Automated recognition of microcalcification clusters in mammograms

NASA Astrophysics Data System (ADS)

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

1993-07-01

The widespread and increasing use of mammographic screening for early breast cancer detection is placing a significant strain on clinical radiologists. Large numbers of radiographic films have to be visually interpreted in fine detail to determine the subtle hallmarks of cancer that may be present. We developed an algorithm for detecting microcalcification clusters, the most common and useful signs of early, potentially curable breast cancer. We describe this algorithm, which utilizes contour map representations of digitized mammographic films, and discuss its benefits in overcoming difficulties often encountered in algorithmic approaches to radiographic image processing. We present experimental analyses of mammographic films employing this contour-based algorithm and discuss practical issues relevant to its use in an automated film interpretation instrument.

Diagnostic power of diffuse reflectance spectroscopy for targeted detection of breast lesions with microcalcifications

PubMed Central

Soares, Jaqueline S.; Barman, Ishan; Dingari, Narahara Chari; Volynskaya, Zoya; Liu, Wendy; Klein, Nina; Plecha, Donna; Dasari, Ramachandra R.; Fitzmaurice, Maryann

2013-01-01

Microcalcifications geographically target the location of abnormalities within the breast and are of critical importance in breast cancer diagnosis. However, despite stereotactic guidance, core needle biopsy fails to retrieve microcalcifications in up to 15% of patients. Here, we introduce an approach based on diffuse reflectance spectroscopy for detection of microcalcifications that focuses on variations in optical absorption stemming from the calcified clusters and the associated cross-linking molecules. In this study, diffuse reflectance spectra are acquired ex vivo from 203 sites in fresh biopsy tissue cores from 23 patients undergoing stereotactic breast needle biopsies. By correlating the spectra with the corresponding radiographic and histologic assessment, we have developed a support vector machine-derived decision algorithm, which shows high diagnostic power (positive predictive value and negative predictive value of 97% and 88%, respectively) for diagnosis of lesions with microcalcifications. We further show that these results are robust and not due to any spurious correlations. We attribute our findings to the presence of proteins (such as elastin), and desmosine and isodesmosine cross-linkers in the microcalcifications. It is important to note that the performance of the diffuse reflectance decision algorithm is comparable to one derived from the corresponding Raman spectra, and the considerably higher intensity of the reflectance signal enables the detection of the targeted lesions in a fraction of the spectral acquisition time. Our findings create a unique landscape for spectroscopic validation of breast core needle biopsy for detection of microcalcifications that can substantially improve the likelihood of an adequate, diagnostic biopsy in the first attempt. PMID:23267090

The impact of digital mammography on screening a young cohort of women for breast cancer in an urban specialist breast unit.

PubMed

Perry, Nicholas M; Patani, N; Milner, S E; Pinker, K; Mokbel, K; Allgood, P C; Duffy, S W

2011-04-01

To compare the diagnostic performance of full-field digital mammography (FFDM) with screen-film mammography (SFM) in a corporate screening programme including younger women. Data were available on 14,946 screening episodes, 5010 FFDM and 9936 SFM. Formal analysis was by logistic regression, adjusting for age and calendar year. FFDM is compared with SFM with reference to cancer detection rates, cancers presenting as clustering microcalcifications, recall rates and PPV of recall. Overall detection rates were 6.4 cancers per thousand screens for FFDM and 2.8 per thousand for SFM (p < 0.001). In women aged 50+ cancer detection was significantly higher for FFDM at 8.6 per thousand vs. 4.0 per thousand, (p = 0.002). In women <50, cancer detection was also significantly higher for FFDM at 4.3 per thousand vs. 1.4 per thousand, (p = 0.02). Cancers detected as clustering microcalcifications increased from 0.4 per thousand with SFM to 2.0 per thousand with FFDM. Rates of assessment recall were higher for FFDM (7.3% vs. 5.0%, p < 0.001). FFDM provided a higher PPV for assessment recall, (32 cancers/364 recalls, 8.8%) than SFM, (28 cancers/493 recalls, 5.7%). Cancer detection rates were significantly higher for FFDM than for SFM, especially for women <50, and cancers detected as clustering microcalcifications.

Columnar cell lesions of the breast: radiological features and histological correlation.

PubMed

Elif, Aktas; Burcu, Sahin; Nazan, Ciledag; Sumru, Cosar Zehra; Kemal, Arda Niyazi

2015-06-01

This study aimed at investigating the characteristic imaging findings of the columnar cell lesions (CCLs) of the breast via mammography (MG), ultrasonography (US), and magnetic resonance imaging (MRI). The MG, US and MRI findings of 72 patients with histopathological diagnosis of CCLs were retrospectively evaluated. Histopathologically, the CCLs were divided into those with and without atypia; the radiological findings of these two groups were compared with a Chi-square test. Sixty-nine patients underwent stereotaxic biopsy (MG-guided in 50 patients and US-guided in 19 patients) and 3 patients underwent US-guided core needle biopsy; all of these patients were diagnosed with CCLs based on a histological examination. The evaluation of the CCLs in patients that underwent MG-guided stereotaxic biopsy revealed that the most common type of microcalcifications were amorphous-indistinct (52%, n= 26/50) and the most common microcalcification distribution pattern was clustered type (76%, n= 38/50). The ratio of CCLs with atypia was similar in patients with high-risk microcalcifications and in those with benign or intermediate-risk microcalcifications (OR: 1.13, 95% CI: 0.573-2.227, p: 0.475). On the other hand, those patients who underwent US-guided biopsies for the evaluation of CCLs had similar proportions of cystic or solid lesions, posterior acoustic shadowing and contour irregularities whether or not they had atypia (p: 0.584, 0.075, 0.187, respectively). Patients with atypia had a higher number of lesions greater than 1 cm via US as compared to those without atypia, but this difference was not statistically significant (p: 0.06). MRI findings were also similar in patients with and without atypia. MG revealed that clustered distribution patterns and amorphous- indistinct type microcalcifications were more commonly seen in patients with CCLs; however, there was no significant relationship between US or MRI findings and CCLs. In addition, the MG, US and MRI findings were similar in patients with CCLs that did or did not have histopathological characteristics of atypia.

Monte Carlo simulation studies for the determination of microcalcification thickness and glandular ratio through dual-energy mammography

NASA Astrophysics Data System (ADS)

Del Lama, L. S.; Godeli, J.; Poletti, M. E.

2017-08-01

The majority of breast carcinomas can be associated to the presence of calcifications before the development of a mass. However, the overlapping tissues can obscure the visualization of microcalcification clusters due to the reduced contrast-noise ratio (CNR). In order to overcome this complication, one potential solution is the use of the dual-energy (DE) technique, in which two different images are acquired at low (LE) and high (HE) energies or kVp to highlight specific lesions or cancel out tissue background. In this work, the DE features were computationally studied considering simulated acquisitions from a modified PENELOPE Monte Carlo code. The employed irradiation geometry considered typical distances used in digital mammography, a CsI detection system and an updated breast model composed of skin, microcalcifications and glandular and adipose tissues. The breast thickness ranged from 2 to 6 cm with glandularities of 25%, 50% and 75%, where microcalcifications with dimensions from 100 up to 600 μm were positioned. In general, results pointed an efficiency index better than 87% for the microcalcification thicknesses and better than 95% for the glandular ratio. The simulations evaluated in this work can be used to optimize the elements from the DE imaging chain, in order to become a complementary tool for the conventional single-exposure images, especially for the visualization and estimation of calcification thicknesses and glandular ratios.

Performance and role of the breast lesion excision system (BLES) in small clusters of suspicious microcalcifications.

PubMed

Scaperrotta, Gianfranco; Ferranti, Claudio; Capalbo, Emanuela; Paolini, Biagio; Marchesini, Monica; Suman, Laura; Folini, Cristina; Mariani, Luigi; Panizza, Pietro

2016-01-01

To assess the diagnostic performance of the BLES as a biopsy tool in patients with ≤ 1 cm clusters of BIRADS 4 microcalcifications, in order to possibly avoid surgical excision in selected patients. This is a retrospective study of 105 patients undergone to stereotactic breast biopsy with the BLES. It excises a single specimen containing the whole mammographic target, allowing better histological assessment due to preserved architecture. Our case series consists of 41 carcinomas (39%) and 64 benign lesions (61%). Cancer involved the specimen margins in 20/41 cases (48.8%) or was close to them (≤ 1 mm) in 14 cases (34.1%); margins were disease-free in only 7 DCIS (17.1%). At subsequent excision of 39/41 malignant cases, underestimation occurred for 5/32 DCIS (15.6%), residual disease was found in 15/39 cancers (38.5%) and no cancer in 19/39 cases (48.7%). For DCIS cases, no residual disease occurred for 66.7% G1-G2 cases and for 35.3% G3 cases (P=0.1556) as well as in 83.3%, 40.0% and 43.8% cases respectively for negative, close and positive BLES margins (P=0.2576). The BLES is a good option for removal of small clusters of breast microcalcifications, giving better histological interpretation, lower underestimation rates and possibly reducing the need of subsequent surgical excision in selected patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

CADx Mammography

NASA Astrophysics Data System (ADS)

Costaridou, Lena

Although a wide variety of Computer-Aided Diagnosis (CADx) schemes have been proposed across breast imaging modalities, and especially in mammography, research is still ongoing to meet the high performance CADx requirements. In this chapter, methodological contributions to CADx in mammography and adjunct breast imaging modalities are reviewed, as they play a major role in early detection, diagnosis and clinical management of breast cancer. At first, basic terms and definitions are provided. Then, emphasis is given to lesion content derivation, both anatomical and functional, considering only quantitative image features of micro-calcification clusters and masses across modalities. Additionally, two CADx application examples are provided. The first example investigates the effect of segmentation accuracy on micro-calcification cluster morphology derivation in X-ray mammography. The second one demonstrates the efficiency of texture analysis in quantification of enhancement kinetics, related to vascular heterogeneity, for mass classification in dynamic contrast-enhanced magnetic resonance imaging.

Multiplexed wavelet transform technique for detection of microcalcification in digitized mammograms.

PubMed

Mini, M G; Devassia, V P; Thomas, Tessamma

2004-12-01

Wavelet transform (WT) is a potential tool for the detection of microcalcifications, an early sign of breast cancer. This article describes the implementation and evaluates the performance of two novel WT-based schemes for the automatic detection of clustered microcalcifications in digitized mammograms. Employing a one-dimensional WT technique that utilizes the pseudo-periodicity property of image sequences, the proposed algorithms achieve high detection efficiency and low processing memory requirements. The detection is achieved from the parent-child relationship between the zero-crossings [Marr-Hildreth (M-H) detector] /local extrema (Canny detector) of the WT coefficients at different levels of decomposition. The detected pixels are weighted before the inverse transform is computed, and they are segmented by simple global gray level thresholding. Both detectors produce 95% detection sensitivity, even though there are more false positives for the M-H detector. The M-H detector preserves the shape information and provides better detection sensitivity for mammograms containing widely distributed calcifications.

Modeling of digital mammograms using bicubic spline functions and additive noise

NASA Astrophysics Data System (ADS)

Graffigne, Christine; Maintournam, Aboubakar; Strauss, Anne

1998-09-01

The purpose of our work is the microcalcifications detection on digital mammograms. In order to do so, we model the grey levels of digital mammograms by the sum of a surface trend (bicubic spline function) and an additive noise or texture. We also introduce a robust estimation method in order to overcome the bias introduced by the microcalcifications. After the estimation we consider the subtraction image values as noise. If the noise is not correlated, we adjust its distribution probability by the Pearson's system of densities. It allows us to threshold accurately the images of subtraction and therefore to detect the microcalcifications. If the noise is correlated, a unilateral autoregressive process is used and its coefficients are again estimated by the least squares method. We then consider non overlapping windows on the residues image. In each window the texture residue is computed and compared with an a priori threshold. This provides correct localization of the microcalcifications clusters. However this technique is definitely more time consuming that then automatic threshold assuming uncorrelated noise and does not lead to significantly better results. As a conclusion, even if the assumption of uncorrelated noise is not correct, the automatic thresholding based on the Pearson's system performs quite well on most of our images.

Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume

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

Samala, Ravi K., E-mail: rsamala@umich.edu; Chan, Heang-Ping; Lu, Yao

Purpose: Develop a computer-aided detection (CADe) system for clustered microcalcifications in digital breast tomosynthesis (DBT) volume enhanced with multiscale bilateral filtering (MSBF) regularization. Methods: With Institutional Review Board approval and written informed consent, two-view DBT of 154 breasts, of which 116 had biopsy-proven microcalcification (MC) clusters and 38 were free of MCs, was imaged with a General Electric GEN2 prototype DBT system. The DBT volumes were reconstructed with MSBF-regularized simultaneous algebraic reconstruction technique (SART) that was designed to enhance MCs and reduce background noise while preserving the quality of other tissue structures. The contrast-to-noise ratio (CNR) of MCs was furthermore » improved with enhancement-modulated calcification response (EMCR) preprocessing, which combined multiscale Hessian response to enhance MCs by shape and bandpass filtering to remove the low-frequency structured background. MC candidates were then located in the EMCR volume using iterative thresholding and segmented by adaptive region growing. Two sets of potential MC objects, cluster centroid objects and MC seed objects, were generated and the CNR of each object was calculated. The number of candidates in each set was controlled based on the breast volume. Dynamic clustering around the centroid objects grouped the MC candidates to form clusters. Adaptive criteria were designed to reduce false positive (FP) clusters based on the size, CNR values and the number of MCs in the cluster, cluster shape, and cluster based maximum intensity projection. Free-response receiver operating characteristic (FROC) and jackknife alternative FROC (JAFROC) analyses were used to assess the performance and compare with that of a previous study. Results: Unpaired two-tailedt-test showed a significant increase (p < 0.0001) in the ratio of CNRs for MCs with and without MSBF regularization compared to similar ratios for FPs. For view-based detection, a sensitivity of 85% was achieved at an FP rate of 2.16 per DBT volume. For case-based detection, a sensitivity of 85% was achieved at an FP rate of 0.85 per DBT volume. JAFROC analysis showed a significant improvement in the performance of the current CADe system compared to that of our previous system (p = 0.003). Conclusions: MBSF regularized SART reconstruction enhances MCs. The enhancement in the signals, in combination with properly designed adaptive threshold criteria, effective MC feature analysis, and false positive reduction techniques, leads to a significant improvement in the detection of clustered MCs in DBT.« less

Automatic insertion of simulated microcalcification clusters in a software breast phantom

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Global detection approach for clustered microcalcifications in mammograms using a deep learning network.

PubMed

Wang, Juan; Nishikawa, Robert M; Yang, Yongyi

2017-04-01

In computerized detection of clustered microcalcifications (MCs) from mammograms, the traditional approach is to apply a pattern detector to locate the presence of individual MCs, which are subsequently grouped into clusters. Such an approach is often susceptible to the occurrence of false positives (FPs) caused by local image patterns that resemble MCs. We investigate the feasibility of a direct detection approach to determining whether an image region contains clustered MCs or not. Toward this goal, we develop a deep convolutional neural network (CNN) as the classifier model to which the input consists of a large image window ([Formula: see text] in size). The multiple layers in the CNN classifier are trained to automatically extract image features relevant to MCs at different spatial scales. In the experiments, we demonstrated this approach on a dataset consisting of both screen-film mammograms and full-field digital mammograms. We evaluated the detection performance both on classifying image regions of clustered MCs using a receiver operating characteristic (ROC) analysis and on detecting clustered MCs from full mammograms by a free-response receiver operating characteristic analysis. For comparison, we also considered a recently developed MC detector with FP suppression. In classifying image regions of clustered MCs, the CNN classifier achieved 0.971 in the area under the ROC curve, compared to 0.944 for the MC detector. In detecting clustered MCs from full mammograms, at 90% sensitivity, the CNN classifier obtained an FP rate of 0.69 clusters/image, compared to 1.17 clusters/image by the MC detector. These results indicate that using global image features can be more effective in discriminating clustered MCs from FPs caused by various sources, such as linear structures, thereby providing a more accurate detection of clustered MCs on mammograms.

Luminance level of a monitor: influence on detectability and detection rate of breast cancer in 2D mammography

NASA Astrophysics Data System (ADS)

Bemelmans, Frédéric; Rashidnasab, Alaleh; Chesterman, Frédérique; Kimpe, Tom; Bosmans, Hilde

2016-03-01

Purpose: To evaluate lesion detectability and reading time as a function of luminance level of the monitor. Material and Methods: 3D mass models and microcalcification clusters were simulated into ROIs of for processing mammograms. Randomly selected ROIs were subdivided in three groups according to their background glandularity: high (>30%), medium (15-30%) and low (<15%). 6 non-spiculated masses (9 - 11mm), 6 spiculated masses (5 - 7mm) and 6 microcalcification clusters (2 - 4mm) were scaled in 3D to create a range of sizes. The linear attenuation coefficient (AC) of the masses was adjusted from 100% glandular tissue to 90%, 80%, 70%, to create different contrasts. Six physicists read the full database on Barco's Coronis Uniti monitor for four different luminance levels (300, 800, 1000 and 1200 Cd/m2), using a 4-AFC tool. Percentage correct (PC) and time were computed for all different conditions. A paired t-test was performed to evaluate the effect of luminance on PC and time. A multi-factorial analysis was performed using MANOVA.. Results: Paired t-test indicated a statistically significant difference for the average time per session between 300 and 1200; 800 and 1200; 1000 and 1200 Cd/m2, for all participants combined. There was no effect on PC. MANOVA denoted significantly lower reading times for high glandularity images at 1200 Cd/m2. Both types of masses were significantly faster detected at 1200 Cd/m2, for the contrast study. In the size study, microcalcification clusters and spiculated masses had a significantly higher detection rate at 1200 Cd/m2. Conclusion: These results demonstrate a significant decrease in reading time, while detectability remained constant.

A fully automatic microcalcification detection approach based on deep convolution neural network

NASA Astrophysics Data System (ADS)

Cai, Guanxiong; Guo, Yanhui; Zhang, Yaqin; Qin, Genggeng; Zhou, Yuanpin; Lu, Yao

2018-02-01

Breast cancer is one of the most common cancers and has high morbidity and mortality worldwide, posing a serious threat to the health of human beings. The emergence of microcalcifications (MCs) is an important signal of early breast cancer. However, it is still challenging and time consuming for radiologists to identify some tiny and subtle individual MCs in mammograms. This study proposed a novel computer-aided MC detection algorithm on the full field digital mammograms (FFDMs) using deep convolution neural network (DCNN). Firstly, a MC candidate detection system was used to obtain potential MC candidates. Then a DCNN was trained using a novel adaptive learning strategy, neutrosophic reinforcement sample learning (NRSL) strategy to speed up the learning process. The trained DCNN served to recognize true MCs. After been classified by DCNN, a density-based regional clustering method was imposed to form MC clusters. The accuracy of the DCNN with our proposed NRSL strategy converges faster and goes higher than the traditional DCNN at same epochs, and the obtained an accuracy of 99.87% on training set, 95.12% on validation set, and 93.68% on testing set at epoch 40. For cluster-based MC cluster detection evaluation, a sensitivity of 90% was achieved at 0.13 false positives (FPs) per image. The obtained results demonstrate that the designed DCNN plays a significant role in the MC detection after being prior trained.

Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms

NASA Astrophysics Data System (ADS)

Nishikawa, Robert M.; Giger, Maryellen L.; Doi, Kunio; Vyborny, Carl J.; Schmidt, Robert A.; Metz, Charles E.; Wu, Chris Y.; Yin, Fang-Fang; Jiang, Yulei; Huo, Zhimin; Lu, Ping; Zhang, Wei; Ema, Takahiro; Bick, Ulrich; Papaioannou, John; Nagel, Rufus H.

1993-07-01

We are developing an 'intelligent' workstation to assist radiologists in diagnosing breast cancer from mammograms. The hardware for the workstation will consist of a film digitizer, a high speed computer, a large volume storage device, a film printer, and 4 high resolution CRT monitors. The software for the workstation is a comprehensive package of automated detection and classification schemes. Two rule-based detection schemes have been developed, one for breast masses and the other for clustered microcalcifications. The sensitivity of both schemes is 85% with a false-positive rate of approximately 3.0 and 1.5 false detections per image, for the mass and cluster detection schemes, respectively. Computerized classification is performed by an artificial neural network (ANN). The ANN has a sensitivity of 100% with a specificity of 60%. Currently, the ANN, which is a three-layer, feed-forward network, requires as input ratings of 14 different radiographic features of the mammogram that were determined subjectively by a radiologist. We are in the process of developing automated techniques to objectively determine these 14 features. The workstation will be placed in the clinical reading area of the radiology department in the near future, where controlled clinical tests will be performed to measure its efficacy.

Grouped fuzzy SVM with EM-based partition of sample space for clustered microcalcification detection.

PubMed

Wang, Huiya; Feng, Jun; Wang, Hongyu

2017-07-20

Detection of clustered microcalcification (MC) from mammograms plays essential roles in computer-aided diagnosis for early stage breast cancer. To tackle problems associated with the diversity of data structures of MC lesions and the variability of normal breast tissues, multi-pattern sample space learning is required. In this paper, a novel grouped fuzzy Support Vector Machine (SVM) algorithm with sample space partition based on Expectation-Maximization (EM) (called G-FSVM) is proposed for clustered MC detection. The diversified pattern of training data is partitioned into several groups based on EM algorithm. Then a series of fuzzy SVM are integrated for classification with each group of samples from the MC lesions and normal breast tissues. From DDSM database, a total of 1,064 suspicious regions are selected from 239 mammography, and the measurement of Accuracy, True Positive Rate (TPR), False Positive Rate (FPR) and EVL = TPR* 1-FPR are 0.82, 0.78, 0.14 and 0.72, respectively. The proposed method incorporates the merits of fuzzy SVM and multi-pattern sample space learning, decomposing the MC detection problem into serial simple two-class classification. Experimental results from synthetic data and DDSM database demonstrate that our integrated classification framework reduces the false positive rate significantly while maintaining the true positive rate.

Evaluation of clinical image processing algorithms used in digital mammography.

PubMed

Zanca, Federica; Jacobs, Jurgen; Van Ongeval, Chantal; Claus, Filip; Celis, Valerie; Geniets, Catherine; Provost, Veerle; Pauwels, Herman; Marchal, Guy; Bosmans, Hilde

2009-03-01

Screening is the only proven approach to reduce the mortality of breast cancer, but significant numbers of breast cancers remain undetected even when all quality assurance guidelines are implemented. With the increasing adoption of digital mammography systems, image processing may be a key factor in the imaging chain. Although to our knowledge statistically significant effects of manufacturer-recommended image processings have not been previously demonstrated, the subjective experience of our radiologists, that the apparent image quality can vary considerably between different algorithms, motivated this study. This article addresses the impact of five such algorithms on the detection of clusters of microcalcifications. A database of unprocessed (raw) images of 200 normal digital mammograms, acquired with the Siemens Novation DR, was collected retrospectively. Realistic simulated microcalcification clusters were inserted in half of the unprocessed images. All unprocessed images were subsequently processed with five manufacturer-recommended image processing algorithms (Agfa Musica 1, IMS Raffaello Mammo 1.2, Sectra Mamea AB Sigmoid, Siemens OPVIEW v2, and Siemens OPVIEW v1). Four breast imaging radiologists were asked to locate and score the clusters in each image on a five point rating scale. The free-response data were analyzed by the jackknife free-response receiver operating characteristic (JAFROC) method and, for comparison, also with the receiver operating characteristic (ROC) method. JAFROC analysis revealed highly significant differences between the image processings (F = 8.51, p < 0.0001), suggesting that image processing strongly impacts the detectability of clusters. Siemens OPVIEW2 and Siemens OPVIEW1 yielded the highest and lowest performances, respectively. ROC analysis of the data also revealed significant differences between the processing but at lower significance (F = 3.47, p = 0.0305) than JAFROC. Both statistical analysis methods revealed that the same six pairs of modalities were significantly different, but the JAFROC confidence intervals were about 32% smaller than ROC confidence intervals. This study shows that image processing has a significant impact on the detection of microcalcifications in digital mammograms. Objective measurements, such as described here, should be used by the manufacturers to select the optimal image processing algorithm.

Effect of image quality on calcification detection in digital mammography

PubMed Central

Warren, Lucy M.; Mackenzie, Alistair; Cooke, Julie; Given-Wilson, Rosalind M.; Wallis, Matthew G.; Chakraborty, Dev P.; Dance, David R.; Bosmans, Hilde; Young, Kenneth C.

2012-01-01

Purpose: This study aims to investigate if microcalcification detection varies significantly when mammographic images are acquired using different image qualities, including: different detectors, dose levels, and different image processing algorithms. An additional aim was to determine how the standard European method of measuring image quality using threshold gold thickness measured with a CDMAM phantom and the associated limits in current EU guidelines relate to calcification detection. Methods: One hundred and sixty two normal breast images were acquired on an amorphous selenium direct digital (DR) system. Microcalcification clusters extracted from magnified images of slices of mastectomies were electronically inserted into half of the images. The calcification clusters had a subtle appearance. All images were adjusted using a validated mathematical method to simulate the appearance of images from a computed radiography (CR) imaging system at the same dose, from both systems at half this dose, and from the DR system at quarter this dose. The original 162 images were processed with both Hologic and Agfa (Musica-2) image processing. All other image qualities were processed with Agfa (Musica-2) image processing only. Seven experienced observers marked and rated any identified suspicious regions. Free response operating characteristic (FROC) and ROC analyses were performed on the data. The lesion sensitivity at a nonlesion localization fraction (NLF) of 0.1 was also calculated. Images of the CDMAM mammographic test phantom were acquired using the automatic setting on the DR system. These images were modified to the additional image qualities used in the observer study. The images were analyzed using automated software. In order to assess the relationship between threshold gold thickness and calcification detection a power law was fitted to the data. Results: There was a significant reduction in calcification detection using CR compared with DR: the alternative FROC (AFROC) area decreased from 0.84 to 0.63 and the ROC area decreased from 0.91 to 0.79 (p < 0.0001). This corresponded to a 30% drop in lesion sensitivity at a NLF equal to 0.1. Detection was also sensitive to the dose used. There was no significant difference in detection between the two image processing algorithms used (p > 0.05). It was additionally found that lower threshold gold thickness from CDMAM analysis implied better cluster detection. The measured threshold gold thickness passed the acceptable limit set in the EU standards for all image qualities except half dose CR. However, calcification detection varied significantly between image qualities. This suggests that the current EU guidelines may need revising. Conclusions: Microcalcification detection was found to be sensitive to detector and dose used. Standard measurements of image quality were a good predictor of microcalcification cluster detection. PMID:22755704

Effect of image quality on calcification detection in digital mammography.

