energy Electronic Cleansing for Fecal-Tagging CT Colonography
Kim, Se Hyung; Lee, June-Goo; Yoshida, Hiroyuki
2013-01-01
Electronic cleansing (EC) is an emerging technique for the removal of tagged fecal materials at fecal-tagging computed tomographic (CT) colonography. However, existing EC methods may generate various types of artifacts that severely impair the quality of the cleansed CT colonographic images. Dual-energy fecal-tagging CT colonography is regarded as a next-generation imaging modality. EC that makes use of dual-energy fecal-tagging CT colonographic images promises to be effective in reducing cleansing artifacts by means of applying the material decomposition capability of dual-energy CT. The dual-energy index (DEI), which is calculated from the relative change in the attenuation values of a material at two different photon energies, is a reliable and effective indicator for differentiating tagged fecal materials from various types of tissues on fecal-tagging CT colonographic images. A DEI-based dual-energy EC scheme uses the DEI to help differentiate the colonic lumen—including the luminal air, tagged fecal materials, and air-tagging mixture—from the colonic soft-tissue structures, and then segments the entire colonic lumen for cleansing of the tagged fecal materials. As a result, dual-energy EC can help identify partial-volume effects in the air-tagging mixture and inhomogeneous tagging in residual fecal materials, the major causes of EC artifacts. This technique has the potential to significantly improve the quality of EC and promises to provide images of a cleansed colon that are free of the artifacts commonly observed with conventional single-energy EC methods. © RSNA, 2013 PMID:23479680
Evaluation of Cassia tora Linn. against Oxidative Stress-induced DNA and Cell Membrane Damage
Kumar, R Sunil; Narasingappa, Ramesh Balenahalli; Joshi, Chandrashekar G; Girish, Talakatta K; Prasada Rao, Ummiti JS; Danagoudar, Ananda
2017-01-01
Objective: The present study aims to evaluate antioxidants and protective role of Cassia tora Linn. against oxidative stress-induced DNA and cell membrane damage. Materials and Methods: The total and profiles of flavonoids were identified and quantified through reversed-phase high-performance liquid chromatography. In vitro antioxidant activity was determined using standard antioxidant assays. The protective role of C. tora extracts against oxidative stress-induced DNA and cell membrane damage was examined by electrophoretic and scanning electron microscopic studies, respectively. Results: The total flavonoid content of CtEA was 106.8 ± 2.8 mg/g d.w.QE, CtME was 72.4 ± 1.12 mg/g d.w.QE, and CtWE was 30.4 ± 0.8 mg/g d.w.QE. The concentration of flavonoids present in CtEA in decreasing order: quercetin >kaempferol >epicatechin; in CtME: quercetin >rutin >kaempferol; whereas, in CtWE: quercetin >rutin >kaempferol. The CtEA inhibited free radical-induced red blood cell hemolysis and cell membrane morphology better than CtME as confirmed by a scanning electron micrograph. CtEA also showed better protection than CtME and CtWE against free radical-induced DNA damage as confirmed by electrophoresis. Conclusion: C. tora contains flavonoids and inhibits oxidative stress and can be used for many health benefits and pharmacotherapy. PMID:28584491
Peripleural lung disease detection based on multi-slice CT images
NASA Astrophysics Data System (ADS)
Matsuhiro, M.; Suzuki, H.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.
2015-03-01
With the development of multi-slice CT technology, obtaining accurate 3D images of lung field in a short time become possible. To support that, a lot of image processing methods need to be developed. Detection peripleural lung disease is difficult due to its existence out of lung region, because lung extraction is often performed based on threshold processing. The proposed method uses thoracic inner region extracted by inner cavity of bone as well as air region, covers peripleural lung diseased cases such as lung nodule, calcification, pleural effusion and pleural plaque. We applied this method to 50 cases including 39 peripleural lung diseased cases. This method was able to detect 39 peripleural lung disease with 2.9 false positive per case.
Automatic extraction of via in the CT image of PCB
NASA Astrophysics Data System (ADS)
Liu, Xifeng; Hu, Yuwei
2018-04-01
In modern industry, the nondestructive testing of printed circuit board (PCB) can prevent effectively the system failure and is becoming more and more important. In order to detect the via in the PCB base on the CT image automatically accurately and reliably, a novel algorithm for via extraction based on weighting stack combining the morphologic character of via is designed. Every slice data in the vertical direction of the PCB is superimposed to enhanced vias target. The OTSU algorithm is used to segment the slice image. OTSU algorithm of thresholding gray level images is efficient for separating an image into two classes where two types of fairly distinct classes exist in the image. Randomized Hough Transform was used to locate the region of via in the segmented binary image. Then the 3D reconstruction of via based on sequence slice images was done by volume rendering. The accuracy of via positioning and detecting from a CT images of PCB was demonstrated by proposed algorithm. It was found that the method is good in veracity and stability for detecting of via in three dimensional.
The presurgical workup before third molar surgery: how much is enough?
Better, Hadar; Abramovitz, Itzhak; Shlomi, Biniamin; Kahn, Adrian; Levy, Yaakov; Shaham, Amit; Chaushu, Gavriel
2004-06-01
We sought to assess the indications for patient referral for computed tomography (CT) scan before third molar extraction. The influence of the data obtained from the CT scans on the surgical outcome and morbidity was also evaluated. There were 189 patients in the study (120 females and 69 males). Sixty-five patients were referred to receive CT and formed the study group. The remaining patients were included in the control group. There were no statistically significant differences between the groups with regard to demographic data and tooth and root angulations. Indications for tooth extraction such as pain, swelling, pericoronitis, caries, endodontic problems, pathology, and prosthetic considerations were similar. The proximity of the tooth root to the inferior alveolar canal was the only statistically significant difference between the 2 groups (P <.001). The treatment plan outcomes for extraction, surgical extraction, and follow-up were comparable. The surgeon changed the initial decision from "surgical extraction" to "follow-up" in only 1 case after CT scan. Within the limits of the present study, it can be concluded that the main reason for CT scan referral is the proximity of the third molar root to the inferior alveolar canal (<1 mm). The data obtained from the CT scan had minimal effect on the final surgical outcome. The routine use of CT scan in cases of third molar extractions cannot be recommended.
Automated segmentations of skin, soft-tissue, and skeleton, from torso CT images
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kiryu, Takuji; Hoshi, Hiroaki
2004-05-01
We have been developing a computer-aided diagnosis (CAD) scheme for automatically recognizing human tissue and organ regions from high-resolution torso CT images. We show some initial results for extracting skin, soft-tissue and skeleton regions. 139 patient cases of torso CT images (male 92, female 47; age: 12-88) were used in this study. Each case was imaged with a common protocol (120kV/320mA) and covered the whole torso with isotopic spatial resolution of about 0.63 mm and density resolution of 12 bits. A gray-level thresholding based procedure was applied to separate the human body from background. The density and distance features to body surface were used to determine the skin, and separate soft-tissue from the others. A 3-D region growing based method was used to extract the skeleton. We applied this system to the 139 cases and found that the skin, soft-tissue and skeleton regions were recognized correctly for 93% of the patient cases. The accuracy of segmentation results was acceptable by evaluating the results slice by slice. This scheme will be included in CAD systems for detecting and diagnosing the abnormal lesions in multi-slice torso CT images.
Algorithm for lung cancer detection based on PET/CT images
NASA Astrophysics Data System (ADS)
Saita, Shinsuke; Ishimatsu, Keita; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Ohtsuka, Hideki; Nishitani, Hiromu; Ohmatsu, Hironobu; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki
2009-02-01
The five year survival rate of the lung cancer is low with about twenty-five percent. In addition it is an obstinate lung cancer wherein three out of four people die within five years. Then, the early stage detection and treatment of the lung cancer are important. Recently, we can obtain CT and PET image at the same time because PET/CT device has been developed. PET/CT is possible for a highly accurate cancer diagnosis because it analyzes quantitative shape information from CT image and FDG distribution from PET image. However, neither benign-malignant classification nor staging intended for lung cancer have been established still enough by using PET/CT images. In this study, we detect lung nodules based on internal organs extracted from CT image, and we also develop algorithm which classifies benignmalignant and metastatic or non metastatic lung cancer using lung structure and FDG distribution(one and two hour after administering FDG). We apply the algorithm to 59 PET/CT images (malignant 43 cases [Ad:31, Sq:9, sm:3], benign 16 cases) and show the effectiveness of this algorithm.
Tong, Xiang; Wang, Ye; Wang, Chengdi; Jin, Jing; Tian, Panwen; Li, Weimin
2018-01-01
Objectives Although different methods have been established to detect epidermal growth factor receptor (EGFR) T790M mutation in circulating tumor DNA (ctDNA), a wide range of diagnostic accuracy values were reported in previous studies. The aim of this meta-analysis was to provide pooled diagnostic accuracy measures for droplet digital PCR (ddPCR) in the diagnosis of EGFR T790M mutation based on ctDNA. Materials and methods A systematic review and meta-analysis were carried out based on resources from Pubmed, Web of Science, Embase and Cochrane Library up to October 11, 2017. Data were extracted to assess the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio (NLR), diagnostic OR (DOR), and areas under the summary receiver-operating characteristic curve (SROC). Results Eleven of 311 studies identified have met the including criteria. The sensitivity and specificity of ddPCR for the detection of T790M mutation in ctDNA ranged from 0.0% to 100.0% and 63.2% to 100.0%, respectively. For the pooled analysis, ddPCR had a performance of 70.1% (95% CI, 62.7%–76.7%) sensitivity, 86.9 % (95% CI, 80.6%–91.7%) specificity, 3.67 (95% CI, 2.33–5.79) PLR, 0.41 (95% CI, 0.32–0.55) NLR, and 10.83 (95% CI, 5.86–20.03) DOR, with the area under the SROC curve being 0.82. Conclusion The ddPCR harbored a good performance for detection of EGFR T790M mutation in ctDNA. PMID:29844700
NASA Astrophysics Data System (ADS)
Yusof, Mohd Fahmi Mohd; Hamid, Puteri Nor Khatijah Abdul; Bauk, Sabar; Hashim, Rokiah; Tajuddin, Abdul Aziz
2015-04-01
Plug density phantoms were constructed in accordance to CT density phantom model 062M CIRS using binderless, pre-treated and tannin-based Rhizophora Spp. particleboards. The Rhizophora Spp. plug phantoms were scanned along with the CT density phantom using Siemens Somatom Definition AS CT scanner at three CT energies of 80, 120 and 140 kVp. 15 slices of images with 1.0 mm thickness each were taken from the central axis of CT density phantom for CT number and CT density profile analysis. The values were compared to water substitute plug phantom from the CT density phantom. The tannin-based Rhizophora Spp. gave the nearest value of CT number to water substitute at 80 and 120 kVp CT energies with χ2 value of 0.011 and 0.014 respectively while the binderless Rhizphora Spp. gave the nearest CT number to water substitute at 140 kVp CT energy with χ2 value of 0.023. The tannin-based Rhizophora Spp. gave the nearest CT density profile to water substitute at all CT energies. This study indicated the suitability of Rhizophora Spp. particleboard as phantom material for the use in CT imaging studies.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yusof, Mohd Fahmi Mohd, E-mail: mfahmi@usm.my; Hamid, Puteri Nor Khatijah Abdul; Tajuddin, Abdul Aziz
2015-04-29
Plug density phantoms were constructed in accordance to CT density phantom model 062M CIRS using binderless, pre-treated and tannin-based Rhizophora Spp. particleboards. The Rhizophora Spp. plug phantoms were scanned along with the CT density phantom using Siemens Somatom Definition AS CT scanner at three CT energies of 80, 120 and 140 kVp. 15 slices of images with 1.0 mm thickness each were taken from the central axis of CT density phantom for CT number and CT density profile analysis. The values were compared to water substitute plug phantom from the CT density phantom. The tannin-based Rhizophora Spp. gave the nearest valuemore » of CT number to water substitute at 80 and 120 kVp CT energies with χ{sup 2} value of 0.011 and 0.014 respectively while the binderless Rhizphora Spp. gave the nearest CT number to water substitute at 140 kVp CT energy with χ{sup 2} value of 0.023. The tannin-based Rhizophora Spp. gave the nearest CT density profile to water substitute at all CT energies. This study indicated the suitability of Rhizophora Spp. particleboard as phantom material for the use in CT imaging studies.« less
Silkwood, Justin D; Matthews, Kenneth L; Shikhaliev, Polad M
2013-05-01
Photon counting spectral (PCS) computed tomography (CT) shows promise for breast imaging. An issue with current photon-counting detectors is low count rate capabilities, artifacts resulting from nonuniform count rate across the field of view, and suboptimal spectral information. These issues are addressed in part by using tissue-equivalent adaptive filtration of the x-ray beam. The purpose of the study was to investigate the effect of adaptive filtration on different aspects of PCS breast CT. The theoretical formulation for the filter shape was derived for different filter materials and evaluated by simulation and an experimental prototype of the filter was fabricated from a tissue-like material (acrylic). The PCS CT images of a glandular breast phantom with adipose and iodine contrast elements were simulated at 40, 60, 90, and 120 kVp tube voltages, with and without adaptive filter. The CT numbers, CT noise, and contrast-to-noise ratio (CNR) were compared for spectral CT images acquired with and without adaptive filters. Similar comparison was made for material-decomposed PCS CT images. The adaptive filter improved the uniformity of CT numbers, CT noise, and CNR in both ordinary and material decomposed PCS CT images. At the same tube output the average CT noise with adaptive filter, although uniform, was higher than the average noise without adaptive filter due to x-ray absorption by the filter. Increasing tube output, so that average skin exposure with the adaptive filter was same as without filter, made the noise with adaptive filter comparable to or lower than that without adaptive filter. Similar effects were observed when energy weighting was applied, and when material decompositions were performed using energy selective CT data. An adaptive filter decreases count rate requirements to the photon counting detectors which enables PCS breast CT based on commercially available detector technologies. Adaptive filter also improves image quality in PCS breast CT by decreasing beam hardening artifacts and by eliminating spatial nonuniformities of CT numbers, noise, and CNR.
Dixon, P M; Savill, D; Horbyl, A; Reardon, R J M; Liuti, T
2014-06-01
Infundibular caries of the equine maxillary cheek teeth is an important disorder that can lead to dental fracture or apical infection. Treatment by removing food debris and carious dental tissue from affected infundibulae using high-pressure abrasion with aluminium hydroxide micro-particles, followed by filling the cleaned defect with endodontic restorative materials is a recommended treatment. However, although anecdotally considered a successful treatment option, there is currently no objective evidence to support this claim. Forty maxillary cheek teeth (CT) that contained 55 infundibulae with caries (mainly grade 2) were extracted post-mortem from 21 adult horses. Five of the CT were sectioned prior to treatment to facilitate visual examination of the carious infundibulae. The remaining carious infundibulae were cleaned using high-pressure abrasion with aluminium hydroxide particles and five CT were sectioned to assess the efficacy of this cleaning process. The remaining 30 CT containing 39 carious infundibulae were then filled with a composite restorative material. The efficacy of this restoration was assessed by computed tomography imaging followed by direct visual examination after sectioning the teeth. Only 46% (18/39) of restored infundibulae, all with shallow (mean 9.6 mm deep) defects, were fully cleaned of food debris and carious material, and filled with restorative material to their full depth. Of these 18, 11 had peripheral defects around the restoration, leaving just 18% (7/39) of restorations without any gross defects. The remaining 54% (21/39) of infundibulae (mean depth of infundibular caries defect, 18.3 mm) still contained food debris and/or carious material in more apical locations, with infundibulae with the deepest caries defects being the least effectively cleaned. The findings of this study indicate that high-pressure micro-particle abrasion is only effective in cleaning food debris from shallow, carious CT infundibulae and consequently, the majority of subsequent infundibular restorations are imperfect. Copyright © 2014. Published by Elsevier Ltd.
Friedman, Daniela B; Kim, Sei-Hill; Tanner, Andrea; Bergeron, Caroline D; Foster, Caroline; General, Kevin
2014-07-01
Clinical trials (CTs) are important for advancing public health and medical research, however, CT recruitment is challenging. The high reading level of CT information and the technical language of providers or researchers can serve as barriers to recruitment. Prior studies on the informed consent process found that consent documents often contain complicated terms. Limited research has examined resources specifically used to recruit individuals into CTs. The purpose of this study was to examine the content and readability of CT recruitment education resources in one U.S. state. Convenience sampling was employed for the collection of CT recruitment materials. A codebook was developed based on previous content analyses and emergent themes from statewide focus groups about CTs. A total of 127 materials were collected and analyzed (37.8% print; 62.2% Web). Most content was focused on treatment-related CTs (60.6%). Inclusion criteria related to specific disease conditions (88.9%) and age (73.6%) were described most often. Only 30% of resources had an explicit call to action. Overall mean readability level was Grade 11.7. Web-based materials were significantly more likely to be written at a higher grade level than print materials (p ≤ .0001). Readability also differed significantly according to resource distributor/creator, CT type, person quoted, and presence or absence of inclusion criteria and an explicit call to action. Our study provides insight into the content and difficulty level of recruitment materials intended to provide initial information about a CT. Future studies should examine individuals' comprehension of recruitment materials and how participation intentions are associated with recruitment messages. Copyright © 2014 Elsevier Inc. All rights reserved.
Na-Ion Intercalation and Charge Storage Mechanism in Two-Dimensional Vanadium Carbide
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bak, Seong -Min; Qiao, Ruimin; Yang, W.
We synthesized two-dimensional vanadium carbide MXene containing surface functional groups (denoted as V 2CT x, where T x are surface functional groups) and studied as anode material for Na-ion batteries. V 2CT x anode exhibits reversible charge storage with good cycling stability and high rate capability through electrochemical test. Furthermore, the charge storage mechanism of V 2CT x material during Na + intercalation/deintercalation and the redox reaction of vanadium were studied using a combination of synchrotron based X-ray diffraction (XRD), hard X-ray absorption near edge spectroscopy (XANES) and soft X-ray absorption spectroscopy (sXAS). Experimental evidence of a major contribution ofmore » redox reaction of vanadium to the charge storage and the reversible capacity of V 2CT x during sodiation/desodiation process have been provided through V K-edge XANES and V L2,3-edge sXAS results. A correlation between the CO 3 2- content and Na + intercalation/deintercalation states in the V 2CT x electrode observed from C and O K-edge in sXAS results imply that some additional charge storage reactions may take place between the Na +-intercalated V 2CT x and the carbonate based non-aqueous electrolyte. Our results of this study will provide valuable information for the further studies on V 2CT x as anode material for Na-ion batteries and capacitors.« less
Na-Ion Intercalation and Charge Storage Mechanism in Two-Dimensional Vanadium Carbide
Bak, Seong -Min; Qiao, Ruimin; Yang, W.; ...
2017-07-14
We synthesized two-dimensional vanadium carbide MXene containing surface functional groups (denoted as V 2CT x, where T x are surface functional groups) and studied as anode material for Na-ion batteries. V 2CT x anode exhibits reversible charge storage with good cycling stability and high rate capability through electrochemical test. Furthermore, the charge storage mechanism of V 2CT x material during Na + intercalation/deintercalation and the redox reaction of vanadium were studied using a combination of synchrotron based X-ray diffraction (XRD), hard X-ray absorption near edge spectroscopy (XANES) and soft X-ray absorption spectroscopy (sXAS). Experimental evidence of a major contribution ofmore » redox reaction of vanadium to the charge storage and the reversible capacity of V 2CT x during sodiation/desodiation process have been provided through V K-edge XANES and V L2,3-edge sXAS results. A correlation between the CO 3 2- content and Na + intercalation/deintercalation states in the V 2CT x electrode observed from C and O K-edge in sXAS results imply that some additional charge storage reactions may take place between the Na +-intercalated V 2CT x and the carbonate based non-aqueous electrolyte. Our results of this study will provide valuable information for the further studies on V 2CT x as anode material for Na-ion batteries and capacitors.« less
NASA Astrophysics Data System (ADS)
Jang, Yujin; Hong, Helen; Chung, Jin Wook; Yoon, Young Ho
2012-02-01
We propose an effective technique for the extraction of liver boundary based on multi-planar anatomy and deformable surface model in abdominal contrast-enhanced CT images. Our method is composed of four main steps. First, for extracting an optimal volume circumscribing a liver, lower and side boundaries are defined by positional information of pelvis and rib. An upper boundary is defined by separating the lungs and heart from CT images. Second, for extracting an initial liver volume, optimal liver volume is smoothed by anisotropic diffusion filtering and is segmented using adaptively selected threshold value. Third, for removing neighbor organs from initial liver volume, morphological opening and connected component labeling are applied to multiple planes. Finally, for refining the liver boundaries, deformable surface model is applied to a posterior liver surface and missing left robe in previous step. Then, probability summation map is generated by calculating regional information of the segmented liver in coronal plane, which is used for restoring the inaccurate liver boundaries. Experimental results show that our segmentation method can accurately extract liver boundaries without leakage to neighbor organs in spite of various liver shape and ambiguous boundary.
Cui, Licong; Bodenreider, Olivier; Shi, Jay; Zhang, Guo-Qiang
2018-02-01
We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develop a scalable and effective approach that automatically identifies missing hierarchical IS-A relations. Our approach involves 3 stages. In stage 1, all non-lattice subgraphs of SNOMED CT's IS-A hierarchical relations are extracted. In stage 2, lexical attributes of fully-specified concept names in such non-lattice subgraphs are extracted. For each concept in a non-lattice subgraph, we enrich its set of attributes with attributes from its ancestor concepts within the non-lattice subgraph. In stage 3, subset inclusion relations between the lexical attribute sets of each pair of concepts in each non-lattice subgraph are compared to existing IS-A relations in SNOMED CT. For concept pairs within each non-lattice subgraph, if a subset relation is identified but an IS-A relation is not present in SNOMED CT IS-A transitive closure, then a missing IS-A relation is reported. The September 2017 release of SNOMED CT (US edition) was used in this investigation. A total of 14,380 non-lattice subgraphs were extracted, from which we suggested a total of 41,357 missing IS-A relations. For evaluation purposes, 200 non-lattice subgraphs were randomly selected from 996 smaller subgraphs (of size 4, 5, or 6) within the "Clinical Finding" and "Procedure" sub-hierarchies. Two domain experts confirmed 185 (among 223) suggested missing IS-A relations, a precision of 82.96%. Our results demonstrate that analyzing the lexical features of concepts in non-lattice subgraphs is an effective approach for auditing SNOMED CT. Copyright © 2017 Elsevier Inc. All rights reserved.
McLean, Michelle; Murrell, Kathy
2002-03-01
WebCT, front-end software for Internet-delivered material, became an integral part of a problem-based learning, student-centred curriculum introduced in January 2001 at the Nelson R. Mandela School of Medicine (South Africa). A template for six curriculum and two supplementary modules was developed. Organiser and Tool pages were added and files uploaded as each module progressed. This study provides feedback from students with regard to the value of WebCT in their curriculum, as well as discussing the value of WebCT for the delivery of digitized material (e.g., images, videos, PowerPoint presentations). In an anonymous survey following the completion of the first module, students, apparently irrespective of their level of computer literacy, responded positively to the communication facility between staff and students and amongst students, the resources and the URLs. Based on these preliminary responses, WebCT courses for all six modules were developed during 2001. With Faculty support, WebCT will probably be integrated into the rest of the MBChB programme. It will be particularly useful when students are off campus, undertaking electives and community service in the later years.
Berenguer, Roberto; Pastor-Juan, María Del Rosario; Canales-Vázquez, Jesús; Castro-García, Miguel; Villas, María Victoria; Legorburo, Francisco Mansilla; Sabater, Sebastià
2018-04-24
Purpose To identify the reproducible and nonredundant radiomics features (RFs) for computed tomography (CT). Materials and Methods Two phantoms were used to test RF reproducibility by using test-retest analysis, by changing the CT acquisition parameters (hereafter, intra-CT analysis), and by comparing five different scanners with the same CT parameters (hereafter, inter-CT analysis). Reproducible RFs were selected by using the concordance correlation coefficient (as a measure of the agreement between variables) and the coefficient of variation (defined as the ratio of the standard deviation to the mean). Redundant features were grouped by using hierarchical cluster analysis. Results A total of 177 RFs including intensity, shape, and texture features were evaluated. The test-retest analysis showed that 91% (161 of 177) of the RFs were reproducible according to concordance correlation coefficient. Reproducibility of intra-CT RFs, based on coefficient of variation, ranged from 89.3% (151 of 177) to 43.1% (76 of 177) where the pitch factor and the reconstruction kernel were modified, respectively. Reproducibility of inter-CT RFs, based on coefficient of variation, also showed large material differences, from 85.3% (151 of 177; wood) to only 15.8% (28 of 177; polyurethane). Ten clusters were identified after the hierarchical cluster analysis and one RF per cluster was chosen as representative. Conclusion Many RFs were redundant and nonreproducible. If all the CT parameters are fixed except field of view, tube voltage, and milliamperage, then the information provided by the analyzed RFs can be summarized in only 10 RFs (each representing a cluster) because of redundancy. © RSNA, 2018 Online supplemental material is available for this article.
SNOMED CT module-driven clinical archetype management.
Allones, J L; Taboada, M; Martinez, D; Lozano, R; Sobrido, M J
2013-06-01
To explore semantic search to improve management and user navigation in clinical archetype repositories. In order to support semantic searches across archetypes, an automated method based on SNOMED CT modularization is implemented to transform clinical archetypes into SNOMED CT extracts. Concurrently, query terms are converted into SNOMED CT concepts using the search engine Lucene. Retrieval is then carried out by matching query concepts with the corresponding SNOMED CT segments. A test collection of the 16 clinical archetypes, including over 250 terms, and a subset of 55 clinical terms from two medical dictionaries, MediLexicon and MedlinePlus, were used to test our method. The keyword-based service supported by the OpenEHR repository offered us a benchmark to evaluate the enhancement of performance. In total, our approach reached 97.4% precision and 69.1% recall, providing a substantial improvement of recall (more than 70%) compared to the benchmark. Exploiting medical domain knowledge from ontologies such as SNOMED CT may overcome some limitations of the keyword-based systems and thus improve the search experience of repository users. An automated approach based on ontology segmentation is an efficient and feasible way for supporting modeling, management and user navigation in clinical archetype repositories. Copyright © 2013 Elsevier Inc. All rights reserved.
Feng, Zhichao; Rong, Pengfei; Cao, Peng; Zhou, Qingyu; Zhu, Wenwei; Yan, Zhimin; Liu, Qianyun; Wang, Wei
2018-04-01
To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC). This single-institutional retrospective study included 58 patients with pathologically proven small renal mass (17 in AMLwvf and 41 in RCC groups). Texture features were extracted from the largest possible tumorous regions of interest (ROIs) by manual segmentation in preoperative three-phase CT images. Interobserver reliability and the Mann-Whitney U test were applied to select features preliminarily. Then support vector machine with recursive feature elimination (SVM-RFE) and synthetic minority oversampling technique (SMOTE) were adopted to establish discriminative classifiers, and the performance of classifiers was assessed. Of the 42 extracted features, 16 candidate features showed significant intergroup differences (P < 0.05) and had good interobserver agreement. An optimal feature subset including 11 features was further selected by the SVM-RFE method. The SVM-RFE+SMOTE classifier achieved the best performance in discriminating between small AMLwvf and RCC, with the highest accuracy, sensitivity, specificity and AUC of 93.9 %, 87.8 %, 100 % and 0.955, respectively. Machine learning analysis of CT texture features can facilitate the accurate differentiation of small AMLwvf from RCC. • Although conventional CT is useful for diagnosis of SRMs, it has limitations. • Machine-learning based CT texture analysis facilitate differentiation of small AMLwvf from RCC. • The highest accuracy of SVM-RFE+SMOTE classifier reached 93.9 %. • Texture analysis combined with machine-learning methods might spare unnecessary surgery for AMLwvf.
NASA Astrophysics Data System (ADS)
Mechlem, Korbinian; Ehn, Sebastian; Sellerer, Thorsten; Pfeiffer, Franz; Noël, Peter B.
2017-03-01
In spectral computed tomography (spectral CT), the additional information about the energy dependence of attenuation coefficients can be exploited to generate material selective images. These images have found applications in various areas such as artifact reduction, quantitative imaging or clinical diagnosis. However, significant noise amplification on material decomposed images remains a fundamental problem of spectral CT. Most spectral CT algorithms separate the process of material decomposition and image reconstruction. Separating these steps is suboptimal because the full statistical information contained in the spectral tomographic measurements cannot be exploited. Statistical iterative reconstruction (SIR) techniques provide an alternative, mathematically elegant approach to obtaining material selective images with improved tradeoffs between noise and resolution. Furthermore, image reconstruction and material decomposition can be performed jointly. This is accomplished by a forward model which directly connects the (expected) spectral projection measurements and the material selective images. To obtain this forward model, detailed knowledge of the different photon energy spectra and the detector response was assumed in previous work. However, accurately determining the spectrum is often difficult in practice. In this work, a new algorithm for statistical iterative material decomposition is presented. It uses a semi-empirical forward model which relies on simple calibration measurements. Furthermore, an efficient optimization algorithm based on separable surrogate functions is employed. This partially negates one of the major shortcomings of SIR, namely high computational cost and long reconstruction times. Numerical simulations and real experiments show strongly improved image quality and reduced statistical bias compared to projection-based material decomposition.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friedrich, Jon M.; Rivers, Mark L.; Perlowitz, Michael A.
We show that synchrotron x-ray microtomography ({mu}CT) followed by digital data extraction can be used to examine the size distribution and particle morphologies of the polydisperse (750 to 2450 {micro}m diameter) particle size standard NIST 1019b. Our size distribution results are within errors of certified values with data collected at 19.5 {micro}m/voxel. One of the advantages of using {mu}CT to investigate the particles examined here is that the morphology of the glass beads can be directly examined. We use the shape metrics aspect ratio and sphericity to examine of individual standard beads morphologies as a function of spherical equivalent diameters.more » We find that the majority of standard beads possess near-spherical aspect ratios and sphericities, but deviations are present at the lower end of the size range. The majority (> 98%) of particles also possess an equant form when examined using a common measure of equidimensionality. Although the NIST 1019b standard consists of loose particles, we point out that an advantage of {mu}CT is that coherent materials comprised of particles can be examined without disaggregation.« less
Micro-CT and nano-CT analysis of filling quality of three different endodontic sealers.
Huang, Yan; Celikten, Berkan; de Faria Vasconcelos, Karla; Ferreira Pinheiro Nicolielo, Laura; Lippiatt, Nicholas; Buyuksungur, Arda; Jacobs, Reinhilde; Orhan, Kaan
2017-12-01
To investigate voids in different root canal sealers using micro-CT and nano-CT, and to explore the feasibility of using nano-CT for quantitative analysis of sealer filling quality. 30 extracted mandibular central incisors were randomly assigned into three groups according to the applied root canal sealers (Total BC Sealer, Sure Seal Root, AH Plus) by the single cone technique. Subsequently, micro-CT and nano-CT were performed to analyse the incidence rate of voids, void fraction, void volume and their distribution in each sample. Micro-CT evaluation showed no significant difference among sealers for the incidence rate of voids or void fraction in the whole filling materials (p > 0.05), whereas a significant difference was found between AH Plus and the other two sealers using nano-CT (p < 0.05). All three sealers presented less void volume in the apical third; however, higher void volumes were observed in the apical and coronal thirds in AH Plus using micro-CT (p < 0.05), while nano-CT results displayed higher void volume in AH Plus among all the sealers and regions (p < 0.05). Bioactive sealers showed higher root filling rate, lower incidence rate of voids, void fraction and void volume than AH Plus under nano-CT analysis, when round root canals were treated by the single cone technique. The disparate results suggest that the higher resolution of nano-CT have a greater ability of distinguishing internal porosity, and therefore suggesting the potential use of nano-CT in quantitative analysis of filling quality of sealers.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ushizima, Daniela M.; Bianchi, Andrea G. C.; DeBianchi, Christina
We introduce a computational analysis workflow to access properties of solid objects using nondestructive imaging techniques that rely on X-ray imaging. The goal is to process and quantify structures from material science sample cross sections. The algorithms can differentiate the porous media (high density material) from the void (background, low density media) using a Boolean classifier, so that we can extract features, such as volume, surface area, granularity spectrum, porosity, among others. Our workflow, Quant-CT, leverages several algorithms from ImageJ, such as statistical region merging and 3D object counter. It also includes schemes for bilateral filtering that use a 3Dmore » kernel, for parallel processing of sub-stacks, and for handling over-segmentation using histogram similarities. The Quant-CT supports fast user interaction, providing the ability for the user to train the algorithm via subsamples to feed its core algorithms with automated parameterization. Quant-CT plugin is currently available for testing by personnel at the Advanced Light Source and Earth Sciences Divisions and Energy Frontier Research Center (EFRC), LBNL, as part of their research on porous materials. The goal is to understand the processes in fluid-rock systems for the geologic sequestration of CO2, and to develop technology for the safe storage of CO2 in deep subsurface rock formations. We describe our implementation, and demonstrate our plugin on porous material images. This paper targets end-users, with relevant information for developers to extend its current capabilities.« less
Automated Agatston score computation in non-ECG gated CT scans using deep learning
NASA Astrophysics Data System (ADS)
Cano-Espinosa, Carlos; González, Germán.; Washko, George R.; Cazorla, Miguel; San José Estépar, Raúl
2018-03-01
Introduction: The Agatston score is a well-established metric of cardiovascular disease related to clinical outcomes. It is computed from CT scans by a) measuring the volume and intensity of the atherosclerotic plaques and b) aggregating such information in an index. Objective: To generate a convolutional neural network that inputs a non-contrast chest CT scan and outputs the Agatston score associated with it directly, without a prior segmentation of Coronary Artery Calcifications (CAC). Materials and methods: We use a database of 5973 non-contrast non-ECG gated chest CT scans where the Agatston score has been manually computed. The heart of each scan is cropped automatically using an object detector. The database is split in 4973 cases for training and 1000 for testing. We train a 3D deep convolutional neural network to regress the Agatston score directly from the extracted hearts. Results: The proposed method yields a Pearson correlation coefficient of r = 0.93; p <= 0.0001 against manual reference standard in the 1000 test cases. It further stratifies correctly 72.6% of the cases with respect to standard risk groups. This compares to more complex state-of-the-art methods based on prior segmentations of the CACs, which achieve r = 0.94 in ECG-gated pulmonary CT. Conclusions: A convolutional neural network can regress the Agatston score from the image of the heart directly, without a prior segmentation of the CACs. This is a new and simpler paradigm in the Agatston score computation that yields similar results to the state-of-the-art literature.
Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen
2014-01-01
Prognosis and diagnosis of cardiac diseases frequently require quantitative evaluation of the ventricle volume, mass, and ejection fraction. The delineation of the myocardial wall is involved in all of these evaluations, which is a challenging task due to large variations in myocardial shapes and image quality. In this work, we present an automatic method for extracting the myocardial wall of the left and right ventricles from cardiac CT images. In the method, the left and right ventricles are located sequentially, in which each ventricle is detected by first identifying the endocardium and then segmenting the epicardium. To this end, the endocardium is localized by utilizing its geometric features obtained on-line from a CT image. After that, a variational region-growing model is employed to extract the epicardium of the ventricles. In particular, the location of the endocardium of the left ventricle is determined via using an active contour model on the blood-pool surface. To localize the right ventricle, the active contour model is applied on a heart surface extracted based on the left ventricle segmentation result. The robustness and accuracy of the proposed approach is demonstrated by experimental results from 33 human and 12 pig CT images. PMID:23744658
NASA Astrophysics Data System (ADS)
Mu, Wei; Qi, Jin; Lu, Hong; Schabath, Matthew; Balagurunathan, Yoganand; Tunali, Ilke; Gillies, Robert James
2018-02-01
Purpose: Investigate the ability of using complementary information provided by the fusion of PET/CT images to predict immunotherapy response in non-small cell lung cancer (NSCLC) patients. Materials and methods: We collected 64 patients diagnosed with primary NSCLC treated with anti PD-1 checkpoint blockade. Using PET/CT images, fused images were created following multiple methodologies, resulting in up to 7 different images for the tumor region. Quantitative image features were extracted from the primary image (PET/CT) and the fused images, which included 195 from primary images and 1235 features from the fusion images. Three clinical characteristics were also analyzed. We then used support vector machine (SVM) classification models to identify discriminant features that predict immunotherapy response at baseline. Results: A SVM built with 87 fusion features and 13 primary PET/CT features on validation dataset had an accuracy and area under the ROC curve (AUROC) of 87.5% and 0.82, respectively, compared to a model built with 113 original PET/CT features on validation dataset 78.12% and 0.68. Conclusion: The fusion features shows better ability to predict immunotherapy response prediction compared to individual image features.
MO-AB-BRA-05: [18F]NaF PET/CT Imaging Biomarkers in Metastatic Prostate Cancer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harmon, S; Perk, T; Lin, C
Purpose: Clinical use of {sup 18}F-Sodium Fluoride (NaF) PET/CT in metastatic settings often lacks technology to quantitatively measure full disease dynamics due to high tumor burden. This study assesses radiomics-based extraction of NaF PET/CT measures, including global metrics of overall burden and local metrics of disease heterogeneity, in metastatic prostate cancer for correlation to clinical outcomes. Methods: Fifty-six metastatic Castrate-Resistant Prostate Cancer (mCRPC) patients had NaF PET/CT scans performed at baseline and three cycles into chemotherapy (N=16) or androgen-receptor (AR) inhibitors (N=39). A novel technology, Quantitative Total Bone Imaging (QTBI), was used for analysis. Employing hybrid PET/CT segmentation and articulatedmore » skeletal-registration, QTBI allows for response assessment of individual lesions. Various SUV metrics were extracted from each lesion (iSUV). Global metrics were extracted from composite lesion-level statistics for each patient (pSUV). Proportion of detected lesions and those with significant response (%-increase or %-decrease) was calculated for each patient based on test-retest limits for iSUV metrics. Cox proportional hazard regression analyses were conducted between imaging metrics and progression-free survival (PFS). Results: Functional burden (pSUV{sub total}) assessed mid-treatment was the strongest univariate predictor of PFS (HR=2.03; p<0.0001). Various global metrics outperformed baseline clinical markers, including fraction of skeletal burden, mean uptake (pSUV{sub mean}), and heterogeneity of average lesion uptake (pSUV{sub hetero}). Of 43 patients with paired baseline/mid-treatment imaging, 40 showed heterogeneity in lesion-level response, containing populations of lesions with both increasing/decreasing metrics. Proportion of lesions with significantly increasing iSUV{sub mean} was highly predictive of clinical PFS (HR=2.0; p=0.0002). Patients exhibiting higher proportion of lesions with decreasing iSUV{sub total} saw prolonged radiographic PFS (HR=0.51; p=0.02). Conclusion: Technology presented here provides comprehensive disease quantification on NaF PET/CT imaging, showing strong correlation to clinical outcomes. Total functional burden as well as proportions of similarly responding lesions was predictive of PFS. This supports ongoing development of NaF PET/CT based imaging biomarkers in mCRPC. Prostate Cancer Foundation.« less
Moroi, Akinori; Yoshizawa, Kunio; Iguchi, Ran; Hiroumi, Ikawa; Kosaka, Akihiko; Hotta, Asami; Tsutsui, Takamitsu; Saita, Yuriko; Ueki, Koichiro
2015-09-01
The purpose of this study was to evaluate, through cephalometric analysis, the skeletal stability following BSSRO performed with and without extraction of the third molar, and to examine the healing of the extraction sockets through computed tomography (CT). Sixty Japanese patients (male: 14, female: 46) diagnosed with mandibular prognathism were included in this study. While 30 patients underwent BSSRO along with extraction of the third molar (extraction group), the other 30 patients underwent BSSRO alone (non-extraction group). Skeletal stability was assessed using axial, frontal, and lateral cephalograms. CT scans were obtained 1 week after surgery and at the 1-year follow-up for all the patients. CT value was measured at the point of the extraction socket on the horizontal plane parallel to the Frankfurt plane using computer software (SimPlant 2011; Materialise Dental, Leuven, Belgium). The region of interest (ROI) was approximately 4 mm(2) and the mean value was recorded. Healing of the extraction sockets was examined through CT 1 year postoperatively. There were no significant differences between the groups for any of the parameters at any observation interval. In the extraction group, there were significant differences between the values of CT obtained 1 week postoperatively and 1 year postoperatively in the extraction socket (P = 0.0003). The results of this study indicate that there is no significant difference in the skeletal stability between BSSRO performed with and without third molar extraction. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
Gastric and enteric anisakiasis successfully treated with Gastrografin therapy: A case report.
Fujikawa, Hiroki; Kuwai, Toshio; Yamaguchi, Toshiki; Miura, Ryoichi; Sumida, Yuki; Takasago, Takeshi; Miyasako, Yuki; Nishimura, Tomoyuki; Iio, Sumio; Imagawa, Hiroki; Yamaguchi, Atsushi; Kouno, Hirotaka; Kohno, Hiroshi
2018-03-16
We report a case of a 59-year-old woman who was diagnosed with gastric and small intestinal anisakiasis, which was successfully treated with endoscopic extraction and Gastrografin therapy. She was admitted to our hospital with epigastric pain and vomiting one day after eating raw fish. She exhibited tenderness in the epigastrium without obvious rebound tenderness or guarding. Computed tomography (CT) demonstrated segmental edema of the intestinal wall with proximal dilatation and a small number of ascites. Because enteric anisakiasis was suspected based on the patient's history of recent raw fish consumption and abdominal CT, we performed gastroscopy and confirmed that nine Anisakis larvae were attached to the gastric mucosa. All of the Anisakis larvae were extracted via endoscopy, and the patient was diagnosed with gastric and enteric anisakiasis. Additionally, in the hospital, we performed ileography twice using Gastrografin, which led to shortened hospital stay. Based on the clinical results of this case, we suggest that Gastrografin therapy is a safe, convenient, and useful method to extract enteric Anisakis larvae.
NASA Astrophysics Data System (ADS)
Zhang, Dong Ping; Edwards, Eddie; Mei, Lin; Rueckert, Daniel
2009-02-01
In this paper, we present a novel approach for coronary artery motion modeling from cardiac Computed Tomography( CT) images. The aim of this work is to develop a 4D motion model of the coronaries for image guidance in robotic-assisted totally endoscopic coronary artery bypass (TECAB) surgery. To utilize the pre-operative cardiac images to guide the minimally invasive surgery, it is essential to have a 4D cardiac motion model to be registered with the stereo endoscopic images acquired intraoperatively using the da Vinci robotic system. In this paper, we are investigating the extraction of the coronary arteries and the modelling of their motion from a dynamic sequence of cardiac CT. We use a multi-scale vesselness filter to enhance vessels in the cardiac CT images. The centerlines of the arteries are extracted using a ridge traversal algorithm. Using this method the coronaries can be extracted in near real-time as only local information is used in vessel tracking. To compute the deformation of the coronaries due to cardiac motion, the motion is extracted from a dynamic sequence of cardiac CT. Each timeframe in this sequence is registered to the end-diastole timeframe of the sequence using a non-rigid registration algorithm based on free-form deformations. Once the images have been registered a dynamic motion model of the coronaries can be obtained by applying the computed free-form deformations to the extracted coronary arteries. To validate the accuracy of the motion model we compare the actual position of the coronaries in each time frame with the predicted position of the coronaries as estimated from the non-rigid registration. We expect that this motion model of coronaries can facilitate the planning of TECAB surgery, and through the registration with real-time endoscopic video images it can reduce the conversion rate from TECAB to conventional procedures.
Meng, Qier; Kitasaka, Takayuki; Nimura, Yukitaka; Oda, Masahiro; Ueno, Junji; Mori, Kensaku
2017-02-01
Airway segmentation plays an important role in analyzing chest computed tomography (CT) volumes for computerized lung cancer detection, emphysema diagnosis and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3D airway tree structure from a CT volume is quite a challenging task. Several researchers have proposed automated airway segmentation algorithms basically based on region growing and machine learning techniques. However, these methods fail to detect the peripheral bronchial branches, which results in a large amount of leakage. This paper presents a novel approach for more accurate extraction of the complex airway tree. This proposed segmentation method is composed of three steps. First, Hessian analysis is utilized to enhance the tube-like structure in CT volumes; then, an adaptive multiscale cavity enhancement filter is employed to detect the cavity-like structure with different radii. In the second step, support vector machine learning will be utilized to remove the false positive (FP) regions from the result obtained in the previous step. Finally, the graph-cut algorithm is used to refine the candidate voxels to form an integrated airway tree. A test dataset including 50 standard-dose chest CT volumes was used for evaluating our proposed method. The average extraction rate was about 79.1 % with the significantly decreased FP rate. A new method of airway segmentation based on local intensity structure and machine learning technique was developed. The method was shown to be feasible for airway segmentation in a computer-aided diagnosis system for a lung and bronchoscope guidance system.
Dictionary learning-based CT detection of pulmonary nodules
NASA Astrophysics Data System (ADS)
Wu, Panpan; Xia, Kewen; Zhang, Yanbo; Qian, Xiaohua; Wang, Ge; Yu, Hengyong
2016-10-01
Segmentation of lung features is one of the most important steps for computer-aided detection (CAD) of pulmonary nodules with computed tomography (CT). However, irregular shapes, complicated anatomical background and poor pulmonary nodule contrast make CAD a very challenging problem. Here, we propose a novel scheme for feature extraction and classification of pulmonary nodules through dictionary learning from training CT images, which does not require accurately segmented pulmonary nodules. Specifically, two classification-oriented dictionaries and one background dictionary are learnt to solve a two-category problem. In terms of the classification-oriented dictionaries, we calculate sparse coefficient matrices to extract intrinsic features for pulmonary nodule classification. The support vector machine (SVM) classifier is then designed to optimize the performance. Our proposed methodology is evaluated with the lung image database consortium and image database resource initiative (LIDC-IDRI) database, and the results demonstrate that the proposed strategy is promising.
WE-EF-207-09: Single-Scan Dual-Energy CT Using Primary Modulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Petrongolo, M; Zhu, L
Purpose: Compared with conventional CT, dual energy CT (DECT) provides better material differentiation but requires projection data with two different effective x-ray spectra. Current DECT scanners use either a two-scan setting or costly imaging components, which are not feasible or available on open-gantry cone-beam CT systems. We propose a hardware-based method which utilizes primary modulation to enable single-scan DECT on a conventional CT scanner. The CT imaging geometry of primary modulation is identical to that used in our previous method for scatter removal, making it possible for future combination with effective scatter correction on the same CT scanner. Methods: Wemore » insert an attenuation sheet with a spatially-varying pattern - primary modulator-between the x-ray source and the imaged object. During the CT scan, the modulator selectively hardens the x-ray beam at specific detector locations. Thus, the proposed method simultaneously acquires high and low energy data. High and low energy CT images are then reconstructed from projections with missing data via an iterative CT reconstruction algorithm with gradient weighting. Proof-of-concept studies are performed using a copper modulator on a cone-beam CT system. Results: Our preliminary results on the Catphan(c) 600 phantom indicate that the proposed method for single-scan DECT is able to successfully generate high-quality high and low energy CT images and distinguish different materials through basis material decomposition. By applying correction algorithms and using all of the acquired projection data, we can reconstruct a single CT image of comparable image quality to conventional CT images, i.e., without primary modulation. Conclusion: This work shows great promise in using a primary modulator to perform high-quality single-scan DECT imaging. Future studies will test method performance on anthropomorphic phantoms and perform quantitative analyses on image qualities and DECT decomposition accuracy. We will use simulations to optimize the modulator material and geometry parameters.« less
... is mixed with water before administration liquid paste tablet When iodine-based and barium-sulfate contrast materials ... for patients with kidney failure or allergies to MRI and/or computed tomography (CT) contrast material. Microbubble ...
Wooden Foreign Body in the Skull Base: How Did We Miss It?
Jusué-Torres, Ignacio; Burks, S Shelby; Levine, Corinna G; Bhatia, Rita G; Casiano, Roy; Bullock, Ross
2016-08-01
Timely detection of intraorbital and skull base wooden foreign bodies is crucial. Wooden foreign bodies are difficult to detect on imaging. The radiologist may fail to identify wooden foreign bodies on two thirds of initial scans and can miss them in almost one third of total cases. A 66-year-old woman sustained a penetrating injury through the left upper eyelid with a small tree branch. The branch was immediately removed in the field, and she was provided with prompt medical care at a local hospital. Initial computed tomography (CT) scan diagnosis was "posttraumatic sinusitis," and this was treated empirically with vancomycin and piperacillin/tazobactam. On the eighth day after injury, she developed progressive swelling and pain of her eyelid with left trigeminal/supraorbital numbness and complete left ophthalmoplegia. A new CT scan showed an open "track" from the region of the left upper orbit/superior rectus to the contralateral sphenoid sinus, which raised suspicion for a retained foreign body. Further imaging confirmed the suspicion. Endoscopic sinus surgery was performed with extraction of the wooden object and evacuation of the left orbital infection. This case indicates that intraorbital and skull base wooden foreign bodies are elusive, demanding a high index of suspicion from both clinicians and radiologists to identify retained material in the setting of ocular or sinus trauma. For better identification of wooden foreign bodies, bone windows on CT should have a width of -1000 Hounsfield units with a soft tissue window level of -500 Hounsfield units. Published by Elsevier Inc.
Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen
2014-01-01
The left ventricular myocardium plays a key role in the entire circulation system and an automatic delineation of the myocardium is a prerequisite for most of the subsequent functional analysis. In this paper, we present a complete system for an automatic segmentation of the left ventricular myocardium from cardiac computed tomography (CT) images using the shape information from images to be segmented. The system follows a coarse-to-fine strategy by first localizing the left ventricle and then deforming the myocardial surfaces of the left ventricle to refine the segmentation. In particular, the blood pool of a CT image is extracted and represented as a triangulated surface. Then, the left ventricle is localized as a salient component on this surface using geometric and anatomical characteristics. After that, the myocardial surfaces are initialized from the localization result and evolved by applying forces from the image intensities with a constraint based on the initial myocardial surface locations. The proposed framework has been validated on 34-human and 12-pig CT images, and the robustness and accuracy are demonstrated. PMID:24723531
Ruth, Veikko; Kolditz, Daniel; Steiding, Christian; Kalender, Willi A
2017-06-01
The performance of metal artifact reduction (MAR) methods in x-ray computed tomography (CT) suffers from incorrect identification of metallic implants in the artifact-affected volumetric images. The aim of this study was to investigate potential improvements of state-of-the-art MAR methods by using prior information on geometry and material of the implant. The influence of a novel prior knowledge-based segmentation (PS) compared with threshold-based segmentation (TS) on 2 MAR methods (linear interpolation [LI] and normalized-MAR [NORMAR]) was investigated. The segmentation is the initial step of both MAR methods. Prior knowledge-based segmentation uses 3-dimensional registered computer-aided design (CAD) data as prior knowledge to estimate the correct position and orientation of the metallic objects. Threshold-based segmentation uses an adaptive threshold to identify metal. Subsequently, for LI and NORMAR, the selected voxels are projected into the raw data domain to mark metal areas. Attenuation values in these areas are replaced by different interpolation schemes followed by a second reconstruction. Finally, the previously selected metal voxels are replaced by the metal voxels determined by PS or TS in the initial reconstruction. First, we investigated in an elaborate phantom study if the knowledge of the exact implant shape extracted from the CAD data provided by the manufacturer of the implant can improve the MAR result. Second, the leg of a human cadaver was scanned using a clinical CT system before and after the implantation of an artificial knee joint. The results were compared regarding segmentation accuracy, CT number accuracy, and the restoration of distorted structures. The use of PS improved the efficacy of LI and NORMAR compared with TS. Artifacts caused by insufficient segmentation were reduced, and additional information was made available within the projection data. The estimation of the implant shape was more exact and not dependent on a threshold value. Consequently, the visibility of structures was improved when comparing the new approach to the standard method. This was further confirmed by improved CT value accuracy and reduced image noise. The PS approach based on prior implant information provides image quality which is superior to TS-based MAR, especially when the shape of the metallic implant is complex. The new approach can be useful for improving MAR methods and dose calculations within radiation therapy based on the MAR corrected CT images.
Deep Learning MR Imaging-based Attenuation Correction for PET/MR Imaging.
Liu, Fang; Jang, Hyungseok; Kijowski, Richard; Bradshaw, Tyler; McMillan, Alan B
2018-02-01
Purpose To develop and evaluate the feasibility of deep learning approaches for magnetic resonance (MR) imaging-based attenuation correction (AC) (termed deep MRAC) in brain positron emission tomography (PET)/MR imaging. Materials and Methods A PET/MR imaging AC pipeline was built by using a deep learning approach to generate pseudo computed tomographic (CT) scans from MR images. A deep convolutional auto-encoder network was trained to identify air, bone, and soft tissue in volumetric head MR images coregistered to CT data for training. A set of 30 retrospective three-dimensional T1-weighted head images was used to train the model, which was then evaluated in 10 patients by comparing the generated pseudo CT scan to an acquired CT scan. A prospective study was carried out for utilizing simultaneous PET/MR imaging for five subjects by using the proposed approach. Analysis of covariance and paired-sample t tests were used for statistical analysis to compare PET reconstruction error with deep MRAC and two existing MR imaging-based AC approaches with CT-based AC. Results Deep MRAC provides an accurate pseudo CT scan with a mean Dice coefficient of 0.971 ± 0.005 for air, 0.936 ± 0.011 for soft tissue, and 0.803 ± 0.021 for bone. Furthermore, deep MRAC provides good PET results, with average errors of less than 1% in most brain regions. Significantly lower PET reconstruction errors were realized with deep MRAC (-0.7% ± 1.1) compared with Dixon-based soft-tissue and air segmentation (-5.8% ± 3.1) and anatomic CT-based template registration (-4.8% ± 2.2). Conclusion The authors developed an automated approach that allows generation of discrete-valued pseudo CT scans (soft tissue, bone, and air) from a single high-spatial-resolution diagnostic-quality three-dimensional MR image and evaluated it in brain PET/MR imaging. This deep learning approach for MR imaging-based AC provided reduced PET reconstruction error relative to a CT-based standard within the brain compared with current MR imaging-based AC approaches. © RSNA, 2017 Online supplemental material is available for this article.
NASA Astrophysics Data System (ADS)
Wibowo, W. E.; Waliyyulhaq, M.; Pawiro, S. A.
2017-05-01
Patient-specific Quality Assurance (QA) technique in lung case Intensity-Modulated Radiation Therapy (IMRT) is traditionally limited to homogeneous material, although the fact that the planning is carried out with inhomogeneous material present. Moreover, the chest area has many of inhomogeneous material, such as lung, soft tissue, and bone, which inhomogeneous material requires special attention to avoid inaccuracies in dose calculation in the Treatment Planning System (TPS). Recent preliminary studies shown that the role of Cone Beam CT (CBCT) can be used not only to position the patient at the time prior to irradiation but also to serve as planning modality. Our study presented the influence of a homogeneous and inhomogeneous materials using Fan Beam CT and Cone Beam CT modalities in IMRT technique on the Gamma Index (GI) value. We used a variation of the segment and Calculation Grid Resolution (CGR). The results showed the deviation of averaged GI value to be between CGR 0.2 cm and 0.4 cm with homogeneous material ranging from -0.44% to 1.46%. For inhomogeneous material, the value was range from -1.74% to 0.98%. In performing patient-specific IMRT QA techniques for lung cancer, homogeneous material can be implemented in evaluating the gamma index.
Hori, Masatoshi; Suzuki, Kenji; Epstein, Mark L.; Baron, Richard L.
2011-01-01
The purpose was to evaluate a relationship between slice thickness and calculated volume on CT liver volumetry by comparing the results for images with various slice thicknesses including three-dimensional images. Twenty adult potential liver donors (12 men, 8 women; mean age, 39 years; range, 24–64) underwent CT with a 64-section multi-detector row CT scanner after intra-venous injection of contrast material. Four image sets with slice thicknesses of 0.625 mm, 2.5 mm, 5 mm, and 10 mm were used. First, a program developed in our laboratory for automated liver extraction was applied to CT images, and the liver boundary was obtained automatically. Then, an abdominal radiologist reviewed all images on which automatically extracted boundaries were superimposed, and edited the boundary on each slice to enhance the accuracy. Liver volumes were determined by counting of the voxels within the liver boundary. Mean whole liver volumes estimated with CT were 1322.5 cm3 on 0.625-mm, 1313.3 cm3 on 2.5-mm, 1310.3 cm3 on 5-mm, and 1268.2 cm3 on 10-mm images. Volumes calculated for three-dimensional (0.625-mm-thick) images were significantly larger than those for thicker images (P<.0001). Partial liver volumes of right lobe, left lobe, and lateral segment were also evaluated in a similar manner. Estimated maximum differences in calculated volumes of lateral segment was −10.9 cm3 (−4.6%) between 0.625-mm and 5-mm images. In conclusion, liver volumes calculated on 2.5-mm or thicker images were significantly smaller than volumes calculated on three-dimensional images. If a maximum error of 5% in the calculated graft volume is within the range of having an insignificant clinical impact, 5-mm thick images are acceptable for CT volumetry. If not, three-dimensional images could be essential. PMID:21850689
Ikuta, Ichiro; Warden, Graham I.; Andriole, Katherine P.; Khorasani, Ramin
2014-01-01
Purpose To test the hypothesis that patient size can be accurately calculated from axial computed tomographic (CT) images, including correction for the effects of anatomy truncation that occur in routine clinical CT image reconstruction. Materials and Methods Institutional review board approval was obtained for this HIPAA-compliant study, with waiver of informed consent. Water-equivalent diameter (DW) was computed from the attenuation-area product of each image within 50 adult CT scans of the thorax and of the abdomen and pelvis and was also measured for maximal field of view (FOV) reconstructions. Linear regression models were created to compare DW with the effective diameter (Deff) used to select size-specific volume CT dose index (CTDIvol) conversion factors as defined in report 204 of the American Association of Physicists in Medicine. Linear regression models relating reductions in measured DW to a metric of anatomy truncation were used to compensate for the effects of clinical image truncation. Results In the thorax, DW versus Deff had an R2 of 0.51 (n = 200, 50 patients at four anatomic locations); in the abdomen and pelvis, R2 was 0.90 (n = 150, 50 patients at three anatomic locations). By correcting for image truncation, the proportion of clinically reconstructed images with an extracted DW within ±5% of the maximal FOV DW increased from 54% to 90% in the thorax (n = 3602 images) and from 95% to 100% in the abdomen and pelvis (6181 images). Conclusion The DW extracted from axial CT images is a reliable measure of patient size, and varying degrees of clinical image truncation can be readily corrected. Automated measurement of patient size combined with CT radiation exposure metrics may enable patient-specific dose estimation on a large scale. © RSNA, 2013 PMID:24086075
Algorithm of pulmonary emphysema extraction using thoracic 3D CT images
NASA Astrophysics Data System (ADS)
Saita, Shinsuke; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Nakano, Yasutaka; Ohmatsu, Hironobu; Tominaga, Keigo; Eguchi, Kenji; Moriyama, Noriyuki
2007-03-01
Recently, due to aging and smoking, emphysema patients are increasing. The restoration of alveolus which was destroyed by emphysema is not possible, thus early detection of emphysema is desired. We describe a quantitative algorithm for extracting emphysematous lesions and quantitatively evaluate their distribution patterns using low dose thoracic 3-D CT images. The algorithm identified lung anatomies, and extracted low attenuation area (LAA) as emphysematous lesion candidates. Applying the algorithm to thoracic 3-D CT images and then by follow-up 3-D CT images, we demonstrate its potential effectiveness to assist radiologists and physicians to quantitatively evaluate the emphysematous lesions distribution and their evolution in time interval changes.
Algorithm of pulmonary emphysema extraction using low dose thoracic 3D CT images
NASA Astrophysics Data System (ADS)
Saita, S.; Kubo, M.; Kawata, Y.; Niki, N.; Nakano, Y.; Omatsu, H.; Tominaga, K.; Eguchi, K.; Moriyama, N.
2006-03-01
Recently, due to aging and smoking, emphysema patients are increasing. The restoration of alveolus which was destroyed by emphysema is not possible, thus early detection of emphysema is desired. We describe a quantitative algorithm for extracting emphysematous lesions and quantitatively evaluate their distribution patterns using low dose thoracic 3-D CT images. The algorithm identified lung anatomies, and extracted low attenuation area (LAA) as emphysematous lesion candidates. Applying the algorithm to 100 thoracic 3-D CT images and then by follow-up 3-D CT images, we demonstrate its potential effectiveness to assist radiologists and physicians to quantitatively evaluate the emphysematous lesions distribution and their evolution in time interval changes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krafft, S; Court, L; Briere, T
2014-06-15
Purpose: Radiation induced lung damage (RILD) is an important dose-limiting toxicity for patients treated with radiation therapy. Scoring systems for RILD are subjective and limit our ability to find robust predictors of toxicity. We investigate the dose and time-related response for texture-based lung CT image features that serve as potential quantitative measures of RILD. Methods: Pre- and post-RT diagnostic imaging studies were collected for retrospective analysis of 21 patients treated with photon or proton radiotherapy for NSCLC. Total lung and selected isodose contours (0–5, 5–15, 15–25Gy, etc.) were deformably registered from the treatment planning scan to the pre-RT and availablemore » follow-up CT studies for each patient. A CT image analysis framework was utilized to extract 3698 unique texture-based features (including co-occurrence and run length matrices) for each region of interest defined by the isodose contours and the total lung volume. Linear mixed models were fit to determine the relationship between feature change (relative to pre-RT), planned dose and time post-RT. Results: Seventy-three follow-up CT scans from 21 patients (median: 3 scans/patient) were analyzed to describe CT image feature change. At the p=0.05 level, dose affected feature change in 2706 (73.1%) of the available features. Similarly, time affected feature change in 408 (11.0%) of the available features. Both dose and time were significant predictors of feature change in a total of 231 (6.2%) of the extracted image features. Conclusion: Characterizing the dose and time-related response of a large number of texture-based CT image features is the first step toward identifying objective measures of lung toxicity necessary for assessment and prediction of RILD. There is evidence that numerous features are sensitive to both the radiation dose and time after RT. Beyond characterizing feature response, further investigation is warranted to determine the utility of these features as surrogates of clinically significant lung injury.« less
Friesen, Melissa C.; Wheeler, David C.; Vermeulen, Roel; Locke, Sarah J.; Zaebst, Dennis D.; Koutros, Stella; Pronk, Anjoeka; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Malats, Nuria; Schwenn, Molly; Johnson, Alison; Armenti, Karla R.; Rothman, Nathanial; Stewart, Patricia A.; Kogevinas, Manolis; Silverman, Debra T.
2016-01-01
Objectives: To efficiently and reproducibly assess occupational diesel exhaust exposure in a Spanish case-control study, we examined the utility of applying decision rules that had been extracted from expert estimates and questionnaire response patterns using classification tree (CT) models from a similar US study. Methods: First, previously extracted CT decision rules were used to obtain initial ordinal (0–3) estimates of the probability, intensity, and frequency of occupational exposure to diesel exhaust for the 10 182 jobs reported in a Spanish case-control study of bladder cancer. Second, two experts reviewed the CT estimates for 350 jobs randomly selected from strata based on each CT rule’s agreement with the expert ratings in the original study [agreement rate, from 0 (no agreement) to 1 (perfect agreement)]. Their agreement with each other and with the CT estimates was calculated using weighted kappa (κ w) and guided our choice of jobs for subsequent expert review. Third, an expert review comprised all jobs with lower confidence (low-to-moderate agreement rates or discordant assignments, n = 931) and a subset of jobs with a moderate to high CT probability rating and with moderately high agreement rates (n = 511). Logistic regression was used to examine the likelihood that an expert provided a different estimate than the CT estimate based on the CT rule agreement rates, the CT ordinal rating, and the availability of a module with diesel-related questions. Results: Agreement between estimates made by two experts and between estimates made by each of the experts and the CT estimates was very high for jobs with estimates that were determined by rules with high CT agreement rates (κ w: 0.81–0.90). For jobs with estimates based on rules with lower agreement rates, moderate agreement was observed between the two experts (κ w: 0.42–0.67) and poor-to-moderate agreement was observed between the experts and the CT estimates (κ w: 0.09–0.57). In total, the expert review of 1442 jobs changed 156 probability estimates, 128 intensity estimates, and 614 frequency estimates. The expert was more likely to provide a different estimate when the CT rule agreement rate was <0.8, when the CT ordinal ratings were low to moderate, or when a module with diesel questions was available. Conclusions: Our reliability assessment provided important insight into where to prioritize additional expert review; as a result, only 14% of the jobs underwent expert review, substantially reducing the exposure assessment burden. Overall, we found that we could efficiently, reproducibly, and reliably apply CT decision rules from one study to assess exposure in another study. PMID:26732820
Retardation of quality changes in camel meat sausages by phenolic compounds and phenolic extracts.
Maqsood, Sajid; Manheem, Kusaimah; Abushelaibi, Aisha; Kadim, Isam Tawfik
2016-11-01
Impact of tannic acid (TA), date seed extract (DSE), catechin (CT) and green tea extract (GTE) on lipid oxidation, microbial load and textural properties of camel meat sausages during 12 days of refrigerated storage was investigated. TA and CT showed higher activities in all antioxidative assays compared to DSE and GTE. Lipid oxidation and microbial growth was higher for control sausages when compared to other samples. TA and CT at a level of 200 mg/kg were more effective in retarding lipid oxidation and lowering microbial count (P < 0.05). Sausages treated with TA and DSE were found to have higher hardness, gumminess and chewiness values compared to other treatments (P < 0.05). Addition of different phenolic compounds or extract did not influence the sensory color of sausages. Furthermore, sensory quality was also found to be superior in TA and CT treated sausages. Therefore, pure phenolic compounds (TA and CT) proved to be more effective in retaining microbial and sensorial qualities of camel meat sausages compared to phenolic extracts (GTE and DSE) over 12 days of storage at 4°C. © 2016 Japanese Society of Animal Science.
Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Wismüller, Axel
2015-01-01
Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns.
Yang, Y X; Teo, S-K; Van Reeth, E; Tan, C H; Tham, I W K; Poh, C L
2015-08-01
Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors' proposed approach. A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors' proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.
Springer, Lindsay F; Chen, Lei-An; Stahlecker, Avery C; Cousins, Peter; Sacks, Gavin L
2016-11-02
In red winemaking, the extractability of condensed tannins (CT) can vary considerably even under identical fermentation conditions, and several explanations for this phenomenon have been proposed. Recent work has demonstrated that grape pathogenesis-related proteins (PRPs) may limit retention of CT added to finished wines, but their relevance to CT extractability has not been evaluated. In this work, Vitis vinifera and interspecific hybrids (Vitis ssp.) from both hot and cool climates were vinified under small-scale, controlled conditions. The final CT concentration in wine was well modeled from initial grape tannin and juice protein concentrations using the Freundlich equation (r 2 = 0.686). In follow-up experiments, separation and pretreatment of juice by bentonite, heating, freezing, or exogenous tannin addition reduced protein concentrations in juices from two grape varieties. The bentonite treatment also led to greater wine CT for one of the varieties, indicating that prefermentation removal of grape protein may be a viable approach to increasing wine CT.
Bolliger, Stephan A; Ross, Steffen; Thali, Michael J; Hostettler, Bernhard; Menkveld-Gfeller, Ursula
2012-01-01
The study of fossils permits the reconstruction of past life on our planet and enhances our understanding of evolutionary processes. However, many fossils are difficult to recognize, being encased in a lithified matrix whose tedious removal is required before examination is possible. The authors describe the use of multidetector computed tomography (CT) in locating, identifying, and examining fossil remains of crocodilians (Mesosuchia) embedded in hard shale, all without removing the matrix. In addition, they describe how three-dimensional (3D) reformatted CT images provided details that were helpful for extraction and preparation. Multidetector CT can help experienced paleontologists localize and characterize fossils in the matrix of a promising rock specimen in a nondestructive manner. Moreover, with its capacity to generate highly accurate 3D images, multidetector CT can help determine whether the fossils warrant extraction and can assist in planning the extraction process. Thus, multidetector CT may well become an invaluable tool in the field of paleoradiology.