PubMed

Warren, Lucy M; Mackenzie, Alistair; Cooke, Julie; Given-Wilson, Rosalind M; Wallis, Matthew G; Chakraborty, Dev P; Dance, David R; Bosmans, Hilde; Young, Kenneth C

2012-06-01

This study aims to investigate if microcalcification detection varies significantly when mammographic images are acquired using different image qualities, including: different detectors, dose levels, and different image processing algorithms. An additional aim was to determine how the standard European method of measuring image quality using threshold gold thickness measured with a CDMAM phantom and the associated limits in current EU guidelines relate to calcification detection. One hundred and sixty two normal breast images were acquired on an amorphous selenium direct digital (DR) system. Microcalcification clusters extracted from magnified images of slices of mastectomies were electronically inserted into half of the images. The calcification clusters had a subtle appearance. All images were adjusted using a validated mathematical method to simulate the appearance of images from a computed radiography (CR) imaging system at the same dose, from both systems at half this dose, and from the DR system at quarter this dose. The original 162 images were processed with both Hologic and Agfa (Musica-2) image processing. All other image qualities were processed with Agfa (Musica-2) image processing only. Seven experienced observers marked and rated any identified suspicious regions. Free response operating characteristic (FROC) and ROC analyses were performed on the data. The lesion sensitivity at a nonlesion localization fraction (NLF) of 0.1 was also calculated. Images of the CDMAM mammographic test phantom were acquired using the automatic setting on the DR system. These images were modified to the additional image qualities used in the observer study. The images were analyzed using automated software. In order to assess the relationship between threshold gold thickness and calcification detection a power law was fitted to the data. There was a significant reduction in calcification detection using CR compared with DR: the alternative FROC (AFROC) area decreased from 0.84 to 0.63 and the ROC area decreased from 0.91 to 0.79 (p < 0.0001). This corresponded to a 30% drop in lesion sensitivity at a NLF equal to 0.1. Detection was also sensitive to the dose used. There was no significant difference in detection between the two image processing algorithms used (p > 0.05). It was additionally found that lower threshold gold thickness from CDMAM analysis implied better cluster detection. The measured threshold gold thickness passed the acceptable limit set in the EU standards for all image qualities except half dose CR. However, calcification detection varied significantly between image qualities. This suggests that the current EU guidelines may need revising. Microcalcification detection was found to be sensitive to detector and dose used. Standard measurements of image quality were a good predictor of microcalcification cluster detection. © 2012 American Association of Physicists in Medicine.

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

Warren, Lucy M.; Mackenzie, Alistair; Cooke, Julie

Purpose: This study aims to investigate if microcalcification detection varies significantly when mammographic images are acquired using different image qualities, including: different detectors, dose levels, and different image processing algorithms. An additional aim was to determine how the standard European method of measuring image quality using threshold gold thickness measured with a CDMAM phantom and the associated limits in current EU guidelines relate to calcification detection. Methods: One hundred and sixty two normal breast images were acquired on an amorphous selenium direct digital (DR) system. Microcalcification clusters extracted from magnified images of slices of mastectomies were electronically inserted into halfmore » of the images. The calcification clusters had a subtle appearance. All images were adjusted using a validated mathematical method to simulate the appearance of images from a computed radiography (CR) imaging system at the same dose, from both systems at half this dose, and from the DR system at quarter this dose. The original 162 images were processed with both Hologic and Agfa (Musica-2) image processing. All other image qualities were processed with Agfa (Musica-2) image processing only. Seven experienced observers marked and rated any identified suspicious regions. Free response operating characteristic (FROC) and ROC analyses were performed on the data. The lesion sensitivity at a nonlesion localization fraction (NLF) of 0.1 was also calculated. Images of the CDMAM mammographic test phantom were acquired using the automatic setting on the DR system. These images were modified to the additional image qualities used in the observer study. The images were analyzed using automated software. In order to assess the relationship between threshold gold thickness and calcification detection a power law was fitted to the data. Results: There was a significant reduction in calcification detection using CR compared with DR: the alternative FROC (AFROC) area decreased from 0.84 to 0.63 and the ROC area decreased from 0.91 to 0.79 (p < 0.0001). This corresponded to a 30% drop in lesion sensitivity at a NLF equal to 0.1. Detection was also sensitive to the dose used. There was no significant difference in detection between the two image processing algorithms used (p > 0.05). It was additionally found that lower threshold gold thickness from CDMAM analysis implied better cluster detection. The measured threshold gold thickness passed the acceptable limit set in the EU standards for all image qualities except half dose CR. However, calcification detection varied significantly between image qualities. This suggests that the current EU guidelines may need revising. Conclusions: Microcalcification detection was found to be sensitive to detector and dose used. Standard measurements of image quality were a good predictor of microcalcification cluster detection.« less

Distribution patterns of microcalcifications in suspected thyroid carcinoma: a classification method helpful for diagnosis.

PubMed

Ning, Chun-Ping; Ji, Qing-Lian; Fang, Shi-Bao; Wang, Hong-Qiao; Zhong, Yan-Mi; Niu, Hai-Tao

2018-06-01

The aim of this study was to compare the distribution patterns of microcalcifications in thyroid cancers with benign cases. In total, 358 patients having microcalcifications on ultrasonography were analysed. Microcalcifications were categorised according to the distribution patterns: (I) microcalcifications inside one (a) or more (b) suspected nodules, (II) microcalcifications not only inside but also surrounding a suspected single (a) or multiple (b) nodules, and (III) focal (a) or diffuse (b) microcalcifications in the absence of any suspected nodule. Differences in distribution patterns of microcalcifications in benign and malignant thyroid lesions were compared. We found that the distribution patterns of microcalcifications differed between malignant (n = 325) and benign lesions (n = 117) (X 2 = 9.926, p < 0.01). Benign lesions were classified as type Ia (66.7%), type Ib (29.1%) or type IIIa (4.3%). The specificity of type II and type IIIb in diagnosing malignant cases was 100%. Among malignant lesions, 172 locations were classified as type Ia, 106 as type Ib, 12 as type IIa, 7 as IIb, 7 as type IIIa and 19 as type IIIb. Accompanying Hashimoto thyroiditis was most frequent in type III (51.6%). Types II and IIIb are highly specific for cancer detection. Microcalcifications outside a nodule and those detected in the absence of any nodule should therefore be reviewed carefully in clinical practice. • A method to classify distribution patterns of thyroid microcalcifications is presented. • Distribution features of microcalcifications are useful for diagnosing thyroid cancers. • Microcalcifications outside a suspicious nodule are highly specific for thyroid cancers. • Microcalcifications without suspicious nodules should also alert the physician to thyroid cancers.

Usefulness of the twinkling artifact on Doppler ultrasound for the detection of breast microcalcifications.

PubMed

Relea, A; Alonso, J A; González, M; Zornoza, C; Bahamonde, S; Viñuela, B E; Encinas, M B

2018-06-12

To determine whether the twinkling artifact on Doppler ultrasound imaging corresponds to microcalcifications previously seen on mammograms and to evaluate the usefulness of this finding in the ultrasound management of suspicious microcalcifications. We used ultrasonography to prospectively examine 46 consecutive patients with groups of microcalcifications suspicious for malignancy identified at mammography, searching for the presence of the twinkling artifact to identify the microcalcifications. Once we identified the microcalcifications, we obtained core-needle biopsy specimens with 11G needles and then used X-rays to check the specimens for the presence of microcalcifications. We analyzed the percentage of detection and obtainment of microcalcifications by core-needle biopsy with this technique and the radiopathologic correlation. Microcalcifications that were not detected by ultrasound or discordant lesions were biopsied by stereotaxy at another center. We also used ultrasound guidance for preoperative marking with clips, usually orienting them radially. We identified and biopsied 41 of the 46 lesions under ultrasound guidance, including 24 of 25 carcinomas (17 in situ). B-mode ultrasound was sufficient for biopsying the microcalcifications in 14 patients, although the presence of the twinkling artifact increased the number of microcalcifications detected and thus enabled more accurate preoperative marking. Thanks to the twinkling sign, we were able to identify 27 additional groups of microcalcifications (89% vs. 30%; p < 0.05). All the surgical specimens had margins free of disease. The twinkling artifact is useful for microcalcifications in ultrasound examinations, enabling a significant increase in the yield of ultrasound-guided biopsies and better preoperative marking of groups of microcalcifications. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

[Comparison of dignity determination of mammographic microcalcification with two systems for digital full-field mammography with different detector resolution: a retrospective clinical study].

PubMed

Schulz-Wendtland, R; Hermann, K-P; Adamietz, B; Meier-Meitinger, M; Wenkel, E; Lell, M; Anders, K; Uder, M

2011-02-01

The aim of this retrospective clinical study was to compare the diagnostic accuracy of the novel 50 µm FFDM (full-field digital mammography) system (DR) with an established 70 µm system (DR) in the differential diagnosis between benign and malignant clusters of microcalcification (n=50) (BI-RADS™ classification 4/5) and to assess the possible incremental value of the 50 µm pixel-pitch on specificity. From March 2009 to September 2009, 50 patients underwent full-field digital mammography (FFDM) (detector resolution 70 µm) (Novation, Siemens, Erlangen, Germany). As there were suspicious signs of microcalcification classified with BI-RADS™ 4/5 after diagnosis and preoperative wire localization, control images were made with the new FFDM system (detector: resolution 50 µm) (Amulet, Fujifilm, Tokyo, Japan) with the same exposure parameters. The diagnosis was determined after the operation by five radiologists with different experience in digital mammography from randomly distributed mediolateral views (monitor reading) whose results were correlated with the final histology of all lesions. Histopathology revealed 19 benign and 31 malignant lesions in 50 patients after open biopsy. The results of the five readers showed a higher sensitivity of the new FFDM system (80.0%) in the ability to recognize malignant microcalcification in comparison to the established system (74.8%). The specificity (75.8 versus 71.6%) was slightly higher for the new system but these results were not statistically significant (p<0.001). Considering the diagnostic accuracy, the new system (detector: resolution 50 µm) was also slightly superior to the well-known system (detector: resolution 70 µm) (80.1% versus 76.4%). Our study has shown that the new full-field digital mammography system using the novel detector compared with the already established FFDM system with respect to the assessment of microcalcification is at least equivalent.

Mammographic images segmentation based on chaotic map clustering algorithm

PubMed Central

2014-01-01

Background This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. Methods The image is divided into pixels subsets characterized by a set of conveniently chosen features and each of the corresponding points in the feature space is associated to a map. A mutual coupling strength between the maps depending on the associated distance between feature space points is subsequently introduced. On the system of maps, the simulated evolution through chaotic dynamics leads to its natural partitioning, which corresponds to a particular segmentation scheme of the initial mammographic image. Results The system provides a high recognition rate for small mass lesions (about 94% correctly segmented inside the breast) and the reproduction of the shape of regions with denser micro-calcifications in about 2/3 of the cases, while being less effective on identification of larger mass lesions. Conclusions We can summarize our analysis by asserting that due to the particularities of the mammographic images, the chaotic map clustering algorithm should not be used as the sole method of segmentation. It is rather the joint use of this method along with other segmentation techniques that could be successfully used for increasing the segmentation performance and for providing extra information for the subsequent analysis stages such as the classification of the segmented ROI. PMID:24666766

Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning.

PubMed

Wang, Jinhua; Yang, Xi; Cai, Hongmin; Tan, Wanchang; Jin, Cangzheng; Li, Li

2016-06-07

Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer.

Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning

PubMed Central

Wang, Jinhua; Yang, Xi; Cai, Hongmin; Tan, Wanchang; Jin, Cangzheng; Li, Li

2016-01-01

Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer. PMID:27273294

Changing patterns of microcalcification on screening mammography for prediction of breast cancer.

PubMed

Kim, Kwan Il; Lee, Kyung Hee; Kim, Tae Ryung; Chun, Yong Soon; Lee, Tae Hoon; Choi, Hye Young; Park, Heung Kyu

2016-05-01

The presence of microcalcification on mammography is one of the earliest signs in breast cancer detection. However, it is difficult to distinguish malignant calcifications from benign calcifications. The aim of this study is to evaluate correlation between changing patterns of microcalcification on screening mammography and malignant breast lesions. Medical records and diagnostic images of 67 women who had previously undergone at least two digital mammograms at least 6 months apart and underwent mammography-guided needle localization and surgical excision between 2011 and 2013 were retrospectively reviewed and analyzed. Breast cancer was detected in the surgical specimens of 20 patients (29.9 %). Annual change of extent of microcalcification on mammography showed statistically significant correlation with pathologic outcome (P = 0.023). The changing pattern of new appearance or increased extent of microcalcification on mammography had positive predictive value of 54.8 % for breast cancer, and it was a statistically significant predictor for breast cancer (P = 0.012). Shape or number change of microcalcification without increased extent had less accurate predictive value for breast cancer, particularly in women younger than 50 years (P < 0.001). This study showed that the pattern of increased extent of microcalcification on screening mammography was a significant predictor for breast cancer. We suggest that mammography-guided needle localization and surgical excision should be considered when increased extent of microcalcification is observed on screening mammography and closed follow-up without pathologic confirmation can be permitted if absence of extension of microcalcification was confirmed in women younger than 50 years.

[Explorations of breast microcalcifications: Guidelines].

PubMed

Chamming's, F; Chopier, J; Mathelin, C; Chéreau, E

2015-12-01

To assess imaging performances for the detection, characterization and biopsy of breast microcalcifications and make recommendations. French and English publications were searched using PubMed, Cochrane Library and international learned societies recommendations. Digital mammography (DR [Direct Radiography] and CR [Computed Radiography]) and screen-film mammography demonstrate good performances for the detection and the characterization of breast microcalcifications. Systematic use of the 2013 edition of the BI-RADS lexicon is recommended for description and characterization of microcalcifications. Faced with BI-RADS 4 or 5 microcalcifications, breast ultrasound is recommended but a normal result does not eliminate the diagnosis of cancer and other examination should be performed. Literature review does not allow recommending digital breast tomosynthesis, elastography or MRI to analyze microcalcifications. In case of probably benign microcalcifications (BI-RADS 3), six months, one year and at least two years follow-up are recommended. In case a biopsy is indicated, it is recommended to use a vacuum-assisted macrobiopsy system with 11-gauges needles or bigger. If no calcification is visible on the radiography of the specimen, it is recommended to obtain additional samples. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Automated analysis for microcalcifications in high resolution digital mammograms

DOEpatents

Mascio, Laura N.

1996-01-01

A method for automatically locating microcalcifications indicating breast cancer. The invention assists mammographers in finding very subtle microcalcifications and in recognizing the pattern formed by all the microcalcifications. It also draws attention to microcalcifications that might be overlooked because a more prominent feature draws attention away from an important object. A new filter has been designed to weed out false positives in one of the steps of the method. Previously, iterative selection threshold was used to separate microcalcifications from the spurious signals resulting from texture or other background. A Selective Erosion or Enhancement (SEE) Filter has been invented to improve this step. Since the algorithm detects areas containing potential calcifications on the mammogram, it can be used to determine which areas need be stored at the highest resolution available, while, in addition, the full mammogram can be reduced to an appropriate resolution for the remaining cancer signs.

Automated analysis for microcalcifications in high resolution digital mammograms

DOEpatents

Mascio, L.N.

1996-12-17

A method is disclosed for automatically locating microcalcifications indicating breast cancer. The invention assists mammographers in finding very subtle microcalcifications and in recognizing the pattern formed by all the microcalcifications. It also draws attention to microcalcifications that might be overlooked because a more prominent feature draws attention away from an important object. A new filter has been designed to weed out false positives in one of the steps of the method. Previously, iterative selection threshold was used to separate microcalcifications from the spurious signals resulting from texture or other background. A Selective Erosion or Enhancement (SEE) Filter has been invented to improve this step. Since the algorithm detects areas containing potential calcifications on the mammogram, it can be used to determine which areas need be stored at the highest resolution available, while, in addition, the full mammogram can be reduced to an appropriate resolution for the remaining cancer signs. 8 figs.

Clinical utility of dual-energy contrast-enhanced spectral mammography for breast microcalcifications without associated mass: a preliminary analysis.

PubMed

Cheung, Yun-Chung; Tsai, Hsiu-Pei; Lo, Yung-Feng; Ueng, Shir-Hwa; Huang, Pei-Chin; Chen, Shin-Chih

2016-04-01

To assess the utility of dual-energy contrast-enhanced spectral mammography (DE-CESM) for evaluation of suspicious malignant microcalcifications. Two hundred and fifty-six DE-CESMs were reviewed from 2012-2013, 59 cases fulfilled the following criteria and were enrolled for analysis: (1) suspicious malignant microcalcifications (BI-RADS 4) on mammogram, (2) no related mass, (3) with pathological diagnoses. The microcalcification morphology and associated enhancement were reviewed to analyse the accuracy of the diagnosis and cancer size measurements versus the results of pathology. Of the 59 microcalcifications, 22 were diagnosed as cancers, 19 were atypical lesions and 18 were benign lesions. Twenty (76.9 %) cancers, three (11.55 %) atypia and three (11.55 %) benign lesions revealed enhancement. The true-positive rate of intermediate- and high-concern microcalcifications was significantly higher than that of low-concern lesions (93.75 % vs. 50 %). Overall, the diagnostic sensitivity of enhancement was 90.9 %, with 83.78 % specificity, 76.92 % positive predictive value, 93.94 % negative predictive value and 86.4 % accuracy. Performance was good (AUC = 0.87) according to a ROC curve and cancer size correlation with a mean difference of 0.05 cm on a Bland-Altman plot. DE-CESM provides additional enhancement information for diagnosing breast microcalcifications and measuring cancer sizes with high correlation to surgicohistology. • DE-CESM provides additional enhancement information for diagnosing suspicious breast microcalcifications. • The enhanced cancer size closely correlates to microscopy by Bland-Altman plot. • DE-CESM could be considered for evaluation of suspicious malignant microcalcifications.

[Examination of Stereotactic Mammotome Biopsy for Microcalcification in Our Hospital].

PubMed

Sueoka, Noriko; Ishizuka, Mariko; Yoshikawa, Katsuhiro; Tsubota, Yu; Yamamoto, Daigo; Kon, Masanori

2017-11-01

We introduced stereotactic mammotome biopsy(ST-MMT)for the purpose of screening and other institutions. There are many benign cases to be diagnosed by pathological findings, so it is thought to be necessary to examine the adaptation of STMMT again. We examined the performance of ST-MMT in a case of a non-palpating calcification lesion. Between August 2013 and December 2016, ST-MMT biopsies were performed for 247 microcalcified lesions revealed by mammography(in both breasts in 9 patients; twice in the ipsilateral breast in 2 patients). The mean age of all patients was 46 years(range, 24- 89 years). We found 39 cases(15.8%)of breast cancer. A final diagnosis of breast cancer was made in 39 patients, who comprised 0% of those with Category 2, 53.8% of those with Category 3, 35.9% of those with Category 4, and 10.3% of those with Category 5. Regarding the morphology and distribution of microcalcifications, breast cancer accounted for 46.2%, 5.1%, 2.6%, 35.9%, 7.7%, and 2.6% of the cases with small round/clustered, amorphous/clustered, pleomorphic/clus- tered, pleomorphic/linear segmental, and fine linear/clustered patterns, respectively. Also, we examined each of the patients, (1) who underwent mammography for medical examinations, (2) who underwent mammography performed at other institutions, (3) who underwent follow-up for microcalcifications and postoperative follow-up mammography. The proportions of breast cancer diagnoses were (1) 11.4%, (2) 20.6%, and (3) 7.1%. Proportions of Category 3 breast cancer were (1) 10.3%, (2) 38.5%, and (3) 5.1%. Among the cases in which ST-MMT was performed in this study, Category 3 accounted for more than half. However, 10.9%(21/192 lesions)were diagnosed as malignant in Category 3. The diagnosis of breast cancer in pa- tients who underwent mammography performed at other institutions was not observed in 79.4%(104/131 lesions), and among the 104 lesions, as a result of reassessment of calcification in our hospital, Category 2 was also included. Calcification in Category 2 lesions was benign in all cases. It was suggested that the indication for ST-MMT biopsy could be further narrowed down by being careful not to over-diagnose.

Secretory pathway Ca2+ -ATPases promote in vitro microcalcifications in breast cancer cells.

PubMed

Dang, Donna; Prasad, Hari; Rao, Rajini

2017-11-01

Calcification of the breast is often an outward manifestation of underlying molecular changes that drive carcinogenesis. Up to 50% of all non-palpable breast tumors and 90% of ductal carcinoma in situ present with radiographically dense mineralization in mammographic scans. However, surprisingly little is known about the molecular pathways that lead to microcalcifications in the breast. Here, we report on a rapid and quantitative in vitro assay to monitor microcalcifications in breast cancer cell lines, including MCF7, MDA-MB-231, and Hs578T. We show that the Secretory Pathway Ca 2+ -ATPases SPCA1 and SPCA2 are strongly induced under osteogenic conditions that elicit microcalcifications. SPCA gene expression is significantly elevated in breast cancer subtypes that are associated with microcalcifications. Ectopic expression of SPCA genes drives microcalcifications and is dependent on pumping activity. Conversely, knockdown of SPCA expression significantly attenuates formation of microcalcifications. We propose that high levels of SPCA pumps may initiate mineralization in the secretory pathway by elevating luminal Ca 2+ . Our new findings offer mechanistic insight and functional implications on a widely observed, yet poorly understood radiographic signature of breast cancer. © 2017 Wiley Periodicals, Inc.

A two-stage method for microcalcification cluster segmentation in mammography by deformable models

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

Arikidis, N.; Kazantzi, A.; Skiadopoulos, S.

Purpose: Segmentation of microcalcification (MC) clusters in x-ray mammography is a difficult task for radiologists. Accurate segmentation is prerequisite for quantitative image analysis of MC clusters and subsequent feature extraction and classification in computer-aided diagnosis schemes. Methods: In this study, a two-stage semiautomated segmentation method of MC clusters is investigated. The first stage is targeted to accurate and time efficient segmentation of the majority of the particles of a MC cluster, by means of a level set method. The second stage is targeted to shape refinement of selected individual MCs, by means of an active contour model. Both methods aremore » applied in the framework of a rich scale-space representation, provided by the wavelet transform at integer scales. Segmentation reliability of the proposed method in terms of inter and intraobserver agreements was evaluated in a case sample of 80 MC clusters originating from the digital database for screening mammography, corresponding to 4 morphology types (punctate: 22, fine linear branching: 16, pleomorphic: 18, and amorphous: 24) of MC clusters, assessing radiologists’ segmentations quantitatively by two distance metrics (Hausdorff distance—HDIST{sub cluster}, average of minimum distance—AMINDIST{sub cluster}) and the area overlap measure (AOM{sub cluster}). The effect of the proposed segmentation method on MC cluster characterization accuracy was evaluated in a case sample of 162 pleomorphic MC clusters (72 malignant and 90 benign). Ten MC cluster features, targeted to capture morphologic properties of individual MCs in a cluster (area, major length, perimeter, compactness, and spread), were extracted and a correlation-based feature selection method yielded a feature subset to feed in a support vector machine classifier. Classification performance of the MC cluster features was estimated by means of the area under receiver operating characteristic curve (Az ± Standard Error) utilizing tenfold cross-validation methodology. A previously developed B-spline active rays segmentation method was also considered for comparison purposes. Results: Interobserver and intraobserver segmentation agreements (median and [25%, 75%] quartile range) were substantial with respect to the distance metrics HDIST{sub cluster} (2.3 [1.8, 2.9] and 2.5 [2.1, 3.2] pixels) and AMINDIST{sub cluster} (0.8 [0.6, 1.0] and 1.0 [0.8, 1.2] pixels), while moderate with respect to AOM{sub cluster} (0.64 [0.55, 0.71] and 0.59 [0.52, 0.66]). The proposed segmentation method outperformed (0.80 ± 0.04) statistically significantly (Mann-Whitney U-test, p < 0.05) the B-spline active rays segmentation method (0.69 ± 0.04), suggesting the significance of the proposed semiautomated method. Conclusions: Results indicate a reliable semiautomated segmentation method for MC clusters offered by deformable models, which could be utilized in MC cluster quantitative image analysis.« less

Fused man-machine classification schemes to enhance diagnosis of breast microcalcifications

NASA Astrophysics Data System (ADS)

Andreadis, Ioannis; Sevastianos, Chatzistergos; George, Spyrou; Konstantina, Nikita

2017-11-01

Computer aided diagnosis (CAD x ) approaches are developed towards the effective discrimination between benign and malignant clusters of microcalcifications. Different sources of information are exploited, such as features extracted from the image analysis of the region of interest, features related to the location of the cluster inside the breast, age of the patient and descriptors provided by the radiologists while performing their diagnostic task. A series of different CAD x schemes are implemented, each of which uses a different category of features and adopts a variety of machine learning algorithms and alternative image processing techniques. A novel framework is introduced where these independent diagnostic components are properly combined according to features critical to a radiologist in an attempt to identify the most appropriate CAD x schemes for the case under consideration. An open access database (Digital Database of Screening Mammography (DDSM)) has been elaborated to construct a large dataset with cases of varying subtlety, in order to ensure the development of schemes with high generalization ability, as well as extensive evaluation of their performance. The obtained results indicate that the proposed framework succeeds in improving the diagnostic procedure, as the achieved overall classification performance outperforms all the independent single diagnostic components, as well as the radiologists that assessed the same cases, in terms of accuracy, sensitivity, specificity and area under the curve following receiver operating characteristic analysis.

A prototype of mammography CADx scheme integrated to imaging quality evaluation techniques

NASA Astrophysics Data System (ADS)

Schiabel, Homero; Matheus, Bruno R. N.; Angelo, Michele F.; Patrocínio, Ana Claudia; Ventura, Liliane

2011-03-01

As all women over the age of 40 are recommended to perform mammographic exams every two years, the demands on radiologists to evaluate mammographic images in short periods of time has increased considerably. As a tool to improve quality and accelerate analysis CADe/Dx (computer-aided detection/diagnosis) schemes have been investigated, but very few complete CADe/Dx schemes have been developed and most are restricted to detection and not diagnosis. The existent ones usually are associated to specific mammographic equipment (usually DR), which makes them very expensive. So this paper describes a prototype of a complete mammography CADx scheme developed by our research group integrated to an imaging quality evaluation process. The basic structure consists of pre-processing modules based on image acquisition and digitization procedures (FFDM, CR or film + scanner), a segmentation tool to detect clustered microcalcifications and suspect masses and a classification scheme, which evaluates as the presence of microcalcifications clusters as well as possible malignant masses based on their contour. The aim is to provide enough information not only on the detected structures but also a pre-report with a BI-RADS classification. At this time the system is still lacking an interface integrating all the modules. Despite this, it is functional as a prototype for clinical practice testing, with results comparable to others reported in literature.

Breast Microcalcification Detection Using Super-Resolution Ultrasound Image Reconstruction

DTIC Science & Technology

2010-09-01

microcalcifications often occur as one of two types: calcium oxalate dihydrate or calcium hydroxyapatite. Their sizes range approximately from 0.1 mm to 0.5 mm...super-resolution imaging, ultrasound imaging, wave equation. 1. INTRODUCTION Microcalcifications, tiny specks of mineral deposits ( calcium ), are the

Detecting breast microcalcifications using super-resolution ultrasound imaging: a clinical study

NASA Astrophysics Data System (ADS)

Huang, Lianjie; Labyed, Yassin; Hanson, Kenneth; Sandoval, Daniel; Pohl, Jennifer; Williamson, Michael

2013-03-01

Imaging breast microcalcifications is crucial for early detection and diagnosis of breast cancer. It is challenging for current clinical ultrasound to image breast microcalcifications. However, new imaging techniques using data acquired with a synthetic-aperture ultrasound system have the potential to significantly improve ultrasound imaging. We recently developed a super-resolution ultrasound imaging method termed the phase-coherent multiple-signal classification (PC-MUSIC). This signal subspace method accounts for the phase response of transducer elements to improve image resolution. In this paper, we investigate the clinical feasibility of our super-resolution ultrasound imaging method for detecting breast microcalcifications. We use our custom-built, real-time synthetic-aperture ultrasound system to acquire breast ultrasound data for 40 patients whose mammograms show the presence of breast microcalcifications. We apply our super-resolution ultrasound imaging method to the patient data, and produce clear images of breast calcifications. Our super-resolution ultrasound PC-MUSIC imaging with synthetic-aperture ultrasound data can provide a new imaging modality for detecting breast microcalcifications in clinic without using ionizing radiation.

Classification of Microcalcification of the Diagnosis of Breast Cancer using Artificial Neural Networks.

DTIC Science & Technology

1995-09-01

employed to classify benign and malignant microcalcifications in the radiographs of pathological specimen. Digital images were acquired by digitizing...associated with benign and malignant processes. The classification of microcalcifications for the diagnosis of breast cancer was achieved at a high level in

Immediate surgical resection of residual microcalcifications after a diagnosis of pure flat epithelial atypia on core biopsy: a word of caution.

PubMed

Noël, Jean-Christophe; Buxant, Frédéric; Engohan-Aloghe, Corinne

2010-12-01

The entity of pure flat epithelial atypia remains a challenge due to controversy of the surgical management of residual microcalcifications after core needle biopsies. This study aims to assess the morphological data observed in immediate surgical resection specimen of residual microcalcifications after a diagnosis of pure flat epithelial atypia on mammotome core biopsy. Sixty-two mammotome core biopsy with a diagnosis of pure flat epithelial atypia (flat epithelial atypia without associated atypical ductal hyperplasia, in situ and/or invasive carcinoma) were identified. From these 62 cases, 20 presented residual microcalcifications and underwent an immediate surgical excision after mammotome. Of the 20 patients with excised microcalcifications, 8 (40%)cases had residual pure flat epithelial atypia, 4 (20%) cases had atypical ductal hyperplasia, 4 (20%) cases had lobular in situ neoplasia, no lesions were retrieved in 4 (20%) case. None of the patients had either in situ ductal carcinoma and/or invasive carcinoma. Surgical resection of residual microcalcifications after the diagnosis of pure flat epithelial atypia on core needle biopsy remains still a debate. The present study shows no cases of in situ ductal and/or invasive carcinoma on immediate excision of residual microcalcifications after mammotome core biopsies. Copyright © 2009 Elsevier Ltd. All rights reserved.

Dark-field imaging in coronary atherosclerosis.

PubMed

Hetterich, Holger; Webber, Nicole; Willner, Marian; Herzen, Julia; Birnbacher, Lorenz; Auweter, Sigrid; Schüller, Ulrich; Bamberg, Fabian; Notohamiprodjo, Susan; Bartsch, Harald; Wolf, Johannes; Marschner, Mathias; Pfeiffer, Franz; Reiser, Maximilian; Saam, Tobias

2017-09-01

Dark-field imaging based on small angle X-ray scattering has been shown to be highly sensitive for microcalcifications, e.g. in breast tissue. We hypothesized (i) that high signal areas in dark-field imaging of atherosclerotic plaque are associated with microcalcifications and (ii) that dark-field imaging is more sensitive for microcalcifications than attenuation-based imaging. Fifteen coronary artery specimens were examined at an experimental set-up consisting of X-ray tube (40kV), grating-interferometer and detector. Tomographic dark-field-, attenuation-, and phase-contrast data were simultaneously acquired. Histopathology served as standard of reference. To explore the potential of dark field imaging in a full-body CT system, simulations were carried out with spherical calcifications of different sizes to simulate small and intermediate microcalcifications. Microcalcifications were present in 10/10 (100%) cross-sections with high dark-field signal and without evidence of calcifications in attenuation- or phase contrast. In positive controls with high signal areas in all three modalities, 10/10 (100%) cross-sections showed macrocalcifications. In negative controls without high signal areas, no calcifications were detected. Simulations showed that the microcalcifications generate substantially higher dark-field than attenuation signal. Dark-field imaging is highly sensitive for microcalcifications in coronary atherosclerotic plaque and might provide complementary information in the assessment of plaque instability. Copyright © 2017 Elsevier B.V. All rights reserved.

Sonographically-guided vacuum-assisted biopsy with digital mammography-guided skin marking of suspicious breast microcalcifications: comparison of outcomes with stereotactic biopsy in Asian women.

PubMed

Hahn, Soo Yeon; Shin, Jung Hee; Han, Boo-Kyung; Ko, Eun Young

2011-02-01

Management of suspicious microcalcifications in very thin breasts is problematic. To evaluate whether sonographically-guided vacuum-assisted biopsy (USVAB) with digital mammography-guided skin marking (DM) for the diagnosis of breast microcalcifications is comparable to stereotactic-guided vacuum-assisted biopsy (SVAB) in Asian women with thin breasts. Retrospective review was performed for 263 consecutive suspicious microcalcification lesions in 261 women who underwent USVAB with DM or SVAB using a prone table between January 2004 and December 2007. SVAB was performed for 190 lesions and USVAB for 73 lesions. Biopsy results were correlated with surgical pathology or followed up for at least 12 months. The diagnostic outcomes of SVAB and USVAB to diagnose microcalcifications were compared. Of 263 lesions, 104 (40%) underwent surgery and 159 (60%) were followed up. SVAB and USVAB groups showed similar final categories or the extent of microcalcifications. US visible lesions were 57 (78%) of 73 at USVAB and 14 (10%) of 140 at SVAB. Of 57 US visible lesions at USVAB, 29 (51%) were not found in initial US but were detectable with the help of DM. Specimen radiographs were negative in 2.1% of lesions at SVAB and in 4.1% at USVAB (p=0.4008). The under-estimation rate and false-negative rate were similar in SVAB and USVAB. US with DM facilitates US visibility of microcalcifications. USVAB with DM can produce acceptable biopsy results, as can SVAB, to diagnose breast microcalcifications in patients with thin breasts.

Dual-Energy Contrast-Enhanced Spectral Mammography: Enhancement Analysis on BI-RADS 4 Non-Mass Microcalcifications in Screened Women.

PubMed

Cheung, Yun-Chung; Juan, Yu-Hsiang; Lin, Yu-Ching; Lo, Yung-Feng; Tsai, Hsiu-Pei; Ueng, Shir-Hwa; Chen, Shin-Cheh

2016-01-01

Mammography screening is a cost-efficient modality with high sensitivity for detecting impalpable cancer with microcalcifications, and results in reduced mortality rates. However, the probability of finding microcalcifications without associated cancerous masses varies. We retrospectively evaluated the diagnosis and cancer probability of the non-mass screened microcalcifications by dual-energy contrast-enhanced spectral mammography (DE-CESM). With ethical approval from our hospital, we enrolled the cases of DE-CESM for analysis under the following inclusion criteria: (1) referrals due to screened BI-RADS 4 microcalcifications; (2) having DE-CESM prior to stereotactic biopsy; (3) no associated mass found by sonography and physical examination; and (4) pathology-based diagnosis using stereotactic vacuum-assisted breast biopsy. We analyzed the added value of post-contrast enhancement on DE-CESM. A total of 94 biopsed lesions were available for analysis in our 87 women, yielding 27 cancers [19 ductal carcinoma in situ (DCIS), and 8 invasive ductal carcinoma (IDC)], 32 pre-malignant and 35 benign lesions. Of these 94 lesions, 33 showed associated enhancement in DE-CESM while the other 61 did not. All 8 IDC (100%) and 16 of 19 DCIS (84.21%) showed enhancement, but the other 3 DCIS (15.79%) did not. Overall sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 88.89%, 86.56%, 72.72%, 95.08% and 87.24%, respectively. The performances of DE-CESM on both amorphous and pleomorphic microcalcifications were satisfactory (AUC 0.8 and 0.92, respectively). The pleomorphous microcalcifications with enhancement showed higher positive predictive value (90.00% vs 46.15%, p = 0.013) and higher cancer probability than the amorphous microcalcifications (46.3% VS 15.1%). The Odds Ratio was 4.85 (95% CI: 1.84-12.82). DE-CESM might provide added value in assessing the non-mass screened breast microcalcification, with enhancement favorable to the diagnosis of cancers or lack of enhancement virtually diagnostic for non-malignant lesions or noninvasive subgroup cancers.

Computer-aided classification of breast microcalcification clusters: merging of features from image processing and radiologists

NASA Astrophysics Data System (ADS)

Lo, Joseph Y.; Gavrielides, Marios A.; Markey, Mia K.; Jesneck, Jonathan L.

2003-05-01

We developed an ensemble classifier for the task of computer-aided diagnosis of breast microcalcification clusters,which are very challenging to characterize for radiologists and computer models alike. The purpose of this study is to help radiologists identify whether suspicious calcification clusters are benign vs. malignant, such that they may potentially recommend fewer unnecessary biopsies for actually benign lesions. The data consists of mammographic features extracted by automated image processing algorithms as well as manually interpreted by radiologists according to a standardized lexicon. We used 292 cases from a publicly available mammography database. From each cases, we extracted 22 image processing features pertaining to lesion morphology, 5 radiologist features also pertaining to morphology, and the patient age. Linear discriminant analysis (LDA) models were designed using each of the three data types. Each local model performed poorly; the best was one based upon image processing features which yielded ROC area index AZ of 0.59 +/- 0.03 and partial AZ above 90% sensitivity of 0.08 +/- 0.03. We then developed ensemble models using different combinations of those data types, and these models all improved performance compared to the local models. The final ensemble model was based upon 5 features selected by stepwise LDA from all 28 available features. This ensemble performed with AZ of 0.69 +/- 0.03 and partial AZ of 0.21 +/- 0.04, which was statistically significantly better than the model based on the image processing features alone (p<0.001 and p=0.01 for full and partial AZ respectively). This demonstrated the value of the radiologist-extracted features as a source of information for this task. It also suggested there is potential for improved performance using this ensemble classifier approach to combine different sources of currently available data.

A Multi-Scale Study on the Role of Trace Metals on Physiological and Pathological Mineralization

NASA Astrophysics Data System (ADS)

Rammelkamp, Derek

The work in this thesis provides mulit-scale contributions towards understanding the effects of trace metals on the pathological mineralization process relating to both the development of healthy bone tissue, the diseased state of osteoporosis, and microcalcifications which develop in breast cancers. A protein level study was performed on ECM protein fibronectin, which plays a role in cell adhesion. The protein studies showed zinc interactions with fibronectin and its fragment, anastellin, to influence protein structure. Zinc is also shown to decrease cell migration in vitro, which may be influenced by changes in fibronectin ECM structure. The effects of osteoporosis on micronutrient composition in vivo were examined using the technique of x-ray fluorescence (XRF) in an ovariectomized rat model. Compared to healthy bone, subtle difference are observed in zinc and iron in osteoporotic rat bones, showing micronutrients may play an important role in healthy bone regulation. Effects of micronutrient zinc was used to inhibit microcalcification formation in breast cancers. Microcalcifications have been linked malignancy of breast cancers, but the process of microcalcification formation has yet to be well understood. In this work, exogenous zinc is used to inhibit microcalcification formation, and metastatic potential in both a 2D and 3D spheroid environment. A novel in vitro self-assembled three dimensional multi-cellular tumor spheroid (MCTS) model for the study of breast cancer microcalcifications was developed for this experiment. A MCTS model for studying breast cancer microcalcifications has potential to be used in drug discovery, or for basic research applications studying mechanisms of microcalcification formation, which are still not fully understood. Taken together this study uses a multi-scale approach to gain a better understanding of micronutrients involved in pathological mineralization.

Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy

PubMed Central

Sathyavathi, R.; Saha, Anushree; Soares, Jaqueline S.; Spegazzini, Nicolas; McGee, Sasha; Rao Dasari, Ramachandra; Fitzmaurice, Maryann; Barman, Ishan

2015-01-01

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93–98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance. PMID:25927331

Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy

NASA Astrophysics Data System (ADS)

Sathyavathi, R.; Saha, Anushree; Soares, Jaqueline S.; Spegazzini, Nicolas; McGee, Sasha; Rao Dasari, Ramachandra; Fitzmaurice, Maryann; Barman, Ishan

2015-04-01

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93-98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance.

Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy.

PubMed

Sathyavathi, R; Saha, Anushree; Soares, Jaqueline S; Spegazzini, Nicolas; McGee, Sasha; Rao Dasari, Ramachandra; Fitzmaurice, Maryann; Barman, Ishan

2015-04-30

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93-98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance.

A novel approach for detection and classification of mammographic microcalcifications using wavelet analysis and extreme learning machine.

PubMed

Malar, E; Kandaswamy, A; Chakravarthy, D; Giri Dharan, A

2012-09-01

The objective of this paper is to reveal the effectiveness of wavelet based tissue texture analysis for microcalcification detection in digitized mammograms using Extreme Learning Machine (ELM). Microcalcifications are tiny deposits of calcium in the breast tissue which are potential indicators for early detection of breast cancer. The dense nature of the breast tissue and the poor contrast of the mammogram image prohibit the effectiveness in identifying microcalcifications. Hence, a new approach to discriminate the microcalcifications from the normal tissue is done using wavelet features and is compared with different feature vectors extracted using Gray Level Spatial Dependence Matrix (GLSDM) and Gabor filter based techniques. A total of 120 Region of Interests (ROIs) extracted from 55 mammogram images of mini-Mias database, including normal and microcalcification images are used in the current research. The network is trained with the above mentioned features and the results denote that ELM produces relatively better classification accuracy (94%) with a significant reduction in training time than the other artificial neural networks like Bayesnet classifier, Naivebayes classifier, and Support Vector Machine. ELM also avoids problems like local minima, improper learning rate, and over fitting. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dual-Energy Contrast-Enhanced Spectral Mammography: Enhancement Analysis on BI-RADS 4 Non-Mass Microcalcifications in Screened Women

PubMed Central

Cheung, Yun-Chung; Juan, Yu-Hsiang; Lin, Yu-Ching; Lo, Yung-Feng; Tsai, Hsiu-Pei; Ueng, Shir-Hwa; Chen, Shin-Cheh

2016-01-01

Background Mammography screening is a cost-efficient modality with high sensitivity for detecting impalpable cancer with microcalcifications, and results in reduced mortality rates. However, the probability of finding microcalcifications without associated cancerous masses varies. We retrospectively evaluated the diagnosis and cancer probability of the non-mass screened microcalcifications by dual-energy contrast-enhanced spectral mammography (DE-CESM). Patients and Methods With ethical approval from our hospital, we enrolled the cases of DE-CESM for analysis under the following inclusion criteria: (1) referrals due to screened BI-RADS 4 microcalcifications; (2) having DE-CESM prior to stereotactic biopsy; (3) no associated mass found by sonography and physical examination; and (4) pathology-based diagnosis using stereotactic vacuum-assisted breast biopsy. We analyzed the added value of post-contrast enhancement on DE-CESM. Results A total of 94 biopsed lesions were available for analysis in our 87 women, yielding 27 cancers [19 ductal carcinoma in situ (DCIS), and 8 invasive ductal carcinoma (IDC)], 32 pre-malignant and 35 benign lesions. Of these 94 lesions, 33 showed associated enhancement in DE-CESM while the other 61 did not. All 8 IDC (100%) and 16 of 19 DCIS (84.21%) showed enhancement, but the other 3 DCIS (15.79%) did not. Overall sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 88.89%, 86.56%, 72.72%, 95.08% and 87.24%, respectively. The performances of DE-CESM on both amorphous and pleomorphic microcalcifications were satisfactory (AUC 0.8 and 0.92, respectively). The pleomorphous microcalcifications with enhancement showed higher positive predictive value (90.00% vs 46.15%, p = 0.013) and higher cancer probability than the amorphous microcalcifications (46.3% VS 15.1%). The Odds Ratio was 4.85 (95% CI: 1.84–12.82). Conclusion DE-CESM might provide added value in assessing the non-mass screened breast microcalcification, with enhancement favorable to the diagnosis of cancers or lack of enhancement virtually diagnostic for non-malignant lesions or noninvasive subgroup cancers. PMID:27611215

High-frequency ultrasound imaging for breast cancer biopsy guidance

PubMed Central

Cummins, Thomas; Yoon, Changhan; Choi, Hojong; Eliahoo, Payam; Kim, Hyung Ham; Yamashita, Mary W.; Hovanessian-Larsen, Linda J.; Lang, Julie E.; Sener, Stephen F.; Vallone, John; Martin, Sue E.; Kirk Shung, K.

2015-01-01

Abstract. Image-guided core needle biopsy is the current gold standard for breast cancer diagnosis. Microcalcifications, an important radiographic finding on mammography suggestive of early breast cancer such as ductal carcinoma in situ, are usually biopsied under stereotactic guidance. This procedure, however, is uncomfortable for patients and requires the use of ionizing radiation. It would be preferable to biopsy microcalcifications under ultrasound guidance since it is a faster procedure, more comfortable for the patient, and requires no radiation. However, microcalcifications cannot reliably be detected with the current standard ultrasound imaging systems. This study is motivated by the clinical need for real-time high-resolution ultrasound imaging of microcalcifications, so that biopsies can be accurately performed under ultrasound guidance. We have investigated how high-frequency ultrasound imaging can enable visualization of microstructures in ex vivo breast tissue biopsy samples. We generated B-mode images of breast tissue and applied the Nakagami filtering technique to help refine image output so that microcalcifications could be better assessed during ultrasound-guided core biopsies. We describe the preliminary clinical results of high-frequency ultrasound imaging of ex vivo breast biopsy tissue with microcalcifications and without Nakagami filtering and the correlation of these images with the pathology examination by hematoxylin and eosin stain and whole slide digital scanning. PMID:26693167

High-resolution computed tomography of single breast cancer microcalcifications in vivo.

PubMed

Inoue, Kazumasa; Liu, Fangbing; Hoppin, Jack; Lunsford, Elaine P; Lackas, Christian; Hesterman, Jacob; Lenkinski, Robert E; Fujii, Hirofumi; Frangioni, John V

2011-08-01

Microcalcification is a hallmark of breast cancer and a key diagnostic feature for mammography. We recently described the first robust animal model of breast cancer microcalcification. In this study, we hypothesized that high-resolution computed tomography (CT) could potentially detect the genesis of a single microcalcification in vivo and quantify its growth over time. Using a commercial CT scanner, we systematically optimized acquisition and reconstruction parameters. Two ray-tracing image reconstruction algorithms were tested: a voxel-driven "fast" cone beam algorithm (FCBA) and a detector-driven "exact" cone beam algorithm (ECBA). By optimizing acquisition and reconstruction parameters, we were able to achieve a resolution of 104 μm full width at half-maximum (FWHM). At an optimal detector sampling frequency, the ECBA provided a 28 μm (21%) FWHM improvement in resolution over the FCBA. In vitro, we were able to image a single 300 μm × 100 μm hydroxyapatite crystal. In a syngeneic rat model of breast cancer, we were able to detect the genesis of a single microcalcification in vivo and follow its growth longitudinally over weeks. Taken together, this study provides an in vivo "gold standard" for the development of calcification-specific contrast agents and a model system for studying the mechanism of breast cancer microcalcification.

Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

PubMed

al-Rifaie, Mohammad Majid; Aber, Ahmed; Hemanth, Duraiswamy Jude

2015-12-01

This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identification of metastasis in bone scans and microcalcifications on mammographs, for the first time, the use of the algorithm in assessing the CT images of the aorta is demonstrated along with its performance in detecting the nasogastric tube in chest X-ray. The swarm intelligence algorithm presented in this study is adapted to address these particular tasks and its functionality is investigated by running the swarms on sample CT images and X-rays whose status have been determined by senior radiologists. In addition, a hybrid swarm intelligence-learning vector quantisation (LVQ) approach is proposed in the context of magnetic resonance (MR) brain image segmentation. The particle swarm optimisation is used to train the LVQ which eliminates the iteration-dependent nature of LVQ. The proposed methodology is used to detect the tumour regions in the abnormal MR brain images.

An unusual case of gastric cancer presenting with breast metastasis with pleomorphic microcalcifications.

PubMed

Luk, Yiu Shiobhon; Ka, Solomon Yig Joon; Lo, Sherwin Shing Wai; Chu, Chi Yeung; Ma, Ming Wai

2012-09-01

Breast metastasis from gastric carcinoma is rare. We present a case of right breast mass with microcalcification in which the diagnosis of poorly differentiated adenocarcinoma from the stomach was made after a biopsy. Pleomorphic microcalcification was noted in the ill-defined breast mass, which is a rare feature in breast metastasis. Since breast metastasis usually signifies advanced metastatic disease, differentiating primary breast cancer from metastasis is important for appropriate treatment.

Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform.

PubMed

Jian, Wushuai; Sun, Xueyan; Luo, Shuqian

2012-12-19

Digital mammography is the most reliable imaging modality for breast carcinoma diagnosis and breast micro-calcifications is regarded as one of the most important signs on imaging diagnosis. In this paper, a computer-aided diagnosis (CAD) system is presented for breast micro-calcifications based on dual-tree complex wavelet transform (DT-CWT) to facilitate radiologists like double reading. Firstly, 25 abnormal ROIs were extracted according to the center and diameter of the lesions manually and 25 normal ROIs were selected randomly. Then micro-calcifications were segmented by combining space and frequency domain techniques. We extracted three texture features based on wavelet (Haar, DB4, DT-CWT) transform. Totally 14 descriptors were introduced to define the characteristics of the suspicious micro-calcifications. Principal Component Analysis (PCA) was used to transform these descriptors to a compact and efficient vector expression. Support Vector Machine (SVM) classifier was used to classify potential micro-calcifications. Finally, we used the receiver operating characteristic (ROC) curve and free-response operating characteristic (FROC) curve to evaluate the performance of the CAD system. The results of SVM classifications based on different wavelets shows DT-CWT has a better performance. Compared with other results, DT-CWT method achieved an accuracy of 96% and 100% for the classification of normal and abnormal ROIs, and the classification of benign and malignant micro-calcifications respectively. In FROC analysis, our CAD system for clinical dataset detection achieved a sensitivity of 83.5% at a false positive per image of 1.85. Compared with general wavelets, DT-CWT could describe the features more effectively, and our CAD system had a competitive performance.

Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform

PubMed Central

2012-01-01

Background Digital mammography is the most reliable imaging modality for breast carcinoma diagnosis and breast micro-calcifications is regarded as one of the most important signs on imaging diagnosis. In this paper, a computer-aided diagnosis (CAD) system is presented for breast micro-calcifications based on dual-tree complex wavelet transform (DT-CWT) to facilitate radiologists like double reading. Methods Firstly, 25 abnormal ROIs were extracted according to the center and diameter of the lesions manually and 25 normal ROIs were selected randomly. Then micro-calcifications were segmented by combining space and frequency domain techniques. We extracted three texture features based on wavelet (Haar, DB4, DT-CWT) transform. Totally 14 descriptors were introduced to define the characteristics of the suspicious micro-calcifications. Principal Component Analysis (PCA) was used to transform these descriptors to a compact and efficient vector expression. Support Vector Machine (SVM) classifier was used to classify potential micro-calcifications. Finally, we used the receiver operating characteristic (ROC) curve and free-response operating characteristic (FROC) curve to evaluate the performance of the CAD system. Results The results of SVM classifications based on different wavelets shows DT-CWT has a better performance. Compared with other results, DT-CWT method achieved an accuracy of 96% and 100% for the classification of normal and abnormal ROIs, and the classification of benign and malignant micro-calcifications respectively. In FROC analysis, our CAD system for clinical dataset detection achieved a sensitivity of 83.5% at a false positive per image of 1.85. Conclusions Compared with general wavelets, DT-CWT could describe the features more effectively, and our CAD system had a competitive performance. PMID:23253202

Pattern Recognition and Size Prediction of Microcalcification Based on Physical Characteristics by Using Digital Mammogram Images.

PubMed

Jothilakshmi, G R; Raaza, Arun; Rajendran, V; Sreenivasa Varma, Y; Guru Nirmal Raj, R

2018-06-05

Breast cancer is one of the life-threatening cancers occurring in women. In recent years, from the surveys provided by various medical organizations, it has become clear that the mortality rate of females is increasing owing to the late detection of breast cancer. Therefore, an automated algorithm is needed to identify the early occurrence of microcalcification, which would assist radiologists and physicians in reducing the false predictions via image processing techniques. In this work, we propose a new algorithm to detect the pattern of a microcalcification by calculating its physical characteristics. The considered physical characteristics are the reflection coefficient and mass density of the binned digital mammogram image. The calculation of physical characteristics doubly confirms the presence of malignant microcalcification. Subsequently, by interpolating the physical characteristics via thresholding and mapping techniques, a three-dimensional (3D) projection of the region of interest (RoI) is obtained in terms of the distance in millimeter. The size of a microcalcification is determined using this 3D-projected view. This algorithm is verified with 100 abnormal mammogram images showing microcalcification and 10 normal mammogram images. In addition to the size calculation, the proposed algorithm acts as a good classifier that is used to classify the considered input image as normal or abnormal with the help of only two physical characteristics. This proposed algorithm exhibits a classification accuracy of 99%.