NASA Astrophysics Data System (ADS)
Haneda, Eri; Luo, Jiajia; Can, Ali; Ramani, Sathish; Fu, Lin; De Man, Bruno
2016-05-01
In this study, we implement and compare model based iterative reconstruction (MBIR) with dictionary learning (DL) over MBIR with pairwise pixel-difference regularization, in the context of transportation security. DL is a technique of sparse signal representation using an over complete dictionary which has provided promising results in image processing applications including denoising,1 as well as medical CT reconstruction.2 It has been previously reported that DL produces promising results in terms of noise reduction and preservation of structural details, especially for low dose and few-view CT acquisitions.2 A distinguishing feature of transportation security CT is that scanned baggage may contain items with a wide range of material densities. While medical CT typically scans soft tissues, blood with and without contrast agents, and bones, luggage typically contains more high density materials (i.e. metals and glass), which can produce severe distortions such as metal streaking artifacts. Important factors of security CT are the emphasis on image quality such as resolution, contrast, noise level, and CT number accuracy for target detection. While MBIR has shown exemplary performance in the trade-off of noise reduction and resolution preservation, we demonstrate that DL may further improve this trade-off. In this study, we used the KSVD-based DL3 combined with the MBIR cost-minimization framework and compared results to Filtered Back Projection (FBP) and MBIR with pairwise pixel-difference regularization. We performed a parameter analysis to show the image quality impact of each parameter. We also investigated few-view CT acquisitions where DL can show an additional advantage relative to pairwise pixel difference regularization.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leng, Shuai; Yu, Lifeng; Wang, Jia
Purpose: Our purpose was to reduce image noise in spectral CT by exploiting data redundancies in the energy domain to allow flexible selection of the number, width, and location of the energy bins. Methods: Using a variety of spectral CT imaging methods, conventional filtered backprojection (FBP) reconstructions were performed and resulting images were compared to those processed using a Local HighlY constrained backPRojection Reconstruction (HYPR-LR) algorithm. The mean and standard deviation of CT numbers were measured within regions of interest (ROIs), and results were compared between FBP and HYPR-LR. For these comparisons, the following spectral CT imaging methods were used:(i)more » numerical simulations based on a photon-counting, detector-based CT system, (ii) a photon-counting, detector-based micro CT system using rubidium and potassium chloride solutions, (iii) a commercial CT system equipped with integrating detectors utilizing tube potentials of 80, 100, 120, and 140 kV, and (iv) a clinical dual-energy CT examination. The effects of tube energy and energy bin width were evaluated appropriate to each CT system. Results: The mean CT number in each ROI was unchanged between FBP and HYPR-LR images for each of the spectral CT imaging scenarios, irrespective of bin width or tube potential. However, image noise, as represented by the standard deviation of CT numbers in each ROI, was reduced by 36%-76%. In all scenarios, image noise after HYPR-LR algorithm was similar to that of composite images, which used all available photons. No difference in spatial resolution was observed between HYPR-LR processing and FBP. Dual energy patient data processed using HYPR-LR demonstrated reduced noise in the individual, low- and high-energy images, as well as in the material-specific basis images. Conclusions: Noise reduction can be accomplished for spectral CT by exploiting data redundancies in the energy domain. HYPR-LR is a robust method for reducing image noise in a variety of spectral CT imaging systems without losing spatial resolution or CT number accuracy. This method improves the flexibility to select energy bins in the manner that optimizes material identification and separation without paying the penalty of increased image noise or its corollary, increased patient dose.« less
Grating Oriented Line-Wise Filtration (GOLF) for Dual-Energy X-ray CT
NASA Astrophysics Data System (ADS)
Xi, Yan; Cong, Wenxiang; Harrison, Daniel; Wang, Ge
2017-12-01
In medical X-ray Computed Tomography (CT), the use of two distinct X-ray source spectra (energies) allows dose-reduction and material discrimination relative to that achieved with only one source spectrum. Existing dual-energy CT methods include source kVp-switching, double-layer detection, dual-source gantry, and two-pass scanning. Each method suffers either from strong spectral correlation or patient-motion artifacts. To simultaneously address these problems, we propose to improve CT data acquisition with the Grating Oriented Line-wise Filtration (GOLF) method, a novel X-ray filter that is placed between the source and patient. GOLF uses a combination of absorption and filtering gratings that are moved relative to each other and in synchronization with the X-ray tube kVp-switching process and/or the detector view-sampling process. Simulation results show that GOLF can improve the spectral performance of kVp-switching to match that of dual-source CT while avoiding patient motion artifacts and dual imaging chains. Although significant flux is absorbed by this pre-patient filter, the proposed GOLF method is a novel path for cost-effectively extracting dual-energy or multi-energy data and reducing radiation dose with or without kVp switching.
Grating Oriented Line-Wise Filtration (GOLF) for Dual-Energy X-ray CT
Xi, Yan; Cong, Wenxiang; Harrison, Daniel
2017-01-01
In medical X-ray Computed Tomography (CT), the use of two distinct X-ray source spectra (energies) allows dose-reduction and material discrimination relative to that achieved with only one source spectrum. Existing dual-energy CT methods include source kVp-switching, double-layer detection, dual-source gantry, and two-pass scanning. Each method suffers either from strong spectral correlation or patient-motion artifacts. To simultaneously address these problems, we propose to improve CT data acquisition with the Grating Oriented Line-wise Filtration (GOLF) method, a novel X-ray filter that is placed between the source and patient. GOLF uses a combination of absorption and filtering gratings that are moved relative to each other and in synchronization with the X-ray tube kVp-switching process and/or the detector view-sampling process. Simulation results show that GOLF can improve the spectral performance of kVp-switching to match that of dual-source CT while avoiding patient motion artifacts and dual imaging chains. Although significant flux is absorbed by this pre-patient filter, the proposed GOLF method is a novel path for cost-effectively extracting dual-energy or multi-energy data and reducing radiation dose with or without kVp switching. PMID:29333113
Liu, Donglai; Zhou, Haiwei; Shi, Dawei; Shen, Shu; Tian, Yabin; Wang, Lin; Lou, Jiatao; Cong, Rong; Lu, Juan; Zhang, Henghui; Zhao, Meiru; Zhu, Shida; Cao, Zhisheng; Jin, Ruilin; Wang, Yin; Zhang, Xiaoni; Yang, Guohua; Wang, Youchun; Zhang, Chuntao
2018-01-01
Background: Widespread clinical implementation of next-generation sequencing (NGS)-based cancer in vitro diagnostic tests (IVDs) highlighted the urgency to establish reference materials which could provide full control of the process from nucleic acid extraction to test report generation. The formalin-fixed, paraffin-embedded (FFPE) tissue and blood plasma containing circulating tumor deoxyribonucleic acid (ctDNA) were mostly used for clinically detecting onco-relevant mutations. Methods: We respectively developed multiplex FFPE and plasma reference materials covering three clinically onco-relevant mutations within the epidermal growth factor receptor ( EGFR ) gene at serial allelic frequencies. All reference materials were quantified and validated via droplet digital polymerase chain reaction (ddPCR), and then were distributed to eight domestic manufacturers for the collaborative evaluation of the performance of several domestic NGS-based cancer IVDs covering four major NGS platforms (NextSeq, HiSeq, Ion Proton and BGISEQ). Results: All expected mutations except one at extremely low allelic frequencies were detected, despite some differences in coefficient of variation (CV) which increased with the decrease of allelic frequency (CVs ranging from 18% to 106%). It was worth noting that the CV value seemed to correlate with a particular mutation as well. The repeatability of determination of different mutations was L858R>T790M>19del. Conclusions: The results indicated our reference materials would be pivotal for quality control of NGS-based cancer IVDs and would guide the further development of reference materials covering more onco-relevant mutations.
WE-H-207A-07: Image-Based Versus Atlas-Based Internal Dosimetry
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fallahpoor, M; Abbasi, M; Parach, A
Purpose: Monte Carlo (MC) simulation is known as the gold standard method for internal dosimetry. It requires radionuclide distribution from PET or SPECT and body structure from CT for accurate dose calculation. The manual or semi-automatic segmentation of organs from CT images is a major obstacle. The aim of this study is to compare the dosimetry results based on patient’s own CT and a digital humanoid phantom as an atlas with pre-specified organs. Methods: SPECT-CT images of a 50 year old woman who underwent bone pain palliation with Samarium-153 EDTMP for osseous metastases from breast cancer were used. The anatomicalmore » date and attenuation map were extracted from SPECT/CT and three XCAT digital phantoms with different BMIs (i.e. matched (38.8) and unmatched (35.5 and 36.7) with patient’s BMI that was 38.3). Segmentation of patient’s organs in CT image was performed using itk-SNAP software. GATE MC Simulator was used for dose calculation. Specific absorbed fractions (SAFs) and S-values were calculated for the segmented organs. Results: The differences between SAFs and S-values are high using different anatomical data and range from −13% to 39% for SAF values and −109% to 79% for S-values in different organs. In the spine, the clinically important target organ for Samarium Therapy, the differences in the S-values and SAF values are higher between XCAT phantom and CT when the phantom with identical BMI is employed (53.8% relative difference in S-value and 26.8% difference in SAF). However, the whole body dose values were the same between the calculations based on the CT and XCAT with different BMIs. Conclusion: The results indicated that atlas-based dosimetry using XCAT phantom even with matched BMI for patient leads to considerable errors as compared to image-based dosimetry that uses the patient’s own CT Patient-specific dosimetry using CT image is essential for accurate results.« less
A neural network approach to lung nodule segmentation
NASA Astrophysics Data System (ADS)
Hu, Yaoxiu; Menon, Prahlad G.
2016-03-01
Computed tomography (CT) imaging is a sensitive and specific lung cancer screening tool for the high-risk population and shown to be promising for detection of lung cancer. This study proposes an automatic methodology for detecting and segmenting lung nodules from CT images. The proposed methods begin with thorax segmentation, lung extraction and reconstruction of the original shape of the parenchyma using morphology operations. Next, a multi-scale hessian-based vesselness filter is applied to extract lung vasculature in lung. The lung vasculature mask is subtracted from the lung region segmentation mask to extract 3D regions representing candidate pulmonary nodules. Finally, the remaining structures are classified as nodules through shape and intensity features which are together used to train an artificial neural network. Up to 75% sensitivity and 98% specificity was achieved for detection of lung nodules in our testing dataset, with an overall accuracy of 97.62%+/-0.72% using 11 selected features as input to the neural network classifier, based on 4-fold cross-validation studies. Receiver operator characteristics for identifying nodules revealed an area under curve of 0.9476.
Lodienė, Greta; Kopperud, Hilde M; Ørstavik, Dag; Bruzell, Ellen M
2013-10-01
Root canal sealing materials may have toxic potential in vitro depending on the cell line, cytotoxicity assay, material chemistry, and degree of polymer curing. The aims of the present study were to detect leaching components from epoxy- or methacrylate-based root canal sealers and to investigate the degree of cytotoxicity after exposure to extracts from these materials. Qualitative determination of substances released from the materials was performed by gas- and liquid chromatography/mass spectrometry. Submandibular salivary gland acinar cell death (apoptosis/necrosis) was determined using a fluorescence staining/microscopy technique. The major leachable monomer from the epoxy-based material was bisphenol-A diglycidyl ether (BADGE), whereas leachables from the methacrylate-based materials were mainly triethylene glycol dimethacrylate (TEGDMA), urethane dimethacrylate (UDMA), hydroxyethyl methacrylate (HEMA), and polyethyleneglycol dimethacrylate (PEGDMA). Exposure to diluted extracts of cured methacrylate-based materials caused a postexposure time-dependent increase in cell death. This effect was not demonstrated as a result of exposure to undiluted extract of cured epoxy-based material. Extracts of all fresh materials induced apoptosis significantly, but at lower dilutions of the epoxy- than the methacrylate-based materials. The degree of leaching, determined from the relative chromatogram peak heights of eluates from the methacrylate-based sealer materials, corresponded with the degree of cell death induced by extracts of these materials. © 2013 Eur J Oral Sci.
Burger, C; Goerres, G; Schoenes, S; Buck, A; Lonn, A H R; Von Schulthess, G K
2002-07-01
The CT data acquired in combined PET/CT studies provide a fast and essentially noiseless source for the correction of photon attenuation in PET emission data. To this end, the CT values relating to attenuation of photons in the range of 40-140 keV must be transformed into linear attenuation coefficients at the PET energy of 511 keV. As attenuation depends on photon energy and the absorbing material, an accurate theoretical relation cannot be devised. The transformation implemented in the Discovery LS PET/CT scanner (GE Medical Systems, Milwaukee, Wis.) uses a bilinear function based on the attenuation of water and cortical bone at the CT and PET energies. The purpose of this study was to compare this transformation with experimental CT values and corresponding PET attenuation coefficients. In 14 patients, quantitative PET attenuation maps were calculated from germanium-68 transmission scans, and resolution-matched CT images were generated. A total of 114 volumes of interest were defined and the average PET attenuation coefficients and CT values measured. From the CT values the predicted PET attenuation coefficients were calculated using the bilinear transformation. When the transformation was based on the narrow-beam attenuation coefficient of water at 511 keV (0.096 cm(-1)), the predicted attenuation coefficients were higher in soft tissue than the measured values. This bias was reduced by replacing 0.096 cm(-1) in the transformation by the linear attenuation coefficient of 0.093 cm(-1) obtained from germanium-68 transmission scans. An analysis of the corrected emission activities shows that the resulting transformation is essentially equivalent to the transmission-based attenuation correction for human tissue. For non-human material, however, it may assign inaccurate attenuation coefficients which will also affect the correction in neighbouring tissue.
NASA Astrophysics Data System (ADS)
Elfarnawany, Mai; Alam, S. Riyahi; Agrawal, Sumit K.; Ladak, Hanif M.
2017-02-01
Cochlear implant surgery is a hearing restoration procedure for patients with profound hearing loss. In this surgery, an electrode is inserted into the cochlea to stimulate the auditory nerve and restore the patient's hearing. Clinical computed tomography (CT) images are used for planning and evaluation of electrode placement, but their low resolution limits the visualization of internal cochlear structures. Therefore, high resolution micro-CT images are used to develop atlas-based segmentation methods to extract these nonvisible anatomical features in clinical CT images. Accurate registration of the high and low resolution CT images is a prerequisite for reliable atlas-based segmentation. In this study, we evaluate and compare different non-rigid B-spline registration parameters using micro-CT and clinical CT images of five cadaveric human cochleae. The varying registration parameters are cost function (normalized correlation (NC), mutual information and mean square error), interpolation method (linear, windowed-sinc and B-spline) and sampling percentage (1%, 10% and 100%). We compare the registration results visually and quantitatively using the Dice similarity coefficient (DSC), Hausdorff distance (HD) and absolute percentage error in cochlear volume. Using MI or MSE cost functions and linear or windowed-sinc interpolation resulted in visually undesirable deformation of internal cochlear structures. Quantitatively, the transforms using 100% sampling percentage yielded the highest DSC and smallest HD (0.828+/-0.021 and 0.25+/-0.09mm respectively). Therefore, B-spline registration with cost function: NC, interpolation: B-spline and sampling percentage: moments 100% can be the foundation of developing an optimized atlas-based segmentation algorithm of intracochlear structures in clinical CT images.
NASA Astrophysics Data System (ADS)
Cattaneo, Paolo M.; Dalstra, Michel; Beckmann, Felix; Donath, Tilman; Melsen, Birte
2004-10-01
This study explores the application of conventional micro tomography (μCT) and synchrotron radiation (SR) based μCT to evaluate the bone around titanium dental implants. The SR experiment was performed at beamline W2 of HASYLAB at DESY using a monochromatic X-ray beam of 50 keV. The testing material consisted of undecalcified bone segments harvested from the upper jaw of a macaca fascicularis monkey each containing a titanium dental implant. The results from the two different techniques were qualitatively compared with conventional histological sections examined under light microscopy. The SR-based μCT produced images that, especially at the bone-implant interface, are less noisy and sharper than the ones obtained with conventional μCT. For the proper evaluation of the implant-bone interface, only the SR-based μCT technique is able to display the areas of bony contact and visualize the true 3D structure of bone around dental implants correctly. This investigation shows that both conventional and SR-based μCT scanning techniques are non-destructive methods, which provide detailed images of bone. However with SR-based μCT it is possible to obtain an improved image quality of the bone surrounding dental implants, which display a level of detail comparable to histological sections. Therefore, SR-based μCT scanning could represent a valid, unbiased three-dimensional alternative to evaluate osseointegration of dental implants
A web-based procedure for liver segmentation in CT images
NASA Astrophysics Data System (ADS)
Yuan, Rong; Luo, Ming; Wang, Luyao; Xie, Qingguo
2015-03-01
Liver segmentation in CT images has been acknowledged as a basic and indispensable part in systems of computer aided liver surgery for operation design and risk evaluation. In this paper, we will introduce and implement a web-based procedure for liver segmentation to help radiologists and surgeons get an accurate result efficiently and expediently. Several clinical datasets are used to evaluate the accessibility and the accuracy. This procedure seems a promising approach for extraction of liver volumetry of various shapes. Moreover, it is possible for user to access the segmentation wherever the Internet is available without any specific machine.
USDA-ARS?s Scientific Manuscript database
We investigated the anti-metastatic activity of four Hericium erinaceus edible mushroom extracts using CT-26 murine colon carcinoma cells as an indicator of inhibition of cell migration to the lung. Hot water (HWE) and microwaved 50% ethanol (MWE) extracts of Hericium erinaceus strongly elicited ca...
Commissioning an in-room mobile CT for adaptive proton therapy with a compact proton system.
Oliver, Jasmine A; Zeidan, Omar; Meeks, Sanford L; Shah, Amish P; Pukala, Jason; Kelly, Patrick; Ramakrishna, Naren R; Willoughby, Twyla R
2018-05-01
To describe the commissioning of AIRO mobile CT system (AIRO) for adaptive proton therapy on a compact double scattering proton therapy system. A Gammex phantom was scanned with varying plug patterns, table heights, and mAs on a CT simulator (CT Sim) and on the AIRO. AIRO-specific CT-stopping power ratio (SPR) curves were created with a commonly used stoichiometric method using the Gammex phantom. A RANDO anthropomorphic thorax, pelvis, and head phantom, and a CIRS thorax and head phantom were scanned on the CT Sim and AIRO. Clinically realistic treatment plans and nonclinical plans were generated on the CT Sim images and subsequently copied onto the AIRO CT scans for dose recalculation and comparison for various AIRO SPR curves. Gamma analysis was used to evaluate dosimetric deviation between both plans. AIRO CT values skewed toward solid water when plugs were scanned surrounded by other plugs in phantom. Low-density materials demonstrated largest differences. Dose calculated on AIRO CT scans with stoichiometric-based SPR curves produced over-ranged proton beams when large volumes of low-density material were in the path of the beam. To create equivalent dose distributions on both data sets, the AIRO SPR curve's low-density data points were iteratively adjusted to yield better proton beam range agreement based on isodose lines. Comparison of the stoichiometric-based AIRO SPR curve and the "dose-adjusted" SPR curve showed slight improvement on gamma analysis between the treatment plan and the AIRO plan for single-field plans at the 1%, 1 mm level, but did not affect clinical plans indicating that HU number differences between the CT Sim and AIRO did not affect dose calculations for robust clinical beam arrangements. Based on this study, we believe the AIRO can be used offline for adaptive proton therapy on a compact double scattering proton therapy system. © 2018 Orlando Health UF Health Cancer Center. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.
Symbolic rule-based classification of lung cancer stages from free-text pathology reports.
Nguyen, Anthony N; Lawley, Michael J; Hansen, David P; Bowman, Rayleen V; Clarke, Belinda E; Duhig, Edwina E; Colquist, Shoni
2010-01-01
To classify automatically lung tumor-node-metastases (TNM) cancer stages from free-text pathology reports using symbolic rule-based classification. By exploiting report substructure and the symbolic manipulation of systematized nomenclature of medicine-clinical terms (SNOMED CT) concepts in reports, statements in free text can be evaluated for relevance against factors relating to the staging guidelines. Post-coordinated SNOMED CT expressions based on templates were defined and populated by concepts in reports, and tested for subsumption by staging factors. The subsumption results were used to build logic according to the staging guidelines to calculate the TNM stage. The accuracy measure and confusion matrices were used to evaluate the TNM stages classified by the symbolic rule-based system. The system was evaluated against a database of multidisciplinary team staging decisions and a machine learning-based text classification system using support vector machines. Overall accuracy on a corpus of pathology reports for 718 lung cancer patients against a database of pathological TNM staging decisions were 72%, 78%, and 94% for T, N, and M staging, respectively. The system's performance was also comparable to support vector machine classification approaches. A system to classify lung TNM stages from free-text pathology reports was developed, and it was verified that the symbolic rule-based approach using SNOMED CT can be used for the extraction of key lung cancer characteristics from free-text reports. Future work will investigate the applicability of using the proposed methodology for extracting other cancer characteristics and types.
Tibe, O; Sutherland, I A; Lesperance, L; Harding, D R K
2013-10-18
The effect of condensed tannins (CT) extracted from forage plants from Botswana on the free-living stages of a number of species of gastrointestinal nematode parasites derived from infected sheep were investigated using in vitro assays. Fresh samples of five different plants (Viscum rotundifolium, Viscum verrucosum, Tapinanthus oleifolius, Grewia flava and Ipomoea sinensis) were collected over two summers (February 2009 and 2010). Fractionation of each crude extract on a Sephadex LH-20 column yielded low molecular weight phenolics and CT-containing fractions. The effect of each purified CT fraction on parasites was evaluated using either egg hatch, larval development or larval migration inhibition assays. Three gastrointestinal nematode species (Haemonchus contortus, Trichostrongylus colubriformis and Teladorsagia circumcincta) derived from infected sheep were evaluated in the study. CT from V. rotundifolium and I. sinensis fractions from samples collected in 2009 and 2010 did not inhibit larval development. However, CT isolated from V. verrucosum, T. oleifolius and G. flava collected in 2009 completely inhibited the development of all parasite species. These CT fractions were more potent in inhibiting larval development of H. contortus than fractions from the same plant species collected in 2010. However, a slight effect on larval migration was observed with some CT extracts. The results suggest that CT extracts of some forage plants from Botswana have anti-parasitic properties in vitro, and that further research is required to determine any in vivo efficacy from feeding the plants to goats in a field situation. Copyright © 2013 Elsevier B.V. All rights reserved.
Deep neural networks for automatic detection of osteoporotic vertebral fractures on CT scans.
Tomita, Naofumi; Cheung, Yvonne Y; Hassanpour, Saeed
2018-07-01
Osteoporotic vertebral fractures (OVFs) are prevalent in older adults and are associated with substantial personal suffering and socio-economic burden. Early diagnosis and treatment of OVFs are critical to prevent further fractures and morbidity. However, OVFs are often under-diagnosed and under-reported in computed tomography (CT) exams as they can be asymptomatic at an early stage. In this paper, we present and evaluate an automatic system that can detect incidental OVFs in chest, abdomen, and pelvis CT examinations at the level of practicing radiologists. Our OVF detection system leverages a deep convolutional neural network (CNN) to extract radiological features from each slice in a CT scan. These extracted features are processed through a feature aggregation module to make the final diagnosis for the full CT scan. In this work, we explored different methods for this feature aggregation, including the use of a long short-term memory (LSTM) network. We trained and evaluated our system on 1432 CT scans, comprised of 10,546 two-dimensional (2D) images in sagittal view. Our system achieved an accuracy of 89.2% and an F1 score of 90.8% based on our evaluation on a held-out test set of 129 CT scans, which were established as reference standards through standard semiquantitative and quantitative methods. The results of our system matched the performance of practicing radiologists on this test set in real-world clinical circumstances. We expect the proposed system will assist and improve OVF diagnosis in clinical settings by pre-screening routine CT examinations and flagging suspicious cases prior to review by radiologists. Copyright © 2018 Elsevier Ltd. All rights reserved.
Xiao, Ting; Xu, Haihua; Grancini, Giulia; Mai, Jiangquan; Petrozza, Annamaria; Jeng, U-Ser; Wang, Yan; Xin, Xin; Lu, Yong; Choon, Ng Siu; Xiao, Hu; Ong, Beng S; Lu, Xinhui; Zhao, Ni
2014-06-09
The interpenetrating morphology formed by the electron donor and acceptor materials is critical for the performance of polymer:fullerene bulk heterojunction (BHJ) photovoltaic (PV) cells. In this work we carried out a systematic investigation on a high PV efficiency (>6%) BHJ system consisting of a newly developed 5,6-difluorobenzo[c] thiadiazole-based copolymer, PFBT-T20TT, and a fullerene derivative. Grazing incidence X-ray scattering measurements reveal the lower-ordered nature of the BHJ system as well as an intermixing morphology with intercalation of fullerene molecules between the PFBT-T20TT lamella. Steady-state and transient photo-induced absorption spectroscopy reveal ultrafast charge transfer (CT) at the PFBT-T20TT/fullerene interface, indicating that the CT process is no longer limited by exciton diffusion. Furthermore, we extracted the hole mobility based on the space limited current (SCLC) model and found that more efficient hole transport is achieved in the PFBT-T20TT:fullerene BHJ as compared to pure PFBT-T20TT, showing a different trend as compared to the previously reported highly crystalline polymer:fullerene blend with a similar intercalation manner. Our study correlates the fullerene intercalated polymer lamella morphology with device performance and provides a coherent model to interpret the high photovoltaic performance of some of the recently developed weakly-ordered BHJ systems based on conjugated polymers with branched side-chain.
Torres, Fernanda Ferrari Esteves; Bosso-Martelo, Roberta; Espir, Camila Galletti; Cirelli, Joni Augusto; Guerreiro-Tanomaru, Juliane Maria; Tanomaru-Filho, Mario
2017-01-01
To evaluate solubility, dimensional stability, filling ability and volumetric change of root-end filling materials using conventional tests and new Micro-CT-based methods. 7. The results suggested correlated or complementary data between the proposed tests. At 7 days, BIO showed higher solubility and at 30 days, showed higher volumetric change in comparison with MTA (p<0.05). With regard to volumetric change, the tested materials were similar (p>0.05) at 7 days. At 30 days, they presented similar solubility. BIO and MTA showed higher dimensional stability than ZOE (p<0.05). ZOE and BIO showed higher filling ability (p<0.05). ZOE presented a higher dimensional change, and BIO had greater solubility after 7 days. BIO presented filling ability and dimensional stability, but greater volumetric change than MTA after 30 days. Micro-CT can provide important data on the physicochemical properties of materials complementing conventional tests.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Y. X.; Van Reeth, E.; Poh, C. L., E-mail: clpoh@ntu.edu.sg
2015-08-15
Purpose: Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors’ proposed approach. Methods: A novel hybrid approach based on deformable image registration (DIR) and finite elementmore » method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. Results: The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors’ proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. Conclusions: The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.« less
Computed Tomography Inspection and Analysis for Additive Manufacturing Components
NASA Technical Reports Server (NTRS)
Beshears, Ronald D.
2017-01-01
Computed tomography (CT) inspection was performed on test articles additively manufactured from metallic materials. Metallic AM and machined wrought alloy test articles with programmed flaws and geometric features were inspected using a 2-megavolt linear accelerator based CT system. Performance of CT inspection on identically configured wrought and AM components and programmed flaws was assessed to determine the impact of additive manufacturing on inspectability of objects with complex geometries.
Implementation of material decomposition using an EMCCD and CMOS-based micro-CT system.
Podgorsak, Alexander R; Nagesh, Sv Setlur; Bednarek, Daniel R; Rudin, Stephen; Ionita, Ciprian N
2017-02-11
This project assessed the effectiveness of using two different detectors to obtain dual-energy (DE) micro-CT data for the carrying out of material decomposition. A micro-CT coupled to either a complementary metal-oxide semiconductor (CMOS) or an electron multiplying CCD (EMCCD) detector was used to acquire image data of a 3D-printed phantom with channels filled with different materials. At any instance, materials such as iohexol contrast agent, water, and platinum were selected to make up the scanned object. DE micro-CT data was acquired, and slices of the scanned object were differentiated by material makeup. The success of the decomposition was assessed quantitatively through the computation of percentage normalized root-mean-square error (%NRMSE). Our results indicate a successful decomposition of iohexol for both detectors (%NRMSE values of 1.8 for EMCCD, 2.4 for CMOS), as well as platinum (%NRMSE value of 4.7). The CMOS detector performed material decomposition on air and water on average with 7 times more %NRMSE, possibly due to the decreased sensitivity of the CMOS system. Material decomposition showed the potential to differentiate between materials such as the iohexol and platinum, perhaps opening the door for its use in the neurovascular anatomical region. Work supported by Toshiba America Medical Systems, and partially supported by NIH grant 2R01EB002873.
Implementation of material decomposition using an EMCCD and CMOS-based micro-CT system
NASA Astrophysics Data System (ADS)
Podgorsak, Alexander R.; Nagesh, S. V. Setlur; Bednarek, Daniel R.; Rudin, Stephen; Ionita, Ciprian N.
2017-03-01
This project assessed the effectiveness of using two different detectors to obtain dual-energy (DE) micro-CT data for the carrying out of material decomposition. A micro-CT coupled to either a complementary metal-oxide semiconductor (CMOS) or an electron multiplying CCD (EMCCD) detector was used to acquire image data of a 3D-printed phantom with channels filled with different materials. At any instance, materials such as iohexol contrast agent, water, and platinum were selected to make up the scanned object. DE micro-CT data was acquired, and slices of the scanned object were differentiated by material makeup. The success of the decomposition was assessed quantitatively through the computation of percentage normalized root-mean-square error (%NRMSE). Our results indicate a successful decomposition of iohexol for both detectors (%NRMSE values of 1.8 for EMCCD, 2.4 for CMOS), as well as platinum (%NRMSE value of 4.7). The CMOS detector performed material decomposition on air and water on average with 7 times more %NRMSE, possibly due to the decreased sensitivity of the CMOS system. Material decomposition showed the potential to differentiate between materials such as the iohexol and platinum, perhaps opening the door for its use in the neurovascular anatomical region. Work supported by Toshiba America Medical Systems, and partially supported by NIH grant 2R01EB002873.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luo, G
2014-06-01
Purpose: In order to receive DICOM files from treatment planning system and generate patient isocenter positioning parameter file for CT laser system automatically, this paper presents a method for communication with treatment planning system and calculation of isocenter parameter for each radiation field. Methods: Coordinate transformation and laser positioning file formats were analyzed, isocenter parameter was calculated via data from DICOM CT Data and DICOM RTPLAN file. An in-house software-DicomGenie was developed based on the object-oriented program platform-Qt with DCMTK SDK (Germany OFFIS company DICOM SDK) . DicomGenie was tested for accuracy using Philips CT simulation plan system (Tumor LOC,more » Philips) and A2J CT positioning laser system (Thorigny Sur Marne, France). Results: DicomGenie successfully established DICOM communication between treatment planning system, DICOM files were received by DicomGenie and patient laser isocenter information was generated accurately. Patient laser parameter data files can be used for for CT laser system directly. Conclusion: In-house software DicomGenie received and extracted DICOM data, isocenter laser positioning data files were created by DicomGenie and can be use for A2J laser positioning system.« less
Simulation-based artifact correction (SBAC) for metrological computed tomography
NASA Astrophysics Data System (ADS)
Maier, Joscha; Leinweber, Carsten; Sawall, Stefan; Stoschus, Henning; Ballach, Frederic; Müller, Tobias; Hammer, Michael; Christoph, Ralf; Kachelrieß, Marc
2017-06-01
Computed tomography (CT) is a valuable tool for the metrolocical assessment of industrial components. However, the application of CT to the investigation of highly attenuating objects or multi-material components is often restricted by the presence of CT artifacts caused by beam hardening, x-ray scatter, off-focal radiation, partial volume effects or the cone-beam reconstruction itself. In order to overcome this limitation, this paper proposes an approach to calculate a correction term that compensates for the contribution of artifacts and thus enables an appropriate assessment of these components using CT. Therefore, we make use of computer simulations of the CT measurement process. Based on an appropriate model of the object, e.g. an initial reconstruction or a CAD model, two simulations are carried out. One simulation considers all physical effects that cause artifacts using dedicated analytic methods as well as Monte Carlo-based models. The other one represents an ideal CT measurement i.e. a measurement in parallel beam geometry with a monochromatic, point-like x-ray source and no x-ray scattering. Thus, the difference between these simulations is an estimate for the present artifacts and can be used to correct the acquired projection data or the corresponding CT reconstruction, respectively. The performance of the proposed approach is evaluated using simulated as well as measured data of single and multi-material components. Our approach yields CT reconstructions that are nearly free of artifacts and thereby clearly outperforms commonly used artifact reduction algorithms in terms of image quality. A comparison against tactile reference measurements demonstrates the ability of the proposed approach to increase the accuracy of the metrological assessment significantly.
Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Diemoz, Paul C.; Wismüller, Axel
2015-01-01
Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns. PMID:25710875
Wu, Yao; Yang, Wei; Lu, Lijun; Lu, Zhentai; Zhong, Liming; Huang, Meiyan; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan
2016-10-01
Attenuation correction is important for PET reconstruction. In PET/MR, MR intensities are not directly related to attenuation coefficients that are needed in PET imaging. The attenuation coefficient map can be derived from CT images. Therefore, prediction of CT substitutes from MR images is desired for attenuation correction in PET/MR. This study presents a patch-based method for CT prediction from MR images, generating attenuation maps for PET reconstruction. Because no global relation exists between MR and CT intensities, we propose local diffeomorphic mapping (LDM) for CT prediction. In LDM, we assume that MR and CT patches are located on 2 nonlinear manifolds, and the mapping from the MR manifold to the CT manifold approximates a diffeomorphism under a local constraint. Locality is important in LDM and is constrained by the following techniques. The first is local dictionary construction, wherein, for each patch in the testing MR image, a local search window is used to extract patches from training MR/CT pairs to construct MR and CT dictionaries. The k-nearest neighbors and an outlier detection strategy are then used to constrain the locality in MR and CT dictionaries. Second is local linear representation, wherein, local anchor embedding is used to solve MR dictionary coefficients when representing the MR testing sample. Under these local constraints, dictionary coefficients are linearly transferred from the MR manifold to the CT manifold and used to combine CT training samples to generate CT predictions. Our dataset contains 13 healthy subjects, each with T1- and T2-weighted MR and CT brain images. This method provides CT predictions with a mean absolute error of 110.1 Hounsfield units, Pearson linear correlation of 0.82, peak signal-to-noise ratio of 24.81 dB, and Dice in bone regions of 0.84 as compared with real CTs. CT substitute-based PET reconstruction has a regression slope of 1.0084 and R 2 of 0.9903 compared with real CT-based PET. In this method, no image segmentation or accurate registration is required. Our method demonstrates superior performance in CT prediction and PET reconstruction compared with competing methods. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.
[Spiral CT angiography in practice].
Pavcec, Zlatko; Zokalj, Ivan; Rumboldt, Zoran; Pal, Andrej; Saghir, Hussein; Ozretić, David; Latin, Branko; Perhoć, Zeljka; Marotti, Miljenko
2005-01-01
Incidence of vascular diseases and development of new radiologic techniques in the last three decades has given strong impuls for introduction of non-invasive vascular diagnostic methods. Thanks to the introduction of Doppler ultrasound, new types of computed tomography (CT) and magnetic resonance (MR) scanners, non-invasive vascular diagnostic methods are replacing conventional invasive (catheter) angiographic methods. Computed tomographic angiography (CTA) is a noninvasive vascular diagnostic method based on continuous scanning with CT scanner during intravenous application of contrast material. Performing of CTA is possible after introduction of spiral CT technique whose characteristics are short imaging time and volumetric data acquisition. The main goal of this article, based on our experiences, is to review the role of CTA, performed on single-slice CT scanner, in managment of patients with vascular pathology.
Leng, Shuai; Yu, Lifeng; Wang, Jia; Fletcher, Joel G; Mistretta, Charles A; McCollough, Cynthia H
2011-09-01
Our purpose was to reduce image noise in spectral CT by exploiting data redundancies in the energy domain to allow flexible selection of the number, width, and location of the energy bins. Using a variety of spectral CT imaging methods, conventional filtered backprojection (FBP) reconstructions were performed and resulting images were compared to those processed using a Local HighlY constrained backPRojection Reconstruction (HYPR-LR) algorithm. The mean and standard deviation of CT numbers were measured within regions of interest (ROIs), and results were compared between FBP and HYPR-LR. For these comparisons, the following spectral CT imaging methods were used:(i) numerical simulations based on a photon-counting, detector-based CT system, (ii) a photon-counting, detector-based micro CT system using rubidium and potassium chloride solutions, (iii) a commercial CT system equipped with integrating detectors utilizing tube potentials of 80, 100, 120, and 140 kV, and (iv) a clinical dual-energy CT examination. The effects of tube energy and energy bin width were evaluated appropriate to each CT system. The mean CT number in each ROI was unchanged between FBP and HYPR-LR images for each of the spectral CT imaging scenarios, irrespective of bin width or tube potential. However, image noise, as represented by the standard deviation of CT numbers in each ROI, was reduced by 36%-76%. In all scenarios, image noise after HYPR-LR algorithm was similar to that of composite images, which used all available photons. No difference in spatial resolution was observed between HYPR-LR processing and FBP. Dual energy patient data processed using HYPR-LR demonstrated reduced noise in the individual, low- and high-energy images, as well as in the material-specific basis images. Noise reduction can be accomplished for spectral CT by exploiting data redundancies in the energy domain. HYPR-LR is a robust method for reducing image noise in a variety of spectral CT imaging systems without losing spatial resolution or CT number accuracy. This method improves the flexibility to select energy bins in the manner that optimizes material identification and separation without paying the penalty of increased image noise or its corollary, increased patient dose.
Mohamed, Abdallah S. R.; Ruangskul, Manee-Naad; Awan, Musaddiq J.; Baron, Charles A.; Kalpathy-Cramer, Jayashree; Castillo, Richard; Castillo, Edward; Guerrero, Thomas M.; Kocak-Uzel, Esengul; Yang, Jinzhong; Court, Laurence E.; Kantor, Michael E.; Gunn, G. Brandon; Colen, Rivka R.; Frank, Steven J.; Garden, Adam S.; Rosenthal, David I.
2015-01-01
Purpose To develop a quality assurance (QA) workflow by using a robust, curated, manually segmented anatomic region-of-interest (ROI) library as a benchmark for quantitative assessment of different image registration techniques used for head and neck radiation therapy–simulation computed tomography (CT) with diagnostic CT coregistration. Materials and Methods Radiation therapy–simulation CT images and diagnostic CT images in 20 patients with head and neck squamous cell carcinoma treated with curative-intent intensity-modulated radiation therapy between August 2011 and May 2012 were retrospectively retrieved with institutional review board approval. Sixty-eight reference anatomic ROIs with gross tumor and nodal targets were then manually contoured on images from each examination. Diagnostic CT images were registered with simulation CT images rigidly and by using four deformable image registration (DIR) algorithms: atlas based, B-spline, demons, and optical flow. The resultant deformed ROIs were compared with manually contoured reference ROIs by using similarity coefficient metrics (ie, Dice similarity coefficient) and surface distance metrics (ie, 95% maximum Hausdorff distance). The nonparametric Steel test with control was used to compare different DIR algorithms with rigid image registration (RIR) by using the post hoc Wilcoxon signed-rank test for stratified metric comparison. Results A total of 2720 anatomic and 50 tumor and nodal ROIs were delineated. All DIR algorithms showed improved performance over RIR for anatomic and target ROI conformance, as shown for most comparison metrics (Steel test, P < .008 after Bonferroni correction). The performance of different algorithms varied substantially with stratification by specific anatomic structures or category and simulation CT section thickness. Conclusion Development of a formal ROI-based QA workflow for registration assessment demonstrated improved performance with DIR techniques over RIR. After QA, DIR implementation should be the standard for head and neck diagnostic CT and simulation CT allineation, especially for target delineation. © RSNA, 2014 Online supplemental material is available for this article. PMID:25380454
Automatic co-segmentation of lung tumor based on random forest in PET-CT images
NASA Astrophysics Data System (ADS)
Jiang, Xueqing; Xiang, Dehui; Zhang, Bin; Zhu, Weifang; Shi, Fei; Chen, Xinjian
2016-03-01
In this paper, a fully automatic method is proposed to segment the lung tumor in clinical 3D PET-CT images. The proposed method effectively combines PET and CT information to make full use of the high contrast of PET images and superior spatial resolution of CT images. Our approach consists of three main parts: (1) initial segmentation, in which spines are removed in CT images and initial connected regions achieved by thresholding based segmentation in PET images; (2) coarse segmentation, in which monotonic downhill function is applied to rule out structures which have similar standardized uptake values (SUV) to the lung tumor but do not satisfy a monotonic property in PET images; (3) fine segmentation, random forests method is applied to accurately segment the lung tumor by extracting effective features from PET and CT images simultaneously. We validated our algorithm on a dataset which consists of 24 3D PET-CT images from different patients with non-small cell lung cancer (NSCLC). The average TPVF, FPVF and accuracy rate (ACC) were 83.65%, 0.05% and 99.93%, respectively. The correlation analysis shows our segmented lung tumor volumes has strong correlation ( average 0.985) with the ground truth 1 and ground truth 2 labeled by a clinical expert.
Automated segmentation of hepatic vessel trees in non-contrast x-ray CT images
NASA Astrophysics Data System (ADS)
Kawajiri, Suguru; Zhou, Xiangrong; Zhang, Xuejin; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Kanematsu, Masayuki; Hoshi, Hiroaki
2007-03-01
Hepatic vessel trees are the key structures in the liver. Knowledge of the hepatic vessel trees is important for liver surgery planning and hepatic disease diagnosis such as portal hypertension. However, hepatic vessels cannot be easily distinguished from other liver tissues in non-contrast CT images. Automated segmentation of hepatic vessels in non-contrast CT images is a challenging issue. In this paper, an approach for automated segmentation of hepatic vessels trees in non-contrast X-ray CT images is proposed. Enhancement of hepatic vessels is performed using two techniques: (1) histogram transformation based on a Gaussian window function; (2) multi-scale line filtering based on eigenvalues of Hessian matrix. After the enhancement of hepatic vessels, candidate of hepatic vessels are extracted by thresholding. Small connected regions of size less than 100 voxels are considered as false-positives and are removed from the process. This approach is applied to 20 cases of non-contrast CT images. Hepatic vessel trees segmented from the contrast-enhanced CT images of the same patient are used as the ground truth in evaluating the performance of the proposed segmentation method. Results show that the proposed method can enhance and segment the hepatic vessel regions in non-contrast CT images correctly.
Jiménez, Roberto; Torralba, Marta; Yagüe-Fabra, José A.; Ontiveros, Sinué; Tosello, Guido
2017-01-01
The dimensional verification of miniaturized components with 3D complex geometries is particularly challenging. Computed Tomography (CT) can represent a suitable alternative solution to micro metrology tools based on optical and tactile techniques. However, the establishment of CT systems’ traceability when measuring 3D complex geometries is still an open issue. In this work, an alternative method for the measurement uncertainty assessment of 3D complex geometries by using CT is presented. The method is based on the micro-CT system Maximum Permissible Error (MPE) estimation, determined experimentally by using several calibrated reference artefacts. The main advantage of the presented method is that a previous calibration of the component by a more accurate Coordinate Measuring System (CMS) is not needed. In fact, such CMS would still hold all the typical limitations of optical and tactile techniques, particularly when measuring miniaturized components with complex 3D geometries and their inability to measure inner parts. To validate the presented method, the most accepted standard currently available for CT sensors, the Verein Deutscher Ingenieure/Verband Deutscher Elektrotechniker (VDI/VDE) guideline 2630-2.1 is applied. Considering the high number of influence factors in CT and their impact on the measuring result, two different techniques for surface extraction are also considered to obtain a realistic determination of the influence of data processing on uncertainty. The uncertainty assessment of a workpiece used for micro mechanical material testing is firstly used to confirm the method, due to its feasible calibration by an optical CMS. Secondly, the measurement of a miniaturized dental file with 3D complex geometry is carried out. The estimated uncertainties are eventually compared with the component’s calibration and the micro manufacturing tolerances to demonstrate the suitability of the presented CT calibration procedure. The 2U/T ratios resulting from the validation workpiece are, respectively, 0.27 (VDI) and 0.35 (MPE), by assuring tolerances in the range of ± 20–30 µm. For the dental file, the EN < 1 value analysis is favorable in the majority of the cases (70.4%) and 2U/T is equal to 0.31 for sub-mm measurands (L < 1 mm and tolerance intervals of ± 40–80 µm). PMID:28509869
Jiménez, Roberto; Torralba, Marta; Yagüe-Fabra, José A; Ontiveros, Sinué; Tosello, Guido
2017-05-16
The dimensional verification of miniaturized components with 3D complex geometries is particularly challenging. Computed Tomography (CT) can represent a suitable alternative solution to micro metrology tools based on optical and tactile techniques. However, the establishment of CT systems' traceability when measuring 3D complex geometries is still an open issue. In this work, an alternative method for the measurement uncertainty assessment of 3D complex geometries by using CT is presented. The method is based on the micro-CT system Maximum Permissible Error (MPE) estimation, determined experimentally by using several calibrated reference artefacts. The main advantage of the presented method is that a previous calibration of the component by a more accurate Coordinate Measuring System (CMS) is not needed. In fact, such CMS would still hold all the typical limitations of optical and tactile techniques, particularly when measuring miniaturized components with complex 3D geometries and their inability to measure inner parts. To validate the presented method, the most accepted standard currently available for CT sensors, the Verein Deutscher Ingenieure/Verband Deutscher Elektrotechniker (VDI/VDE) guideline 2630-2.1 is applied. Considering the high number of influence factors in CT and their impact on the measuring result, two different techniques for surface extraction are also considered to obtain a realistic determination of the influence of data processing on uncertainty. The uncertainty assessment of a workpiece used for micro mechanical material testing is firstly used to confirm the method, due to its feasible calibration by an optical CMS. Secondly, the measurement of a miniaturized dental file with 3D complex geometry is carried out. The estimated uncertainties are eventually compared with the component's calibration and the micro manufacturing tolerances to demonstrate the suitability of the presented CT calibration procedure. The 2U/T ratios resulting from the validation workpiece are, respectively, 0.27 (VDI) and 0.35 (MPE), by assuring tolerances in the range of ± 20-30 µm. For the dental file, the E N < 1 value analysis is favorable in the majority of the cases (70.4%) and 2U/T is equal to 0.31 for sub-mm measurands (L < 1 mm and tolerance intervals of ± 40-80 µm).
TORRES, Fernanda Ferrari Esteves; BOSSO-MARTELO, Roberta; ESPIR, Camila Galletti; CIRELLI, Joni Augusto; GUERREIRO-TANOMARU, Juliane Maria; TANOMARU-FILHO, Mario
2017-01-01
Abstract Objective To evaluate solubility, dimensional stability, filling ability and volumetric change of root-end filling materials using conventional tests and new Micro-CT-based methods. Material and Methods 7 Results The results suggested correlated or complementary data between the proposed tests. At 7 days, BIO showed higher solubility and at 30 days, showed higher volumetric change in comparison with MTA (p<0.05). With regard to volumetric change, the tested materials were similar (p>0.05) at 7 days. At 30 days, they presented similar solubility. BIO and MTA showed higher dimensional stability than ZOE (p<0.05). ZOE and BIO showed higher filling ability (p<0.05). Conclusions ZOE presented a higher dimensional change, and BIO had greater solubility after 7 days. BIO presented filling ability and dimensional stability, but greater volumetric change than MTA after 30 days. Micro-CT can provide important data on the physicochemical properties of materials complementing conventional tests. PMID:28877275
Wu, C; de Jong, J R; Gratama van Andel, H A; van der Have, F; Vastenhouw, B; Laverman, P; Boerman, O C; Dierckx, R A J O; Beekman, F J
2011-09-21
Attenuation of photon flux on trajectories between the source and pinhole apertures affects the quantitative accuracy of reconstructed single-photon emission computed tomography (SPECT) images. We propose a Chang-based non-uniform attenuation correction (NUA-CT) for small-animal SPECT/CT with focusing pinhole collimation, and compare the quantitative accuracy with uniform Chang correction based on (i) body outlines extracted from x-ray CT (UA-CT) and (ii) on hand drawn body contours on the images obtained with three integrated optical cameras (UA-BC). Measurements in phantoms and rats containing known activities of isotopes were conducted for evaluation. In (125)I, (201)Tl, (99m)Tc and (111)In phantom experiments, average relative errors comparing to the gold standards measured in a dose calibrator were reduced to 5.5%, 6.8%, 4.9% and 2.8%, respectively, with NUA-CT. In animal studies, these errors were 2.1%, 3.3%, 2.0% and 2.0%, respectively. Differences in accuracy on average between results of NUA-CT, UA-CT and UA-BC were less than 2.3% in phantom studies and 3.1% in animal studies except for (125)I (3.6% and 5.1%, respectively). All methods tested provide reasonable attenuation correction and result in high quantitative accuracy. NUA-CT shows superior accuracy except for (125)I, where other factors may have more impact on the quantitative accuracy than the selected attenuation correction.
Solomon, Justin; Mileto, Achille; Nelson, Rendon C; Roy Choudhury, Kingshuk; Samei, Ehsan
2016-04-01
To determine if radiation dose and reconstruction algorithm affect the computer-based extraction and analysis of quantitative imaging features in lung nodules, liver lesions, and renal stones at multi-detector row computed tomography (CT). Retrospective analysis of data from a prospective, multicenter, HIPAA-compliant, institutional review board-approved clinical trial was performed by extracting 23 quantitative imaging features (size, shape, attenuation, edge sharpness, pixel value distribution, and texture) of lesions on multi-detector row CT images of 20 adult patients (14 men, six women; mean age, 63 years; range, 38-72 years) referred for known or suspected focal liver lesions, lung nodules, or kidney stones. Data were acquired between September 2011 and April 2012. All multi-detector row CT scans were performed at two different radiation dose levels; images were reconstructed with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction (MBIR) algorithms. A linear mixed-effects model was used to assess the effect of radiation dose and reconstruction algorithm on extracted features. Among the 23 imaging features assessed, radiation dose had a significant effect on five, three, and four of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Adaptive statistical iterative reconstruction had a significant effect on three, one, and one of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). MBIR reconstruction had a significant effect on nine, 11, and 15 of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Of note, the measured size of lung nodules and renal stones with MBIR was significantly different than those for the other two algorithms (P < .002 for all comparisons). Although lesion texture was significantly affected by the reconstruction algorithm used (average of 3.33 features affected by MBIR throughout lesion types; P < .002, for all comparisons), no significant effect of the radiation dose setting was observed for all but one of the texture features (P = .002-.998). Radiation dose settings and reconstruction algorithms affect the extraction and analysis of quantitative imaging features in lesions at multi-detector row CT.
SU-F-J-172: Hybrid MR/CT Compatible Phantom for MR-Only Based Radiotherapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, M; Lee, S; Song, K
2016-06-15
Purpose: Development of hybrid MR/CT compatible phantom was introduced to fully establish MR image only radiation treatment and this suggested technique using in-house developed hybrid MR/CT compatible phantom image would utilize to generate radiation treatment planning and perform dose calculation without multi-modal registration process or generation of pseudo CT. Methods: Fundamental characteristics for “hybrid MR/CT compatible phantom” was established: Relaxation times equivalent to human tissue, dielectric properties, homogeneous relaxation times, sufficient strength to fabricate a torso, ease of handling, a wide variety of density material for calibration, chemical and physical stability over an extended time. For this requirements, chemical componentmore » in each tested plug which would be tissue equivalent to human tissue on MR and CT image and production of phantom body and plug was performed. Chemical component has described below: Agaros, GdCl{sub 3}, NaN{sub 3}, NaCl, K{sub 2}Co{sub 3}, deionized-distilled water. Various mixture of chemical component to simulate human tissue on both MR and CT image was tested by measuring T1, T2 relaxation time and signal intensity (SI) on MR image and Hounsfield unit (HU) on CT and each value was compared. The hybrid MR/CT compatible phantom with 14 plugs was designed and has made. Total height and external diameter was decided by internal size of 32 channel MR head-coil. Results: Tissue-equivalent chemical component materials and hybrid MR/CT compatible phantom was developed. The range of T1, T2 relaxation time and SI on MR image, HU on CT was acquired and could be adjusted to correspond to simulated human tissue. Conclusion: Current result shows its possibility for MR-only based radiotherapy and the best mixing rate of chemical component for tissue-equivalent image on MR and CT was founded. However, additional technical issues remain to be overcome. Conversion of SI on MR image into HU and dose calculation based on converted MRI will be progressing.« less
Ghadiri, H; Ay, M R; Shiran, M B; Soltanian-Zadeh, H
2013-01-01
Objective: Recently introduced energy-sensitive X-ray CT makes it feasible to discriminate different nanoparticulate contrast materials. The purpose of this work is to present a K-edge ratio method for differentiating multiple simultaneous contrast agents using spectral CT. Methods: The ratio of two images relevant to energy bins straddling the K-edge of the materials is calculated using an analytic CT simulator. In the resulting parametric map, the selected contrast agent regions can be identified using a thresholding algorithm. The K-edge ratio algorithm is applied to spectral images of simulated phantoms to identify and differentiate up to four simultaneous and targeted CT contrast agents. Results: We show that different combinations of simultaneous CT contrast agents can be identified by the proposed K-edge ratio method when energy-sensitive CT is used. In the K-edge parametric maps, the pixel values for biological tissues and contrast agents reach a maximum of 0.95, whereas for the selected contrast agents, the pixel values are larger than 1.10. The number of contrast agents that can be discriminated is limited owing to photon starvation. For reliable material discrimination, minimum photon counts corresponding to 140 kVp, 100 mAs and 5-mm slice thickness must be used. Conclusion: The proposed K-edge ratio method is a straightforward and fast method for identification and discrimination of multiple simultaneous CT contrast agents. Advances in knowledge: A new spectral CT-based algorithm is proposed which provides a new concept of molecular CT imaging by non-iteratively identifying multiple contrast agents when they are simultaneously targeting different organs. PMID:23934964
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ali, I; Ahmad, S; Alsbou, N
Purpose: To develop 4D-cone-beam CT (CBCT) algorithm by motion modeling that extracts actual length, CT numbers level and motion amplitude of a mobile target retrospective to image reconstruction by motion modeling. Methods: The algorithm used three measurable parameters: apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine actual length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm were tested with mobile targets that with different well-known sizes made from tissue-equivalent gel which was inserted into a thorax phantom. The phantom moved sinusoidally in one-direction to simulatemore » respiratory motion using eight amplitudes ranging 0–20mm. Results: Using this 4D-CBCT algorithm, three unknown parameters were extracted that include: length of the target, CT number level, speed or motion amplitude for the mobile targets retrospective to image reconstruction. The motion algorithms solved for the three unknown parameters using measurable apparent length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on the actual target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, actual target length and motion amplitude. Motion frequency and phase did not affect the elongation and CT number distribution of the mobile target and could not be determined. Conclusion: A 4D-CBCT motion algorithm was developed to extract three parameters that include actual length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement to motion tracking and sorting of the images into different breathing phases which has potential applications in diagnostic CT imaging and radiotherapy.« less
Personalized Guideline-Based Treatment Recommendations Using Natural Language Processing Techniques.
Becker, Matthias; Böckmann, Britta
2017-01-01
Clinical guidelines and clinical pathways are accepted and proven instruments for quality assurance and process optimization. Today, electronic representation of clinical guidelines exists as unstructured text, but is not well-integrated with patient-specific information from electronic health records. Consequently, generic content of the clinical guidelines is accessible, but it is not possible to visualize the position of the patient on the clinical pathway, decision support cannot be provided by personalized guidelines for the next treatment step. The Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) provides common reference terminology as well as the semantic link for combining the pathways and the patient-specific information. This paper proposes a model-based approach to support the development of guideline-compliant pathways combined with patient-specific structured and unstructured information using SNOMED CT. To identify SNOMED CT concepts, a software was developed to extract SNOMED CT codes out of structured and unstructured German data to map these with clinical pathways annotated in accordance with the systematized nomenclature.
Kim, Yemi; Lee, Ho-Young; Yoon, Hai-Jeon; Kim, Bom Sahn
2016-04-01
The aim of this study was to determine the clinical utility of positron emission tomography/computed tomography (PET/CT) using 18F-FDG and 18F-NaF for the diagnosis of osteonecrosis of the jaw (ONJ), by observing characteristics in rat models treated with zoledronic acid (ZA) and/or dexamethasone (DX) followed by tooth extraction. A total of 48 rats were divided randomly into four groups: Group 1, rats treated with ZA and DX; Group 2, rats treated with ZA; Group 3, rats treated with DX; and Group 4, rats treated with vehicle as normal controls. They underwent examinations with both 18F-FDG and 18F-NaF PET/CT at 4 weeks prior to tooth extraction (baseline) and 4 weeks after tooth extraction. Rats were then sacrificed to evaluate the histological incidence and characteristics of ONJ. Histological and radiological characteristics of all groups were compared to assess the effects of medication and tooth extraction. Baseline PET/CT studies using 18F-FDG and 18F-NaF showed no difference in uptake among the groups. However, 18F-FDG PET/CT performed at 4 weeks after tooth extraction showed increased glucose metabolism at the extraction site in both the ZA/DX and the ZA-only groups compared with that in the vehicle-treated group, in accordance with the higher incidence of histological ONJ (p < 0.05, respectively). 18F-NaF PET/CT performed at 4 weeks after tooth extraction showed decreased bone uptake in the extraction site in the ZA/DX, ZA, and DX groups versus the vehicle group (all p < 0.05), but this was not correlated with the incidence of histological ONJ. The incidence of ONJ was highest in the ZA/DX group (66.7%), followed by the ZA group, both of which were significantly higher than in the DX and vehicle groups (both p < 0.05). 18F-FDG PET/CT as an inflammatory marker appeared to be a more appropriate imaging modality than 18F-NaF PET/CT in diagnosing ONJ in a rat model including a ZA/DX group. However, the decreased bone remodeling tendency highlighted by 18F-NaF PET/CT may be an indicator of a possible risk of ONJ before the onset of clinical signs and symptoms. Copyright © 2016 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
Harms, Joseph; Wang, Tonghe; Petrongolo, Michael; Niu, Tianye; Zhu, Lei
2016-01-01
Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is based on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan©600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan©600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution. PMID:27147376
Reddy, Samala Murali Mohan; Dorishetty, Pramod; Augustine, George; Deshpande, Abhijit P; Ayyadurai, Niraikulam; Shanmugam, Ganesh
2017-11-28
Charge-transfer (CT) gel materials obtained from low-molecular-weight (LMW) compounds through a supramolecular self-assembly approach have received fascinating attention by many researchers because of their interesting material property and potential applications. However, most of the CT gel materials constructed were of organogels while the construction of CT gels in the form of a hydrogel is a challenge because of the solubility issue in water, which considerably limits the use of CT hydrogels. Herein, for the first time, we report a new LMW gelator [N α -(fluorenylmethoxycarbonyl)-N ε -(δ-butyric-1-pyrenyl)-l-lysine, (FmKPy)], composed of two functional moieties such as fluorenylmethoxycarbonyl and pyrene, which not only parade both hydro and organo (ambidextrous) supramolecular gel formation but also exhibit CT ambidextrous gels when mixed with an electron acceptor such as 2,4,7-trinitro-9-fluorenone (TNF). This finding is significant as the established CT organogelator in the literature did not form an organogel in the absence of an electron acceptor or lose their gelation property upon the addition of the acceptor. CT between pyrene and TNF was confirmed by the color change as well as the appearance of the CT band in the visible region of the absorption spectrum. CT between FmKPy and TNF was supported by the solvent dilution method using tetrahydrofuran as the gel breaker and pyrene fluorescence quenching in the case compound containing pyrene and TNF. The morphology of FmKPy ambidextrous gels indicates the fibrous nature while the self-assembled structure is primarily stabilized by π-π stacking among fluorenyl and pyrenyl moieties and hydrogen bonding between amide groups. The FmKPy-TNF CT ambidextrous gel retains the fibrous nature; however, the size of the fibers changed. In FmKPy-TNF CT gels, TNF is intercalated between pyrene moieties in the self-assembled structure as confirmed by fluorescence quenching and powder X-ray diffraction. The FmKPy ambidextrous gel exhibits significant properties such as low minimum gelation concentration (MGC), thixotropic nature, pH stimuli response, and high thermal stability. Upon the addition of TNF, the FmKPy-TNF CT ambidextrous gel maintains all these properties except MGC which increased for FmKPy-TNF. Because pyrene-based LMW organogels have been developed widely for many applications while their hydrogels were limited, the current finding of the pyrene-based ambidextrous fluorescent gel with the CT property provides a wide opportunity to use FmKPy as a soft material maker and also for potential applications in fields like surface coating, three-dimensional printing, and so forth.
Computed Tomography Inspection and Analysis for Additive Manufacturing Components
NASA Technical Reports Server (NTRS)
Beshears, Ronald D.
2016-01-01
Computed tomography (CT) inspection was performed on test articles additively manufactured from metallic materials. Metallic AM and machined wrought alloy test articles with programmed flaws were inspected using a 2MeV linear accelerator based CT system. Performance of CT inspection on identically configured wrought and AM components and programmed flaws was assessed using standard image analysis techniques to determine the impact of additive manufacturing on inspectability of objects with complex geometries.
Investigation on charge transfer bands of Ce 4+ in Sr 2CeO 4 blue phosphor
NASA Astrophysics Data System (ADS)
Li, Ling; Zhou, Shihong; Zhang, Siyuan
2008-03-01
Bulk and nano-materials Sr2CeO4 were prepared by solid-state reaction and sol-gel technique, respectively. Photoluminescence shows that luminescence has the characteristic of a ligand-to-metal charge transfer (CT) emission. Compared with bulk Sr2CeO4, the nano-material exhibits stronger emission intensity, longer decay time, and higher CT excitation energy. Three CT excitation peaks were observed in both bulk and nano samples. Based on the theoretical calculations of the average energy gap of the chemical bond using the dielectric theory of complex crystal, the highest and the lowest energy CT bands were assigned to the transitions O1 → Ce4+ and O2 → Ce4+, respectively. The middle bands were due to the superposition of the transitions Ce-O1 and Ce-O2.
Rocha, Eduardo Passos; Anchieta, Rodolfo Bruniera; de Almeida, Erika Oliveira; Freitas, Amilcar Chagas; Martini, Ana Paula; Sotto-Maior, Bruno Sales; Luersen, Marco Antonio; Ko, Ching Chang
2015-01-01
Veneer fracture is the most common complication in zirconia-based restorations. The aim of this study was to evaluate the mechanical behavior of a zirconia-based crown in a lower canine tooth supporting removable partial denture (RPD) prosthesis, varying the bond quality of the veneer/coping interface. Microtomography (μCT) data of an extracted left lower canine were used to build the finite element model (M) varying the core material (gold core - MAu; zirconia core - MZi) and the quality of the veneer/core interface (complete bonded - MZi; incomplete bonded - MZi-NL). The incomplete bonding condition was only applied for zirconia coping by using contact elements (Target/Contact) with 0.3 frictional coefficients. Stress fields were obtained using Ansys Workbench 10.0. The loading condition (L = 1 N) was vertically applied at the base of the RPD prosthesis metallic support towards the dental apex. Maximum principal (σmax) and von Mises equivalent (σvM) stresses were obtained. The σmax (MPa) for the bonded condition was similar between gold and zirconia cores (MAu, 0.42; MZi, 0.40). The incomplete bonded condition (MZi-NL) raised σmax in the veneer up to 800% (3.23 MPa) in contrast to the bonded condition. The peak of σvM increased up to 270% in the MZi-NL. The incomplete bond condition increasing the stress in the veneer/zirconia interface.
NASA Astrophysics Data System (ADS)
Komini Babu, Siddharth; Mohamed, Alexander I.; Whitacre, Jay F.; Litster, Shawn
2015-06-01
This paper presents the use of nanometer scale resolution X-ray computed tomography (nano-CT) in the three-dimensional (3D) imaging of a Li-ion battery cathode, including the separate volumes of active material, binder plus conductive additive, and pore. The different high and low atomic number (Z) materials are distinguished by sequentially imaging the lithium cobalt oxide electrode in absorption and then Zernike phase contrast modes. Morphological parameters of the active material and the additives are extracted from the 3D reconstructions, including the distribution of contact areas between the additives and the active material. This method could provide a better understanding of the electric current distribution and structural integrity of battery electrodes, as well as provide detailed geometries for computational models.
Marinozzi, Franco; Bini, Fabiano; Marinozzi, Andrea; Zuppante, Francesca; De Paolis, Annalisa; Pecci, Raffaella; Bedini, Rossella
2013-01-01
Micro-CT analysis is a powerful technique for a non-invasive evaluation of the morphometric parameters of trabecular bone samples. This elaboration requires a previous binarization of the images. A problem which arises from the binarization process is the partial volume artifact. Voxels at the external surface of the sample can contain both bone and air so thresholding operates an incorrect estimation of volume occupied by the two materials. The aim of this study is the extraction of bone volumetric information directly from the image histograms, by fitting them with a suitable set of functions. Nineteen trabecular bone samples were extracted from femoral heads of eight patients subject to a hip arthroplasty surgery. Trabecular bone samples were acquired using micro-CT Scanner. Hystograms of the acquired images were computed and fitted by Gaussian-like functions accounting for: a) gray levels produced by the bone x-ray absorption, b) the portions of the image occupied by air and c) voxels that contain a mixture of bone and air. This latter contribution can be considered such as an estimation of the partial volume effect. The comparison of the proposed technique to the bone volumes measured by a reference instrument such as by a helium pycnometer show the method as a good way for an accurate bone volume calculation of trabecular bone samples.
Long, Alexandra S; Watson, Margaret; Arlt, Volker M; White, Paul A
2016-08-01
Coal tar (CT) is a thick black liquid produced as a by-product of coal carbonization to produce coke or manufactured gas. It is comprised a complex mixture of polycyclic aromatic compounds, including a wide range of polycyclic aromatic hydrocarbons (PAHs), many of which are genotoxic and carcinogenic. CT is used in some pavement sealants (also known as sealcoat), which are applied to pavement in order to seal and beautify the surface. Human exposure is known to occur not only during application, but also as a result of the weathering process, as elevated levels of PAHs have been found in settled house dust in residences adjacent to CT-sealed surfaces. In this study we examined the genotoxicity of an extract of a commercially available CT-based sealcoat in the transgenic Muta™Mouse model. Mice were orally exposed to 3 doses of sealcoat extract daily for 28 days. We evaluated genotoxicity by examining: (1) stable DNA adducts and (2) lacZ mutations in bone marrow, liver, lung, small intestine, and glandular stomach, as well as (3) micronucleated red blood cells. Significant increases were seen for each endpoint and in all tissues. The potency of the response differed across tissues, with the highest frequency of adducts occurring in liver and lung, and the highest frequency of mutations occurring in small intestine. The results of this study are the first demonstration of mammalian genotoxicity following exposure to CT-containing pavement sealcoat. This work provides in vivo evidence to support the contention that there may be adverse health effects in mammals, and potentially in humans, from exposure to coal tar. Environ. Mol. Mutagen. 57:535-545, 2016. © 2016 Her Majesty the Queen in Right of Canada. © 2016 Reproduced with the permission of the Government of Canada.
Sinibaldi, R; Conti, A; Sinjari, B; Spadone, S; Pecci, R; Palombo, M; Komlev, V S; Ortore, M G; Tromba, G; Capuani, S; Guidotti, R; De Luca, F; Caputi, S; Traini, T; Della Penna, S
2018-03-01
Bone repair/regeneration is usually investigated through X-ray computed microtomography (μCT) supported by histology of extracted samples, to analyse biomaterial structure and new bone formation processes. Magnetic resonance imaging (μMRI) shows a richer tissue contrast than μCT, despite at lower resolution, and could be combined with μCT in the perspective of conducting non-destructive 3D investigations of bone. A pipeline designed to combine μMRI and μCT images of bone samples is here described and applied on samples of extracted human jawbone core following bone graft. We optimized the coregistration procedure between μCT and μMRI images to avoid bias due to the different resolutions and contrasts. Furthermore, we used an Adaptive Multivariate Clustering, grouping homologous voxels in the coregistered images, to visualize different tissue types within a fused 3D metastructure. The tissue grouping matched the 2D histology applied only on 1 slice, thus extending the histology labelling in 3D. Specifically, in all samples, we could separate and map 2 types of regenerated bone, calcified tissue, soft tissues, and/or fat and marrow space. Remarkably, μMRI and μCT alone were not able to separate the 2 types of regenerated bone. Finally, we computed volumes of each tissue in the 3D metastructures, which might be exploited by quantitative simulation. The 3D metastructure obtained through our pipeline represents a first step to bridge the gap between the quality of information obtained from 2D optical microscopy and the 3D mapping of the bone tissue heterogeneity and could allow researchers and clinicians to non-destructively characterize and follow-up bone regeneration. Copyright © 2017 John Wiley & Sons, Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hepel, Jaroslaw T.; Department of Radiation Oncology, Brown University, Rhode Island Hospital, Providence, RI; Evans, Suzanne B.