Progressive Secondary Neurodegeneration and Microcalcification Co-Occur in Osteopontin-Deficient Mice

PubMed Central

Maetzler, Walter; Berg, Daniela; Funke, Claudia; Sandmann, Freya; Stünitz, Holger; Maetzler, Corina; Nitsch, Cordula

2010-01-01

In the brain, osteopontin (OPN) may function in a variety of pathological conditions, including neurodegeneration, microcalcification, and inflammation. In this study, we addressed the role of OPN in primary and secondary neurodegeneration, microcalcification, and inflammation after an excitotoxic lesion by examining OPN knock-out (KO) mice. Two, four, and ten weeks after injection of the glutamate analogue ibotenate into the corticostriatal boundary, the brains of 12 mice per survival time and strain were evaluated. OPN was detectable in neuron-shaped cells, in microglia, and at the surface of dense calcium deposits. At this primary lesion site, although the glial reaction was attenuated in OPN-KO mice, lesion size and presence of microcalcification were comparable between OPN-KO and wild-type mice. In contrast, secondary neurodegeneration at the thalamus was more prominent in OPN-KO mice, and this difference increased over time. This was paralleled by a dramatic rise in the regional extent of dense microcalcification. Despite these differences, the numbers of glial cells did not significantly differ between the two strains. This study demonstrates for the first time a genetic model with co-occurrence of neurodegeneration and microcalcification, mediated by the lack of OPN, and suggests a basic involvement of OPN action in these conditions. In the case of secondary retrograde or transneuronal degeneration, OPN may have a protective role as intracellular actor. PMID:20522649

Digital Image Processing Technique for Breast Cancer Detection

NASA Astrophysics Data System (ADS)

Guzmán-Cabrera, R.; Guzmán-Sepúlveda, J. R.; Torres-Cisneros, M.; May-Arrioja, D. A.; Ruiz-Pinales, J.; Ibarra-Manzano, O. G.; Aviña-Cervantes, G.; Parada, A. González

2013-09-01

Breast cancer is the most common cause of death in women and the second leading cause of cancer deaths worldwide. Primary prevention in the early stages of the disease becomes complex as the causes remain almost unknown. However, some typical signatures of this disease, such as masses and microcalcifications appearing on mammograms, can be used to improve early diagnostic techniques, which is critical for women’s quality of life. X-ray mammography is the main test used for screening and early diagnosis, and its analysis and processing are the keys to improving breast cancer prognosis. As masses and benign glandular tissue typically appear with low contrast and often very blurred, several computer-aided diagnosis schemes have been developed to support radiologists and internists in their diagnosis. In this article, an approach is proposed to effectively analyze digital mammograms based on texture segmentation for the detection of early stage tumors. The proposed algorithm was tested over several images taken from the digital database for screening mammography for cancer research and diagnosis, and it was found to be absolutely suitable to distinguish masses and microcalcifications from the background tissue using morphological operators and then extract them through machine learning techniques and a clustering algorithm for intensity-based segmentation.

Region-growing approach to detect microcalcifications in digital mammograms

NASA Astrophysics Data System (ADS)

Shin, Jin-Wook; Chae, Soo-Ik; Sook, Yoon M.; Park, Dong-Sun

2001-09-01

Detecting early symptoms of breast cancer is very important to enhance the possibility of cure. There have been active researches to develop computer-aided diagnosis(CAD) systems detecting early symptoms of breast cancer in digital mammograms. An expert or a CAD system can recognize the early symptoms based on microcalcifications appeared in digital mammographic images. Microcalcifications have higher gray value than surrounding regions, so these can be detected by expanding a region from a local maximum. However the resultant image contains unnecessary elements such as noise, holes and valleys. Mathematical morphology is a good solution to delete regions that are affected by the unnecessary elements. In this paper, we present a method that effectively detects microcalcifications in digital mammograms using a combination of local maximum operation and the region-growing operation.

Aortic microcalcification is associated with elastin fragmentation in Marfan syndrome.

PubMed

Wanga, Shaynah; Hibender, Stijntje; Ridwan, Yanto; van Roomen, Cindy; Vos, Mariska; van der Made, Ingeborg; van Vliet, Nicole; Franken, Romy; van Riel, Luigi Amjg; Groenink, Maarten; Zwinderman, Aeilko H; Mulder, Barbara Jm; de Vries, Carlie Jm; Essers, Jeroen; de Waard, Vivian

2017-11-01

Marfan syndrome (MFS) is a connective tissue disorder in which aortic rupture is the major cause of death. MFS patients with an aortic diameter below the advised limit for prophylactic surgery (<5 cm) may unexpectedly experience an aortic dissection or rupture, despite yearly monitoring. Hence, there is a clear need for improved prognostic markers to predict such aortic events. We hypothesize that elastin fragments play a causal role in aortic calcification in MFS, and that microcalcification serves as a marker for aortic disease severity. To address this hypothesis, we analysed MFS patient and mouse aortas. MFS patient aortic tissue showed enhanced microcalcification in areas with extensive elastic lamina fragmentation in the media. A causal relationship between medial injury and microcalcification was revealed by studies in vascular smooth muscle cells (SMCs); elastin peptides were shown to increase the activity of the calcification marker alkaline phosphatase (ALP) and reduce the expression of the calcification inhibitor matrix GLA protein in human SMCs. In murine Fbn1 C1039G/+ MFS aortic SMCs, Alpl mRNA and activity were upregulated as compared with wild-type SMCs. The elastin peptide-induced ALP activity was prevented by incubation with lactose or a neuraminidase inhibitor, which inhibit the elastin receptor complex, and a mitogen-activated protein kinase kinase-1/2 inhibitor, indicating downstream involvement of extracellular signal-regulated kinase-1/2 (ERK1/2) phosphorylation. Histological analyses in MFS mice revealed macrocalcification in the aortic root, whereas the ascending aorta contained microcalcification, as identified with the near-infrared fluorescent bisphosphonate probe OsteoSense-800. Significantly, microcalcification correlated strongly with aortic diameter, distensibility, elastin breaks, and phosphorylated ERK1/2. In conclusion, microcalcification co-localizes with aortic elastin degradation in MFS aortas of humans and mice, where elastin-derived peptides induce a calcification process in SMCs via the elastin receptor complex and ERK1/2 activation. We propose microcalcification as a novel imaging marker to monitor local elastin degradation and thus predict aortic events in MFS patients. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Automated System for Early Breast Cancer Detection in Mammograms

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Visualization of microcalcifications using photoacoustic imaging: feasibility study

NASA Astrophysics Data System (ADS)

Hsiao, Tsai-Chu; Wang, Po-Hsun; Fan, Chih-Tai; Cheng, Yao-You; Li, Meng-Lin

2011-03-01

Recently, photoacoustic imaging has been intensively studied for blood vessel imaging, and shown its capability of revealing vascular features suggestive of malignancy of breast cancer. In this study, we explore the feasibility of visualization of micro-calcifications using photoacoustic imaging. Breast micro-calcification is also known as one of the most important indicators for early breast cancer detection. The non-ionizing radiation and speckle free nature of photoacoustic imaging overcomes the drawbacks of current diagnostic tools - X-ray mammography and ultrasound imaging, respectively. We employed a 10-MHz photoacoustic imaging system to verify our idea. A sliced chicken breast phantom with granulated calcium hydroxyapatite (HA) - major chemical composition of the breast calcification associated with malignant breast cancers - embedded was imaged. With the near infared (NIR) laser excitation, it is shown that the distribution of ~500 μm HAs can be clearly imaged. In addition, photoacoustic signals from HAs rivals those of blood given an optimal NIR wavelength. In summary, photoacoustic imaging shows its promise for breast micro-calcification detection. Moreover, fusion of the photoacoustic and ultrasound images can reveal the location and distribution of micro-calcifications within anatomical landmarks of the breast tissue, which is clinically useful for biopsy and diagnosis of breast cancer staging.

Varying levels of small microcalcifications and macrophages in ATTR and AL cardiac amyloidosis: implications for utilizing nuclear medicine studies to subtype amyloidosis.

PubMed

Stats, Miriam A; Stone, James R

2016-01-01

Recently, there has been much interest in using nuclear medicine studies to noninvasively identify and subtype cardiac amyloidosis. In particular, modified bone scans using (99m)Tc-3,3-diphosphono-1,2-propanodicarboxylic acid ((99m)Tc-DPD) and (99m)Tc-pyrophosphate ((99m)Tc-PYP) are being used to selectively identify patients with ATTR amyloidosis rather than AL amyloidosis. The morphologic basis underlying the selectivity of these imaging modalities for ATTR amyloidosis has been unclear. To determine if variations in microcalcifications and/or macrophages within ATTR and AL amyloidosis might be responsible for the selectivity for these imaging modalities, 8 endomyocardial biopsies of ATTR amyloidosis and 7 endomyocardial biopsies of AL amyloidosis were stained with von Kossa calcium stains and with immunohistochemistry for the macrophage marker CD68. Compared with AL amyloidosis, there was a greater density of small microcalcifications in cases of ATTR amyloidosis (mean=16.8 vs. 6.5 per 200× field, P=.008). In contrast, there were fewer macrophages in ATTR amyloidosis compared with AL amyloidosis (mean=2.5 vs. 11.7 per 200× field, P=.0004). The density of microcalcifications within each group was not related to patient age, echocardiographic features of cardiac function, or serum levels of calcium and creatinine. These data suggest that microcalcifications but not macrophages likely underlie the selectivity of modified bone scans for ATTR amyloidosis and suggest that other pathologic entities containing microcalcifications might also result in positive scans with these imaging modalities. Copyright © 2016 Elsevier Inc. All rights reserved.

Locally adaptive decision in detection of clustered microcalcifications in mammograms.

PubMed

Sainz de Cea, María V; Nishikawa, Robert M; Yang, Yongyi

2018-02-15

In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value  <10 -4 ). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.

Flat epithelial atypia of the breast: pathological-radiological correlation.

PubMed

Solorzano, Silma; Mesurolle, Benoît; Omeroglu, Attila; El Khoury, Mona; Kao, Ellen; Aldis, Ann; Meterissian, Sarkis

2011-09-01

This study was undertaken to determine the prevalence of flat epithelial atypia at ultrasound-guided and stereotactically guided needle biopsies, to describe the mammographic and sonographic features of flat epithelial atypia, and to determine the significance of lesions diagnosed as flat epithelial atypia at imaging-guided needle biopsies. Retrospective review of a database of 1369 consecutive sonographically and stereotactically guided needle biopsies performed during a 12-month period yielded 33 lesions with flat epithelial atypia as the most severe pathologic entity (32 patients). Two radiologists retrospectively reviewed the imaging presentation, by combined consensus, according to the BI-RADS lexicon. Twenty-two of 33 flat epithelial atypia diagnoses (67%) were obtained under stereotactic guidance, and 11 (33%) were obtained under sonographic guidance. Six patients had synchronous breast cancer. Flat epithelial atypia lesions presented mammographically most often as microcalcifications (20/33 [61%]) distributed in a cluster (14/20 [70%]) with amorphous morphology (13/20 [65%]). Sonographically, flat epithelial atypia lesions appeared most often as masses (9/11 [82%]), with an irregular shape (6/9 [67%]), microlobulated margins (5/9 [56%]), and hypoechoic or complex echotexture (7/9 [78%]). Twenty-eight of 33 lesions (85%) were surgically excised, confirming the flat epithelial atypia diagnosis in 11 of the 28 lesions (39%), yielding carcinoma in four (14%) and atypical ductal hyperplasia in six (21%). Columnar cell changes without atypia were diagnosed in four lesions (14%), and lobular carcinoma in situ was diagnosed in three lesions (11%). Mammographic and sonographic presentation of flat epithelial atypia is not specific (clustered amorphous microcalcifications and irregular, hypoechoic or complex masses). Given the underestimation rate of malignancy, surgical excision should be considered when imaging-guided biopsy yields flat epithelial atypia.

Comparison of Genetic Algorithm, Particle Swarm Optimization and Biogeography-based Optimization for Feature Selection to Classify Clusters of Microcalcifications

NASA Astrophysics Data System (ADS)

Khehra, Baljit Singh; Pharwaha, Amar Partap Singh

2017-04-01

Ductal carcinoma in situ (DCIS) is one type of breast cancer. Clusters of microcalcifications (MCCs) are symptoms of DCIS that are recognized by mammography. Selection of robust features vector is the process of selecting an optimal subset of features from a large number of available features in a given problem domain after the feature extraction and before any classification scheme. Feature selection reduces the feature space that improves the performance of classifier and decreases the computational burden imposed by using many features on classifier. Selection of an optimal subset of features from a large number of available features in a given problem domain is a difficult search problem. For n features, the total numbers of possible subsets of features are 2n. Thus, selection of an optimal subset of features problem belongs to the category of NP-hard problems. In this paper, an attempt is made to find the optimal subset of MCCs features from all possible subsets of features using genetic algorithm (GA), particle swarm optimization (PSO) and biogeography-based optimization (BBO). For simulation, a total of 380 benign and malignant MCCs samples have been selected from mammogram images of DDSM database. A total of 50 features extracted from benign and malignant MCCs samples are used in this study. In these algorithms, fitness function is correct classification rate of classifier. Support vector machine is used as a classifier. From experimental results, it is also observed that the performance of PSO-based and BBO-based algorithms to select an optimal subset of features for classifying MCCs as benign or malignant is better as compared to GA-based algorithm.

Locally adaptive decision in detection of clustered microcalcifications in mammograms

NASA Astrophysics Data System (ADS)

Sainz de Cea, María V.; Nishikawa, Robert M.; Yang, Yongyi

2018-02-01

In computer-aided detection or diagnosis of clustered microcalcifications (MCs) in mammograms, the performance often suffers from not only the presence of false positives (FPs) among the detected individual MCs but also large variability in detection accuracy among different cases. To address this issue, we investigate a locally adaptive decision scheme in MC detection by exploiting the noise characteristics in a lesion area. Instead of developing a new MC detector, we propose a decision scheme on how to best decide whether a detected object is an MC or not in the detector output. We formulate the individual MCs as statistical outliers compared to the many noisy detections in a lesion area so as to account for the local image characteristics. To identify the MCs, we first consider a parametric method for outlier detection, the Mahalanobis distance detector, which is based on a multi-dimensional Gaussian distribution on the noisy detections. We also consider a non-parametric method which is based on a stochastic neighbor graph model of the detected objects. We demonstrated the proposed decision approach with two existing MC detectors on a set of 188 full-field digital mammograms (95 cases). The results, evaluated using free response operating characteristic (FROC) analysis, showed a significant improvement in detection accuracy by the proposed outlier decision approach over traditional thresholding (the partial area under the FROC curve increased from 3.95 to 4.25, p-value  <10-4). There was also a reduction in case-to-case variability in detected FPs at a given sensitivity level. The proposed adaptive decision approach could not only reduce the number of FPs in detected MCs but also improve case-to-case consistency in detection.

Dual Energy Method for Breast Imaging: A Simulation Study.

PubMed

Koukou, V; Martini, N; Michail, C; Sotiropoulou, P; Fountzoula, C; Kalyvas, N; Kandarakis, I; Nikiforidis, G; Fountos, G

2015-01-01

Dual energy methods can suppress the contrast between adipose and glandular tissues in the breast and therefore enhance the visibility of calcifications. In this study, a dual energy method based on analytical modeling was developed for the detection of minimum microcalcification thickness. To this aim, a modified radiographic X-ray unit was considered, in order to overcome the limited kVp range of mammographic units used in previous DE studies, combined with a high resolution CMOS sensor (pixel size of 22.5 μm) for improved resolution. Various filter materials were examined based on their K-absorption edge. Hydroxyapatite (HAp) was used to simulate microcalcifications. The contrast to noise ratio (CNR tc ) of the subtracted images was calculated for both monoenergetic and polyenergetic X-ray beams. The optimum monoenergetic pair was 23/58 keV for the low and high energy, respectively, resulting in a minimum detectable microcalcification thickness of 100 μm. In the polyenergetic X-ray study, the optimal spectral combination was 40/70 kVp filtered with 100 μm cadmium and 1000 μm copper, respectively. In this case, the minimum detectable microcalcification thickness was 150 μm. The proposed dual energy method provides improved microcalcification detectability in breast imaging with mean glandular dose values within acceptable levels.

Dual Energy Method for Breast Imaging: A Simulation Study

PubMed Central

2015-01-01

Dual energy methods can suppress the contrast between adipose and glandular tissues in the breast and therefore enhance the visibility of calcifications. In this study, a dual energy method based on analytical modeling was developed for the detection of minimum microcalcification thickness. To this aim, a modified radiographic X-ray unit was considered, in order to overcome the limited kVp range of mammographic units used in previous DE studies, combined with a high resolution CMOS sensor (pixel size of 22.5 μm) for improved resolution. Various filter materials were examined based on their K-absorption edge. Hydroxyapatite (HAp) was used to simulate microcalcifications. The contrast to noise ratio (CNRtc) of the subtracted images was calculated for both monoenergetic and polyenergetic X-ray beams. The optimum monoenergetic pair was 23/58 keV for the low and high energy, respectively, resulting in a minimum detectable microcalcification thickness of 100 μm. In the polyenergetic X-ray study, the optimal spectral combination was 40/70 kVp filtered with 100 μm cadmium and 1000 μm copper, respectively. In this case, the minimum detectable microcalcification thickness was 150 μm. The proposed dual energy method provides improved microcalcification detectability in breast imaging with mean glandular dose values within acceptable levels. PMID:26246848

Can magnetic resonance imaging obviate the need for biopsy for microcalcifications?

PubMed Central

Chishima, Takashi

2017-01-01

Background Although microcalcifications detected with mammography (MG) are usually biopsied, biopsies cannot be performed in all cases. We sought to determine if magnetic resonance imaging (MRI) findings could indicate whether stereotactic vacuum-assisted biopsy (SVAB) is necessary. Methods Patients with mammographically detected Breast Imaging-Reporting and Data System (BI-RADS) 3, 4, and 5 microcalcifications were analyzed from April 2012 to September 2014. All patients underwent MRI. All patients with enhancing lesions in the region of the microcalcifications underwent SVAB. Non-enhancing lesions were followed or biopsied, depending on the patient's preferences. MRI findings were classified as either malignant-suspicious or benign-suspicious (“none” or “nonspecific”), and we evaluated the positive predictive value (PPV) and negative predictive value (NPV) of these classifications for predicting malignancy. Results A total of 87 patients underwent both MRI and SVAB. The NPV of MRI was 100% in the group with no enhancement. In BI-RADS category 3, there were 57 benign-suspicious lesions on MRI, of which eight were malignant (NPV of MRI: 85.0%). Conclusions It may be possible to omit SVAB for microcalcifications if there is no enhancement on MRI; however, any kind of enhancement indicates the need for biopsy in cases of BI-RADS 3 calcifications on MG. PMID:28861368

Validation of a modified PENELOPE Monte Carlo code for applications in digital and dual-energy mammography

NASA Astrophysics Data System (ADS)

Del Lama, L. S.; Cunha, D. M.; Poletti, M. E.

2017-08-01

The presence and morphology of microcalcification clusters are the main point to provide early indications of breast carcinomas. However, the visualization of those structures may be jeopardized due to overlapping tissues even for digital mammography systems. Although digital mammography is the current standard for breast cancer diagnosis, further improvements should be achieved in order to address some of those physical limitations. One possible solution for such issues is the application of the dual-energy technique (DE), which is able to highlight specific lesions or cancel out the tissue background. In this sense, this work aimed to evaluate several quantities of interest in radiation applications and compare those values with works present in the literature to validate a modified PENELOPE code for digital mammography applications. For instance, the scatter-to-primary ratio (SPR), the scatter fraction (SF) and the normalized mean glandular dose (DgN) were evaluated by simulations and the resulting values were compared to those found in earlier studies. Our results present a good correlation for the evaluated quantities, showing agreement equal or better than 5% for the scatter and dosimetric-related quantities when compared to the literature. Finally, a DE imaging chain was simulated and the visualization of microcalcifications was investigated.

Digital mammography: observer performance study of the effects of pixel size on radiologists' characterization of malignant and benign microcalcifications

NASA Astrophysics Data System (ADS)

Chan, Heang-Ping; Helvie, Mark A.; Petrick, Nicholas; Sahiner, Berkman; Adler, Dorit D.; Blane, Caroline E.; Joynt, Lynn K.; Paramagul, Chintana; Roubidoux, Marilyn A.; Wilson, Todd E.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

1999-05-01

A receiver operating characteristic (ROC) experiment was conducted to evaluate the effects of pixel size on the characterization of mammographic microcalcifications. Digital mammograms were obtained by digitizing screen-film mammograms with a laser film scanner. One hundred twelve two-view mammograms with biopsy-proven microcalcifications were digitized at a pixel size of 35 micrometer X 35 micrometer. A region of interest (ROI) containing the microcalcifications was extracted from each image. ROI images with pixel sizes of 70 micrometers, 105 micrometers, and 140 micrometers were derived from the ROI of 35 micrometer pixel size by averaging 2 X 2, 3 X 3, and 4 X 4 neighboring pixels, respectively. The ROI images were printed on film with a laser imager. Seven MQSA-approved radiologists participated as observers. The likelihood of malignancy of the microcalcifications was rated on a 10-point confidence rating scale and analyzed with ROC methodology. The classification accuracy was quantified by the area, Az, under the ROC curve. The statistical significance of the differences in the Az values for different pixel sizes was estimated with the Dorfman-Berbaum-Metz (DBM) method for multi-reader, multi-case ROC data. It was found that five of the seven radiologists demonstrated a higher classification accuracy with the 70 micrometer or 105 micrometer images. The average Az also showed a higher classification accuracy in the range of 70 to 105 micrometer pixel size. However, the differences in A(subscript z/ between different pixel sizes did not achieve statistical significance. The low specificity of image features of microcalcifications an the large interobserver and intraobserver variabilities may have contributed to the relatively weak dependence of classification accuracy on pixel size.

Sonographic findings of high-grade and non-high-grade ductal carcinoma in situ of the breast.

PubMed

Park, Ji-Sung; Park, Young-Mi; Kim, Eun-Kyung; Kim, Suk-Jung; Han, Sang-Suk; Lee, Sun-Joo; In, Hyun-Sin; Ryu, Ji-Hwa

2010-12-01

The purpose of this study was to differentiate between high-grade and non-high-grade ductal carcinoma in situ (DCIS) of the breast on sonography. From October 2003 to August 2009, 76 DCIS lesions in 73 women who underwent sonography and mammography were included in this study. Lesions were confirmed by mastectomy, breast-conserving surgery, or surgical biopsy. Images were analyzed by 2 radiologists with consensus and were correlated with histologic grades. Of the 76 lesions, 44 were classified as high--grade and 32 as non-high-grade DCIS. Fifty-seven lesions (75.0%) were identified on sonography, which revealed a mass in 30 cases, microcalcifications in 20, ductal changes in 4, and architectural distortion in 3. All cases with false-negative findings on sonography (n = 19) showed microcalcifications on mammography. On sonography, masses were more frequently found in non-high-grade (62.5%) than high-grade DCIS (22.7%; P < .01). No significant difference was seen in the sonographic features of masses between high-grade and non-high-grade DCIS. Microcalcifications were more common in high-grade (43.2%) than non-high-grade (3.1%) DCIS (P = .02). Most sonographically visible microcalcifications had associated findings such as ductal changes (n = 11), a mass (n = 7), or a hypoechoic area (n = 5). The detection rate of microcalcifications on sonography was higher in high-grade (62.9%) than non-high-grade DCIS (25.0%; P = .023). Microcalcifications with associated ductal changes (11 of 31 [35.5%]) were the most common sonographic findings in high-grade DCIS. An irregular hypoechoic mass with an indistinct and microlobulated margin (13 of 26 [50.0%]) was the most frequent finding in non-high-grade DCIS.

Staging of breast cancer and the advanced applications of digital mammogram: what the physician needs to know?

PubMed

Helal, Maha H; Mansour, Sahar M; Zaglol, Mai; Salaleldin, Lamia A; Nada, Omniya M; Haggag, Marwa A

2017-03-01

To study the role of advanced applications of digital mammogram, whether contrast-enhanced spectral mammography (CESM) or digital breast tomosynthesis (DBT), in the "T" staging of histologically proven breast cancer before planning for treatment management. In this prospective analysis, we evaluated 98 proved malignant breast masses regarding their size, multiplicity and the presence of associated clusters of microcalcifications. Evaluation methods included digital mammography (DM), 3D tomosynthesis and CESM. Traditional DM was first performed then in a period of 10-14-day interval; breast tomosynthesis and contrast-based mammography were performed for the involved breast only. Views at tomosynthesis were acquired in a "step-and-shoot" tube motion mode to produce multiple (11-15), low-dose images and in contrast-enhanced study, low-energy (22-33 kVp) and high-energy (44-49 kVp) exposures were taken after the i.v. injection of the contrast agent. Operative data were the gold standard reference. Breast tomosynthesis showed the highest accuracy in size assessment (n = 69, 70.4%) than contrast-enhanced (n = 49, 50%) and regular mammography (n = 59, 60.2%). Contrast-enhanced mammography presented the least performance in assessing calcifications, yet it was most sensitive in the detection of multiplicity (92.3%), followed by tomosynthesis (77%) and regular mammography (53.8%). The combined analysis of the three modalities provided an accuracy of 74% in the "T" staging of breast cancer. The combined application of tomosynthesis and contrast-enhanced digital mammogram enhanced the performance of the traditional DM and presented an informative method in the staging of breast cancer. Advances in knowledge: Staging and management planning of breast cancer can divert according to tumour size, multiplicity and the presence of microcalcifications. DBT shows sharp outlines of the tumour with no overlap tissue and spots microcalcifications. Contrast-enhanced spectral mammogram shows the extent of abnormal contrast uptake and detects multiplicity. Integrated analysis provides optimal findings for proper "T" staging of breast cancer.

Assessment of Breast Specimens With or Without Calcifications in Diagnosing Malignant and Atypia for Mammographic Breast Microcalcifications Without Mass: A STARD-Compliant Diagnostic Accuracy Article.

PubMed

Cheung, Yun-Chung; Juan, Yu-Hsiang; Ueng, Shir-Hwa; Lo, Yung-Feng; Huang, Pei-Chin; Lin, Yu-Ching; Chen, Shin-Cheh

2015-10-01

Presence of microcalcifications within the specimens frequently signifies a successful attempt of stereotactic vacuum-assisted breast biopsy (VABB) in obtaining a pathologic diagnosis of the breast microcalcifications. In this study, the authors aimed to assess and compare the accuracy and consistency of calcified or noncalcified specimens obtained from same sites of sampling on isolated microcalcifications without mass in diagnosing high-risk and malignant lesions. To the best of our knowledge, an individual case-based prospective comparison has not been reported.With the approval from institutional review board of our hospital (Chang Gung Memorial Hospital), the authors retrospectively reviewed all clinical cases of stereotactic VABBs on isolated breast microcalcifications without mass from our database. The authors included those having either surgery performed or had clinical follow-up of at least 3 years for analysis. All the obtained specimens with or without calcification were identified using specimen radiographs and separately submitted for pathologic evaluation. The concordance of diagnosis was assessed for both atypia and malignant lesions.A total of 390 stereotactic VABB procedures (1206 calcified and 1456 noncalcified specimens) were collected and reviewed. The consistent rates between calcified and noncalcified specimens were low for atypia and malignant microcalcifications (44.44% in flat epithelial atypia, 46.51% in atypical ductal hyperplasia, 55.73% in ductal carcinoma in situ, and 71.42% in invasive ductal carcinoma). The discordance in VABB diagnoses indicated that 41.33% of malignant lesions would be misdiagnosed by noncalcified specimens. Furthermore, calcified specimens showed higher diagnostic accuracy of breast cancer as compared with the noncalcified specimens (91.54 % versus 69.49%, respectively). The evaluation of both noncalcified specimens and calcified specimens did not show improvement of diagnostic accuracy as compared with evaluating calcified specimens alone (91.54% versus 91.54%, respectively).The high prevalence of diagnostic discordance between the calcified and noncalcified specimens indicated the higher value of calcified specimens in diagnosing atypia and malignant microcalcifications. Noncalcified specimens did not provide additional diagnostic benefit from this study. The separation of calcified and noncalcified specimens may facilitate more focused interpretation from pathologists among the large number of specimens.

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

PubMed Central

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

2015-01-01

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

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

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

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

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

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Task-Driven Dictionary Learning Based on Mutual Information for Medical Image Classification.

PubMed

Diamant, Idit; Klang, Eyal; Amitai, Michal; Konen, Eli; Goldberger, Jacob; Greenspan, Hayit

2017-06-01

We present a novel variant of the bag-of-visual-words (BoVW) method for automated medical image classification. Our approach improves the BoVW model by learning a task-driven dictionary of the most relevant visual words per task using a mutual information-based criterion. Additionally, we generate relevance maps to visualize and localize the decision of the automatic classification algorithm. These maps demonstrate how the algorithm works and show the spatial layout of the most relevant words. We applied our algorithm to three different tasks: chest x-ray pathology identification (of four pathologies: cardiomegaly, enlarged mediastinum, right consolidation, and left consolidation), liver lesion classification into four categories in computed tomography (CT) images and benign/malignant clusters of microcalcifications (MCs) classification in breast mammograms. Validation was conducted on three datasets: 443 chest x-rays, 118 portal phase CT images of liver lesions, and 260 mammography MCs. The proposed method improves the classical BoVW method for all tested applications. For chest x-ray, area under curve of 0.876 was obtained for enlarged mediastinum identification compared to 0.855 using classical BoVW (with p-value 0.01). For MC classification, a significant improvement of 4% was achieved using our new approach (with p-value = 0.03). For liver lesion classification, an improvement of 6% in sensitivity and 2% in specificity were obtained (with p-value 0.001). We demonstrated that classification based on informative selected set of words results in significant improvement. Our new BoVW approach shows promising results in clinically important domains. Additionally, it can discover relevant parts of images for the task at hand without explicit annotations for training data. This can provide computer-aided support for medical experts in challenging image analysis tasks.

Columnar cell lesions without atypia initially diagnosed on breast needle biopsies: is imaging follow-up enough?

PubMed

Seo, Mirinae; Chang, Jung Min; Kim, Won Hwa; Park, In-Ae; Lee, Su Hyun; Cho, Nariya; Moon, Woo Kyung

2013-10-01

The purpose of this study was to evaluate the underestimation rate and predictive factor of underestimation of columnar cell lesions (CCLs) without atypia diagnosed through breast core needle biopsies (CNBs). From January 2007 through December 2011, 141 CCLs without atypia, including columnar cell change and columnar cell hyperplasia, were diagnosed in 138 women by CNB. Excisional (n = 16) or imaging follow-up (n = 125) findings were available in all cases. On a per-lesion basis, the underestimation rate and predictive factor of underestimation were evaluated. Among the 16 surgically excised lesions, there were two malignancies (one ductal carcinoma in situ and one invasive ductal carcinoma) and one lobular carcinoma in situ. Overall, the pooled underestimation rate of malignancy was 1.4% (2/141). With regard to lesion variables, the mean lesion size was significantly larger in the underestimation group of CCLs (p = 0.007). Fine pleomorphic morphology of microcalcifications (p < 0.001), the distribution of the microcalcifications (p = 0.007), BI-RADS final assessment (p = 0.001), and imaging-pathologic correlation (p < 0.001) were significantly associated with underestimation. Multivariate analysis showed that fine pleomorphic morphology of microcalcifications (p < 0.0001) was an independent predictor of underestimation in 58 lesions with microcalcifications on mammography. The overall underestimation rate of malignancy was 1.4%. Imaging follow-up is reasonable for CCLs without atypia at CNB, especially in small lesions with less suspicious imaging findings. Fine pleomorphic microcalcifications and higher BI-RADS category might be helpful in the prediction of underestimation of a high-risk lesion or malignancy.

[Comparative study between film mammography and xeromammography; including specimen radiography].

PubMed

Maeda, M; Hayakawa, K; Okuno, Y; Torizuka, T; Mitsumori, M; Soga, T; Misaki, T; Dokou, S; Ito, K

1990-10-01

We retrospectively evaluated preoperative film- and xeromammography of 23 cases with breast cancers, and compared with postoperative specimen radiography to assess tumor delineation and microcalcification detectability. In tumor detection and margin delineation, film mammography was superior to xeromammography, and in microcalcification, film mammography was equal to xeromammography. These results had a effect on the diagnosis of breast cancers.

Wavelet-based 3D reconstruction of microcalcification clusters from two mammographic views: new evidence that fractal tumors are malignant and Euclidean tumors are benign.

PubMed

Batchelder, Kendra A; Tanenbaum, Aaron B; Albert, Seth; Guimond, Lyne; Kestener, Pierre; Arneodo, Alain; Khalil, Andre

2014-01-01

The 2D Wavelet-Transform Modulus Maxima (WTMM) method was used to detect microcalcifications (MC) in human breast tissue seen in mammograms and to characterize the fractal geometry of benign and malignant MC clusters. This was done in the context of a preliminary analysis of a small dataset, via a novel way to partition the wavelet-transform space-scale skeleton. For the first time, the estimated 3D fractal structure of a breast lesion was inferred by pairing the information from two separate 2D projected mammographic views of the same breast, i.e. the cranial-caudal (CC) and mediolateral-oblique (MLO) views. As a novelty, we define the "CC-MLO fractal dimension plot", where a "fractal zone" and "Euclidean zones" (non-fractal) are defined. 118 images (59 cases, 25 malignant and 34 benign) obtained from a digital databank of mammograms with known radiologist diagnostics were analyzed to determine which cases would be plotted in the fractal zone and which cases would fall in the Euclidean zones. 92% of malignant breast lesions studied (23 out of 25 cases) were in the fractal zone while 88% of the benign lesions were in the Euclidean zones (30 out of 34 cases). Furthermore, a Bayesian statistical analysis shows that, with 95% credibility, the probability that fractal breast lesions are malignant is between 74% and 98%. Alternatively, with 95% credibility, the probability that Euclidean breast lesions are benign is between 76% and 96%. These results support the notion that the fractal structure of malignant tumors is more likely to be associated with an invasive behavior into the surrounding tissue compared to the less invasive, Euclidean structure of benign tumors. Finally, based on indirect 3D reconstructions from the 2D views, we conjecture that all breast tumors considered in this study, benign and malignant, fractal or Euclidean, restrict their growth to 2-dimensional manifolds within the breast tissue.

Staging of breast cancer and the advanced applications of digital mammogram: what the physician needs to know?

PubMed Central

Helal, Maha H; Zaglol, Mai; Salaleldin, Lamia A; Nada, Omniya M; Haggag, Marwa A

2017-01-01

Objective: To study the role of advanced applications of digital mammogram, whether contrast-enhanced spectral mammography (CESM) or digital breast tomosynthesis (DBT), in the “T” staging of histologically proven breast cancer before planning for treatment management. Methods: In this prospective analysis, we evaluated 98 proved malignant breast masses regarding their size, multiplicity and the presence of associated clusters of microcalcifications. Evaluation methods included digital mammography (DM), 3D tomosynthesis and CESM. Traditional DM was first performed then in a period of 10–14-day interval; breast tomosynthesis and contrast-based mammography were performed for the involved breast only. Views at tomosynthesis were acquired in a “step-and-shoot” tube motion mode to produce multiple (11–15), low-dose images and in contrast-enhanced study, low-energy (22–33 kVp) and high-energy (44–49 kVp) exposures were taken after the i.v. injection of the contrast agent. Operative data were the gold standard reference. Results: Breast tomosynthesis showed the highest accuracy in size assessment (n = 69, 70.4%) than contrast-enhanced (n = 49, 50%) and regular mammography (n = 59, 60.2%). Contrast-enhanced mammography presented the least performance in assessing calcifications, yet it was most sensitive in the detection of multiplicity (92.3%), followed by tomosynthesis (77%) and regular mammography (53.8%). The combined analysis of the three modalities provided an accuracy of 74% in the “T” staging of breast cancer. Conclusion: The combined application of tomosynthesis and contrast-enhanced digital mammogram enhanced the performance of the traditional DM and presented an informative method in the staging of breast cancer. Advances in knowledge: Staging and management planning of breast cancer can divert according to tumour size, multiplicity and the presence of microcalcifications. DBT shows sharp outlines of the tumour with no overlap tissue and spots microcalcifications. Contrast-enhanced spectral mammogram shows the extent of abnormal contrast uptake and detects multiplicity. Integrated analysis provides optimal findings for proper “T” staging of breast cancer. PMID:28055247

Digital mammography: more microcalcifications, more columnar cell lesions without atypia.

PubMed

Verschuur-Maes, Anoek H J; van Gils, Carla H; van den Bosch, Maurice A A J; De Bruin, Peter C; van Diest, Paul J

2011-09-01

The incidence of columnar cell lesions in breast core needle biopsies since full-field digital mammography in comparison with screen-filmed mammography was analyzed. As tiny microcalcifications characterize columnar cell lesions at mammography, we hypothesized that more columnar cell lesions are diagnosed since full-field digital mammography due to its higher sensitivity for microcalcifications. In all, 3437 breast core needle biopsies performed in three hospitals and resulting from in total 55 159 mammographies were revised: 1424 taken in the screen-filmed mammography and 2013 in the full-field digital mammography period. Between the screen-filmed mammography and full-field digital mammography periods, we compared the proportion of mammographies that led to core needle biopsies, the mammographic indication for core needle biopsies (density, microcalcifications, or both) and the proportion of columnar cell lesions with or without atypia. The columnar cell lesions were graded according to Schnitt, and we included atypical ductal hyperplasia arising in the context of columnar cell lesions. Proportions were compared using χ(2) tests and prevalence ratios were adjusted for age and hospital. We found that more core needle biopsies per mammogram were taken in the full-field digital mammography period (7.6%) compared with the screen-filmed mammography period (5.0%, P<0.0001). Microcalcifications were more often diagnosed with full-field digital mammography than with screen-filmed mammography (adjusted prevalence ratio: 1.14, confidence interval 95%: 1.01-1.28). Core needle biopsies from the full-field digital mammography era showed more columnar cell lesions (10.8%) than those from the screen-filmed mammography era (4.9%; adjusted prevalence ratio: 1.93, confidence interval 95%: 1.48-2.51), particularly due to more columnar cell lesions without atypia (8.2% respectively 2.8%) while the proportion of columnar cell lesions with atypia remained nearly constant (2.0 vs 2.6%). In conclusion, since the implementation of full-field digital mammography, more microcalcifications are seen at mammography, more often resulting in core needle biopsies, which especially yields more columnar cell lesions without atypia.

Imprint cytology on microcalcifications excised by vacuum-assisted breast biopsy: a rapid preliminary diagnosis.

PubMed

Fotou, Maria; Oikonomou, Vassiliki; Zagouri, Flora; Sergentanis, Theodoros N; Nonni, Afroditi; Athanassiadou, Pauline; Drouveli, Theodora; Atsouris, Efstratios; Kotzia, Evagelia; Zografos, George C

2007-04-03

To evaluate imprint cytology in the context of specimens with microcalcifications derived from Vacuum-Assisted Breast Biopsy (VABB). A total of 93 women with microcalcifications BI-RADS 3 and 4 underwent VABB and imprint samples were examined. VABB was performed on Fischer's table using 11-gauge Mammotome vacuum probes. A mammogram of the cores after the procedure confirmed the excision of microcalcifications. For the application of imprint cytology, the cores with microcalcifications confirmed by mammogram were gently rolled against glass microscope slides and thus imprint smears were made. For rapid preliminary diagnosis Diff-Quick stain, modified Papanicolaou stain and May Grunwald Giemsa were used. Afterwards, the core was dipped into a CytoRich Red Collection fluid for a few seconds in order to obtain samples with the use of the specimen wash. After the completion of cytological procedures, the core was prepared for routine histological study. The pathologist was blind to the preliminary cytological results. The cytological and pathological diagnoses were comparatively evaluated. According to the pathological examination, 73 lesions were benign, 15 lesions were carcinomas (12 ductal carcinomas in situ, 3 invasive ductal carcinomas), and 5 lesions were precursor: 3 cases of atypical ductal hyperplasia (ADH) and 2 cases of lobular neoplasia (LN). The observed sensitivity and specificity of the cytological imprints for cancer were 100% (one-sided, 97.5% CI: 78.2%-100%). Only one case of ADH could be detected by imprint cytology. Neither of the two LN cases was detected by the imprints. The imprints were uninformative in 11 out of 93 cases (11.8%). There was no uninformative case among women with malignancy. Imprint cytology provides a rapid, accurate preliminary diagnosis in a few minutes. This method might contribute to the diagnosis of early breast cancer and possibly attenuates patients' anxiety.

Mammography of ductal carcinoma in situ of the breast: review of 909 cases with radiographic-pathologic correlations.

PubMed

Barreau, Béatrice; de Mascarel, Isabelle; Feuga, Caroline; MacGrogan, Gaétan; Dilhuydy, Marie-Hélène; Picot, Véronique; Dilhuydy, Jean-Marie; de Lara, Christine Tunon; Bussières, Emmanuel; Schreer, I

2005-04-01

We retrospectively analysed mammographies of 909 ductal carcinoma in situ (DCIS) (1980-1999) and compared our results to those of literature. Microcalcifications were present in 75% of the cases, and soft-tissue abnormalities in 27% cases with association with calcifications in 14% of cases. Palpable masses were found in 12% of the cases and nipple discharge was present in 12% of the cases. The radiographic-pathologic correlation allowed to suspect the DCIS "aggressiveness" on radiologic signs. Granular, linear, branching and/or galactophoric topography of the microcalcifications were correlated with necrosis, grade 3, comedocarcinoma type. A number of microcalcifications higher than 20 was correlated with necrosis and grade 3. Mammographic size was correlated to histologic size. Masses were correlated with grade 1. A diagnosis strategy can be proposed with a multidisciplinar approach.

Predictors of invasive breast cancer in mammographically detected microcalcification in patients with a core biopsy diagnosis of flat epithelial atypia, atypical ductal hyperplasia or ductal carcinoma in situ and recommendations for a selective approach to sentinel lymph node biopsy.

PubMed

Catteau, Xavier; Simon, Philippe; Noël, Jean-Christophe

2012-04-15

15±30% of malignancies detected through screening programs are ductal carcinoma in situ (DCIS), and the majority of DCIS cases present in the form of mammographic microcalcification. This study was performed in order to determine the value of features in predicting invasive disease in patients with mammographic calcification and to help determine which patients (with, Core Needle Biopsy-diagnosed DCIS) are the most appropriate candidates for Sentinel Lymph Node (SLN) biopsy. The original aspect of this study was to select patients with mammographic microcalcification but without an associated mass. The factor that we identified to be associated with invasive disease at final surgical excision was the presence of necrosis at core histology. SLN biopsy or complete axillary lymph node dissection was performed in 22 (40%) patients of whom only one (4.5%) had a micrometastasis. Further larger studies are needed to see if it would be interesting to propose a SLN biopsy in case of necrosis on CNB-diagnosed DCIS with microcalcifications but not associated with a mass. Copyright © 2012 Elsevier GmbH. All rights reserved.

A controlled phantom study of a noise equalization algorithm for detecting microcalcifications in digital mammograms.

PubMed

Gürün, O O; Fatouros, P P; Kuhn, G M; de Paredes, E S

2001-04-01

We report on some extensions and further developments of a well-known microcalcification detection algorithm based on adaptive noise equalization. Tissue equivalent phantom images with and without labeled microcalcifications were subjected to this algorithm, and analyses of results revealed some shortcomings in the approach. Particularly, it was observed that the method of estimating the width of distributions in the feature space was based on assumptions which resulted in the loss of similarity preservation characteristics. A modification involving a change of estimator statistic was made, and the modified approach was tested on the same phantom images. Other modifications for improving detectability such as downsampling and use of alternate local contrast filters were also tested. The results indicate that these modifications yield improvements in detectability, while extending the generality of the approach. Extensions to real mammograms and further directions of research are discussed.

Genesis and growth of extracellular vesicle-derived microcalcification in atherosclerotic plaques

PubMed Central

Hutcheson, Joshua D.; Goettsch, Claudia; Bertazzo, Sergio; Maldonado, Natalia; Ruiz, Jessica L.; Goh, Wilson; Yabusaki, Katsumi; Faits, Tyler; Bouten, Carlijn; Franck, Gregory; Quillard, Thibaut; Libby, Peter; Aikawa, Masanori; Weinbaum, Sheldon; Aikawa, Elena

2015-01-01

Clinical evidence links arterial calcification and cardiovascular risk. Finite-element modelling of the stress distribution within atherosclerotic plaques has suggested that subcellular microcalcifications in the fibrous cap may promote material failure of the plaque, but that large calcifications can stabilize it. Yet the physicochemical mechanisms underlying such mineral formation and growth in atheromata remain unknown. Here, by using three-dimensional collagen hydrogels that mimic structural features of the atherosclerotic fibrous cap, and high-resolution microscopic and spectroscopic analyses of both the hydrogels and of calcified human plaques, we demonstrate that calcific mineral formation and maturation results from a series of events involving the aggregation of calcifying extracellular vesicles, and the formation of microcalcifications and ultimately large calcification zones. We also show that calcification morphology and the plaque’s collagen content – two determinants of atherosclerotic plaque stability - are interlinked. PMID:26752654

D3D augmented reality imaging system: proof of concept in mammography.

PubMed

Douglas, David B; Petricoin, Emanuel F; Liotta, Lance; Wilson, Eugene

2016-01-01

The purpose of this article is to present images from simulated breast microcalcifications and assess the pattern of the microcalcifications with a technical development called "depth 3-dimensional (D3D) augmented reality". A computer, head display unit, joystick, D3D augmented reality software, and an in-house script of simulated data of breast microcalcifications in a ductal distribution were used. No patient data was used and no statistical analysis was performed. The D3D augmented reality system demonstrated stereoscopic depth perception by presenting a unique image to each eye, focal point convergence, head position tracking, 3D cursor, and joystick fly-through. The D3D augmented reality imaging system offers image viewing with depth perception and focal point convergence. The D3D augmented reality system should be tested to determine its utility in clinical practice.

Reducing false positives of microcalcification detection systems by removal of breast arterial calcifications.

PubMed

Mordang, Jan-Jurre; Gubern-Mérida, Albert; den Heeten, Gerard; Karssemeijer, Nico

2016-04-01

In the past decades, computer-aided detection (CADe) systems have been developed to aid screening radiologists in the detection of malignant microcalcifications. These systems are useful to avoid perceptual oversights and can increase the radiologists' detection rate. However, due to the high number of false positives marked by these CADe systems, they are not yet suitable as an independent reader. Breast arterial calcifications (BACs) are one of the most frequent false positives marked by CADe systems. In this study, a method is proposed for the elimination of BACs as positive findings. Removal of these false positives will increase the performance of the CADe system in finding malignant microcalcifications. A multistage method is proposed for the removal of BAC findings. The first stage consists of a microcalcification candidate selection, segmentation and grouping of the microcalcifications, and classification to remove obvious false positives. In the second stage, a case-based selection is applied where cases are selected which contain BACs. In the final stage, BACs are removed from the selected cases. The BACs removal stage consists of a GentleBoost classifier trained on microcalcification features describing their shape, topology, and texture. Additionally, novel features are introduced to discriminate BACs from other positive findings. The CADe system was evaluated with and without BACs removal. Here, both systems were applied on a validation set containing 1088 cases of which 95 cases contained malignant microcalcifications. After bootstrapping, free-response receiver operating characteristics and receiver operating characteristics analyses were carried out. Performance between the two systems was compared at 0.98 and 0.95 specificity. At a specificity of 0.98, the sensitivity increased from 37% to 52% and the sensitivity increased from 62% up to 76% at a specificity of 0.95. Partial areas under the curve in the specificity range of 0.8-1.0 were significantly different between the system without BACs removal and the system with BACs removal, 0.129 ± 0.009 versus 0.144 ± 0.008 (p<0.05), respectively. Additionally, the sensitivity at one false positive per 50 cases and one false positive per 25 cases increased as well, 37% versus 51% (p<0.05) and 58% versus 67% (p<0.05) sensitivity, respectively. Additionally, the CADe system with BACs removal reduces the number of false positives per case by 29% on average. The same sensitivity at one false positive per 50 cases in the CADe system without BACs removal can be achieved at one false positive per 80 cases in the CADe system with BACs removal. By using dedicated algorithms to detect and remove breast arterial calcifications, the performance of CADe systems can be improved, in particular, at false positive rates representative for operating points used in screening.

Design of a model observer to evaluate calcification detectability in breast tomosynthesis and application to smoothing prior optimization.

PubMed

Michielsen, Koen; Nuyts, Johan; Cockmartin, Lesley; Marshall, Nicholas; Bosmans, Hilde

2016-12-01

In this work, the authors design and validate a model observer that can detect groups of microcalcifications in a four-alternative forced choice experiment and use it to optimize a smoothing prior for detectability of microcalcifications. A channelized Hotelling observer (CHO) with eight Laguerre-Gauss channels was designed to detect groups of five microcalcifications in a background of acrylic spheres by adding the CHO log-likelihood ratios calculated at the expected locations of the five calcifications. This model observer is then applied to optimize the detectability of the microcalcifications as a function of the smoothing prior. The authors examine the quadratic and total variation (TV) priors, and a combination of both. A selection of these reconstructions was then evaluated by human observers to validate the correct working of the model observer. The authors found a clear maximum for the detectability of microcalcification when using the total variation prior with weight β TV = 35. Detectability only varied over a small range for the quadratic and combined quadratic-TV priors when weight β Q of the quadratic prior was changed by two orders of magnitude. Spearman correlation with human observers was good except for the highest value of β for the quadratic and TV priors. Excluding those, the authors found ρ = 0.93 when comparing detection fractions, and ρ = 0.86 for the fitted detection threshold diameter. The authors successfully designed a model observer that was able to predict human performance over a large range of settings of the smoothing prior, except for the highest values of β which were outside the useful range for good image quality. Since detectability only depends weakly on the strength of the combined prior, it is not possible to pick an optimal smoothness based only on this criterion. On the other hand, such choice can now be made based on other criteria without worrying about calcification detectability.

Diagnostic PET Imaging of Mammary Microcalcifications Using 64Cu-DOTA-Alendronate in a Rat Model of Breast Cancer.

PubMed

Ahrens, Bradley J; Li, Lin; Ciminera, Alexandra K; Chea, Junie; Poku, Erasmus; Bading, James R; Weist, Michael R; Miller, Marcia M; Colcher, David M; Shively, John E

2017-09-01

The development of improved breast cancer screening methods is hindered by a lack of cancer-specific imaging agents and effective small-animal models to test them. The purpose of this study was to evaluate 64 Cu-DOTA-alendronate as a mammary microcalcification-targeting PET imaging agent, using an ideal rat model. Our long-term goal is to develop 64 Cu-DOTA-alendronate for the detection and noninvasive differentiation of malignant versus benign breast tumors with PET. Methods: DOTA-alendronate was synthesized, radiolabeled with 64 Cu, and administered to normal or tumor-bearing aged, female, retired breeder Sprague-Dawley rats for PET imaging. Mammary tissues were subsequently labeled and imaged with light, confocal, and electron microscopy to verify microcalcification targeting specificity of DOTA-alendronate and elucidate the histologic and ultrastructural characteristics of the microcalcifications in different mammary tumor types. Tumor uptake, biodistribution, and dosimetry studies were performed to evaluate the efficacy and safety of 64 Cu-DOTA-alendronate. Results: 64 Cu-DOTA-alendronate was radiolabeled with a 98% yield. PET imaging using aged, female, retired breeder rats showed specific binding of 64 Cu-DOTA-alendronate in mammary glands and mammary tumors. The highest uptake of 64 Cu-DOTA-alendronate was in malignant tumors and the lowest uptake in benign tumors and normal mammary tissue. Confocal analysis with carboxyfluorescein-alendronate confirmed the microcalcification binding specificity of alendronate derivatives. Biodistribution studies revealed tissue alendronate concentrations peaking within the first hour, then decreasing over the next 48 h. Our dosimetric analysis demonstrated a 64 Cu effective dose within the acceptable range for clinical PET imaging agents and the potential for translation into human patients. Conclusion: 64 Cu-DOTA-alendronate is a promising PET imaging agent for the sensitive and specific detection of mammary tumors as well as the differentiation of malignant versus benign tumors based on absolute labeling uptake. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Diagnostic PET Imaging of Mammary Microcalcifications Using 64Cu-DOTA-Alendronate in a Rat Model of Breast Cancer

PubMed Central

Ahrens, Bradley J.; Li, Lin; Ciminera, Alexandra K.; Chea, Junie; Poku, Erasmus; Bading, James R.; Weist, Michael R.; Miller, Marcia M.; Colcher, David M.