2009-06-01
Purpose: To evaluate the accuracy of two clinical techniques for electron boost planning compared with computed tomography (CT)-based planning. Additionally, we evaluated the tumor bed characteristics at whole breast planning and boost planning. Methods and Materials: A total of 30 women underwent tumor bed boost planning within 2 weeks of completing whole breast radiotherapy using three planning techniques: scar-based planning, palpation/clinical-based planning, and CT-based planning. The plans were analyzed for dosimetric coverage of the CT-delineated tumor bed. The cavity visualization score was used to define the CT-delineated tumor bed as well or poorly defined. Results: Scar-based planning resulted in inferiormore » tumor bed coverage compared with CT-based planning, with the minimal dose received by 90% of the target volume >90% in 53% and a geographic miss in 53%. The results of palpation/clinical-based planning were significantly better: 87% and 10% for the minimal dose received by 90% of the target volume >90% and geographic miss, respectively. Of the 30 tumor beds, 16 were poorly defined by the cavity visualization score. Of these 16, 8 were well demarcated by the surgical clips. The evaluation of the 22 well-defined tumor beds revealed similar results. A comparison of the tumor bed volume from the initial planning CT scan to the boost planning CT scan revealed a decrease in size in 77% of cases. The mean decrease in volume was 52%. Conclusion: The results of our study have shown that CT-based planning allows for optimal tumor bed coverage compared with clinical and scar-based approaches. However, in the setting of a poorly visualized cavity on CT without surgical clips, palpation/clinical-based planning can help delineate the appropriate target volumes and is superior to scar-based planning. CT simulation at boost planning could allow for a reduction in the boost volumes.« less
Alsbou, Nesreen; Ahmad, Salahuddin; Ali, Imad
2016-05-17
A motion algorithm has been developed to extract length, CT number level and motion amplitude of a mobile target from cone-beam CT (CBCT) images. The algorithm uses three measurable parameters: Apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm are tested with mobile targets having different well-known sizes that are made from tissue-equivalent gel which is inserted into a thorax phantom. The phantom moves sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0-20 mm. Using this motion algorithm, three unknown parameters are extracted that include: Length of the target, CT number level, speed or motion amplitude for the mobile targets from CBCT images. The motion algorithm solves for the three unknown parameters using measured length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agrees with the measured lengths which are dependent on the target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, the target length and motion amplitude. Motion frequency and phase do not affect the elongation and CT number distribution of the mobile target and could not be determined. A motion algorithm has been developed to extract three parameters that include length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement of motion tracking and sorting of the images into different breathing phases. The motion model developed here works well for tumors that have simple shapes, high contrast relative to surrounding tissues and move nearly in regular motion pattern that can be approximated with a simple sinusoidal function. This algorithm has potential applications in diagnostic CT imaging and radiotherapy in terms of motion management.
TU-G-BRA-02: Can We Extract Lung Function Directly From 4D-CT Without Deformable Image Registration?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kipritidis, J; Woodruff, H; Counter, W
Purpose: Dynamic CT ventilation imaging (CT-VI) visualizes air volume changes in the lung by evaluating breathing-induced lung motion using deformable image registration (DIR). Dynamic CT-VI could enable functionally adaptive lung cancer radiation therapy, but its sensitivity to DIR parameters poses challenges for validation. We hypothesize that a direct metric using CT parameters derived from Hounsfield units (HU) alone can provide similar ventilation images without DIR. We compare the accuracy of Direct and Dynamic CT-VIs versus positron emission tomography (PET) images of inhaled {sup 68}Ga-labelled nanoparticles (‘Galligas’). Methods: 25 patients with lung cancer underwent Galligas 4D-PET/CT scans prior to radiation therapy.more » For each patient we produced three CT- VIs. (i) Our novel method, Direct CT-VI, models blood-gas exchange as the product of air and tissue density at each lung voxel based on time-averaged 4D-CT HU values. Dynamic CT-VIs were produced by evaluating: (ii) regional HU changes, and (iii) regional volume changes between the exhale and inhale 4D-CT phase images using a validated B-spline DIR method. We assessed the accuracy of each CT-VI by computing the voxel-wise Spearman correlation with free-breathing Galligas PET, and also performed a visual analysis. Results: Surprisingly, Direct CT-VIs exhibited better global correlation with Galligas PET than either of the dynamic CT-VIs. The (mean ± SD) correlations were (0.55 ± 0.16), (0.41 ± 0.22) and (0.29 ± 0.27) for Direct, Dynamic HU-based and Dynamic volume-based CT-VIs respectively. Visual comparison of Direct CT-VI to PET demonstrated similarity for emphysema defects and ventral-to-dorsal gradients, but inability to identify decreased ventilation distal to tumor-obstruction. Conclusion: Our data supports the hypothesis that Direct CT-VIs are as accurate as Dynamic CT-VIs in terms of global correlation with Galligas PET. Visual analysis, however, demonstrated that different CT-VI algorithms might have varying accuracy depending on the underlying cause of ventilation abnormality. This research was supported by a National Health and Medical Research Council (NHMRC) Australia Fellowship, an Cancer Institute New South Wales Early Career Fellowship 13-ECF-1/15 and NHMRC scholarship APP1038399. No commercial funding was received for this work.« less
Extraction of liver volumetry based on blood vessel from the portal phase CT dataset
NASA Astrophysics Data System (ADS)
Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Utsunomiya, Tohru; Shimada, Mitsuo
2012-02-01
At liver surgery planning stage, the liver volumetry would be essential for surgeons. Main problem at liver extraction is the wide variability of livers in shapes and sizes. Since, hepatic blood vessels structure varies from a person to another and covers liver region, the present method uses that information for extraction of liver in two stages. The first stage is to extract abdominal blood vessels in the form of hepatic and nonhepatic blood vessels. At the second stage, extracted vessels are used to control extraction of liver region automatically. Contrast enhanced CT datasets at only the portal phase of 50 cases is used. Those data include 30 abnormal livers. A reference for all cases is done through a comparison of two experts labeling results and correction of their inter-reader variability. Results of the proposed method agree with the reference at an average rate of 97.8%. Through application of different metrics mentioned at MICCAI workshop for liver segmentation, it is found that: volume overlap error is 4.4%, volume difference is 0.3%, average symmetric distance is 0.7 mm, Root mean square symmetric distance is 0.8 mm, and maximum distance is 15.8 mm. These results represent the average of overall data and show an improved accuracy compared to current liver segmentation methods. It seems to be a promising method for extraction of liver volumetry of various shapes and sizes.
Chen, Liang; Sun, Peng; Wang, Ting; Chen, Kaixian; Jia, Qi; Wang, Heyao; Li, Yiming
2012-09-12
The procyanidin oligomers are thought to be responsible for the antidiabetic activity of cinnamon. To investigate the hypoglycemic effects of different procyanidin oligomer types, the procyanidin oligomer-rich extracts were prepared from two different cinnamon species. Using high-performance liquid chromatography with purified procyanidin oligomers as reference compounds, we found that the Cinnamomum cassia extract (CC-E) and Cinnamomum tamala extract (CT-E) were rich in B- and A-type procyanidin oligomers, respectively. In the experiment, 8-week-old diabetic (db/db) mice were gavaged with CC-E and CT-E (both 200 mg/kg per day) for 4 weeks. Both CC-E and CT-E exhibited antidiabetic effects. Moreover, histopathological studies of the pancreas, liver, and adipose tissue showed that CC-E promoted lipid accumulation in the adipose tissue and liver, whereas CT-E mainly improved the insulin concentration in the blood and pancreas.
Application of ionic liquid for extraction and separation of bioactive compounds from plants.
Tang, Baokun; Bi, Wentao; Tian, Minglei; Row, Kyung Ho
2012-09-01
In recent years, ionic liquids (ILs), as green and designer solvents, have accelerated research in analytical chemistry. This review highlights some of the unique properties of ILs and provides an overview of the preparation and application of IL or IL-based materials to extract bioactive compounds in plants. IL or IL-based materials in conjunction with liquid-liquid extraction (LLE), ultrasonic-assisted extraction (UAE), microwave-assisted extraction (MAE), high performance liquid chromatography (HPLC) and solid-phase extraction (SPE) analytical technologies etc., have been applied successfully to the extraction or separation of bioactive compounds from plants. This paper reviews the available data and references to examine the advantages of IL and IL-based materials in these applications. In addition, the main target compounds reviewed in this paper are bioactive compounds with multiple therapeutic effects and pharmacological activities. Based on the importance of the targets, this paper reviews the applications of ILs, IL-based materials or co-working with analytical technologies. The exploitation of new applications of ILs on the extraction of bioactive compounds from plant samples is expected to increase. Copyright © 2012 Elsevier B.V. All rights reserved.
Dhakal, Suraj; Meyling, Nicolai V; Williams, Andrew R; Mueller-Harvey, Irene; Fryganas, Christos; Kapel, Christian M O; Fredensborg, Brian L
2015-01-15
Natural anti-parasitic compounds in plants such as condensed tannins (CT) have anthelmintic properties against a range of gastrointestinal nematodes, but for other helminths such effects are unexplored. The aim of this study was to assess the effects of CT from three different plant extracts in a model system employing the rat tapeworm, Hymenolepis diminuta, in its intermediate host, Tenebrio molitor. An in vitro study examined infectivity of H. diminuta cysticercoids (excystation success) isolated from infected beetles exposed to different concentrations of CT extracts from pine bark (PB) (Pinus sps), hazelnut pericarp (HN) (Corylus avellana) or white clover flowers (WC) (Trifolium repens), in comparison with the anthelmintic drug praziquantel (positive control). In the in vitro study, praziquantel and CT from all three plant extracts had dose-dependent inhibitory effects on cysticercoid excystation. The HN extract was most effective at inhibiting excystation, followed by PB and WC. An in vivo study was carried out on infected beetles (measured as cysticercoid establishment) fed different doses of PB, HN and praziquantel. There was a highly significant inhibitory effect of HN on cysticercoid development (p=0.0002). Overall, CT showed a promising anti-cestodal effect against the metacestode stage of H. diminuta. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Yu, H.; Wang, Z.; Zhang, C.; Chen, N.; Zhao, Y.; Sawchuk, A. P.; Dalsing, M. C.; Teague, S. D.; Cheng, Y.
2014-11-01
Existing research of patient-specific computational hemodynamics (PSCH) heavily relies on software for anatomical extraction of blood arteries. Data reconstruction and mesh generation have to be done using existing commercial software due to the gap between medical image processing and CFD, which increases computation burden and introduces inaccuracy during data transformation thus limits the medical applications of PSCH. We use lattice Boltzmann method (LBM) to solve the level-set equation over an Eulerian distance field and implicitly and dynamically segment the artery surfaces from radiological CT/MRI imaging data. The segments seamlessly feed to the LBM based CFD computation of PSCH thus explicit mesh construction and extra data management are avoided. The LBM is ideally suited for GPU (graphic processing unit)-based parallel computing. The parallel acceleration over GPU achieves excellent performance in PSCH computation. An application study will be presented which segments an aortic artery from a chest CT dataset and models PSCH of the segmented artery.
TH-CD-206-09: Learning-Based MRI-CT Prostate Registration Using Spare Patch-Deformation Dictionary
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, X; Jani, A; Rossi, P
Purpose: To enable MRI-guided prostate radiotherapy, MRI-CT deformable registration is required to map the MRI-defined tumor and key organ contours onto the CT images. Due to the intrinsic differences in grey-level intensity characteristics between MRI and CT images, the integration of MRI into CT-based radiotherapy is very challenging. We are developing a learning-based registration approach to address this technical challenge. Methods: We propose to estimate the deformation between MRI and CT images in a patch-wise fashion by using the sparse representation technique. Specifically, we assume that two image patches should follow the same deformation if their patch-wise appearance patterns aremore » similar. We first extract a set of key points in the new CT image. Then, for each key point, we adaptively construct a coupled dictionary from the training MRI-CT images, where each coupled element includes both appearance and deformation of the same image patch. After calculating the sparse coefficients in representing the patch appearance of each key point based on the constructed dictionary, we can predict the deformation for this point by applying the same sparse coefficients to the respective deformations in the dictionary. Results: This registration technique was validated with 10 prostate-cancer patients’ data and its performance was compared with the commonly used free-form-deformation-based registration. Several landmarks in both images were identified to evaluate the accuracy of our approach. Overall, the averaged target registration error of the intensity-based registration and the proposed method was 3.8±0.4 mm and 1.9±0.3 mm, respectively. Conclusion: We have developed a novel prostate MR-CT registration approach based on patch-deformation dictionary, demonstrated its clinical feasibility, and validated its accuracy. This technique will either reduce or compensate for the effect of patient-specific treatment variation measured during the course of radiotherapy, is therefore well-suited for a number of MRI-guided adaptive radiotherapy, and potentially enhance prostate radiotherapy treatment outcome.« less
Identification of irradiated strawberries (in French)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deschreider, A.R.; Vigneron, J.M.
1973-01-01
From international colloquium: the identification of irradiated foodstuffs; Karlsruhe, Germany (24 0ct 1973). Packaged strawberries were irradiated with doses of 100, 200, and 500 krad of /sup 60/Co gamma rays. The irradiation of the fruit at these levels could not be detected either by measuring of the coloration of the anthocyanin extraction or the radioactivity of the phenylalanine-ammonia-lyase. If there is any plastic in the packaging material, examination under close infrared light reveals spectral modification when the dose level reaches 200 krad. (GE)
Chatterjee, Shruti; Zahid, M Shamim Hasan; Awasthi, Sharda Prasad; Chowdhury, Nityananda; Asakura, Masahiro; Hinenoya, Atsushi; Ramamurthy, T; Iwaoka, Emiko; Aoki, Shunji; Yamasaki, Shinji
2016-09-21
A newly emerged Vibrio cholerae O1 El Tor variant strain with multidrug resistance is considered a threat to public health. Recent strategies to suppress virulence factors production instead of bacterial growth may lead to less selective pressure for the emergence of resistant strains. The use of spices and their active constituents as the inhibitory agents against cholera toxin (CT) production in V. cholerae may be an alternative approach to treat cholera. In this study, we examined the potential of sweet fennel seed (Foeniculum vulgare Miller var. dulce) methanol extract to inhibit CT production in V. cholerae without affecting viability. The methanol extract of sweet fennel seeds significantly inhibited CT production in various V. cholerae strains, regardless of serogroup or biotype. Interestingly, trans-anethole and 4-allylanisole, essential oil components of sweet fennel seeds, also demonstrated similar effects. Here, we report that sub-bactericidal concentrations of sweet fennel seed methanol extract and its major components can drastically inhibit CT production in various V. cholerae strains.
Hill, Vincent R; Narayanan, Jothikumar; Gallen, Rachel R; Ferdinand, Karen L; Cromeans, Theresa; Vinjé, Jan
2015-05-26
Drinking and environmental water samples contain a diverse array of constituents that can interfere with molecular testing techniques, especially when large volumes of water are concentrated to the small volumes needed for effective molecular analysis. In this study, a suite of enteric viruses, bacteria, and protozoan parasites were seeded into concentrated source water and finished drinking water samples, in order to investigate the relative performance of nucleic acid extraction techniques for molecular testing. Real-time PCR and reverse transcription-PCR crossing threshold (CT) values were used as the metrics for evaluating relative performance. Experimental results were used to develop a guanidinium isothiocyanate-based lysis buffer (UNEX buffer) that enabled effective simultaneous extraction and recovery of DNA and RNA from the suite of study microbes. Procedures for bead beating, nucleic acid purification, and PCR facilitation were also developed and integrated in the protocol. The final lysis buffer and sample preparation procedure was found to be effective for a panel of drinking water and source water concentrates when compared to commercial nucleic acid extraction kits. The UNEX buffer-based extraction protocol enabled PCR detection of six study microbes, in 100 L finished water samples from four drinking water treatment facilities, within three CT values (i.e., within 90% difference) of the reagent-grade water control. The results from this study indicate that this newly formulated lysis buffer and sample preparation procedure can be useful for standardized molecular testing of drinking and environmental waters.
Hill, Vincent R.; Narayanan, Jothikumar; Gallen, Rachel R.; Ferdinand, Karen L.; Cromeans, Theresa; Vinjé, Jan
2015-01-01
Drinking and environmental water samples contain a diverse array of constituents that can interfere with molecular testing techniques, especially when large volumes of water are concentrated to the small volumes needed for effective molecular analysis. In this study, a suite of enteric viruses, bacteria, and protozoan parasites were seeded into concentrated source water and finished drinking water samples, in order to investigate the relative performance of nucleic acid extraction techniques for molecular testing. Real-time PCR and reverse transcription-PCR crossing threshold (CT) values were used as the metrics for evaluating relative performance. Experimental results were used to develop a guanidinium isothiocyanate-based lysis buffer (UNEX buffer) that enabled effective simultaneous extraction and recovery of DNA and RNA from the suite of study microbes. Procedures for bead beating, nucleic acid purification, and PCR facilitation were also developed and integrated in the protocol. The final lysis buffer and sample preparation procedure was found to be effective for a panel of drinking water and source water concentrates when compared to commercial nucleic acid extraction kits. The UNEX buffer-based extraction protocol enabled PCR detection of six study microbes, in 100 L finished water samples from four drinking water treatment facilities, within three CT values (i.e., within 90% difference) of the reagent-grade water control. The results from this study indicate that this newly formulated lysis buffer and sample preparation procedure can be useful for standardized molecular testing of drinking and environmental waters. PMID:26016775
NASA Astrophysics Data System (ADS)
Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te
2018-03-01
Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p = 0.002 518), sigma (p = 0.002 781), uniformity (p = 0.032 41), and entropy (p = 0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining truly malignant nodules and therefore reduce problems in lung cancer screening.
Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te
2018-03-14
Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p = 0.002 518), sigma (p = 0.002 781), uniformity (p = 0.032 41), and entropy (p = 0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining truly malignant nodules and therefore reduce problems in lung cancer screening.
Garlan, Fanny; Blanchet, Benoit; Kramkimel, Nora; Puszkiel, Alicja; Golmard, Jean-Louis; Noe, Gaelle; Dupin, Nicolas; Laurent-Puig, Pierre; Vidal, Michel; Taly, Valerie; Thomas-Schoemann, Audrey
2017-06-01
Circulating tumor DNA (ctDNA) has been reported as a prognostic marker in melanoma. In BRAF V600-mutant melanoma, a plasma under-exposure to vemurafenib could favor emerging resistance but no biological data are available to support this hypothesis. We aimed to investigate the relationship between vemurafenib plasma concentrations and the ctDNA plasma concentration during follow-up of BRAF-mutated melanoma patients. Eleven patients treated with single-agent vemurafenib for advanced BRAF V600-mutant melanoma were analyzed in an exploratory monocentric study. The vemurafenib plasma concentration was measured by liquid chromatography. ctDNA was extracted from plasma samples and the ctDNA concentration was evaluated using picoliter droplet-based digital PCR with Taqman ® detection probes targeting the BRAF p.V600E/K mutation and wild-type BRAF sequences. At baseline, plasma ctDNA was detectable in 72% (n = 8/11) of patients and the ctDNA concentration decreased in 88% of these patients (n = 7/8) from day (D) 0 to D15 after vemurafenib initiation. During follow-up, an increased ctDNA concentration was detected in nine patients: in five patients, the first increase in ctDNA concentrations followed a decrease in vemurafenib concentrations. More interestingly, an inverse correlation between vemurafenib concentration and ctDNA concentrations was demonstrated (p = 0.026). The ctDNA concentration at baseline was associated with overall survival (hazard ratio = 2.61, 95% CI 1.04-6.56; p = 0.04). This study demonstrates the relevance of vemurafenib plasma monitoring during the follow-up of metastatic melanoma patients. Plasma drug monitoring and ctDNA concentrations could be combined to monitor tumor evolution in melanoma patients treated with anti-BRAF therapies.
SU-F-I-59: Quality Assurance Phantom for PET/CT Alignment and Attenuation Correction
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lin, T; Hamacher, K
2016-06-15
Purpose: This study utilizes a commercial PET/CT phantom to investigate two specific properties of a PET/CT system: the alignment accuracy of PET images with those from CT used for attenuation correction and the accuracy of this correction in PET images. Methods: A commercial PET/CT phantom consisting of three aluminum rods, two long central cylinders containing uniform activity, and attenuating materials such as air, water, bone and iodine contrast was scanned using a standard PET/CT protocol. Images reconstructed with 2 mm slice thickness and a 512 by 512 matrix were obtained. The center of each aluminum rod in the PET andmore » CT images was compared to evaluate alignment accuracy. ROIs were drawn on transaxial images of the central rods at each section of attenuating material to determine the corrected activity (in BQML). BQML values were graphed as a function of slice number to provide a visual representation of the attenuation-correction throughout the whole phantom. Results: Alignment accuracy is high between the PET and CT images. The maximum deviation between the two in the axial plane is less than 1.5 mm, which is less than the width of a single pixel. BQML values measured along different sections of the large central rods are similar among the different attenuating materials except iodine contrast. Deviation of BQML values in the air and bone sections from the water section is less than 1%. Conclusion: Accurate alignment of PET and CT images is critical to ensure proper calculation and application of CT-based attenuation correction. This study presents a simple and quick method to evaluate the two with a single acquisition. As the phantom also includes spheres of increasing diameter, this could serve as a straightforward means to annually evaluate the status of a modern PET/CT system.« less
Spine centerline extraction and efficient spine reading of MRI and CT data
NASA Astrophysics Data System (ADS)
Lorenz, C.; Vogt, N.; Börnert, P.; Brosch, T.
2018-03-01
Radiological assessment of the spine is performed regularly in the context of orthopedics, neurology, oncology, and trauma management. Due to the extension and curved geometry of the spinal column, reading is time-consuming and requires substantial user interaction to navigate through the data during inspection. In this paper a spine geometry guided viewing approach is proposed facilitating reading by reducing the degrees of freedom to be manipulated during inspection of the data. The method is using the spine centerline as a representation of the spine geometry. We assume that renderings most useful for reading are those that can be locally defined based on a rotation and translation relative to the spine centerline. The resulting renderings conserve locally the relation to the spine and lead to curved planar reformats that can be adjusted using a small set of parameters to minimize user interaction. The spine centerline is extracted by an automated image to image foveal fully convolutional neural network (FFCN) based approach. The network consists of three parallel convolutional pathways working on different levels of resolution and processed fields of view. The outputs of the parallel pathways are combined by a subsequent feature integration pathway to yield the (final) centerline probability map, which is converted into a set of spine centerline points. The network has been trained separately using two data set types, one comprising a mixture of T1 and T2 weighted spine MR images and one using CT image data. We achieve an average centerline position error of 1.7 mm for MR and 0.9 mm for CT and a DICE coefficient of 0.84 for MR and 0.95 for CT. Based on the thus obtained centerline viewing and multi-planar reformatting can be easily facilitated.
Parisi, C; Mastoraki, S; Markou, A; Strati, A; Chimonidou, M; Georgoulias, V; Lianidou, E S
2016-10-01
Liquid biopsy is based on minimally invasive blood tests and has the potential to characterize the evolution of a solid tumor in real time, by extracting molecular information from circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA). Epigenetic silencing of tumor and metastasis suppressor genes plays a key role in survival and metastatic potential of cancer cells. Our group was the first to show the presence of epigenetic alterations in CTCs. We present the development and analytical validation of a highly specific and sensitive Multiplex Methylation Specific PCR-coupled liquid bead array (MMSPA) for the simultaneous detection of the methylation status of three tumor and metastasis suppressor genes (CST6, SOX17 and BRMS1) in liquid biopsy material (CTCs, corresponding ctDNA) and paired primary breast tumors. In the EpCAM-positive CTCs fraction we observed methylation of: a) CST6, in 11/30(37%) and 11/30(37%), b) BRMS1 in 8/30(27%) and 11/30(37%) c) SOX17 in 8/30(27%) and 13/30(43%) early breast cancer patients and patients with verified metastasis respectively. In ctDNA we observed methylation of: a) CST6, in 5/30(17%) and 10/31(32%), b) BRMS1 in 8/30 (27%) and 8/31 (26%) c) SOX17 in 5/30(17%) and 13/31(42%) early breast cancer patients and patients with verified metastasis respectively. Our results indicate a high cancerous load at the epigenetic level in EpCAM-positive CTCs fractions and corresponding ctDNA in breast cancer. The main principle of the developed methodology has the potential to be extended in a large number of gene-targets and be applied in many types of cancer. Copyright © 2016. Published by Elsevier B.V.
Segmentation of the ovine lung in 3D CT Images
NASA Astrophysics Data System (ADS)
Shi, Lijun; Hoffman, Eric A.; Reinhardt, Joseph M.
2004-04-01
Pulmonary CT images can provide detailed information about the regional structure and function of the respiratory system. Prior to any of these analyses, however, the lungs must be identified in the CT data sets. A popular animal model for understanding lung physiology and pathophysiology is the sheep. In this paper we describe a lung segmentation algorithm for CT images of sheep. The algorithm has two main steps. The first step is lung extraction, which identifies the lung region using a technique based on optimal thresholding and connected components analysis. The second step is lung separation, which separates the left lung from the right lung by identifying the central fissure using an anatomy-based method incorporating dynamic programming and a line filter algorithm. The lung segmentation algorithm has been validated by comparing our automatic method to manual analysis for five pulmonary CT datasets. The RMS error between the computer-defined and manually-traced boundary is 0.96 mm. The segmentation requires approximately 10 minutes for a 512x512x400 dataset on a PC workstation (2.40 GHZ CPU, 2.0 GB RAM), while it takes human observer approximately two hours to accomplish the same task.
Multimodal imaging of the human knee down to the cellular level
NASA Astrophysics Data System (ADS)
Schulz, G.; Götz, C.; Müller-Gerbl, M.; Zanette, I.; Zdora, M.-C.; Khimchenko, A.; Deyhle, H.; Thalmann, P.; Müller, B.
2017-06-01
Computed tomography reaches the best spatial resolution for the three-dimensional visualization of human tissues among the available nondestructive clinical imaging techniques. Nowadays, sub-millimeter voxel sizes are regularly obtained. Regarding investigations on true micrometer level, lab-based micro-CT (μCT) has become gold standard. The aim of the present study is firstly the hierarchical investigation of a human knee post mortem using hard X-ray μCT and secondly a multimodal imaging using absorption and phase contrast modes in order to investigate hard (bone) and soft (cartilage) tissues on the cellular level. After the visualization of the entire knee using a clinical CT, a hierarchical imaging study was performed using the lab-system nanotom® m. First, the entire knee was measured with a pixel length of 65 μm. The highest resolution with a pixel length of 3 μm could be achieved after extracting cylindrically shaped plugs from the femoral bones. For the visualization of the cartilage, grating-based phase contrast μCT (I13-2, Diamond Light Source) was performed. With an effective voxel size of 2.3 μm it was possible to visualize individual chondrocytes within the cartilage.
NASA Astrophysics Data System (ADS)
Takahashi, Noriyuki; Kinoshita, Toshibumi; Ohmura, Tomomi; Matsuyama, Eri; Toyoshima, Hideto
2018-02-01
The rapid increase in the incidence of Alzheimer's disease (AD) has become a critical issue in low and middle income countries. In general, MR imaging has become sufficiently suitable in clinical situations, while CT scan might be uncommonly used in the diagnosis of AD due to its low contrast between brain tissues. However, in those countries, CT scan, which is less costly and readily available, will be desired to become useful for the diagnosis of AD. For CT scan, the enlargement of the temporal horn of the lateral ventricle (THLV) is one of few findings for the diagnosis of AD. In this paper, we present an automated volumetry of THLV with segmentation based on Bayes' rule on CT images. In our method, first, all CT data sets are normalized into an atlas by using linear affine transformation and non-linear wrapping techniques. Next, a probability map of THLV is constructed in the normalized data. Then, THLV regions are extracted based on Bayes' rule. Finally, the volume of the THLV is evaluated. This scheme was applied to CT scans from 20 AD patients and 20 controls to evaluate the performance of the method for detecting AD. The estimated THLV volume was markedly increased in the AD group compared with the controls (P < .0001), and the area under the receiver operating characteristic curve (AUC) was 0.921. Therefore, this computerized method may have the potential to accurately detect AD on CT images.
A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction.
Kang, Eunhee; Min, Junhong; Ye, Jong Chul
2017-10-01
Due to the potential risk of inducing cancer, radiation exposure by X-ray CT devices should be reduced for routine patient scanning. However, in low-dose X-ray CT, severe artifacts typically occur due to photon starvation, beam hardening, and other causes, all of which decrease the reliability of the diagnosis. Thus, a high-quality reconstruction method from low-dose X-ray CT data has become a major research topic in the CT community. Conventional model-based de-noising approaches are, however, computationally very expensive, and image-domain de-noising approaches cannot readily remove CT-specific noise patterns. To tackle these problems, we want to develop a new low-dose X-ray CT algorithm based on a deep-learning approach. We propose an algorithm which uses a deep convolutional neural network (CNN) which is applied to the wavelet transform coefficients of low-dose CT images. More specifically, using a directional wavelet transform to extract the directional component of artifacts and exploit the intra- and inter- band correlations, our deep network can effectively suppress CT-specific noise. In addition, our CNN is designed with a residual learning architecture for faster network training and better performance. Experimental results confirm that the proposed algorithm effectively removes complex noise patterns from CT images derived from a reduced X-ray dose. In addition, we show that the wavelet-domain CNN is efficient when used to remove noise from low-dose CT compared to existing approaches. Our results were rigorously evaluated by several radiologists at the Mayo Clinic and won second place at the 2016 "Low-Dose CT Grand Challenge." To the best of our knowledge, this work is the first deep-learning architecture for low-dose CT reconstruction which has been rigorously evaluated and proven to be effective. In addition, the proposed algorithm, in contrast to existing model-based iterative reconstruction (MBIR) methods, has considerable potential to benefit from large data sets. Therefore, we believe that the proposed algorithm opens a new direction in the area of low-dose CT research. © 2017 American Association of Physicists in Medicine.
SU-F-I-06: Evaluation of Imaging Dose for Modulation Layer Based Dual Energy Cone-Beam CT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ju, Eunbin; Ahn, SoHyun; Cho, Samju
Purpose: Dual energy cone beam CT system is finding a variety of promising applications in diagnostic CT, both in imaging of endogenous materials and exogenous materials across a range of body sites. Dual energy cone beam CT system to suggest in this study acquire image by rotating 360 degree with half of the X-ray window covered using copper modulation layer. In the region that covered by modulation layer absorb the low energy X-ray by modulation layer. Relative high energy X-ray passes through the layer and contributes to image reconstruction. Dose evaluation should be carried out in order to utilize suchmore » an imaging acquirement technology for clinical use. Methods: For evaluating imaging dose of modulation layer based dual energy cone beam CT system, Prototype cone beam CT that configured X-ray tube (D054SB, Toshiba, Japan) and detector (PaxScan 2520V, Varian Medical Systems, Palo Alto, CA) is used. A range of 0.5–2.0 mm thickness of modulation layer is implemented in Monte Carlo simulation (MCNPX, ver. 2.6.0, Los Alamos National Laboratory, USA) with half of X-ray window covered. In-house phantom using in this study that has 3 cylindrical phantoms configured water, Teflon air with PMMA covered for verifying the comparability the various material in human body and is implemented in Monte Carlo simulation. The actual dose with 2.0 mm copper covered half of X-ray window is measured using Gafchromic EBT3 film with 5.0 mm bolus for compared with simulative dose. Results: Dose in phantom reduced 33% by copper modulation layer of 2.0 mm. Scattering dose occurred in modulation layer by Compton scattering effect is 0.04% of overall dose. Conclusion: Modulation layer of that based dual energy cone beam CT has not influence on unnecessary scatter dose. This study was supported by the Radiation Safety Research Programs (1305033) through the Nuclear Safety and Security Commission.« less
Adaptive learning compressive tracking based on Markov location prediction
NASA Astrophysics Data System (ADS)
Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan
2017-03-01
Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.
Multi-layer cube sampling for liver boundary detection in PET-CT images.
Liu, Xinxin; Yang, Jian; Song, Shuang; Song, Hong; Ai, Danni; Zhu, Jianjun; Jiang, Yurong; Wang, Yongtian
2018-06-01
Liver metabolic information is considered as a crucial diagnostic marker for the diagnosis of fever of unknown origin, and liver recognition is the basis of automatic diagnosis of metabolic information extraction. However, the poor quality of PET and CT images is a challenge for information extraction and target recognition in PET-CT images. The existing detection method cannot meet the requirement of liver recognition in PET-CT images, which is the key problem in the big data analysis of PET-CT images. A novel texture feature descriptor called multi-layer cube sampling (MLCS) is developed for liver boundary detection in low-dose CT and PET images. The cube sampling feature is proposed for extracting more texture information, which uses a bi-centric voxel strategy. Neighbour voxels are divided into three regions by the centre voxel and the reference voxel in the histogram, and the voxel distribution information is statistically classified as texture feature. Multi-layer texture features are also used to improve the ability and adaptability of target recognition in volume data. The proposed feature is tested on the PET and CT images for liver boundary detection. For the liver in the volume data, mean detection rate (DR) and mean error rate (ER) reached 95.15 and 7.81% in low-quality PET images, and 83.10 and 21.08% in low-contrast CT images. The experimental results demonstrated that the proposed method is effective and robust for liver boundary detection.
An open library of CT patient projection data
NASA Astrophysics Data System (ADS)
Chen, Baiyu; Leng, Shuai; Yu, Lifeng; Holmes, David; Fletcher, Joel; McCollough, Cynthia
2016-03-01
Lack of access to projection data from patient CT scans is a major limitation for development and validation of new reconstruction algorithms. To meet this critical need, we are building a library of CT patient projection data in an open and vendor-neutral format, DICOM-CT-PD, which is an extended DICOM format that contains sinogram data, acquisition geometry, patient information, and pathology identification. The library consists of scans of various types, including head scans, chest scans, abdomen scans, electrocardiogram (ECG)-gated scans, and dual-energy scans. For each scan, three types of data are provided, including DICOM-CT-PD projection data at various dose levels, reconstructed CT images, and a free-form text file. Several instructional documents are provided to help the users extract information from DICOM-CT-PD files, including a dictionary file for the DICOM-CT-PD format, a DICOM-CT-PD reader, and a user manual. Radiologist detection performance based on the reconstructed CT images is also provided. So far 328 head cases, 228 chest cases, and 228 abdomen cases have been collected for potential inclusion. The final library will include a selection of 50 head, chest, and abdomen scans each from at least two different manufacturers, and a few ECG-gated scans and dual-source, dual-energy scans. It will be freely available to academic researchers, and is expected to greatly facilitate the development and validation of CT reconstruction algorithms.
State of the art: dual-energy CT of the abdomen.
Marin, Daniele; Boll, Daniel T; Mileto, Achille; Nelson, Rendon C
2014-05-01
Recent technologic advances in computed tomography (CT)--enabling the nearly simultaneous acquisition of clinical images using two different x-ray energy spectra--have sparked renewed interest in dual-energy CT. By interrogating the unique characteristics of different materials at different x-ray energies, dual-energy CT can be used to provide quantitative information about tissue composition, overcoming the limitations of attenuation-based conventional single-energy CT imaging. In the past few years, intensive research efforts have been devoted to exploiting the unique and powerful opportunities of dual-energy CT for a variety of clinical applications. This has led to CT protocol modifications for radiation dose reduction, improved diagnostic performance for detection and characterization of diseases, as well as image quality optimization. In this review, the authors discuss the basic principles, instrumentation and design, examples of current clinical applications in the abdomen and pelvis, and future opportunities of dual-energy CT.
Robust x-ray based material identification using multi-energy sinogram decomposition
NASA Astrophysics Data System (ADS)
Yuan, Yaoshen; Tracey, Brian; Miller, Eric
2016-05-01
There is growing interest in developing X-ray computed tomography (CT) imaging systems with improved ability to discriminate material types, going beyond the attenuation imaging provided by most current systems. Dual- energy CT (DECT) systems can partially address this problem by estimating Compton and photoelectric (PE) coefficients of the materials being imaged, but DECT is greatly degraded by the presence of metal or other materials with high attenuation. Here we explore the advantages of multi-energy CT (MECT) systems based on photon-counting detectors. The utility of MECT has been demonstrated in medical applications where photon- counting detectors allow for the resolution of absorption K-edges. Our primary concern is aviation security applications where K-edges are rare. We simulate phantoms with differing amounts of metal (high, medium and low attenuation), both for switched-source DECT and for MECT systems, and include a realistic model of detector energy 0 resolution. We extend the DECT sinogram decomposition method of Ying et al. to MECT, allowing estimation of separate Compton and photoelectric sinograms. We furthermore introduce a weighting based on a quadratic approximation to the Poisson likelihood function that deemphasizes energy bins with low signal. Simulation results show that the proposed approach succeeds in estimating material properties even in high-attenuation scenarios where the DECT method fails, improving the signal to noise ratio of reconstructions by over 20 dB for the high-attenuation phantom. Our work demonstrates the potential of using photon counting detectors for stably recovering material properties even when high attenuation is present, thus enabling the development of improved scanning systems.
MARS spectral molecular imaging of lamb tissue: data collection and image analysis
NASA Astrophysics Data System (ADS)
Aamir, R.; Chernoglazov, A.; Bateman, C. J.; Butler, A. P. H.; Butler, P. H.; Anderson, N. G.; Bell, S. T.; Panta, R. K.; Healy, J. L.; Mohr, J. L.; Rajendran, K.; Walsh, M. F.; de Ruiter, N.; Gieseg, S. P.; Woodfield, T.; Renaud, P. F.; Brooke, L.; Abdul-Majid, S.; Clyne, M.; Glendenning, R.; Bones, P. J.; Billinghurst, M.; Bartneck, C.; Mandalika, H.; Grasset, R.; Schleich, N.; Scott, N.; Nik, S. J.; Opie, A.; Janmale, T.; Tang, D. N.; Kim, D.; Doesburg, R. M.; Zainon, R.; Ronaldson, J. P.; Cook, N. J.; Smithies, D. J.; Hodge, K.
2014-02-01
Spectral molecular imaging is a new imaging technique able to discriminate and quantify different components of tissue simultaneously at high spatial and high energy resolution. Our MARS scanner is an x-ray based small animal CT system designed to be used in the diagnostic energy range (20-140 keV). In this paper, we demonstrate the use of the MARS scanner, equipped with the Medipix3RX spectroscopic photon-processing detector, to discriminate fat, calcium, and water in tissue. We present data collected from a sample of lamb meat including bone as an illustrative example of human tissue imaging. The data is analyzed using our 3D Algebraic Reconstruction Algorithm (MARS-ART) and by material decomposition based on a constrained linear least squares algorithm. The results presented here clearly show the quantification of lipid-like, water-like and bone-like components of tissue. However, it is also clear to us that better algorithms could extract more information of clinical interest from our data. Because we are one of the first to present data from multi-energy photon-processing small animal CT systems, we make the raw, partial and fully processed data available with the intention that others can analyze it using their familiar routines. The raw, partially processed and fully processed data of lamb tissue along with the phantom calibration data can be found at http://hdl.handle.net/10092/8531.
Automated segmentation of murine lung tumors in x-ray micro-CT images
NASA Astrophysics Data System (ADS)
Swee, Joshua K. Y.; Sheridan, Clare; de Bruin, Elza; Downward, Julian; Lassailly, Francois; Pizarro, Luis
2014-03-01
Recent years have seen micro-CT emerge as a means of providing imaging analysis in pre-clinical study, with in-vivo micro-CT having been shown to be particularly applicable to the examination of murine lung tumors. Despite this, existing studies have involved substantial human intervention during the image analysis process, with the use of fully-automated aids found to be almost non-existent. We present a new approach to automate the segmentation of murine lung tumors designed specifically for in-vivo micro-CT-based pre-clinical lung cancer studies that addresses the specific requirements of such study, as well as the limitations human-centric segmentation approaches experience when applied to such micro-CT data. Our approach consists of three distinct stages, and begins by utilizing edge enhancing and vessel enhancing non-linear anisotropic diffusion filters to extract anatomy masks (lung/vessel structure) in a pre-processing stage. Initial candidate detection is then performed through ROI reduction utilizing obtained masks and a two-step automated segmentation approach that aims to extract all disconnected objects within the ROI, and consists of Otsu thresholding, mathematical morphology and marker-driven watershed. False positive reduction is finally performed on initial candidates through random-forest-driven classification using the shape, intensity, and spatial features of candidates. We provide validation of our approach using data from an associated lung cancer study, showing favorable results both in terms of detection (sensitivity=86%, specificity=89%) and structural recovery (Dice Similarity=0.88) when compared against manual specialist annotation.
Segmentation algorithm of colon based on multi-slice CT colonography
NASA Astrophysics Data System (ADS)
Hu, Yizhong; Ahamed, Mohammed Shabbir; Takahashi, Eiji; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Suzuki, Masahiro; Iinuma, Gen; Moriyama, Noriyuki
2012-02-01
CT colonography is a radiology test that looks at people's large intestines(colon). CT colonography can screen many options of colon cancer. This test is used to detect polyps or cancers of the colon. CT colonography is safe and reliable. It can be used if people are too sick to undergo other forms of colon cancer screening. In our research, we proposed a method for automatic segmentation of the colon from abdominal computed Tomography (CT) images. Our multistage detection method extracted colon and spited colon into different parts according to the colon anatomy information. We found that among the five segmented parts of the colon, sigmoid (20%) and rectum (50%) are more sensitive toward polyps and masses than the other three parts. Our research focused on detecting the colon by the individual diagnosis of sigmoid and rectum. We think it would make the rapid and easy diagnosis of colon in its earlier stage and help doctors for analysis of correct position of each part and detect the colon rectal cancer much easier.
Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning.
Cha, Kenny H; Hadjiiski, Lubomir; Chan, Heang-Ping; Weizer, Alon Z; Alva, Ajjai; Cohan, Richard H; Caoili, Elaine M; Paramagul, Chintana; Samala, Ravi K
2017-08-18
Cross-sectional X-ray imaging has become the standard for staging most solid organ malignancies. However, for some malignancies such as urinary bladder cancer, the ability to accurately assess local extent of the disease and understand response to systemic chemotherapy is limited with current imaging approaches. In this study, we explored the feasibility that radiomics-based predictive models using pre- and post-treatment computed tomography (CT) images might be able to distinguish between bladder cancers with and without complete chemotherapy responses. We assessed three unique radiomics-based predictive models, each of which employed different fundamental design principles ranging from a pattern recognition method via deep-learning convolution neural network (DL-CNN), to a more deterministic radiomics feature-based approach and then a bridging method between the two, utilizing a system which extracts radiomics features from the image patterns. Our study indicates that the computerized assessment using radiomics information from the pre- and post-treatment CT of bladder cancer patients has the potential to assist in assessment of treatment response.
NASA Astrophysics Data System (ADS)
Yamauchi, Daisuke; Tamaoki, Daisuke; Hayami, Masato; Uesugi, Kentaro; Takeuchi, Akihisa; Suzuki, Yoshio; Karahara, Ichirou; Mineyuki, Yoshinobu
2012-07-01
How biological form is determined is one of the important questions in developmental biology. Physical forces are thought to be the primary determinants of the biological forms, and several theories for this were proposed nearly a century ago. To evaluate how physical forces can influence biological forms, precise determination of cell and tissue shapes and their geometries is necessary. Computed tomography (CT) is useful for visualizing three-dimensional structures without destroying a sample. Because recent progress in micro-CT has enabled visualizing cells and tissues at the sub-micron level, we investigated if we could extract cell and tissue outlines of seeds using refraction contrast X-ray CT available at the SPring-8 synchrotron radiation facility. We used Arabidopsis seeds because Arabidopsis is a well-known model plant and its seed size is small enough to obtain whole images using the X-ray CT experimental system. We could trace the outlines of tissues in dry seeds using beamline BL20B2 (10 keV, 2.4µm.pixel-1). Although we could also detect the outlines of some cell types, the image resolution was not adequate to extract whole cell edges. To detect the edges of cells in the epidermis and cortex, we obtained CT images using beamline BL20XU (8 keV, 0.5 µm.pixel-1). With these CT images, we could extract the facets and edges of each cell and determine cell vertices. This method enabled us to compare the numbers of cell facets among various cell types. We could also describe cell geometry as a set of points that showed these cell vertices.
MicroCT and optical coherence tomography imagistic assessment of the dental roots adhesive
NASA Astrophysics Data System (ADS)
Sinescu, Cosmin; Negrutiu, Meda Lavinia; Nica, Luminita; Manescu, Adrian; Duma, Virgil-Florin; Podoleanu, Adrian G.
2015-03-01
Several obturation methods are available today to study the 3D filling of the root canal. There are also several methods capable to evaluate the ability to seal apically the root canals. However, the common methods of investigation are invasive; they also lead to the destruction of the samples. If the sectioning differs slightly from the desired area, the investigation is non-conclusive regarding the micro-leakages. Also, although the use of Cone-Beam Micro Computer Tomography (CBCT) appears to be most promising for endodontic purposes, its effective radiation doses are higher than with conventional intra-oral and panoramic imaging. In contrast, enface (ef) Optical Coherence Tomography (OCT) proves to be efficient for the investigation of material defects of dental restorations, dental materials, and micro-leakage at the interfaces, where the penetration depth depends on the material. Therefore, ef OCT has been proposed in our studies as a potential tool for in vivo endodontic imaging. Twenty five recently extracted human maxillary molars were selected for the study for caries or periodontal reasons. The pulp chambers were completely opened, the dental pulp was removed, and the root canals were shaped. Silver nanoparticles were used in half of the samples in order to increase the scattering of the adhesive material in comparison with the dental roots walls. The sample teeth were then probed using Time Domain (TD) OCT working at 1300 nm. A synchrotron radiation X-Ray microCT experiment was also performed. The imagistic results pointed out the efficiency of the silver nanoparticle layer used in order to increase the scattering of the root canal adhesive scattering for the OCT non-invasive investigation. MicroCT allowed for obtaining qualitative data related to the depth penetration of the root canal adhesive into the dentin walls.
Kawahara, Daisuke; Ozawa, Shuichi; Yokomachi, Kazushi; Tanaka, Sodai; Higaki, Toru; Fujioka, Chikako; Suzuki, Tatsuhiko; Tsuneda, Masato; Nakashima, Takeo; Ohno, Yoshimi; Nagata, Yasushi
2018-02-01
To evaluate the accuracy of raw-data-based effective atomic number (Z eff ) values and monochromatic CT numbers for contrast material of varying iodine concentrations, obtained using dual-energy CT. We used a tissue characterization phantom and varying concentrations of iodinated contrast medium. A comparison between the theoretical values of Z eff and that provided by the manufacturer was performed. The measured and theoretical monochromatic CT numbers at 40-130 keV were compared. The average difference between the Z eff values of lung (inhale) inserts in the tissue characterization phantom was 81.3% and the average Z eff difference was within 8.4%. The average difference between the Z eff values of the varying concentrations of iodinated contrast medium was within 11.2%. For the varying concentrations of iodinated contrast medium, the differences between the measured and theoretical monochromatic CT values increased with decreasing monochromatic energy. The Z eff and monochromatic CT numbers in the tissue characterization phantom were reasonably accurate. The accuracy of the raw-data-based Z eff values was higher than that of image-based Z eff values in the tissue-equivalent phantom. The accuracy of Z eff values in the contrast medium was in good agreement within the maximum SD found in the iodine concentration range of clinical dynamic CT imaging. Moreover, the optimum monochromatic energy for human tissue and iodinated contrast medium was found to be 70 keV. Advances in knowledge: The accuracy of the Z eff values and monochromatic CT numbers of the contrast medium created by raw-data-based, dual-energy CT could be sufficient in clinical conditions.
Yu, Huan; Caldwell, Curtis; Mah, Katherine; Mozeg, Daniel
2009-03-01
Coregistered fluoro-deoxy-glucose (FDG) positron emission tomography/computed tomography (PET/CT) has shown potential to improve the accuracy of radiation targeting of head and neck cancer (HNC) when compared to the use of CT simulation alone. The objective of this study was to identify textural features useful in distinguishing tumor from normal tissue in head and neck via quantitative texture analysis of coregistered 18F-FDG PET and CT images. Abnormal and typical normal tissues were manually segmented from PET/CT images of 20 patients with HNC and 20 patients with lung cancer. Texture features including some derived from spatial grey-level dependence matrices (SGLDM) and neighborhood gray-tone-difference matrices (NGTDM) were selected for characterization of these segmented regions of interest (ROIs). Both K nearest neighbors (KNNs) and decision tree (DT)-based KNN classifiers were employed to discriminate images of abnormal and normal tissues. The area under the curve (AZ) of receiver operating characteristics (ROC) was used to evaluate the discrimination performance of features in comparison to an expert observer. The leave-one-out and bootstrap techniques were used to validate the results. The AZ of DT-based KNN classifier was 0.95. Sensitivity and specificity for normal and abnormal tissue classification were 89% and 99%, respectively. In summary, NGTDM features such as PET Coarseness, PET Contrast, and CT Coarseness extracted from FDG PET/CT images provided good discrimination performance. The clinical use of such features may lead to improvement in the accuracy of radiation targeting of HNC.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harms, Joseph; Wang, Tonghe; Petrongolo, Michael
Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is basedmore » on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan{sup ©}600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan{sup ©}600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Faby, Sebastian, E-mail: sebastian.faby@dkfz.de; Kuchenbecker, Stefan; Sawall, Stefan
2015-07-15
Purpose: To study the performance of different dual energy computed tomography (DECT) techniques, which are available today, and future multi energy CT (MECT) employing novel photon counting detectors in an image-based material decomposition task. Methods: The material decomposition performance of different energy-resolved CT acquisition techniques is assessed and compared in a simulation study of virtual non-contrast imaging and iodine quantification. The material-specific images are obtained via a statistically optimal image-based material decomposition. A projection-based maximum likelihood approach was used for comparison with the authors’ image-based method. The different dedicated dual energy CT techniques are simulated employing realistic noise models andmore » x-ray spectra. The authors compare dual source DECT with fast kV switching DECT and the dual layer sandwich detector DECT approach. Subsequent scanning and a subtraction method are studied as well. Further, the authors benchmark future MECT with novel photon counting detectors in a dedicated DECT application against the performance of today’s DECT using a realistic model. Additionally, possible dual source concepts employing photon counting detectors are studied. Results: The DECT comparison study shows that dual source DECT has the best performance, followed by the fast kV switching technique and the sandwich detector approach. Comparing DECT with future MECT, the authors found noticeable material image quality improvements for an ideal photon counting detector; however, a realistic detector model with multiple energy bins predicts a performance on the level of dual source DECT at 100 kV/Sn 140 kV. Employing photon counting detectors in dual source concepts can improve the performance again above the level of a single realistic photon counting detector and also above the level of dual source DECT. Conclusions: Substantial differences in the performance of today’s DECT approaches were found for the application of virtual non-contrast and iodine imaging. Future MECT with realistic photon counting detectors currently can only perform comparably to dual source DECT at 100 kV/Sn 140 kV. Dual source concepts with photon counting detectors could be a solution to this problem, promising a better performance.« less
Poster — Thur Eve — 14: Improving Tissue Segmentation for Monte Carlo Dose Calculation using DECT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Di Salvio, A.; Bedwani, S.; Carrier, J-F.
2014-08-15
Purpose: To improve Monte Carlo dose calculation accuracy through a new tissue segmentation technique with dual energy CT (DECT). Methods: Electron density (ED) and effective atomic number (EAN) can be extracted directly from DECT data with a stoichiometric calibration method. Images are acquired with Monte Carlo CT projections using the user code egs-cbct and reconstructed using an FDK backprojection algorithm. Calibration is performed using projections of a numerical RMI phantom. A weighted parameter algorithm then uses both EAN and ED to assign materials to voxels from DECT simulated images. This new method is compared to a standard tissue characterization frommore » single energy CT (SECT) data using a segmented calibrated Hounsfield unit (HU) to ED curve. Both methods are compared to the reference numerical head phantom. Monte Carlo simulations on uniform phantoms of different tissues using dosxyz-nrc show discrepancies in depth-dose distributions. Results: Both SECT and DECT segmentation methods show similar performance assigning soft tissues. Performance is however improved with DECT in regions with higher density, such as bones, where it assigns materials correctly 8% more often than segmentation with SECT, considering the same set of tissues and simulated clinical CT images, i.e. including noise and reconstruction artifacts. Furthermore, Monte Carlo results indicate that kV photon beam depth-dose distributions can double between two tissues of density higher than muscle. Conclusions: A direct acquisition of ED and the added information of EAN with DECT data improves tissue segmentation and increases the accuracy of Monte Carlo dose calculation in kV photon beams.« less
Yunker, Bryan E; Cordes, Dietmar; Scherzinger, Ann L; Dodd, Gerald D; Shandas, Robin; Feng, Yusheng; Hunter, Kendall S
2013-05-01
This study investigated the ultrasound, MRI, and CT imaging characteristics of several industrial casting and molding compounds as a precursor to the future development of durable and anatomically correct flow phantoms. A set of usability and performance criteria was established for a proposed phantom design capable of supporting liquid flow during imaging. A literature search was conducted to identify the materials and methods previously used in phantom fabrication. A database of human tissue and casting material properties was compiled to facilitate the selection of appropriate materials for testing. Several industrial casting materials were selected, procured, and used to fabricate test samples that were imaged with ultrasound, MRI, and CT. Five silicones and one polyurethane were selected for testing. Samples of all materials were successfully fabricated. All imaging modalities were able to discriminate between the materials tested. Ultrasound testing showed that three of the silicones could be imaged to a depth of at least 2.5 cm (1 in.). The RP-6400 polyurethane exhibited excellent contrast and edge detail for MRI phantoms and appears to be an excellent water reference for CT applications. The 10T and 27T silicones appear to be usable water references for MRI imaging. Based on study data and the stated selection criteria, the P-4 silicone provided sufficient material contrast to water and edge detail for use across all imaging modalities with the benefits of availability, low cost, dimensional stability, nontoxic, nonflammable, durable, cleanable, and optical clarity. The physical and imaging differences of the materials documented in this study may be useful for other applications.
NASA Astrophysics Data System (ADS)
Yang, Zili
2017-07-01
Heart segmentation is an important auxiliary method in the diagnosis of many heart diseases, such as coronary heart disease and atrial fibrillation, and in the planning of tumor radiotherapy. Most of the existing methods for full heart segmentation treat the heart as a whole part and cannot accurately extract the bottom of the heart. In this paper, we propose a new method based on linear gradient model to segment the whole heart from the CT images automatically and accurately. Twelve cases were tested in order to test this method and accurate segmentation results were achieved and identified by clinical experts. The results can provide reliable clinical support.
Automatic lesion tracking for a PET/CT based computer aided cancer therapy monitoring system
NASA Astrophysics Data System (ADS)
Opfer, Roland; Brenner, Winfried; Carlsen, Ingwer; Renisch, Steffen; Sabczynski, Jörg; Wiemker, Rafael
2008-03-01
Response assessment of cancer therapy is a crucial component towards a more effective and patient individualized cancer therapy. Integrated PET/CT systems provide the opportunity to combine morphologic with functional information. However, dealing simultaneously with several PET/CT scans poses a serious workflow problem. It can be a difficult and tedious task to extract response criteria based upon an integrated analysis of PET and CT images and to track these criteria over time. In order to improve the workflow for serial analysis of PET/CT scans we introduce in this paper a fast lesion tracking algorithm. We combine a global multi-resolution rigid registration algorithm with a local block matching and a local region growing algorithm. Whenever the user clicks on a lesion in the base-line PET scan the course of standardized uptake values (SUV) is automatically identified and shown to the user as a graph plot. We have validated our method by a data collection from 7 patients. Each patient underwent two or three PET/CT scans during the course of a cancer therapy. An experienced nuclear medicine physician manually measured the courses of the maximum SUVs for altogether 18 lesions. As a result we obtained that the automatic detection of the corresponding lesions resulted in SUV measurements which are nearly identical to the manually measured SUVs. Between 38 measured maximum SUVs derived from manual and automatic detected lesions we observed a correlation of 0.9994 and a average error of 0.4 SUV units.
Development of a fluorescent x-ray source for medical imaging
NASA Astrophysics Data System (ADS)
Toyofuku, F.; Tokumori, K.; Nishimura, K.; Saito, T.; Takeda, T.; Itai, Y.; Hyodo, K.; Ando, M.; Endo, M.; Naito, H.; Uyama, C.
1995-02-01
A fluorescent x-ray source for medical imaging, such as K-edge subtraction angiography and monochromatic x-ray CT, has been developed. Using a 6.5 GeV accumulation ring in Tsukuba, fluorescent x rays, which range from about 30 to 70 keV are generated by irradiating several target materials. Measurements have been made of output intensities and energy spectra for different target angles and extraction angles. The intensities of fluorescent x rays at a 30 mA beam current are on the order of 1-3×106 photons/mm2/s at 30 cm from the local spot where the incident beam is collimated to 1 mm2. A phantom which contains three different contrast media (iodine, barium, gadolinium) was used for the K-edge energy subtraction, and element selective CT images were obtained.
Accurate registration of temporal CT images for pulmonary nodules detection
NASA Astrophysics Data System (ADS)
Yan, Jichao; Jiang, Luan; Li, Qiang
2017-02-01
Interpretation of temporal CT images could help the radiologists to detect some subtle interval changes in the sequential examinations. The purpose of this study was to develop a fully automated scheme for accurate registration of temporal CT images for pulmonary nodule detection. Our method consisted of three major registration steps. Firstly, affine transformation was applied in the segmented lung region to obtain global coarse registration images. Secondly, B-splines based free-form deformation (FFD) was used to refine the coarse registration images. Thirdly, Demons algorithm was performed to align the feature points extracted from the registered images in the second step and the reference images. Our database consisted of 91 temporal CT cases obtained from Beijing 301 Hospital and Shanghai Changzheng Hospital. The preliminary results showed that approximately 96.7% cases could obtain accurate registration based on subjective observation. The subtraction images of the reference images and the rigid and non-rigid registered images could effectively remove the normal structures (i.e. blood vessels) and retain the abnormalities (i.e. pulmonary nodules). This would be useful for the screening of lung cancer in our future study.
Robust model-based 3d/3D fusion using sparse matching for minimally invasive surgery.
Neumann, Dominik; Grbic, Sasa; John, Matthias; Navab, Nassir; Hornegger, Joachim; Ionasec, Razvan
2013-01-01
Classical surgery is being disrupted by minimally invasive and transcatheter procedures. As there is no direct view or access to the affected anatomy, advanced imaging techniques such as 3D C-arm CT and C-arm fluoroscopy are routinely used for intra-operative guidance. However, intra-operative modalities have limited image quality of the soft tissue and a reliable assessment of the cardiac anatomy can only be made by injecting contrast agent, which is harmful to the patient and requires complex acquisition protocols. We propose a novel sparse matching approach for fusing high quality pre-operative CT and non-contrasted, non-gated intra-operative C-arm CT by utilizing robust machine learning and numerical optimization techniques. Thus, high-quality patient-specific models can be extracted from the pre-operative CT and mapped to the intra-operative imaging environment to guide minimally invasive procedures. Extensive quantitative experiments demonstrate that our model-based fusion approach has an average execution time of 2.9 s, while the accuracy lies within expert user confidence intervals.
Guo, Zongxia; Gong, Ruiying; Jiang, Yi; Wan, Xiaobo
2015-08-14
Oligopeptide-based derivatives are important synthons for bio-based functional materials. In this article, a Gly-(L-Val)-Gly-(L-Val)-coumarin (GVGV-Cou) conjugate was synthesized, which forms 3D networks in ethanol. The gel nanostructures were characterized by UV-vis spectroscopy, FT-IR spectroscopy, X-ray diffraction (XRD), SEM and TEM. It is suggested that the formation of charge transfer (CT) complexes between the coumarin moieties is the main driving force for the gel formation. The capability of the gel to encapsulate and release dyes was explored. Both Congo Red (CR) and Methylene Blue (MB) can be trapped in the CT gel matrix and released over time. The present gel might be used as a functional soft material for guest encapsulation and release.
Park, Wonse; Choi, Ji-Wook; Kim, Jae-Young; Kim, Bong-Chul; Kim, Hyung Jun; Lee, Sang-Hwy
2010-03-01
Paresthesia is a well-known complication of extraction of mandibular third molars (MTMs). The authors evaluated the relationship between paresthesia after MTM extraction and the cortical integrity of the inferior alveolar canal (IAC) by using computed tomography (CT). The authors designed a retrospective cohort study involving participants considered, on the basis of panoramic imaging, to be at high risk of experiencing injury of the inferior alveolar nerve who subsequently underwent CT imaging and extraction of the MTMs. The primary predictor variable was the contact relationship between the IAC and the MTM as viewed on a CT image, classified into three groups: group 1, no contact; group 2, contact between the MTM and the intact IAC cortex; group 3, contact between the MTM and the interrupted IAC cortex. The secondary predictor variable was the number of CT image slices showing the cortical interruption around the MTM. The outcome variable was the presence or absence of postoperative paresthesia after MTM extraction. The study sample comprised 179 participants who underwent MTM extraction (a total of 259 MTMs). Their mean age was 23.6 years, and 85 (47.5 percent) were male. The overall prevalence of paresthesia was 4.2 percent (11 of 259 teeth). The prevalence of paresthesia in group 3 (involving an interrupted IAC cortex) was 11.8 percent (10 of 85 cases), while for group 2 (involving an intact IAC cortex) and group 1 (involving no contact) it was 1.0 percent (1 of 98 cases) and 0.0 percent (no cases), respectively. The frequency of nerve damage increased with the number of CT image slices showing loss of cortical integrity (P=.043). The results of this study indicate that loss of IAC cortical integrity is associated with an increased risk of experiencing paresthesia after MTM extraction.
Padma, A; Sukanesh, R
2013-01-01
A computer software system is designed for the segmentation and classification of benign from malignant tumour slices in brain computed tomography (CT) images. This paper presents a method to find and select both the dominant run length and co-occurrence texture features of region of interest (ROI) of the tumour region of each slice to be segmented by Fuzzy c means clustering (FCM) and evaluate the performance of support vector machine (SVM)-based classifiers in classifying benign and malignant tumour slices. Two hundred and six tumour confirmed CT slices are considered in this study. A total of 17 texture features are extracted by a feature extraction procedure, and six features are selected using Principal Component Analysis (PCA). This study constructed the SVM-based classifier with the selected features and by comparing the segmentation results with the experienced radiologist labelled ground truth (target). Quantitative analysis between ground truth and segmented tumour is presented in terms of segmentation accuracy, segmentation error and overlap similarity measures such as the Jaccard index. The classification performance of the SVM-based classifier with the same selected features is also evaluated using a 10-fold cross-validation method. The proposed system provides some newly found texture features have an important contribution in classifying benign and malignant tumour slices efficiently and accurately with less computational time. The experimental results showed that the proposed system is able to achieve the highest segmentation and classification accuracy effectiveness as measured by jaccard index and sensitivity and specificity.
Freesmeyer, Martin; Kühnel, Christian; Westphal, Julian G
2015-01-01
Benign thyroid diseases are widely common in western societies. However, the volumetry of the thyroid gland, especially when enlarged or abnormally formed, proves to be a challenge in clinical routine. The aim of this study was to develop a simple and rapid threshold-based isocontour extraction method for thyroid volumetry from (124)I-PET/CT data in patients scheduled for radioactive iodine therapy. PET/CT data from 45 patients were analysed 30 h after 1 MBq (124)I administration. Anatomical reference volume was calculated using manually contoured data from low-dose CT images of the neck (MC). In addition, we applied an automatic isocontour extraction method (IC0.2/1.0), with two different threshold values (0.2 and 1.0 kBq/ml), for volumetry of the PET data-set. IC0.2/1.0 shape data that showed significant variation from MC data were excluded. Subsequently, a mathematical correlation using a model of linear regression with multiple variables and step-wise elimination (mIC0.2/1.0), between IC0.2/1.0 and MC, was established. Data from 41 patients (IC0.2), and 32 patients (IC1.0) were analysed. The mathematically calculated volume, mIC, showed a median deviation from the reference (MC), of ±9 % (1-54 %) for mIC0.2 and of ±8.2 % (1-50 %) for mIC1.0 CONCLUSION: Contour extraction with both, mIC1.0 and mIC0.2 gave rapid and reliable results. However, mIC0.2 can be applied to significantly more patients (>90 %) and is, therefore, deemed to be more suitable for clinical routine, keeping in mind the potential advantages of using (124)I-PET/CT for the preparation of patients scheduled for radioactive iodine therapy.
Wang, Xiaoqin; Li, Guizhen; Row, Kyung Ho
2017-08-01
Magnetic graphene oxide was modified by four imidazole-based ionic liquids to synthesize materials for the extraction of polysaccharides by magnetic solid-phase extraction. Fucoidan and laminarin were chosen as the representative polysaccharides owing to their excellent pharmaceutical value and availability. Fourier transform infrared spectroscopy, field-emission scanning electron microscopy, and thermogravimetric analysis were applied to characterize the synthesized materials. Single-factor experiments showed that the extraction efficiency of polysaccharides was affected by the amount of ionic liquids for modification, solid-liquid ratio of brown alga and ethanol, the stirring time of brown alga and ionic liquid-modified magnetic graphene oxide materials, and amount of 1-(3-aminopropyl)imidazole chloride modified magnetic graphene oxide materials added to the brown alga sample solution. The results indicated that 1-(3-aminopropyl)imidazole chloride modified magnetic graphene oxide possessed better extraction ability than graphene oxide, magnetic graphene oxide, and other three ionic-liquid-modified magnetic graphene oxide materials. The highest extraction recoveries of fucoidan and laminarin extracted by 1-(3-aminopropyl)imidazole chloride modified magnetic graphene oxide were 93.3 and 87.2%, respectively. In addition, solid materials could be separated and reused easily owing to their magnetic properties. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Silva, E J; Perez, R; Valentim, R M; Belladonna, F G; De-Deus, G A; Lima, I C; Neves, A A
2017-04-01
To evaluate, using a novel micro-CT approach, the solubility and dimensional changes of an MTA-based sealer inside the root canal system after a solubility challenge. The MTA-based material (MTA Fillapex) was compared to a gold standard epoxy-based endodontic sealer (AH Plus). Ten human mandibular premolars with a single canal were divided randomly into two groups (n = 5) according to the sealer used. The canals were instrumented using the Reciproc System (VDW) with a R40 file and filled with R40 gutta-percha cones and one of the sealers. The filled canals were immediately scanned in a micro-CT, and after that, the teeth were immersed in 20 mL phosphate-buffered saline (PBS) at 37 °C for 7 days, when they were removed and rescanned. Final image stacks were registered against the initial stacks and the numerical difference between the initial and final volume of the filling material was obtained. Calculations were performed to identify dimensional changes of the filling material. All image stacks were 3D rendered to disclose areas of dislocation of the filling material inside or outside the root canal. The Shapiro-Wilk's test revealed that data were normally distributed; thus, the Student's t-test was used to detect statistically significant changes, assuming a 5% α-error. No significant changes were seen for the percentage volume of material lost after the solubility challenge for both AH Plus and MTA Fillapex groups (1.44% and 1.16%, respectively). A significant difference was, however, found for the volume of filling material which revealed dimensional changes after the solubility test (6.68% for MTA Fillapex and 1.09% for AH Plus). In fact, observation of 3D models disclosed that MTA Fillapex was associated with material extrusion through the foramen in all but one sample. In AH Plus filled samples, no material extrusion was detected. Although the solubility of both sealers was similar using this novel micro-CT approach, MTA Fillapex was associated with significant dimensional changes related to material extrusion through the apex after PBS storage compared to AH Plus. © 2016 International Endodontic Journal. Published by John Wiley & Sons Ltd.
Dual-energy and low-kVp CT in the abdomen.
Yeh, Benjamin M; Shepherd, John A; Wang, Zhen J; Teh, Hui Seong; Hartman, Robert P; Prevrhal, Sven
2009-07-01
The purpose of this article is to discuss the influence of tube potential on CT images and explore the potential impact of dual-energy CT on imaging of the abdomen and pelvis. Low peak tube voltage (kVp) settings provide high conspicuity of contrast materials at CT but may result in high image noise, particularly in larger patients. Material decomposition at dual-energy CT can differentiate renal stones by their composition, quantify tissue iron stores, improve the detection of pathologic hyperenhancement, and reduce contrast material and radiation dose compared with conventional CT. Further clinical research and technique refinement will be needed as the usage of these exciting technologies spreads.
Comparison of atlas-based techniques for whole-body bone segmentation.