2017-01-01

The development of improved breast cancer screening methods is hindered by a lack of cancer-specific imaging agents and effective small-animal models to test them. The purpose of this study was to evaluate 64Cu-DOTA-alendronate as a mammary microcalcification-targeting PET imaging agent, using an ideal rat model. Our long-term goal is to develop 64Cu-DOTA-alendronate for the detection and noninvasive differentiation of malignant versus benign breast tumors with PET. Methods: DOTA-alendronate was synthesized, radiolabeled with 64Cu, and administered to normal or tumor-bearing aged, female, retired breeder Sprague–Dawley rats for PET imaging. Mammary tissues were subsequently labeled and imaged with light, confocal, and electron microscopy to verify microcalcification targeting specificity of DOTA-alendronate and elucidate the histologic and ultrastructural characteristics of the microcalcifications in different mammary tumor types. Tumor uptake, biodistribution, and dosimetry studies were performed to evaluate the efficacy and safety of 64Cu-DOTA-alendronate. Results: 64Cu-DOTA-alendronate was radiolabeled with a 98% yield. PET imaging using aged, female, retired breeder rats showed specific binding of 64Cu-DOTA-alendronate in mammary glands and mammary tumors. The highest uptake of 64Cu-DOTA-alendronate was in malignant tumors and the lowest uptake in benign tumors and normal mammary tissue. Confocal analysis with carboxyfluorescein-alendronate confirmed the microcalcification binding specificity of alendronate derivatives. Biodistribution studies revealed tissue alendronate concentrations peaking within the first hour, then decreasing over the next 48 h. Our dosimetric analysis demonstrated a 64Cu effective dose within the acceptable range for clinical PET imaging agents and the potential for translation into human patients. Conclusion: 64Cu-DOTA-alendronate is a promising PET imaging agent for the sensitive and specific detection of mammary tumors as well as the differentiation of malignant versus benign tumors based on absolute labeling uptake. PMID:28450564

Applying Data Mining Techniques to Improve Breast Cancer Diagnosis.

PubMed

Diz, Joana; Marreiros, Goreti; Freitas, Alberto

2016-09-01

In the field of breast cancer research, and more than ever, new computer aided diagnosis based systems have been developed aiming to reduce diagnostic tests false-positives. Within this work, we present a data mining based approach which might support oncologists in the process of breast cancer classification and diagnosis. The present study aims to compare two breast cancer datasets and find the best methods in predicting benign/malignant lesions, breast density classification, and even for finding identification (mass / microcalcification distinction). To carry out these tasks, two matrices of texture features extraction were implemented using Matlab, and classified using data mining algorithms, on WEKA. Results revealed good percentages of accuracy for each class: 89.3 to 64.7 % - benign/malignant; 75.8 to 78.3 % - dense/fatty tissue; 71.0 to 83.1 % - finding identification. Among the different tests classifiers, Naive Bayes was the best to identify masses texture, and Random Forests was the first or second best classifier for the majority of tested groups.

Cytologic features of the normal pineal gland on squash preparations.

PubMed

Murro, Diana; Alsadi, Alaa; Nag, Sukriti; Arvanitis, Leonidas; Gattuso, Paolo

2014-11-01

As primary pineal lesions are extremely rare, many surgical pathologists are unfamiliar with normal pineal cytologic features. We describe cytologic features of the normal pineal gland in patients of varying ages and identify common diagnostic pitfalls. We performed a retrospective review of pineal gland biopsies performed at our institution, where approximately 30,000 surgical specimens are accessioned yearly, for the last 23 years. Only two pineal gland biopsies were found. Although both cases were initially diagnosed as low-grade gliomas on frozen section, the final diagnosis was benign pineal tissue based on light microscopy and immunohistochemistry results. Additionally, we performed squash preparations of five normal pineal gland autopsy specimens with Papanicolaou and Diff-Quik® (Dade Behring, Newark, DE) stains. Infant preparations were highly cellular smears composed of numerous, uniform, single cells with indistinct cytoplasm, small round-to-oval nuclei, fine chromatin, and absent nucleoli and calcifications. The vague microfollicular pattern mimicked a pineocytoma and the fine fibrillary background mimicked a glial neoplasm. Young adult smears were similar; however, microcalcifications were present with fewer background single cells. Older patients had much less cellular smears composed of small clusters of cells with fusiform-to-spindle nuclei, a fine chromatin pattern, and indistinct cytoplasmic borders. There were fewer background single cells and more microcalcifications. The cytologic features of the native pineal gland vary with age. Normal pineal tissue can be confused with a pineocytoma or low-grade glioma. Familiarity with normal pineal gland cytological features will help to avoid a potential misdiagnosis. © 2014 Wiley Periodicals, Inc.

Reducing false positives of microcalcification detection systems by removal of breast arterial calcifications

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

Mordang, Jan-Jurre, E-mail: Jan-Jurre.Mordang@radboudumc.nl; Gubern-Mérida, Albert; Karssemeijer, Nico

Purpose: In the past decades, computer-aided detection (CADe) systems have been developed to aid screening radiologists in the detection of malignant microcalcifications. These systems are useful to avoid perceptual oversights and can increase the radiologists’ detection rate. However, due to the high number of false positives marked by these CADe systems, they are not yet suitable as an independent reader. Breast arterial calcifications (BACs) are one of the most frequent false positives marked by CADe systems. In this study, a method is proposed for the elimination of BACs as positive findings. Removal of these false positives will increase the performancemore » of the CADe system in finding malignant microcalcifications. Methods: A multistage method is proposed for the removal of BAC findings. The first stage consists of a microcalcification candidate selection, segmentation and grouping of the microcalcifications, and classification to remove obvious false positives. In the second stage, a case-based selection is applied where cases are selected which contain BACs. In the final stage, BACs are removed from the selected cases. The BACs removal stage consists of a GentleBoost classifier trained on microcalcification features describing their shape, topology, and texture. Additionally, novel features are introduced to discriminate BACs from other positive findings. Results: The CADe system was evaluated with and without BACs removal. Here, both systems were applied on a validation set containing 1088 cases of which 95 cases contained malignant microcalcifications. After bootstrapping, free-response receiver operating characteristics and receiver operating characteristics analyses were carried out. Performance between the two systems was compared at 0.98 and 0.95 specificity. At a specificity of 0.98, the sensitivity increased from 37% to 52% and the sensitivity increased from 62% up to 76% at a specificity of 0.95. Partial areas under the curve in the specificity range of 0.8–1.0 were significantly different between the system without BACs removal and the system with BACs removal, 0.129 ± 0.009 versus 0.144 ± 0.008 (p<0.05), respectively. Additionally, the sensitivity at one false positive per 50 cases and one false positive per 25 cases increased as well, 37% versus 51% (p<0.05) and 58% versus 67% (p<0.05) sensitivity, respectively. Additionally, the CADe system with BACs removal reduces the number of false positives per case by 29% on average. The same sensitivity at one false positive per 50 cases in the CADe system without BACs removal can be achieved at one false positive per 80 cases in the CADe system with BACs removal. Conclusions: By using dedicated algorithms to detect and remove breast arterial calcifications, the performance of CADe systems can be improved, in particular, at false positive rates representative for operating points used in screening.« less

Morphological filtering and multiresolution fusion for mammographic microcalcification detection

NASA Astrophysics Data System (ADS)

Chen, Lulin; Chen, Chang W.; Parker, Kevin J.

1997-04-01

Mammographic images are often of relatively low contrast and poor sharpness with non-stationary background or clutter and are usually corrupted by noise. In this paper, we propose a new method for microcalcification detection using gray scale morphological filtering followed by multiresolution fusion and present a unified general filtering form called the local operating transformation for whitening filtering and adaptive thresholding. The gray scale morphological filters are used to remove all large areas that are considered as non-stationary background or clutter variations, i.e., to prewhiten images. The multiresolution fusion decision is based on matched filter theory. In addition to the normal matched filter, the Laplacian matched filter which is directly related through the wavelet transforms to multiresolution analysis is exploited for microcalcification feature detection. At the multiresolution fusion stage, the region growing techniques are used in each resolution level. The parent-child relations between resolution levels are adopted to make final detection decision. FROC is computed from test on the Nijmegen database.

Computer aided system for segmentation and visualization of microcalcifications in digital mammograms.

PubMed

Reljin, Branimir; Milosević, Zorica; Stojić, Tomislav; Reljin, Irini

2009-01-01

Two methods for segmentation and visualization of microcalcifications in digital or digitized mammograms are described. First method is based on modern mathematical morphology, while the second one uses the multifractal approach. In the first method, by using an appropriate combination of some morphological operations, high local contrast enhancement, followed by significant suppression of background tissue, irrespective of its radiology density, is obtained. By iterative procedure, this method highly emphasizes only small bright details, possible microcalcifications. In a multifractal approach, from initial mammogram image, a corresponding multifractal "images" are created, from which a radiologist has a freedom to change the level of segmentation. An appropriate user friendly computer aided visualization (CAV) system with embedded two methods is realized. The interactive approach enables the physician to control the level and the quality of segmentation. Suggested methods were tested through mammograms from MIAS database as a gold standard, and from clinical praxis, using digitized films and digital images from full field digital mammograph.

Improving the accuracy in detection of clustered microcalcifications with a context-sensitive classification model.

PubMed

Wang, Juan; Nishikawa, Robert M; Yang, Yongyi

2016-01-01

In computer-aided detection of microcalcifications (MCs), the detection accuracy is often compromised by frequent occurrence of false positives (FPs), which can be attributed to a number of factors, including imaging noise, inhomogeneity in tissue background, linear structures, and artifacts in mammograms. In this study, the authors investigated a unified classification approach for combating the adverse effects of these heterogeneous factors for accurate MC detection. To accommodate FPs caused by different factors in a mammogram image, the authors developed a classification model to which the input features were adapted according to the image context at a detection location. For this purpose, the input features were defined in two groups, of which one group was derived from the image intensity pattern in a local neighborhood of a detection location, and the other group was used to characterize how a MC is different from its structural background. Owing to the distinctive effect of linear structures in the detector response, the authors introduced a dummy variable into the unified classifier model, which allowed the input features to be adapted according to the image context at a detection location (i.e., presence or absence of linear structures). To suppress the effect of inhomogeneity in tissue background, the input features were extracted from different domains aimed for enhancing MCs in a mammogram image. To demonstrate the flexibility of the proposed approach, the authors implemented the unified classifier model by two widely used machine learning algorithms, namely, a support vector machine (SVM) classifier and an Adaboost classifier. In the experiment, the proposed approach was tested for two representative MC detectors in the literature [difference-of-Gaussians (DoG) detector and SVM detector]. The detection performance was assessed using free-response receiver operating characteristic (FROC) analysis on a set of 141 screen-film mammogram (SFM) images (66 cases) and a set of 188 full-field digital mammogram (FFDM) images (95 cases). The FROC analysis results show that the proposed unified classification approach can significantly improve the detection accuracy of two MC detectors on both SFM and FFDM images. Despite the difference in performance between the two detectors, the unified classifiers can reduce their FP rate to a similar level in the output of the two detectors. In particular, with true-positive rate at 85%, the FP rate on SFM images for the DoG detector was reduced from 1.16 to 0.33 clusters/image (unified SVM) and 0.36 clusters/image (unified Adaboost), respectively; similarly, for the SVM detector, the FP rate was reduced from 0.45 clusters/image to 0.30 clusters/image (unified SVM) and 0.25 clusters/image (unified Adaboost), respectively. Similar FP reduction results were also achieved on FFDM images for the two MC detectors. The proposed unified classification approach can be effective for discriminating MCs from FPs caused by different factors (such as MC-like noise patterns and linear structures) in MC detection. The framework is general and can be applicable for further improving the detection accuracy of existing MC detectors.

Computer object segmentation by nonlinear image enhancement, multidimensional clustering, and geometrically constrained contour optimization

NASA Astrophysics Data System (ADS)

Bruynooghe, Michel M.

1998-04-01

In this paper, we present a robust method for automatic object detection and delineation in noisy complex images. The proposed procedure is a three stage process that integrates image segmentation by multidimensional pixel clustering and geometrically constrained optimization of deformable contours. The first step is to enhance the original image by nonlinear unsharp masking. The second step is to segment the enhanced image by multidimensional pixel clustering, using our reducible neighborhoods clustering algorithm that has a very interesting theoretical maximal complexity. Then, candidate objects are extracted and initially delineated by an optimized region merging algorithm, that is based on ascendant hierarchical clustering with contiguity constraints and on the maximization of average contour gradients. The third step is to optimize the delineation of previously extracted and initially delineated objects. Deformable object contours have been modeled by cubic splines. An affine invariant has been used to control the undesired formation of cusps and loops. Non linear constrained optimization has been used to maximize the external energy. This avoids the difficult and non reproducible choice of regularization parameters, that are required by classical snake models. The proposed method has been applied successfully to the detection of fine and subtle microcalcifications in X-ray mammographic images, to defect detection by moire image analysis, and to the analysis of microrugosities of thin metallic films. The later implementation of the proposed method on a digital signal processor associated to a vector coprocessor would allow the design of a real-time object detection and delineation system for applications in medical imaging and in industrial computer vision.

Hepatic alveolar echinococcosis: correlative US and CT study

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

Didier, D.; Weiler, S.; Rohmer, P.

1985-01-01

A total of 24 cases of hepatic alveolar echinococcosis (HAE) due to Echinococcus multilocularis was assessed by US and CT. The diagnosis was confirmed in all cases by immunologic and histologic study. Both US and CT patterns of HAE showed changes of liver morphology in both contour and size. Abnormal areas of parenchyma were nodular or in fields, irregular, heterogeneous, and basically echogenic. Clustered microcalcifications were encountered within the abnormal parenchymal fields in 50% of cases, and necrotized zones occurred in 40% of cases. Dilatation of intrahepatic bile ducts was commonly seen, especially on US; hilar involvement was frequent. Follow-upmore » by both techniques can display increases of primary lesions, occurrence of new foci, and local or regional extensions. Precise evaluations of the lesions arising from correlative use of US and CT permits adequate therapeutic management.« less

Flat epithelial atypia in directional vacuum-assisted biopsy of breast microcalcifications: surgical excision may not be necessary.

PubMed

McCroskey, Zulfia; Sneige, Nour; Herman, Carolyn R; Miller, Ross A; Venta, Luz A; Ro, Jae Y; Schwartz, Mary R; Ayala, Alberto G

2018-02-21

The aim of this study was to analyze the clinicopathological features of patients with flat epithelial atypia, diagnosed in directional vacuum-assisted biopsy targeting microcalcifications, to identify upgrade rate to in situ ductal or invasive breast carcinoma, and determine factors predicting carcinoma in the subsequent excision. We retrospectively evaluated the histological, clinical, and mammographic features of 69 cases from 65 women, with directional vacuum-assisted biopsy-diagnosed flat epithelial atypia with or without atypical ductal hyperplasia or atypical lobular hyperplasia, which underwent subsequent surgical excision. The extent and percentage of microcalcifications sampled by directional vacuum-assisted biopsy were evaluated by mammography. All biopsy and surgical excision slides were reviewed. The age of the women ranged from 40 to 85 years (mean 57 years). All patients presented with mammographically detected microcalcifications only, except in one case that had associated architectural distortion. Extent of calcifications ranged from <1 cm (n = 47), 1-3 cm (n = 15) to > 3 cm (n = 6), and no measurement (n = 1). A mean of 11 cores (range 6-25) was obtained from each lesion. Post-biopsy mammogram revealed >90% removal of calcifications in 81% of cases. Pure flat epithelial atypia represented nearly two-thirds of directional vacuum-assisted biopsy specimens (n = 43, 62%), while flat epithelial atypia coexisted with atypical ductal hyperplasia (18 cases, 26%), or atypical lobular hyperplasia (8 cases, 12%). Upon excision, none of the cases were upgraded to in situ ductal or invasive breast cancer. In one case, however, an incidental, tubular carcinoma (4 mm) was found away from biopsy site. Excluding this case, the upgrade rate was 0%. Our study adds to the growing evidence that diagnosis of flat epithelial atypia on directional vacuum-assisted biopsy for microcalcifications as the only imaging finding is not associated with a significant upgrade to carcinoma on excision, and therefore, excision may not be necessary. Additionally, excision may not be necessary for flat epithelial atypia with atypical ductal hyperplasia limited to ≤2 terminal duct-lobular units, if at least 90% of calcifications have been removed on biopsy.

Flat epithelial atypia: conservative management of patients without residual microcalcifications post-vacuum-assisted breast biopsy.

PubMed

Schiaffino, Simone; Gristina, Licia; Villa, Alessandro; Tosto, Simona; Monetti, Francesco; Carli, Franca; Calabrese, Massimo

2018-01-01

To determine the malignancy rate (defined in this study as stability or absence of malignancy developed on close imaging follow-up post-biopsy) of conservative management in patients with a vacuum-assisted breast biopsy (VAB) diagnosis of flat epithelial atypia (FEA), performed on single group of microcalcifications, completely removed during procedure. This is a retrospective, monocentric, observational study, approved by IRB. Inclusion criteria were: VAB performed on a single group of microcalcifications; the absence of residual calcifications post-VAB; diagnosis of isolated FEA as the most advanced proliferative lesion; radiological follow-up at least of 12 months. The personal history of breast cancer or other high-risk lesions was an exclusion criteria. The patients enrolled were conservatively managed, without surgical excision, through close follow-up: the first two mammographies performed with an interval of 6 months after biopsy, followed by annual mammographic and clinical checks. 48 consecutive patients were enrolled in the study, all females, with age range of 39-76 years (mean 53,3 years) and radiological follow-up range of 13-75 months (mean 41.5 months). All the lesions were classified as BI-RADS 4b. The diameter range of the group of calcifications was 3-10 mm (mean 5, 6 mm). In each patient, 7 to 15 samples (mean 11) were obtained. Among all the patients, there was only one case (2%) of new microcalcifications, developed in the same breast, 26 months after and 8 mm from the site of previous VAB, and interpreted as ADH at surgical excision. All the checks of the other patients were negative. Even with a limited follow-up, we found a malignancy rate lower than 2%, through a defined population. Further studies with bigger number of patients and extended follow-up are needed to reinforce this hypothesis. Advances in knowledge: Surgical excision may not be necessary in patients with VAB diagnosis of isolated FEA, without residual microcalcifications post-procedure and considered concordant with the mammographic presentation, considering the low rate of malignancy at subsequent follow-ups.

A novel approach to breast cancer diagnosis via PET imaging of microcalcifications using 18F-NaF

PubMed Central

Wilson, George H.; Gore, John C.; Yankeelov, Thomas E.; Barnes, Stephanie; Peterson, Todd E.; True, Jarrod M.; Shokouhi, Sepideh; McIntyre, J. Oliver.; Sanders, Melinda; Abramson, Vandana; Ngyuen, The-Quyen; Mahadevan-Jansen, Anita; Tantawy, Mohammed N.

2015-01-01

Rationale Current radiological methods for diagnosing breast cancer detect specific morphological features of solid tumors and/or any associated calcium deposits. These deposits originate from an early molecular microcalcification process which consists of two types: type 1 is calcium oxylate (CO) and type II is carbonated calcium hydroxyapetite (HAP). Type I microcalcifications are mainly associated with benign tumors while type II have been shown to be produced, internally, by malignant cells. No current non-invasive in vivo techniques are available for detecting intratumoral microcalcifications. Such a technique would have a significant impact on breast cancer diagnosis and prognosis in preclinical and clinical settings. 18F-NaF PET has been solely used for bone imaging by targeting the bone HAP. In this work, we provide preliminary evidence that 18F-NaF PET imaging can be used to detect breast cancer by targeting the HAP lattice within the tumor microenvironment with high specificity and soft-tissue contrast-to-background ratio, while delineating tumors from inflammation. METHODS Mice were injected with approximately 106 MDA-MB-231 cells subcutaneously and imaged with 18F-NaF PET/CT in a 120 min dynamic sequence when the tumors reached a size of ~250 mm3. Regions-of-interest (ROIs) were drawn around the tumor, muscle, and bone. The concentration of the radiotracer within those ROIs were compared to one another. For comparison to inflammation, rats with inflammatory paws were subjected to 18F-NaF PET imaging. RESULTS Tumor uptake of 18F− was significantly higher (p<0.05) than muscle uptake where the tumor-to-muscle ratio was ~3.5. The presence of type II microcalcification in the MDA-MB-231 cell line was confirmed histologically using alizarin red S and von Kossa staining as well as Raman microspectroscopy. No uptake of 18F− was observed in the rat inflamed tissue. Lack of HAP in the inflamed tissue was verified histologically. CONCLUSIONS This study provides preliminary evidence suggesting that specific targeting of the HAP within the tumor microenvironment with 18F may be able to distinguishing between inflammation and cancer. PMID:24833491

[Efficacy of storage phosphor-based digital mammography in diagnosis of breast cancer--comparison with film-screen mammography].

PubMed

Kitahama, H

1991-05-25

The aim of this study is to present efficacy of storage phosphor-based digital mammography (CR-mammography) in diagnosis of breast cancer. Ninety-seven cases with breast cancer including 44 cases less than 2 cm in macroscopic size (t1 cases) were evaluated using storage phosphor-based digital mammography (2000 x 2510 pixels by 10 bits). Abnormal findings on CR-mammography were detected in 86 cases (88.7%) of 97 women with breast cancer. Sensitivity of CR-mammography was 88.7%. It was superior to that of film-screen mammography. On t1 breast cancer cases, sensitivity on CR-mammography was 88.6%. False negative rate in t1 breast cancer cases was reduced by image processing using CR-mammography. To evaluate microcalcifications, CR-mammograms and film-screen mammograms were investigated in 22 cases of breast cancer proven pathologically the existence of microcalcifications and 11 paraffin tissue blocks of breast cancer. CR-mammography was superior to film-screen mammography in recognizing of microcalcifications. As regards the detectability for the number and the shape of microcalcifications, CR-mammography was equivalent to film-screen mammography. Receiver operating characteristic (ROC) analysis by eight observers was performed for CR-mammography and film-screen mammography with 54 breast cancer patients and 54 normal cases. The detectability of abnormal findings of breast cancer on CR-mammography (ROC area = 0.91) was better than that on film-screen mammography (ROC area = 0.88) (p less than 0.05). Efficacy of storage phosphor-based digital mammography in diagnosis of breast cancer was discussed and demonstrated in this study.

The radiological features, diagnosis and management of screen-detected lobular neoplasia of the breast: Findings from the Sloane Project.

PubMed

Maxwell, Anthony J; Clements, Karen; Dodwell, David J; Evans, Andrew J; Francis, Adele; Hussain, Monuwar; Morris, Julie; Pinder, Sarah E; Sawyer, Elinor J; Thomas, Jeremy; Thompson, Alastair

2016-06-01

To investigate the radiological features, diagnosis and management of screen-detected lobular neoplasia (LN) of the breast. 392 women with pure LN alone were identified within the prospective UK cohort study of screen-detected non-invasive breast neoplasia (the Sloane Project). Demography, radiological features and diagnostic and therapeutic procedures were analysed. Non-pleomorphic LN (369/392) was most frequently diagnosed among women aged 50-54 and in 53.5% was at the first screen. It occurred most commonly on the left (58.0%; p = 0.003), in the upper outer quadrant and confined to one site (single quadrant or retroareolar region). No bilateral cases were found. The predominant radiological feature was microcalcification (most commonly granular) which increased in frequency with increasing breast density. Casting microcalcification as a predominant feature had a significantly higher lesion size compared to granular and punctate patterns (p = 0.034). 326/369 (88.3%) women underwent surgery, including 17 who underwent >1 operation, six who had mastectomy and six who had axillary surgery. Two patients had radiotherapy and 15 had endocrine treatment. Pleomorphic lobular carcinoma in situ (23/392) presented as granular microcalcification in 12; four women had mastectomy and six had radiotherapy. Screen-detected LN occurs in relatively young women and is predominantly non-pleomorphic and unilateral. It is typically associated with granular or punctate microcalcification in the left upper outer quadrant. Management, including surgical resection, is highly variable and requires evidence-based guideline development. Copyright © 2016 Elsevier Ltd. All rights reserved.

An adaptive algorithm for the detection of microcalcifications in simulated low-dose mammography.

PubMed

Treiber, O; Wanninger, F; Führ, H; Panzer, W; Regulla, D; Winkler, G

2003-02-21

This paper uses the task of microcalcification detection as a benchmark problem to assess the potential for dose reduction in x-ray mammography. We present the results of a newly developed algorithm for detection of microcalcifications as a case study for a typical commercial film-screen system (Kodak Min-R 2000/2190). The first part of the paper deals with the simulation of dose reduction for film-screen mammography based on a physical model of the imaging process. Use of a more sensitive film-screen system is expected to result in additional smoothing of the image. We introduce two different models of that behaviour, called moderate and strong smoothing. We then present an adaptive, model-based microcalcification detection algorithm. Comparing detection results with ground-truth images obtained under the supervision of an expert radiologist allows us to establish the soundness of the detection algorithm. We measure the performance on the dose-reduced images in order to assess the loss of information due to dose reduction. It turns out that the smoothing behaviour has a strong influence on detection rates. For moderate smoothing. a dose reduction by 25% has no serious influence on the detection results. whereas a dose reduction by 50% already entails a marked deterioration of the performance. Strong smoothing generally leads to an unacceptable loss of image quality. The test results emphasize the impact of the more sensitive film-screen system and its characteristics on the problem of assessing the potential for dose reduction in film-screen mammography. The general approach presented in the paper can be adapted to fully digital mammography.

An adaptive algorithm for the detection of microcalcifications in simulated low-dose mammography

NASA Astrophysics Data System (ADS)

Treiber, O.; Wanninger, F.; Führ, H.; Panzer, W.; Regulla, D.; Winkler, G.