Arabi, Hossein; Zaidi, Habib
2017-02-01
We evaluate the accuracy of whole-body bone extraction from whole-body MR images using a number of atlas-based segmentation methods. The motivation behind this work is to find the most promising approach for the purpose of MRI-guided derivation of PET attenuation maps in whole-body PET/MRI. To this end, a variety of atlas-based segmentation strategies commonly used in medical image segmentation and pseudo-CT generation were implemented and evaluated in terms of whole-body bone segmentation accuracy. Bone segmentation was performed on 23 whole-body CT/MR image pairs via leave-one-out cross validation procedure. The evaluated segmentation techniques include: (i) intensity averaging (IA), (ii) majority voting (MV), (iii) global and (iv) local (voxel-wise) weighting atlas fusion frameworks implemented utilizing normalized mutual information (NMI), normalized cross-correlation (NCC) and mean square distance (MSD) as image similarity measures for calculating the weighting factors, along with other atlas-dependent algorithms, such as (v) shape-based averaging (SBA) and (vi) Hofmann's pseudo-CT generation method. The performance evaluation of the different segmentation techniques was carried out in terms of estimating bone extraction accuracy from whole-body MRI using standard metrics, such as Dice similarity (DSC) and relative volume difference (RVD) considering bony structures obtained from intensity thresholding of the reference CT images as the ground truth. Considering the Dice criterion, global weighting atlas fusion methods provided moderate improvement of whole-body bone segmentation (DSC= 0.65 ± 0.05) compared to non-weighted IA (DSC= 0.60 ± 0.02). The local weighed atlas fusion approach using the MSD similarity measure outperformed the other strategies by achieving a DSC of 0.81 ± 0.03 while using the NCC and NMI measures resulted in a DSC of 0.78 ± 0.05 and 0.75 ± 0.04, respectively. Despite very long computation time, the extracted bone obtained from both SBA (DSC= 0.56 ± 0.05) and Hofmann's methods (DSC= 0.60 ± 0.02) exhibited no improvement compared to non-weighted IA. Finding the optimum parameters for implementation of the atlas fusion approach, such as weighting factors and image similarity patch size, have great impact on the performance of atlas-based segmentation approaches. The voxel-wise atlas fusion approach exhibited excellent performance in terms of cancelling out the non-systematic registration errors leading to accurate and reliable segmentation results. Denoising and normalization of MR images together with optimization of the involved parameters play a key role in improving bone extraction accuracy. Copyright © 2016 Elsevier B.V. All rights reserved.
Place, Benjamin J
2017-05-01
To address community needs, the National Institute of Standards and Technology has developed a candidate Standard Reference Material (SRM) for infant/adult nutritional formula based on milk and whey protein concentrates with isolated soy protein called SRM 1869 Infant/Adult Nutritional Formula. One major component of this candidate SRM is the fatty acid content. In this study, multiple extraction techniques were evaluated to quantify the fatty acids in this new material. Extraction methods that were based on lipid extraction followed by transesterification resulted in lower mass fraction values for all fatty acids than the values measured by methods utilizing in situ transesterification followed by fatty acid methyl ester extraction (ISTE). An ISTE method, based on the identified optimal parameters, was used to determine the fatty acid content of the new infant/adult nutritional formula reference material.
Radiology metrics for safe use and regulatory compliance with CT imaging
NASA Astrophysics Data System (ADS)
Paden, Robert; Pavlicek, William
2018-03-01
The MACRA Act creates a Merit-Based Payment System, with monitoring patient exposure from CT providing one possible quality metric for meeting merit requirements. Quality metrics are also required by The Joint Commission, ACR, and CMS as facilities are tasked to perform reviews of CT irradiation events outside of expected ranges, review protocols for appropriateness, and validate parameters for low dose lung cancer screening. In order to efficiently collect and analyze irradiation events and associated DICOM tags, all clinical CT devices were DICOM connected to a parser which extracted dose related information for storage into a database. Dose data from every exam is compared to the appropriate external standard exam type. AAPM recommended CTDIvol values for head and torso, adult and pediatrics, coronary and perfusion exams are used for this study. CT doses outside the expected range were automatically formatted into a report for analysis and review documentation. CT Technologist textual content, the reason for proceeding with an irradiation above the recommended threshold, is captured for inclusion in the follow up reviews by physics staff. The use of a knowledge based approach in labeling individual protocol and device settings is a practical solution resulting in efficiency of analysis and review. Manual methods would require approximately 150 person-hours for our facility, exclusive of travel time and independent of device availability. An efficiency of 89% time savings occurs through use of this informatics tool including a low dose CT comparison review and low dose lung cancer screening requirements set forth by CMS.
Assessment of angiogenesis in osseointegration of a silica-collagen biomaterial using 3D-nano-CT.
Alt, Volker; Kögelmaier, Daniela Vera; Lips, Katrin S; Witt, Vera; Pacholke, Sabine; Heiss, Christian; Kampschulte, Marian; Heinemann, Sascha; Hanke, Thomas; Thormann, Ulrich; Schnettler, Reinhard; Langheinrich, Alexander C
2011-10-01
Bony integration of biomaterials is a complex process in which angiogenesis plays a crucial role. We evaluated micro- and nano-CT imaging to demonstrate and quantify neovascularization in bony integration of a biomaterial and to give an image based estimation for the needed resolution for imaging angiogenesis in an animal model of femora defect healing. In 8 rats 5mm full-size defects were created at the left femur that was filled with silica-collagen bone substitute material and internally fixed with plate osteosynthesis. After 6 weeks the femora were infused in situ with Microfil, harvested and scanned for micro-CT (9 μm)(3) and nano-CT (3 μm)(3) imaging. Using those 3D images, the newly formed blood vessels in the area of the biomaterial were assessed and the total vascular volume fraction, the volume of the bone substitute material and the volume of the bone defect were quantitatively characterized. Results were complemented by histology. Differences were statistically assessed using (ANOVA). High-resolution nano-CT demonstrated new blood vessel formation surrounding the biomaterial in all animals at capillary level. Immunohistochemistry confirmed the newly formed blood vessels surrounding the bone substitute material. The mean vascular volume fraction (VVF) around the implant was calculated to be 3.01 ± 0.4%. The VVF was inversely correlated with the volume of the bone substitute material (r=0.8) but not with the dimension of the fracture zone (r=0.3). Nano-CT imaging is feasible for quantitative analysis of angiogenesis during bony integration of biomaterials and a promising tool in this context for the future. Copyright © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
SU-E-T-09: A Dosimetric Analysis of Various Clinically Used Bolus Materials
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stowe, M; Yeager, C; Zhou, F
Purpose: To evaluate the dosimetric effect of various clinically used bolus materials. Methods: Materials investigated include solid water, superflab, wet gauze, wet sheets, Play-Doh{sup ™}, and gauze embedded with petroleum jelly. Each bolusing material was scanned in a Philips CT to determine the Hounsfield unit (HU) and to verify uniformity throughout the material. Using the corresponding HU, boluses of 0.5 cm and 1.0 cm thicknesses were created in the Eclipse treatment planning system (TPS) on a solid water phantom. Dose was calculated at various depths for beam energies 6 MV, 6 MeV, 9 MeV, and 12 MeV to determine themore » effects of each material on deposition of dose. In addition, linac-based measurements at these energies were made using a farmer chamber in solid water. Wet sheets and wet gauze were measured with various water content to quantify the effects on dose. Results: Preliminary CT scans find a range in HU of bolus materials from −120 to almost 300. There is a trend in the dose at depth based on the HU of the material; however inconsistencies are found when the bolus materials have a negative HU value. The measured data indicates that there is a linear relationship between the mass of water in a material and the dose reading, the slope of which is material dependent. Conclusion: Due to the variation in HU of the bolus materials studied, it is recommended that any new bolus be evaluated before clinical use to determine physical and dosimetric properties. If possible, patients should have bolus included in their CT scans; or if the bolus is created in the TPS, the HU should correspond to the material used. For water-soaked materials, once the bolus material is selected (gauze or sheet), the bolusing effect is only dependent on the amount of water applied to the material.« less
Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L
2018-01-01
The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.
NASA Astrophysics Data System (ADS)
Qin, Wenjian; Wu, Jia; Han, Fei; Yuan, Yixuan; Zhao, Wei; Ibragimov, Bulat; Gu, Jia; Xing, Lei
2018-05-01
Segmentation of liver in abdominal computed tomography (CT) is an important step for radiation therapy planning of hepatocellular carcinoma. Practically, a fully automatic segmentation of liver remains challenging because of low soft tissue contrast between liver and its surrounding organs, and its highly deformable shape. The purpose of this work is to develop a novel superpixel-based and boundary sensitive convolutional neural network (SBBS-CNN) pipeline for automated liver segmentation. The entire CT images were first partitioned into superpixel regions, where nearby pixels with similar CT number were aggregated. Secondly, we converted the conventional binary segmentation into a multinomial classification by labeling the superpixels into three classes: interior liver, liver boundary, and non-liver background. By doing this, the boundary region of the liver was explicitly identified and highlighted for the subsequent classification. Thirdly, we computed an entropy-based saliency map for each CT volume, and leveraged this map to guide the sampling of image patches over the superpixels. In this way, more patches were extracted from informative regions (e.g. the liver boundary with irregular changes) and fewer patches were extracted from homogeneous regions. Finally, deep CNN pipeline was built and trained to predict the probability map of the liver boundary. We tested the proposed algorithm in a cohort of 100 patients. With 10-fold cross validation, the SBBS-CNN achieved mean Dice similarity coefficients of 97.31 ± 0.36% and average symmetric surface distance of 1.77 ± 0.49 mm. Moreover, it showed superior performance in comparison with state-of-art methods, including U-Net, pixel-based CNN, active contour, level-sets and graph-cut algorithms. SBBS-CNN provides an accurate and effective tool for automated liver segmentation. It is also envisioned that the proposed framework is directly applicable in other medical image segmentation scenarios.
MaPLE: A MapReduce Pipeline for Lattice-based Evaluation and Its Application to SNOMED CT
Zhang, Guo-Qiang; Zhu, Wei; Sun, Mengmeng; Tao, Shiqiang; Bodenreider, Olivier; Cui, Licong
2015-01-01
Non-lattice fragments are often indicative of structural anomalies in ontological systems and, as such, represent possible areas of focus for subsequent quality assurance work. However, extracting the non-lattice fragments in large ontological systems is computationally expensive if not prohibitive, using a traditional sequential approach. In this paper we present a general MapReduce pipeline, called MaPLE (MapReduce Pipeline for Lattice-based Evaluation), for extracting non-lattice fragments in large partially ordered sets and demonstrate its applicability in ontology quality assurance. Using MaPLE in a 30-node Hadoop local cloud, we systematically extracted non-lattice fragments in 8 SNOMED CT versions from 2009 to 2014 (each containing over 300k concepts), with an average total computing time of less than 3 hours per version. With dramatically reduced time, MaPLE makes it feasible not only to perform exhaustive structural analysis of large ontological hierarchies, but also to systematically track structural changes between versions. Our change analysis showed that the average change rates on the non-lattice pairs are up to 38.6 times higher than the change rates of the background structure (concept nodes). This demonstrates that fragments around non-lattice pairs exhibit significantly higher rates of change in the process of ontological evolution. PMID:25705725
MaPLE: A MapReduce Pipeline for Lattice-based Evaluation and Its Application to SNOMED CT.
Zhang, Guo-Qiang; Zhu, Wei; Sun, Mengmeng; Tao, Shiqiang; Bodenreider, Olivier; Cui, Licong
2014-10-01
Non-lattice fragments are often indicative of structural anomalies in ontological systems and, as such, represent possible areas of focus for subsequent quality assurance work. However, extracting the non-lattice fragments in large ontological systems is computationally expensive if not prohibitive, using a traditional sequential approach. In this paper we present a general MapReduce pipeline, called MaPLE (MapReduce Pipeline for Lattice-based Evaluation), for extracting non-lattice fragments in large partially ordered sets and demonstrate its applicability in ontology quality assurance. Using MaPLE in a 30-node Hadoop local cloud, we systematically extracted non-lattice fragments in 8 SNOMED CT versions from 2009 to 2014 (each containing over 300k concepts), with an average total computing time of less than 3 hours per version. With dramatically reduced time, MaPLE makes it feasible not only to perform exhaustive structural analysis of large ontological hierarchies, but also to systematically track structural changes between versions. Our change analysis showed that the average change rates on the non-lattice pairs are up to 38.6 times higher than the change rates of the background structure (concept nodes). This demonstrates that fragments around non-lattice pairs exhibit significantly higher rates of change in the process of ontological evolution.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Collins-Fekete, C; Centre Hospitalier University de Quebec, Quebec, QC; Mass General Hospital
Purpose: The relative stopping power (RSP) uncertainty is the largest contributor to the range uncertainty in proton therapy. The purpose of this work is to develop a robust and systematic method that yields accurate patient specific RSPs by combining pre-treatment X-ray CT and daily proton radiography. Methods: The method is formulated as a penalized least squares optimization (PLSO) problem min(|Ax-B|). The matrix A represents the cumulative path-length crossed in each material computed by calculating proton trajectories through the X-ray CT. The material RSPs are denoted by x and B is the pRad, expressed as water equivalent thickness. The equation ismore » solved using a convex-conic optimizer. Geant4 simulations were made to assess the feasibility of the method. RSP extracted from the Geant4 materials were used as a reference and the clinical HU-RSP curve as a comparison. The PLSO was first tested on a Gammex RMI-467 phantom. Then, anthropomorphic phantoms of the head, pelvis and lung were studied and resulting RSPs were evaluated. A pencil beam was generated in each phantom to evaluate the proton range accuracy achievable by using the optimized RSPs. Finally, experimental data of a pediatric head phantom (CIRS) were acquired using a recently completed experimental pCT scanner. Results: Numerical simulations showed precise RSP (<0.75%) for Gammex materials except low-density lung (LN-300) (1.2%). Accurate RSP have been obtained for the head (µ=−0.10%, 1.5σ=1.12%), lung (µ=−0.33, 1.5σ=1.02%) and pelvis anthropomorphic phantoms (µ=0.12, 1.5σ=0,99%). The range precision has been improved with an average R80 difference to the reference (µ±1.5σ) of −0.20±0.35%, −0.47±0.92% and −0.06±0.17% in the head, lung and pelvis phantoms respectively, compared to the 3.5% clinical margin. Experimental HU-RSP curve have been produced on the CIRS pediatric head. Conclusion: The proposed PLSO with prior knowledge X-ray CT shows promising potential (R80 σ<1.0% over all sites) to decrease the range uncertainty.« less
Dense volumetric detection and segmentation of mediastinal lymph nodes in chest CT images
NASA Astrophysics Data System (ADS)
Oda, Hirohisa; Roth, Holger R.; Bhatia, Kanwal K.; Oda, Masahiro; Kitasaka, Takayuki; Iwano, Shingo; Homma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Schnabel, Julia A.; Mori, Kensaku
2018-02-01
We propose a novel mediastinal lymph node detection and segmentation method from chest CT volumes based on fully convolutional networks (FCNs). Most lymph node detection methods are based on filters for blob-like structures, which are not specific for lymph nodes. The 3D U-Net is a recent example of the state-of-the-art 3D FCNs. The 3D U-Net can be trained to learn appearances of lymph nodes in order to output lymph node likelihood maps on input CT volumes. However, it is prone to oversegmentation of each lymph node due to the strong data imbalance between lymph nodes and the remaining part of the CT volumes. To moderate the balance of sizes between the target classes, we train the 3D U-Net using not only lymph node annotations but also other anatomical structures (lungs, airways, aortic arches, and pulmonary arteries) that can be extracted robustly in an automated fashion. We applied the proposed method to 45 cases of contrast-enhanced chest CT volumes. Experimental results showed that 95.5% of lymph nodes were detected with 16.3 false positives per CT volume. The segmentation results showed that the proposed method can prevent oversegmentation, achieving an average Dice score of 52.3 +/- 23.1%, compared to the baseline method with 49.2 +/- 23.8%, respectively.
Multi-scale imaging and elastic simulation of carbonates
NASA Astrophysics Data System (ADS)
Faisal, Titly Farhana; Awedalkarim, Ahmed; Jouini, Mohamed Soufiane; Jouiad, Mustapha; Chevalier, Sylvie; Sassi, Mohamed
2016-05-01
Digital Rock Physics (DRP) is an emerging technology that can be used to generate high quality, fast and cost effective special core analysis (SCAL) properties compared to conventional experimental techniques and modeling techniques. The primary workflow of DRP conssits of three elements: 1) image the rock sample using high resolution 3D scanning techniques (e.g. micro CT, FIB/SEM), 2) process and digitize the images by segmenting the pore and matrix phases 3) simulate the desired physical properties of the rocks such as elastic moduli and velocities of wave propagation. A Finite Element Method based algorithm, that discretizes the basic Hooke's Law equation of linear elasticity and solves it numerically using a fast conjugate gradient solver, developed by Garboczi and Day [1] is used for mechanical and elastic property simulations. This elastic algorithm works directly on the digital images by treating each pixel as an element. The images are assumed to have periodic constant-strain boundary condition. The bulk and shear moduli of the different phases are required inputs. For standard 1.5" diameter cores however the Micro-CT scanning reoslution (around 40 μm) does not reveal smaller micro- and nano- pores beyond the resolution. This results in an unresolved "microporous" phase, the moduli of which is uncertain. Knackstedt et al. [2] assigned effective elastic moduli to the microporous phase based on self-consistent theory (which gives good estimation of velocities for well cemented granular media). Jouini et al. [3] segmented the core plug CT scan image into three phases and assumed that micro porous phase is represented by a sub-extracted micro plug (which too was scanned using Micro-CT). Currently the elastic numerical simulations based on CT-images alone largely overpredict the bulk, shear and Young's modulus when compared to laboratory acoustic tests of the same rocks. For greater accuracy of numerical simulation prediction, better estimates of moduli inputs for this current unresolved phase is important. In this work we take a multi-scale imaging approach by first extracting a smaller 0.5" core and scanning at approx 13 µm, then further extracting a 5mm diameter core scanned at 5 μm. From this last scale, region of interests (containing unresolved areas) are identified for scanning at higher resolutions using Focalised Ion Beam (FIB/SEM) scanning technique reaching 50 nm resolution. Numerical simulation is run on such a small unresolved section to obtain a better estimate of the effective moduli which is then used as input for simulations performed using CT-images. Results are compared with expeirmental acoustic test moduli obtained also at two scales: 1.5" and 0.5" diameter cores.
Automated anatomical labeling method for abdominal arteries extracted from 3D abdominal CT images
NASA Astrophysics Data System (ADS)
Oda, Masahiro; Hoang, Bui Huy; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Mori, Kensaku
2012-02-01
This paper presents an automated anatomical labeling method of abdominal arteries. In abdominal surgery, understanding of blood vessel structure concerning with a target organ is very important. Branching pattern of blood vessels differs among individuals. It is required to develop a system that can assist understanding of a blood vessel structure and anatomical names of blood vessels of a patient. Previous anatomical labbeling methods for abdominal arteries deal with either of the upper or lower abdominal arteries. In this paper, we present an automated anatomical labeling method of both of the upper and lower abdominal arteries extracted from CT images. We obtain a tree structure of artery regions and calculate feature values for each branch. These feature values include the diameter, curvature, direction, and running vectors of a branch. Target arteries of this method are grouped based on branching conditions. The following processes are separately applied for each group. We compute candidate artery names by using classifiers that are trained to output artery names. A correction process of the candidate anatomical names based on the rule of majority is applied to determine final names. We applied the proposed method to 23 cases of 3D abdominal CT images. Experimental results showed that the proposed method is able to perform nomenclature of entire major abdominal arteries. The recall and the precision rates of labeling are 79.01% and 80.41%, respectively.
Chang, Suyon; Han, Kyunghwa; Youn, Jong-Chan; Im, Dong Jin; Kim, Jin Young; Suh, Young Joo; Hong, Yoo Jin; Hur, Jin; Kim, Young Jin; Choi, Byoung Wook; Lee, Hye-Jeong
2018-05-01
Purpose To investigate the diagnostic utility of dual-energy computed tomography (CT)-based monochromatic imaging for myocardial delayed enhancement (MDE) assessment in patients with cardiomyopathy. Materials and Methods The institutional review board approved this prospective study, and informed consent was obtained from all participants who were enrolled in the study. Forty patients (27 men and 13 women; mean age, 56 years ± 15 [standard deviation]; age range, 22-81 years) with cardiomyopathy underwent cardiac magnetic resonance (MR) imaging and dual-energy CT. Conventional (120-kV) and monochromatic (60-, 70-, and 80-keV) images were reconstructed from the dual-energy CT acquisition. Subjective quality score, contrast-to-noise ratio (CNR), and beam-hardening artifacts were compared pairwise with the Friedman test at post hoc analysis. With cardiac MR imaging as the reference standard, diagnostic performance of dual-energy CT in MDE detection and its predictive ability for pattern classification were compared pairwise by using logistic regression analysis with the generalized estimating equation in a per-segment analysis. The Bland-Altman method was used to find agreement between cardiac MR imaging and CT in MDE quantification. Results Among the monochromatic images, 70-keV CT images resulted in higher subjective quality (mean score, 3.38 ± 0.54 vs 3.15 ± 0.43; P = .0067), higher CNR (mean, 4.26 ± 1.38 vs 3.93 ± 1.33; P = .0047), and a lower value for beam-hardening artifacts (mean, 3.47 ± 1.56 vs 4.15 ± 1.67; P < .0001) when compared with conventional CT. When compared with conventional CT, 70-keV CT showed improved diagnostic performance for MDE detection (sensitivity, 94.6% vs 90.4% [P = .0032]; specificity, 96.0% vs 94.0% [P = .0031]; and accuracy, 95.6% vs 92.7% [P < .0001]) and improved predictive ability for pattern classification (subendocardial, 91.5% vs 84.3% [P = .0111]; epicardial, 94.3% vs 73.5% [P = .0001]; transmural, 93.0% vs 77.7% [P = .0018]; mesocardial, 85.4% vs 69.2% [P = .0047]; and patchy. 84.4% vs 78.4% [P = .1514]). For MDE quantification, 70-keV CT showed a small bias 0.1534% (95% limits of agreement: -4.7013, 5.0080). Conclusion Dual-energy CT-based 70-keV monochromatic images improve MDE assessment in patients with cardiomyopathy via improved image quality and CNR and reduced beam-hardening artifacts when compared with conventional CT images. © RSNA, 2017 Online supplemental material is available for this article.
Ezhuthupurakkal, Preedia Babu; Polaki, Lokeswara Rao; Suyavaran, Arumugam; Subastri, Ariraman; Sujatha, Venugopal; Thirunavukkarasu, Chinnasamy
2017-05-01
Biomedical application of selenium nanoparticles (SeNPs) demands the eco-friendly composite for synthesis of SeNPs. The present study reports an aqueous extract of Allium sativum (AqEAS) plug-up the current need. Modern spectroscopic, microscopic and gravimetric techniques were employed to characterize the synthesized nanoparticles. Characterization studies revealed the formation of crystalline spherical shaped SeNPs. FTIR spectrum brings out the presence of different functional groups in AqEAS, which influence the SeNPs formation and stabilization. Furthermore the different aspects of the interaction between SeNPs and CT-DNA were scrutinized by various spectroscopic and cyclic voltametric studies. The results reveals the intercalation and groove binding mode of interaction of SeNPs with stacked base pair of CT-DNA. The Stern-Volmer quenching constant (K SV ) were found to be 7.02×10 6 M- 1 (ethidium bromide), 4.22×10 6 M- 1 (acridine orange) and 7.6×10 6 M- 1 (Hoechst) indicating strong binding of SeNPs with CT-DNA. The SeNPs - CT-DNA interactions were directly visualized by atomic force microscopy. The present study unveils the cost effective, innocuous, highly stable SeNPs intricate mechanism of DNA interaction, which will be a milestone in DNA targeted chemotherapy. Copyright © 2017 Elsevier B.V. All rights reserved.
Kar, Subrata; Majumder, D Dutta
2017-08-01
Investigation of brain cancer can detect the abnormal growth of tissue in the brain using computed tomography (CT) scans and magnetic resonance (MR) images of patients. The proposed method classifies brain cancer on shape-based feature extraction as either benign or malignant. The authors used input variables such as shape distance (SD) and shape similarity measure (SSM) in fuzzy tools, and used fuzzy rules to evaluate the risk status as an output variable. We presented a classifier neural network system (NNS), namely Levenberg-Marquardt (LM), which is a feed-forward back-propagation learning algorithm used to train the NN for the status of brain cancer, if any, and which achieved satisfactory performance with 100% accuracy. The proposed methodology is divided into three phases. First, we find the region of interest (ROI) in the brain to detect the tumors using CT and MR images. Second, we extract the shape-based features, like SD and SSM, and grade the brain tumors as benign or malignant with the concept of SD function and SSM as shape-based parameters. Third, we classify the brain cancers using neuro-fuzzy tools. In this experiment, we used a 16-sample database with SSM (μ) values and classified the benignancy or malignancy of the brain tumor lesions using the neuro-fuzzy system (NFS). We have developed a fuzzy expert system (FES) and NFS for early detection of brain cancer from CT and MR images. In this experiment, shape-based features, such as SD and SSM, were extracted from the ROI of brain tumor lesions. These shape-based features were considered as input variables and, using fuzzy rules, we were able to evaluate brain cancer risk values for each case. We used an NNS with LM, a feed-forward back-propagation learning algorithm, as a classifier for the diagnosis of brain cancer and achieved satisfactory performance with 100% accuracy. The proposed network was trained with MR image datasets of 16 cases. The 16 cases were fed to the ANN with 2 input neurons, one hidden layer of 10 neurons and 2 output neurons. Of the 16-sample database, 10 datasets for training, 3 datasets for validation, and 3 datasets for testing were used in the ANN classification system. From the SSM (µ) confusion matrix, the number of output datasets of true positive, false positive, true negative and false negative was 6, 0, 10, and 0, respectively. The sensitivity, specificity and accuracy were each equal to 100%. The method of diagnosing brain cancer presented in this study is a successful model to assist doctors in the screening and treatment of brain cancer patients. The presented FES successfully identified the presence of brain cancer in CT and MR images using the extracted shape-based features and the use of NFS for the identification of brain cancer in the early stages. From the analysis and diagnosis of the disease, the doctors can decide the stage of cancer and take the necessary steps for more accurate treatment. Here, we have presented an investigation and comparison study of the shape-based feature extraction method with the use of NFS for classifying brain tumors as showing normal or abnormal patterns. The results have proved that the shape-based features with the use of NFS can achieve a satisfactory performance with 100% accuracy. We intend to extend this methodology for the early detection of cancer in other regions such as the prostate region and human cervix.
Xing, Gusheng; Wang, Shuang; Li, Chenrui; Zhao, Xinming; Zhou, Chunwu
2015-03-01
To investigate the value of quantitative iodine-based material decomposition images with gemstone spectral CT imaging in the follow-up of patients with hepatocellular carcinoma (HCC) after transcatheter arterial chemoebolization (TACE). Consecutive 32 HCC patients with previous TACE treatment were included in this study. For the follow-up, arterial phase (AP) and venous phase (VP) dual-phase CT scans were performed with a single-source dual-energy CT scanner (Discovery CT 750HD, GE Healthcare). Iodine concentrations were derived from iodine-based material-decomposition images in the liver parenchyma, tumors and coagulation necrosis (CN) areas. The iodine concentration difference (ICD) between the arterial-phase (AP) and venal-phase (VP) were quantitatively evaluated in different tissues.The lesion-to-normal parenchyma iodine concentration ratio (LNR) was calculated. ROC analysis was performed for the qualitative evaluation, and the area under ROC (Az) was calculated to represent the diagnostic ability of ICD and LNR. In all the 32 HCC patients, the region of interesting (ROI) for iodine concentrations included liver parenchyma (n=42), tumors (n=28) and coagulation necrosis (n=24). During the AP the iodine concentration of CNs (median value 0.088 µg/mm(3)) appeared significantly higher than that of the tumors (0.064 µg/mm(3), P=0.022) and liver parenchyma (0.048 µg/mm(3), P=0.005). But it showed no significant difference between liver parenchyma and tumors (P=0.454). During the VP the iodine concentration in hepatic parenchyma (median value 0.181 µg/mm(3)) was significantly higher than that in CNs (0.140 µg/mm(3), P=0.042). There was no significant difference between liver parenchyma and tumors, CNs and tumors (both P>0.05). The median value of ICD in CNs was 0.006 µg/mm(3), significantly lower than that of the HCC (0.201 µg/mm(3), P<0.001) and hepatic parenchyma (0.117 µg/mm(3), P<0.001). The ICDs in tumors and hepatic parenchyma showed no significant difference (P=0.829). During the AP, the LNR had no significant difference between CNs and tumors (a median value 1.805 vs. 1.310, P=0.389), and during the VP, the difference was also non-significant (the median value 0.647 vs. 0.713, P=0.660). The mean Az value of ICDs for evaluation of surviving tumor tissues was 0.804, whiles LNR measured a disappointing result in both AV images and VP images. Quantitative iodine-based material decomposition images with gemstone spectral CT imaging can improve the diagnostic efficacy of CT imaging for HCC patients after TACE treatment.
OLED-based physiologically-friendly very low-color temperature illumination for night
NASA Astrophysics Data System (ADS)
Jou, Jwo-Huei; Shen, Shih-Ming; Tang, Ming-Chun; Chen, Pin-Chu; Chen, Szu-Hao; Wang, Yi-Shan; Chen, Chien-Chih; Wang, Ching-Chun; Hsieh, Chun-Yu; Lin, Chin-Chiao; Chen, Chien-Tien
2012-09-01
Numerous medical research studies reveal intense white or blue light to drastically suppress at night the secretion of melatonin (MLT), a protective oncostatic hormone. Lighting devices with lower color-temperature (CT) possess lesser MLT suppression effect based on the same luminance, explaining why physicians have long been calling for the development of lighting sources with low CT or free from blue emission for use at night to safeguard human health. We will demonstrate in the presentation the fabrication of OLED devices with very-low CT, especially those with CT much lower than that of incandescent bulbs (2500K) or even candles (2000K). Without any light extraction method, OLEDs with an around 1800K CT are easily obtainable with an efficacy of 30 lm/W at 1,000 nits. To also ensure high color-rendering to provide visual comfort, low CT OLEDs composing long wavelength dominant 5-spectrum emission have been fabricated. While keeping the color-rendering index as high as 85 and CT as low as 2100K, the resulting efficacy can also be much greater than that of incandescent bulbs (15 lm/W), proving these low CT OLED devices to be also capable of being energy-saving and high quality. The color-temperature can be further decreased to 1700K or lower upon removing the undesired short wavelength emission but on the cost of losing some color rendering index. It is hoped that the devised energy-saving, high quality low CT OLED could properly echo the call for a physiologically-friendly illumination for night, and more attention could be drawn to the development of MLT suppression-less non-white light.
Exploring Hominin and Non-hominin Primate Dental Fossil Remains with Neutron Microtomography
NASA Astrophysics Data System (ADS)
Zanolli, Clément; Schillinger, Burkhard; Beaudet, Amélie; Kullmer, Ottmar; Macchiarelli, Roberto; Mancini, Lucia; Schrenk, Friedemann; Tuniz, Claudio; Vodopivec, Vladimira
Fossil dental remains are an archive of unique information for paleobiological studies. Computed microtomography based on X-ray microfocus sources (X-μCT) and Synchrotron Radiation (SR-μCT) allow subtle quantification at the micron and sub-micron scale of the meso- and microstructural signature imprinted in the mineralized tissues, such as enamel and dentine, through high-resolution ;virtual histology;. Nonetheless, depending on the degree of alterations undergone during fossilization, X-ray analyses of tooth tissues do not always provide distinct imaging contrasts, thus preventing the extraction of essential morphological and anatomical details. We illustrate here by three examples the successful application of neutron microtomography (n-μCT) in cases where X-rays have previously failed to deliver contrasts between dental tissues of fossilized specimen.
Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications
Leng, Shuai; Yu, Lifeng; Fletcher, Joel G.
2015-01-01
In x-ray computed tomography (CT), materials having different elemental compositions can be represented by identical pixel values on a CT image (ie, CT numbers), depending on the mass density of the material. Thus, the differentiation and classification of different tissue types and contrast agents can be extremely challenging. In dual-energy CT, an additional attenuation measurement is obtained with a second x-ray spectrum (ie, a second “energy”), allowing the differentiation of multiple materials. Alternatively, this allows quantification of the mass density of two or three materials in a mixture with known elemental composition. Recent advances in the use of energy-resolving, photon-counting detectors for CT imaging suggest the ability to acquire data in multiple energy bins, which is expected to further improve the signal-to-noise ratio for material-specific imaging. In this review, the underlying motivation and physical principles of dual- or multi-energy CT are reviewed and each of the current technical approaches is described. In addition, current and evolving clinical applications are introduced. © RSNA, 2015 PMID:26302388
Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib
2016-09-07
Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of -1.5 ± 5.0% (mean ± SD) in bony structures compared to -19.9 ± 11.8% and -8.1 ± 8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40 ± 7.56%, 96.00 ± 4.11% and 97.67 ± 3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.
NASA Astrophysics Data System (ADS)
Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib
2016-09-01
Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of -1.5 ± 5.0% (mean ± SD) in bony structures compared to -19.9 ± 11.8% and -8.1 ± 8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40 ± 7.56%, 96.00 ± 4.11% and 97.67 ± 3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, J; Chuong, M; Choi, W
Purpose: To identify PET/CT based imaging predictors of anal cancer recurrence and evaluate baseline vs. mid-treatment vs. post-treatment PET/CT scans in the tumor recurrence prediction. Methods: FDG-PET/CT scans were obtained at baseline, during chemoradiotherapy (CRT, midtreatment), and after CRT (post-treatment) in 17 patients of anal cancer. Four patients had tumor recurrence. For each patient, the mid-treatment and post-treatment scans were respectively aligned to the baseline scan by a rigid registration followed by a deformable registration. PET/CT image features were computed within the manually delineated tumor volume of each scan to characterize the intensity histogram, spatial patterns (texture), and shape ofmore » the tumors, as well as the changes of these features resulting from CRT. A total of 335 image features were extracted. An Exact Logistic Regression model was employed to analyze these PET/CT image features in order to identify potential predictors for tumor recurrence. Results: Eleven potential predictors of cancer recurrence were identified with p < 0.10, including five shape features, five statistical texture features, and one CT intensity histogram feature. Six features were indentified from posttreatment scans, 3 from mid-treatment scans, and 2 from baseline scans. These features indicated that there were differences in shape, intensity, and spatial pattern between tumors with and without recurrence. Recurrent tumors tended to have more compact shape (higher roundness and lower elongation) and larger intensity difference between baseline and follow-up scans, compared to non-recurrent tumors. Conclusion: PET/CT based anal cancer recurrence predictors were identified. The post-CRT PET/CT is the most important scan for the prediction of cancer recurrence. The baseline and mid-CRT PET/CT also showed value in the prediction and would be more useful for the predication of tumor recurrence in early stage of CRT. This work was supported in part by the National Cancer Institute Grant R01CA172638.« less
Saito, Masatoshi
2015-07-01
For accurate tissue inhomogeneity correction in radiotherapy treatment planning, the author previously proposed a simple conversion of the energy-subtracted computed tomography (CT) number to an electron density (ΔHU-ρe conversion), which provides a single linear relationship between ΔHU and ρe over a wide ρe range. The purpose of the present study was to reveal the relation between the ΔHU image for ρe calibration and a virtually monochromatic CT image by performing numerical analyses based on the basis material decomposition in dual-energy CT. The author determined the weighting factor, α0, of the ΔHU-ρe conversion through numerical analyses of the International Commission on Radiation Units and Measurements Report-46 human body tissues using their attenuation coefficients and given ρe values. Another weighting factor, α(E), for synthesizing a virtual monochromatic CT image from high- and low-kV CT images, was also calculated in the energy range of 0.03 < E < 5 MeV, assuming that cortical bone and water were the basis materials. The mass attenuation coefficients for these materials were obtained using the xcom photon cross sections database. The effective x-ray energies used to calculate the attenuation were chosen to imitate a dual-source CT scanner operated at 80-140 and 100-140 kV/Sn. The determined α0 values were 0.455 for 80-140 kV/Sn and 0.743 for 100-140 kV/Sn. These values coincided almost perfectly with the respective maximal points of the calculated α(E) curves located at approximately 1 MeV, in which the photon-matter interaction in human body tissues is exclusively the incoherent (Compton) scattering. The ΔHU image could be regarded substantially as a CT image acquired with monoenergetic 1-MeV photons, which provides a linear relationship between CT numbers and electron densities.
NASA Astrophysics Data System (ADS)
Gavrielides, Marios A.; DeFilippo, Gino; Berman, Benjamin P.; Li, Qin; Petrick, Nicholas; Schultz, Kurt; Siegelman, Jenifer
2017-03-01
Computed tomography is primarily the modality of choice to assess stability of nonsolid pulmonary nodules (sometimes referred to as ground-glass opacity) for three or more years, with change in size being the primary factor to monitor. Since volume extracted from CT is being examined as a quantitative biomarker of lung nodule size, it is important to examine factors affecting the performance of volumetric CT for this task. More specifically, the effect of reconstruction algorithms and measurement method in the context of low-dose CT protocols has been an under-examined area of research. In this phantom study we assessed volumetric CT with two different measurement methods (model-based and segmentation-based) for nodules with radiodensities of both nonsolid (-800HU and -630HU) and solid (-10HU) nodules, sizes of 5mm and 10mm, and two different shapes (spherical and spiculated). Imaging protocols included CTDIvol typical of screening (1.7mGy) and sub-screening (0.6mGy) scans and different types of reconstruction algorithms across three scanners. Results showed that radio-density was the factor contributing most to overall error based on ANOVA. The choice of reconstruction algorithm or measurement method did not affect substantially the accuracy of measurements; however, measurement method affected repeatability with repeatability coefficients ranging from around 3-5% for the model-based estimator to around 20-30% across reconstruction algorithms for the segmentation-based method. The findings of the study can be valuable toward developing standardized protocols and performance claims for nonsolid nodules.
Knowledge-Based Image Analysis.
1981-04-01
UNCLASSIF1 ED ETL-025s N IIp ETL-0258 AL Ai01319 S"Knowledge-based image analysis u George C. Stockman Barbara A. Lambird I David Lavine Laveen N. Kanal...extraction, verification, region classification, pattern recognition, image analysis . 3 20. A. CT (Continue on rever.. d. It necessary and Identify by...UNCLgSTFTF n In f SECURITY CLASSIFICATION OF THIS PAGE (When Date Entered) .L1 - I Table of Contents Knowledge Based Image Analysis I Preface
Corrugated Textile based Triboelectric Generator for Wearable Energy Harvesting
Choi, A Young; Lee, Chang Jun; Park, Jiwon; Kim, Dogyun; Kim, Youn Tae
2017-01-01
Triboelectric energy harvesting has been applied to various fields, from large-scale power generation to small electronics. Triboelectric energy is generated when certain materials come into frictional contact, e.g., static electricity from rubbing a shoe on a carpet. In particular, textile-based triboelectric energy-harvesting technologies are one of the most promising approaches because they are not only flexible, light, and comfortable but also wearable. Most previous textile-based triboelectric generators (TEGs) generate energy by vertically pressing and rubbing something. However, we propose a corrugated textile-based triboelectric generator (CT-TEG) that can generate energy by stretching. Moreover, the CT-TEG is sewn into a corrugated structure that contains an effective air gap without additional spacers. The resulting CT-TEG can generate considerable energy from various deformations, not only by pressing and rubbing but also by stretching. The maximum output performances of the CT-TEG can reach up to 28.13 V and 2.71 μA with stretching and releasing motions. Additionally, we demonstrate the generation of sufficient energy from various activities of a human body to power about 54 LEDs. These results demonstrate the potential application of CT-TEGs for self-powered systems. PMID:28349928
Corrugated Textile based Triboelectric Generator for Wearable Energy Harvesting
NASA Astrophysics Data System (ADS)
Choi, A. Young; Lee, Chang Jun; Park, Jiwon; Kim, Dogyun; Kim, Youn Tae
2017-03-01
Triboelectric energy harvesting has been applied to various fields, from large-scale power generation to small electronics. Triboelectric energy is generated when certain materials come into frictional contact, e.g., static electricity from rubbing a shoe on a carpet. In particular, textile-based triboelectric energy-harvesting technologies are one of the most promising approaches because they are not only flexible, light, and comfortable but also wearable. Most previous textile-based triboelectric generators (TEGs) generate energy by vertically pressing and rubbing something. However, we propose a corrugated textile-based triboelectric generator (CT-TEG) that can generate energy by stretching. Moreover, the CT-TEG is sewn into a corrugated structure that contains an effective air gap without additional spacers. The resulting CT-TEG can generate considerable energy from various deformations, not only by pressing and rubbing but also by stretching. The maximum output performances of the CT-TEG can reach up to 28.13 V and 2.71 μA with stretching and releasing motions. Additionally, we demonstrate the generation of sufficient energy from various activities of a human body to power about 54 LEDs. These results demonstrate the potential application of CT-TEGs for self-powered systems.
Yunker, Bryan E.; Cordes, Dietmar; Scherzinger, Ann L.; Dodd, Gerald D.; Shandas, Robin; Feng, Yusheng; Hunter, Kendall S.
2013-01-01
Purpose: This study investigated the ultrasound, MRI, and CT imaging characteristics of several industrial casting and molding compounds as a precursor to the future development of durable and anatomically correct flow phantoms. Methods: A set of usability and performance criteria was established for a proposed phantom design capable of supporting liquid flow during imaging. A literature search was conducted to identify the materials and methods previously used in phantom fabrication. A database of human tissue and casting material properties was compiled to facilitate the selection of appropriate materials for testing. Several industrial casting materials were selected, procured, and used to fabricate test samples that were imaged with ultrasound, MRI, and CT. Results: Five silicones and one polyurethane were selected for testing. Samples of all materials were successfully fabricated. All imaging modalities were able to discriminate between the materials tested. Ultrasound testing showed that three of the silicones could be imaged to a depth of at least 2.5 cm (1 in.). The RP-6400 polyurethane exhibited excellent contrast and edge detail for MRI phantoms and appears to be an excellent water reference for CT applications. The 10T and 27T silicones appear to be usable water references for MRI imaging. Conclusions: Based on study data and the stated selection criteria, the P-4 silicone provided sufficient material contrast to water and edge detail for use across all imaging modalities with the benefits of availability, low cost, dimensional stability, nontoxic, nonflammable, durable, cleanable, and optical clarity. The physical and imaging differences of the materials documented in this study may be useful for other applications. PMID:23635298
NASA Astrophysics Data System (ADS)
Bultreys, Tom; Boone, Marijn A.; Boone, Matthieu N.; De Schryver, Thomas; Masschaele, Bert; Van Hoorebeke, Luc; Cnudde, Veerle
2016-09-01
Over the past decade, the wide-spread implementation of laboratory-based X-ray micro-computed tomography (micro-CT) scanners has revolutionized both the experimental and numerical research on pore-scale transport in geological materials. The availability of these scanners has opened up the possibility to image a rock's pore space in 3D almost routinely to many researchers. While challenges do persist in this field, we treat the next frontier in laboratory-based micro-CT scanning: in-situ, time-resolved imaging of dynamic processes. Extremely fast (even sub-second) micro-CT imaging has become possible at synchrotron facilities over the last few years, however, the restricted accessibility of synchrotrons limits the amount of experiments which can be performed. The much smaller X-ray flux in laboratory-based systems bounds the time resolution which can be attained at these facilities. Nevertheless, progress is being made to improve the quality of measurements performed on the sub-minute time scale. We illustrate this by presenting cutting-edge pore scale experiments visualizing two-phase flow and solute transport in real-time with a lab-based environmental micro-CT set-up. To outline the current state of this young field and its relevance to pore-scale transport research, we critically examine its current bottlenecks and their possible solutions, both on the hardware and the software level. Further developments in laboratory-based, time-resolved imaging could prove greatly beneficial to our understanding of transport behavior in geological materials and to the improvement of pore-scale modeling by providing valuable validation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yadava, G; Imai, Y; Hsieh, J
2014-06-15
Purpose: Quantitative accuracy of Iodine Hounsfield Unit (HU) in conventional single-kVp scanning is susceptible to beam-hardening effect. Dual-energy CT has unique capabilities of quantification using monochromatic CT images, but this scanning mode requires the availability of the state-of-the-art CT scanner and, therefore, is limited in routine clinical practice. Purpose of this work was to develop a beam-hardening-correction (BHC) for single-kVp CT that can linearize Iodine projections at any nominal energy, apply this approach to study Iodine response with respect to keV, and compare with dual-energy based monochromatic images obtained from material-decomposition using 80kVp and 140kVp. Methods: Tissue characterization phantoms (Gammexmore » Inc.), containing solid-Iodine inserts of different concentrations, were scanned using GE multi-slice CT scanner at 80, 100, 120, and 140 kVp. A model-based BHC algorithm was developed where Iodine was estimated using re-projection of image volume and corrected through an iterative process. In the correction, the re-projected Iodine was linearized using a polynomial mapping between monochromatic path-lengths at various nominal energies (40 to 140 keV) and physically modeled polychromatic path-lengths. The beam-hardening-corrected 80kVp and 140kVp images (linearized approximately at effective energy of the beam) were used for dual-energy material-decomposition in Water-Iodine basis-pair followed by generation of monochromatic images. Characterization of Iodine HU and noise in the images obtained from singlekVp with BHC at various nominal keV, and corresponding dual-energy monochromatic images, was carried out. Results: Iodine HU vs. keV response from single-kVp with BHC and dual-energy monochromatic images were found to be very similar, indicating that single-kVp data may be used to create material specific monochromatic equivalent using modelbased projection linearization. Conclusion: This approach may enable quantification of Iodine contrast enhancement and potential reduction in injected contrast without using dual-energy scanning. However, in general, dual-energy scanning has unique value in material characterization and quantification, and its value cannot be discounted. GE Healthcare Employee.« less
MicroCT with energy-resolved photon-counting detectors
Wang, X; Meier, D; Mikkelsen, S; Maehlum, G E; Wagenaar, D J; Tsui, BMW; Patt, B E; Frey, E C
2011-01-01
The goal of this paper was to investigate the benefits that could be realistically achieved on a microCT imaging system with an energy-resolved photon-counting x-ray detector. To this end, we built and evaluated a prototype microCT system based on such a detector. The detector is based on cadmium telluride (CdTe) radiation sensors and application-specific integrated circuit (ASIC) readouts. Each detector pixel can simultaneously count x-ray photons above six energy thresholds, providing the capability for energy-selective x-ray imaging. We tested the spectroscopic performance of the system using polychromatic x-ray radiation and various filtering materials with Kabsorption edges. Tomographic images were then acquired of a cylindrical PMMA phantom containing holes filled with various materials. Results were also compared with those acquired using an intensity-integrating x-ray detector and single-energy (i.e. non-energy-selective) CT. This paper describes the functionality and performance of the system, and presents preliminary spectroscopic and tomographic results. The spectroscopic experiments showed that the energy-resolved photon-counting detector was capable of measuring energy spectra from polychromatic sources like a standard x-ray tube, and resolving absorption edges present in the energy range used for imaging. However, the spectral quality was degraded by spectral distortions resulting from degrading factors, including finite energy resolution and charge sharing. We developed a simple charge-sharing model to reproduce these distortions. The tomographic experiments showed that the availability of multiple energy thresholds in the photon-counting detector allowed us to simultaneously measure target-to-background contrasts in different energy ranges. Compared with single-energy CT with an integrating detector, this feature was especially useful to improve differentiation of materials with different attenuation coefficient energy dependences. PMID:21464527
MicroCT with energy-resolved photon-counting detectors.
Wang, X; Meier, D; Mikkelsen, S; Maehlum, G E; Wagenaar, D J; Tsui, B M W; Patt, B E; Frey, E C
2011-05-07
The goal of this paper was to investigate the benefits that could be realistically achieved on a microCT imaging system with an energy-resolved photon-counting x-ray detector. To this end, we built and evaluated a prototype microCT system based on such a detector. The detector is based on cadmium telluride (CdTe) radiation sensors and application-specific integrated circuit (ASIC) readouts. Each detector pixel can simultaneously count x-ray photons above six energy thresholds, providing the capability for energy-selective x-ray imaging. We tested the spectroscopic performance of the system using polychromatic x-ray radiation and various filtering materials with K-absorption edges. Tomographic images were then acquired of a cylindrical PMMA phantom containing holes filled with various materials. Results were also compared with those acquired using an intensity-integrating x-ray detector and single-energy (i.e. non-energy-selective) CT. This paper describes the functionality and performance of the system, and presents preliminary spectroscopic and tomographic results. The spectroscopic experiments showed that the energy-resolved photon-counting detector was capable of measuring energy spectra from polychromatic sources like a standard x-ray tube, and resolving absorption edges present in the energy range used for imaging. However, the spectral quality was degraded by spectral distortions resulting from degrading factors, including finite energy resolution and charge sharing. We developed a simple charge-sharing model to reproduce these distortions. The tomographic experiments showed that the availability of multiple energy thresholds in the photon-counting detector allowed us to simultaneously measure target-to-background contrasts in different energy ranges. Compared with single-energy CT with an integrating detector, this feature was especially useful to improve differentiation of materials with different attenuation coefficient energy dependences.
Circulating tumor DNA: a promising biomarker in the liquid biopsy of cancer.
Cheng, Feifei; Su, Li; Qian, Cheng
2016-07-26
Tissue biopsy is the standard diagnostic procedure for cancers and also provides a material for genotyping, which can assist in the targeted therapies of cancers. However, tissue biopsy-based cancer diagnostic procedures have limitations in their assessment of cancer development, prognosis and genotyping, due to tumor heterogeneity and evolution. Circulating tumor DNA (ctDNA) is single- or double-stranded DNA released by the tumor cells into the blood and it thus harbors the mutations of the original tumor. In recent years, liquid biopsy based on ctDNA analysis has shed a new light on the molecular diagnosis and monitoring of cancer. Studies found that the screening of genetic mutations using ctDNA is highly sensitive and specific, suggesting that ctDNA analysis may significantly improve current systems of tumor diagnosis, even facilitating early-stage detection. Moreover, ctDNA analysis is capable of accurately determining the tumor progression, prognosis and assisting in targeted therapy. Therefore, using ctDNA as a liquid biopsy may herald a revolution for tumor management. Herein, we review the biology of ctDNA, its detection methods and potential applications in tumor diagnosis, treatment and prognosis.
Circulating tumor DNA: a promising biomarker in the liquid biopsy of cancer
Cheng, Feifei; Su, Li; Qian, Cheng
2016-01-01
Tissue biopsy is the standard diagnostic procedure for cancers and also provides a material for genotyping, which can assist in the targeted therapies of cancers. However, tissue biopsy-based cancer diagnostic procedures have limitations in their assessment of cancer development, prognosis and genotyping, due to tumor heterogeneity and evolution. Circulating tumor DNA (ctDNA) is single- or double-stranded DNA released by the tumor cells into the blood and it thus harbors the mutations of the original tumor. In recent years, liquid biopsy based on ctDNA analysis has shed a new light on the molecular diagnosis and monitoring of cancer. Studies found that the screening of genetic mutations using ctDNA is highly sensitive and specific, suggesting that ctDNA analysis may significantly improve current systems of tumor diagnosis, even facilitating early-stage detection. Moreover, ctDNA analysis is capable of accurately determining the tumor progression, prognosis and assisting in targeted therapy. Therefore, using ctDNA as a liquid biopsy may herald a revolution for tumor management. Herein, we review the biology of ctDNA, its detection methods and potential applications in tumor diagnosis, treatment and prognosis. PMID:27223063
Thimm, Benjamin W; Hofmann, Sandra; Schneider, Philipp; Carretta, Roberto; Müller, Ralph
2012-03-01
Computed tomography (CT) represents a truly three-dimensional (3D) imaging technique that can provide high-resolution images on the cellular level. Thus, one approach to detect single cells is X-ray absorption-based CT, where cells are labeled with a dense, opaque material providing the required contrast for CT imaging. Within the present work, a novel cell-labeling method has been developed showing the feasibility of labeling fixed cells with iron oxide (FeO) particles for subsequent CT imaging and quantitative morphometry. A biotin-streptavidin detection system was exploited to bind FeO particles to its target endothelial cells. The binding of the particles was predominantly close to the cell centers on 2D surfaces as shown by light microscopy, scanning electron microscopy, and CT. When cells were cultured on porous, 3D polyurethane surfaces, significantly more FeO particles were detected compared with surfaces without cells and FeO particle labeling using CT. Here, we report on the implementation and evaluation of a novel cell detection method based on high-resolution CT. This system has potential in cell tracking for 3D in vitro imaging in the future.
Sodickson, Aaron; Warden, Graham I; Farkas, Cameron E; Ikuta, Ichiro; Prevedello, Luciano M; Andriole, Katherine P; Khorasani, Ramin
2012-08-01
To develop and validate an informatics toolkit that extracts anatomy-specific computed tomography (CT) radiation exposure metrics (volume CT dose index and dose-length product) from existing digital image archives through optical character recognition of CT dose report screen captures (dose screens) combined with Digital Imaging and Communications in Medicine attributes. This institutional review board-approved HIPAA-compliant study was performed in a large urban health care delivery network. Data were drawn from a random sample of CT encounters that occurred between 2000 and 2010; images from these encounters were contained within the enterprise image archive, which encompassed images obtained at an adult academic tertiary referral hospital and its affiliated sites, including a cancer center, a community hospital, and outpatient imaging centers, as well as images imported from other facilities. Software was validated by using 150 randomly selected encounters for each major CT scanner manufacturer, with outcome measures of dose screen retrieval rate (proportion of correctly located dose screens) and anatomic assignment precision (proportion of extracted exposure data with correctly assigned anatomic region, such as head, chest, or abdomen and pelvis). The 95% binomial confidence intervals (CIs) were calculated for discrete proportions, and CIs were derived from the standard error of the mean for continuous variables. After validation, the informatics toolkit was used to populate an exposure repository from a cohort of 54 549 CT encounters; of which 29 948 had available dose screens. Validation yielded a dose screen retrieval rate of 99% (597 of 605 CT encounters; 95% CI: 98%, 100%) and an anatomic assignment precision of 94% (summed DLP fraction correct 563 in 600 CT encounters; 95% CI: 92%, 96%). Patient safety applications of the resulting data repository include benchmarking between institutions, CT protocol quality control and optimization, and cumulative patient- and anatomy-specific radiation exposure monitoring. Large-scale anatomy-specific radiation exposure data repositories can be created with high fidelity from existing digital image archives by using open-source informatics tools.
ERIC Educational Resources Information Center
Lindner, James R.; Murphy, Tim H.
2001-01-01
Responses from 89 of 111 agricultural education students explored their perceptions of the use of WebCT. Results show that 72% were able accomplish course objectives and 92% were able to access grades online. However, 82% did not take advantage of the online learning community, and 76% continued to rely on print-based course materials. (Contains…
Automated detection of lung nodules with three-dimensional convolutional neural networks
NASA Astrophysics Data System (ADS)
Pérez, Gustavo; Arbeláez, Pablo
2017-11-01
Lung cancer is the cancer type with highest mortality rate worldwide. It has been shown that early detection with computer tomography (CT) scans can reduce deaths caused by this disease. Manual detection of cancer nodules is costly and time-consuming. We present a general framework for the detection of nodules in lung CT images. Our method consists of the pre-processing of a patient's CT with filtering and lung extraction from the entire volume using a previously calculated mask for each patient. From the extracted lungs, we perform a candidate generation stage using morphological operations, followed by the training of a three-dimensional convolutional neural network for feature representation and classification of extracted candidates for false positive reduction. We perform experiments on the publicly available LIDC-IDRI dataset. Our candidate extraction approach is effective to produce precise candidates with a recall of 99.6%. In addition, false positive reduction stage manages to successfully classify candidates and increases precision by a factor of 7.000.
Siri, Sangeeta K; Latte, Mrityunjaya V
2017-11-01
Many different diseases can occur in the liver, including infections such as hepatitis, cirrhosis, cancer and over effect of medication or toxins. The foremost stage for computer-aided diagnosis of liver is the identification of liver region. Liver segmentation algorithms extract liver image from scan images which helps in virtual surgery simulation, speedup the diagnosis, accurate investigation and surgery planning. The existing liver segmentation algorithms try to extort exact liver image from abdominal Computed Tomography (CT) scan images. It is an open problem because of ambiguous boundaries, large variation in intensity distribution, variability of liver geometry from patient to patient and presence of noise. A novel approach is proposed to meet challenges in extracting the exact liver image from abdominal CT scan images. The proposed approach consists of three phases: (1) Pre-processing (2) CT scan image transformation to Neutrosophic Set (NS) and (3) Post-processing. In pre-processing, the noise is removed by median filter. The "new structure" is designed to transform a CT scan image into neutrosophic domain which is expressed using three membership subset: True subset (T), False subset (F) and Indeterminacy subset (I). This transform approximately extracts the liver image structure. In post processing phase, morphological operation is performed on indeterminacy subset (I) and apply Chan-Vese (C-V) model with detection of initial contour within liver without user intervention. This resulted in liver boundary identification with high accuracy. Experiments show that, the proposed method is effective, robust and comparable with existing algorithm for liver segmentation of CT scan images. Copyright © 2017 Elsevier B.V. All rights reserved.
Salami, Saheed A; Valenti, Bernardo; Bella, Marco; O'Grady, Michael N; Luciano, Giuseppe; Kerry, Joseph P; Jones, Eleanor; Priolo, Alessandro; Newbold, Charles J
2018-05-01
This study characterised the response of ruminal fermentation and the rumen microbiome in lambs fed commercial vegetal sources of hydrolysable tannins (HT) and condensed tannins (CT). Forty-four lambs (19.56 ± 2.06 kg) were randomly assigned to either a concentrate diet (CON, n = 8) or CON supplemented with 4% of two HT [chestnut (Castanea sativa, HT-c) and tara (Caesalpinia spinosa, HT-t)] and CT [mimosa (Acacia negra, CT-m) and gambier (Uncaria gambir, CT-g)] extracts (all, n = 9) for 75 days pre-slaughter. Tannin supplementation did not influence ruminal fermentation traits. Quantitative PCR demonstrated that tannins did not affect the absolute abundance of ruminal bacteria or fungi. However, CT-m (-12.8%) and CT-g (-11.5%) significantly reduced the abundance of methanogens, while HT-t (-20.7%) and CT-g (-20.8%) inhibited protozoal abundance. Ribosomal amplicon sequencing revealed that tannins caused changes in the phylogenetic structure of the bacterial and methanogen communities. Tannins inhibited the fibrolytic bacterium, Fibrobacter and tended to suppress the methanogen genus, Methanosphaera. Results demonstrated that both HT and CT sources could impact the ruminal microbiome when supplemented at 4% inclusion level. HT-t, CT-m and CT-g extracts displayed specific antimicrobial activity against methanogens and protozoa without compromising ruminal fermentation in a long-term feeding trial.
NASA Astrophysics Data System (ADS)
Manna, Arun K.; Dunietz, Barry D.
2014-09-01
We investigate photoinduced charge transfer (CT) processes within dyads consisting of porphyrin derivatives in which one ring ligates a Zn metal center and where the rings vary by their degree of conjugation. Using a first-principles approach, we show that molecular-scale means can tune CT rates through stabilization affected by the polar environment. Such means of CT tuning are important for achieving high efficiency optoelectronic applications using organic semiconducting materials. Our fully quantum mechanical scheme is necessary for reliably modeling the CT process across different regimes, in contrast to the pervading semi-classical Marcus picture that grossly underestimates transfer in the far-inverted regime.
Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion
NASA Astrophysics Data System (ADS)
Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Tade, Funmilayo; Schuster, David M.; Nieh, Peter; Master, Viraj; Fei, Baowei
2017-02-01
Automatic segmentation of the prostate on CT images has many applications in prostate cancer diagnosis and therapy. However, prostate CT image segmentation is challenging because of the low contrast of soft tissue on CT images. In this paper, we propose an automatic segmentation method by combining a deep learning method and multi-atlas refinement. First, instead of segmenting the whole image, we extract the region of interesting (ROI) to delete irrelevant regions. Then, we use the convolutional neural networks (CNN) to learn the deep features for distinguishing the prostate pixels from the non-prostate pixels in order to obtain the preliminary segmentation results. CNN can automatically learn the deep features adapting to the data, which are different from some handcrafted features. Finally, we select some similar atlases to refine the initial segmentation results. The proposed method has been evaluated on a dataset of 92 prostate CT images. Experimental results show that our method achieved a Dice similarity coefficient of 86.80% as compared to the manual segmentation. The deep learning based method can provide a useful tool for automatic segmentation of the prostate on CT images and thus can have a variety of clinical applications.
LexValueSets: An Approach for Context-Driven Value Sets Extraction
Pathak, Jyotishman; Jiang, Guoqian; Dwarkanath, Sridhar O.; Buntrock, James D.; Chute, Christopher G.
2008-01-01
The ability to model, share and re-use value sets across multiple medical information systems is an important requirement. However, generating value sets semi-automatically from a terminology service is still an unresolved issue, in part due to the lack of linkage to clinical context patterns that provide the constraints in defining a concept domain and invocation of value sets extraction. Towards this goal, we develop and evaluate an approach for context-driven automatic value sets extraction based on a formal terminology model. The crux of the technique is to identify and define the context patterns from various domains of discourse and leverage them for value set extraction using two complementary ideas based on (i) local terms provided by the Subject Matter Experts (extensional) and (ii) semantic definition of the concepts in coding schemes (intensional). A prototype was implemented based on SNOMED CT rendered in the LexGrid terminology model and a preliminary evaluation is presented. PMID:18998955
Park, Yang-Kyun; Son, Tae-geun; Kim, Hwiyoung; Lee, Jaegi; Sung, Wonmo; Kim, Il Han; Lee, Kunwoo; Bang, Young-bong; Ye, Sung-Joon
2013-09-06
Phase-based respiratory-gated radiotherapy relies on the reproducibility of patient breathing during the treatment. To monitor the positional reproducibility of patient breathing against a 4D CT simulation, we developed a real-time motion verification system (RMVS) using an optical tracking technology. The system in the treatment room was integrated with a real-time position management system. To test the system, an anthropomorphic phantom that was mounted on a motion platform moved on a programmed breathing pattern and then underwent a 4D CT simulation with RPM. The phase-resolved anterior surface lines were extracted from the 4D CT data to constitute 4D reference lines. In the treatment room, three infrared reflective markers were attached on the superior, middle, and inferior parts of the phantom along with the body midline and then RMVS could track those markers using an optical camera system. The real-time phase information extracted from RPM was delivered to RMVS via in-house network software. Thus, the real-time anterior-posterior positions of the markers were simultaneously compared with the 4D reference lines. The technical feasibility of RMVS was evaluated by repeating the above procedure under several scenarios such as ideal case (with identical motion parameters between simulation and treatment), cycle change, baseline shift, displacement change, and breathing type changes (abdominal or chest breathing). The system capability for operating under irregular breathing was also investigated using real patient data. The evaluation results showed that RMVS has a competence to detect phase-matching errors between patient's motion during the treatment and 4D CT simulation. Thus, we concluded that RMVS could be used as an online quality assurance tool for phase-based gating treatments.
Deep learning for biomarker regression: application to osteoporosis and emphysema on chest CT scans
NASA Astrophysics Data System (ADS)
González, Germán.; Washko, George R.; San José Estépar, Raúl
2018-03-01
Introduction: Biomarker computation using deep-learning often relies on a two-step process, where the deep learning algorithm segments the region of interest and then the biomarker is measured. We propose an alternative paradigm, where the biomarker is estimated directly using a regression network. We showcase this image-tobiomarker paradigm using two biomarkers: the estimation of bone mineral density (BMD) and the estimation of lung percentage of emphysema from CT scans. Materials and methods: We use a large database of 9,925 CT scans to train, validate and test the network for which reference standard BMD and percentage emphysema have been already computed. First, the 3D dataset is reduced to a set of canonical 2D slices where the organ of interest is visible (either spine for BMD or lungs for emphysema). This data reduction is performed using an automatic object detector. Second, The regression neural network is composed of three convolutional layers, followed by a fully connected and an output layer. The network is optimized using a momentum optimizer with an exponential decay rate, using the root mean squared error as cost function. Results: The Pearson correlation coefficients obtained against the reference standards are r = 0.940 (p < 0.00001) and r = 0.976 (p < 0.00001) for BMD and percentage emphysema respectively. Conclusions: The deep-learning regression architecture can learn biomarkers from images directly, without indicating the structures of interest. This approach simplifies the development of biomarker extraction algorithms. The proposed data reduction based on object detectors conveys enough information to compute the biomarkers of interest.
Chen, G; Fan, W; Mishra, S; El-Atem, A; Schuetz, M A; Xiao, Y
2012-10-01
The finite element (FE) analysis is an effective method to study the strength and predict the fracture risk of endodontically-treated teeth. This paper presents a rapid method developed to generate a comprehensive tooth FE model using data retrieved from micro-computed tomography (μCT). With this method, the inhomogeneity of material properties of teeth was included into the model without dividing the tooth model into different regions. The material properties of the tooth were assumed to be related to the mineral density. The fracture risk at different tooth portions was assessed for root canal treatments. The micro-CT images of a tooth were processed by a Matlab software programme and the CT numbers were retrieved. The tooth contours were obtained with thresholding segmentation using Amira. The inner and outer surfaces of the tooth were imported into Solidworks and a three-dimensional (3D) tooth model was constructed. An assembly of the tooth model with the periodontal ligament (PDL) layer and surrounding bone was imported into ABAQUS. The material properties of the tooth were calculated from the retrieved CT numbers via ABAQUS user's subroutines. Three root canal geometries (original and two enlargements) were investigated. The proposed method in this study can generate detailed 3D finite element models of a tooth with different root canal enlargements and filling materials, and would be very useful for the assessment of the fracture risk at different tooth portions after root canal treatments. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Park, Peter C.; Schreibmann, Eduard; Roper, Justin
2015-03-15
Purpose: Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations. Methods and Materials: The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR.more » Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases. Results: The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases. Conclusions: Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts.« less
Khamverdi, Z.; Kasraie, Sh.; Rezaei-Soufi, L.; Jebeli, S.
2010-01-01
Introduction: Whitening toothpastes which have been accepted in populations may affect properties of enamel and restorative materials. The aim of this study was to compare the microhardness of human enamel and Z250 microhybrid composite resin after brushing with two whitening toothpastes. Materials and Methods: In this experimental study of enamel specimens, forty five freshly extracted human incisors were prepared and divided into three groups of control enamel (ClE), Crest enamel (CtE) and Aquafresh enamel (AfE). For composite resin specimens, forty five cylindrical-shaped specimens of light-cured Z250 composite were prepared and divided into three groups of control composite (ClC), Crest composite (CtC) and Aquafresh composite (AfC). The control groups were brushed without toothpaste. Crest and Aquafresh group specimens were brushed with Crest and Aquafresh whitening toothpastes, respectively. Vickers microhardness test was performed for all groups. Data were analyzed by One-way ANOVA and Tukey tests. Results: Microhardness values of ClE, CtE, AfE, ClC, CtC and AfC groups were 332.99 ± 26.59, 313.99 ± 20.56, 323.57 ± 27.96, 137.1 ± 3.16, 122.95 ± 3.27 and 130.36 ± 4.8, respectively. One-way ANOVA showed no significant differences among three enamel groups but there was significant difference among composite groups (p<0.01). Conclusion: Crest and Aquafresh whitening toothpastes did not affect enamel hardness but reduced the microhardness value of Z-250 composite resin. However, Crest whitening toothpaste decreased the microhardness more than Aquafresh. PMID:21998788
Extraction of volatile and metals from extraterrestrial materials
NASA Technical Reports Server (NTRS)
Lewis, John S.
1990-01-01
Since March 1, 1989, attention was concentrated on the extraction of ilmenite from extraterrestrial materials and on the planning and development of laboratory facilities for carbonyl extraction of ferrous metal alloys. Work under three subcontracts was administered by this project: (1) electrolytic production of oxygen from molten lunar materials; (2) microwave processing of lunar materials; and (3) production of a resource-oriented space science data base.
Pre-operative segmentation of neck CT datasets for the planning of neck dissections
NASA Astrophysics Data System (ADS)
Cordes, Jeanette; Dornheim, Jana; Preim, Bernhard; Hertel, Ilka; Strauss, Gero
2006-03-01
For the pre-operative segmentation of CT neck datasets, we developed the software assistant NeckVision. The relevant anatomical structures for neck dissection planning can be segmented and the resulting patient-specific 3D-models are visualized afterwards in another software system for intervention planning. As a first step, we examined the appropriateness of elementary segmentation techniques based on gray values and contour information to extract the structures in the neck region from CT data. Region growing, interactive watershed transformation and live-wire are employed for segmentation of different target structures. It is also examined, which of the segmentation tasks can be automated. Based on this analysis, the software assistant NeckVision was developed to optimally support the workflow of image analysis for clinicians. The usability of NeckVision was tested within a first evaluation with four otorhinolaryngologists from the university hospital of Leipzig, four computer scientists from the university of Magdeburg and two laymen in both fields.
Nogueira, Mariana A; Abreu, Pedro H; Martins, Pedro; Machado, Penousal; Duarte, Hugo; Santos, João
2017-02-13
Positron Emission Tomography - Computed Tomography (PET/CT) imaging is the basis for the evaluation of response-to-treatment of several oncological diseases. In practice, such evaluation is manually performed by specialists, which is rather complex and time-consuming. Evaluation measures have been proposed, but with questionable reliability. The usage of before and after-treatment image descriptors of the lesions for treatment response evaluation is still a territory to be explored. In this project, Artificial Neural Network approaches were implemented to automatically assess treatment response of patients suffering from neuroendocrine tumors and Hodgkyn lymphoma, based on image features extracted from PET/CT. The results show that the considered set of features allows for the achievement of very high classification performances, especially when data is properly balanced. After synthetic data generation and PCA-based dimensionality reduction to only two components, LVQNN assured classification accuracies of 100%, 100%, 96.3% and 100% regarding the 4 response-to-treatment classes.
Image quality improvement in cone-beam CT using the super-resolution technique.
Oyama, Asuka; Kumagai, Shinobu; Arai, Norikazu; Takata, Takeshi; Saikawa, Yusuke; Shiraishi, Kenshiro; Kobayashi, Takenori; Kotoku, Jun'ichi
2018-04-05
This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high-resolution and low-resolution image bases. For this study, a CBCT image, as a low-resolution image, is represented as a linear combination of atoms, the image bases in the low-resolution dictionary. The corresponding super-resolution image was inferred by multiplying the coefficients and the high-resolution dictionary atoms extracted from planning CT images. To evaluate the proposed method, we computed the root mean square error (RMSE) and structural similarity (SSIM). The resulting RMSE and SSIM between the super-resolution images and the planning CT images were, respectively, as much as 0.81 and 1.29 times better than those obtained without using the super-resolution technique. We used super-resolution technique to improve the CBCT image quality.
NASA Astrophysics Data System (ADS)
He, Nana; Zhang, Xiaolong; Zhao, Juanjuan; Zhao, Huilan; Qiang, Yan
2017-07-01
While the popular thin layer scanning technology of spiral CT has helped to improve diagnoses of lung diseases, the large volumes of scanning images produced by the technology also dramatically increase the load of physicians in lesion detection. Computer-aided diagnosis techniques like lesions segmentation in thin CT sequences have been developed to address this issue, but it remains a challenge to achieve high segmentation efficiency and accuracy without much involvement of human manual intervention. In this paper, we present our research on automated segmentation of lung parenchyma with an improved geodesic active contour model that is geodesic active contour model based on similarity (GACBS). Combining spectral clustering algorithm based on Nystrom (SCN) with GACBS, this algorithm first extracts key image slices, then uses these slices to generate an initial contour of pulmonary parenchyma of un-segmented slices with an interpolation algorithm, and finally segments lung parenchyma of un-segmented slices. Experimental results show that the segmentation results generated by our method are close to what manual segmentation can produce, with an average volume overlap ratio of 91.48%.
Verket, Anders; Lyngstadaas, Ståle P; Rønold, Hans J; Wohlfahrt, Johan C
2014-02-01
This study investigated osseointegration of dental implants inserted in healed extraction sockets preserved with porous titanium granules (PTG). Three adult female minipigs (Gøttingen minipig; Ellegaard A/S, Dalmose, Denmark) had the mandibular teeth P2, P3 and P4 extracted. The extraction sockets were preserved with metallic PTG (Tigran PTG; Tigran Technologies AB, Malmö, Sweden) n = 12, heat oxidized white porous titanium granules (WPTG) (Tigran PTG White) n = 12 or left empty (sham) n = 6. All sites were covered with collagen membranes (Bio-Gide; Geistlich Pharma, Wolhausen, Switzerland) and allowed 11 weeks of healing before implants (Straumann Bone Level; Straumann, Basel, Switzerland) were inserted. The temperature was measured during preparation of the osteotomies. Resonance frequency analysis (RFA, Osstell; Osstell AB, Gothenburg, Sweden) was performed at implant insertion and at termination. After 6 weeks of submerged implant healing, the pigs were euthanized and jaw segments were excised for microCT and histological analyses. In the temperature and RFA analyses no significant differences were recorded between the test groups. The microCT analysis demonstrated an average bone volume of 61.7% for the PTG group compared to 50.3% for the WPTG group (P = 0.03) and 57.1% for the sham group. Histomorphometry demonstrated an average bone-to-implant contact of 68.2% for the PTG group compared to 36.6% for the WPTG group and 60.9% for the sham group (n.s). Eight out of ten implants demonstrated apical osseous defects in the WPTG group, but similar defects were observed in all groups. PTG preserved extraction sockets demonstrate a similar outcome as the sham control group for all analyses suggesting that this material potentially can be used for extraction socket preservation prior to implant installment. Apical osseous defects were however observed in all groups including the sham group, and a single cause could not be determined. © 2012 John Wiley & Sons A/S.
Dual energy computed tomography for the head.
Naruto, Norihito; Itoh, Toshihide; Noguchi, Kyo
2018-02-01
Dual energy CT (DECT) is a promising technology that provides better diagnostic accuracy in several brain diseases. DECT can generate various types of CT images from a single acquisition data set at high kV and low kV based on material decomposition algorithms. The two-material decomposition algorithm can separate bone/calcification from iodine accurately. The three-material decomposition algorithm can generate a virtual non-contrast image, which helps to identify conditions such as brain hemorrhage. A virtual monochromatic image has the potential to eliminate metal artifacts by reducing beam-hardening effects. DECT also enables exploration of advanced imaging to make diagnosis easier. One such novel application of DECT is the X-Map, which helps to visualize ischemic stroke in the brain without using iodine contrast medium.
Spectra of clinical CT scanners using a portable Compton spectrometer.
Duisterwinkel, H A; van Abbema, J K; van Goethem, M J; Kawachimaru, R; Paganini, L; van der Graaf, E R; Brandenburg, S
2015-04-01
Spectral information of the output of x-ray tubes in (dual source) computer tomography (CT) scanners can be used to improve the conversion of CT numbers to proton stopping power and can be used to advantage in CT scanner quality assurance. The purpose of this study is to design, validate, and apply a compact portable Compton spectrometer that was constructed to accurately measure x-ray spectra of CT scanners. In the design of the Compton spectrometer, the shielding materials were carefully chosen and positioned to reduce background by x-ray fluorescence from the materials used. The spectrum of Compton scattered x-rays alters from the original source spectrum due to various physical processes. Reconstruction of the original x-ray spectrum from the Compton scattered spectrum is based on Monte Carlo simulations of the processes involved. This reconstruction is validated by comparing directly and indirectly measured spectra of a mobile x-ray tube. The Compton spectrometer is assessed in a clinical setting by measuring x-ray spectra at various tube voltages of three different medical CT scanner x-ray tubes. The directly and indirectly measured spectra are in good agreement (their ratio being 0.99) thereby validating the reconstruction method. The measured spectra of the medical CT scanners are consistent with theoretical spectra and spectra obtained from the x-ray tube manufacturer. A Compton spectrometer has been successfully designed, constructed, validated, and applied in the measurement of x-ray spectra of CT scanners. These measurements show that our compact Compton spectrometer can be rapidly set-up using the alignment lasers of the CT scanner, thereby enabling its use in commissioning, troubleshooting, and, e.g., annual performance check-ups of CT scanners.
Bulla, A; Casoli, C; Farace, F; Mazzarello, V; De Luca, L; Rubino, C; Montella, A
2014-01-01
The aim of the present study is to propose a new contrast agent that can be easily applied both to CT and dissection studies to replace lead oxide based formulas for comparative anatomical analyses of the vascularisation of cadaveric specimens. The infusion material was an epoxy resin, especially modified by the addition of barium sulphate to enhance its radiopacity. The final copolymer was toxicologically safe. To test the properties of the new material, several cadaveric limb injections were performed. The injected specimens were both CT scanned to perform 3D vascular reconstructions and dissected by anatomical planes. There was a perfect correspondence between the image studies and the dissections: even the smallest arteries on CT scan can be identified on the specimen and vice versa. The properties of the epoxy allowed an easy dissection of the vessels. The new imaging techniques available today, such as CT scan, can evaluate the vascular anatomy in high detail and 3D. This new contrast agent may help realising detailed vascular studies comparing CT scan results with anatomical dissections. Moreover, it may be useful for teaching surgical skills in the field of plastic surgery.
NASA Astrophysics Data System (ADS)
Yuan, Fusong; Lv, Peijun; Yang, Huifang; Wang, Yong; Sun, Yuchun
2015-07-01
Objectives: Based on the pixel gray value measurements, establish a beam-hardening artifacts index of the cone-beam CT tomographic image, and preliminarily evaluate its applicability. Methods: The 5mm-diameter metal ball and resin ball were fixed on the light-cured resin base plate respectively, while four vitro molars were fixed above and below the ball, on the left and right respectively, which have 10mm distance with the metal ball. Then, cone beam CT was used to scan the fixed base plate twice. The same layer tomographic images were selected from the two data and imported into the Photoshop software. The circle boundary was built through the determination of the center and radius of the circle, according to the artifact-free images section. Grayscale measurement tools were used to measure the internal boundary gray value G0, gray value G1 and G2 of 1mm and 20mm artifacts outside the circular boundary, the length L1 of the arc with artifacts in the circular boundary, the circumference L2. Hardening artifacts index was set A = (G1 / G0) * 0.5 + (G2 / G1) * 0.4 + (L2 / L1) * 0.1. Then, the A values of metal and resin materials were calculated respectively. Results: The A value of cobalt-chromium alloy material is 1, and resin material is 0. Conclusion: The A value reflects comprehensively the three factors of hardening artifacts influencing normal oral tissue image sharpness of cone beam CT. The three factors include relative gray value, the decay rate and range of artifacts.
Farina, Roberto; Bressan, Eriberto; Taut, Andrei; Cucchi, Alessandro; Trombelli, Leonardo
2014-10-01
To address the criticisms raised by Anitua et al. (European Journal of Oral Implantology, 6, 2013, 9-11) to the article "Plasma Rich in Growth Factors (PRGF) in Human Post-Extraction Sockets: an Histological and Histomorphometric Study.", recently published by Farina and colleagues (Clinical Oral Implants Research 2012; doi: 10.1111/clr.12033). All the methodological aspects criticized in the letter by Anitua et al. were thoroughly reconsidered and discussed in a structured short communication. When indicated, pertinent, additional material was included to reinforce our considerations. As most clinical studies in implant dentistry, including previous studies evaluating the efficacy/effectiveness of PRGF, the study by Farina et al. has some limitations. However, it is currently the only published controlled trial using quantitative parameters related to PRGF-induced early bone formation. Despite all limitations, the results of the study by Farina et al., which were based on different quantitative parameters (micro-CT scan, immunohistochemical markers of wound healing and bone deposition), indicated a limited effect of PRGF on early bone formation in extraction sockets. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Suzuki, H.; Matsuhiro, M.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, Masahiro; Moriyama, N.
2014-03-01
Chronic obstructive pulmonary disease is a major public health problem that is predicted to be third leading cause of death in 2030. Although spirometry is traditionally used to quantify emphysema progression, it is difficult to detect the loss of pulmonary function by emphysema in early stage, and to assess the susceptibility to smoking. This study presents quantification method of smoking-induced emphysema progression based on annual changes of low attenuation volume (LAV) by each lung lobe acquired from low-dose CT images in lung cancer screening. The method consists of three steps. First, lung lobes are segmented using extracted interlobar fissures by enhancement filter based on fourdimensional curvature. Second, LAV of each lung lobe is segmented. Finally, smoking-induced emphysema progression is assessed by statistical analysis of the annual changes represented by linear regression of LAV percentage in each lung lobe. This method was applied to 140 participants in lung cancer CT screening for six years. The results showed that LAV progressions of nonsmokers, past smokers, and current smokers are different in terms of pack-year and smoking cessation duration. This study demonstrates effectiveness in diagnosis and prognosis of early emphysema in lung cancer CT screening.
ERIC Educational Resources Information Center
Specht, Pamela Hammers
1985-01-01
The article describes a study conducted to determine whether experiential learning-based discussion is more effective than lecture-based discussion in facilitating understanding of material presented in a typical undergraduate business course, specifically organizational communication networks. (CT)
68Ga-PSMA-11 Dynamic PET/CT Imaging in Primary Prostate Cancer.
Sachpekidis, Christos; Kopka, Klaus; Eder, Matthias; Hadaschik, Boris A; Freitag, Martin T; Pan, Leyun; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia
2016-11-01
The aim of our study is to assess the pharmacokinetics and biodistribution of Ga-PSMA-11 in patients suffering from primary prostate cancer (PC) by means of dynamic and whole-body PET/CT. Twenty-four patients with primary, previously untreated PC were enrolled in the study. All patients underwent dynamic PET/CT (dPET/CT) scanning of the pelvis and whole-body PET/CT studies with Ga-PSMA-11. The evaluation of dPET/CT studies was based on qualitative evaluation, SUV calculation, and quantitative analysis based on two-tissue compartment modeling and a noncompartmental approach leading to the extraction of fractal dimension (FD). A total of 23/24 patients (95.8%) were Ga-PSMA-11 positive. In 9/24 patients (37.5%), metastatic lesions were detected. PC-associated lesions demonstrated the following mean values: SUVaverage = 14.3, SUVmax = 23.4, K1 = 0.24 (1/min), k3 = 0.34 (1/min), influx = 0.15 (1/min), and FD = 1.27. The parameters SUVaverage, SUVmax, k3, influx, and FD derived from PC-associated lesions were significantly higher than respective values derived from reference prostate tissue. Time-activity curves derived from PC-associated lesions revealed an increasing Ga-PSMA-11 accumulation during dynamic PET acquisition. Correlation analysis revealed a moderate but significant correlation between PSA levels and SUVaverage (r = 0.60) and SUVmax (r = 0.57), and a weak but significant correlation between Gleason score and SUVaverage (r = 0.33) and SUVmax (r = 0.28). Ga-PSMA-11 PET/CT confirmed its capacity in detecting primary PC with a detection rate of 95.8%. Dynamic PET/CT studies of the pelvis revealed an increase in tracer uptake in PC-associated lesions during the 60 minutes of dynamic PET acquisition, a finding with potential applications in anti-PSMA approaches.
A new method to measure electron density and effective atomic number using dual-energy CT images
NASA Astrophysics Data System (ADS)
Ramos Garcia, Luis Isaac; Pérez Azorin, José Fernando; Almansa, Julio F.
2016-01-01
The purpose of this work is to present a new method to extract the electron density ({ρ\\text{e}} ) and the effective atomic number (Z eff) from dual-energy CT images, based on a Karhunen-Loeve expansion (KLE) of the atomic cross section per electron. This method was used to calibrate a Siemens Definition CT using the CIRS phantom. The predicted electron density and effective atomic number using 80 kVp and 140 kVp were compared with a calibration phantom and an independent set of samples. The mean absolute deviations between the theoretical and calculated values for all the samples were 1.7 % ± 0.1 % for {ρ\\text{e}} and 4.1 % ± 0.3 % for Z eff. Finally, these results were compared with other stoichiometric method. The application of the KLE to represent the atomic cross section per electron is a promising method for calculating {ρ\\text{e}} and Z eff using dual-energy CT images.
Improved proton CT imaging using a bismuth germanium oxide scintillator.
Tanaka, Sodai; Nishio, Teiji; Tsuneda, Masato; Matsushita, Keiichiro; Kabuki, Shigeto; Uesaka, Mitsuru
2018-02-02
Range uncertainty is among the most formidable challenges associated with the treatment planning of proton therapy. Proton imaging, which includes proton radiography and proton computed tomography (pCT), is a useful verification tool. We have developed a pCT detection system that uses a thick bismuth germanium oxide (BGO) scintillator and a CCD camera. The current method is based on a previous detection system that used a plastic scintillator, and implements improved image processing techniques. In the new system, the scintillation light intensity is integrated along the proton beam path by the BGO scintillator, and acquired as a two-dimensional distribution with the CCD camera. The range of a penetrating proton is derived from the integrated light intensity using a light-to-range conversion table, and a pCT image can be reconstructed. The proton range in the BGO scintillator is shorter than in the plastic scintillator, so errors due to extended proton ranges can be reduced. To demonstrate the feasibility of the pCT system, an experiment was performed using a 70 MeV proton beam created by the AVF930 cyclotron at the National Institute of Radiological Sciences. The accuracy of the light-to-range conversion table, which is susceptible to errors due to its spatial dependence, was investigated, and the errors in the acquired pixel values were less than 0.5 mm. Images of various materials were acquired, and the pixel-value errors were within 3.1%, which represents an improvement over previous results. We also obtained a pCT image of an edible chicken piece, the first of its kind for a biological material, and internal structures approximately one millimeter in size were clearly observed. This pCT imaging system is fast and simple, and based on these findings, we anticipate that we can acquire 200 MeV pCT images using the BGO scintillator system.
Yang, Chuang-Bo; Zhang, Shuang; Jia, Yong-Jun; Duan, Hai-Feng; Ma, Guang-Ming; Zhang, Xi-Rong; Yu, Yong; He, Tai-Ping
2017-04-01
This study aimed to investigate the clinical value of spectral computed tomography (CT) in the detection of cholesterol gallstones from surrounding bile. This study was approved by the institutional review board. The unenhanced spectral CT data of 24 patients who had surgically confirmed cholesterol gallstones were analyzed. Lipid concentrations and CT numbers were measured from fat-based material decomposition image and virtual monochromatic image sets (40-140 keV), respectively. The difference in lipid concentration and CT number between cholesterol gallstones and the surrounding bile were statistically analyzed. Receiver operating characteristic analysis was applied to determine the diagnostic accuracy of using lipid concentration to differentiate cholesterol gallstones from bile. Cholesterol gallstones were bright on fat-based material decomposition images yielding a 92% detection rate (22 of 24). The lipid concentrations (552.65 ± 262.36 mg/mL), CT number at 40 keV (-31.57 ± 16.88 HU) and 140 keV (24.30 ± 5.85 HU) for the cholesterol gallstones were significantly different from those of bile (-13.94 ± 105.12 mg/mL, 12.99 ± 9.39 HU and 6.19 ± 4.97 HU, respectively). Using 182.59 mg/mL as the threshold value for lipid concentration, one could obtain sensitivity of 95.5% and specificity of 100% with accuracy of 0.994 for differentiating cholesterol gallstones from bile. Virtual monochromatic spectral CT images at 40 keV and 140 keV provide significant CT number differences between cholesterol gallstones and the surrounding bile. Spectral CT provides an excellent detection rate for cholesterol gallstones. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
Improved proton CT imaging using a bismuth germanium oxide scintillator
NASA Astrophysics Data System (ADS)
Tanaka, Sodai; Nishio, Teiji; Tsuneda, Masato; Matsushita, Keiichiro; Kabuki, Shigeto; Uesaka, Mitsuru
2018-02-01
Range uncertainty is among the most formidable challenges associated with the treatment planning of proton therapy. Proton imaging, which includes proton radiography and proton computed tomography (pCT), is a useful verification tool. We have developed a pCT detection system that uses a thick bismuth germanium oxide (BGO) scintillator and a CCD camera. The current method is based on a previous detection system that used a plastic scintillator, and implements improved image processing techniques. In the new system, the scintillation light intensity is integrated along the proton beam path by the BGO scintillator, and acquired as a two-dimensional distribution with the CCD camera. The range of a penetrating proton is derived from the integrated light intensity using a light-to-range conversion table, and a pCT image can be reconstructed. The proton range in the BGO scintillator is shorter than in the plastic scintillator, so errors due to extended proton ranges can be reduced. To demonstrate the feasibility of the pCT system, an experiment was performed using a 70 MeV proton beam created by the AVF930 cyclotron at the National Institute of Radiological Sciences. The accuracy of the light-to-range conversion table, which is susceptible to errors due to its spatial dependence, was investigated, and the errors in the acquired pixel values were less than 0.5 mm. Images of various materials were acquired, and the pixel-value errors were within 3.1%, which represents an improvement over previous results. We also obtained a pCT image of an edible chicken piece, the first of its kind for a biological material, and internal structures approximately one millimeter in size were clearly observed. This pCT imaging system is fast and simple, and based on these findings, we anticipate that we can acquire 200 MeV pCT images using the BGO scintillator system.
Sapthagirivasan, V; Anburajan, M; Janarthanam, S
2015-08-01
The early detection of osteoporosis risk enhances the lifespan and quality of life of an individual. A reasonable in-vivo assessment of trabecular bone strength at the proximal femur helps to evaluate the fracture risk and henceforth, to understand the associated structural dynamics on occurrence of osteoporosis. The main aim of our study was to develop a framework to automatically determine the trabecular bone strength from clinical femur CT images and thereby to estimate its correlation with BMD. All the 50 studied south Indian female subjects aged 30 to 80 years underwent CT and DXA measurements at right femur region. Initially, the original CT slices were intensified and active contour model was utilised for the extraction of the neck region. After processing through a novel process called trabecular enrichment approach (TEA), the three dimensional (3D) trabecular features were extracted. The extracted 3D trabecular features, such as volume fraction (VF), solidity of delta points (SDP) and boundness, demonstrated a significant correlation with femoral neck bone mineral density (r = 0.551, r = 0.432, r = 0.552 respectively) at p < 0.001. The higher area under the curve values of the extracted features (VF: 85.3 %; 95CI: 68.2-100 %, SDP: 82.1 %; 95CI: 65.1-98.9 % and boundness: 90.4 %; 95CI: 78.7-100 %) were observed. The findings suggest that the proposed framework with TEA method would be useful for spotting women vulnerable to osteoporotic risk.
Creation of a 3D printed temporal bone model from clinical CT data.
Cohen, Joss; Reyes, Samuel A
2015-01-01
Generate and describe the process of creating a 3D printed, rapid prototype temporal bone model from clinical quality CT images. We describe a technique to create an accurate, alterable, and reproducible rapid prototype temporal bone model using freely available software to segment clinical CT data and generate three different 3D models composed of ABS plastic. Each model was evaluated based on the appearance and size of anatomical structures and response to surgical drilling. Mastoid air cells had retained scaffolding material in the initial versions. This required modifying the model to allow drainage of the scaffolding material. External auditory canal dimensions were similar to those measured from the clinical data. Malleus, incus, oval window, round window, promontory, horizontal semicircular canal, and mastoid segment of the facial nerve canal were identified in all models. The stapes was only partially formed in two models and absent in the third. Qualitative feel of the ABS plastic was softer than bone. The pate produced by drilling was similar to bone dust when appropriate irrigation was used. We present a rapid prototype temporal bone model made based on clinical CT data using 3D printing technology. The model can be made quickly and inexpensively enough to have potential applications for educational training. Copyright © 2015 Elsevier Inc. All rights reserved.
Liang, Jibei; Cheng, Tao; Huang, Yi; Liu, Jianhua
2018-05-28
Enhanced bioremediation is a favorable approach for petroleum pollutant cleanup, which depends on the growth of oil-eating microorganisms. In this study, we show that, by using the modified T-RFLP (mT-RFLP) methodology, one of the four major microbial populations derived from oil sludge has failed to propagate in MS medium supplemented with 2% yeast extract (YE). rDNA sequence-based analysis indicated that the four populations were Donghicola sp. CT5, Bacillus sp. CT6, Alcaligenes sp. CT10, and Pseudomonas sp. ZS1. Four purified strains grow well individually in MS medium supplemented with 2% YE, suggesting that ZS1 growth is antagonized by other strains. Co-growth analysis using mT-RFLP methodology and plate inhibitory assay indicated that ZS1 exhibited antagonistic effect against CT5 and CT6. On the other hand, co-growth analysis and plate inhibition assay showed that CT10 antagonized against ZS1. To investigate the potential compounds responsible for the antagonism, supernatant of CT10 culture was subjected to GC-MS analysis. Analysis indicated that CT10 produced a number of antimicrobial compounds including cyclodipeptide c-(L-Pro-L-Phe), which was known to inhibit the growth of Pseudomonas sp. Growth test using the purified c-(L-Pro-L-Phe) from CT10 confirmed its inhibitory activity. We further showed that, using both gravimetric and GC analysis, CT10 antagonism against the oil-eating ZS1 led to the diminishing of crude oil degradation. Together, our results indicate that bioremediation can be affected by environmental antagonists.
An algorithm for intelligent sorting of CT-related dose parameters.
Cook, Tessa S; Zimmerman, Stefan L; Steingall, Scott R; Boonn, William W; Kim, Woojin
2012-02-01
Imaging centers nationwide are seeking innovative means to record and monitor computed tomography (CT)-related radiation dose in light of multiple instances of patient overexposure to medical radiation. As a solution, we have developed RADIANCE, an automated pipeline for extraction, archival, and reporting of CT-related dose parameters. Estimation of whole-body effective dose from CT dose length product (DLP)--an indirect estimate of radiation dose--requires anatomy-specific conversion factors that cannot be applied to total DLP, but instead necessitate individual anatomy-based DLPs. A challenge exists because the total DLP reported on a dose sheet often includes multiple separate examinations (e.g., chest CT followed by abdominopelvic CT). Furthermore, the individual reported series DLPs may not be clearly or consistently labeled. For example, "arterial" could refer to the arterial phase of the triple liver CT or the arterial phase of a CT angiogram. To address this problem, we have designed an intelligent algorithm to parse dose sheets for multi-series CT examinations and correctly separate the total DLP into its anatomic components. The algorithm uses information from the departmental PACS to determine how many distinct CT examinations were concurrently performed. Then, it matches the number of distinct accession numbers to the series that were acquired and anatomically matches individual series DLPs to their appropriate CT examinations. This algorithm allows for more accurate dose analytics, but there remain instances where automatic sorting is not feasible. To ultimately improve radiology patient care, we must standardize series names and exam names to unequivocally sort exams by anatomy and correctly estimate whole-body effective dose.
An algorithm for intelligent sorting of CT-related dose parameters
NASA Astrophysics Data System (ADS)
Cook, Tessa S.; Zimmerman, Stefan L.; Steingal, Scott; Boonn, William W.; Kim, Woojin
2011-03-01
Imaging centers nationwide are seeking innovative means to record and monitor CT-related radiation dose in light of multiple instances of patient over-exposure to medical radiation. As a solution, we have developed RADIANCE, an automated pipeline for extraction, archival and reporting of CT-related dose parameters. Estimation of whole-body effective dose from CT dose-length product (DLP)-an indirect estimate of radiation dose-requires anatomy-specific conversion factors that cannot be applied to total DLP, but instead necessitate individual anatomy-based DLPs. A challenge exists because the total DLP reported on a dose sheet often includes multiple separate examinations (e.g., chest CT followed by abdominopelvic CT). Furthermore, the individual reported series DLPs may not be clearly or consistently labeled. For example, Arterial could refer to the arterial phase of the triple liver CT or the arterial phase of a CT angiogram. To address this problem, we have designed an intelligent algorithm to parse dose sheets for multi-series CT examinations and correctly separate the total DLP into its anatomic components. The algorithm uses information from the departmental PACS to determine how many distinct CT examinations were concurrently performed. Then, it matches the number of distinct accession numbers to the series that were acquired, and anatomically matches individual series DLPs to their appropriate CT examinations. This algorithm allows for more accurate dose analytics, but there remain instances where automatic sorting is not feasible. To ultimately improve radiology patient care, we must standardize series names and exam names to unequivocally sort exams by anatomy and correctly estimate whole-body effective dose.
Kang, Sung-Won; Lee, Woo-Jin; Choi, Soon-Chul; Lee, Sam-Sun; Heo, Min-Suk; Huh, Kyung-Hoe
2015-01-01
Purpose We have developed a new method of segmenting the areas of absorbable implants and bone using region-based segmentation of micro-computed tomography (micro-CT) images, which allowed us to quantify volumetric bone-implant contact (VBIC) and volumetric absorption (VA). Materials and Methods The simple threshold technique generally used in micro-CT analysis cannot be used to segment the areas of absorbable implants and bone. Instead, a region-based segmentation method, a region-labeling method, and subsequent morphological operations were successively applied to micro-CT images. The three-dimensional VBIC and VA of the absorbable implant were then calculated over the entire volume of the implant. Two-dimensional (2D) bone-implant contact (BIC) and bone area (BA) were also measured based on the conventional histomorphometric method. Results VA and VBIC increased significantly with as the healing period increased (p<0.05). VBIC values were significantly correlated with VA values (p<0.05) and with 2D BIC values (p<0.05). Conclusion It is possible to quantify VBIC and VA for absorbable implants using micro-CT analysis using a region-based segmentation method. PMID:25793178
TH-C-18A-08: A Management Tool for CT Dose Monitoring, Analysis, and Protocol Review
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, J; Chan, F; Newman, B
2014-06-15
Purpose: To develop a customizable tool for enterprise-wide managing of CT protocols and analyzing radiation dose information of CT exams for a variety of quality control applications Methods: All clinical CT protocols implemented on the 11 CT scanners at our institution were extracted in digital format. The original protocols had been preset by our CT management team. A commercial CT dose tracking software (DoseWatch,GE healthcare,WI) was used to collect exam information (exam date, patient age etc.), scanning parameters, and radiation doses for all CT exams. We developed a Matlab-based program (MathWorks,MA) with graphic user interface which allows to analyze themore » scanning protocols with the actual dose estimates, and compare the data to national (ACR,AAPM) and internal reference values for CT quality control. Results: The CT protocol review portion of our tool allows the user to look up the scanning and image reconstruction parameters of any protocol on any of the installed CT systems among about 120 protocols per scanner. In the dose analysis tool, dose information of all CT exams (from 05/2013 to 02/2014) was stratified on a protocol level, and within a protocol down to series level, i.e. each individual exposure event. This allows numerical and graphical review of dose information of any combination of scanner models, protocols and series. The key functions of the tool include: statistics of CTDI, DLP and SSDE, dose monitoring using user-set CTDI/DLP/SSDE thresholds, look-up of any CT exam dose data, and CT protocol review. Conclusion: our inhouse CT management tool provides radiologists, technologists and administration a first-hand near real-time enterprise-wide knowledge on CT dose levels of different exam types. Medical physicists use this tool to manage CT protocols, compare and optimize dose levels across different scanner models. It provides technologists feedback on CT scanning operation, and knowledge on important dose baselines and thresholds.« less
MRI and CT contrast media extravasation: A systematic review.
Heshmatzadeh Behzadi, Ashkan; Farooq, Zerwa; Newhouse, Jeffery H; Prince, Martin R
2018-03-01
This systematic review combines data from multiple papers on contrast media extravasation to identify factors contributing to increased extravasation risk. Data were extracted from 17 papers reporting 2191 extravasations in 1,104,872 patients (0.2%) undergoing computed tomography (CT) or magnetic resonance imaging (MRI). Extravasation rates were 0.045% for gadolinium-based contrast agents (GBCA) and nearly 6-fold higher, 0.26% for iodinated contrast agents. Factors associated with increased contrast media extravasations included: older age, female gender, using an existing intravenous (IV) instead of placing a new IV in radiology, in-patient status, use of automated power injection, high injection rates, catheter location, and failing to warm up the more viscous contrast media to body temperature. Contrast media extravasation is infrequent but nearly 6 times less frequent with GBCA for MRI compared with iodinated contrast used in CT.
WE-FG-207B-04: Noise Suppression for Energy-Resolved CT Via Variance Weighted Non-Local Filtration
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harms, J; Zhu, L
Purpose: The photon starvation problem is exacerbated in energy-resolved CT, since the detected photons are shared by multiple energy channels. Using pixel similarity-based non-local filtration, we aim to produce accurate and high-resolution energy-resolved CT images with significantly reduced noise. Methods: Averaging CT images reconstructed from different energy channels reduces noise at the price of losing spectral information, while conventional denoising techniques inevitably degrade image resolution. Inspired by the fact that CT images of the same object at different energies share the same structures, we aim to reduce noise of energy-resolved CT by averaging only pixels of similar materials - amore » non-local filtration technique. For each CT image, an empirical exponential model is used to calculate the material similarity between two pixels based on their CT values and the similarity values are organized in a matrix form. A final similarity matrix is generated by averaging these similarity matrices, with weights inversely proportional to the estimated total noise variance in the sinogram of different energy channels. Noise suppression is achieved for each energy channel via multiplying the image vector by the similarity matrix. Results: Multiple scans on a tabletop CT system are used to simulate 6-channel energy-resolved CT, with energies ranging from 75 to 125 kVp. On a low-dose acquisition at 15 mA of the Catphan©600 phantom, our method achieves the same image spatial resolution as a high-dose scan at 80 mA with a noise standard deviation (STD) lower by a factor of >2. Compared with another non-local noise suppression algorithm (ndiNLM), the proposed algorithms obtains images with substantially improved resolution at the same level of noise reduction. Conclusion: We propose a noise-suppression method for energy-resolved CT. Our method takes full advantage of the additional structural information provided by energy-resolved CT and preserves image values at each energy level. Research reported in this publication was supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R21EB019597. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.« less
A review of automated image understanding within 3D baggage computed tomography security screening.
Mouton, Andre; Breckon, Toby P
2015-01-01
Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT.
Schmid-Bindert, Gerald; Wang, Yongsheng; Jiang, Hongbin; Sun, Hui; Henzler, Thomas; Wang, Hao; Pilz, Lothar R.; Ren, Shengxiang; Zhou, Caicun
2013-01-01
Background Multiple biomarker testing is necessary to facilitate individualized treatment of lung cancer patients. More than 80% of lung cancers are diagnosed based on very small tumor samples. Often there is not enough tissue for molecular analysis. We compared three minimal invasive sampling methods with respect to RNA quantity for molecular testing. Methods 106 small biopsies were prospectively collected by three different methods forceps biopsy, endobronchial ultrasound (EBUS) guided transbronchial needle aspiration (TBNA), and CT-guided core biopsy. Samples were split into two halves. One part was formalin fixed and paraffin embedded for standard pathological evaluation. The other part was put in RNAlater for immediate RNA/DNA extraction. If the pathologist confirmed the diagnosis of non-small cell lung cancer(NSCLC), the following molecular markers were tested: EGFR mutation, ERCC1, RRM1 and BRCA1. Results Overall, RNA-extraction was possible in 101 out of 106 patients (95.3%). We found 49% adenocarcinomas, 38% squamouscarcinomas, and 14% non-otherwise-specified(NOS). The highest RNA yield came from endobronchial ultrasound guided needle aspiration, which was significantly higher than bronchoscopy (37.74±41.09 vs. 13.74±15.53 ng respectively, P = 0.005) and numerically higher than CT-core biopsy (37.74±41.09 vs. 28.72±44.27 ng respectively, P = 0.244). EGFR mutation testing was feasible in 100% of evaluable patients and its incidence was 40.8%, 7.9% and 14.3% in adenocarcinomas, squamouscarcinomas and NSCLC NOS subgroup respectively. There was no difference in the feasibility of molecular testing between the three sampling methods with feasibility rates for ERCC1, RRM1 and BRCA1 of 91%, 87% and 81% respectively. Conclusion All three methods can provide sufficient tumor material for multiple biomarkers testing from routinely obtained small biopsies in lung cancer patients. In our study EBUS guided needle aspiration provided the highest amount of tumor RNA compared to bronchoscopy or CT guided core biopsy. Thus EBUS should be considered as an acceptable option for tissue acquisition for molecular testing. PMID:24205040
Computerized PET/CT image analysis in the evaluation of tumour response to therapy
Wang, J; Zhang, H H
2015-01-01
Current cancer therapy strategy is mostly population based, however, there are large differences in tumour response among patients. It is therefore important for treating physicians to know individual tumour response. In recent years, many studies proposed the use of computerized positron emission tomography/CT image analysis in the evaluation of tumour response. Results showed that computerized analysis overcame some major limitations of current qualitative and semiquantitative analysis and led to improved accuracy. In this review, we summarize these studies in four steps of the analysis: image registration, tumour segmentation, image feature extraction and response evaluation. Future works are proposed and challenges described. PMID:25723599
NASA Astrophysics Data System (ADS)
Almeida, Isabel P.; Schyns, Lotte E. J. R.; Vaniqui, Ana; van der Heyden, Brent; Dedes, George; Resch, Andreas F.; Kamp, Florian; Zindler, Jaap D.; Parodi, Katia; Landry, Guillaume; Verhaegen, Frank
2018-06-01
Proton beam ranges derived from dual-energy computed tomography (DECT) images from a dual-spiral radiotherapy (RT)-specific CT scanner were assessed using Monte Carlo (MC) dose calculations. Images from a dual-source and a twin-beam DECT scanner were also used to establish a comparison to the RT-specific scanner. Proton ranges extracted from conventional single-energy CT (SECT) were additionally performed to benchmark against literature values. Using two phantoms, a DECT methodology was tested as input for GEANT4 MC proton dose calculations. Proton ranges were calculated for different mono-energetic proton beams irradiating both phantoms; the results were compared to the ground truth based on the phantom compositions. The same methodology was applied in a head-and-neck cancer patient using both SECT and dual-spiral DECT scans from the RT-specific scanner. A pencil-beam-scanning plan was designed, which was subsequently optimized by MC dose calculations, and differences in proton range for the different image-based simulations were assessed. For phantoms, the DECT method yielded overall better material segmentation with >86% of the voxel correctly assigned for the dual-spiral and dual-source scanners, but only 64% for a twin-beam scanner. For the calibration phantom, the dual-spiral scanner yielded range errors below 1.2 mm (0.6% of range), like the errors yielded by the dual-source scanner (<1.1 mm, <0.5%). With the validation phantom, the dual-spiral scanner yielded errors below 0.8 mm (0.9%), whereas SECT yielded errors up to 1.6 mm (2%). For the patient case, where the absolute truth was missing, proton range differences between DECT and SECT were on average in ‑1.2 ± 1.2 mm (‑0.5% ± 0.5%). MC dose calculations were successfully performed on DECT images, where the dual-spiral scanner resulted in media segmentation and range accuracy as good as the dual-source CT. In the patient, the various methods showed relevant range differences.
X-ray Computed Tomography Assessment of Air Void Distribution in Concrete
NASA Astrophysics Data System (ADS)
Lu, Haizhu
Air void size and spatial distribution have long been regarded as critical parameters in the frost resistance of concrete. In cement-based materials, entrained air void systems play an important role in performance as related to durability, permeability, and heat transfer. Many efforts have been made to measure air void parameters in a more efficient and reliable manner in the past several decades. Standardized measurement techniques based on optical microscopy and stereology on flat cut and polished surfaces are widely used in research as well as in quality assurance and quality control applications. Other more automated methods using image processing have also been utilized, but still starting from flat cut and polished surfaces. The emergence of X-ray computed tomography (CT) techniques provides the capability of capturing the inner microstructure of materials at the micrometer and nanometer scale. X-ray CT's less demanding sample preparation and capability to measure 3D distributions of air voids directly provide ample prospects for its wider use in air void characterization in cement-based materials. However, due to the huge number of air voids that can exist within a limited volume, errors can easily arise in the absence of a formalized data processing procedure. In this study, air void parameters in selected types of cement-based materials (lightweight concrete, structural concrete elements, pavements, and laboratory mortars) have been measured using micro X-ray CT. The focus of this study is to propose a unified procedure for processing the data and to provide solutions to deal with common problems that arise when measuring air void parameters: primarily the reliable segmentation of objects of interest, uncertainty estimation of measured parameters, and the comparison of competing segmentation parameters.
Timeframe of socket cortication after tooth extraction: A retrospective radiographic study.
Bertl, Kristina; Kukla, Edmund Benjamin; Albugami, Rajaa; Beck, Florian; Gahleitner, André; Stavropoulos, Andreas
2018-01-01
To assess the timeframe between tooth extraction and radiographically detectable socket cortication in humans. Two hundred and fifty patients with a CT scan ≤36 months after tooth extraction were included. First, three orthoradial multiplanar reconstruction slices, representing the major part of the extraction socket, were scored regarding the degree of bone healing as (i) healed, that is, complete/continuous cortication of the socket entrance, or (ii) non-healed. Thereafter, based on the results of all three slices, the stage of cortication of the extraction socket, as one unit, was classified as (i) non-corticated, that is, all three slices judged as non-healed, (ii) partially corticated, that is, 1 or 2 slices judged as non-healed, or (iii) completely corticated, that is, all three slices judged as healed. The possible effect of several independent parameters, that is, age, gender, timeframe between tooth extraction and CT scan, tooth type, extent of radiographic bone loss of the extracted tooth, tooth-gap type, smoking status, presence of any systemic disease, and medication intake, on cortication status was statistically evaluated. Three to 6 months after tooth extraction, 27% of the sockets were judged as non-corticated and 53% were judged as partially corticated. After 9-12 months, >80% of the sockets were corticated, while some incompletely corticated sockets were detected up to 15 months after extraction. Each additional month after tooth extraction contributed significantly to a higher likelihood of a more advanced stage of cortication, while radiographic bone loss ≥75% significantly prolonged cortication time; no other independent variable had a significant effect. The results indicate a considerably long timeframe until complete cortication of an extraction socket, that is, 3-6 months after tooth extraction 3 of 4 sockets were still not completely corticated, and only after 9-12 months, complete cortication was observed in about 80% of the sockets. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Marginal Gaps between 2 Calcium Silicate and Glass Ionomer Cements and Apical Root Dentin.
Biočanin, Vladimir; Antonijević, Đorđe; Poštić, Srđan; Ilić, Dragan; Vuković, Zorica; Milić, Marija; Fan, Yifang; Li, Zhiyu; Brković, Božidar; Đurić, Marija
2018-05-01
The outcome of periapical surgery has been directly improved with the introduction of novel material formulations. The aim of the study was to compare the retrograde obturation quality of the following materials: calcium silicate (Biodentine; Septodont, Saint-Maur-des-Fosses, France), mineral trioxide aggregate (MTA+; Cerkamed Company, Stalowa Wola, Poland), and glass ionomer cement (Fuji IX; GC Corporation, Tokyo, Japan). Materials' wettability was calculated concerning the contact angles of the cements measured using a glycerol drop. Cements' porosity was determined using mercury intrusion porosimetry and micro-computed tomographic (μCT) imaging. Extracted upper human incisors were retrofilled, and μCT analysis was applied to calculate the volume of the gap between the retrograde filling material and root canal dentin. Experiments were performed before and after soaking the materials in simulated body fluid (SBF). No statistically significant differences were found among the contact angles of the studied materials after being soaked in SBF. The material with the lowest nanoporosity (Fuji IX: 2.99% and 4.17% before and after SBF, respectively) showed the highest values of microporosity (4.2% and 3.1% before and after SBF, respectively). Biodentine had the lowest value of microporosity (1.2% and 0.8% before and after SBF, respectively) and the lowest value of microgap to the root canal wall ([10 ± 30] × 10 -3 mm 3 ). Biodentine and MTA possess certain advantages over Fuji IX for hermetic obturation of retrograde root canals. Biodentine shows a tendency toward the lowest marginal gap at the cement-to-dentin interface. Copyright © 2018 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.
Kim, Sue Youn; Kim, Hyeon-Cheol; Shin, Su-Jung; Kim, Euiseong
2018-04-01
The purpose of this study was to evaluate the gap volume between dentin and root-end filling materials. Four root-end filling materials were compared in the present study: ProRoot MTA (PRM; Dentsply Tulsa Dental, Tulsa, OK), MTA Angelus (MAG; Angelus, Londrina, Brazil), EndoCem MTA (ECM; Maruchi, Wonju, Korea), and RetroMTA (RTM; BioMTA, Seoul, Korea). Forty-eight single-rooted, extracted human teeth were instrumented with nickel-titanium instruments and oburated with gutta-percha. The apical 3 mm of the root tip was resected, and root-end preparation was performed with a diamond bur. The root-end cavity was filled with the experimental filling materials for the 4 designated groups (n = 10). Then, the samples were scanned with micro-computed tomographic (micro-CT) imaging. Three-dimensional images of the samples were reconstructed, and the volume of the gap between the tooth surface (dentinal wall) and the root-end filling materials was measured. The percentage volume of the gap between the tooth structure and the root-end filling material (V G %) was calculated. Data were analyzed using the Kruskal-Wallis and Mann-Whitney U tests at a significance level of 95%. The median V G % values for the PRM, MAG, ECM, and RTM groups were 0.00472, 0.00134, 0.00014, and 0.00071, respectively. The ProRoot MTA group showed the greatest gap volume percentage among the experimental groups with a significant statistical difference (P < .05). From the micro-CT analysis, ProRoot MTA had a greater gap volume percentage than other root-end filling materials. Copyright © 2017 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.
Objective image characterization of a spectral CT scanner with dual-layer detector
NASA Astrophysics Data System (ADS)
Ozguner, Orhan; Dhanantwari, Amar; Halliburton, Sandra; Wen, Gezheng; Utrup, Steven; Jordan, David
2018-01-01
This work evaluated the performance of a detector-based spectral CT system by obtaining objective reference data, evaluating attenuation response of iodine and accuracy of iodine quantification, and comparing conventional CT and virtual monoenergetic images in three common phantoms. Scanning was performed using the hospital’s clinical adult body protocol. Modulation transfer function (MTF) was calculated for a tungsten wire and visual line pair targets were evaluated. Image noise power spectrum (NPS) and pixel standard deviation were calculated. MTF for monoenergetic images agreed with conventional images within 0.05 lp cm-1. NPS curves indicated that noise texture of 70 keV monoenergetic images is similar to conventional images. Standard deviation measurements showed monoenergetic images have lower noise except at 40 keV. Mean CT number and CNR agreed with conventional images at 75 keV. Measured iodine concentration agreed with true concentration within 6% for inserts at the center of the phantom. Performance of monoenergetic images at detector based spectral CT is the same as, or better than, that of conventional images. Spectral acquisition and reconstruction with a detector based platform represents the physical behaviour of iodine as expected and accurately quantifies the material concentration.
Simultaneous extraction of centerlines, stenosis, and thrombus detection in renal CT angiography
NASA Astrophysics Data System (ADS)
Subramanyan, Krishna; Durgan, Jacob; Hodgkiss, Thomas D.; Chandra, Shalabh
2004-05-01
The Renal Artery Stenosis (RAS) is the major cause of renovascular hypertension and CT angiography has shown tremendous promise as a noninvasive method for reliably detecting renal artery stenosis. The purpose of this study was to validate the semi-automated methods to assist in extraction of renal branches and characterizing the associated renal artery stenosis. Automatically computed diagnostic images such as straight MIP, curved MPR, cross-sections, and diameters from multi-slice CT are presented and evaluated for its acceptance. We used vessel-tracking image processing methods to extract the aortic-renal vessel tree in a CT data in axial slice images. Next, from the topology and anatomy of the aortic vessel tree, the stenosis, and thrombus section and branching of the renal arteries are extracted. The results are presented in curved MPR and continuously variable MIP images. In this study, 15 patients were scanned with contrast on Mx8000 CT scanner (Philips Medical Systems), with 1.0 mm thickness, 0.5mm slice spacing, and 120kVp and a stack of 512x512x150 volume sets were reconstructed. The automated image processing took less than 50 seconds to compute the centerline and borders of the aortic/renal vessel tree. The overall assessment of manual and automatically generated stenosis yielded a weighted kappa statistic of 0.97 at right renal arteries, 0.94 at the left renal branches. The thrombus region contoured manually and semi-automatically agreed upon at 0.93. The manual time to process each case is approximately 25 to 30 minutes.
Morphology filter bank for extracting nodular and linear patterns in medical images.
Hashimoto, Ryutaro; Uchiyama, Yoshikazu; Uchimura, Keiichi; Koutaki, Gou; Inoue, Tomoki
2017-04-01
Using image processing to extract nodular or linear shadows is a key technique of computer-aided diagnosis schemes. This study proposes a new method for extracting nodular and linear patterns of various sizes in medical images. We have developed a morphology filter bank that creates multiresolution representations of an image. Analysis bank of this filter bank produces nodular and linear patterns at each resolution level. Synthesis bank can then be used to perfectly reconstruct the original image from these decomposed patterns. Our proposed method shows better performance based on a quantitative evaluation using a synthesized image compared with a conventional method based on a Hessian matrix, often used to enhance nodular and linear patterns. In addition, experiments show that our method can be applied to the followings: (1) microcalcifications of various sizes in mammograms can be extracted, (2) blood vessels of various sizes in retinal fundus images can be extracted, and (3) thoracic CT images can be reconstructed while removing normal vessels. Our proposed method is useful for extracting nodular and linear shadows or removing normal structures in medical images.
Marwede, Dirk; Schulz, Thomas; Kahn, Thomas
2008-12-01
To validate a preliminary version of a radiological lexicon (RadLex) against terms found in thoracic CT reports and to index report content in RadLex term categories. Terms from a random sample of 200 thoracic CT reports were extracted using a text processor and matched against RadLex. Report content was manually indexed by two radiologists in consensus in term categories of Anatomic Location, Finding, Modifier, Relationship, Image Quality, and Uncertainty. Descriptive statistics were used and differences between age groups and report types were tested for significance using Kruskal-Wallis and Mann-Whitney Test (significance level <0.05). From 363 terms extracted, 304 (84%) were found and 59 (16%) were not found in RadLex. Report indexing showed a mean of 16.2 encoded items per report and 3.2 Finding per report. Term categories most frequently encoded were Modifier (1,030 of 3,244, 31.8%), Anatomic Location (813, 25.1%), Relationship (702, 21.6%) and Finding (638, 19.7%). Frequency of indexed items per report was higher in older age groups, but no significant difference was found between first study and follow up study reports. Frequency of distinct findings per report increased with patient age (p < 0.05). RadLex already covers most terms present in thoracic CT reports based on a small sample analysis from one institution. Applications for report encoding need to be developed to validate the lexicon against a larger sample of reports and address the issue of automatic relationship encoding.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goodsitt, Mitchell M.; Christodoulou, Emmanuel G.; Larson, Sandra C.
2011-04-15
Purpose: This study was performed to investigate the accuracies of the synthesized monochromatic images and effective atomic number maps obtained with the new GE Discovery CT750 HD CT scanner. Methods: A Gammex-RMI model 467 tissue characterization phantom and the CT number linearity section of a Phantom Laboratory Catphan 600 phantom were scanned using the dual energy (DE) feature on the GE CT750 HD scanner. Synthesized monochromatic images at various energies between 40 and 120 keV and effective atomic number (Z{sub eff}) maps were generated. Regions of interest were placed within these images/maps to measure the average monochromatic CT numbers andmore » average Z{sub eff} of the materials within these phantoms. The true Z{sub eff} values were either supplied by the phantom manufacturer or computed using Mayneord's equation. The linear attenuation coefficients for the true CT numbers were computed using the NIST XCOM program with the input of manufacturer supplied elemental compositions and densities. The effects of small variations in the assumed true densities of the materials were also investigated. Finally, the effect of body size on the accuracies of the synthesized monochromatic CT numbers was investigated using a custom lumbar section phantom with and without an external fat-mimicking ring. Results: Other than the Z{sub eff} of the simulated lung inserts in the tissue characterization phantom, which could not be measured by DECT, the Z{sub eff} values of all of the other materials in the tissue characterization and Catphan phantoms were accurate to 15%. The accuracies of the synthesized monochromatic CT numbers of the materials in both phantoms varied with energy and material. For the 40-120 keV range, RMS errors between the measured and true CT numbers in the Catphan are 8-25 HU when the true CT numbers were computed using the nominal plastic densities. These RMS errors improve to 3-12 HU for assumed true densities within the nominal density {+-}0.02 g/cc range. The RMS errors between the measured and true CT numbers of the tissue mimicking materials in the tissue characterization phantom over the 40-120 keV range varied from about 6 HU-248 HU and did not improve as dramatically with small changes in assumed true density. Conclusions: Initial tests indicate that the Z{sub eff} values computed with DECT on this scanner are reasonably accurate; however, the synthesized monochromatic CT numbers can be very inaccurate, especially for dense tissue mimicking materials at low energies. Furthermore, the synthesized monochromatic CT numbers of materials still depend on the amount of the surrounding tissues especially at low keV, demonstrating that the numbers are not truly monochromatic. Further research is needed to develop DE methods that produce more accurate synthesized monochromatic CT numbers.« less
MO-FG-204-01: Improved Noise Suppression for Dual-Energy CT Through Entropy Minimization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Petrongolo, M; Zhu, L
2015-06-15
Purpose: In dual energy CT (DECT), noise amplification during signal decomposition significantly limits the utility of basis material images. Since clinically relevant objects contain a limited number of materials, we propose to suppress noise for DECT based on image entropy minimization. An adaptive weighting scheme is employed during noise suppression to improve decomposition accuracy with limited effect on spatial resolution and image texture preservation. Methods: From decomposed images, we first generate a 2D plot of scattered data points, using basis material densities as coordinates. Data points representing the same material generate a highly asymmetric cluster. We orient an axis bymore » minimizing the entropy in a 1D histogram of these points projected onto the axis. To suppress noise, we replace pixel values of decomposed images with center-of-mass values in the direction perpendicular to the optimal axis. To limit errors due to cluster overlap, we weight each data point’s contribution based on its high and low energy CT values and location within the image. The proposed method’s performance is assessed on physical phantom studies. Electron density is used as the quality metric for decomposition accuracy. Our results are compared to those without noise suppression and with a recently developed iterative method. Results: The proposed method reduces noise standard deviations of the decomposed images by at least one order of magnitude. On the Catphan phantom, this method greatly preserves the spatial resolution and texture of the CT images and limits induced error in measured electron density to below 1.2%. In the head phantom study, the proposed method performs the best in retaining fine, intricate structures. Conclusion: The entropy minimization based algorithm with adaptive weighting substantially reduces DECT noise while preserving image spatial resolution and texture. Future investigations will include extensive investigations on material decomposition accuracy that go beyond the current electron density calculations. This work was supported in part by the National Institutes of Health (NIH) under Grant Number R21 EB012700.« less
Respiratory trace feature analysis for the prediction of respiratory-gated PET quantification.
Wang, Shouyi; Bowen, Stephen R; Chaovalitwongse, W Art; Sandison, George A; Grabowski, Thomas J; Kinahan, Paul E
2014-02-21
The benefits of respiratory gating in quantitative PET/CT vary tremendously between individual patients. Respiratory pattern is among many patient-specific characteristics that are thought to play an important role in gating-induced imaging improvements. However, the quantitative relationship between patient-specific characteristics of respiratory pattern and improvements in quantitative accuracy from respiratory-gated PET/CT has not been well established. If such a relationship could be estimated, then patient-specific respiratory patterns could be used to prospectively select appropriate motion compensation during image acquisition on a per-patient basis. This study was undertaken to develop a novel statistical model that predicts quantitative changes in PET/CT imaging due to respiratory gating. Free-breathing static FDG-PET images without gating and respiratory-gated FDG-PET images were collected from 22 lung and liver cancer patients on a PET/CT scanner. PET imaging quality was quantified with peak standardized uptake value (SUV(peak)) over lesions of interest. Relative differences in SUV(peak) between static and gated PET images were calculated to indicate quantitative imaging changes due to gating. A comprehensive multidimensional extraction of the morphological and statistical characteristics of respiratory patterns was conducted, resulting in 16 features that characterize representative patterns of a single respiratory trace. The six most informative features were subsequently extracted using a stepwise feature selection approach. The multiple-regression model was trained and tested based on a leave-one-subject-out cross-validation. The predicted quantitative improvements in PET imaging achieved an accuracy higher than 90% using a criterion with a dynamic error-tolerance range for SUV(peak) values. The results of this study suggest that our prediction framework could be applied to determine which patients would likely benefit from respiratory motion compensation when clinicians quantitatively assess PET/CT for therapy target definition and response assessment.
Respiratory trace feature analysis for the prediction of respiratory-gated PET quantification
NASA Astrophysics Data System (ADS)
Wang, Shouyi; Bowen, Stephen R.; Chaovalitwongse, W. Art; Sandison, George A.; Grabowski, Thomas J.; Kinahan, Paul E.
2014-02-01
The benefits of respiratory gating in quantitative PET/CT vary tremendously between individual patients. Respiratory pattern is among many patient-specific characteristics that are thought to play an important role in gating-induced imaging improvements. However, the quantitative relationship between patient-specific characteristics of respiratory pattern and improvements in quantitative accuracy from respiratory-gated PET/CT has not been well established. If such a relationship could be estimated, then patient-specific respiratory patterns could be used to prospectively select appropriate motion compensation during image acquisition on a per-patient basis. This study was undertaken to develop a novel statistical model that predicts quantitative changes in PET/CT imaging due to respiratory gating. Free-breathing static FDG-PET images without gating and respiratory-gated FDG-PET images were collected from 22 lung and liver cancer patients on a PET/CT scanner. PET imaging quality was quantified with peak standardized uptake value (SUVpeak) over lesions of interest. Relative differences in SUVpeak between static and gated PET images were calculated to indicate quantitative imaging changes due to gating. A comprehensive multidimensional extraction of the morphological and statistical characteristics of respiratory patterns was conducted, resulting in 16 features that characterize representative patterns of a single respiratory trace. The six most informative features were subsequently extracted using a stepwise feature selection approach. The multiple-regression model was trained and tested based on a leave-one-subject-out cross-validation. The predicted quantitative improvements in PET imaging achieved an accuracy higher than 90% using a criterion with a dynamic error-tolerance range for SUVpeak values. The results of this study suggest that our prediction framework could be applied to determine which patients would likely benefit from respiratory motion compensation when clinicians quantitatively assess PET/CT for therapy target definition and response assessment.
The Development of Engineering Tomography for Monolithic and Composite Materials and Components
NASA Technical Reports Server (NTRS)
Hemann, John
1997-01-01
The research accomplishments under this grant were very extensive in the areas of the development of engineering tomography for monolithic and composite materials and components. Computed tomography was used on graphite composite pins and bushings to find porosity, cracks, and delaminations. It supported the following two programs: Reusable Launch Vehicle (RLV) and Southern Research institute (SRI). Did research using CT and radiography on Nickel based Superalloy dogbones and found density variations and gas shrinkage porosity. Did extensive radiography and CT of PMC composite flywheels and found delamination and non-uniform fiber distribution. This grant supported the Attitude Control Energy Storage Experiment (ACESE) program. Found broken fibers and cracks of outer stainless steel fibers using both radiographic and CT techniques on Pratt and Whitney fuel lines; Supported the Pratt & Whitney and Aging Aircraft engines program. Grant research helped identify and corroborate thickness variations and density differences in a silicon nitride "ROTH" tube using computed tomography.
Image processing based detection of lung cancer on CT scan images
NASA Astrophysics Data System (ADS)
Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi
2017-10-01
In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.
Carlbom, Lina; Caballero-Corbalán, José; Granberg, Dan; Sörensen, Jens; Eriksson, Barbro; Ahlström, Håkan
2017-01-01
Aim We wanted to explore if whole-body magnetic resonance imaging (MRI) including diffusion-weighted (DW) and liver-specific contrast agent-enhanced imaging could be valuable in lesion detection of neuroendocrine tumors (NET). [11C]-5-Hydroxytryptophan positron emission tomography/computed tomography (5-HTP PET/CT) was used for comparison. Materials and methods Twenty-one patients with NET were investigated with whole-body MRI, including DW imaging (DWI) and contrast-enhanced imaging of the liver, and whole-body 5-HTP PET/CT. Seven additional patients underwent upper abdomen MRI including DWI, liver-specific contrast agent-enhanced imaging, and 5-HTP PET/CT. Results There was a patient-based concordance of 61% and a lesion-based concordance of 53% between the modalities. MRI showed good concordance with PET in detecting bone metastases but was less sensitive in detecting metastases in mediastinal lymph nodes. MRI detected more liver metastases than 5-HTP PET/CT. Conclusion Whole-body MRI with DWI did not detect all NET lesions found with whole-body 5-HTP PET/CT. Our findings indicate that MRI of the liver including liver-specific contrast agent-enhanced imaging and DWI could be a useful complement to whole-body 5-HTP PET/CT. PMID:27894208
Material separation in x-ray CT with energy resolved photon-counting detectors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang Xiaolan; Meier, Dirk; Taguchi, Katsuyuki
Purpose: The objective of the study was to demonstrate that, in x-ray computed tomography (CT), more than two types of materials can be effectively separated with the use of an energy resolved photon-counting detector and classification methodology. Specifically, this applies to the case when contrast agents that contain K-absorption edges in the energy range of interest are present in the object. This separation is enabled via the use of recently developed energy resolved photon-counting detectors with multiple thresholds, which allow simultaneous measurements of the x-ray attenuation at multiple energies. Methods: To demonstrate this capability, we performed simulations and physical experimentsmore » using a six-threshold energy resolved photon-counting detector. We imaged mouse-sized cylindrical phantoms filled with several soft-tissue-like and bone-like materials and with iodine-based and gadolinium-based contrast agents. The linear attenuation coefficients were reconstructed for each material in each energy window and were visualized as scatter plots between pairs of energy windows. For comparison, a dual-kVp CT was also simulated using the same phantom materials. In this case, the linear attenuation coefficients at the lower kVp were plotted against those at the higher kVp. Results: In both the simulations and the physical experiments, the contrast agents were easily separable from other soft-tissue-like and bone-like materials, thanks to the availability of the attenuation coefficient measurements at more than two energies provided by the energy resolved photon-counting detector. In the simulations, the amount of separation was observed to be proportional to the concentration of the contrast agents; however, this was not observed in the physical experiments due to limitations of the real detector system. We used the angle between pairs of attenuation coefficient vectors in either the 5-D space (for non-contrast-agent materials using energy resolved photon-counting acquisition) or a 2-D space (for contrast agents using energy resolved photon-counting acquisition and all materials using dual-kVp acquisition) as a measure of the degree of separation. Compared to dual-kVp techniques, an energy resolved detector provided a larger separation and the ability to separate different target materials using measurements acquired in different energy window pairs with a single x-ray exposure. Conclusions: We concluded that x-ray CT with an energy resolved photon-counting detector with more than two energy windows allows the separation of more than two types of materials, e.g., soft-tissue-like, bone-like, and one or more materials with K-edges in the energy range of interest. Separating material types using energy resolved photon-counting detectors has a number of advantages over dual-kVp CT in terms of the degree of separation and the number of materials that can be separated simultaneously.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Niebuhr, Nina I., E-mail: n.niebuhr@dkfz.de; Johnen, Wibke; Güldaglar, Timur
Purpose: Phantom surrogates were developed to allow multimodal [computed tomography (CT), magnetic resonance imaging (MRI), and teletherapy] and anthropomorphic tissue simulation as well as materials and methods to construct deformable organ shapes and anthropomorphic bone models. Methods: Agarose gels of variable concentrations and loadings were investigated to simulate various soft tissue types. Oils, fats, and Vaseline were investigated as surrogates for adipose tissue and bone marrow. Anthropomorphic shapes of bone and organs were realized using 3D-printing techniques based on segmentations of patient CT-scans. All materials were characterized in dual energy CT and MRI to adapt CT numbers, electron density, effectivemore » atomic number, as well as T1- and T2-relaxation times to patient and literature values. Results: Soft tissue simulation could be achieved with agarose gels in combination with a gadolinium-based contrast agent and NaF to simulate muscle, prostate, and tumor tissues. Vegetable oils were shown to be a good representation for adipose tissue in all modalities. Inner bone was realized using a mixture of Vaseline and K{sub 2}HPO{sub 4}, resulting in both a fatty bone marrow signal in MRI and inhomogeneous areas of low and high attenuation in CT. The high attenuation of outer bone was additionally adapted by applying gypsum bandages to the 3D-printed hollow bone case with values up to 1200 HU. Deformable hollow organs were manufactured using silicone. Signal loss in the MR images based on the conductivity of the gels needs to be further investigated. Conclusions: The presented surrogates and techniques allow the customized construction of multimodality, anthropomorphic, and deformable phantoms as exemplarily shown for a pelvic phantom, which is intended to study adaptive treatment scenarios in MR-guided radiation therapy.« less
Niebuhr, Nina I; Johnen, Wibke; Güldaglar, Timur; Runz, Armin; Echner, Gernot; Mann, Philipp; Möhler, Christian; Pfaffenberger, Asja; Jäkel, Oliver; Greilich, Steffen
2016-02-01
Phantom surrogates were developed to allow multimodal [computed tomography (CT), magnetic resonance imaging (MRI), and teletherapy] and anthropomorphic tissue simulation as well as materials and methods to construct deformable organ shapes and anthropomorphic bone models. Agarose gels of variable concentrations and loadings were investigated to simulate various soft tissue types. Oils, fats, and Vaseline were investigated as surrogates for adipose tissue and bone marrow. Anthropomorphic shapes of bone and organs were realized using 3D-printing techniques based on segmentations of patient CT-scans. All materials were characterized in dual energy CT and MRI to adapt CT numbers, electron density, effective atomic number, as well as T1- and T2-relaxation times to patient and literature values. Soft tissue simulation could be achieved with agarose gels in combination with a gadolinium-based contrast agent and NaF to simulate muscle, prostate, and tumor tissues. Vegetable oils were shown to be a good representation for adipose tissue in all modalities. Inner bone was realized using a mixture of Vaseline and K2HPO4, resulting in both a fatty bone marrow signal in MRI and inhomogeneous areas of low and high attenuation in CT. The high attenuation of outer bone was additionally adapted by applying gypsum bandages to the 3D-printed hollow bone case with values up to 1200 HU. Deformable hollow organs were manufactured using silicone. Signal loss in the MR images based on the conductivity of the gels needs to be further investigated. The presented surrogates and techniques allow the customized construction of multimodality, anthropomorphic, and deformable phantoms as exemplarily shown for a pelvic phantom, which is intended to study adaptive treatment scenarios in MR-guided radiation therapy.
Mutual information-based feature selection for radiomics
NASA Astrophysics Data System (ADS)
Oubel, Estanislao; Beaumont, Hubert; Iannessi, Antoine
2016-03-01
Background The extraction and analysis of image features (radiomics) is a promising field in the precision medicine era, with applications to prognosis, prediction, and response to treatment quantification. In this work, we present a mutual information - based method for quantifying reproducibility of features, a necessary step for qualification before their inclusion in big data systems. Materials and Methods Ten patients with Non-Small Cell Lung Cancer (NSCLC) lesions were followed over time (7 time points in average) with Computed Tomography (CT). Five observers segmented lesions by using a semi-automatic method and 27 features describing shape and intensity distribution were extracted. Inter-observer reproducibility was assessed by computing the multi-information (MI) of feature changes over time, and the variability of global extrema. Results The highest MI values were obtained for volume-based features (VBF). The lesion mass (M), surface to volume ratio (SVR) and volume (V) presented statistically significant higher values of MI than the rest of features. Within the same VBF group, SVR showed also the lowest variability of extrema. The correlation coefficient (CC) of feature values was unable to make a difference between features. Conclusions MI allowed to discriminate three features (M, SVR, and V) from the rest in a statistically significant manner. This result is consistent with the order obtained when sorting features by increasing values of extrema variability. MI is a promising alternative for selecting features to be considered as surrogate biomarkers in a precision medicine context.
Fell, Shari; Bröckl, Stephanie; Büttner, Mathias; Rettinger, Anna; Zimmermann, Pia; Straubinger, Reinhard K
2016-09-15
Bovine tuberculosis (bTB), which is caused by Mycobacterium bovis and M. caprae, is a notifiable animal disease in Germany. Diagnostic procedure is based on a prescribed protocol that is published in the framework of German bTB legislation. In this protocol small sample volumes are used for DNA extraction followed by real-time PCR analyses. As mycobacteria tend to concentrate in granuloma and the infected tissue in early stages of infection does not necessarily show any visible lesions, it is likely that DNA extraction from only small tissue samples (20-40 mg) of a randomly chosen spot from the organ and following PCR testing may result in false negative results. In this study two DNA extraction methods were developed to process larger sample volumes to increase the detection sensitivity of mycobacterial DNA in animal tissue. The first extraction method is based on magnetic capture, in which specific capture oligonucleotides were utilized. These nucleotides are linked to magnetic particles and capture Mycobacterium-tuberculosis-complex (MTC) DNA released from 10 to 15 g of tissue material. In a second approach remaining sediments from the magnetic capture protocol were further processed with a less complex extraction protocol that can be used in daily routine diagnostics. A total number of 100 tissue samples from 34 cattle (n = 74) and 18 red deer (n = 26) were analyzed with the developed protocols and results were compared to the prescribed protocol. All three extraction methods yield reliable results by the real-time PCR analysis. The use of larger sample volume led to a sensitivity increase of DNA detection which was shown by the decrease of Ct-values. Furthermore five samples which were tested negative or questionable by the official extraction protocol were detected positive by real time PCR when the alternative extraction methods were used. By calculating the kappa index, the three extraction protocols resulted in a moderate (0.52; protocol 1 vs 3) to almost perfect agreement (1.00; red deer sample testing with all protocols). Both new methods yielded increased detection rates for MTC DNA detection in large sample volumes and consequently improve the official diagnostic protocol.