2003-02-01

This paper uses the task of microcalcification detection as a benchmark problem to assess the potential for dose reduction in x-ray mammography. We present the results of a newly developed algorithm for detection of microcalcifications as a case study for a typical commercial film-screen system (Kodak Min-R 2000/2190). The first part of the paper deals with the simulation of dose reduction for film-screen mammography based on a physical model of the imaging process. Use of a more sensitive film-screen system is expected to result in additional smoothing of the image. We introduce two different models of that behaviour, called moderate and strong smoothing. We then present an adaptive, model-based microcalcification detection algorithm. Comparing detection results with ground-truth images obtained under the supervision of an expert radiologist allows us to establish the soundness of the detection algorithm. We measure the performance on the dose-reduced images in order to assess the loss of information due to dose reduction. It turns out that the smoothing behaviour has a strong influence on detection rates. For moderate smoothing, a dose reduction by 25% has no serious influence on the detection results, whereas a dose reduction by 50% already entails a marked deterioration of the performance. Strong smoothing generally leads to an unacceptable loss of image quality. The test results emphasize the impact of the more sensitive film-screen system and its characteristics on the problem of assessing the potential for dose reduction in film-screen mammography. The general approach presented in the paper can be adapted to fully digital mammography.

A comparison of diagnostic performance of vacuum-assisted biopsy and core needle biopsy for breast microcalcification: a systematic review and meta-analysis.

PubMed

Huang, Xu Chen; Hu, Xu Hua; Wang, Xiao Ran; Zhou, Chao Xi; Wang, Fei Fei; Yang, Shan; Wang, Gui Ying

2018-03-16

Core needle biopsy (CNB) and vacuum-assisted biopsy (VAB) are both popularly used breast percutaneous biopsies. Both of them have become reliable alternatives to open surgical biopsy (OSB) for breast microcalcification (BM). It is controversial that which biopsy method is more accurate and safer for BM. Hence, we conducted this meta-analysis to compare the diagnostic performance between CNB and VAB for BM, aiming to find out the better method. Articles according with including and excluding criteria were collected from the databases, PubMed, Embase, and the Cochrane Library. Preset outcomes were abstracted and pooled to find out the potential advantages in CNB or VAB. Seven studies were identified and entered final meta-analysis from initially found 138 studies. The rate of ductal carcinoma in situ (DCIS) underestimation was significantly lower in VAB than CNB group [risk ratio (RR) = 1.83, 95% confidence interval (CI) 1.40 to 2.40, p < 0.001]. The microcalcification retrieval rate was significantly higher in VAB than CNB group (RR = 0.89, 95% CI 0.81 to 0.98, p = 0.02), while CNB owned a significantly lower complication rate than VAB (RR = 0.18, 95% CI 0.03 to 0.93, p = 0.04). The atypical ductal hyperplasia (ADH) underestimation rates were not compared for the limited number of studies reporting this outcome. Compared with CNB, VAB shows better diagnostic performance in DCIS underestimation rate and microcalcification retrieval rate. However, CNB shows a significantly lower complication rate. More studies are needed to verify these findings.

Analysis of perceived similarity between pairs of microcalcification clusters in mammograms

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

Wang, Juan; Jing, Hao; Wernick, Miles N.

2014-05-15

Purpose: Content-based image retrieval aims to assist radiologists by presenting example images with known pathology that are visually similar to the case being evaluated. In this work, the authors investigate several fundamental issues underlying the similarity ratings between pairs of microcalcification (MC) lesions on mammograms as judged by radiologists: the degree of variability in the similarity ratings, the impact of this variability on agreement between readers in retrieval of similar lesions, and the factors contributing to the readers’ similarity ratings. Methods: The authors conduct a reader study on a set of 1000 image pairs of MC lesions, in which amore » group of experienced breast radiologists rated the degree of similarity between each image pair. The image pairs are selected, from among possible pairings of 222 cases (110 malignant, 112 benign), based on quantitative image attributes (features) and the results of a preliminary reader study. Next, the authors apply analysis of variance (ANOVA) to quantify the level of variability in the readers’ similarity ratings, and study how the variability in individual reader ratings affects consistency between readers. The authors also measure the extent to which readers agree on images which are most similar to a given query, for which the Dice coefficient is used. To investigate how the similarity ratings potentially relate to the attributes underlying the cases, the authors study the fraction of perceptually similar images that also share the same benign or malignant pathology as the query image; moreover, the authors apply multidimensional scaling (MDS) to embed the cases according to their mutual perceptual similarity in a two-dimensional plot, which allows the authors to examine the manner in which similar lesions relate to one another in terms of benign or malignant pathology and clustered MCs. Results: The ANOVA results show that the coefficient of determination in the reader similarity ratings is 0.59. The variability level in the similarity ratings is proved to be a limiting factor, leading to only moderate correlation between the readers in their readings. The Dice coefficient, measuring agreement between readers in retrieval of similar images, can vary from 0.45 to 0.64 with different levels of similarity for individual readers, but is higher for average ratings from a group of readers (from 0.59 to 0.78). More importantly, the fraction of retrieved cases that match the benign or malignant pathology of the query image was found to increase with the degree of similarity among the retrieved images, reaching average value as high as 0.69 for the radiologists (p-value <10{sup −4} compared to random guessing). Moreover, MDS embedding of all the cases shows that cases having the same pathology tend to cluster together, and that neighboring cases in the plot tend to be similar in their clustered MCs. Conclusions: While individual readers exhibit substantial variability in their similarity ratings, similarity ratings averaged from a group of readers can achieve a high level of intergroup consistency and agreement in retrieval of similar images. More importantly, perceptually similar cases are also likely to be similar in their underlying benign or malignant pathology and image features of clustered MCs, which could be of diagnostic value in computer-aided diagnosis for lesions with clustered MCs.« less

Impact of compressed breast thickness and dose on lesion detectability in digital mammography: FROC study with simulated lesions in real mammograms

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

Salvagnini, Elena, E-mail: elena.salvagnini@gmail.

Purpose: The aim of this work was twofold: (1) to examine whether, with standard automatic exposure control (AEC) settings that maintain pixel values in the detector constant, lesion detectability in clinical images decreases as a function of breast thickness and (2) to verify whether a new AEC setup can increase lesion detectability at larger breast thicknesses. Methods: Screening patient images, acquired on two identical digital mammography systems, were collected over a period of 2 yr. Mammograms were acquired under standard AEC conditions (part 1) and subsequently with a new AEC setup (part 2), programmed to use the standard AEC settingsmore » for compressed breast thicknesses ≤49 mm, while a relative dose increase was applied above this thickness. The images were divided into four thickness groups: T1 ≤ 29 mm, T2 = 30–49 mm, T3 = 50–69 mm, and T4 ≥ 70 mm, with each thickness group containing 130 randomly selected craniocaudal lesion-free images. Two measures of density were obtained for every image: a BI-RADS score and a map of volumetric breast density created with a software application (VolparaDensity, Matakina, NZ). This information was used to select subsets of four images, containing one image from each thickness group, matched to a (global) BI-RADS score and containing a region with the same (local) VOLPARA volumetric density value. One selected lesion (a microcalcification cluster or a mass) was simulated into each of the four images. This process was repeated so that, for a given thickness group, half the images contained a single lesion and half were lesion-free. The lesion templates created and inserted in groups T3 and T4 for the first part of the study were then inserted into the images of thickness groups T3 and T4 acquired with higher dose settings. Finally, all images were visualized using the ViewDEX software and scored by four radiologists performing a free search study. A statistical jackknife-alternative free-response receiver operating characteristic analysis was applied. Results: For part 1, the alternative free-response receiver operating characteristic curves for the four readers were 0.80, 0.65, 0.55 and 0.56 in going from T1 to T4, indicating a decrease in detectability with increasing breast thickness. P-values and the 95% confidence interval showed no significant difference for the T3-T4 comparison (p = 0.78) while all the other differences were significant (p < 0.05). Separate analysis of microcalcification clusters presented the same results while for mass detection, the only significant difference came when comparing T1 to the other thickness groups. Comparing the scores of part 1 and part 2, results for the T3 group acquired with the new AEC setup and T3 group at standard AEC doses were significantly different (p = 0.0004), indicating improved detection. For this group a subanalysis for microcalcification detection gave the same results while no significant difference was found for mass detection. Conclusions: These data using clinical images confirm results found in simple QA tests for many mammography systems that detectability falls as breast thickness increases. Results obtained with the AEC setup for constant detectability above 49 mm showed an increase in lesion detection with compressed breast thickness, bringing detectability of lesions to the same level.« less

Noninvasive Molecular Imaging of Disease Activity in Atherosclerosis

PubMed Central

Aikawa, Elena; Newby, David E.; Tarkin, Jason M.; Rudd, James H.F.; Narula, Jagat; Fayad, Zahi A.

2016-01-01

Major focus has been placed on the identification of vulnerable plaques as a means of improving the prediction of myocardial infarction. However, this strategy has recently been questioned on the basis that the majority of these individual coronary lesions do not in fact go on to cause clinical events. Attention is, therefore, shifting to alternative imaging modalities that might provide a more complete pan-coronary assessment of the atherosclerotic disease process. These include markers of disease activity with the potential to discriminate between patients with stable burnt-out disease that is no longer metabolically active and those with active atheroma, faster disease progression, and increased risk of infarction. This review will examine how novel molecular imaging approaches can provide such assessments, focusing on inflammation and microcalcification activity, the importance of these processes to coronary atherosclerosis, and the advantages and challenges posed by these techniques. PMID:27390335

Breast 3 T-MR imaging: indication for stereotactic vacuum-assisted breast biopsy.

PubMed

Yamamoto, Nobuko; Yoshizako, Takeshi; Yoshikawa, Kazuaki; Itakura, Masayuki; Maruyama, Riruke; Kitagaki, Hajime

2014-01-01

The purpose of this study was to assess indications for stereotactic vacuum-assisted breast biopsy (SVAB) evaluated by breast 3 T-magnetic resonance (3 T-MR) imaging in patients showing suspicious microcalcifications on mammography and negative ultrasound (US) findings. Fifty-five patients with 55 breast lesions showing suspicious microcalcifications on mammography and negative US findings underwent preoperative 3 T-MR examination including dynamic MR imaging. All patients underwent SVAB within 1 month of MR imaging. The pathological diagnosis of each breast lesion was made by examining tissues obtained by SVAB or radical/partial mastectomy. 3 T-MR imaging findings were evaluated by using the American College of Radiology Breast Imaging Reporting and Data System Atlas (BI-RADS-MRI) and then were correlated with the histopathological findings. When BI-RADS 4 and 5 MR imaging lesions were assumed to be malignant, the usefulness of 3 T-MR imaging was evaluated for diagnosis of impalpable breast lesions by SVAB among lesions with microcalcification detected by mammography and negative US findings. There were 21 malignant lesions, including 5 invasive ductal carcinomas, 16 lesions of ductal carcinoma in situ (DCIS). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 3 T-MR imaging for deciding the indications for SVAB was 90.5%, 97.1%, 95.0%, 94.3%, and 94.5%, respectively. The one-false negative case was a DCIS with small enhancing lesions (0.5 mm). The one false-positive case was ductal adenoma with a linear ductal pattern of enhancement. 3 T-MR imaging may be useful for deciding the indications for SVAB in patients who have breast lesions with microcalcification that are impalpable and are detected by mammography and negative US findings. However, our findings should be considered preliminary and further prospective investigation is required.

Differentiation of Ductal Carcinoma In-Situ from Benign Micro-Calcifications by Dedicated Breast Computed Tomography

PubMed Central

Shakeri, Shadi A.; Abbey, Craig K.; Gazi, Peymon; Prionas, Nicolas; Nosratieh, Anita; Li, Chin-Shang; Boone, John M.; Lindfors, Karen K.

2015-01-01

Purpose Compare conspicuity of ductal carcinoma in-situ (DCIS) to benign calcifications on unenhanced (bCT), contrast-enhanced dedicated breast CT (CEbCT) and mammography (DM). Methods and Materials The institutional review board approved this HIPAA-compliant study. 42 women with Breast Imaging Reporting and Data System 4 or 5 category micro-calcifications had breast CT before biopsy. Three subjects with invasive disease at surgery were excluded. Two breast radiologists independently compared lesion conspicuity scores (CS) for CEbCT, to bCT and DM. Enhancement was measured in Hounsfield units (HU). Mean CS ± standard deviations are shown. Receiver operating characteristic analysis (ROC) measured radiologists’ discrimination performance by comparing CS to enhancement alone. Statistical measurements were made using ANOVA F-test, Wilcoxon rank-sum test and robust linear regression analyses. Results 39 lesions (17 DCIS, 22 benign) were analyzed. DCIS (8.5±0.9, n=17) was more conspicuous than benign micro-calcifications (3.6±2.9, n=22; p<0.0001) on CEbCT. DCIS was equally conspicuous on CEbCT and DM (8.5±0.9, 8.7±0.8, n=17; p=0.85) and more conspicuous when compared to bCT (5.3±2.6, n=17; p<0.001). All DCIS enhanced; mean enhancement (90HU ±53HU, n=17) was higher compared to benign lesions (33 ±30HU, n=22)(p<0.0001). ROC analysis of the radiologists’ CS showed high discrimination performance (AUC=0.94) compared to enhancement alone (AUC=0.85) (p<0.026). Conclusion DCIS is more conspicuous than benign micro-calcifications on CEbCT. DCIS visualization on CEbCT is equal to mammography but improved compared to bCT. Radiologists’ discrimination performance using CEBCT is significantly higher than enhancement values alone. CEbCT may have an advantage over mammography by reducing false positive examinations when calcifications are analyzed. PMID:26520874

Hierarchical Segmentation Enhances Diagnostic Imaging

NASA Technical Reports Server (NTRS)

2007-01-01

Bartron Medical Imaging LLC (BMI), of New Haven, Connecticut, gained a nonexclusive license from Goddard Space Flight Center to use the RHSEG software in medical imaging. To manage image data, BMI then licensed two pattern-matching software programs from NASA's Jet Propulsion Laboratory that were used in image analysis and three data-mining and edge-detection programs from Kennedy Space Center. More recently, BMI made NASA history by being the first company to partner with the Space Agency through a Cooperative Research and Development Agreement to develop a 3-D version of RHSEG. With U.S. Food and Drug Administration clearance, BMI will sell its Med-Seg imaging system with the 2-D version of the RHSEG software to analyze medical imagery from CAT and PET scans, MRI, ultrasound, digitized X-rays, digitized mammographies, dental X-rays, soft tissue analyses, moving object analyses, and soft-tissue slides such as Pap smears for the diagnoses and management of diseases. Extending the software's capabilities to three dimensions will eventually enable production of pixel-level views of a tumor or lesion, early identification of plaque build-up in arteries, and identification of density levels of microcalcification in mammographies.

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

PubMed Central

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

2013-01-01

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

DAFi: A directed recursive data filtering and clustering approach for improving and interpreting data clustering identification of cell populations from polychromatic flow cytometry data.

PubMed

Lee, Alexandra J; Chang, Ivan; Burel, Julie G; Lindestam Arlehamn, Cecilia S; Mandava, Aishwarya; Weiskopf, Daniela; Peters, Bjoern; Sette, Alessandro; Scheuermann, Richard H; Qian, Yu

2018-04-17

Computational methods for identification of cell populations from polychromatic flow cytometry data are changing the paradigm of cytometry bioinformatics. Data clustering is the most common computational approach to unsupervised identification of cell populations from multidimensional cytometry data. However, interpretation of the identified data clusters is labor-intensive. Certain types of user-defined cell populations are also difficult to identify by fully automated data clustering analysis. Both are roadblocks before a cytometry lab can adopt the data clustering approach for cell population identification in routine use. We found that combining recursive data filtering and clustering with constraints converted from the user manual gating strategy can effectively address these two issues. We named this new approach DAFi: Directed Automated Filtering and Identification of cell populations. Design of DAFi preserves the data-driven characteristics of unsupervised clustering for identifying novel cell subsets, but also makes the results interpretable to experimental scientists through mapping and merging the multidimensional data clusters into the user-defined two-dimensional gating hierarchy. The recursive data filtering process in DAFi helped identify small data clusters which are otherwise difficult to resolve by a single run of the data clustering method due to the statistical interference of the irrelevant major clusters. Our experiment results showed that the proportions of the cell populations identified by DAFi, while being consistent with those by expert centralized manual gating, have smaller technical variances across samples than those from individual manual gating analysis and the nonrecursive data clustering analysis. Compared with manual gating segregation, DAFi-identified cell populations avoided the abrupt cut-offs on the boundaries. DAFi has been implemented to be used with multiple data clustering methods including K-means, FLOCK, FlowSOM, and the ClusterR package. For cell population identification, DAFi supports multiple options including clustering, bisecting, slope-based gating, and reversed filtering to meet various autogating needs from different scientific use cases. © 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

Cone-beam micro computed tomography dedicated to the breast.

PubMed

Sarno, Antonio; Mettivier, Giovanni; Di Lillo, Francesca; Cesarelli, Mario; Bifulco, Paolo; Russo, Paolo

2016-12-01

We developed a scanner for micro computed tomography dedicated to the breast (BµCT) with a high resolution flat-panel detector and a microfocus X-ray tube. We evaluated the system spatial resolution via the 3D modulation transfer function (MTF). In addition to conventional absorption-based X-ray imaging, such a prototype showed capabilities for propagation-based phase-contrast and related edge enhancement effects in 3D imaging. The system limiting spatial resolution is 6.2mm -1 (MTF at 10%) in the vertical direction and 3.8mm -1 in the radial direction, values which compare favorably with the spatial resolution reached by mini focus breast CT scanners of other groups. The BµCT scanner was able to detect both microcalcification clusters and masses in an anthropomorphic breast phantom at a dose comparable to that of two-view mammography. The use of a breast holder is proposed in order to have 1-2min long scan times without breast motion artifacts. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Values of pathological analysis of lost tissue fragments in the vacuum canister during a vacuum-assisted stereotactic biopsy of the breast.

PubMed

El Khoury, M; Mesurolle, B; Omeroglu, A; Aldis, A; Kao, E

2013-05-01

Determine values of pathological analysis of the canister content during a vacuum-assisted breast biopsy (VABB). Approval was obtained from the ethical committee. Prospective radiological and pathological analyses of the canister content collected during 231 VABBs performed on 231 patients were carried out. χ(2) test was used to determine predictors on canister pathology. The canister pathology was reported separately in 212 cases. It showed only blood in 78/212 (37%) cases and benign (including high-risk lesions) and malignant results in, respectively, 113/212 (53%) and 21/212 (10%) cases. Respective specimen analysis was benign, including high-risk lesions in 162/212 cases (76%) and malignant in 50/212 (24%) cases. Microcalcifications were documented on canister X-ray in 70/231 (30%) cases. There was significant association between the canister and the specimen pathology (p<0.0001). In none of the cases was microcalcifications seen exclusively in the canister content or pathological upgrading found in the canister content compared with the specimen. Small tissue fragments and microcalcifications may be lost in the canister during a VABB. Nevertheless, our results did not show any significant value for systematic analysis of the canister content. There is no added diagnostic value to retrieval and analysis of tissue lost in the canister during a VABB.

Evaluation of search strategies for microcalcifications and masses in 3D images

NASA Astrophysics Data System (ADS)

Eckstein, Miguel P.; Lago, Miguel A.; Abbey, Craig K.

2018-03-01

Medical imaging is quickly evolving towards 3D image modalities such as computed tomography (CT), magnetic resonance imaging (MRI) and digital breast tomosynthesis (DBT). These 3D image modalities add volumetric information but further increase the need for radiologists to search through the image data set. Although much is known about search strategies in 2D images less is known about the functional consequences of different 3D search strategies. We instructed readers to use two different search strategies: drillers had their eye movements restricted to a few regions while they quickly scrolled through the image stack, scanners explored through eye movements the 2D slices. We used real-time eye position monitoring to ensure observers followed the drilling or the scanning strategy while approximately preserving the percentage of the volumetric data covered by the useful field of view. We investigated search for two signals: a simulated microcalcification and a larger simulated mass. Results show an interaction between the search strategy and lesion type. In particular, scanning provided significantly better detectability for microcalcifications at the cost of 5 times more time to search while there was little change in the detectability for the larger simulated masses. Analyses of eye movements support the hypothesis that the effectiveness of a search strategy in 3D imaging arises from the interaction of the fixational sampling of visual information and the signals' visibility in the visual periphery.

Classification of breast microcalcifications using spectral mammography

NASA Astrophysics Data System (ADS)

Ghammraoui, B.; Glick, S. J.

2017-03-01

Purpose: To investigate the potential of spectral mammography to distinguish between type I calcifications, consisting of calcium oxalate dihydrate or weddellite compounds that are more often associated with benign lesions, and type II calcifications containing hydroxyapatite which are predominantly associated with malignant tumors. Methods: Using a ray tracing algorithm, we simulated the total number of x-ray photons recorded by the detector at one pixel from a single pencil-beam projection through a breast of 50/50 (adipose/glandular) tissues with inserted microcalcifications of different types and sizes. Material decomposition using two energy bins was then applied to characterize the simulated calcifications into hydroxyapatite and weddellite using maximumlikelihood estimation, taking into account the polychromatic source, the detector response function and the energy dependent attenuation. Results: Simulation tests were carried out for different doses and calcification sizes for multiple realizations. The results were summarized using receiver operating characteristic (ROC) analysis with the area under the curve (AUC) taken as an overall indicator of discrimination performance and showing high AUC values up to 0.99. Conclusion: Our simulation results obtained for a uniform breast imaging phantom indicate that spectral mammography using two energy bins has the potential to be used as a non-invasive method for discrimination between type I and type II microcalcifications to improve early breast cancer diagnosis and reduce the number of unnecessary breast biopsies.

Quantitative comparison of clustered microcalcifications in for-presentation and for-processing mammograms in full-field digital mammography.

PubMed

Wang, Juan; Nishikawa, Robert M; Yang, Yongyi

2017-07-01

Mammograms acquired with full-field digital mammography (FFDM) systems are provided in both "for-processing'' and "for-presentation'' image formats. For-presentation images are traditionally intended for visual assessment by the radiologists. In this study, we investigate the feasibility of using for-presentation images in computerized analysis and diagnosis of microcalcification (MC) lesions. We make use of a set of 188 matched mammogram image pairs of MC lesions from 95 cases (biopsy proven), in which both for-presentation and for-processing images are provided for each lesion. We then analyze and characterize the MC lesions from for-presentation images and compare them with their counterparts in for-processing images. Specifically, we consider three important aspects in computer-aided diagnosis (CAD) of MC lesions. First, we quantify each MC lesion with a set of 10 image features of clustered MCs and 12 textural features of the lesion area. Second, we assess the detectability of individual MCs in each lesion from the for-presentation images by a commonly used difference-of-Gaussians (DoG) detector. Finally, we study the diagnostic accuracy in discriminating between benign and malignant MC lesions from the for-presentation images by a pretrained support vector machine (SVM) classifier. To accommodate the underlying background suppression and image enhancement in for-presentation images, a normalization procedure is applied. The quantitative image features of MC lesions from for-presentation images are highly consistent with that from for-processing images. The values of Pearson's correlation coefficient between features from the two formats range from 0.824 to 0.961 for the 10 MC image features, and from 0.871 to 0.963 for the 12 textural features. In detection of individual MCs, the FROC curve from for-presentation is similar to that from for-processing. In particular, at sensitivity level of 80%, the average number of false-positives (FPs) per image region is 9.55 for both for-presentation and for-processing images. Finally, for classifying MC lesions as malignant or benign, the area under the ROC curve is 0.769 in for-presentation, compared to 0.761 in for-processing (P = 0.436). The quantitative results demonstrate that MC lesions in for-presentation images are highly consistent with that in for-processing images in terms of image features, detectability of individual MCs, and classification accuracy between malignant and benign lesions. These results indicate that for-presentation images can be compatible with for-processing images for use in CAD algorithms for MC lesions. © 2017 American Association of Physicists in Medicine.

SU-D-206-06: Task-Specific Optimization of Scintillator Thickness for CMOS-Detector Based Cone-Beam Breast CT

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

Vedantham, S; Shrestha, S; Shi, L

Purpose: To optimize the cesium iodide (CsI:Tl) scintillator thickness in a complimentary metal-oxide semiconductor (CMOS)-based detector for use in dedicated cone-beam breast CT. Methods: The imaging task considered was the detection of a microcalcification cluster comprising six 220µm diameter calcium carbonate spheres, arranged in the form of a regular pentagon with 2 mm spacing on its sides and a central calcification, similar to that in ACR-recommended mammography accreditation phantom, at a mean glandular dose of 4.5 mGy. Generalized parallel-cascades based linear systems analysis was used to determine Fourier-domain image quality metrics in reconstructed object space, from which the detectability indexmore » inclusive of anatomical noise was determined for a non-prewhitening numerical observer. For 300 projections over 2π, magnification-associated focal-spot blur, Monte Carlo derived x-ray scatter, K-fluorescent emission and reabsorption within CsI:Tl, CsI:Tl quantum efficiency and optical blur, fiberoptic plate transmission efficiency and blur, CMOS quantum efficiency, pixel aperture function and additive noise, and filtered back-projection to isotropic 105µm voxel pitch with bilinear interpolation were modeled. Imaging geometry of a clinical prototype breast CT system, a 60 kV Cu/Al filtered x-ray spectrum from 0.3 mm focal spot incident on a 14 cm diameter semi-ellipsoidal breast were used to determine the detectability index for 300–600 µm thick (75µm increments) CsI:Tl. The CsI:Tl thickness that maximized the detectability index was considered optimal. Results: The limiting resolution (10% modulation transfer function, MTF) progressively decreased with increasing CsI:Tl thickness. The zero-frequency detective quantum efficiency, DQE(0), in projection space increased with increasing CsI:Tl thickness. The maximum detectability index was achieved with 525µm thick CsI:Tl scintillator. Reduced MTF at mid-to-high frequencies for 600µm thick CsI:Tl lowered the detectability index than 525µm CsI:Tl. Conclusion: For the x-ray spectrum and imaging conditions considered, a 525µm thick CsI:Tl scintillator integrated with the CMOS detector is optimal for detecting microcalcification cluster. Funding support: Supported in part by NIH R01 CA195512. The contents are solely the responsibility of the authors and do not reflect the official views of the NIH or the NCI. Disclosures: SV, GV and AK - Research collaboration, Koning Corp., West Henrietta, NY.« less

Recognition of genetically modified product based on affinity propagation clustering and terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Jianjun; Kan, Jianquan

2018-04-01

In this paper, based on the terahertz spectrum, a new identification method of genetically modified material by support vector machine (SVM) based on affinity propagation clustering is proposed. This algorithm mainly uses affinity propagation clustering algorithm to make cluster analysis and labeling on unlabeled training samples, and in the iterative process, the existing SVM training data are continuously updated, when establishing the identification model, it does not need to manually label the training samples, thus, the error caused by the human labeled samples is reduced, and the identification accuracy of the model is greatly improved.

Large area CMOS active pixel sensor x-ray imager for digital breast tomosynthesis: Analysis, modeling, and characterization.