Yohannes, Indra; Kolditz, Daniel; Langner, Oliver; Kalender, Willi A
2012-03-07
Tissue- and water-equivalent materials (TEMs) are widely used in quality assurance and calibration procedures, both in radiodiagnostics and radiotherapy. In radiotherapy, particularly, the TEMs are often used for computed tomography (CT) number calibration in treatment planning systems. However, currently available TEMs may not be very accurate in the determination of the calibration curves due to their limitation in mimicking radiation characteristics of the corresponding real tissues in both low- and high-energy ranges. Therefore, we are proposing a new formulation of TEMs using a stoichiometric analysis method to obtain TEMs for the calibration purposes. We combined the stoichiometric calibration and the basic data method to compose base materials to develop TEMs matching standard real tissues from ICRU Report 44 and 46. First, the CT numbers of six materials with known elemental compositions were measured to get constants for the stoichiometric calibration. The results of the stoichiometric calibration were used together with the basic data method to formulate new TEMs. These new TEMs were scanned to validate their CT numbers. The electron density and the stopping power calibration curves were also generated. The absolute differences of the measured CT numbers of the new TEMs were less than 4 HU for the soft tissues and less than 22 HU for the bone compared to the ICRU real tissues. Furthermore, the calculated relative electron density and electron and proton stopping powers of the new TEMs differed by less than 2% from the corresponding ICRU real tissues. The new TEMs which were formulated using the proposed technique increase the simplicity of the calibration process and preserve the accuracy of the stoichiometric calibration simultaneously.
Soules, Regis; Noguer, Emmanuel; Iuliano, Luigi; Zerbinati, Chiara; Leignadier, Julie; Rives, Arnaud; de Medina, Philippe; Silvente-Poirot, Sandrine; Poirot, Marc
2017-10-01
5,6α-epoxycholesterol (5,6α-EC) and 5,6β-epoxycholesterol (5,6β-EC) are oxysterols involved in the anticancer pharmacology of the widely used antitumor drug tamoxifen. They are both metabolized into cholestane-3β,5α,6β-triol (CT) by the cholesterol-5,6-epoxide hydrolase (ChEH) enzyme, and CT is metabolized by an as-yet uncharacterized enzyme into 6-oxo-cholestan-3β,5α-diol (OCDO). A recent feasibility study showed that the 5,6-ECs may represent surrogate markers of tamoxifen activity in breast cancer patients undergoing endocrine therapy, thus there is a growing interest in their accurate quantification. These oxysterols are usually quantified by gas-liquid chromatography coupled to mass spectrometry (GC/MS), using an isotope dilution methodology with the corresponding deuterated oxysterol. This method is considered to be relative quantitative since all of the standards used are deuterated oxysterols, however it is not known whether the preparation of each oxysterol is affected in the same way by the extraction, pre-purification by solid phase extraction (SPE) and trimethylsilylation steps, particularly when using biological samples that contain many other reactive compounds. Thus, in this study we investigated the yield of the 5,6-ECs, CT and OCDO recovery from patient serum samples at different stages of their work-up and trimethylsilylation prior to GC/MS analysis, using [ 14 C]-labeled analogs to follow these oxysterols at each step. We measured a 40 to 60% loss of material for the 5,6-ECs and OCDO, however we also describe the conditions that improved their recovery. Our data also show that the use of deuterated 5,6α-EC, 5,6β-EC, CT and OCDO is an absolute requirement for their accurate quantification. Copyright © 2017 Elsevier B.V. All rights reserved.
Volume imaging NDE and serial sectioning of carbon fiber composites
NASA Astrophysics Data System (ADS)
Hakim, Issa; Schumacher, David; Sundar, Veeraraghavan; Donaldson, Steven; Creuz, Aline; Schneider, Rainer; Keller, Juergen; Browning, Charles; May, Daniel; Ras, Mohamad Abo; Meyendorf, Norbert
2018-04-01
A composite material is a combination of two or more materials with very different mechanical, thermal and electrical properties. The various forms of composite materials, due to their high material properties, are widely used as structural materials in the aviation, space, marine, automobile, and sports industries. However, some defects like voids, delamination, or inhomogeneous fiber distribution that form during the fabricating processes of composites can seriously affect the mechanical properties of the composite material. In this study, several imaging NDE techniques such as: thermography, high frequency eddy current, ultrasonic, x-ray radiography, x-ray laminography, and high resolution x-ray CT were conducted to characterize the microstructure of carbon fiber composites. Then, a 3D analysis was implemented by the destructive technique of serial sectioning for the same sample tested by the NDE methods. To better analyze the results of this work and extract a clear volume image for all features and defects contained in the composite material, an intensive comparison was conducted among hundreds of 3D-NDE and multi serial sections' scan images showing the microstructure variation.
Automated extraction of radiation dose information from CT dose report images.
Li, Xinhua; Zhang, Da; Liu, Bob
2011-06-01
The purpose of this article is to describe the development of an automated tool for retrieving texts from CT dose report images. Optical character recognition was adopted to perform text recognitions of CT dose report images. The developed tool is able to automate the process of analyzing multiple CT examinations, including text recognition, parsing, error correction, and exporting data to spreadsheets. The results were precise for total dose-length product (DLP) and were about 95% accurate for CT dose index and DLP of scanned series.
NASA Astrophysics Data System (ADS)
He, Dianning; Zamora, Marta; Oto, Aytekin; Karczmar, Gregory S.; Fan, Xiaobing
2017-09-01
Differences between region-of-interest (ROI) and pixel-by-pixel analysis of dynamic contrast enhanced (DCE) MRI data were investigated in this study with computer simulations and pre-clinical experiments. ROIs were simulated with 10, 50, 100, 200, 400, and 800 different pixels. For each pixel, a contrast agent concentration as a function of time, C(t), was calculated using the Tofts DCE-MRI model with randomly generated physiological parameters (K trans and v e) and the Parker population arterial input function. The average C(t) for each ROI was calculated and then K trans and v e for the ROI was extracted. The simulations were run 100 times for each ROI with new K trans and v e generated. In addition, white Gaussian noise was added to C(t) with 3, 6, and 12 dB signal-to-noise ratios to each C(t). For pre-clinical experiments, Copenhagen rats (n = 6) with implanted prostate tumors in the hind limb were used in this study. The DCE-MRI data were acquired with a temporal resolution of ~5 s in a 4.7 T animal scanner, before, during, and after a bolus injection (<5 s) of Gd-DTPA for a total imaging duration of ~10 min. K trans and v e were calculated in two ways: (i) by fitting C(t) for each pixel, and then averaging the pixel values over the entire ROI, and (ii) by averaging C(t) over the entire ROI, and then fitting averaged C(t) to extract K trans and v e. The simulation results showed that in heterogeneous ROIs, the pixel-by-pixel averaged K trans was ~25% to ~50% larger (p < 0.01) than the ROI-averaged K trans. At higher noise levels, the pixel-averaged K trans was greater than the ‘true’ K trans, but the ROI-averaged K trans was lower than the ‘true’ K trans. The ROI-averaged K trans was closer to the true K trans than pixel-averaged K trans for high noise levels. In pre-clinical experiments, the pixel-by-pixel averaged K trans was ~15% larger than the ROI-averaged K trans. Overall, with the Tofts model, the extracted physiological parameters from the pixel-by-pixel averages were larger than the ROI averages. These differences were dependent on the heterogeneity of the ROI.
Dias, Denise Costa; Cassiani, Silvia Helena De Bortoli
2003-01-01
This investigation focused on a learning environment via internet, through which Intravenous Therapy (IVT) was taught. Due to its complexity, Intravenous Therapy was chosen against numerous subjects to be taught through an e-learning environment, by comprising both technical procedures and conceptual aspects that can be discussed through a virtual learning environment. The objectives of this study were to develop educational material about Intravenous Therapy to guide students through the learning related to intravenous therapy, to have the related educational material evaluated by experts, and to evaluate the students' use of this material, considering difficulties and/or advantages, participation/interaction in this environment, and usability of its tools. The interface used for the internet-based training program was WebCT.
Lung lobe segmentation based on statistical atlas and graph cuts
NASA Astrophysics Data System (ADS)
Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku
2012-03-01
This paper presents a novel method that can extract lung lobes by utilizing probability atlas and multilabel graph cuts. Information about pulmonary structures plays very important role for decision of the treatment strategy and surgical planning. The human lungs are divided into five anatomical regions, the lung lobes. Precise segmentation and recognition of lung lobes are indispensable tasks in computer aided diagnosis systems and computer aided surgery systems. A lot of methods for lung lobe segmentation are proposed. However, these methods only target the normal cases. Therefore, these methods cannot extract the lung lobes in abnormal cases, such as COPD cases. To extract lung lobes in abnormal cases, this paper propose a lung lobe segmentation method based on probability atlas of lobe location and multilabel graph cuts. The process consists of three components; normalization based on the patient's physique, probability atlas generation, and segmentation based on graph cuts. We apply this method to six cases of chest CT images including COPD cases. Jaccard index was 79.1%.
Efficient Skeletonization of Volumetric Objects.
Zhou, Yong; Toga, Arthur W
1999-07-01
Skeletonization promises to become a powerful tool for compact shape description, path planning, and other applications. However, current techniques can seldom efficiently process real, complicated 3D data sets, such as MRI and CT data of human organs. In this paper, we present an efficient voxel-coding based algorithm for Skeletonization of 3D voxelized objects. The skeletons are interpreted as connected centerlines. consisting of sequences of medial points of consecutive clusters. These centerlines are initially extracted as paths of voxels, followed by medial point replacement, refinement, smoothness, and connection operations. The voxel-coding techniques have been proposed for each of these operations in a uniform and systematic fashion. In addition to preserving basic connectivity and centeredness, the algorithm is characterized by straightforward computation, no sensitivity to object boundary complexity, explicit extraction of ready-to-parameterize and branch-controlled skeletons, and efficient object hole detection. These issues are rarely discussed in traditional methods. A range of 3D medical MRI and CT data sets were used for testing the algorithm, demonstrating its utility.
Preliminary experiments on pharmacokinetic diffuse fluorescence tomography of CT-scanning mode
NASA Astrophysics Data System (ADS)
Zhang, Yanqi; Wang, Xin; Yin, Guoyan; Li, Jiao; Zhou, Zhongxing; Zhao, Huijuan; Gao, Feng; Zhang, Limin
2016-10-01
In vivo tomographic imaging of the fluorescence pharmacokinetic parameters in tissues can provide additional specific and quantitative physiological and pathological information to that of fluorescence concentration. This modality normally requires a highly-sensitive diffuse fluorescence tomography (DFT) working in dynamic way to finally extract the pharmacokinetic parameters from the measured pharmacokinetics-associated temporally-varying boundary intensity. This paper is devoted to preliminary experimental validation of our proposed direct reconstruction scheme of instantaneous sampling based pharmacokinetic-DFT: A highly-sensitive DFT system of CT-scanning mode working with parallel four photomultiplier-tube photon-counting channels is developed to generate an instantaneous sampling dataset; A direct reconstruction scheme then extracts images of the pharmacokinetic parameters using the adaptive-EKF strategy. We design a dynamic phantom that can simulate the agent metabolism in living tissue. The results of the dynamic phantom experiments verify the validity of the experiment system and reconstruction algorithms, and demonstrate that system provides good resolution, high sensitivity and quantitativeness at different pump speed.
Estimating local noise power spectrum from a few FBP-reconstructed CT scans
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zeng, Rongping, E-mail: rongping.zeng@fda.hhs.gov; Gavrielides, Marios A.; Petrick, Nicholas
Purpose: Traditional ways to estimate 2D CT noise power spectrum (NPS) involve an ensemble average of the power spectrums of many noisy scans. When only a few scans are available, regions of interest are often extracted from different locations to obtain sufficient samples to estimate the NPS. Using image samples from different locations ignores the nonstationarity of CT noise and thus cannot accurately characterize its local properties. The purpose of this work is to develop a method to estimate local NPS using only a few fan-beam CT scans. Methods: As a result of FBP reconstruction, the CT NPS has themore » same radial profile shape for all projection angles, with the magnitude varying with the noise level in the raw data measurement. This allows a 2D CT NPS to be factored into products of a 1D angular and a 1D radial function in polar coordinates. The polar separability of CT NPS greatly reduces the data requirement for estimating the NPS. The authors use this property and derive a radial NPS estimation method: in brief, the radial profile shape is estimated from a traditional NPS based on image samples extracted at multiple locations. The amplitudes are estimated by fitting the traditional local NPS to the estimated radial profile shape. The estimated radial profile shape and amplitudes are then combined to form a final estimate of the local NPS. We evaluate the accuracy of the radial NPS method and compared it to traditional NPS methods in terms of normalized mean squared error (NMSE) and signal detectability index. Results: For both simulated and real CT data sets, the local NPS estimated with no more than six scans using the radial NPS method was very close to the reference NPS, according to the metrics of NMSE and detectability index. Even with only two scans, the radial NPS method was able to achieve a fairly good accuracy. Compared to those estimated using traditional NPS methods, the accuracy improvement was substantial when a few scans were available. Conclusions: The radial NPS method was shown to be accurate and efficient in estimating the local NPS of FBP-reconstructed 2D CT images. It presents strong advantages over traditional NPS methods when the number of scans is limited and can be extended to estimate the in-plane NPS of cone-beam CT and multislice helical CT scans.« less
Sethi, Gaurav; Saini, B S
2015-12-01
This paper presents an abdomen disease diagnostic system based on the flexi-scale curvelet transform, which uses different optimal scales for extracting features from computed tomography (CT) images. To optimize the scale of the flexi-scale curvelet transform, we propose an improved genetic algorithm. The conventional genetic algorithm assumes that fit parents will likely produce the healthiest offspring that leads to the least fit parents accumulating at the bottom of the population, reducing the fitness of subsequent populations and delaying the optimal solution search. In our improved genetic algorithm, combining the chromosomes of a low-fitness and a high-fitness individual increases the probability of producing high-fitness offspring. Thereby, all of the least fit parent chromosomes are combined with high fit parent to produce offspring for the next population. In this way, the leftover weak chromosomes cannot damage the fitness of subsequent populations. To further facilitate the search for the optimal solution, our improved genetic algorithm adopts modified elitism. The proposed method was applied to 120 CT abdominal images; 30 images each of normal subjects, cysts, tumors and stones. The features extracted by the flexi-scale curvelet transform were more discriminative than conventional methods, demonstrating the potential of our method as a diagnostic tool for abdomen diseases.
Texture-based segmentation and analysis of emphysema depicted on CT images
NASA Astrophysics Data System (ADS)
Tan, Jun; Zheng, Bin; Wang, Xingwei; Lederman, Dror; Pu, Jiantao; Sciurba, Frank C.; Gur, David; Leader, J. Ken
2011-03-01
In this study we present a texture-based method of emphysema segmentation depicted on CT examination consisting of two steps. Step 1, a fractal dimension based texture feature extraction is used to initially detect base regions of emphysema. A threshold is applied to the texture result image to obtain initial base regions. Step 2, the base regions are evaluated pixel-by-pixel using a method that considers the variance change incurred by adding a pixel to the base in an effort to refine the boundary of the base regions. Visual inspection revealed a reasonable segmentation of the emphysema regions. There was a strong correlation between lung function (FEV1%, FEV1/FVC, and DLCO%) and fraction of emphysema computed using the texture based method, which were -0.433, -.629, and -0.527, respectively. The texture-based method produced more homogeneous emphysematous regions compared to simple thresholding, especially for large bulla, which can appear as speckled regions in the threshold approach. In the texture-based method, single isolated pixels may be considered as emphysema only if neighboring pixels meet certain criteria, which support the idea that single isolated pixels may not be sufficient evidence that emphysema is present. One of the strength of our complex texture-based approach to emphysema segmentation is that it goes beyond existing approaches that typically extract a single or groups texture features and individually analyze the features. We focus on first identifying potential regions of emphysema and then refining the boundary of the detected regions based on texture patterns.
Mittal, Neelam; Jain, Jyoti
2014-01-01
The purpose of this study was to evaluate the efficacy of nickel-titanium rotary retreatment systems versus stainless steel hand retreatment system with or without solvent for gutta-percha removal during retreatment. Sixty extracted human mandibular molar teeth with single canal in a distal root was prepared with ProTaper rotary nickel-titanium files and obturated with gutta-percha and sealer. The teeth were randomly divided into six groups of 10 specimens in each groups. The volume of filling material before and after retreatment were evaluated in cm(3) using the computed tomography (CT) scanner proprietary software. Maximum amount of filling material removed during retreatment with ProTaper retreatment system with solvent and minimum with hand retreatment system with solvent. None of the technique was 100% effective in removing the filling materials, but the ProTaper retreatment system with solvent was better.
Calibration free beam hardening correction for cardiac CT perfusion imaging
NASA Astrophysics Data System (ADS)
Levi, Jacob; Fahmi, Rachid; Eck, Brendan L.; Fares, Anas; Wu, Hao; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.
2016-03-01
Myocardial perfusion imaging using CT (MPI-CT) and coronary CTA have the potential to make CT an ideal noninvasive gate-keeper for invasive coronary angiography. However, beam hardening artifacts (BHA) prevent accurate blood flow calculation in MPI-CT. BH Correction (BHC) methods require either energy-sensitive CT, not widely available, or typically a calibration-based method. We developed a calibration-free, automatic BHC (ABHC) method suitable for MPI-CT. The algorithm works with any BHC method and iteratively determines model parameters using proposed BHA-specific cost function. In this work, we use the polynomial BHC extended to three materials. The image is segmented into soft tissue, bone, and iodine images, based on mean HU and temporal enhancement. Forward projections of bone and iodine images are obtained, and in each iteration polynomial correction is applied. Corrections are then back projected and combined to obtain the current iteration's BHC image. This process is iterated until cost is minimized. We evaluate the algorithm on simulated and physical phantom images and on preclinical MPI-CT data. The scans were obtained on a prototype spectral detector CT (SDCT) scanner (Philips Healthcare). Mono-energetic reconstructed images were used as the reference. In the simulated phantom, BH streak artifacts were reduced from 12+/-2HU to 1+/-1HU and cupping was reduced by 81%. Similarly, in physical phantom, BH streak artifacts were reduced from 48+/-6HU to 1+/-5HU and cupping was reduced by 86%. In preclinical MPI-CT images, BHA was reduced from 28+/-6 HU to less than 4+/-4HU at peak enhancement. Results suggest that the algorithm can be used to reduce BHA in conventional CT and improve MPI-CT accuracy.
Sun, Z; Al Ghamdi, KS; Baroum, IH
2012-01-01
Purpose: To investigate whether the multislice CT scanning protocols of head, chest and abdomen are adjusted according to patient’s age in paediatric patients. Materials and Methods: Multislice CT examination records of paediatric patients undergoing head, chest and abdomen scans from three public hospitals during a one-year period were retrospectively reviewed. Patients were categorised into the following age groups: under 4 years, 5–8 years, 9–12 years and 13–16 years, while the tube current was classified into the following ranges: < 49 mA, 50–99 mA, 100–149 mA, 150–199 mA, > 200 mA and unknown. Results: A total of 4998 patient records, comprising a combination of head, chest and abdomen CT scans, were assessed, with head CT scans representing nearly half of the total scans. Age-based adjusted CT protocols were observed in most of the scans with higher tube current setting being used with increasing age. However, a high tube current (150–199 mA) was still used in younger patients (0–8 years) undergoing head CT scans. In one hospital, CT protocols remained constant across all age groups, indicating potential overexposure to the patients. Conclusion: This analysis shows that paediatric CT scans are adjusted according to the patient’s age in most of the routine CT examinations. This indicates increased awareness regarding radiation risks associated with CT. However, high tube current settings are still used in younger patient groups, thus, optimisation of paediatric CT protocols and implementation of current guidelines, such as age-and weight-based scanning, should be recommended in daily practice. PMID:22970059
Su, Xingye; Kong, Liang; Li, Xin; Chen, Xueguo; Guo, Ming; Zou, Hanfa
2005-05-27
Biofingerprinting chromatogram analysis, which is defined as the comparison of fingerprinting chromatograms of the extract of traditional Chinese medicines (TCMs) before and after the interaction with biological systems (DNA, protein, cell, etc.), was proposed for screening and analysis of the multiple bioactive compounds in TCMs. A method of microdialysis sampling combined with high performance liquid chromatography (HPLC) was applied to the study of DNA-binding property for the extracts of TCMs. Seven compounds were found to bind to calf thymus DNA (ct-DNA) from the TCMs of Coptis chinensis Franch (Coptis), but only three ones from Phellodendron amurense Rupr. (Phellodendron) and none from Sophoraflavescens Ait. (Sophora) to bind to ct-DNA, respectively. Three of them were identified as berberine, palmatine and jatrorrhizine and their association constants (K) to ct-DNA were determined by microdialysis/HPLC. Competitive binding behaviors of them to ct-DNA were also investigated.
Optimizing spectral CT parameters for material classification tasks
NASA Astrophysics Data System (ADS)
Rigie, D. S.; La Rivière, P. J.
2016-06-01
In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies.
Optimizing Spectral CT Parameters for Material Classification Tasks
Rigie, D. S.; La Rivière, P. J.
2017-01-01
In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies. PMID:27227430
DOE Office of Scientific and Technical Information (OSTI.GOV)
Paul, Jijo; Yang, Cungeng; Wu, Hui
Purpose: To investigate early tumor and normal tissue responses during the course of radiation therapy (RT) for lung cancer using quantitative analysis of daily computed tomography (CT) scans. Methods and Materials: Daily diagnostic-quality CT scans acquired using CT-on-rails during CT-guided RT for 20 lung cancer patients were quantitatively analyzed. On each daily CT set, the contours of the gross tumor volume (GTV) and lungs were generated and the radiation dose delivered was reconstructed. The changes in CT image intensity (Hounsfield unit [HU]) features in the GTV and the multiple normal lung tissue shells around the GTV were extracted from themore » daily CT scans. The associations between the changes in the mean HUs, GTV, accumulated dose during RT delivery, and patient survival rate were analyzed. Results: During the RT course, radiation can induce substantial changes in the HU histogram features on the daily CT scans, with reductions in the GTV mean HUs (dH) observed in the range of 11 to 48 HU (median 30). The dH is statistically related to the accumulated GTV dose (R{sup 2} > 0.99) and correlates weakly with the change in GTV (R{sup 2} = 0.3481). Statistically significant increases in patient survival rates (P=.038) were observed for patients with a higher dH in the GTV. In the normal lung, the 4 regions proximal to the GTV showed statistically significant (P<.001) HU reductions from the first to last fraction. Conclusion: Quantitative analysis of the daily CT scans indicated that the mean HUs in lung tumor and surrounding normal tissue were reduced during RT delivery. This reduction was observed in the early phase of the treatment, is patient specific, and correlated with the delivered dose. A larger HU reduction in the GTV correlated significantly with greater patient survival. The changes in daily CT features, such as the mean HU, can be used for early assessment of the radiation response during RT delivery for lung cancer.« less
Variability of protein content in calcium oxalate monohydrate stones.
Williams, James C; Zarse, Chad A; Jackson, Molly E; Witzmann, Frank A; McAteer, James A
2006-08-01
Urinary stones are heterogeneous in their fragility to lithotripter shockwaves. As a first step in gaining a better understanding of the role of matrix in stone fragility, we measured extractible protein in calcium oxalate monohydrate (COM) stones that were extensively characterized by micro-computed tomography (micro CT). Stones were scanned using micro CT (Scanco mCT20, 34 microm). They were ground, and the protein extracted using four methods: 0.25M EDTA, 2% SDS reducing buffer, 9M urea buffer, and 10% acetic acid. Protein was measured using NanoOrange. The SDS extracts were also examined using polyacrylamide electrophoresis (PAGE). Extracted protein was highest with the SDS or urea methods (0.28% +/- 0.13% and 0.24% +/- 0.11%, respectively) and lower using the EDTA method (0.17% +/- 0.05%; P < 0.02). Acetic acid extracted little protein (0.006 +/- 0.002%; P < 0.001). Individual stones were significantly different in extractability of protein by the different methods, and SDS-PAGE revealed different protein patterns for individual stones. Extracted protein did not correlate with X-ray-lucent void percentage, which ranged from 0.06% to 2.8% of stone volume, or with apatite content. Extractible stone-matrix protein differs for individual COM stones, and yield is dependent on the extraction method. The presence of X-ray-lucent voids or minor amounts of apatite in stones did not correlate with protein content. The amounts of protein recovered were much lower than reported by Boyce, showing that these methods extracted only a fraction of the protein bound up in the stones. The results suggest that none of the methods tested will be useful for helping to answer the question of whether matrix content differs among stones of differing fragility to lithotripter shockwaves.
Accurate airway segmentation based on intensity structure analysis and graph-cut
NASA Astrophysics Data System (ADS)
Meng, Qier; Kitsaka, Takayuki; Nimura, Yukitaka; Oda, Masahiro; Mori, Kensaku
2016-03-01
This paper presents a novel airway segmentation method based on intensity structure analysis and graph-cut. Airway segmentation is an important step in analyzing chest CT volumes for computerized lung cancer detection, emphysema diagnosis, asthma diagnosis, and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3-D airway tree structure from a CT volume is quite challenging. Several researchers have proposed automated algorithms basically based on region growing and machine learning techniques. However these methods failed to detect the peripheral bronchi branches. They caused a large amount of leakage. This paper presents a novel approach that permits more accurate extraction of complex bronchial airway region. Our method are composed of three steps. First, the Hessian analysis is utilized for enhancing the line-like structure in CT volumes, then a multiscale cavity-enhancement filter is employed to detect the cavity-like structure from the previous enhanced result. In the second step, we utilize the support vector machine (SVM) to construct a classifier for removing the FP regions generated. Finally, the graph-cut algorithm is utilized to connect all of the candidate voxels to form an integrated airway tree. We applied this method to sixteen cases of 3D chest CT volumes. The results showed that the branch detection rate of this method can reach about 77.7% without leaking into the lung parenchyma areas.
Halm, Brunhild M; Franke, Adrian A; Lai, Jennifer F; Li, Xingnan; Custer, Laurie J; Pagano, Ian; Cooney, Robert V; Turner, Helen C; Brenner, David J
2015-03-01
Computed tomography (CT) is an imaging modality that exposes patients to ionizing radiation (IR). We review and report findings from our pilot study evaluating whether blood markers are altered in 17 children undergoing medically indicated CT scans. Blood was drawn before ('pre-CT') and 1 hour after ('post-CT' CT scans. Plasma carotenoids, tocopherols, Q10, ascorbic acid (AA) and uric acid (UA) were analyzed by RP-HPLC with diode-array and electrochemical detection. Dehydroascorbic acid (DHAA) was calculated by subtraction from total AA. Total antioxidant capacity (TAC) was measured using the ORAC assay. Cytokines were quantified using a multiplex immunoassay. γ-H2AX foci were visualized using immunofluorescence. Mean pre- and post-CT changes were compared using t-tests; P-levels < .05 indicated significance. All major plasma lipid soluble antioxidant levels were lower post- vs pre-CT (P < .05) possibly from the scavenging of free radicals formed by CT-induced IR. Average AA levels increased (134%) while DHAA levels were decreased (29%) post-CT, probably due to intracellular recycling of AA from DHAA. TAC levels in lipophilic and hydrophilic extracts were unchanged, suggesting that other antioxidants may have assisted in free radical quenching, which would corroborate their lower concentrations post-CT. Cytokine levels were unchanged and dose-dependent increases in γ-H2AX foci, a measure of double strand DNA breaks, were observed (P = .046, n = 3 children). Our results suggest that CT-derived IR can influence the antioxidant system and may elicit detrimental responses on the cellular level of young children. When possible and if appropriate non-IR based techniques such as ultrasound or magnetic resonance imaging should be used.
Co-distribution of cysteine cathepsins and matrix metalloproteases in human dentin.
Scaffa, Polliana Mendes Candia; Breschi, Lorenzo; Mazzoni, Annalisa; Vidal, Cristina de Mattos Pimenta; Curci, Rosa; Apolonio, Fabianni; Gobbi, Pietro; Pashley, David; Tjäderhane, Leo; Tersariol, Ivarne Luis Dos Santos; Nascimento, Fábio Dupart; Carrilho, Marcela Rocha
2017-02-01
It has been hypothesized that cysteine cathepsins (CTs) along with matrix metalloproteases (MMPs) may work in conjunction in the proteolysis of mature dentin matrix. The aim of this study was to verify simultaneously the distribution and presence of cathepsins B (CT-B) and K (CT-K) in partially demineralized dentin; and further to evaluate the activity of CTs and MMPs in the same tissue. The distribution of CT-B and CT-K in sound human dentin was assessed by immunohistochemistry. A double-immunolabeling technique was used to identify, at once, the occurrence of those enzymes in dentin. Activities of CTs and MMPs in dentin extracts were evaluated spectrofluorometrically. In addition, in situ gelatinolytic activity of dentin was assayed by zymography. The results revealed the distribution of CT-B and CT-K along the dentin organic matrix and also indicated co-occurrence of MMPs and CTs in that tissue. The enzyme kinetics studies showed proteolytic activity in dentin extracts for both classes of proteases. Furthermore, it was observed that, at least for sound human dentin matrices, the activity of MMPs seems to be predominant over the CTs one. Copyright © 2016 Elsevier Ltd. All rights reserved.
Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM).
Gao, Hao; Yu, Hengyong; Osher, Stanley; Wang, Ge
2011-11-01
We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations.
Pan, W R; Rozen, W M; Stretch, J; Thierry, B; Ashton, M W; Corlett, R J
2008-09-01
Lymphatic anatomy has become increasingly clinically important as surgical techniques evolve for investigating and treating cancer metastases. However, due to limited anatomical techniques available, research in this field has been insufficient. The techniques of computed tomography (CT) and magnetic resonance (MR) lymphangiography have not been described previously in the imaging of cadaveric lymphatic anatomy. This preliminary work describes the feasibility of these advanced imaging technologies for imaging lymphatic anatomy. A single, fresh cadaveric lower limb underwent lymphatic dissection and cannulation utilizing microsurgical techniques. Contrast materials for both CT and MR studies were chosen based on their suitability for subsequent clinical use, and imaging was undertaken with a view to mapping lymphatic anatomy. Microdissection studies were compared with imaging findings in each case. Both MR-based and CT-based contrast media in current clinical use were found to be suitable for demonstrating cadaveric lymphatic anatomy upon direct intralymphatic injection. MR lymphangiography and CT lymphangiography are feasible modalities for cadaveric anatomical research for lymphatic anatomy. Future studies including refinements in scanning techniques may offer these technologies to the clinical setting.
MRI and CT contrast media extravasation
Heshmatzadeh Behzadi, Ashkan; Farooq, Zerwa; Newhouse, Jeffery H.; Prince, Martin R.
2018-01-01
Abstract Background: This systematic review combines data from multiple papers on contrast media extravasation to identify factors contributing to increased extravasation risk. Methods: Data were extracted from 17 papers reporting 2191 extravasations in 1,104,872 patients (0.2%) undergoing computed tomography (CT) or magnetic resonance imaging (MRI). Results: Extravasation rates were 0.045% for gadolinium-based contrast agents (GBCA) and nearly 6-fold higher, 0.26% for iodinated contrast agents. Factors associated with increased contrast media extravasations included: older age, female gender, using an existing intravenous (IV) instead of placing a new IV in radiology, in-patient status, use of automated power injection, high injection rates, catheter location, and failing to warm up the more viscous contrast media to body temperature. Conclusion: Contrast media extravasation is infrequent but nearly 6 times less frequent with GBCA for MRI compared with iodinated contrast used in CT. PMID:29489663
Real-time fusion of endoscopic views with dynamic 3-D cardiac images: a phantom study.
Szpala, Stanislaw; Wierzbicki, Marcin; Guiraudon, Gerard; Peters, Terry M
2005-09-01
Minimally invasive robotically assisted cardiac surgical systems currently do not routinely employ 3-D image guidance. However, preoperative magnetic resonance and computed tomography (CT) images have the potential to be used in this role, if appropriately registered with the patient anatomy and animated synchronously with the motion of the actual heart. This paper discusses the fusion of optical images of a beating heart phantom obtained from an optically tracked endoscope, with volumetric images of the phantom created from a dynamic CT dataset. High quality preoperative dynamic CT images are created by first extracting the motion parameters of the heart from the series of temporal frames, and then applying this information to animate a high-quality heart image acquired at end systole. Temporal synchronization of the endoscopic and CT model is achieved by selecting the appropriate CT image from the dynamic set, based on an electrocardiographic trigger signal. The spatial error between the optical and virtual images is 1.4 +/- 1.1 mm, while the time discrepancy is typically 50-100 ms. Index Terms-Image guidance, image warping, minimally invasive cardiac surgery, virtual endoscopy, virtual reality.
Uzgur, Recep; Ercan, Ertuğrul; Uzgur, Zeynep; Çolak, Hakan; Yalçın, Muhammet; Özcan, Mutlu
2016-08-12
To evaluate the marginal and internal cement thicknesses of inlay restorations made of various CAD/CAM materials using 3D X-ray micro-computed tomography (micro-CT) technique. Caries-free extracted mandibular molars (N = 30) with similar size were randomly assigned to three groups (N = 10 per group). Mesio-occlusal-distal (MOD) cavities were prepared, and inlay restorations were obtained by milling out CAD/CAM materials namely, (a) IPS: monolithic lithium disilicate (control), (b) VE: polymer-infiltrated ceramic, and (c) CS: nano-ceramic using a CAM unit. Marginal and internal cement thicknesses were measured using 3D micro-CT. Data were analyzed using 1-way ANOVA and Tukey's tests (alpha = 0.05). The mean marginal and internal cement thickness were not significant in all inlay materials (p > 0.05). Mean marginal cement thickness (μm) was the lowest for the IPS group (67.54 ± 10.16) followed by VE (84.09 ± 3.94) and CS (95.18 ± 10.58) (p > 0.05). The internal cement thickness (μm) was the lowest in the CS group (54.85 ± 6.94) followed by IPS (60.58 ± 9.22) and VE (77.53 ± 12.13) (p > 0.05). Marginal and internal cement thicknesses of MOD inlays made of monolithic lithium disilicate, polymer-infiltrated ceramic, and nano-ceramic CAD/CAM materials were similar and all less than 100 μm, which could be considered clinically acceptable. MOD inlays made of different CAD/CAM materials presented similar cement thickness, less than 100 μm. © 2016 by the American College of Prosthodontists.
Bair, Ryan J.; Bair, Eric; Viswanathan, Akila N.
2016-01-01
PURPOSE We assessed a novel Food and Drug Administration–approved hydrogel, synthesized as absorbable iodinated particles, in gynecologic-cancer patients undergoing computed tomography (CT) or magnetic resonance (MR) based brachytherapy after external beam radiation. METHODS AND MATERIALS Nineteen patients underwent CT-guided (n = 13) or MR-guided (n = 6) brachytherapy for gynecologic cancers. Seventy-seven hydrogel injections were placed. The hydrogel material was injected into gross residual disease and/or key anatomic landmarks in amounts ranging from 0.1 to 0.4 mL. The visibility of the tracer was scored on CT and on MR images using a 5-point scoring scale. A Cohen’s kappa statistic was calculated to assess interobserver agreement. To assess the unadjusted effects of baseline parameters on hydrogel visibility, we modeled visibility using a linear mixed-effect model. RESULTS Injections were without complication. The kappa statistic was 0.77 (95% confidence interval [CI], 0.68–0.87). The volume of hydrogel injected was significantly associated with visibility on both CT (p = 0.032) and magnetic resonance imaging (p = 0.016). We analyzed visibility by location, controlling for amount. A 0.1-cc increase in volume injected was associated with increases of 0.54 (95% CI = 0.05–1.03) in the CT visibility score and 0.83 (95% CI = 0.17–1.49) in the MR visibility score. Injection of 0.4 cc or more was required for unequivocal visibility on CT or MR. No statistically significant correlation was found between tumor type, tumor location, or anatomical location of injection and visibility on either CT or magnetic resonance imaging. CONCLUSIONS In this first report of an injectable radiopaque hydrogel, targets were visualized to assist with three-dimensional–based brachytherapy in gynecologic malignancies. This marker has potential for several applications, is easy to inject and visualize, and caused no acute complications. PMID:26481393
Dillman, Jonathan R.; Goodsitt, Mitchell M.; Christodoulou, Emmanuel G.; Keshavarzi, Nahid; Strouse, Peter J.
2014-01-01
Purpose To retrospectively compare image quality and radiation dose between a reduced-dose computed tomographic (CT) protocol that uses model-based iterative reconstruction (MBIR) and a standard-dose CT protocol that uses 30% adaptive statistical iterative reconstruction (ASIR) with filtered back projection. Materials and Methods Institutional review board approval was obtained. Clinical CT images of the chest, abdomen, and pelvis obtained with a reduced-dose protocol were identified. Images were reconstructed with two algorithms: MBIR and 100% ASIR. All subjects had undergone standard-dose CT within the prior year, and the images were reconstructed with 30% ASIR. Reduced- and standard-dose images were evaluated objectively and subjectively. Reduced-dose images were evaluated for lesion detectability. Spatial resolution was assessed in a phantom. Radiation dose was estimated by using volumetric CT dose index (CTDIvol) and calculated size-specific dose estimates (SSDE). A combination of descriptive statistics, analysis of variance, and t tests was used for statistical analysis. Results In the 25 patients who underwent the reduced-dose protocol, mean decrease in CTDIvol was 46% (range, 19%–65%) and mean decrease in SSDE was 44% (range, 19%–64%). Reduced-dose MBIR images had less noise (P > .004). Spatial resolution was superior for reduced-dose MBIR images. Reduced-dose MBIR images were equivalent to standard-dose images for lungs and soft tissues (P > .05) but were inferior for bones (P = .004). Reduced-dose 100% ASIR images were inferior for soft tissues (P < .002), lungs (P < .001), and bones (P < .001). By using the same reduced-dose acquisition, lesion detectability was better (38% [32 of 84 rated lesions]) or the same (62% [52 of 84 rated lesions]) with MBIR as compared with 100% ASIR. Conclusion CT performed with a reduced-dose protocol and MBIR is feasible in the pediatric population, and it maintains diagnostic quality. © RSNA, 2013 Online supplemental material is available for this article. PMID:24091359
Shen, Chenyang; Li, Bin; Chen, Liyuan; Yang, Ming; Lou, Yifei; Jia, Xun
2018-04-01
Accurate calculation of proton stopping power ratio (SPR) relative to water is crucial to proton therapy treatment planning, since SPR affects prediction of beam range. Current standard practice derives SPR using a single CT scan. Recent studies showed that dual-energy CT (DECT) offers advantages to accurately determine SPR. One method to further improve accuracy is to incorporate prior knowledge on human tissue composition through a dictionary approach. In addition, it is also suggested that using CT images with multiple (more than two) energy channels, i.e., multi-energy CT (MECT), can further improve accuracy. In this paper, we proposed a sparse dictionary-based method to convert CT numbers of DECT or MECT to elemental composition (EC) and relative electron density (rED) for SPR computation. A dictionary was constructed to include materials generated based on human tissues of known compositions. For a voxel with CT numbers of different energy channels, its EC and rED are determined subject to a constraint that the resulting EC is a linear non-negative combination of only a few tissues in the dictionary. We formulated this as a non-convex optimization problem. A novel algorithm was designed to solve the problem. The proposed method has a unified structure to handle both DECT and MECT with different number of channels. We tested our method in both simulation and experimental studies. Average errors of SPR in experimental studies were 0.70% in DECT, 0.53% in MECT with three energy channels, and 0.45% in MECT with four channels. We also studied the impact of parameter values and established appropriate parameter values for our method. The proposed method can accurately calculate SPR using DECT and MECT. The results suggest that using more energy channels may improve the SPR estimation accuracy. © 2018 American Association of Physicists in Medicine.
Sun, Peng; Wang, Ting; Chen, Lu; Yu, Bang-wei; Jia, Qi; Chen, Kai-xian; Fan, Hui-min; Li, Yi-ming; Wang, He-yao
2016-01-01
Aim: Cinnamon extracts rich in procyanidin oligomers have shown to improve pancreatic β-cell function in diabetic db/db mice. The aim of this study was to identify the active compounds in extracts from two species of cinnamon responsible for the pancreatic β-cell protection in vitro. Methods: Cinnamon extracts were prepared from Cinnamomum tamala (CT-E) and Cinnamomum cassia (CC-E). Six compounds procyanidin B2 (cpd1), (−)-epicatechin (cpd2), cinnamtannin B1 (cpd3), procyanidin C1 (cpd4), parameritannin A1 (cpd5) and cinnamtannin D1 (cpd6) were isolated from the extracts. INS-1 pancreatic β-cells were exposed to palmitic acid (PA) or H2O2 to induce lipotoxicity and oxidative stress. Cell viability and apoptosis as well as ROS levels were assessed. Glucose-stimulated insulin secretion was examined in PA-treated β-cells and murine islets. Results: CT-E, CC-E as well as the compounds, except cpd5, did not cause cytotoxicity in the β-cells up to the maximum dosage using in this experiment. CT-E and CC-E (12.5–50 μg/mL) dose-dependently increased cell viability in both PA- and H2O2-treated β-cells, and decreased ROS accumulation in H2O2-treated β-cells. CT-E caused more prominent β-cell protection than CC-E. Furthermore, CT-E (25 and 50 μg/mL) dose-dependently increased glucose-stimulated insulin secretion in PA-treated β-cells and murine islets, but CC-E had little effect. Among the 6 compounds, trimer procyanidins cpd3, cpd4 and cpd6 (12.5–50 μmol/L) dose-dependently increased the cell viability and decreased ROS accumulation in H2O2-treated β-cells. The trimer procyanidins also increased glucose-stimulated insulin secretion in PA-treated β-cells. Conclusion: Trimer procyanidins in the cinnamon extracts contribute to the pancreatic β-cell protection, thus to the anti-diabetic activity. PMID:27238208
Harms, Hendrik Johannes; Tolbod, Lars Poulsen; Hansson, Nils Henrik Stubkjær; Kero, Tanja; Orndahl, Lovisa Holm; Kim, Won Yong; Bjerner, Tomas; Bouchelouche, Kirsten; Wiggers, Henrik; Frøkiær, Jørgen; Sörensen, Jens
2015-12-01
The aim of this study was to develop and validate an automated method for extracting forward stroke volume (FSV) using indicator dilution theory directly from dynamic positron emission tomography (PET) studies for two different tracers and scanners. 35 subjects underwent a dynamic (11)C-acetate PET scan on a Siemens Biograph TruePoint-64 PET/CT (scanner I). In addition, 10 subjects underwent both dynamic (15)O-water PET and (11)C-acetate PET scans on a GE Discovery-ST PET/CT (scanner II). The left ventricular (LV)-aortic time-activity curve (TAC) was extracted automatically from PET data using cluster analysis. The first-pass peak was isolated by automatic extrapolation of the downslope of the TAC. FSV was calculated as the injected dose divided by the product of heart rate and the area under the curve of the first-pass peak. Gold standard FSV was measured using phase-contrast cardiovascular magnetic resonance (CMR). FSVPET correlated highly with FSVCMR (r = 0.87, slope = 0.90 for scanner I, r = 0.87, slope = 1.65, and r = 0.85, slope = 1.69 for scanner II for (15)O-water and (11)C-acetate, respectively) although a systematic bias was observed for both scanners (p < 0.001 for all). FSV based on (11)C-acetate and (15)O-water correlated highly (r = 0.99, slope = 1.03) with no significant difference between FSV estimates (p = 0.14). FSV can be obtained automatically using dynamic PET/CT and cluster analysis. Results are almost identical for (11)C-acetate and (15)O-water. A scanner-dependent bias was observed, and a scanner calibration factor is required for multi-scanner studies. Generalization of the method to other tracers and scanners requires further validation.
Li, Ke; Bevins, Nicholas; Zambelli, Joseph; Chen, Guang-Hong
2013-02-01
Using a grating interferometer, a conventional x-ray cone beam computed tomography (CT) data acquisition system can be used to simultaneously generate both conventional absorption CT (ACT) and differential phase contrast CT (DPC-CT) images from a single data acquisition. Since the two CT images were extracted from the same set of x-ray projections, it is expected that intrinsic relationships exist between the noise properties of the two contrast mechanisms. The purpose of this paper is to investigate these relationships. First, a theoretical framework was developed using a cascaded system model analysis to investigate the relationship between the noise power spectra (NPS) of DPC-CT and ACT. Based on the derived analytical expressions of the NPS, the relationship between the spatial-frequency-dependent noise equivalent quanta (NEQ) of DPC-CT and ACT was derived. From these fundamental relationships, the NPS and NEQ of the DPC-CT system can be derived from the corresponding ACT system or vice versa. To validate these theoretical relationships, a benchtop cone beam DPC-CT/ACT system was used to experimentally measure the modulation transfer function (MTF) and NPS of both DPC-CT and ACT. The measured three-dimensional (3D) MTF and NPS were then combined to generate the corresponding 3D NEQ. Two fundamental relationships have been theoretically derived and experimentally validated for the NPS and NEQ of DPC-CT and ACT: (1) the 3D NPS of DPC-CT is quantitatively related to the corresponding 3D NPS of ACT by an inplane-only spatial-frequency-dependent factor 1∕f (2), the ratio of window functions applied to DPC-CT and ACT, and a numerical factor C(g) determined by the geometry and efficiency of the grating interferometer. Note that the frequency-dependent factor is independent of the frequency component f(z) perpendicular to the axial plane. (2) The 3D NEQ of DPC-CT is related to the corresponding 3D NEQ of ACT by an f (2) scaling factor and numerical factors that depend on both the attenuation and refraction properties of the image object, as well as C(g) and the MTF of the grating interferometer. The performance of a DPC-CT system is intrinsically related to the corresponding ACT system. As long as the NPS and NEQ of an ACT system is known, the corresponding NPS and NEQ of the DPC-CT system can be readily estimated using additional characteristics of the grating interferometer.
Herts, Brian R; Baker, Mark E; Obuchowski, Nancy; Primak, Andrew; Schneider, Erika; Rhana, Harpreet; Dong, Frank
2013-06-01
The purpose of this article is to determine the decrease in volume CT dose index (CTDI(vol)) and dose-length product (DLP) achieved by switching from fixed quality reference tube current protocols with automatic tube current modulation to protocols adjusting the quality reference tube current, slice collimation, and peak kilovoltage according to patient weight. All adult patients who underwent CT examinations of the abdomen or abdomen and pelvis during 2010 using weight-based protocols who also underwent a CT examination in 2008 or 2009 using fixed quality reference tube current protocols were identified from the radiology information system. Protocol pages were electronically retrieved, and the CT model, examination date, scan protocol, CTDI(vol), and DLP were extracted from the DICOM header or by optical character recognition. There were 15,779 scans with dose records for 2700 patients. Changes in CTDI(vol) and DLP were compared only between examinations of the same patient and same CT system model for examinations performed in 2008 or 2009 and those performed in 2010. The final analysis consisted of 1117 comparisons in 1057 patients, and 1209 comparisons in 988 patients for CTDI(vol) and DLP, respectively. The change to a weight-based protocol resulted in a statistically significant reduction in CTDI(vol) and DLP on three MDCT system models (p < 0.001). The largest average CTDI(vol) decrease was 13.9%, and the largest average DLP decrease was 16.1% on a 64-MDCT system. Both the CTDI(vol) and DLP decreased the most for patients who weighed less than 250 lb (112.5 kg). Adjusting the CT protocol by selecting parameters according to patient weight is a viable method for reducing CT radiation dose. The largest reductions occurred in the patients weighing less than 250 lb.
Chen, Xiaojian; Oshima, Kiyoko; Schott, Diane; Wu, Hui; Hall, William; Song, Yingqiu; Tao, Yalan; Li, Dingjie; Zheng, Cheng; Knechtges, Paul; Erickson, Beth; Li, X Allen
2017-01-01
In an effort for early assessment of treatment response, we investigate radiation induced changes in quantitative CT features of tumor during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. On each daily CT, the pancreatic head, the spinal cord and the aorta were delineated and the histograms of CT number (CTN) in these contours were extracted. Eight histogram-based radiomic metrics including the mean CTN (MCTN), peak position, volume, standard deviation (SD), skewness, kurtosis, energy and entropy were calculated for each fraction. Paired t-test was used to check the significance of the change of specific metric at specific time. GEE model was used to test the association between changes of metrics over time for different pathology responses. In general, CTN histogram in the pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the 1st to the 26th fraction in MCTN ranged from -15.8 to 3.9 HU with an average of -4.7 HU (p<0.001). Meanwhile the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less peaked). The changes of MCTN, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response is associated with the changes of MCTN, SD, and skewness. In cases of good response, patients tend to have large reductions in MCTN and skewness, and large increases in SD and kurtosis. Significant changes in CT radiomic features, such as the MCTN, skewness, and kurtosis in tumor were observed during the course of CRT for pancreas cancer based on quantitative analysis of daily CTs. These changes may be potentially used for early assessment of treatment response and stratification for therapeutic intensification.
da Silva, Felipe-Rodolfo-Pereira; Guimarães-Vasconcelos, Any-Carolina-Cardoso; de-Carvalho-França, Luiz-Felipe; di-Lenardo, David; Rodrigues, Luana-Silva; Barreto-do-Nascimento, Maria-Luísa-Lima
2017-01-01
Background Periodontitis results from an inflammatory response caused by accumulative microorganisms in periodontal sites. Several factors are involved in pathogenesis of periodontitis, for example the -889 C/T polymorphism in interleukin-1A gene. This study aimed to evaluate the relationship between this polymorphism and risk of development of chronic periodontitis by a meta-analysis based in new published findings. Material and Methods Thereunto a review in literature was performed in the electronic biomedical and education databases (Cochrane Library, Google Scholar, MEDLINE and PubMed) to studies published before August 2, 2015, the abstracts were evaluated and the data extraction performed by two calibrated examiners. The calculations of the meta-analysis were obtained through statistical software Review Manager version 5.2 with calculation of Odds Ratio (OR), heterogeneity (I²) and Funnel plots with P <0.05. Results In overall, twenty-one case/control studies were selected with 2,174 patients with chronic periodontitis and 1, 756 controls. The meta-analysis showed T allele was associated with chronic periodontitis (OR = 1.22, 95% CI: 1.09, 1.36, P = 0.0004) with decreased value to heterogeneity (I² = 15%, P = 0.28). TT genotype was associated to patients with chronic periodontitis (OR = 1.40, 95% CI: 1.07, 1.83, P = 0.01). No publication bias was found in this meta-analysis by asymmetry in Funnel plots. Conclusions This meta-analysis with 2,174 patients with chronic periodontitis and 1, 756 controls evidenced the -889 C/T polymorphism is associated to risk of development of chronic periodontitis with no significant value to heterogeneity to allelic evaluation. Key words:Alleles, odds ratio, periodontal disease, cytokines. PMID:27918732
Tacher, Vania; Duran, Rafael; Lin, MingDe; Sohn, Jae Ho; Sharma, Karun V.; Wang, Zhijun; Chapiro, Julius; Gacchina Johnson, Carmen; Bhagat, Nikhil; Dreher, Matthew R.; Schäfer, Dirk; Woods, David L.; Lewis, Andrew L.; Tang, Yiqing; Grass, Michael; Wood, Bradford J.
2016-01-01
Purpose To assess the visibility of radiopaque microspheres during transarterial embolization (TAE) in the VX2 rabbit liver tumor model by using multimodality imaging, including single-snapshot radiography, cone-beam computed tomography (CT), multidetector CT, and micro-CT. Materials and Methods The study was approved by the institutional animal care and use committee. Fifteen VX2-tumor-bearing rabbits were assigned to three groups depending on the type of embolic agent injected: 70–150-μm radiopaque microspheres in saline (radiopaque microsphere group), 70–150-μm radiopaque microspheres in contrast material (radiopaque microsphere plus contrast material group), and 70–150-μm radiolucent microspheres in contrast material (nonradiopaque microsphere plus contrast material group). Rabbits were imaged with single-snapshot radiography, cone-beam CT, and multidetector CT. Three to 5 weeks after sacrifice, excised livers were imaged with micro-CT and histologic analysis was performed. The visibility of the embolic agent was assessed with all modalities before and after embolization by using a qualitative three-point scale score reading study and a quantitative assessment of the signal-to-noise ratio (SNR) change in various regions of interest, including the tumor and its feeding arteries. The Kruskal-Wallis test was used to compare the rabbit characteristics across groups, and the Wilcoxon signed rank test was used to compare SNR measurements before and after embolization. Results Radiopaque microspheres were qualitatively visualized within tumor feeding arteries and targeted tissue with all imaging modalities (P < .05), and their presence was confirmed with histologic examination. SNRs of radiopaque microsphere deposition increased after TAE on multidetector CT, cone-beam CT, and micro-CT images (P < .05). Similar results were obtained when contrast material was added to radiopaque microspheres, except for additional image attenuation due to tumor enhancement. For the group with nonradiopaque microspheres and contrast material, retained tumoral contrast remained qualitatively visible with all modalities except for micro-CT, which demonstrated soluble contrast material washout over time. Conclusion Radiopaque microspheres were visible with all imaging modalities and helped increase conspicuity of the tumor as well as its feeding arteries after TAE in a rabbit VX2 liver tumor model. © RSNA, 2015 PMID:26678453
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, T; Zhu, L
Purpose: Conventional dual energy CT (DECT) reconstructs CT and basis material images from two full-size projection datasets with different energy spectra. To relax the data requirement, we propose an iterative DECT reconstruction algorithm using one full scan and a second sparse-view scan by utilizing redundant structural information of the same object acquired at two different energies. Methods: We first reconstruct a full-scan CT image using filtered-backprojection (FBP) algorithm. The material similarities of each pixel with other pixels are calculated by an exponential function about pixel value differences. We assume that the material similarities of pixels remains in the second CTmore » scan, although pixel values may vary. An iterative method is designed to reconstruct the second CT image from reduced projections. Under the data fidelity constraint, the algorithm minimizes the L2 norm of the difference between pixel value and its estimation, which is the average of other pixel values weighted by their similarities. The proposed algorithm, referred to as structure preserving iterative reconstruction (SPIR), is evaluated on physical phantoms. Results: On the Catphan600 phantom, SPIR-based DECT method with a second 10-view scan reduces the noise standard deviation of a full-scan FBP CT reconstruction by a factor of 4 with well-maintained spatial resolution, while iterative reconstruction using total-variation regularization (TVR) degrades the spatial resolution at the same noise level. The proposed method achieves less than 1% measurement difference on electron density map compared with the conventional two-full-scan DECT. On an anthropomorphic pediatric phantom, our method successfully reconstructs the complicated vertebra structures and decomposes bone and soft tissue. Conclusion: We develop an effective method to reduce the number of views and therefore data acquisition in DECT. We show that SPIR-based DECT using one full scan and a second 10-view scan can provide high-quality DECT images and accurate electron density maps as conventional two-full-scan DECT.« less
[Diagnosis of strangulated Spiegel hernia based on CT scan: about a case].
Akpo, Geraud; Deme, Hamidou; Badji, Nfally; Niang, Fallou; Toure, Mohamadou; Niang, Ibrahima; Diouf, Malick; Niang, El Hadj
2016-01-01
We report a case of a 86-year old woman with Spiegel hernia complicated by occlusion whose diagnosis was based on CT scan. She was examined in the Emergency Surgery Department for brutal onset of pain in the right iliac fossa associated with vomiting. On physical examination the patient was febrile (38.2° C). It showed hard, sensitive and mobile mass located in the right iliac fossa, with respect to both planes. Abdominal CT scan showed a hernia sac with the neck measuring 13 mm in the right iliac fossa, in front of the aponeurosis of the external oblique muscle. It contained fat and a small bowel loop (curved arrow) with two zones of transition giving a double beak-like appearance at the level of the neck. CT scan showed a lack of enhancement of the wall of the loop after administration of contrast material. The diagnosis of strangulated spiegel hernia associated with sign of arterial ischemia of the digestive wall was retained. Surgery was perfomed with simple postoperative management.
NASA Astrophysics Data System (ADS)
Vtorushina, A. N.; Nikonova, E. D.
2016-02-01
This paper deals with the urgent issue of the search of new drugs based on plant raw materials that have an influence on various stages of oxidation processes occurring in the human body. The aim of this paper is to determine the antioxidant activity of the bilberry extracts that are used in the medicine practice by a cathodic voltammetry method. We consider the influence of water and alcohol bilberry extracts on the process of oxygen electroreduction. From these extracts the most activity relation to the process of cathodic oxygen reduction showed alcohol (40%) bilberry extract. It was also stated that the alcohol extract of bilberry has a greater antioxidant activity than other known antioxidants such as ascorbic acid, glucose, dihydroquercetin. Thus, after consideration of a number of plant objects, we showed the possibility of applying the method of cathodic voltammetry for the determination of total antioxidant activity of plant material and identifying and highlighting the most perspective sources of biologically active substances (BAS), as well as the ability of identifying extractants that fully extract BAS from plant raw materials. The activity data of extracts of plant raw materials gives an opportunity of establishing an effective yield phytopreparation based on bilberry that has an antioxidant effect.
Blood vessel-based liver segmentation through the portal phase of a CT dataset
NASA Astrophysics Data System (ADS)
Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Moriyama, Noriyuki; Utsunomiya, Toru; Shimada, Mitsuo
2013-02-01
Blood vessels are dispersed throughout the human body organs and carry unique information for each person. This information can be used to delineate organ boundaries. The proposed method relies on abdominal blood vessels (ABV) to segment the liver considering the potential presence of tumors through the portal phase of a CT dataset. ABV are extracted and classified into hepatic (HBV) and nonhepatic (non-HBV) with a small number of interactions. HBV and non-HBV are used to guide an automatic segmentation of the liver. HBV are used to individually segment the core region of the liver. This region and non-HBV are used to construct a boundary surface between the liver and other organs to separate them. The core region is classified based on extracted posterior distributions of its histogram into low intensity tumor (LIT) and non-LIT core regions. Non-LIT case includes normal part of liver, HBV, and high intensity tumors if exist. Each core region is extended based on its corresponding posterior distribution. Extension is completed when it reaches either a variation in intensity or the constructed boundary surface. The method was applied to 80 datasets (30 Medical Image Computing and Computer Assisted Intervention (MICCAI) and 50 non-MICCAI data) including 60 datasets with tumors. Our results for the MICCAI-test data were evaluated by sliver07 [1] with an overall score of 79.7, which ranks seventh best on the site (December 2013). This approach seems a promising method for extraction of liver volumetry of various shapes and sizes and low intensity hepatic tumors.
Normanno, Nicola; Denis, Marc G.; Thress, Kenneth S.; Ratcliffe, Marianne; Reck, Martin
2017-01-01
Cancer treatment is evolving towards therapies targeted at specific molecular abnormalities that drive tumor growth. Consequently, to determine which patients are eligible, accurate assessment of molecular aberrations within tumors is required. Obtaining sufficient tumor tissue for molecular testing can present challenges; therefore, circulating free tumor-derived DNA (ctDNA) found in blood plasma has been proposed as an alternative source of tumor DNA. The diagnostic utility of ctDNA for the detection of epidermal growth factor receptor (EGFR) mutations harbored in tumors of patients with advanced non-small-cell lung cancer (NSCLC) is supported by the results of several large studies/meta-analyses. However, recent real-world studies suggest that the performance of ctDNA testing varies between geographic regions/laboratories, demonstrating the need for standardized guidance. In this review, we outline recommendations for obtaining an accurate result using ctDNA, relating to pre-analytical plasma processing, ctDNA extraction, and appropriate EGFR mutation detection methods, based on clinical trial results. We conclude that there are several advantages associated with ctDNA, including the potential for repeated sampling particularly following progression after first-line tyrosine kinase inhibitor (TKI) therapy, as TKIs targeting resistance mutations (eg T790M) are now approved for use in the USA/EU/Japan (at time of writing). However, evidence suggests that ctDNA does not allow detection of EGFR mutations in all patients with known mutation-positive NSCLC. Therefore, although tumor tissue should be the first sample choice for EGFR testing at diagnosis, ctDNA is a promising alternative diagnostic approach. PMID:27980215
Wang, Long; Wu, Yishi; Chen, Jianwei; Wang, Lanfen; Liu, Yanping; Yu, Zhenyi; Yao, Jiannian; Fu, Hongbing
2017-11-16
A new class of donor-acceptor heterodimers based on two singlet fission (SF)-active chromophores, i.e., pentacene (Pc) and perylenediimide (PDI), was developed to investigate the role of charge transfer (CT) state on the excitonic dynamics. The CT state is efficiently generated upon photoexcitation. However, the resulting CT state decays to different energy states depending on the energy levels of the CT state. It undergoes extremely rapid deactivation to the ground state in polar CH 2 Cl 2 , whereas it undergoes transformation to a Pc triplet in nonpolar toluene. The efficient triplet generation in toluene is not due to SF but CT-mediated intersystem crossing. In light of the energy landscape, it is suggested that the deep energy level of the CT state relative to that of the triplet pair state makes the CT state actually serve as a trap state that cannot undergoes an intramolecular singlet fission process. These results provide guidance for the design of SF materials and highlight the requisite for more widely applicable design principles.
Non-Invasive Transcranial Brain Therapy Guided by CT Scans: an In Vivo Monkey Study
NASA Astrophysics Data System (ADS)
Marquet, F.; Pernot, M.; Aubry, J.-F.; Montaldo, G.; Tanter, M.; Boch, A.-L.; Kujas, M.; Seilhean, D.; Fink, M.
2007-05-01
Brain therapy using focused ultrasound remains very limited due to the strong aberrations induced by the skull. A minimally invasive technique using time-reversal was validated recently in-vivo on 20 sheeps. But such a technique requires a hydrophone at the focal point for the first step of the time-reversal procedure. A completely noninvasive therapy requires a reliable model of the acoustic properties of the skull in order to simulate this first step. 3-D simulations based on high-resolution CT images of a skull have been successfully performed with a finite differences code developed in our Laboratory. Thanks to the skull porosity, directly extracted from the CT images, we reconstructed acoustic speed, density and absorption maps and performed the computation. Computed wavefronts are in good agreement with experimental wavefronts acquired through the same part of the skull and this technique was validated in-vitro in the laboratory. A stereotactic frame has been designed and built in order to perform non invasive transcranial focusing in vivo. Here we describe all the steps of our new protocol, from the CT-scans to the therapy treatment and the first in vivo results on a monkey will be presented. This protocol is based on protocols already existing in radiotherapy.
A study on quantifying COPD severity by combining pulmonary function tests and CT image analysis
NASA Astrophysics Data System (ADS)
Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku
2011-03-01
This paper describes a novel method that can evaluate chronic obstructive pulmonary disease (COPD) severity by combining measurements of pulmonary function tests and measurements obtained from CT image analysis. There is no cure for COPD. However, with regular medical care and consistent patient compliance with treatments and lifestyle changes, the symptoms of COPD can be minimized and progression of the disease can be slowed. Therefore, many diagnosis methods based on CT image analysis have been proposed for quantifying COPD. Most of diagnosis methods for COPD extract the lesions as low-attenuation areas (LAA) by thresholding and evaluate the COPD severity by calculating the LAA in the lung (LAA%). However, COPD is usually the result of a combination of two conditions, emphysema and chronic obstructive bronchitis. Therefore, the previous methods based on only LAA% do not work well. The proposed method utilizes both of information including the measurements of pulmonary function tests and the results of the chest CT image analysis to evaluate the COPD severity. In this paper, we utilize a multi-class AdaBoost to combine both of information and classify the COPD severity into five stages automatically. The experimental results revealed that the accuracy rate of the proposed method was 88.9% (resubstitution scheme) and 64.4% (leave-one-out scheme).
NASA Astrophysics Data System (ADS)
Sebatubun, M. M.; Haryawan, C.; Windarta, B.
2018-03-01
Lung cancer causes a high mortality rate in the world than any other cancers. That can be minimised if the symptoms and cancer cells have been detected early. One of the techniques used to detect lung cancer is by computed tomography (CT) scan. CT scan images have been used in this study to identify one of the lesion characteristics named ground glass opacity (GGO). It has been used to determine the level of malignancy of the lesion. There were three phases in identifying GGO: image cropping, feature extraction using grey level co-occurrence matrices (GLCM) and classification using Naïve Bayes Classifier. In order to improve the classification results, the most significant feature was sought by feature selection using gain ratio evaluation. Based on the results obtained, the most significant features could be identified by using feature selection method used in this research. The accuracy rate increased from 83.33% to 91.67%, the sensitivity from 82.35% to 94.11% and the specificity from 84.21% to 89.47%.
NASA Astrophysics Data System (ADS)
Shi, Liehang; Ling, Tonghui; Zhang, Jianguo
2016-03-01
Radiologists currently use a variety of terminologies and standards in most hospitals in China, and even there are multiple terminologies being used for different sections in one department. In this presentation, we introduce a medical semantic comprehension system (MedSCS) to extract semantic information about clinical findings and conclusion from free text radiology reports so that the reports can be classified correctly based on medical terms indexing standards such as Radlex or SONMED-CT. Our system (MedSCS) is based on both rule-based methods and statistics-based methods which improve the performance and the scalability of MedSCS. In order to evaluate the over all of the system and measure the accuracy of the outcomes, we developed computation methods to calculate the parameters of precision rate, recall rate, F-score and exact confidence interval.
Costa, Mónica; Alves, Susana P; Cappucci, Alice; Cook, Shaun R; Duarte, Ana; Caldeira, Rui M; McAllister, Tim A; Bessa, Rui J B
2018-04-04
The hypothesis that condensed tannins have higher inhibitory effect on ruminal biohydrogenation than hydrolyzable tannins was tested. Condensed tannin extract from mimosa (CT) and hydrolyzable tannin extract from chestnut (HT) or their mixture (MIX) were incorporated (10%) into oil supplemented diets and fed to rumen fistulated sheep. Fatty acid and dimethyl acetal composition of rumen contents and bacterial biomass were determined. Selected rumen bacteria were analyzed by quantitative real time PCR. Lower ( P < 0.05) rumen volatile fatty acids concentrations were observed with CT compared to HT. Moreover, lower concentration ( P < 0.05) of Fibrobacter succinogenes, Ruminococcus flavefaciens, Ruminococcus albus, and Butyrivibrio proteoclasticus were observed with CT compared to HT. The extension of biohydrogenation of 18:2n-6 and 18:3n-3 did not differ among treatments but was much more variable with CT and MIX than with HT. The trans-/ cis-18:1 ratio in bacterial biomass was higher ( P < 0.05) with HT than CT. Thus, mimosa condensed tannins had a higher inhibitory effect on ruminal metabolism and biohydrogenation than chestnut hydrolyzable tannins.
Kasparek, Maximilian F; Töpker, Michael; Lazar, Mathias; Weber, Michael; Kasparek, Michael; Mang, Thomas; Apfaltrer, Paul; Kubista, Bernd; Windhager, Reinhard; Ringl, Helmut
2018-06-07
To evaluate the influence of different scan parameters for single-energy CT and dual-energy CT, as well as the impact of different material used in a TKA prosthesis on image quality and the extent of metal artifacts. Eight pairs of TKA prostheses from different vendors were examined in a phantom set-up. Each pair consisted of a conventional CoCr prosthesis and the corresponding anti-allergic prosthesis (full titanium, ceramic, or ceramic-coated) from the same vendor. Nine different (seven dual-energy CT and two single-energy CT) scan protocols with different characteristics were used to determine the most suitable CT protocol for TKA imaging. Quantitative image analysis included assessment of blooming artifacts (metal implants appear thicker on CT than they are, given as virtual growth in mm in this paper) and streak artifacts (thick dark lines around metal). Qualitative image analysis was used to investigate the bone-prosthesis interface. The full titanium prosthesis and full ceramic knee showed significantly fewer blooming artifacts compared to the standard CoCr prosthesis (mean virtual growth 0.6-2.2 mm compared to 2.9-4.6 mm, p < 0.001). Dual-energy CT protocols showed less blooming (range 3.3-3.8 mm) compared to single-energy protocols (4.6-5.5 mm). The full titanium and full ceramic prostheses showed significantly fewer streak artifacts (mean standard deviation 77-86 Hounsfield unit (HU)) compared to the standard CoCr prosthesis (277-334 HU, p < 0.001). All dual-energy CT protocols had fewer metal streak artifacts (215-296 HU compared to single-energy CT protocols (392-497 HU)). Full titanium and ceramic prostheses were ranked superior with regard to the image quality at the bone/prosthesis interface compared to a standard CoCr prosthesis, and all dual-energy CT protocols were ranked better than single-energy protocols. Dual-energy CT and ceramic or titanium prostheses reduce CT artifacts and provide superior image quality of total knee arthroplasty at the bone/prosthesis interface. These findings support the use of dual-energy CT as a solid imaging base for clinical decision-making and the use of full-titanium or ceramic prostheses to allow for better CT visualization of the bone-prosthesis interface.
ERIC Educational Resources Information Center
Kobe, John R,
1981-01-01
Describes a new approach to adult learning: a teaching process which uses competency-based, individualized instructional materials regardless of the level of the student. Discusses business/school cooperation, the manager/teacher's role, and the teacher training program. (CT)
Simulation-based Extraction of Key Material Parameters from Atomic Force Microscopy
NASA Astrophysics Data System (ADS)
Alsafi, Huseen; Peninngton, Gray
Models for the atomic force microscopy (AFM) tip and sample interaction contain numerous material parameters that are often poorly known. This is especially true when dealing with novel material systems or when imaging samples that are exposed to complicated interactions with the local environment. In this work we use Monte Carlo methods to extract sample material parameters from the experimental AFM analysis of a test sample. The parameterized theoretical model that we use is based on the Virtual Environment for Dynamic AFM (VEDA) [1]. The extracted material parameters are then compared with the accepted values for our test sample. Using this procedure, we suggest a method that can be used to successfully determine unknown material properties in novel and complicated material systems. We acknowledge Fisher Endowment Grant support from the Jess and Mildred Fisher College of Science and Mathematics,Towson University.
[Application of computed tomography (CT) examination for forensic medicine].
Urbanik, Andrzej; Chrzan, Robert
2013-01-01
The aim of the study is to present a own experiences in usage of post mortem CT examination for forensic medicine. With the help of 16-slice CT scanner 181 corpses were examined. Obtained during acquisition imaging data are later developed with dedicated programmes. Analyzed images were extracted from axial sections, multiplanar reconstructions as well as 3D reconstructions. Gained information helped greatly when classical autopsy was performed by making it more accurate. A CT scan images recorded digitally enable to evaluate corpses at any time, despite processes of putrefaction or cremation. If possible CT examination should precede classical autopsy.
Jee, Jeong-Hyun; Lee, Wan; Lee, Byung Do
2010-08-01
Many dental patients take bisphosphonates to reduce the risk of hip and vertebral fractures. In vivo micro-computed tomography (micro-CT) was used to examine the longitudinal inhibitory effect of alendronate on the healing of extraction sockets in ovariectomized rats. Twenty 5-week-old Sprague-Dawley rats were assigned randomly to 1 of 3 groups: sham-operated (n = 5), and 2 ovariectomized (OVX) groups: saline treated (0.1 mL/100 g/d, n = 7) and alendronate treated (1 mg/kg/d, n = 8). Before micro-CT scanning, the left maxillary first molars of the rats were extracted. In vivo micro-CT (spatial resolution 50 x 50 mum) of the jaw was performed at baseline and at 2-week intervals for 6 weeks. Alveolar-bone radiographic densities and dimensions were analyzed with repeated measures analysis of variance. The bony healing patterns of the extraction sockets were also evaluated in each group. The radiographic socket densities of the sham-treated and OVX-alendronate groups significantly increased during the first 4 weeks after extraction (P < .05). At 2 weeks, the radiographic densities of the sockets in the OVX-saline group increased, but the increase was significantly lower than for the other groups at 4 weeks (P < .05). Newly formed bone was identified in the extraction sockets in all groups 2 to 6 weeks after extraction. There was a significant loss of alveolar ridge height at the second week postextraction compared with baseline, and at the fourth week compared with the second week (P < .05) except in the alendronate group. Alendronate appears to promote the healing of extraction sockets in estrogen-deficient rats and helps resist the loss of alveolar bone adjacent to extraction sockets. Copyright 2010 Mosby, Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Solomon, Justin; Ba, Alexandre; Diao, Andrew; Lo, Joseph; Bier, Elianna; Bochud, François; Gehm, Michael; Samei, Ehsan
2016-03-01
In x-ray computed tomography (CT), task-based image quality studies are typically performed using uniform background phantoms with low-contrast signals. Such studies may have limited clinical relevancy for modern non-linear CT systems due to possible influence of background texture on image quality. The purpose of this study was to design and implement anatomically informed textured phantoms for task-based assessment of low-contrast detection. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find the CLB parameters that were most reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, a cylinder phantom (165 mm in diameter and 30 mm height) was designed, containing 20 low-contrast spherical signals (6 mm in diameter at targeted contrast levels of ~3.2, 5.2, 7.2, 10, and 14 HU, 4 repeats per signal). The phantom was voxelized and input into a commercial multi-material 3D printer (Object Connex 350), with custom software for voxel-based printing. Using principles of digital half-toning and dithering, the 3D printer was programmed to distribute two base materials (VeroWhite and TangoPlus, nominal voxel size of 42x84x30 microns) to achieve the targeted spatial distribution of x-ray attenuation properties. The phantom was used for task-based image quality assessment of a clinically available iterative reconstruction algorithm (Sinogram Affirmed Iterative Reconstruction, SAFIRE) using a channelized Hotelling observer paradigm. Images of the textured phantom and a corresponding uniform phantom were acquired at six dose levels and observer model performance was estimated for each condition (5 contrasts x 6 doses x 2 reconstructions x 2 backgrounds = 120 total conditions). Based on the observer model results, the dose reduction potential of SAFIRE was computed and compared between the uniform and textured phantom. The dose reduction potential of SAFIRE was found to be 23% based on the uniform phantom and 17% based on the textured phantom. This discrepancy demonstrates the need to consider background texture when assessing non-linear reconstruction algorithms.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steinmann, A; Stafford, R; Yung, J
Purpose: MRI guided radiotherapy (MRIgRT) is an emerging technology which will eventually require a proficient quality auditing system. Due to different principles in which MR and CT acquire images, there is a need for a multi-imaging-modality, end-to-end QA phantom for MRIgRT. The purpose of this study is to identify lung, soft tissue, and tumor equivalent substitutes that share similar human-like CT and MR properties (i.e. Hounsfield units and relaxation times). Methods: Materials of interested such as common CT QA phantom materials, and other proprietary gels/silicones from Polytek, SmoothOn, and CompositeOne were first scanned on a GE 1.5T Signa HDxT MR.more » Materials that could be seen on both T1-weighted and T2-weighted images were then scanned on a GE Lightspeed RT16 CT simulator and a GE Discovery 750HD CT scanner and their HU values were then measured. The materials with matching HU values of lung (−500 to −700HU), muscle (+40HU) and soft tissue (+100 to +300HU) were further scanned on GE 1.5T Signa HDx to measure their T1 and T2 relaxation times from varying parameters of TI and TE. Results: Materials that could be visualized on T1-weighted and T2-weighted images from a 1.5T MR unit and had an appropriate average CT number, −650, −685, 46,169, and 168 HUs were: compressed cork saturated with water, Polytek Platsil™ Gel-00 combined with mini styrofoam balls, radiotherapy bolus material, SmoothOn Dragon-Skin™ and SmoothOn Ecoflex™, respectively. Conclusion: Post processing analysis is currently being performed to accurately map T1 and T2 values for each material tested. From previous MR visualization and CT examinations it is expected that Dragon-Skin™, Ecoflex™ and bolus will have values consistent with tissue and tumor substitutes. We also expect compressed cork statured with water, and Polytek™-styrofoam combination to have approximate T1 and T2 values suitable for lung-equivalent materials.« less
Salo, Zoryana; Beek, Maarten; Wright, David; Whyne, Cari Marisa
2015-04-13
Current methods for the development of pelvic finite element (FE) models generally are based upon specimen specific computed tomography (CT) data. This approach has traditionally required segmentation of CT data sets, which is time consuming and necessitates high levels of user intervention due to the complex pelvic anatomy. The purpose of this research was to develop and assess CT landmark-based semi-automated mesh morphing and mapping techniques to aid the generation and mechanical analysis of specimen-specific FE models of the pelvis without the need for segmentation. A specimen-specific pelvic FE model (source) was created using traditional segmentation methods and morphed onto a CT scan of a different (target) pelvis using a landmark-based method. The morphed model was then refined through mesh mapping by moving the nodes to the bone boundary. A second target model was created using traditional segmentation techniques. CT intensity based material properties were assigned to the morphed/mapped model and to the traditionally segmented target models. Models were analyzed to evaluate their geometric concurrency and strain patterns. Strains generated in a double-leg stance configuration were compared to experimental strain gauge data generated from the same target cadaver pelvis. CT landmark-based morphing and mapping techniques were efficiently applied to create a geometrically multifaceted specimen-specific pelvic FE model, which was similar to the traditionally segmented target model and better replicated the experimental strain results (R(2)=0.873). This study has shown that mesh morphing and mapping represents an efficient validated approach for pelvic FE model generation without the need for segmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.
MMKG: An approach to generate metallic materials knowledge graph based on DBpedia and Wikipedia
NASA Astrophysics Data System (ADS)
Zhang, Xiaoming; Liu, Xin; Li, Xin; Pan, Dongyu
2017-02-01
The research and development of metallic materials are playing an important role in today's society, and in the meanwhile lots of metallic materials knowledge is generated and available on the Web (e.g., Wikipedia) for materials experts. However, due to the diversity and complexity of metallic materials knowledge, the knowledge utilization may encounter much inconvenience. The idea of knowledge graph (e.g., DBpedia) provides a good way to organize the knowledge into a comprehensive entity network. Therefore, the motivation of our work is to generate a metallic materials knowledge graph (MMKG) using available knowledge on the Web. In this paper, an approach is proposed to build MMKG based on DBpedia and Wikipedia. First, we use an algorithm based on directly linked sub-graph semantic distance (DLSSD) to preliminarily extract metallic materials entities from DBpedia according to some predefined seed entities; then based on the results of the preliminary extraction, we use an algorithm, which considers both semantic distance and string similarity (SDSS), to achieve the further extraction. Second, due to the absence of materials properties in DBpedia, we use an ontology-based method to extract properties knowledge from the HTML tables of corresponding Wikipedia Web pages for enriching MMKG. Materials ontology is used to locate materials properties tables as well as to identify the structure of the tables. The proposed approach is evaluated by precision, recall, F1 and time performance, and meanwhile the appropriate thresholds for the algorithms in our approach are determined through experiments. The experimental results show that our approach returns expected performance. A tool prototype is also designed to facilitate the process of building the MMKG as well as to demonstrate the effectiveness of our approach.
The microstructure of capsule containing self-healing materials: A micro-computed tomography study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Van Stappen, Jeroen, E-mail: Jeroen.Vanstappen@uge
Autonomic self-healing materials are materials with built-in (micro-) capsules or vessels, which upon fracturing release healing agents in order to recover the material's physical and mechanical properties. In order to better understand and engineer these materials, a thorough characterization of the material's microstructural behavior is essential and often overlooked. In this context, micro-computed tomography (μCT) can be used to investigate the three dimensional distribution and (de)bonding of (micro-) capsules in their native state in a polymer system with self-healing properties. Furthermore, in-situ μCT experiments in a self-healing polymer and a self-healing concrete system can elucidate the breakage and leakage behaviormore » of (micro-) capsules at the micrometer scale. While challenges related to image resolution and contrast complicate the characterization in specific cases, non-destructive 3D imaging with μCT is shown to contribute to the understanding of the link between the microstructure and the self-healing behavior of these complex materials. - Highlights: • μCT imaging allows for the analysis of microcapsule distribution patterns in self-healing materials. • μCT allows for qualitative and quantitative measurements of healing agent release from carriers in self-healing materials. • Experimental set-ups can be optimized by changing chemical compounds in the system to ensure maximum quality imaging.« less
NASA Astrophysics Data System (ADS)
Chakraborty, Jayasree; Pulvirenti, Alessandra; Yamashita, Rikiya; Midya, Abhishek; Gönen, Mithat; Klimstra, David S.; Reidy, Diane L.; Allen, Peter J.; Do, Richard K. G.; Simpson, Amber L.
2018-02-01
Pancreatic neuroendocrine tumors (PanNETs) account for approximately 5% of all pancreatic tumors, affecting one individual per million each year.1 PanNETs are difficult to treat due to biological variability from benign to highly malignant, indolent to very aggressive. The World Health Organization classifies PanNETs into three categories based on cell proliferative rate, usually detected using the Ki67 index and cell morphology: low-grade (G1), intermediate-grade (G2) and high-grade (G3) tumors. Knowledge of grade prior to treatment would select patients for optimal therapy: G1/G2 tumors respond well to somatostatin analogs and targeted or cytotoxic drugs whereas G3 tumors would be targeted with platinum or alkylating agents.2, 3 Grade assessment is based on the pathologic examination of the surgical specimen, biopsy or ne-needle aspiration; however, heterogeneity in the proliferative index can lead to sampling errors.4 Based on studies relating qualitatively assessed shape and enhancement characteristics on CT imaging to tumor grade in PanNET,5 we propose objective classification of PanNET grade with quantitative analysis of CT images. Fifty-five patients were included in our retrospective analysis. A pathologist graded the tumors. Texture and shape-based features were extracted from CT. Random forest and naive Bayes classifiers were compared for the classification of G1/G2 and G3 PanNETs. The best area under the receiver operating characteristic curve (AUC) of 0:74 and accuracy of 71:64% was achieved with texture features. The shape-based features achieved an AUC of 0:70 and accuracy of 78:73%.
Quantization of liver tissue in dual kVp computed tomography using linear discriminant analysis
NASA Astrophysics Data System (ADS)
Tkaczyk, J. Eric; Langan, David; Wu, Xiaoye; Xu, Daniel; Benson, Thomas; Pack, Jed D.; Schmitz, Andrea; Hara, Amy; Palicek, William; Licato, Paul; Leverentz, Jaynne
2009-02-01
Linear discriminate analysis (LDA) is applied to dual kVp CT and used for tissue characterization. The potential to quantitatively model both malignant and benign, hypo-intense liver lesions is evaluated by analysis of portal-phase, intravenous CT scan data obtained on human patients. Masses with an a priori classification are mapped to a distribution of points in basis material space. The degree of localization of tissue types in the material basis space is related to both quantum noise and real compositional differences. The density maps are analyzed with LDA and studied with system simulations to differentiate these factors. The discriminant analysis is formulated so as to incorporate the known statistical properties of the data. Effective kVp separation and mAs relates to precision of tissue localization. Bias in the material position is related to the degree of X-ray scatter and partial-volume effect. Experimental data and simulations demonstrate that for single energy (HU) imaging or image-based decomposition pixel values of water-like tissues depend on proximity to other iodine-filled bodies. Beam-hardening errors cause a shift in image value on the scale of that difference sought between in cancerous and cystic lessons. In contrast, projection-based decomposition or its equivalent when implemented on a carefully calibrated system can provide accurate data. On such a system, LDA may provide novel quantitative capabilities for tissue characterization in dual energy CT.
NASA Astrophysics Data System (ADS)
Yaguchi, Atsushi; Okazaki, Tomoya; Takeguchi, Tomoyuki; Matsumoto, Sumiaki; Ohno, Yoshiharu; Aoyagi, Kota; Yamagata, Hitoshi
2015-03-01
Reflecting global interest in lung cancer screening, considerable attention has been paid to automatic segmentation and volumetric measurement of lung nodules on CT. Ground glass opacity (GGO) nodules deserve special consideration in this context, since it has been reported that they are more likely to be malignant than solid nodules. However, due to relatively low contrast and indistinct boundaries of GGO nodules, segmentation is more difficult for GGO nodules compared with solid nodules. To overcome this difficulty, we propose a method for accurately segmenting not only solid nodules but also GGO nodules without prior information about nodule types. First, the histogram of CT values in pre-extracted lung regions is modeled by a Gaussian mixture model and a threshold value for including high-attenuation regions is computed. Second, after setting up a region of interest around the nodule seed point, foreground regions are extracted by using the threshold and quick-shift-based mode seeking. Finally, for separating vessels from the nodule, a vessel-likelihood map derived from elongatedness of foreground regions is computed, and a region growing scheme starting from the seed point is applied to the map with the aid of fast marching method. Experimental results using an anthropomorphic chest phantom showed that our method yielded generally lower volumetric measurement errors for both solid and GGO nodules compared with other methods reported in preceding studies conducted using similar technical settings. Also, our method allowed reasonable segmentation of GGO nodules in low-dose images and could be applied to clinical CT images including part-solid nodules.
Zhou, Fengjuan; Zheng, Xiaofei; Xie, Meng; Mo, Anchun; Wu, Hongkun
2017-06-01
To evaluate the microenvironment changes in the sockets substituted with bovine-derived xenografts during the early healing period. After extraction of the right maxillary incisor of Sprague Dawley rats, 48 rats were randomly divided into 2 groups. The extraction sockets of the test group were filled with Bio-Oss, whereas the control group was allowed to heal without intervention. The bone quality of the extraction sockets was observed through micro-CT and immunohistochemistry. Micro-CT scanning showed that the bone mineral density in the test group was significantly higher than that in the control group during the early healing period, whereas immunohistochemistry showed that the bone formation-related factors were significantly different between the test and control groups. The bovine-derived xenografts may interfere with the healing process of the extraction socket in the early healing stage. Bone formation of the extraction socket was delayed after grafting with bone substitute.
Clé-Ovejero, Adrià; Sánchez-Torres, Alba; Camps-Font, Octavi; Gay-Escoda, Cosme; Figueiredo, Rui; Valmaseda-Castellón, Eduard
2017-08-01
Clinicians generally use panoramic radiographic (PR) images to assess the proximity of the mandibular third molar to the inferior alveolar nerve (IAN). However, in cases in which a patient needs to undergo a third-molar extraction, many clinicians also assess computed tomographic (CT) images to prevent nerve damage. Two of the authors independently searched MEDLINE (through PubMed), Cochrane Library, Scopus, and Ovid. The authors included randomized or nonrandomized longitudinal studies whose investigators had compared the number of IAN injuries after third-molar extraction in patients who had undergone preoperative CT with patients who had undergone only PR. The authors analyzed the full text of 26 of the 745 articles they initially selected. They included 6 studies in the meta-analysis. Four of the studies had a high risk of bias, and the investigators of only 1 study had used blinding with the patients. The authors observed no statistically significant differences between groups related to the total number of nerve injuries (risk ratio, 0.96; 95% confidence interval, 0.50 to 1.85; P = .91). The prognosis of the injuries was similar for both groups. Although having preoperative CT images might be useful for clinicians in terms of diagnosing and extracting mandibular third molars, having these CT images does not reduce patients' risk of experiencing IAN injuries nor does it affect their prognosis. Copyright © 2017 American Dental Association. Published by Elsevier Inc. All rights reserved.
Automatic Fontanel Extraction from Newborns' CT Images Using Variational Level Set
NASA Astrophysics Data System (ADS)
Kazemi, Kamran; Ghadimi, Sona; Lyaghat, Alireza; Tarighati, Alla; Golshaeyan, Narjes; Abrishami-Moghaddam, Hamid; Grebe, Reinhard; Gondary-Jouet, Catherine; Wallois, Fabrice
A realistic head model is needed for source localization methods used for the study of epilepsy in neonates applying Electroencephalographic (EEG) measurements from the scalp. The earliest models consider the head as a series of concentric spheres, each layer corresponding to a different tissue whose conductivity is assumed to be homogeneous. The results of the source reconstruction depend highly on the electric conductivities of the tissues forming the head.The most used model is constituted of three layers (scalp, skull, and intracranial). Most of the major bones of the neonates’ skull are ossified at birth but can slightly move relative to each other. This is due to the sutures, fibrous membranes that at this stage of development connect the already ossified flat bones of the neurocranium. These weak parts of the neurocranium are called fontanels. Thus it is important to enter the exact geometry of fontaneles and flat bone in a source reconstruction because they show pronounced in conductivity. Computer Tomography (CT) imaging provides an excellent tool for non-invasive investigation of the skull which expresses itself in high contrast to all other tissues while the fontanels only can be identified as absence of bone, gaps in the skull formed by flat bone. Therefore, the aim of this paper is to extract the fontanels from CT images applying a variational level set method. We applied the proposed method to CT-images of five different subjects. The automatically extracted fontanels show good agreement with the manually extracted ones.
Humphries, Stephen M; Yagihashi, Kunihiro; Huckleberry, Jason; Rho, Byung-Hak; Schroeder, Joyce D; Strand, Matthew; Schwarz, Marvin I; Flaherty, Kevin R; Kazerooni, Ella A; van Beek, Edwin J R; Lynch, David A
2017-10-01
Purpose To evaluate associations between pulmonary function and both quantitative analysis and visual assessment of thin-section computed tomography (CT) images at baseline and at 15-month follow-up in subjects with idiopathic pulmonary fibrosis (IPF). Materials and Methods This retrospective analysis of preexisting anonymized data, collected prospectively between 2007 and 2013 in a HIPAA-compliant study, was exempt from additional institutional review board approval. The extent of lung fibrosis at baseline inspiratory chest CT in 280 subjects enrolled in the IPF Network was evaluated. Visual analysis was performed by using a semiquantitative scoring system. Computer-based quantitative analysis included CT histogram-based measurements and a data-driven textural analysis (DTA). Follow-up CT images in 72 of these subjects were also analyzed. Univariate comparisons were performed by using Spearman rank correlation. Multivariate and longitudinal analyses were performed by using a linear mixed model approach, in which models were compared by using asymptotic χ 2 tests. Results At baseline, all CT-derived measures showed moderate significant correlation (P < .001) with pulmonary function. At follow-up CT, changes in DTA scores showed significant correlation with changes in both forced vital capacity percentage predicted (ρ = -0.41, P < .001) and diffusing capacity for carbon monoxide percentage predicted (ρ = -0.40, P < .001). Asymptotic χ 2 tests showed that inclusion of DTA score significantly improved fit of both baseline and longitudinal linear mixed models in the prediction of pulmonary function (P < .001 for both). Conclusion When compared with semiquantitative visual assessment and CT histogram-based measurements, DTA score provides additional information that can be used to predict diminished function. Automatic quantification of lung fibrosis at CT yields an index of severity that correlates with visual assessment and functional change in subjects with IPF. © RSNA, 2017.
Accurate airway centerline extraction based on topological thinning using graph-theoretic analysis.
Bian, Zijian; Tan, Wenjun; Yang, Jinzhu; Liu, Jiren; Zhao, Dazhe
2014-01-01
The quantitative analysis of the airway tree is of critical importance in the CT-based diagnosis and treatment of popular pulmonary diseases. The extraction of airway centerline is a precursor to identify airway hierarchical structure, measure geometrical parameters, and guide visualized detection. Traditional methods suffer from extra branches and circles due to incomplete segmentation results, which induce false analysis in applications. This paper proposed an automatic and robust centerline extraction method for airway tree. First, the centerline is located based on the topological thinning method; border voxels are deleted symmetrically to preserve topological and geometrical properties iteratively. Second, the structural information is generated using graph-theoretic analysis. Then inaccurate circles are removed with a distance weighting strategy, and extra branches are pruned according to clinical anatomic knowledge. The centerline region without false appendices is eventually determined after the described phases. Experimental results show that the proposed method identifies more than 96% branches and keep consistency across different cases and achieves superior circle-free structure and centrality.
Graph representation of hepatic vessel based on centerline extraction and junction detection
NASA Astrophysics Data System (ADS)
Zhang, Xing; Tian, Jie; Deng, Kexin; Li, Xiuli; Yang, Fei
2012-02-01
In the area of computer-aided diagnosis (CAD), segmentation and analysis of hepatic vessel is a prerequisite for hepatic diseases diagnosis and surgery planning. For liver surgery planning, it is crucial to provide the surgeon with a patient-individual three-dimensional representation of the liver along with its vasculature and lesions. The representation allows an exploration of the vascular anatomy and the measurement of vessel diameters, following by intra-patient registration, as well as the analysis of the shape and volume of vascular territories. In this paper, we present an approach for generation of hepatic vessel graph based on centerline extraction and junction detection. The proposed approach involves the following concepts and methods: 1) Flux driven automatic centerline extraction; 2) Junction detection on the centerline using hollow sphere filtering; 3) Graph representation of hepatic vessel based on the centerline and junction. The approach is evaluated on contrast-enhanced liver CT datasets to demonstrate its availability and effectiveness.
Ventura, Sónia P M; E Silva, Francisca A; Quental, Maria V; Mondal, Dibyendu; Freire, Mara G; Coutinho, João A P
2017-05-24
Ionic liquids (ILs) have been proposed as promising media for the extraction and separation of bioactive compounds from the most diverse origins. This critical review offers a compilation on the main results achieved by the use of ionic-liquid-based processes in the extraction and separation/purification of a large range of bioactive compounds (including small organic extractable compounds from biomass, lipids, and other hydrophobic compounds, proteins, amino acids, nucleic acids, and pharmaceuticals). ILs have been studied as solvents, cosolvents, cosurfactants, electrolytes, and adjuvants, as well as used in the creation of IL-supported materials for separation purposes. The IL-based processes hitherto reported, such as IL-based solid-liquid extractions, IL-based liquid-liquid extractions, IL-modified materials, and IL-based crystallization approaches, are here reviewed and compared in terms of extraction and separation performance. The key accomplishments and future challenges to the field are discussed, with particular emphasis on the major lacunas found within the IL community dedicated to separation processes and by suggesting some steps to overcome the current limitations.
2017-01-01
Ionic liquids (ILs) have been proposed as promising media for the extraction and separation of bioactive compounds from the most diverse origins. This critical review offers a compilation on the main results achieved by the use of ionic-liquid-based processes in the extraction and separation/purification of a large range of bioactive compounds (including small organic extractable compounds from biomass, lipids, and other hydrophobic compounds, proteins, amino acids, nucleic acids, and pharmaceuticals). ILs have been studied as solvents, cosolvents, cosurfactants, electrolytes, and adjuvants, as well as used in the creation of IL-supported materials for separation purposes. The IL-based processes hitherto reported, such as IL-based solid–liquid extractions, IL-based liquid–liquid extractions, IL-modified materials, and IL-based crystallization approaches, are here reviewed and compared in terms of extraction and separation performance. The key accomplishments and future challenges to the field are discussed, with particular emphasis on the major lacunas found within the IL community dedicated to separation processes and by suggesting some steps to overcome the current limitations. PMID:28151648
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ikushima, K; Arimura, H; Jin, Z
Purpose: In radiation treatment planning, delineation of gross tumor volume (GTV) is very important, because the GTVs affect the accuracies of radiation therapy procedure. To assist radiation oncologists in the delineation of GTV regions while treatment planning for lung cancer, we have proposed a machine-learning-based delineation framework of GTV regions of solid and ground glass opacity (GGO) lung tumors following by optimum contour selection (OCS) method. Methods: Our basic idea was to feed voxel-based image features around GTV contours determined by radiation oncologists into a machine learning classifier in the training step, after which the classifier produced the degree ofmore » GTV for each voxel in the testing step. Ten data sets of planning CT and PET/CT images were selected for this study. The support vector machine (SVM), which learned voxel-based features which include voxel value and magnitudes of image gradient vector that obtained from each voxel in the planning CT and PET/CT images, extracted initial GTV regions. The final GTV regions were determined using the OCS method that was able to select a global optimum object contour based on multiple active delineations with a level set method around the GTV. To evaluate the results of proposed framework for ten cases (solid:6, GGO:4), we used the three-dimensional Dice similarity coefficient (DSC), which denoted the degree of region similarity between the GTVs delineated by radiation oncologists and the proposed framework. Results: The proposed method achieved an average three-dimensional DSC of 0.81 for ten lung cancer patients, while a standardized uptake value-based method segmented GTV regions with the DSC of 0.43. The average DSCs for solid and GGO were 0.84 and 0.76, respectively, obtained by the proposed framework. Conclusion: The proposed framework with the support vector machine may be useful for assisting radiation oncologists in delineating solid and GGO lung tumors.« less
Deep 3D convolution neural network for CT brain hemorrhage classification
NASA Astrophysics Data System (ADS)
Jnawali, Kamal; Arbabshirani, Mohammad R.; Rao, Navalgund; Patel, Alpen A.
2018-02-01
Intracranial hemorrhage is a critical conditional with the high mortality rate that is typically diagnosed based on head computer tomography (CT) images. Deep learning algorithms, in particular, convolution neural networks (CNN), are becoming the methodology of choice in medical image analysis for a variety of applications such as computer-aided diagnosis, and segmentation. In this study, we propose a fully automated deep learning framework which learns to detect brain hemorrhage based on cross sectional CT images. The dataset for this work consists of 40,367 3D head CT studies (over 1.5 million 2D images) acquired retrospectively over a decade from multiple radiology facilities at Geisinger Health System. The proposed algorithm first extracts features using 3D CNN and then detects brain hemorrhage using the logistic function as the last layer of the network. Finally, we created an ensemble of three different 3D CNN architectures to improve the classification accuracy. The area under the curve (AUC) of the receiver operator characteristic (ROC) curve of the ensemble of three architectures was 0.87. Their results are very promising considering the fact that the head CT studies were not controlled for slice thickness, scanner type, study protocol or any other settings. Moreover, the proposed algorithm reliably detected various types of hemorrhage within the skull. This work is one of the first applications of 3D CNN trained on a large dataset of cross sectional medical images for detection of a critical radiological condition
Ma, Zelan; Fang, Mengjie; Huang, Yanqi; He, Lan; Chen, Xin; Liang, Cuishan; Huang, Xiaomei; Cheng, Zixuan; Dong, Di; Liang, Changhong; Xie, Jiajun; Tian, Jie; Liu, Zaiyi
2017-06-01
To evaluate the value of CT-based radiomics signature for differentiating Borrmann type IV gastric cancer (GC) from primary gastric lymphoma (PGL). 40 patients with Borrmann type IV GC and 30 patients with PGL were retrospectively recruited. 485 radiomics features were extracted and selected from the portal venous CT images to build a radiomics signature. Subjective CT findings, including gastric wall peristalsis, perigastric fat infiltration, lymphadenopathy below the renal hila and enhancement pattern, were assessed to construct a subjective findings model. The radiomics signature, subjective CT findings, age and gender were integrated into a combined model by multivariate analysis. The diagnostic performance of these three models was assessed with receiver operating characteristics curves (ROC) and were compared using DeLong test. The subjective findings model, the radiomics signature and the combined model showed a diagnostic accuracy of 81.43% (AUC [area under the curve], 0.806; 95% CI [confidence interval]: 0.696-0.917; sensitivity, 63.33%; specificity, 95.00%), 84.29% (AUC, 0.886 [95% CI: 0.809-0.963]; sensitivity, 86.67%; specificity, 82.50%), 87.14% (AUC, 0.903 [95%CI: 0.831-0.975]; sensitivity, 70.00%; specificity, 100%), respectively. There were no significant differences in AUC among these three models (P=0.051-0.422). Radiomics analysis has the potential to accurately differentiate Borrmann type IV GC from PGL. Copyright © 2017 Elsevier B.V. All rights reserved.
Dynamic updating atlas for heart segmentation with a nonlinear field-based model.
Cai, Ken; Yang, Rongqian; Yue, Hongwei; Li, Lihua; Ou, Shanxing; Liu, Feng
2017-09-01
Segmentation of cardiac computed tomography (CT) images is an effective method for assessing the dynamic function of the heart and lungs. In the atlas-based heart segmentation approach, the quality of segmentation usually relies upon atlas images, and the selection of those reference images is a key step. The optimal goal in this selection process is to have the reference images as close to the target image as possible. This study proposes an atlas dynamic update algorithm using a scheme of nonlinear deformation field. The proposed method is based on the features among double-source CT (DSCT) slices. The extraction of these features will form a base to construct an average model and the created reference atlas image is updated during the registration process. A nonlinear field-based model was used to effectively implement a 4D cardiac segmentation. The proposed segmentation framework was validated with 14 4D cardiac CT sequences. The algorithm achieved an acceptable accuracy (1.0-2.8 mm). Our proposed method that combines a nonlinear field-based model and dynamic updating atlas strategies can provide an effective and accurate way for whole heart segmentation. The success of the proposed method largely relies on the effective use of the prior knowledge of the atlas and the similarity explored among the to-be-segmented DSCT sequences. Copyright © 2016 John Wiley & Sons, Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leng, S; Vrieze, T; Kuhlmann, J
2014-06-15
Purpose: To assess image quality and radiation dose reduction in abdominal CT imaging, physical phantoms having realistic background textures and lesions are highly desirable. The purpose of this work was to construct a liver phantom with realistic background and lesions using patient CT images and a 3D printer. Methods: Patient CT images containing liver lesions were segmented into liver tissue, contrast-enhanced vessels, and liver lesions using commercial software (Mimics, Materialise, Belgium). Stereolithography (STL) files of each segmented object were created and imported to a 3D printer (Object350 Connex, Stratasys, MN). After test scans were performed to map the eight availablemore » printing materials into CT numbers, printing materials were assigned to each object and a physical liver phantom printed. The printed phantom was scanned on a clinical CT scanner and resulting images were compared with the original patient CT images. Results: The eight available materials used to print the liver phantom had CT number ranging from 62 to 117 HU. In scans of the liver phantom, the liver lesions and veins represented in the STL files were all visible. Although the absolute value of the CT number in the background liver material (approx. 85 HU) was higher than in patients (approx. 40 HU), the difference in CT numbers between lesions and background were representative of the low contrast values needed for optimization tasks. Future work will investigate materials with contrast sufficient to emulate contrast-enhanced arteries. Conclusion: Realistic liver phantoms can be constructed from patient CT images using a commercial 3D printer. This technique may provide phantoms able to determine the effect of radiation dose reduction and noise reduction techniques on the ability to detect subtle liver lesions in the context of realistic background textures.« less
Han, K S; Choi, H J; Jung, D C; Park, S; Cho, K S; Joung, J Y; Seo, H K; Chung, J; Lee, K H
2011-03-01
To evaluate the diagnostic accuracy of conventional cystography for the detection of urine leakage at the vesicourethral anastomosis (VUA) site after radical prostatectomy based on computed tomography (CT) cystography. Patients who underwent radical prostatectomies at a single tertiary cancer centre were prospectively enrolled. Conventional cystography was routinely performed on postoperative day 7. Non-enhanced pelvic CT images were obtained after retrograde instillation of the same contrast material for a reference standard of urine leakage at the VUA site. Urine leakage was classified as follows: none; a plication abnormality; mild; moderate; and excessive. One hundred and twenty consecutive patients were enrolled. Conventional cystography detected 14 urine leakages, but CT cystography detected 40 urine leakages, which consisted of 28 mild and 12 moderate urine leakages. When using CT cystography as the standard measurement, conventional cystography showed a diagnostic accuracy of 17.8% (5/28) for mild urine leakage and 75% (9/12) for moderate leakage. Of nine patients diagnosed with mild leakage on conventional cystography, four (44.4%) had complicated moderate urine leakages based on CT cystography, requiring prolonged catheterization. The sensitivity, specificity, positive and negative predictive values, and accuracy of conventional cystography were 35, 100, 100, 75.4, and 78.3%, respectively. Conventional cystography is less accurate than CT cystography for diagnosing urine leakage at the VUA site after a radical prostatectomy. The present results suggest that CT cystography is a good choice for diagnostic imaging of urine leakage after radical prostatectomy. Copyright © 2010 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
A general framework of noise suppression in material decomposition for dual-energy CT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Petrongolo, Michael; Dong, Xue; Zhu, Lei, E-mail: leizhu@gatech.edu
Purpose: As a general problem of dual-energy CT (DECT), noise amplification in material decomposition severely reduces the signal-to-noise ratio on the decomposed images compared to that on the original CT images. In this work, the authors propose a general framework of noise suppression in material decomposition for DECT. The method is based on an iterative algorithm recently developed in their group for image-domain decomposition of DECT, with an extension to include nonlinear decomposition models. The generalized framework of iterative DECT decomposition enables beam-hardening correction with simultaneous noise suppression, which improves the clinical benefits of DECT. Methods: The authors propose tomore » suppress noise on the decomposed images of DECT using convex optimization, which is formulated in the form of least-squares estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance–covariance matrix of the decomposed images as the penalty weight in the least-squares term. Analytical formulas are derived to compute the variance–covariance matrix for decomposed images with general-form numerical or analytical decomposition. As a demonstration, the authors implement the proposed algorithm on phantom data using an empirical polynomial function of decomposition measured on a calibration scan. The polynomial coefficients are determined from the projection data acquired on a wedge phantom, and the signal decomposition is performed in the projection domain. Results: On the Catphan{sup ®}600 phantom, the proposed noise suppression method reduces the average noise standard deviation of basis material images by one to two orders of magnitude, with a superior performance on spatial resolution as shown in comparisons of line-pair images and modulation transfer function measurements. On the synthesized monoenergetic CT images, the noise standard deviation is reduced by a factor of 2–3. By using nonlinear decomposition on projections, the authors’ method effectively suppresses the streaking artifacts of beam hardening and obtains more uniform images than their previous approach based on a linear model. Similar performance of noise suppression is observed in the results of an anthropomorphic head phantom and a pediatric chest phantom generated by the proposed method. With beam-hardening correction enabled by their approach, the image spatial nonuniformity on the head phantom is reduced from around 10% on the original CT images to 4.9% on the synthesized monoenergetic CT image. On the pediatric chest phantom, their method suppresses image noise standard deviation by a factor of around 7.5, and compared with linear decomposition, it reduces the estimation error of electron densities from 33.3% to 8.6%. Conclusions: The authors propose a general framework of noise suppression in material decomposition for DECT. Phantom studies have shown the proposed method improves the image uniformity and the accuracy of electron density measurements by effective beam-hardening correction and reduces noise level without noticeable resolution loss.« less
Kok, Annette M; Nguyen, V Lai; Speelman, Lambert; Brands, Peter J; Schurink, Geert-Willem H; van de Vosse, Frans N; Lopata, Richard G P
2015-05-01
Abdominal aortic aneurysms (AAAs) are local dilations that can lead to a fatal hemorrhage when ruptured. Wall stress analysis of AAAs is a novel tool that has proven high potential to improve risk stratification. Currently, wall stress analysis of AAAs is based on computed tomography (CT) and magnetic resonance imaging; however, three-dimensional (3D) ultrasound (US) has great advantages over CT and magnetic resonance imaging in terms of costs, speed, and lack of radiation. In this study, the feasibility of 3D US as input for wall stress analysis is investigated. Second, 3D US-based wall stress analysis was compared with CT-based results. The 3D US and CT data were acquired in 12 patients (diameter, 35-90 mm). US data were segmented manually and compared with automatically acquired CT geometries by calculating the similarity index and Hausdorff distance. Wall stresses were simulated at P = 140 mm Hg and compared between both modalities. The similarity index of US vs CT was 0.75 to 0.91 (n = 12), with a median Hausdorff distance ranging from 4.8 to 13.9 mm, with the higher values found at the proximal and distal sides of the AAA. Wall stresses were in accordance with literature, and a good agreement was found between US- and CT-based median stresses and interquartile stresses, which was confirmed by Bland-Altman and regression analysis (n = 8). Wall stresses based on US were typically higher (+23%), caused by geometric irregularities due to the registration of several 3D volumes and manual segmentation. In future work, an automated US registration and segmentation approach is the essential point of improvement before pursuing large-scale patient studies. This study is a first step toward US-based wall stress analysis, which would be the modality of choice to monitor wall stress development over time because no ionizing radiation and contrast material are involved. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.
Staging of neuroendocrine tumours: comparison of [68Ga]DOTATOC multiphase PET/CT and whole-body MRI
Schwenzer, N. F.; Sperling, O.; Aschoff, P.; Lichy, M. P.; Müller, M.; Brendle, C.; Werner, M. K.; Claussen, C. D.; Pfannenberg, C.
2013-01-01
Abstract Purpose: In patients with a neuroendocrine tumour (NET), the extent of disease strongly influences the outcome and multidisciplinary therapeutic management. Thus, systematic analysis of the diagnostic performance of the existing staging modalities is necessary. The aim of this study was to compare the diagnostic performance of 2 whole-body imaging modalities, [68Ga]DOTATOC positron emission tomography (PET)/computed tomography (CT) and magnetic resonance imaging (MRI) in patients with NET with regard to possible impact on treatment decisions. Materials and methods: [68Ga]DOTATOC-PET/CT and whole-body magnetic resonance imaging (wbMRI) were performed on 51 patients (25 females, 26 males, mean age 57 years) with histologically proven NET and suspicion of metastatic spread within a mean interval of 2.4 days (range 0–28 days). PET/CT was performed after intravenous administration of 150 MBq [68Ga]DOTATOC. The CT protocol comprised multiphase contrast-enhanced imaging. The MRI protocol consisted of standard sequences before and after intravenous contrast administration at 1.5 T. Each modality (PET, CT, PET/CT, wbMRI) was evaluated independently by 2 experienced readers. Consensus decision based on correlation of all imaging data, histologic and surgical findings and clinical follow-up was established as the standard of reference. Lesion-based and patient-based analysis was performed. Detection rates and accuracy were compared using the McNemar test. P values <0.05 were considered significant. The impact of whole-body imaging on the treatment decision was evaluated by the interdisciplinary tumour board of our institution. Results: 593 metastatic lesions were detected in 41 of 51 (80%) patients with NET (lung 54, liver 266, bone 131, lymph node 99, other 43). One hundred and twenty PET-negative lesions were detected by CT or MRI. Of all 593 lesions detected, PET identified 381 (64%) true-positive lesions, CT 482 (81%), PET/CT 545 (92%) and wbMRI 540 (91%). Comparison of lesion-based detection rates between PET/CT and wbMRI revealed significantly higher sensitivity of PET/CT for metastatic lymph nodes (100% vs 73%; P < 0.0001) and pulmonary lesions (100% vs 87%; P = 0.0233), whereas wbMRI had significantly higher detection rates for liver (99% vs 92%; P < 0.0001) and bone lesions (96% vs 82%; P < 0.0001). Of all 593 lesions, 22 were found only in PET, 11 only in CT and 47 only in wbMRI. The patient-based overall assessment of the metastatic status of the patient showed comparable sensitivity of PET/CT and MRI with slightly higher accuracy of PET/CT. Patient-based analysis of metastatic organ involvement revealed significantly higher accuracy of PET/CT for bone and lymph node metastases (100% vs 88%; P = 0.0412 and 98% vs 78%; P = 0.0044) and for the overall comparison (99% vs 89%; P < 0.0001). The imaging results influenced the treatment decision in 30 patients (59%) with comparable information from PET/CT and wbMRI in 30 patients, additional relevant information from PET/CT in 16 patients and from wbMRI in 7 patients. Conclusion: PET/CT and wbMRI showed comparable overall lesion-based detection rates for metastatic involvement in NET but significantly differed in organ-based detection rates with superiority of PET/CT for lymph node and pulmonary lesions and of wbMRI for liver and bone metastases. Patient-based analysis revealed superiority of PET/CT for NET staging. Individual treatment strategies benefit from complementary information from PET/CT and MRI. PMID:23466785
DOE Office of Scientific and Technical Information (OSTI.GOV)
Christianson, O; Winslow, J; Samei, E
2014-06-15
Purpose: One of the principal challenges of clinical imaging is to achieve an ideal balance between image quality and radiation dose across multiple CT models. The number of scanners and protocols at large medical centers necessitates an automated quality assurance program to facilitate this objective. Therefore, the goal of this work was to implement an automated CT image quality and radiation dose monitoring program based on actual patient data and to use this program to assess consistency of protocols across CT scanner models. Methods: Patient CT scans are routed to a HIPPA compliant quality assurance server. CTDI, extracted using opticalmore » character recognition, and patient size, measured from the localizers, are used to calculate SSDE. A previously validated noise measurement algorithm determines the noise in uniform areas of the image across the scanned anatomy to generate a global noise level (GNL). Using this program, 2358 abdominopelvic scans acquired on three commercial CT scanners were analyzed. Median SSDE and GNL were compared across scanner models and trends in SSDE and GNL with patient size were used to determine the impact of differing automatic exposure control (AEC) algorithms. Results: There was a significant difference in both SSDE and GNL across scanner models (9–33% and 15–35% for SSDE and GNL, respectively). Adjusting all protocols to achieve the same image noise would reduce patient dose by 27–45% depending on scanner model. Additionally, differences in AEC methodologies across vendors resulted in disparate relationships of SSDE and GNL with patient size. Conclusion: The difference in noise across scanner models indicates that protocols are not optimally matched to achieve consistent image quality. Our results indicated substantial possibility for dose reduction while achieving more consistent image appearance. Finally, the difference in AEC methodologies suggests the need for size-specific CT protocols to minimize variability in image quality across CT vendors.« less
Zhang, Tao; Liu, Tiejun; Li, Fali; Li, Mengchen; Liu, Dongbo; Zhang, Rui; He, Hui; Li, Peiyang; Gong, Jinnan; Luo, Cheng; Yao, Dezhong; Xu, Peng
2016-07-01
Motor imagery (MI)-based brain-computer interfaces (BCIs) have been widely used for rehabilitation of motor abilities and prosthesis control for patients with motor impairments. However, MI-BCI performance exhibits a wide variability across subjects, and the underlying neural mechanism remains unclear. Several studies have demonstrated that both the fronto-parietal attention network (FPAN) and MI are involved in high-level cognitive processes that are crucial for the control of BCIs. Therefore, we hypothesized that the FPAN may play an important role in MI-BCI performance. In our study, we recorded multi-modal datasets consisting of MI electroencephalography (EEG) signals, T1-weighted structural and resting-state functional MRI data for each subject. MI-BCI performance was evaluated using the common spatial pattern to extract the MI features from EEG signals. One cortical structural feature (cortical thickness (CT)) and two measurements (degree centrality (DC) and eigenvector centrality (EC)) of node centrality were derived from the structural and functional MRI data, respectively. Based on the information extracted from the EEG and MRI, a correlation analysis was used to elucidate the relationships between the FPAN and MI-BCI performance. Our results show that the DC of the right ventral intraparietal sulcus, the EC and CT of the left inferior parietal lobe, and the CT of the right dorsolateral prefrontal cortex were significantly associated with MI-BCI performance. Moreover, the receiver operating characteristic analysis and machine learning classification revealed that the EC and CT of the left IPL could effectively predict the low-aptitude BCI users from the high-aptitude BCI users with 83.3% accuracy. Those findings consistently reveal that the individuals who have efficient FPAN would perform better on MI-BCI. Our findings may deepen the understanding of individual variability in MI-BCI performance, and also may provide a new biomarker to predict individual MI-BCI performance. Copyright © 2016 Elsevier Inc. All rights reserved.
Glick, Stephen J.; Didier, Clay
2013-01-01
A number of research groups have been investigating the use of dedicated breast computerized tomography (CT). Preliminary results have been encouraging, suggesting an improved visualization of masses on breast CT as compared to conventional mammography. Nonetheless, there are many challenges to overcome before breast CT can become a routine clinical reality. One potential improvement over current breast CT prototypes would be the use of photon counting detectors with cadmium zinc telluride (CZT) (or CdTe) semiconductor material. These detectors can operate at room temperature and provide high detection efficiency and the capability of multi-energy imaging; however, one factor in particular that limits image quality is the emission of characteristic x-rays. In this study, the degradative effects of characteristic x-rays are examined when using a CZT detector under breast CT operating conditions. Monte Carlo simulation software was used to evaluate the effect of characteristic x-rays and the detector element size on spatial and spectral resolution for a CZT detector used under breast CT operating conditions. In particular, lower kVp spectra and thinner CZT thicknesses were studied than that typically used with CZT based conventional CT detectors. In addition, the effect of characteristic x-rays on the accuracy of material decomposition in spectral CT imaging was explored. It was observed that when imaging with 50-60 kVp spectra, the x-ray transmission through CZT was very low for all detector thicknesses studied (0.5–3.0 mm), thus retaining dose efficiency. As expected, characteristic x-ray escape from the detector element of x-ray interaction increased with decreasing detector element size, approaching a 50% escape fraction for a 100 μm size detector element. The detector point spread function was observed to have only minor degradation with detector element size greater than 200 μm and lower kV settings. Characteristic x-rays produced increasing distortion in the spectral response with decreasing detector element size. If not corrected for, this caused a large bias in estimating tissue density parameters for material decomposition. It was also observed that degradation of the spectral response due to characteristic x-rays caused worsening precision in the estimation of tissue density parameters. It was observed that characteristic x-rays do cause some degradation in the spatial and spectral resolution of thin CZT detectors operating under breast CT conditions. These degradations should be manageable with careful selection of the detector element size. Even with the observed spectral distortion from characteristic x-rays, it is still possible to correctly estimate tissue parameters for material decomposition using spectral CT if accurate modeling is used. PMID:24187383
Lung imaging in rodents using dual energy micro-CT
NASA Astrophysics Data System (ADS)
Badea, C. T.; Guo, X.; Clark, D.; Johnston, S. M.; Marshall, C.; Piantadosi, C.
2012-03-01
Dual energy CT imaging is expected to play a major role in the diagnostic arena as it provides material decomposition on an elemental basis. The purpose of this work is to investigate the use of dual energy micro-CT for the estimation of vascular, tissue, and air fractions in rodent lungs using a post-reconstruction three-material decomposition method. We have tested our method using both simulations and experimental work. Using simulations, we have estimated the accuracy limits of the decomposition for realistic micro-CT noise levels. Next, we performed experiments involving ex vivo lung imaging in which intact lungs were carefully removed from the thorax, were injected with an iodine-based contrast agent and inflated with air at different volume levels. Finally, we performed in vivo imaging studies in (n=5) C57BL/6 mice using fast prospective respiratory gating in endinspiration and end-expiration for three different levels of positive end-expiratory pressure (PEEP). Prior to imaging, mice were injected with a liposomal blood pool contrast agent. The mean accuracy values were for Air (95.5%), Blood (96%), and Tissue (92.4%). The absolute accuracy in determining all fraction materials was 94.6%. The minimum difference that we could detect in material fractions was 15%. As expected, an increase in PEEP levels for the living mouse resulted in statistically significant increases in air fractions at end-expiration, but no significant changes in end-inspiration. Our method has applicability in preclinical pulmonary studies where various physiological changes can occur as a result of genetic changes, lung disease, or drug effects.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Park, J; Lee, J; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul
Purpose: To evaluate the effect of a tungsten eye-shield on the dose distribution of a patient. Methods: A 3D scanner was used to extract the dimension and shape of a tungsten eye-shield in the STL format. Scanned data was transferred into a 3D printer. A dummy eye shield was then produced using bio-resin (3D systems, VisiJet M3 Proplast). For a patient with mucinous carcinoma, the planning CT was obtained with the dummy eye-shield placed on the patient’s right eye. Field shaping of 6 MeV was performed using a patient-specific cerrobend block on the 15 x 15 cm{sup 2} applicator. Themore » gantry angle was 330° to cover the planning target volume near by the lens. EGS4/BEAMnrc was commissioned from our measurement data from a Varian 21EX. For the CT-based dose calculation using EGS4/DOSXYZnrc, the CT images were converted to a phantom file through the ctcreate program. The phantom file had the same resolution as the planning CT images. By assigning the CT numbers of the dummy eye-shield region to 17000, the real dose distributions below the tungsten eye-shield were calculated in EGS4/DOSXYZnrc. In the TPS, the CT number of the dummy eye-shield region was assigned to the maximum allowable CT number (3000). Results: As compared to the maximum dose, the MC dose on the right lens or below the eye shield area was less than 2%, while the corresponding RTP calculated dose was an unrealistic value of approximately 50%. Conclusion: Utilizing a 3D scanner and a 3D printer, a dummy eye-shield for electron treatment can be easily produced. The artifact-free CT images were successfully incorporated into the CT-based Monte Carlo simulations. The developed method was useful in predicting the realistic dose distributions around the lens blocked with the tungsten shield.« less
Conventional empirical law reverses in the phase transitions of 122-type iron-based superconductors
Yu, Zhenhai; Wang, Lin; Wang, Luhong; ...
2014-11-24
Phase transition of solid-state materials is a fundamental research topic in condensed matter physics, materials science and geophysics. It has been well accepted and widely proven that isostructural compounds containing different cations undergo same pressure-induced phase transitions but at progressively lower pressures as the cation radii increases. However, we discovered that this conventional law reverses in the structural transitions in 122-type iron-based superconductors. In this report, a combined low temperature and high pressure X-ray diffraction (XRD) measurement has identified the phase transition curves among the tetragonal (T), orthorhombic (O) and the collapsed-tetragonal (cT) phases in the structural phase diagram ofmore » the iron-based superconductor AFe 2As 2 (A = Ca, Sr, Eu, and Ba). As a result, the cation radii dependence of the phase transition pressure (T → cT) shows an opposite trend in which the compounds with larger ambient radii cations have a higher transition pressure.« less
NASA Astrophysics Data System (ADS)
Luong, Duy; Court, Richard W.; Sims, Mark R.; Cullen, David C.; Sephton, Mark A.
2014-09-01
The first step in many life detection protocols on Mars involves attempts to extract or isolate organic matter from its mineral matrix. A number of extraction options are available and include heat and solvent assisted methods. Recent operations on Mars indicate that heating samples can cause the loss or obfuscation of organic signals from target materials, raising the importance of solvent-based systems for future missions. Several solvent types are available (e.g. organic solvents, surfactant based solvents and subcritical water extraction) but a comparison of their efficiencies in Mars relevant materials is missing. We have spiked the well characterised Mars analogue material JSC Mars-1 with a number of representative organic standards. Extraction of the spiked JSC Mars-1 with the three solvent methods provides insights into the relative efficiency of these methods and indicates how they may be used on future Mars missions.
MCNPX simulation of proton dose distribution in homogeneous and CT phantoms
NASA Astrophysics Data System (ADS)
Lee, C. C.; Lee, Y. J.; Tung, C. J.; Cheng, H. W.; Chao, T. C.
2014-02-01
A dose simulation system was constructed based on the MCNPX Monte Carlo package to simulate proton dose distribution in homogeneous and CT phantoms. Conversion from Hounsfield unit of a patient CT image set to material information necessary for Monte Carlo simulation is based on Schneider's approach. In order to validate this simulation system, inter-comparison of depth dose distributions among those obtained from the MCNPX, GEANT4 and FLUKA codes for a 160 MeV monoenergetic proton beam incident normally on the surface of a homogeneous water phantom was performed. For dose validation within the CT phantom, direct comparison with measurement is infeasible. Instead, this study took the approach to indirectly compare the 50% ranges (R50%) along the central axis by our system to the NIST CSDA ranges for beams with 160 and 115 MeV energies. Comparison result within the homogeneous phantom shows good agreement. Differences of simulated R50% among the three codes are less than 1 mm. For results within the CT phantom, the MCNPX simulated water equivalent Req,50% are compatible with the CSDA water equivalent ranges from the NIST database with differences of 0.7 and 4.1 mm for 160 and 115 MeV beams, respectively.
Ebert, P J; Bailey, E A; Shreck, A L; Jennings, J S; Cole, N A
2017-03-01
Condensed tannins (CT) may decrease greenhouse gas emissions and alter the site of N excreted by ruminants. We evaluated the effect of top-dressing a steam-flaked corn-based finishing diet (14.4% CP and NEg 1.47 Mcal/kg) for beef cattle with a commercially available CT extract at 3 levels (0, 0.5, and 1.0% of diet, DM basis). Angus-crossbred steers ( = 27; 350 ± 32 kg initial BW) were individually fed via Calan gates for 126 d. Diet digestibility and N balance were estimated after 34 and 95 d on feed (Phase 1 and Phase 2, respectively) using titanium dioxide as a marker of fecal output and the creatinine:BW ratio as a marker for urine output. Ruminal CH and metabolic CO fluxes were measured using a GreenFeed system (C-Lock Inc., Rapid City, SD) for 2 sampling periods that coincided with fecal and urine sampling. Urine energy loss was estimated from urine N excretion, assuming all excreted N was urea. Oxygen consumption was estimated from CO production assuming a respiratory quotient of 1.05. Average daily gain (2.08, 2.14, and 2.08 kg/d for 0, 0.5, and 1.0% CT, respectively) and G:F did not differ ( = 0.88) among treatments. Starch intake and OM intake did not differ ( ≥ 0.42) among treatments during each phase. Apparent total tract starch digestibility during Phase 1 linearly decreased ( = 0.04) with inclusion of CT. Apparent total tract digestibility of OM and starch were not different among treatments ( ≥ 0.13) during Phase 2. Nitrogen intake did not differ ( ≥ 0.16) among treatments during each phase, but fecal N excretion linearly increased ( = 0.05) with inclusion of CT during Phase 1. Urinary N excretion was not different ( ≥ 0.39) among treatments during both phases, but urinary N as a proportion of total N excretion linearly decreased ( = 0.01) when CT was included in the diet during Phase 1. Retained N was not different ( ≥ 0.27) among treatments during each phase. Fluxes of CO were similar ( ≥ 0.37) among treatments during both phases. No differences ( ≥ 0.23) were observed for percentage of GE intake lost as CH (2.99, 3.12, and 3.09% in Phase 1 and 3.54, 3.55, and 4.35% in Phase 2) for 0, 0.5, and 1.0% CT, respectively. No difference ( ≥ 0.42) was observed for heat production lost as a percent of GE intake during both phases. Growth performance, gas emissions, and energetic losses were not affected by the inclusion CT in a steam-flaked corn-based finishing diet.
Jiang, Zheng; Wang, Hong; Wu, Qi-nan
2015-06-01
To optimize the processing of polysaccharide extraction from Spirodela polyrrhiza. Five factors related to extraction rate of polysaccharide were optimized by the Plackett-Burman design. Based on this study, three factors, including alcohol volume fraction, extraction temperature and ratio of material to liquid, were regarded as investigation factors by Box-Behnken response surface methodology. The effect order of three factors on the extraction rate of polysaccharide from Spirodela polyrrhiza were as follows: extraction temperature, alcohol volume fraction,ratio of material to liquid. According to Box-Behnken response, the best extraction conditions were: alcohol volume fraction of 81%, ratio of material to liquid of 1:42, extraction temperature of 100 degrees C, extraction time of 60 min for four times. Plackett-Burman design and Box-Behnken response surface methodology used to optimize the extraction process for the polysaccharide in this study is effective and stable.
Zhang, Jianhua; Nie, Xianzhou; Boquel, Sébastien; Al-Daoud, Fadi; Pelletier, Yvan
2015-12-01
The sensitivity of reverse transcription-polymerase chain reaction (RT-PCR) for virus detection is influenced by many factors such as specificity of primers and quality of templates. These factors become extremely important for successful detection when virus concentration is low. Total RNA isolated from Potato virus Y (PVY)-infected potato plants using the sodium sulfite RNA isolation method or RNeasy plant mini kit contains a high proportion of host RNA and may also contain trace amount of phenolic and polysaccharide residues, which may inhibit RT-PCR. The goal of this study was to enhance the sensitivity of PVY detection by reducing host RNA in the extract by differential centrifugation followed by extraction using an RNeasy mini kit (DCR method). One-step RT-PCR had relatively low amplification efficiency for PVY RNA when a high proportion of plant RNA was present. SYBR Green-based real time RT-PCR showed that the RNA isolated by the DCR method had a higher cycle threshold value (Ct) for the elongation factor 1-α mRNA (Ef1α) of potato than the Ct value of the RNA extracted using the RNeasy plant mini kit, indicating that the DCR method significantly reduced the proportion of potato RNA in the extract. The detectable amount of RNA extracted using the DCR method was <0.001ng when plant sap from 10 PVY-infected and PVY-free potato leaflets in a 1.5:100 fresh weight ratio was extracted, compared with 0.01 and 0.02ng of RNA using the RNeasy plant mini kit and sodium sulfite RNA isolation methods, respectively. Copyright © 2015. Published by Elsevier B.V.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chao, M; Yuan, Y; Rosenzweig, K
2015-06-15
Purpose: To develop a novel technique to enhance the image contrast of clinical cone beam CT projections and extract respiratory signals based on anatomical motion using the modified Amsterdam Shroud (AS) method to benefit image guided radiation therapy. Methods: Thoracic cone beam CT projections acquired prior to treatment were preprocessed to increase their contrast for better respiratory signal extraction. Air intensity on raw images was firstly estimated and then applied to correct the projections to generate new attenuation images that were subsequently improved with deeper anatomy feature enhancement through taking logarithm operation, derivative along superior-inferior direction, respectively. All pixels onmore » individual post-processed two dimensional images were horizontally summed to one column and all projections were combined side by side to create an AS image from which patient’s respiratory signal was extracted. The impact of gantry rotation on the breathing signal rendering was also investigated. Ten projection image sets from five lung cancer patients acquired with the Varian Onboard Imager on 21iX Clinac (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Results: Application of the air correction on raw projections showed that more than an order of magnitude of contrast enhancement was achievable. The typical contrast on the raw projections is around 0.02 while that on attenuation images could greater than 0.5. Clear and stable breathing signal can be reliably extracted from the new images while the uncorrected projection sets failed to yield clear signals most of the time. Conclusion: Anatomy feature plays a key role in yielding breathing signal from the projection images using the AS technique. The air correction process facilitated the contrast enhancement significantly and attenuation images thus obtained provides a practical solution to obtaining markerless breathing motion tracking.« less
NASA Astrophysics Data System (ADS)
Laguda, Edcer Jerecho
Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient's medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method. Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated. Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated. Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.
NASA Astrophysics Data System (ADS)
Ramakrishnan, Sowmya; Alvino, Christopher; Grady, Leo; Kiraly, Atilla
2011-03-01
We present a complete automatic system to extract 3D centerlines of ribs from thoracic CT scans. Our rib centerline system determines the positional information for the rib cage consisting of extracted rib centerlines, spinal canal centerline, pairing and labeling of ribs. We show an application of this output to produce an enhanced visualization of the rib cage by the method of Kiraly et al., in which the ribs are digitally unfolded along their centerlines. The centerline extraction consists of three stages: (a) pre-trace processing for rib localization, (b) rib centerline tracing, and (c) post-trace processing to merge the rib traces. Then we classify ribs from non-ribs and determine anatomical rib labeling. Our novel centerline tracing technique uses the Random Walker algorithm to segment the structural boundary of the rib in successive 2D cross sections orthogonal to the longitudinal direction of the ribs. Then the rib centerline is progressively traced along the rib using a 3D Kalman filter. The rib centerline extraction framework was evaluated on 149 CT datasets with varying slice spacing, dose, and under a variety of reconstruction kernels. The results of the evaluation are presented. The extraction takes approximately 20 seconds on a modern radiology workstation and performs robustly even in the presence of partial volume effects or rib pathologies such as bone metastases or fractures, making the system suitable for assisting clinicians in expediting routine rib reading for oncology and trauma applications.
Saam, Tobias; Herzen, Julia; Hetterich, Holger; Fill, Sandra; Willner, Marian; Stockmar, Marco; Achterhold, Klaus; Zanette, Irene; Weitkamp, Timm; Schüller, Ulrich; Auweter, Sigrid; Adam-Neumair, Silvia; Nikolaou, Konstantin; Reiser, Maximilian F.; Pfeiffer, Franz; Bamberg, Fabian
2013-01-01
Objectives Phase-contrast imaging is a novel X-ray based technique that provides enhanced soft tissue contrast. The aim of this study was to evaluate the feasibility of visualizing human carotid arteries by grating-based phase-contrast tomography (PC-CT) at two different experimental set-ups: (i) applying synchrotron radiation and (ii) using a conventional X-ray tube. Materials and Methods Five ex-vivo carotid artery specimens were examined with PC-CT either at the European Synchrotron Radiation Facility using a monochromatic X-ray beam (2 specimens; 23 keV; pixel size 5.4 µm), or at a laboratory set-up on a conventional X-ray tube (3 specimens; 35-40 kVp; 70 mA; pixel size 100 µm). Tomographic images were reconstructed and compared to histopathology. Two independent readers determined vessel dimensions and one reader determined signal-to-noise ratios (SNR) between PC-CT and absorption images. Results In total, 51 sections were included in the analysis. Images from both set-ups provided sufficient contrast to differentiate individual vessel layers. All PCI-based measurements strongly predicted but significantly overestimated lumen, intima and vessel wall area for both the synchrotron and the laboratory-based measurements as compared with histology (all p<0.001 with slope >0.53 per mm2, 95%-CI: 0.35 to 0.70). Although synchrotron-based images were characterized by higher SNRs than laboratory-based images; both PC-CT set-ups had superior SNRs compared to corresponding conventional absorption-based images (p<0.001). Inter-reader reproducibility was excellent (ICCs >0.98 and >0.84 for synchrotron and for laboratory-based measurements; respectively). Conclusion Experimental PC-CT of carotid specimens is feasible with both synchrotron and conventional X-ray sources, producing high-resolution images suitable for vessel characterization and atherosclerosis research. PMID:24039969
NASA Astrophysics Data System (ADS)
Ametova, Evelina; Ferrucci, Massimiliano; Chilingaryan, Suren; Dewulf, Wim
2018-06-01
The recent emergence of advanced manufacturing techniques such as additive manufacturing and an increased demand on the integrity of components have motivated research on the application of x-ray computed tomography (CT) for dimensional quality control. While CT has shown significant empirical potential for this purpose, there is a need for metrological research to accelerate the acceptance of CT as a measuring instrument. The accuracy in CT-based measurements is vulnerable to the instrument geometrical configuration during data acquisition, namely the relative position and orientation of x-ray source, rotation stage, and detector. Consistency between the actual instrument geometry and the corresponding parameters used in the reconstruction algorithm is critical. Currently available procedures provide users with only estimates of geometrical parameters. Quantification and propagation of uncertainty in the measured geometrical parameters must be considered to provide a complete uncertainty analysis and to establish confidence intervals for CT dimensional measurements. In this paper, we propose a computationally inexpensive model to approximate the influence of errors in CT geometrical parameters on dimensional measurement results. We use surface points extracted from a computer-aided design (CAD) model to model discrepancies in the radiographic image coordinates assigned to the projected edges between an aligned system and a system with misalignments. The efficacy of the proposed method was confirmed on simulated and experimental data in the presence of various geometrical uncertainty contributors.
A rib-specific multimodal registration algorithm for fused unfolded rib visualization using PET/CT
NASA Astrophysics Data System (ADS)
Kaftan, Jens N.; Kopaczka, Marcin; Wimmer, Andreas; Platsch, Günther; Declerck, Jérôme
2014-03-01
Respiratory motion affects the alignment of PET and CT volumes from PET/CT examinations in a non-rigid manner. This becomes particularly apparent if reviewing fine anatomical structures such as ribs when assessing bone metastases, which frequently occur in many advanced cancers. To make this routine diagnostic task more efficient, a fused unfolded rib visualization for 18F-NaF PET/CT is presented. It allows to review the whole rib cage in a single image. This advanced visualization is enabled by a novel rib-specific registration algorithm that rigidly optimizes the local alignment of each individual rib in both modalities based on a matched filter response function. More specifically, rib centerlines are automatically extracted from CT and subsequently individually aligned to the corresponding bone-specific PET rib uptake pattern. The proposed method has been validated on 20 PET/CT scans acquired at different clinical sites. It has been demonstrated that the presented rib- specific registration method significantly improves the rib alignment without having to run complex deformable registration algorithms. At the same time, it guarantees that rib lesions are not further deformed, which may otherwise affect quantitative measurements such as SUVs. Considering clinically relevant distance thresholds, the centerline portion with good alignment compared to the ground truth improved from 60:6% to 86:7% after registration while approximately 98% can be still considered as acceptably aligned.
Pauli, José R.; Cintra, Dennys E.; de Souza, Claudio T.; Ropelle, Eduardo R.; R. da Silva, Adelino S.
2015-01-01
The purpose of this study was to verify the effects of overtraining (OT) on insulin, inflammatory and gluconeogenesis signaling pathways in the livers of mice. Rodents were divided into control (CT), overtrained by downhill running (OTR/down), overtrained by uphill running (OTR/up) and overtrained by running without inclination (OTR). Rotarod, incremental load, exhaustive and grip force tests were used to evaluate performance. Thirty-six hours after a grip force test, the livers were extracted for subsequent protein analyses. The phosphorylation of insulin receptor beta (pIRbeta), glycogen synthase kinase 3 beta (pGSK3beta) and forkhead box O1 (pFoxo1) increased in OTR/down versus CT. pGSK3beta was higher in OTR/up versus CT, and pFoxo1 was higher in OTR/up and OTR versus CT. Phosphorylation of protein kinase B (pAkt) and insulin receptor substrate 1 (pIRS–1) were higher in OTR/up versus CT and OTR/down. The phosphorylation of IκB kinase alpha and beta (pIKKalpha/beta) was higher in all OT protocols versus CT, and the phosphorylation of stress-activated protein kinases/Jun amino-terminal kinases (pSAPK-JNK) was higher in OTR/down versus CT. Protein levels of peroxisome proliferator-activated receptor-gamma coactivator 1alpha (PGC-1alpha) and hepatocyte nuclear factor 4alpha (HNF-4alpha) were higher in OTR versus CT. In summary, OTR/down improved the major proteins of insulin signaling pathway but up-regulated TRB3, an Akt inhibitor, and its association with Akt. PMID:26445495
Pramanik, Rocky; Asplin, John R; Jackson, Molly E; Williams, James C
2008-10-01
Apatite and brushite kidney stones share calcium and phosphate as their main inorganic components. We tested the hypothesis that these stone types differ in the amount of proteins present in the stones. Intact stones were intensively analyzed by microcomputed tomography (micro CT) for both morphology (including the volume of voids, i.e., space devoid of X-ray dense material) and mineral type. To extract all proteins present in kidney stones in soluble form we developed a three-step extraction procedure using the ground stone powder. Apatite stones had significantly higher levels of total protein content and void volume compared to brushite stones. The void volume was highly correlated with the total protein contents in all stones (r2 = 0.61, P < 0.0001), and brushite stones contained significantly fewer void regions and proteins than did apatite stones (3.2 +/- 4.5% voids for brushite vs. 10.8 +/- 11.2% for apatite, P < 0.005; 4.1 +/- 1.6% protein for brushite vs. 6.0 +/- 2.4% for apatite, P < 0.03). Morphological observations other than void volume did not correlate with protein content of stones, and neither did the presence or absence of minor mineral components. Our results show that protein content of brushite and apatite stones is higher than that was previously thought, and also suggest that micro CT-visible void regions are related to the presence of protein.
Butcher, Robert; Houghton, Jo; Derrick, Tamsyn; Ramadhani, Athumani; Herrera, Beatriz; Last, Anna R; Massae, Patrick A; Burton, Matthew J; Holland, Martin J; Roberts, Chrissy H
2017-08-01
Trachoma, caused by the intracellular bacterium Chlamydia trachomatis (Ct), is the leading infectious cause of preventable blindness. Many commercial platforms are available that provide highly sensitive and specific detection of Ct DNA. However, the majority of these commercial platforms are inaccessible for population-level surveys in resource-limited settings typical to trachoma control programmes. We developed two low-cost quantitative PCR (qPCR) tests for Ct using readily available reagents on standard real-time thermocyclers. Each multiplex qPCR test targets one genomic and one plasmid Ct target in addition to an endogenous positive control for Homo sapiens DNA. The quantitative performance of the qPCR assays in clinical samples was determined by comparison to a previously evaluated droplet digital PCR (ddPCR) test. The diagnostic performance of the qPCR assays were evaluated against a commercial assay (artus C. trachomatis Plus RG PCR, Qiagen) using molecular diagnostics quality control standards and clinical samples. We examined the yield of Ct DNA prepared from five different DNA extraction kits and a cold chain-free dry-sample preservation method using swabs spiked with fixed concentrations of human and Ct DNA. The qPCR assay was highly reproducible (Ct plasmid and genomic targets mean total coefficients of variance 41.5% and 48.3%, respectively). The assay detected 8/8 core specimens upon testing of a quality control panel and performed well in comparison to commercially marketed comparator test (sensitivity and specificity>90%). Optimal extraction and sample preservation methods for research applications were identified. We describe a pipeline from collection to diagnosis providing the most efficient sample preservation and extraction with significant per test cost savings over a commercial qPCR diagnostic assay. The assay and its evaluation should allow control programs wishing to conduct independent research within the context of trachoma control, access to an affordable test with defined performance characteristics. Copyright © 2017. Published by Elsevier B.V.
Liver fat quantification using fast kVp-switching dual energy CT
NASA Astrophysics Data System (ADS)
Kriston, Andras; Mendonça, Paulo; Silva, Alvin; Paden, Robert G.; Pavlicek, William; Sahani, Dushyant; Janos Kis, Benedek; Rusko, Laszlo; Okerlund, Darin; Bhotika, Rahul
2011-03-01
Nonalcoholic steatohepatitis (NASH) is a liver disease that occurs in patients that lack a history of the well-proven association of alcohol use. A major symptom of NASH is increased fat deposition in the liver. Gemstone Spectral Imaging (GSI) with fast kVp-switching enables projection-based material decomposition, offering the opportunity to accurately characterize tissue types, e.g., fat and healthy liver tissue, based on their energy-sensitive material attenuation and density. We describe our pilot efforts to apply GSI to locate and quantify the amount of fat deposition in the liver. Two approaches are presented, one that computes percentage fat from the difference in HU values at high and low energies and the second based on directly computing fat volume fraction at each voxel using multi-material decomposition. Simulation software was used to create a phantom with a set of concentric rings, each composed of fat and soft tissue in different relative amounts with attenuation values obtained from the National Institute of Standards and Technology. Monte Carlo 80 and 140 kVp X-ray projections were acquired and CT images of the phantom were reconstructed. Results demonstrated the sensitivity of dual energy CT to the presence of fat and its ability to distinguish fat from soft tissue. Additionally, actual patient (liver) datasets were acquired using GSI and monochromatic images at 70 and 140 keV were reconstructed. Preliminary results demonstrate a tissue sensitivity that appears sufficient to quantify fat content with a degree of accuracy as may be needed for non-invasive clinical assessment of NASH.
Cranioplasty prosthesis manufacturing based on reverse engineering technology
Chrzan, Robert; Urbanik, Andrzej; Karbowski, Krzysztof; Moskała, Marek; Polak, Jarosław; Pyrich, Marek
2012-01-01
Summary Background Most patients with large focal skull bone loss after craniectomy are referred for cranioplasty. Reverse engineering is a technology which creates a computer-aided design (CAD) model of a real structure. Rapid prototyping is a technology which produces physical objects from virtual CAD models. The aim of this study was to assess the clinical usefulness of these technologies in cranioplasty prosthesis manufacturing. Material/Methods CT was performed on 19 patients with focal skull bone loss after craniectomy, using a dedicated protocol. A material model of skull deficit was produced using computer numerical control (CNC) milling, and individually pre-operatively adjusted polypropylene-polyester prosthesis was prepared. In a control group of 20 patients a prosthesis was manually adjusted to each patient by a neurosurgeon during surgery, without using CT-based reverse engineering/rapid prototyping. In each case, the prosthesis was implanted into the patient. The mean operating times in both groups were compared. Results In the group of patients with reverse engineering/rapid prototyping-based cranioplasty, the mean operating time was shorter (120.3 min) compared to that in the control group (136.5 min). The neurosurgeons found the new technology particularly useful in more complicated bone deficits with different curvatures in various planes. Conclusions Reverse engineering and rapid prototyping may reduce the time needed for cranioplasty neurosurgery and improve the prosthesis fitting. Such technologies may utilize data obtained by commonly used spiral CT scanners. The manufacturing of individually adjusted prostheses should be commonly used in patients planned for cranioplasty with synthetic material. PMID:22207125
68Ga-PSMA PET/CT in the evaluation of bone metastases in prostate cancer.
Sachpekidis, Christos; Bäumer, P; Kopka, K; Hadaschik, B A; Hohenfellner, M; Kopp-Schneider, A; Haberkorn, U; Dimitrakopoulou-Strauss, A
2018-06-01
The aims of this retrospective analysis were to compare 68 Ga-PSMA PET findings and low-dose CT findings (120 kV, 30 mA), and to obtain semiquantitative and quantitative 68 Ga-PSMA PET data in patients with prostate cancer (PC) bone metastases. In total, 152 PET/CT scans from 140 patients were evaluated. Of these patients, 30 had previously untreated primary PC, and 110 had biochemical relapse after treatment of primary PC. All patients underwent dynamic PET/CT scanning of the pelvis and lower abdomen as well as whole-body PET/CT with 68 Ga-PSMA-11. The PET/CT scans were analysed qualitatively (visually), semiquantitatively (SUV), and quantitatively based on a two-tissue compartment model and a noncompartmental approach leading to the extraction of the fractal dimension. Differences were considered significant for p values <0.05. In total, 168 68 Ga-PSMA-positive and 113 CT-positive skeletal lesions were detected in 37 patients (8 with primary PC, 29 with biochemical recurrence). Of these 168 lesions, 103 were both 68 Ga-PSMA PET-positive and CT-positive, 65 were only 68 Ga-PSMA-positive, and 10 were only CT-positive. The Yang test showed that there were significantly more 68 Ga-PSMA PET-positive lesions than CT-positive lesions. Association analysis showed that PSA plasma levels were significantly correlated with several 68 Ga-PSMA-11-associated parameters in bone metastases, including the degree of tracer uptake (SUV average and SUV max ), its transport rate from plasma to the interstitial/intracellular compartment (K 1 ), its rate of binding to the PSMA receptor and its internalization (k 3 ), its influx rate (K i ), and its distribution heterogeneity. 68 Ga-PSMA PET/CT is a useful diagnostic tool in the detection of bone metastases in PC. 68 Ga-PSMA PET visualizes more bone metastases than low-dose CT. PSA plasma levels are significantly correlated with several 68 Ga-PSMA PET parameters.
Aorta and pulmonary artery segmentation using optimal surface graph cuts in non-contrast CT
NASA Astrophysics Data System (ADS)
Sedghi Gamechi, Zahra; Arias-Lorza, Andres M.; Pedersen, Jesper Holst; de Bruijne, Marleen
2018-03-01
Accurate measurements of the size and shape of the aorta and pulmonary arteries are important as risk factors for cardiovascular diseases, and for Chronicle Obstacle Pulmonary Disease (COPD).1 The aim of this paper is to propose an automated method for segmenting the aorta and pulmonary arteries in low-dose non-ECGgated non-contrast CT scans. Low contrast and the high noise level make the automatic segmentation in such images a challenging task. In the proposed method, first, a minimum cost path tracking algorithm traces the centerline between user-defined seed points. The cost function is based on a multi-directional medialness filter and a lumen intensity similarity metric. The vessel radius is also estimated from the medialness filter. The extracted centerlines are then smoothed and dilated non-uniformly according to the extracted local vessel radius and subsequently used as initialization for a graph-cut segmentation. The algorithm is evaluated on 225 low-dose non-ECG-gated non-contrast CT scans from a lung cancer screening trial. Quantitatively analyzing 25 scans with full manual annotations, we obtain a dice overlap of 0.94+/-0.01 for the aorta and 0.92+/-0.01 for pulmonary arteries. Qualitative validation by visual inspection on 200 scans shows successful segmentation in 93% of all cases for the aorta and 94% for pulmonary arteries.
Mougiakakou, Stavroula G; Valavanis, Ioannis K; Nikita, Alexandra; Nikita, Konstantina S
2007-09-01
The aim of the present study is to define an optimally performing computer-aided diagnosis (CAD) architecture for the classification of liver tissue from non-enhanced computed tomography (CT) images into normal liver (C1), hepatic cyst (C2), hemangioma (C3), and hepatocellular carcinoma (C4). To this end, various CAD architectures, based on texture features and ensembles of classifiers (ECs), are comparatively assessed. Number of regions of interests (ROIs) corresponding to C1-C4 have been defined by experienced radiologists in non-enhanced liver CT images. For each ROI, five distinct sets of texture features were extracted using first order statistics, spatial gray level dependence matrix, gray level difference method, Laws' texture energy measures, and fractal dimension measurements. Two different ECs were constructed and compared. The first one consists of five multilayer perceptron neural networks (NNs), each using as input one of the computed texture feature sets or its reduced version after genetic algorithm-based feature selection. The second EC comprised five different primary classifiers, namely one multilayer perceptron NN, one probabilistic NN, and three k-nearest neighbor classifiers, each fed with the combination of the five texture feature sets or their reduced versions. The final decision of each EC was extracted by using appropriate voting schemes, while bootstrap re-sampling was utilized in order to estimate the generalization ability of the CAD architectures based on the available relatively small-sized data set. The best mean classification accuracy (84.96%) is achieved by the second EC using a fused feature set, and the weighted voting scheme. The fused feature set was obtained after appropriate feature selection applied to specific subsets of the original feature set. The comparative assessment of the various CAD architectures shows that combining three types of classifiers with a voting scheme, fed with identical feature sets obtained after appropriate feature selection and fusion, may result in an accurate system able to assist differential diagnosis of focal liver lesions from non-enhanced CT images.
Time-Domain Terahertz Computed Axial Tomography NDE System
NASA Technical Reports Server (NTRS)
Zimdars, David
2012-01-01
NASA has identified the need for advanced non-destructive evaluation (NDE) methods to characterize aging and durability in aircraft materials to improve the safety of the nation's airline fleet. 3D THz tomography can play a major role in detection and characterization of flaws and degradation in aircraft materials, including Kevlar-based composites and Kevlar and Zylon fabric covers for soft-shell fan containment where aging and durability issues are critical. A prototype computed tomography (CT) time-domain (TD) THz imaging system has been used to generate 3D images of several test objects including a TUFI tile (a thermal protection system tile used on the Space Shuttle and possibly the Orion or similar capsules). This TUFI tile had simulated impact damage that was located and the depth of damage determined. The CT motion control gan try was designed and constructed, and then integrated with a T-Ray 4000 control unit and motion controller to create a complete CT TD-THz imaging system prototype. A data collection software script was developed that takes multiple z-axis slices in sequence and saves the data for batch processing. The data collection software was integrated with the ability to batch process the slice data with the CT TD-THz image reconstruction software. The time required to take a single CT slice was decreased from six minutes to approximately one minute by replacing the 320 ps, 100-Hz waveform acquisition system with an 80 ps, 1,000-Hz waveform acquisition system. The TD-THZ computed tomography system was built from pre-existing commercial off-the-shelf subsystems. A CT motion control gantry was constructed from COTS components that can handle larger samples. The motion control gantry allows inspection of sample sizes of up to approximately one cubic foot (.0.03 cubic meters). The system reduced to practice a CT-TDTHz system incorporating a COTS 80- ps/l-kHz waveform scanner. The incorporation of this scanner in the system allows acquisition of 3D slice data with better signal-to-noise using a COTS scanner rather than the gchirped h scanner. The system also reduced to practice a prototype for commercial CT systems for insulating materials where safety concerns cannot accommodate x-ray. A software script was written to automate the COTS software to collect and process TD-THz CT data.
Probabilistic sparse matching for robust 3D/3D fusion in minimally invasive surgery.
Neumann, Dominik; Grbic, Sasa; John, Matthias; Navab, Nassir; Hornegger, Joachim; Ionasec, Razvan
2015-01-01
Classical surgery is being overtaken by minimally invasive and transcatheter procedures. As there is no direct view or access to the affected anatomy, advanced imaging techniques such as 3D C-arm computed tomography (CT) and C-arm fluoroscopy are routinely used in clinical practice for intraoperative guidance. However, due to constraints regarding acquisition time and device configuration, intraoperative modalities have limited soft tissue image quality and reliable assessment of the cardiac anatomy typically requires contrast agent, which is harmful to the patient and requires complex acquisition protocols. We propose a probabilistic sparse matching approach to fuse high-quality preoperative CT images and nongated, noncontrast intraoperative C-arm CT images by utilizing robust machine learning and numerical optimization techniques. Thus, high-quality patient-specific models can be extracted from the preoperative CT and mapped to the intraoperative imaging environment to guide minimally invasive procedures. Extensive quantitative experiments on 95 clinical datasets demonstrate that our model-based fusion approach has an average execution time of 1.56 s, while the accuracy of 5.48 mm between the anchor anatomy in both images lies within expert user confidence intervals. In direct comparison with image-to-image registration based on an open-source state-of-the-art medical imaging library and a recently proposed quasi-global, knowledge-driven multi-modal fusion approach for thoracic-abdominal images, our model-based method exhibits superior performance in terms of registration accuracy and robustness with respect to both target anatomy and anchor anatomy alignment errors.
Hochreiter, Joseph J.
1982-01-01
This report presents chemical-quality data collected from May 1980 to January 1981 at several locations within the Delaware River estuary and selected New Jersey tributaries. Samples of surface water were analyzed Environmental Protection Agency ' priority pollutants, ' including acid extractable, base/neutral extractable and volatile organic compounds, in addition to selected dissolved inorganic constituents. Surficial bed material at selected locations was examined for trace metals, insecticides, polychlorinated biphenyls, and base/neutral extractable organic compounds. Trace levels (1-50 micrograms per liter) of purgeable organic compounds, particularly those associated with the occurrence of hydrocarbons, were found in about 60% of the water samples taken. DDT, DDD, DDE, PCB 's and chlordane are present in most surficial bed material samples. Diazinon was the only organophosphorous insecticide detected in the study (1.6 micrograms per kilogram at one location). High values for select trace metals in bed material were discovered at two locations. Of the 10 sites sampled, the surficial bed material containing the most contamination was found along one cross section of Raccoon Creek at Bridgeport. An additional analysis of Raccoon Creek revealed bed material containing toluene, oil and grease, and trace quantities of 15 base/neutral extractable organic compounds, including polynuclear aromatic hydrocarbons, phthalate esters, and chlorinated benzenes.
Wysham, Weiya Z; Schaffer, Elisabeth M; Coles, Theresa; Roque, Dario R; Wheeler, Stephanie B; Kim, Kenneth H
2017-05-01
AURELIA, a randomized phase III trial of adding bevacizumab (B) to single agent chemotherapy (CT) for the treatment of platinum-resistant recurrent ovarian cancer, demonstrated improved progression free survival (PFS) in the B+CT arm compared to CT alone. We aimed to evaluate the cost effectiveness of adding B to CT in the treatment of platinum-resistant recurrent ovarian cancer. A decision tree model was constructed to evaluate the cost effectiveness of adding bevacizumab (B) to single agent chemotherapy (CT) based on the arms of the AURELIA trial. Costs, quality-adjusted life years (QALYs), and progression free survival (PFS) were modeled over fifteen months. Model inputs were extracted from published literature and public sources. Incremental cost effectiveness ratios (ICERs) per QALY gained and ICERs per progression free life year saved (PF-LYS) were calculated. One-way sensitivity analyses were performed to evaluate the robustness of results. The ICER associated with B+CT is $410,455 per QALY gained and $217,080 per PF-LYS. At a willingness to pay (WTP) threshold of $50,000/QALY, adding B to single agent CT is not cost effective for this patient population. Even at a WTP threshold of $100,000/QALY, B+CT is not cost effective. These findings are robust to sensitivity analyses. Despite gains in QALY and PFS, the addition of B to single agent CT for treatment of platinum-resistant recurrent ovarian cancer is not cost effective. Benefits, risks, and costs associated with treatment should be taken into consideration when prescribing chemotherapy for this patient population. Copyright © 2017 Elsevier Inc. All rights reserved.
University of Hawai‘i Cancer Center Connection
Halm, Brunhild M; Lai, Jennifer F; Li, Xingnan; Custer, Laurie J; Pagano, Ian; Cooney, Robert V; Turner, Helen C; Brenner, David J
2015-01-01
Computed tomography (CT) is an imaging modality that exposes patients to ionizing radiation (IR). We review and report findings from our pilot study evaluating whether blood markers are altered in 17 children undergoing medically indicated CT scans. Blood was drawn before (‘pre-CT’) and 1 hour after (‘post-CT’ CT scans. Plasma carotenoids, tocopherols, Q10, ascorbic acid (AA) and uric acid (UA) were analyzed by RP-HPLC with diode-array and electrochemical detection. Dehydroascorbic acid (DHAA) was calculated by subtraction from total AA. Total antioxidant capacity (TAC) was measured using the ORAC assay. Cytokines were quantified using a multiplex immunoassay. γ-H2AX foci were visualized using immunofluorescence. Mean pre- and post-CT changes were compared using t-tests; P-levels < .05 indicated significance. All major plasma lipid soluble antioxidant levels were lower post- vs pre-CT (P < .05) possibly from the scavenging of free radicals formed by CT-induced IR. Average AA levels increased (134%) while DHAA levels were decreased (29%) post-CT, probably due to intracellular recycling of AA from DHAA. TAC levels in lipophilic and hydrophilic extracts were unchanged, suggesting that other antioxidants may have assisted in free radical quenching, which would corroborate their lower concentrations post-CT. Cytokine levels were unchanged and dose-dependent increases in γ-H2AX foci, a measure of double strand DNA breaks, were observed (P = .046, n = 3 children). Our results suggest that CT-derived IR can influence the antioxidant system and may elicit detrimental responses on the cellular level of young children. When possible and if appropriate non-IR based techniques such as ultrasound or magnetic resonance imaging should be used. PMID:25821654
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi
2017-02-01
We have proposed an end-to-end learning approach that trained a deep convolutional neural network (CNN) for automatic CT image segmentation, which accomplished a voxel-wised multiple classification to directly map each voxel on 3D CT images to an anatomical label automatically. The novelties of our proposed method were (1) transforming the anatomical structures segmentation on 3D CT images into a majority voting of the results of 2D semantic image segmentation on a number of 2D-slices from different image orientations, and (2) using "convolution" and "deconvolution" networks to achieve the conventional "coarse recognition" and "fine extraction" functions which were integrated into a compact all-in-one deep CNN for CT image segmentation. The advantage comparing to previous works was its capability to accomplish real-time image segmentations on 2D slices of arbitrary CT-scan-range (e.g. body, chest, abdomen) and produced correspondingly-sized output. In this paper, we propose an improvement of our proposed approach by adding an organ localization module to limit CT image range for training and testing deep CNNs. A database consisting of 240 3D CT scans and a human annotated ground truth was used for training (228 cases) and testing (the remaining 12 cases). We applied the improved method to segment pancreas and left kidney regions, respectively. The preliminary results showed that the accuracies of the segmentation results were improved significantly (pancreas was 34% and kidney was 8% increased in Jaccard index from our previous results). The effectiveness and usefulness of proposed improvement for CT image segmentations were confirmed.
Lung vessel segmentation in CT images using graph-cuts
NASA Astrophysics Data System (ADS)
Zhai, Zhiwei; Staring, Marius; Stoel, Berend C.
2016-03-01
Accurate lung vessel segmentation is an important operation for lung CT analysis. Filters that are based on analyzing the eigenvalues of the Hessian matrix are popular for pulmonary vessel enhancement. However, due to their low response at vessel bifurcations and vessel boundaries, extracting lung vessels by thresholding the vesselness is not sufficiently accurate. Some methods turn to graph-cuts for more accurate segmentation, as it incorporates neighbourhood information. In this work, we propose a new graph-cuts cost function combining appearance and shape, where CT intensity represents appearance and vesselness from a Hessian-based filter represents shape. Due to the amount of voxels in high resolution CT scans, the memory requirement and time consumption for building a graph structure is very high. In order to make the graph representation computationally tractable, those voxels that are considered clearly background are removed from the graph nodes, using a threshold on the vesselness map. The graph structure is then established based on the remaining voxel nodes, source/sink nodes and the neighbourhood relationship of the remaining voxels. Vessels are segmented by minimizing the energy cost function with the graph-cuts optimization framework. We optimized the parameters used in the graph-cuts cost function and evaluated the proposed method with two manually labeled sub-volumes. For independent evaluation, we used 20 CT scans of the VESSEL12 challenge. The evaluation results of the sub-volume data show that the proposed method produced a more accurate vessel segmentation compared to the previous methods, with F1 score 0.76 and 0.69. In the VESSEL12 data-set, our method obtained a competitive performance with an area under the ROC curve of 0.975, especially among the binary submissions.
Automatic detection of cardiovascular risk in CT attenuation correction maps in Rb-82 PET/CTs
NASA Astrophysics Data System (ADS)
Išgum, Ivana; de Vos, Bob D.; Wolterink, Jelmer M.; Dey, Damini; Berman, Daniel S.; Rubeaux, Mathieu; Leiner, Tim; Slomka, Piotr J.
2016-03-01
CT attenuation correction (CTAC) images acquired with PET/CT visualize coronary artery calcium (CAC) and enable CAC quantification. CAC scores acquired with CTAC have been suggested as a marker of cardiovascular disease (CVD). In this work, an algorithm previously developed for automatic CAC scoring in dedicated cardiac CT was applied to automatic CAC detection in CTAC. The study included 134 consecutive patients undergoing 82-Rb PET/CT. Low-dose rest CTAC scans were acquired (100 kV, 11 mAs, 1.4mm×1.4mm×3mm voxel size). An experienced observer defined the reference standard with the clinically used intensity level threshold for calcium identification (130 HU). Five scans were removed from analysis due to artifacts. The algorithm extracted potential CAC by intensity-based thresholding and 3D connected component labeling. Each candidate was described by location, size, shape and intensity features. An ensemble of extremely randomized decision trees was used to identify CAC. The data set was randomly divided into training and test sets. Automatically identified CAC was quantified using volume and Agatston scores. In 33 test scans, the system detected on average 469mm3/730mm3 (64%) of CAC with 36mm3 false positive volume per scan. The intraclass correlation coefficient for volume scores was 0.84. Each patient was assigned to one of four CVD risk categories based on the Agatston score (0-10, 11-100, 101-400, <400). The correct CVD category was assigned to 85% of patients (Cohen's linearly weighted κ0.82). Automatic detection of CVD risk based on CAC scoring in rest CTAC images is feasible. This may enable large scale studies evaluating clinical value of CAC scoring in CTAC data.
Optimization of dose and image quality in adult and pediatric computed tomography scans
NASA Astrophysics Data System (ADS)
Chang, Kwo-Ping; Hsu, Tzu-Kun; Lin, Wei-Ting; Hsu, Wen-Lin
2017-11-01
Exploration to maximize CT image and reduce radiation dose was conducted while controlling for multiple factors. The kVp, mAs, and iteration reconstruction (IR), affect the CT image quality and radiation dose absorbed. The optimal protocols (kVp, mAs, IR) are derived by figure of merit (FOM) based on CT image quality (CNR) and CT dose index (CTDIvol). CT image quality metrics such as CT number accuracy, SNR, low contrast materials' CNR and line pair resolution were also analyzed as auxiliary assessments. CT protocols were carried out with an ACR accreditation phantom and a five-year-old pediatric head phantom. The threshold values of the adult CT scan parameters, 100 kVp and 150 mAs, were determined from the CT number test and line pairs in ACR phantom module 1and module 4 respectively. The findings of this study suggest that the optimal scanning parameters for adults be set at 100 kVp and 150-250 mAs. However, for improved low- contrast resolution, 120 kVp and 150-250 mAs are optimal. Optimal settings for pediatric head CT scan were 80 kVp/50 mAs, for maxillary sinus and brain stem, while 80 kVp /300 mAs for temporal bone. SNR is not reliable as the independent image parameter nor the metric for determining optimal CT scan parameters. The iteration reconstruction (IR) approach is strongly recommended for both adult and pediatric CT scanning as it markedly improves image quality without affecting radiation dose.
Morgan, T J; Herod, A A; Brain, S A; Chambers, F M; Kandiyoti, R
2005-11-18
Soil from a redundant coke oven site has been examined by extraction of soluble materials using 1-methyl-2-pyrrolidinone (NMP) followed by size exclusion chromatography (SEC) of the extracted material. The extracted material was found to closely resemble a high temperature coal tar pitch. Standard humic and fulvic acids were also examined since these materials are very soluble in NMP and would be extracted with pitch if present in the soil. Humic substances derived from peat samples and NMP-extracts of peats were also examined. The results show that the humic and fulvic substances were not extracted directly by NMP from peats. They were extracted using caustic soda solution and were different from the peat extracts in NMP. These results indicate that humic and fulvic acids were soluble in NMP in the protonated polyelectrolyte form but not in the original native polyelectrolyte form. The extraction of soil using NMP followed by SEC appears to be a promising method for identifying contamination by coal-based industries.
Material model of pelvic bone based on modal analysis: a study on the composite bone.
Henyš, Petr; Čapek, Lukáš
2017-02-01
Digital models based on finite element (FE) analysis are widely used in orthopaedics to predict the stress or strain in the bone due to bone-implant interaction. The usability of the model depends strongly on the bone material description. The material model that is most commonly used is based on a constant Young's modulus or on the apparent density of bone obtained from computer tomography (CT) data. The Young's modulus of bone is described in many experimental works with large variations in the results. The concept of measuring and validating the material model of the pelvic bone based on modal analysis is introduced in this pilot study. The modal frequencies, damping, and shapes of the composite bone were measured precisely by an impact hammer at 239 points. An FE model was built using the data pertaining to the geometry and apparent density obtained from the CT of the composite bone. The isotropic homogeneous Young's modulus and Poisson's ratio of the cortical and trabecular bone were estimated from the optimisation procedure including Gaussian statistical properties. The performance of the updated model was investigated through the sensitivity analysis of the natural frequencies with respect to the material parameters. The maximal error between the numerical and experimental natural frequencies of the bone reached 1.74 % in the first modal shape. Finally, the optimised parameters were matched with the data sheets of the composite bone. The maximal difference between the calibrated material properties and that obtained from the data sheet was 34 %. The optimisation scheme of the FE model based on the modal analysis data provides extremely useful calibration of the FE models with the uncertainty bounds and without the influence of the boundary conditions.
NASA Astrophysics Data System (ADS)
Erdt, Marius; Sakas, Georgios
2010-03-01
This work presents a novel approach for model based segmentation of the kidney in images acquired by Computed Tomography (CT). The developed computer aided segmentation system is expected to support computer aided diagnosis and operation planning. We have developed a deformable model based approach based on local shape constraints that prevents the model from deforming into neighboring structures while allowing the global shape to adapt freely to the data. Those local constraints are derived from the anatomical structure of the kidney and the presence and appearance of neighboring organs. The adaptation process is guided by a rule-based deformation logic in order to improve the robustness of the segmentation in areas of diffuse organ boundaries. Our work flow consists of two steps: 1.) a user guided positioning and 2.) an automatic model adaptation using affine and free form deformation in order to robustly extract the kidney. In cases which show pronounced pathologies, the system also offers real time mesh editing tools for a quick refinement of the segmentation result. Evaluation results based on 30 clinical cases using CT data sets show an average dice correlation coefficient of 93% compared to the ground truth. The results are therefore in most cases comparable to manual delineation. Computation times of the automatic adaptation step are lower than 6 seconds which makes the proposed system suitable for an application in clinical practice.
Chai, Orit; Peery, Dana; Bdolah-Abram, Tali; Moscovich, Efrat; Kelmer, Efrat; Klainbart, Sigal; Milgram, Joshua; Shamir, Merav H
2017-09-01
OBJECTIVE To characterize CT findings and outcomes in dogs with head trauma and design a prognostic scale. ANIMALS 27 dogs admitted to the Koret School Veterinary Teaching Hospital within 72 hours after traumatic head injury that underwent CT imaging of the head. PROCEDURES Data were extracted from medical records regarding dog signalment, history, physical and neurologic examination findings, and modified Glasgow coma scale scores. All CT images were retrospectively evaluated by a radiologist unaware of dog status. Short-term (10 days after trauma) and long-term (≥ 6 months after trauma) outcomes were determined, and CT findings and other variables were analyzed for associations with outcome. A prognostic CT-based scale was developed on the basis of the results. RESULTS Cranial vault fractures, parenchymal abnormalities, or both were identified via CT in 24 of 27 (89%) dogs. Three (11%) dogs had only facial bone fractures. Intracranial hemorrhage was identified in 16 (59%) dogs, cranial vault fractures in 15 (56%), midline shift in 14 (52%), lateral ventricle asymmetry in 12 (44%), and hydrocephalus in 7 (26%). Hemorrhage and ventricular asymmetry were significantly and negatively associated with short- and long-term survival, respectively. The developed 7-point prognostic scale included points for hemorrhage, midline shift or lateral ventricle asymmetry, cranial vault fracture, and depressed fracture (1 point each) and infratentorial lesion (3 points). CONCLUSIONS AND CLINICAL RELEVANCE The findings reported here may assist in determining prognoses for other dogs with head trauma. The developed scale may be useful for outcome assessment of dogs with head trauma; however, it must be validated before clinical application.
Low-Dose Contrast-Enhanced Breast CT Using Spectral Shaping Filters: An Experimental Study.
Makeev, Andrey; Glick, Stephen J
2017-12-01
Iodinated contrast-enhanced X-ray imaging of the breast has been studied with various modalities, including full-field digital mammography (FFDM), digital breast tomosynthesis (DBT), and dedicated breast CT. Contrast imaging with breast CT has a number of advantages over FFDM and DBT, including the lack of breast compression, and generation of fully isotropic 3-D reconstructions. Nonetheless, for breast CT to be considered as a viable tool for routine clinical use, it would be desirable to reduce radiation dose. One approach for dose reduction in breast CT is spectral shaping using X-ray filters. In this paper, two high atomic number filter materials are studied, namely, gadolinium (Gd) and erbium (Er), and compared with Al and Cu filters currently used in breast CT systems. Task-based performance is assessed by imaging a cylindrical poly(methyl methacrylate) phantom with iodine inserts on a benchtop breast CT system that emulates clinical breast CT. To evaluate detectability, a channelized hoteling observer (CHO) is used with sums of Laguerre-Gauss channels. It was observed that spectral shaping using Er and Gd filters substantially increased the dose efficiency (defined as signal-to-noise ratio of the CHO divided by mean glandular dose) as compared with kilovolt peak and filter settings used in commercial and prototype breast CT systems. These experimental phantom study results are encouraging for reducing dose of breast CT, however, further evaluation involving patients is needed.
Deep Learning to Classify Radiology Free-Text Reports.
Chen, Matthew C; Ball, Robyn L; Yang, Lingyao; Moradzadeh, Nathaniel; Chapman, Brian E; Larson, David B; Langlotz, Curtis P; Amrhein, Timothy J; Lungren, Matthew P
2018-03-01
Purpose To evaluate the performance of a deep learning convolutional neural network (CNN) model compared with a traditional natural language processing (NLP) model in extracting pulmonary embolism (PE) findings from thoracic computed tomography (CT) reports from two institutions. Materials and Methods Contrast material-enhanced CT examinations of the chest performed between January 1, 1998, and January 1, 2016, were selected. Annotations by two human radiologists were made for three categories: the presence, chronicity, and location of PE. Classification of performance of a CNN model with an unsupervised learning algorithm for obtaining vector representations of words was compared with the open-source application PeFinder. Sensitivity, specificity, accuracy, and F1 scores for both the CNN model and PeFinder in the internal and external validation sets were determined. Results The CNN model demonstrated an accuracy of 99% and an area under the curve value of 0.97. For internal validation report data, the CNN model had a statistically significant larger F1 score (0.938) than did PeFinder (0.867) when classifying findings as either PE positive or PE negative, but no significant difference in sensitivity, specificity, or accuracy was found. For external validation report data, no statistical difference between the performance of the CNN model and PeFinder was found. Conclusion A deep learning CNN model can classify radiology free-text reports with accuracy equivalent to or beyond that of an existing traditional NLP model. © RSNA, 2017 Online supplemental material is available for this article.
Online course design for teaching critical thinking.
Schaber, Patricia; Shanedling, Janet
2012-01-01
Teaching critical thinking (CT) skills, a goal in higher education, is seldom considered in the primary design of either classroom or online courses, and is even less frequently measured in student learning. In health professional education, CT along with clinical reasoning skills is essential for the development of clinical practitioners. This study, measuring CT skill development in an online theory course, supports using a cyclical course design to build higher level processes in student thinking. Eighty-six Masters of Occupational Therapy students in four sections of an occupation-based theory course were evaluated on elements in the Paul and Elder CT Model throughout the course and surveyed for their perceptions in their ability to think critically at course completion. Results of this study demonstrated that the online theory course design contributed to improving critical thinking skills and student's perceived CT skill development as applicable to their future professional practice. In a focus group, eight students identified four effective course design features that contributed to their CT skill development: highly structured learning, timely feedback from instructor, repetition of assignments, and active engagement with the material.
Automating the expert consensus paradigm for robust lung tissue classification
NASA Astrophysics Data System (ADS)
Rajagopalan, Srinivasan; Karwoski, Ronald A.; Raghunath, Sushravya; Bartholmai, Brian J.; Robb, Richard A.
2012-03-01
Clinicians confirm the efficacy of dynamic multidisciplinary interactions in diagnosing Lung disease/wellness from CT scans. However, routine clinical practice cannot readily accomodate such interactions. Current schemes for automating lung tissue classification are based on a single elusive disease differentiating metric; this undermines their reliability in routine diagnosis. We propose a computational workflow that uses a collection (#: 15) of probability density functions (pdf)-based similarity metrics to automatically cluster pattern-specific (#patterns: 5) volumes of interest (#VOI: 976) extracted from the lung CT scans of 14 patients. The resultant clusters are refined for intra-partition compactness and subsequently aggregated into a super cluster using a cluster ensemble technique. The super clusters were validated against the consensus agreement of four clinical experts. The aggregations correlated strongly with expert consensus. By effectively mimicking the expertise of physicians, the proposed workflow could make automation of lung tissue classification a clinical reality.
Segmenting human from photo images based on a coarse-to-fine scheme.
Lu, Huchuan; Fang, Guoliang; Shao, Xinqing; Li, Xuelong
2012-06-01
Human segmentation in photo images is a challenging and important problem that finds numerous applications ranging from album making and photo classification to image retrieval. Previous works on human segmentation usually demand a time-consuming training phase for complex shape-matching processes. In this paper, we propose a straightforward framework to automatically recover human bodies from color photos. Employing a coarse-to-fine strategy, we first detect a coarse torso (CT) using the multicue CT detection algorithm and then extract the accurate region of the upper body. Then, an iterative multiple oblique histogram algorithm is presented to accurately recover the lower body based on human kinematics. The performance of our algorithm is evaluated on our own data set (contains 197 images with human body region ground truth data), VOC 2006, and the 2010 data set. Experimental results demonstrate the merits of the proposed method in segmenting a person with various poses.
Efficient and robust model-to-image alignment using 3D scale-invariant features.
Toews, Matthew; Wells, William M
2013-04-01
This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.
Automated detection of pulmonary nodules in CT images with support vector machines
NASA Astrophysics Data System (ADS)
Liu, Lu; Liu, Wanyu; Sun, Xiaoming
2008-10-01
Many methods have been proposed to avoid radiologists fail to diagnose small pulmonary nodules. Recently, support vector machines (SVMs) had received an increasing attention for pattern recognition. In this paper, we present a computerized system aimed at pulmonary nodules detection; it identifies the lung field, extracts a set of candidate regions with a high sensitivity ratio and then classifies candidates by the use of SVMs. The Computer Aided Diagnosis (CAD) system presented in this paper supports the diagnosis of pulmonary nodules from Computed Tomography (CT) images as inflammation, tuberculoma, granuloma..sclerosing hemangioma, and malignant tumor. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of SVMs classifiers. The achieved classification performance was 100%, 92.75% and 90.23% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.
Efficient and Robust Model-to-Image Alignment using 3D Scale-Invariant Features
Toews, Matthew; Wells, William M.
2013-01-01
This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a-posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. PMID:23265799
Robust hepatic vessel segmentation using multi deep convolution network
NASA Astrophysics Data System (ADS)
Kitrungrotsakul, Titinunt; Han, Xian-Hua; Iwamoto, Yutaro; Foruzan, Amir Hossein; Lin, Lanfen; Chen, Yen-Wei
2017-03-01
Extraction of blood vessels of the organ is a challenging task in the area of medical image processing. It is really difficult to get accurate vessel segmentation results even with manually labeling by human being. The difficulty of vessels segmentation is the complicated structure of blood vessels and its large variations that make them hard to recognize. In this paper, we present deep artificial neural network architecture to automatically segment the hepatic vessels from computed tomography (CT) image. We proposed novel deep neural network (DNN) architecture for vessel segmentation from a medical CT volume, which consists of three deep convolution neural networks to extract features from difference planes of CT data. The three networks have share features at the first convolution layer but will separately learn their own features in the second layer. All three networks will join again at the top layer. To validate effectiveness and efficiency of our proposed method, we conduct experiments on 12 CT volumes which training data are randomly generate from 5 CT volumes and 7 using for test. Our network can yield an average dice coefficient 0.830, while 3D deep convolution neural network can yield around 0.7 and multi-scale can yield only 0.6.
Dual-energy micro-CT imaging for differentiation of iodine- and gold-based nanoparticles
NASA Astrophysics Data System (ADS)
Badea, C. T.; Johnston, S. M.; Qi, Y.; Ghaghada, K.; Johnson, G. A.
2011-03-01
Spectral CT imaging is expected to play a major role in the diagnostic arena as it provides material decomposition on an elemental basis. One fascinating possibility is the ability to discriminate multiple contrast agents targeting different biological sites. We investigate the feasibility of dual energy micro-CT for discrimination of iodine (I) and gold (Au) contrast agents when simultaneously present in the body. Simulations and experiments were performed to measure the CT enhancement for I and Au over a range of voltages from 40-to-150 kVp using a dual source micro-CT system. The selected voltages for dual energy micro-CT imaging of Au and I were 40 kVp and 80 kVp. On a massconcentration basis, the relative average enhancement of Au to I was 2.75 at 40 kVp and 1.58 at 80 kVp. We have demonstrated the method in a preclinical model of colon cancer to differentiate vascular architecture and extravasation. The concentration maps of Au and I allow quantitative measure of the bio-distribution of both agents. In conclusion, dual energy micro-CT can be used to discriminate probes containing I and Au with immediate impact in pre-clinical research.
Computed tomography of radioactive objects and materials
NASA Astrophysics Data System (ADS)
Sawicka, B. D.; Murphy, R. V.; Tosello, G.; Reynolds, P. W.; Romaniszyn, T.
1990-12-01
Computed tomography (CT) has been performed on a number of radioactive objects and materials. Several unique technical problems are associated with CT of radioactive specimens. These include general safety considerations, techniques to reduce background-radiation effects on CT images and selection criteria for the CT source to permit object penetration and to reveal accurate values of material density. In the present paper, three groups of experiments will be described, for objects with low, medium and high levels of radioactivity. CT studies on radioactive specimens will be presented. They include the following: (1) examination of individual ceramic reactor-fuel (uranium dioxide) pellets, (2) examination of fuel samples from the Three Mile Island reactor, (3) examination of a CANDU (CANada Deuterium Uraniun: registered trademark) nuclear-fuel bundle which underwent a simulated loss-of-coolant accident resulting in high-temperature damage and (4) examination of a PWR nuclear-reactor fuel assembly.
NASA Astrophysics Data System (ADS)
Lee, Donghoon; Kim, Ye-seul; Choi, Sunghoon; Lee, Haenghwa; Jo, Byungdu; Choi, Seungyeon; Shin, Jungwook; Kim, Hee-Joung
2017-03-01
The chest digital tomosynthesis(CDT) is recently developed medical device that has several advantage for diagnosing lung disease. For example, CDT provides depth information with relatively low radiation dose compared to computed tomography (CT). However, a major problem with CDT is the image artifacts associated with data incompleteness resulting from limited angle data acquisition in CDT geometry. For this reason, the sensitivity of lung disease was not clear compared to CT. In this study, to improve sensitivity of lung disease detection in CDT, we developed computer aided diagnosis (CAD) systems based on machine learning. For design CAD systems, we used 100 cases of lung nodules cropped images and 100 cases of normal lesion cropped images acquired by lung man phantoms and proto type CDT. We used machine learning techniques based on support vector machine and Gabor filter. The Gabor filter was used for extracting characteristics of lung nodules and we compared performance of feature extraction of Gabor filter with various scale and orientation parameters. We used 3, 4, 5 scales and 4, 6, 8 orientations. After extracting features, support vector machine (SVM) was used for classifying feature of lesions. The linear, polynomial and Gaussian kernels of SVM were compared to decide the best SVM conditions for CDT reconstruction images. The results of CAD system with machine learning showed the capability of automatically lung lesion detection. Furthermore detection performance was the best when Gabor filter with 5 scale and 8 orientation and SVM with Gaussian kernel were used. In conclusion, our suggested CAD system showed improving sensitivity of lung lesion detection in CDT and decide Gabor filter and SVM conditions to achieve higher detection performance of our developed CAD system for CDT.
Computer-Aided Diagnostic (CAD) Scheme by Use of Contralateral Subtraction Technique
NASA Astrophysics Data System (ADS)
Nagashima, Hiroyuki; Harakawa, Tetsumi
We developed a computer-aided diagnostic (CAD) scheme for detection of subtle image findings of acute cerebral infarction in brain computed tomography (CT) by using a contralateral subtraction technique. In our computerized scheme, the lateral inclination of image was first corrected automatically by rotating and shifting. The contralateral subtraction image was then derived by subtraction of reversed image from original image. Initial candidates for acute cerebral infarctions were identified using the multiple-thresholding and image filtering techniques. As the 1st step for removing false positive candidates, fourteen image features were extracted in each of the initial candidates. Halfway candidates were detected by applying the rule-based test with these image features. At the 2nd step, five image features were extracted using the overlapping scale with halfway candidates in interest slice and upper/lower slice image. Finally, acute cerebral infarction candidates were detected by applying the rule-based test with five image features. The sensitivity in the detection for 74 training cases was 97.4% with 3.7 false positives per image. The performance of CAD scheme for 44 testing cases had an approximate result to training cases. Our CAD scheme using the contralateral subtraction technique can reveal suspected image findings of acute cerebral infarctions in CT images.
WE-AB-BRA-12: Post-Implant Dosimetry in Prostate Brachytherapy by X-Ray and MRI Fusion
DOE Office of Scientific and Technical Information (OSTI.GOV)
Park, S; Song, D; Lee, J
Purpose: For post-implant dosimetric assessment after prostate brachytherapy, CT-MR fusion approach has been advocated due to the superior accuracy on both seeds localization and soft tissue delineation. However, CT deposits additional radiation to the patient, and seed identification in CT requires manual review and correction. In this study, we propose an accurate, low-dose, and cost-effective post-implant dosimetry approach based on X-ray and MRI. Methods: Implanted seeds are reconstructed using only three X-ray fluoroscopy images by solving a combinatorial optimization problem. The reconstructed seeds are then registered to MR images using an intensity-based points-to-volume registration. MR images are first pre-processed bymore » geometric and Gaussian filtering, yielding smooth candidate seed-only images. To accommodate potential soft tissue deformation, our registration is performed in two steps, an initial affine followed by local deformable registrations. An evolutionary optimizer in conjunction with a points-to-volume similarity metric is used for the affine registration. Local prostate deformation and seed migration are then adjusted by the deformable registration step with external and internal force constraints. Results: We tested our algorithm on twenty patient data sets. For quantitative evaluation, we obtained ground truth seed positions by fusing the post-implant CT-MR images. Seeds were semi-automatically extracted from CT and manually corrected and then registered to the MR images. Target registration error (TRE) was computed by measuring the Euclidean distances from the ground truth to the closest registered X-ray seeds. The overall TREs (mean±standard deviation in mm) are 1.6±1.1 (affine) and 1.3±0.8 (affine+deformable). The overall computation takes less than 1 minute. Conclusion: It has been reported that the CT-based seed localization error is ∼1.6mm and the seed localization uncertainty of 2mm results in less than 5% deviation of prostate D90. The average error of 1.3mm with our system outperforms the CT-based approach and is considered well within the clinically acceptable limit. Supported in part by NIH/NCI grant 5R01CA151395. The X-ray-based implant reconstruction method (US patent No. 8,233,686) was licensed to Acoustic MedSystems Inc.« less
TU-CD-BRB-01: Normal Lung CT Texture Features Improve Predictive Models for Radiation Pneumonitis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krafft, S; The University of Texas Graduate School of Biomedical Sciences, Houston, TX; Briere, T
2015-06-15
Purpose: Existing normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) traditionally rely on dosimetric and clinical data but are limited in terms of performance and generalizability. Extraction of pre-treatment image features provides a potential new category of data that can improve NTCP models for RP. We consider quantitative measures of total lung CT intensity and texture in a framework for prediction of RP. Methods: Available clinical and dosimetric data was collected for 198 NSCLC patients treated with definitive radiotherapy. Intensity- and texture-based image features were extracted from the T50 phase of the 4D-CT acquired for treatment planning. Amore » total of 3888 features (15 clinical, 175 dosimetric, and 3698 image features) were gathered and considered candidate predictors for modeling of RP grade≥3. A baseline logistic regression model with mean lung dose (MLD) was first considered. Additionally, a least absolute shrinkage and selection operator (LASSO) logistic regression was applied to the set of clinical and dosimetric features, and subsequently to the full set of clinical, dosimetric, and image features. Model performance was assessed by comparing area under the curve (AUC). Results: A simple logistic fit of MLD was an inadequate model of the data (AUC∼0.5). Including clinical and dosimetric parameters within the framework of the LASSO resulted in improved performance (AUC=0.648). Analysis of the full cohort of clinical, dosimetric, and image features provided further and significant improvement in model performance (AUC=0.727). Conclusions: To achieve significant gains in predictive modeling of RP, new categories of data should be considered in addition to clinical and dosimetric features. We have successfully incorporated CT image features into a framework for modeling RP and have demonstrated improved predictive performance. Validation and further investigation of CT image features in the context of RP NTCP modeling is warranted. This work was supported by the Rosalie B. Hite Fellowship in Cancer research awarded to SPK.« less
Minamimoto, Ryogo; Fayad, Luis; Advani, Ranjana; Vose, Julie; Macapinlac, Homer; Meza, Jane; Hankins, Jordan; Mottaghy, Felix; Juweid, Malik
2016-01-01
Purpose To compare the performance characteristics of interim fluorine 18 (18F) fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) (after two cycles of chemotherapy) by using the most prominent standardized interpretive criteria (including International Harmonization Project [IHP] criteria, European Organization for Research and Treatment of Cancer [EORTC] criteria, and PET Response Criteria in Solid Tumors (PERCIST) versus those of interim 18F fluorothymidine (FLT) PET/CT and simple visual interpretation. Materials and Methods This HIPAA-compliant prospective study was approved by the institutional review boards, and written informed consent was obtained. Patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL) underwent both FLT and FDG PET/CT 18–24 days after two cycles of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone or rituximab, etoposide, prednisone, vincristine, cyclophosphamide, and doxorubicin. For FDG PET/CT interpretation, IHP criteria, EORTC criteria, PERCIST, Deauville criteria, standardized uptake value, total lesion glycolysis, and metabolic tumor volume were used. FLT PET/CT images were interpreted with visual assessment by two reviewers in consensus. The interim (after cycle 2) FDG and FLT PET/CT studies were then compared with the end-of-treatment FDG PET/CT studies to determine which interim examination and/or criteria best predicted the result after six cycles of chemotherapy. Results From November 2011 to May 2014, there were 60 potential patients for inclusion, of whom 46 patients (24 men [mean age, 60.9 years ± 13.7; range, 28–78 years] and 22 women [mean age, 57.2 years ± 13.4; range, 25–76 years]) fulfilled the criteria. Thirty-four patients had complete response, and 12 had residual disease at the end of treatment. FLT PET/CT had a significantly higher positive predictive value (PPV) (91%) in predicting residual disease than did any FDG PET/CT interpretation method (42%–46%). No difference in negative predictive value (NPV) was found between FLT PET/CT (94%) and FDG PET/CT (82%–95%), regardless of the interpretive criteria used. FLT PET/CT showed statistically higher (P < .001–.008) or similar NPVs than did FDG PET/CT. Conclusion Early interim FLT PET/CT had a significantly higher PPV than standardized FDG PET/CT–based interpretation for therapeutic response assessment in DLBCL. © RSNA, 2016 Online supplemental material is available for this article. PMID:26854705
Park, Sang Kyu; Kim, Jin Hong; Ohto, Tatsuhiko; Yamada, Ryo; Jones, Andrew O F; Whang, Dong Ryeol; Cho, Illhun; Oh, Sangyoon; Hong, Seung Hwa; Kwon, Ji Eon; Kim, Jong H; Olivier, Yoann; Fischer, Roland; Resel, Roland; Gierschner, Johannes; Tada, Hirokazu; Park, Soo Young
2017-09-01
A new 2:1 donor (D):acceptor (A) mixed-stacked charge-transfer (CT) cocrystal comprising isometrically structured dicyanodistyrylbenzene-based D and A molecules is designed and synthesized. Uniform 2D-type morphology is manifested by the exquisite interplay of intermolecular interactions. In addition to its appealing structural features, unique optoelectronic properties are unveiled. Exceptionally high photoluminescence quantum yield (Φ F ≈ 60%) is realized by non-negligible oscillator strength of the S 1 transition, and rigidified 2D-type structure. Moreover, this luminescent 2D-type CT crystal exhibits balanced ambipolar transport (µ h and µ e of ≈10 -4 cm 2 V -1 s -1 ). As a consequence of such unique optoelectronic characteristics, the first CT electroluminescence is demonstrated in a single active-layered organic light-emitting transistor (OLET) device. The external quantum efficiency of this OLET is as high as 1.5% to suggest a promising potential of luminescent mixed-stacked CT cocrystals in OLET applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
NASA Astrophysics Data System (ADS)
Taasti, Vicki T.; Michalak, Gregory J.; Hansen, David C.; Deisher, Amanda J.; Kruse, Jon J.; Krauss, Bernhard; Muren, Ludvig P.; Petersen, Jørgen B. B.; McCollough, Cynthia H.
2018-01-01
Dual energy CT (DECT) has been shown, in theoretical and phantom studies, to improve the stopping power ratio (SPR) determination used for proton treatment planning compared to the use of single energy CT (SECT). However, it has not been shown that this also extends to organic tissues. The purpose of this study was therefore to investigate the accuracy of SPR estimation for fresh pork and beef tissue samples used as surrogates of human tissues. The reference SPRs for fourteen tissue samples, which included fat, muscle and femur bone, were measured using proton pencil beams. The tissue samples were subsequently CT scanned using four different scanners with different dual energy acquisition modes, giving in total six DECT-based SPR estimations for each sample. The SPR was estimated using a proprietary algorithm (syngo.via DE Rho/Z Maps, Siemens Healthcare, Forchheim, Germany) for extracting the electron density and the effective atomic number. SECT images were also acquired and SECT-based SPR estimations were performed using a clinical Hounsfield look-up table. The mean and standard deviation of the SPR over large volume-of-interests were calculated. For the six different DECT acquisition methods, the root-mean-square errors (RMSEs) for the SPR estimates over all tissue samples were between 0.9% and 1.5%. For the SECT-based SPR estimation the RMSE was 2.8%. For one DECT acquisition method, a positive bias was seen in the SPR estimates, having a mean error of 1.3%. The largest errors were found in the very dense cortical bone from a beef femur. This study confirms the advantages of DECT-based SPR estimation although good results were also obtained using SECT for most tissues.
Radiomics biomarkers for accurate tumor progression prediction of oropharyngeal cancer
NASA Astrophysics Data System (ADS)
Hadjiiski, Lubomir; Chan, Heang-Ping; Cha, Kenny H.; Srinivasan, Ashok; Wei, Jun; Zhou, Chuan; Prince, Mark; Papagerakis, Silvana
2017-03-01
Accurate tumor progression prediction for oropharyngeal cancers is crucial for identifying patients who would best be treated with optimized treatment and therefore minimize the risk of under- or over-treatment. An objective decision support system that can merge the available radiomics, histopathologic and molecular biomarkers in a predictive model based on statistical outcomes of previous cases and machine learning may assist clinicians in making more accurate assessment of oropharyngeal tumor progression. In this study, we evaluated the feasibility of developing individual and combined predictive models based on quantitative image analysis from radiomics, histopathology and molecular biomarkers for oropharyngeal tumor progression prediction. With IRB approval, 31, 84, and 127 patients with head and neck CT (CT-HN), tumor tissue microarrays (TMAs) and molecular biomarker expressions, respectively, were collected. For 8 of the patients all 3 types of biomarkers were available and they were sequestered in a test set. The CT-HN lesions were automatically segmented using our level sets based method. Morphological, texture and molecular based features were extracted from CT-HN and TMA images, and selected features were merged by a neural network. The classification accuracy was quantified using the area under the ROC curve (AUC). Test AUCs of 0.87, 0.74, and 0.71 were obtained with the individual predictive models based on radiomics, histopathologic, and molecular features, respectively. Combining the radiomics and molecular models increased the test AUC to 0.90. Combining all 3 models increased the test AUC further to 0.94. This preliminary study demonstrates that the individual domains of biomarkers are useful and the integrated multi-domain approach is most promising for tumor progression prediction.
NASA Astrophysics Data System (ADS)
Li, Zhengji; Teng, Qizhi; He, Xiaohai; Yue, Guihua; Wang, Zhengyong
2017-09-01
The parameter evaluation of reservoir rocks can help us to identify components and calculate the permeability and other parameters, and it plays an important role in the petroleum industry. Until now, computed tomography (CT) has remained an irreplaceable way to acquire the microstructure of reservoir rocks. During the evaluation and analysis, large samples and high-resolution images are required in order to obtain accurate results. Owing to the inherent limitations of CT, however, a large field of view results in low-resolution images, and high-resolution images entail a smaller field of view. Our method is a promising solution to these data collection limitations. In this study, a framework for sparse representation-based 3D volumetric super-resolution is proposed to enhance the resolution of 3D voxel images of reservoirs scanned with CT. A single reservoir structure and its downgraded model are divided into a large number of 3D cubes of voxel pairs and these cube pairs are used to calculate two overcomplete dictionaries and the sparse-representation coefficients in order to estimate the high frequency component. Future more, to better result, a new feature extract method with combine BM4D together with Laplacian filter are introduced. In addition, we conducted a visual evaluation of the method, and used the PSNR and FSIM to evaluate it qualitatively.
Annaratone, Laura; Volante, Marco; Asioli, Sofia; Rangel, Nelson; Bussolati, Gianni
2013-06-01
The aim of this study was to assess the suitability of using real-time quantitative PCR (RT-qPCR) to characterize neuroendocrine (NE) tumors of the pancreas. For a series of tumors, we evaluated several genes of interest, and the data were matched with the "classical" immunohistochemical (IHC) features. In 21 cases, we extracted RNA from formalin-fixed paraffin-embedded (FFPE) blocks, and in nine cases, we also extracted RNA from fresh-frozen tissue. The RT-qPCR procedure was performed using two sets of customized arrays. The test using the first set, covering 96 genes of interest, was focused on assessing the feasibility of the procedure, and the results were used to select 18 genes indicative of NE differentiation, clinical behavior, and therapeutic responsiveness for use in the second set of arrays. Threshold cycle (Ct) values were used to calculate the fold-changes in gene expression using the 2-∆∆Ct method. Statistical procedures were used to analyze the results, which were matched with the IHC and follow-up data. Material from fresh-frozen samples performed better in terms of the level of amplification, but acceptable and concordant results were also obtained from FFPE samples. In addition, high concordance was observed between the mRNA and protein expression levels of somatostatin receptor type 2A (R = 0.52, p = 0.016). Genes associated with NE differentiation, as well as the gastrin-releasing peptide receptor and O-6-methylguanine-DNA methyltransferase genes, were underexpressed, whereas angiogenesis-associated markers (CDH13 and SLIT2) were overexpressed in tissues with malignant behavior. The RT-qPCR procedure is practical and feasible in economic terms for the characterization of NE tumors of the pancreas and can complement morphological and IHC-based evaluations. Thus, the results of the RT-qPCR procedure might offer an objective basis for therapeutic choices.
Anzai, Yoshimi; Heilbrun, Marta E; Haas, Derek; Boi, Luca; Moshre, Kirk; Minoshima, Satoshi; Kaplan, Robert; Lee, Vivian S
2017-02-01
The lack of understanding of the real costs (not charge) of delivering healthcare services poses tremendous challenges in the containment of healthcare costs. In this study, we applied an established cost accounting method, the time-driven activity-based costing (TDABC), to assess the costs of performing an abdomen and pelvis computed tomography (AP CT) in an academic radiology department and identified opportunities for improved efficiency in the delivery of this service. The study was exempt from an institutional review board approval. TDABC utilizes process mapping tools from industrial engineering and activity-based costing. The process map outlines every step of discrete activity and duration of use of clinical resources, personnel, and equipment. By multiplying the cost per unit of capacity by the required task time for each step, and summing each component cost, the overall costs of AP CT is determined for patients in three settings, inpatient (IP), outpatient (OP), and emergency departments (ED). The component costs to deliver an AP CT study were as follows: radiologist interpretation: 40.1%; other personnel (scheduler, technologist, nurse, pharmacist, and transporter): 39.6%; materials: 13.9%; and space and equipment: 6.4%. The cost of performing CT was 13% higher for ED patients and 31% higher for inpatients (IP), as compared to that for OP. The difference in cost was mostly due to non-radiologist personnel costs. Approximately 80% of the direct costs of AP CT to the academic medical center are related to labor. Potential opportunities to reduce the costs include increasing the efficiency of utilization of CT, substituting lower cost resources when appropriate, and streamlining the ordering system to clarify medical necessity and clinical indications. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
TU-G-204-02: Automatic Sclerotic Bone Metastases Detection in the Pelvic Region From Dual Energy CT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fehr, D; Schmidtlein, C; Hwang, S
Purpose: To automatically detect sclerotic bone metastases in the pelvic region using dual energy computed tomography (DECT). Methods: We developed a two stage algorithm to automatically detect sclerotic bone metastases in the pelvis from DECT for patients with multiple bone metastatic lesions and with hip implants. The first stage consists of extracting the bone and marrow regions by using a support vector machine (SVM) classifier. We employed a novel representation of the DECT images using multi-material decomposition, which represents each voxel as a mixture of different physical materials (e.g. bone+water+fat). Following the extraction of bone and marrow, in the secondmore » stage, a bi -histogram equalization method was employed to enhance the contrast to reveal the bone metastases. Next, meanshift segmentation was performed to separate the voxels by their intensity levels. Finally, shape-based filtering was performed to extract the possible locations of the metastatic lesions using multiple shape criteria. We used the following shape parameters: area, eccentricity, major and minor axis, perimeter and skeleton. Results: A radiologist with several years of experience with DECT manually labeled 64 regions consisting of metastatic lesions from 10 different patients. However, the patients had many more metastasic lesions throughout the pelvis. Our method correctly identified 46 of the marked 64 regions (72%). In addition, our method also identified several other lesions, which can then be validated by the radiologist. The missed lesions were typically very large elongated regions consisting of several islands of very small (<4mm) lesions. Conclusion: We developed an algorithm to automatically detect sclerotic lesions in the pelvic region from DECT. Preliminary assessment shows that our algorithm generated lesions agreeing with the radiologist generated candidate regions. Furthermore, our method reveals additional lesions that can be inspected by the radiologist, thereby, reducing radiologist effort in identifying all the lesions with poor contrast from the DECT images.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Teramoto, Atsushi, E-mail: teramoto@fujita-hu.ac.jp; Fujita, Hiroshi; Yamamuro, Osamu
Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using anmore » active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules using PET/CT images.« less
Automatic liver contouring for radiotherapy treatment planning
NASA Astrophysics Data System (ADS)
Li, Dengwang; Liu, Li; Kapp, Daniel S.; Xing, Lei
2015-09-01
To develop automatic and efficient liver contouring software for planning 3D-CT and four-dimensional computed tomography (4D-CT) for application in clinical radiation therapy treatment planning systems. The algorithm comprises three steps for overcoming the challenge of similar intensities between the liver region and its surrounding tissues. First, the total variation model with the L1 norm (TV-L1), which has the characteristic of multi-scale decomposition and an edge-preserving property, is used for removing the surrounding muscles and tissues. Second, an improved level set model that contains both global and local energy functions is utilized to extract liver contour information sequentially. In the global energy function, the local correlation coefficient (LCC) is constructed based on the gray level co-occurrence matrix both of the initial liver region and the background region. The LCC can calculate the correlation of a pixel with the foreground and background regions, respectively. The LCC is combined with intensity distribution models to classify pixels during the evolutionary process of the level set based method. The obtained liver contour is used as the candidate liver region for the following step. In the third step, voxel-based texture characterization is employed for refining the liver region and obtaining the final liver contours. The proposed method was validated based on the planning CT images of a group of 25 patients undergoing radiation therapy treatment planning. These included ten lung cancer patients with normal appearing livers and ten patients with hepatocellular carcinoma or liver metastases. The method was also tested on abdominal 4D-CT images of a group of five patients with hepatocellular carcinoma or liver metastases. The false positive volume percentage, the false negative volume percentage, and the dice similarity coefficient between liver contours obtained by a developed algorithm and a current standard delineated by the expert group are on an average 2.15-2.57%, 2.96-3.23%, and 91.01-97.21% for the CT images with normal appearing livers, 2.28-3.62%, 3.15-4.33%, and 86.14-93.53% for the CT images with hepatocellular carcinoma or liver metastases, and 2.37-3.96%, 3.25-4.57%, and 82.23-89.44% for the 4D-CT images also with hepatocellular carcinoma or liver metastases, respectively. The proposed three-step method can achieve efficient automatic liver contouring for planning CT and 4D-CT images with follow-up treatment planning and should find widespread applications in future treatment planning systems.
X-ray micro-CT measurement of large parts at very low temperature
NASA Astrophysics Data System (ADS)
Koutecký, T.; Zikmund, T.; Glittová, D.; Paloušek, D.; Živčák, J.; Kaiser, J.
2017-03-01
At present, the automotive industry, along with other industries, has increasing demands on accuracy of produced parts and assemblies. Besides the regular dimensional and geometrical inspection, in some cases, also a verification at very low temperatures is required. X-ray computed tomography (CT), as a tool for non-destructive testing, is able to examine samples and then determine dimensions for strictly stable temperature conditions necessary for the stability of the CT system. Until now, no system that allows scanning of samples larger than a few millimeters at temperatures much below 0 °C has been presented. This paper presents a cooling system for CT imaging of parts with length up to 300 mm at the extreme temperature conditions of -40 °C, which are based on automotive industry requests. It describes the equipment and conditions under which it is possible to achieve a temperature stability of samples at low temperatures, while keeping an independent temperature regulation of the CT system. The presented system uses a standard industrial CT device and a newly designed cooling stage with passive cooling based on phase-change material. The system is demonstrated on the measurement of plastic part (car door handle) at temperatures of -40 °C and 20 °C. The paper also presents the method of how to interpret the thermal changes using tools of the commercial software VGStudio MAX (Volume Graphics GmbH, Germany).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Guckenberger, Matthias; Wilbert, Juergen; Krieger, Thomas
2009-06-01
Purpose: To evaluate the accuracy of direct reconstruction of mid-ventilation and peak-phase four-dimensional (4D) computed tomography (CT) frames based on the external breathing signal. Methods and Materials: For 11 patients with 15 pulmonary targets, a respiration-correlated CT study (4D CT) was acquired for treatment planning. After retrospective time-based sorting of raw projection data and reconstruction of eight CT frames equally distributed over the breathing cycle, mean tumor position (P{sub mean}), mid-ventilation frame, and breathing motion were evaluated based on the internal tumor trajectory. Analysis of the external breathing signal (pressure sensor around abdomen) with amplitude-based sorting of projections was performedmore » for direct reconstruction of the mid-ventilation frame and frames at peak phases of the breathing cycle. Results: On the basis of the eight 4D CT frames equally spaced in time, tumor motion was largest in the craniocaudal direction, with 12 {+-} 7 mm on average. Tumor motion between the two frames reconstructed at peak phases was not different in the craniocaudal and anterior-posterior directions but was systematically smaller in the left-right direction by 1 mm on average. The 3-dimensional distance between P{sub mean} and the tumor position in the mid-ventilation frame based on the internal tumor trajectory was 1.2 {+-} 1 mm. Reconstruction of the mid-ventilation frame at the mean amplitude position of the external breathing signal resulted in tumor positions 2.0 {+-} 1.1 mm distant from P{sub mean}. Breathing-induced motion artifacts in mid-ventilation frames caused negligible changes in tumor volume and shape. Conclusions: Direct reconstruction of the mid-ventilation frame and frames at peak phases based on the external breathing signal was reliable. This makes the reconstruction of only three 4D CT frames sufficient for application of the mid-ventilation technique in clinical practice.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cai Jing; Read, Paul W.; Baisden, Joseph M.
Purpose: To evaluate the error in four-dimensional computed tomography (4D-CT) maximal intensity projection (MIP)-based lung tumor internal target volume determination using a simulation method based on dynamic magnetic resonance imaging (dMRI). Methods and Materials: Eight healthy volunteers and six lung tumor patients underwent a 5-min MRI scan in the sagittal plane to acquire dynamic images of lung motion. A MATLAB program was written to generate re-sorted dMRI using 4D-CT acquisition methods (RedCAM) by segmenting and rebinning the MRI scans. The maximal intensity projection images were generated from RedCAM and dMRI, and the errors in the MIP-based internal target area (ITA)more » from RedCAM ({epsilon}), compared with those from dMRI, were determined and correlated with the subjects' respiratory variability ({nu}). Results: Maximal intensity projection-based ITAs from RedCAM were comparatively smaller than those from dMRI in both phantom studies ({epsilon} = -21.64% {+-} 8.23%) and lung tumor patient studies ({epsilon} = -20.31% {+-} 11.36%). The errors in MIP-based ITA from RedCAM correlated linearly ({epsilon} = -5.13{nu} - 6.71, r{sup 2} = 0.76) with the subjects' respiratory variability. Conclusions: Because of the low temporal resolution and retrospective re-sorting, 4D-CT might not accurately depict the excursion of a moving tumor. Using a 4D-CT MIP image to define the internal target volume might therefore cause underdosing and an increased risk of subsequent treatment failure. Patient-specific respiratory variability might also be a useful predictor of the 4D-CT-induced error in MIP-based internal target volume determination.« less