PubMed

Zhao, Chumin; Kanicki, Jerzy; Konstantinidis, Anastasios C; Patel, Tushita

2015-11-01

Large area x-ray imagers based on complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology have been proposed for various medical imaging applications including digital breast tomosynthesis (DBT). The low electronic noise (50-300 e-) of CMOS APS x-ray imagers provides a possible route to shrink the pixel pitch to smaller than 75 μm for microcalcification detection and possible reduction of the DBT mean glandular dose (MGD). In this study, imaging performance of a large area (29×23 cm2) CMOS APS x-ray imager [Dexela 2923 MAM (PerkinElmer, London)] with a pixel pitch of 75 μm was characterized and modeled. The authors developed a cascaded system model for CMOS APS x-ray imagers using both a broadband x-ray radiation and monochromatic synchrotron radiation. The experimental data including modulation transfer function, noise power spectrum, and detective quantum efficiency (DQE) were theoretically described using the proposed cascaded system model with satisfactory consistency to experimental results. Both high full well and low full well (LFW) modes of the Dexela 2923 MAM CMOS APS x-ray imager were characterized and modeled. The cascaded system analysis results were further used to extract the contrast-to-noise ratio (CNR) for microcalcifications with sizes of 165-400 μm at various MGDs. The impact of electronic noise on CNR was also evaluated. The LFW mode shows better DQE at low air kerma (Ka<10 μGy) and should be used for DBT. At current DBT applications, air kerma (Ka∼10 μGy, broadband radiation of 28 kVp), DQE of more than 0.7 and ∼0.3 was achieved using the LFW mode at spatial frequency of 0.5 line pairs per millimeter (lp/mm) and Nyquist frequency ∼6.7 lp/mm, respectively. It is shown that microcalcifications of 165-400 μm in size can be resolved using a MGD range of 0.3-1 mGy, respectively. In comparison to a General Electric GEN2 prototype DBT system (at MGD of 2.5 mGy), an increased CNR (by ∼10) for microcalcifications was observed using the Dexela 2923 MAM CMOS APS x-ray imager at a lower MGD (2.0 mGy). The Dexela 2923 MAM CMOS APS x-ray imager is capable to achieve a high imaging performance at spatial frequencies up to 6.7 lp/mm. Microcalcifications of 165 μm are distinguishable based on reported data and their modeling results due to the small pixel pitch of 75 μm. At the same time, potential dose reduction is expected using the studied CMOS APS x-ray imager.

Investigation of statistical iterative reconstruction for dedicated breast CT

PubMed Central

Makeev, Andrey; Glick, Stephen J.

2013-01-01

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

BioCluster: tool for identification and clustering of Enterobacteriaceae based on biochemical data.

PubMed

Abdullah, Ahmed; Sabbir Alam, S M; Sultana, Munawar; Hossain, M Anwar

2015-06-01

Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochemical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor-intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and similarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface (GUI) tool named BioCluster. This tool was designed for automated clustering and identification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering (HC) and the Improved Hierarchical Clustering (IHC), a modified algorithm that was developed specifically for the clustering and identification of Enterobacteriaceae species. IHC takes into account the variability in result of 1-47 biochemical tests within this Enterobacteriaceae family. This tool also provides different options to optimize the clustering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http://microbialgen.du.ac.bd/biocluster/. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

Cluster synchronization transmission of different external signals in discrete uncertain network

NASA Astrophysics Data System (ADS)

Li, Chengren; Lü, Ling; Chen, Liansong; Hong, Yixuan; Zhou, Shuang; Yang, Yiming

2018-07-01

We research cluster synchronization transmissions of different external signals in discrete uncertain network. Based on the Lyapunov theorem, the network controller and the identification law of uncertain adjustment parameter are designed, and they are efficiently used to achieve the cluster synchronization and the identification of uncertain adjustment parameter. In our technical scheme, the network nodes in each cluster and the transmitted external signal can be different, and they allow the presence of uncertain parameters in the network. Especially, we are free to choose the clustering topologies, the cluster number and the node number in each cluster.

Ultrasound-based clinical prediction rule model for detecting papillary thyroid cancer in cervical lymph nodes: A pilot study.

PubMed

Patel, Nayana U; McKinney, Kristin; Kreidler, Sarah M; Bieker, Teresa M; Russ, Paul; Roberts, Katherine; Glueck, Deborah H; Albuja-Cruz, Maria; Klopper, Joshua; Haugen, Bryan R

2016-01-01

To identify sonographic features of cervical lymph nodes (LNs) that are associated with papillary thyroid cancer (PTC) and to develop a prediction model for classifying nodes as metastatic or benign. This retrospective study included the records of postthyroidectomy patients with PTC who had undergone cervical ultrasound and LN biopsy. LN location, size, shape, hilum, echopattern, Doppler flow, and microcalcifications were assessed. Model selection was used to identify features associated with malignant LNs and to build a predictive, binary-outcome, generalized linear mixed model. A cross-validated receiver operating characteristic analysis was conducted to assess the accuracy of the model for classifying metastatic nodes. We analyzed records from 71 LNs (23 metastatic) in 44 patients (16 with PTC). The predictive model included a nonhomogeneous echopattern (odds ratio [OR], 5.73; 95% confidence interval [CI], 1.07-30.74; p = 0.04), microcalcifications (OR, 4.91; 95% CI, 0.91-26.54; p = 0.06), and volume (OR, 2.57; 95% CI, 0.66-9.99; p = 0.16) as predictors. The model had an area under the curve of 0.74 (95% CI, 0.60-0.85), sensitivity of 65% (95% CI, 50% to 78%), and specificity of 85% (95% CI, 73% to 94%) at the Youden optimal cut point of 0.38. Nonhomogeneous echopattern, microcalcifications, and node volume were predictive of malignant LNs in patients with PTC. A larger sample is needed to validate this model. © 2015 Wiley Periodicals, Inc.

50 μm pixel pitch wafer-scale CMOS active pixel sensor x-ray detector for digital breast tomosynthesis.

PubMed

Zhao, C; Konstantinidis, A C; Zheng, Y; Anaxagoras, T; Speller, R D; Kanicki, J

2015-12-07

Wafer-scale CMOS active pixel sensors (APSs) have been developed recently for x-ray imaging applications. The small pixel pitch and low noise are very promising properties for medical imaging applications such as digital breast tomosynthesis (DBT). In this work, we evaluated experimentally and through modeling the imaging properties of a 50 μm pixel pitch CMOS APS x-ray detector named DynAMITe (Dynamic Range Adjustable for Medical Imaging Technology). A modified cascaded system model was developed for CMOS APS x-ray detectors by taking into account the device nonlinear signal and noise properties. The imaging properties such as modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE) were extracted from both measurements and the nonlinear cascaded system analysis. The results show that the DynAMITe x-ray detector achieves a high spatial resolution of 10 mm(-1) and a DQE of around 0.5 at spatial frequencies  <1 mm(-1). In addition, the modeling results were used to calculate the image signal-to-noise ratio (SNRi) of microcalcifications at various mean glandular dose (MGD). For an average breast (5 cm thickness, 50% glandular fraction), 165 μm microcalcifications can be distinguished at a MGD of 27% lower than the clinical value (~1.3 mGy). To detect 100 μm microcalcifications, further optimizations of the CMOS APS x-ray detector, image aquisition geometry and image reconstruction techniques should be considered.

Detection of simulated microcalcifications in fixed mammary tissue: An ROC study of the effect of local versus global histogram equalization.

PubMed

Sund, T; Olsen, J B

2006-09-01

To investigate whether sliding window adaptive histogram equalization (SWAHE) of digital mammograms improves the detection of simulated calcifications, as compared to images normalized by global histogram equalization (GHE). Direct digital mammograms were obtained from mammary tissue phantoms superimposed with different frames. Each frame was divided into forty squares by a wire mesh, and contained granular calcifications randomly positioned in about 50% of the squares. Three radiologists read the mammograms on a display monitor. They classified their confidence in the presence of microcalcifications in each square on a scale of 1 to 5. Images processed with GHE were first read and used as a reference. In a later session, the same images processed with SWAHE were read. The results were compared using ROC methodology. When the total areas AZ were compared, the results were completely equivocal. When comparing the high-specificity partial ROC area AZ,0.2 below false-positive fraction (FPF) 0.20, two of the three observers performed best with the images processed with SWAHE. The difference was not statistically significant. When the reader's confidence threshold in malignancy is set at a high level, increasing the contrast of mammograms with SWAHE may enhance the visibility of microcalcifications without adversely affecting the false-positive rate. When the reader's confidence threshold is set at a low level, the effect of SWAHE is an increase of false positives. Further investigation is needed to confirm the validity of the conclusions.

Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis.

PubMed

Cohen, Mitchell J; Grossman, Adam D; Morabito, Diane; Knudson, M Margaret; Butte, Atul J; Manley, Geoffrey T

2010-01-01

Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome. Multivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality. We identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters. Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.

Rapid identification of Enterobacter hormaechei and Enterobacter cloacae genetic cluster III.

PubMed

Ohad, S; Block, C; Kravitz, V; Farber, A; Pilo, S; Breuer, R; Rorman, E

2014-05-01

Enterobacter cloacae complex bacteria are of both clinical and environmental importance. Phenotypic methods are unable to distinguish between some of the species in this complex, which often renders their identification incomplete. The goal of this study was to develop molecular assays to identify Enterobacter hormaechei and Ent. cloacae genetic cluster III which are relatively frequently encountered in clinical material. The molecular assays developed in this study are qPCR technology based and served to identify both Ent. hormaechei and Ent. cloacae genetic cluster III. qPCR results were compared to hsp60 sequence analysis. Most clinical isolates were assigned to Ent. hormaechei subsp. steigerwaltii and Ent. cloacae genetic cluster III. The latter was proportionately more frequently isolated from bloodstream infections than from other material (P < 0·05). The qPCR assays detecting Ent. hormaechei and Ent. cloacae genetic cluster III demonstrated high sensitivity and specificity. The presented qPCR assays allow accurate and rapid identification of clinical isolates of the Ent. cloacae complex. The improved identifications obtained can specifically assist analysis of Ent. hormaechei and Ent. cloacae genetic cluster III in nosocomial outbreaks and can promote rapid environmental monitoring. An association was observed between Ent. cloacae cluster III and systemic infection that deserves further attention. © 2014 The Society for Applied Microbiology.

X-ray phase contrast imaging of the breast: Analysis of tissue simulating materials

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

Vedantham, Srinivasan; Karellas, Andrew

Purpose: Phase contrast imaging, particularly of the breast, is being actively investigated. The purpose of this work is to investigate the x-ray phase contrast properties of breast tissues and commonly used breast tissue substitutes or phantom materials with an aim of determining the phantom materials best representative of breast tissues. Methods: Elemental compositions of breast tissues including adipose, fibroglandular, and skin were used to determine the refractive index, n= 1 -{delta}+i {beta}. The real part of the refractive index, specifically the refractive index decrement ({delta}), over the energy range of 5-50 keV were determined using XOP software (version 2.3, Europeanmore » Synchrotron Radiation Facility, France). Calcium oxalate and calcium hydroxyapatite were considered to represent the material compositions of microcalcifications in vivo. Nineteen tissue substitutes were considered as possible candidates to represent adipose tissue, fibroglandular tissue and skin, and four phantom materials were considered as possible candidates to represent microcalcifications. For each material, either the molecular formula, if available, or the elemental composition based on weight fraction, was used to determine {delta}. At each x-ray photon energy, the absolute percent difference in {delta} between the breast tissue and the substitute material was determined, from which three candidates were selected. From these candidate tissue substitutes, the material that minimized the absolute percent difference in linear attenuation coefficient {mu}, and hence {beta}, was considered to be best representative of that breast tissue. Results: Over the energy range of 5-50 keV, while the {delta} of CB3 and fibroglandular tissue-equivalent material were within 1% of that of fibroglandular tissue, the {mu} of fibroglandular tissue-equivalent material better approximated the fibroglandular tissue. While the {delta} of BR10 and adipose tissue-equivalent material were within 1% of that of adipose tissue, the tissue-equivalent material better approximated the adipose tissue in terms of {mu}. Polymethyl methacrylate, a commonly used tissue substitute, exhibited {delta} greater than fibroglandular tissue by {approx}12%. The A-150 plastic closely approximated the skin. Several materials exhibited {delta} between that of adipose and fibroglandular tissue. However, there was an energy-dependent mismatch in terms of equivalent fibroglandular weight fraction between {delta} and {mu} for these materials. For microcalcifications, aluminum and calcium carbonate were observed to straddle the {delta} and {mu} of calcium oxalate and calcium hydroxyapatite. Aluminum oxide, commonly used to represent microcalcifications in the American College of Radiology recommended phantoms for accreditation exhibited {delta} greater than calcium hydroxyapatite by {approx}23%. Conclusions: A breast phantom comprising A-150 plastic to represent the skin, commercially available adipose and fibroglandular tissue-equivalent formulations to represent adipose and fibroglandular tissue, respectively, was found to be best suited for x-ray phase-sensitive imaging of the breast. Calcium carbonate or aluminum can be used to represent microcalcifications.« less

Large area CMOS active pixel sensor x-ray imager for digital breast tomosynthesis: Analysis, modeling, and characterization

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

Zhao, Chumin; Kanicki, Jerzy, E-mail: kanicki@eecs.umich.edu; Konstantinidis, Anastasios C.

Purpose: Large area x-ray imagers based on complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology have been proposed for various medical imaging applications including digital breast tomosynthesis (DBT). The low electronic noise (50–300 e{sup −}) of CMOS APS x-ray imagers provides a possible route to shrink the pixel pitch to smaller than 75 μm for microcalcification detection and possible reduction of the DBT mean glandular dose (MGD). Methods: In this study, imaging performance of a large area (29 × 23 cm{sup 2}) CMOS APS x-ray imager [Dexela 2923 MAM (PerkinElmer, London)] with a pixel pitch of 75 μm was characterizedmore » and modeled. The authors developed a cascaded system model for CMOS APS x-ray imagers using both a broadband x-ray radiation and monochromatic synchrotron radiation. The experimental data including modulation transfer function, noise power spectrum, and detective quantum efficiency (DQE) were theoretically described using the proposed cascaded system model with satisfactory consistency to experimental results. Both high full well and low full well (LFW) modes of the Dexela 2923 MAM CMOS APS x-ray imager were characterized and modeled. The cascaded system analysis results were further used to extract the contrast-to-noise ratio (CNR) for microcalcifications with sizes of 165–400 μm at various MGDs. The impact of electronic noise on CNR was also evaluated. Results: The LFW mode shows better DQE at low air kerma (K{sub a} < 10 μGy) and should be used for DBT. At current DBT applications, air kerma (K{sub a} ∼ 10 μGy, broadband radiation of 28 kVp), DQE of more than 0.7 and ∼0.3 was achieved using the LFW mode at spatial frequency of 0.5 line pairs per millimeter (lp/mm) and Nyquist frequency ∼6.7 lp/mm, respectively. It is shown that microcalcifications of 165–400 μm in size can be resolved using a MGD range of 0.3–1 mGy, respectively. In comparison to a General Electric GEN2 prototype DBT system (at MGD of 2.5 mGy), an increased CNR (by ∼10) for microcalcifications was observed using the Dexela 2923 MAM CMOS APS x-ray imager at a lower MGD (2.0 mGy). Conclusions: The Dexela 2923 MAM CMOS APS x-ray imager is capable to achieve a high imaging performance at spatial frequencies up to 6.7 lp/mm. Microcalcifications of 165 μm are distinguishable based on reported data and their modeling results due to the small pixel pitch of 75 μm. At the same time, potential dose reduction is expected using the studied CMOS APS x-ray imager.« less

Investigation of statistical iterative reconstruction for dedicated breast CT

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

Makeev, Andrey; Glick, Stephen J.

2013-08-15

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

X-ray phase contrast imaging of the breast: Analysis of tissue simulating materials1

PubMed Central

Vedantham, Srinivasan; Karellas, Andrew

2013-01-01

Purpose: Phase contrast imaging, particularly of the breast, is being actively investigated. The purpose of this work is to investigate the x-ray phase contrast properties of breast tissues and commonly used breast tissue substitutes or phantom materials with an aim of determining the phantom materials best representative of breast tissues. Methods: Elemental compositions of breast tissues including adipose, fibroglandular, and skin were used to determine the refractive index, n = 1 − δ + i β. The real part of the refractive index, specifically the refractive index decrement (δ), over the energy range of 5–50 keV were determined using XOP software (version 2.3, European Synchrotron Radiation Facility, France). Calcium oxalate and calcium hydroxyapatite were considered to represent the material compositions of microcalcifications in vivo. Nineteen tissue substitutes were considered as possible candidates to represent adipose tissue, fibroglandular tissue and skin, and four phantom materials were considered as possible candidates to represent microcalcifications. For each material, either the molecular formula, if available, or the elemental composition based on weight fraction, was used to determine δ. At each x-ray photon energy, the absolute percent difference in δ between the breast tissue and the substitute material was determined, from which three candidates were selected. From these candidate tissue substitutes, the material that minimized the absolute percent difference in linear attenuation coefficient μ, and hence β, was considered to be best representative of that breast tissue. Results: Over the energy range of 5–50 keV, while the δ of CB3 and fibroglandular tissue-equivalent material were within 1% of that of fibroglandular tissue, the μ of fibroglandular tissue-equivalent material better approximated the fibroglandular tissue. While the δ of BR10 and adipose tissue-equivalent material were within 1% of that of adipose tissue, the tissue-equivalent material better approximated the adipose tissue in terms of μ. Polymethyl methacrylate, a commonly used tissue substitute, exhibited δ greater than fibroglandular tissue by ∼12%. The A-150 plastic closely approximated the skin. Several materials exhibited δ between that of adipose and fibroglandular tissue. However, there was an energy-dependent mismatch in terms of equivalent fibroglandular weight fraction between δ and μ for these materials. For microcalcifications, aluminum and calcium carbonate were observed to straddle the δ and μ of calcium oxalate and calcium hydroxyapatite. Aluminum oxide, commonly used to represent microcalcifications in the American College of Radiology recommended phantoms for accreditation exhibited δ greater than calcium hydroxyapatite by ∼23%. Conclusions: A breast phantom comprising A-150 plastic to represent the skin, commercially available adipose and fibroglandular tissue-equivalent formulations to represent adipose and fibroglandular tissue, respectively, was found to be best suited for x-ray phase-sensitive imaging of the breast. Calcium carbonate or aluminum can be used to represent microcalcifications. PMID:23556900

Histopathology findings of non-mass cancers on breast ultrasound.

PubMed

Kim, Hye Rin; Jung, Hae Kyoung

2018-06-01

There is little research done on non-mass cancers (NMCs) on breast ultrasound (US). To evaluate large-sectional histopathology findings of NMCs on breast US. The mammographic and histopathology features of biopsy proven 36 breast cancers which showed pure non-mass lesions on US were retrospectively reviewed. The most common mammographic finding was microcalcification (23/35, 65.7%); fine pleomorphic microcalcification was predominant (18/23, 78.3%). The main tumor type was pure ductal carcinoma in situ (DCIS) (14/36, 38.9%) and DCIS with micro- or minimal invasion (11/36, 30.6%). Among the 25 DCIS, histologic grade was high in 15 (60.0%) and intermediate in nine (36%); comedo necrosis was seen in 17 (68%). Immunohistochemical analysis was available in 27 lesions and showed HER2-overexpression in 12 (44.4%) and triple-negative in two (7.4%). According to our limited patient sample, NMCs on breast US were mainly associated with high-grade DCIS.

Detection method of visible and invisible nipples on digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Effects of antiperspirant aluminum percent composition and mode of application on mock microcalcifications in mammography.

PubMed

Mesurolle, Benoît; Ceccarelli, Joan; Karp, Igor; Sun, Simon; El-Khoury, Mona

2014-02-01

Active ingredients in antiperspirants - namely, aluminum-based complexes - can produce radiopaque particles on mammography, mimicking microcalcifications. The present study was designed to investigate whether the appearance of antiperspirant induced radiopaque particles observed on mammograms is dependent on the percentage of aluminum-based complexes in antiperspirants and/or on their mode of application. A total of 43 antiperspirants with aluminum-based complex percentages ranging between 16% and 25% were tested. Each antiperspirant was applied to a single use plastic shield and then placed on an ultrasound gel pad, simulating breast tissue. Two experiments were performed, comparing antiperspirants based on (1) their percentage of aluminum-based complexes (20 antiperspirants) and (2) their mode of applications (solid, gel, and roll-on) (26 antiperspirants). Two experienced, blinded radiologists read images produced in consensus and assessed the appearance of radiopaque particles based on their density and shape. In experiment 1, there was no statistically significant association between the percent aluminum composition of invisible solid antiperspirants and the density or shape of the radiopaque particles (p-values>0.05). In experiment 2, there was a statistically significant association between the shape of the radiopaque particles and the mode of application of the antiperspirant (p-value=0.0015). Our study suggests that the mammographic appearance of the radiopaque antiperspirant particles is not related to their percent composition of aluminum complexes. However, their mode of application appears to influence the shape of radiopaque particles, solid antiperspirants mimicking microcalcifications the most and roll-on antiperspirants the least. Copyright © 2013. Published by Elsevier Ireland Ltd.

Identification of hydrologically homogeneous regions in Ganga-Brahmaputra river basin using Self Organising Maps

NASA Astrophysics Data System (ADS)

Ojha, C. S. P.; Sharma, C.

2017-12-01

Identification of hydrologically homogeneous regions is crucial for topographically complex regions such as Himalayan river basins. Ganga-Brahmaputra river basin extends through three countries, i.e., India Nepal and China. High elevations and rugged topography impose challenge for in-situ gauges. So, it is always recommended to use data from hydrological similar site in absence of site records. We have tried to find out hydrologically homogeneous regions using Self-Organising-Map (SOM) in Ganga-Brahmaputra river basin. The station characteristics used for identification of homogeneous regions are annual precipitation, total wet season (July to September) precipitation, total dry season (January to March) precipitation, Latitude, Longitude and elevation. Precipitation data was obtained from Climate Research Unit (CRU). Number of cluster are find out using hierarchical k-means clustering. We found that the basin can be divided in 9 clusters. Mere division of regions in clusters does not clarify that identified cluster are homogeneous. The homogeneity of the clusters is found out using Hosking and Wallis heterogeneity test. All the clusters were found to be acceptably homogeneous with the value of Hosking-Wallis test static H<1.

ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data.

PubMed

Oluwadare, Oluwatosin; Cheng, Jianlin

2017-11-14

With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-C technique can generate genome-wide chromosomal interaction (contact) data, which can be used to investigate the higher-level organization of chromosomes, such as Topologically Associated Domains (TAD), i.e., locally packed chromosome regions bounded together by intra chromosomal contacts. The identification of the TADs for a genome is useful for studying gene regulation, genomic interaction, and genome function. Here, we formulate the TAD identification problem as an unsupervised machine learning (clustering) problem, and develop a new TAD identification method called ClusterTAD. We introduce a novel method to represent chromosomal contacts as features to be used by the clustering algorithm. Our results show that ClusterTAD can accurately predict the TADs on a simulated Hi-C data. Our method is also largely complementary and consistent with existing methods on the real Hi-C datasets of two mouse cells. The validation with the chromatin immunoprecipitation (ChIP) sequencing (ChIP-Seq) data shows that the domain boundaries identified by ClusterTAD have a high enrichment of CTCF binding sites, promoter-related marks, and enhancer-related histone modifications. As ClusterTAD is based on a proven clustering approach, it opens a new avenue to apply a large array of clustering methods developed in the machine learning field to the TAD identification problem. The source code, the results, and the TADs generated for the simulated and real Hi-C datasets are available here: https://github.com/BDM-Lab/ClusterTAD .

Examining the effectiveness of discriminant function analysis and cluster analysis in species identification of male field crickets based on their calling songs.

PubMed

Jaiswara, Ranjana; Nandi, Diptarup; Balakrishnan, Rohini

2013-01-01

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.

Multilingual Data Selection for Low Resource Speech Recognition

DTIC Science & Technology

2016-09-12

Figure 1: Identification of language clusters using scores from an LID system training languages used in the Base and OP1 evaluation periods of the Babel...the posterior scores over frames. For a set of languages that are used to train the lan- guage identification (LID) network, pairs of languages that...which are combined during test time to produce 10 dimensional language 3854 Figure 3: Identification of language clusters using scores from individually

The cost effectiveness of vacuum-assisted versus core-needle versus surgical biopsy of breast lesions.

PubMed

Fernández-García, P; Marco-Doménech, S F; Lizán-Tudela, L; Ibáñez-Gual, M V; Navarro-Ballester, A; Casanovas-Feliu, E

To determine the cost effectiveness of breast biopsy by 9G vacuum-assisted guided by vertical stereotaxy or ultrasonography in comparison with breast biopsy by 14G core-needle biopsy and surgical biopsy. We analyzed a total of 997 biopsies (181 vacuum-assisted, 626 core, and 190 surgical biopsies). We calculated the total costs (indirect and direct) of the three types of biopsy. We did not calculate intangible costs. We measured the percentage of correct diagnoses obtained with each technique. To identify the most cost-effective option, we calculated the mean ratios for the three types of biopsies. Total costs were €225.09 for core biopsy, €638.90 for vacuum-assisted biopsy, and €1780.01 for surgical biopsy. The overall percentage of correct diagnoses was 91.81% for core biopsy, 94.03% for vacuum-assisted biopsy, and 100% for surgical biopsy; however, these differences did not reach statistical significance (p=0.3485). For microcalcifications, the percentage of correct diagnoses was 50% for core biopsy and 96.77% for vacuum-assisted biopsy (p<0.0001). For nodules, there were no significant differences among techniques. The mean cost-effectiveness ratio considering all lesions was 2.45 for core biopsy, 6.79 for vacuum-assisted biopsy, and 17.80 for surgical biopsy. Core biopsy was the dominant option for the diagnosis of suspicious breast lesions in general. However, in cases with microcalcifications, the low percentage of correct diagnoses achieved by core biopsy (50%) advises against its use in this context, where vacuum-assisted biopsy would be the technique of choice because it is more cost-effective than surgical biopsy, the other technique indicated for biopsying microcalcifications. Copyright © 2016 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Introducing DeBRa: a detailed breast model for radiological studies

NASA Astrophysics Data System (ADS)

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

2009-07-01

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

Upgrade of ductal carcinoma in situ on core biopsies to invasive disease at final surgery: a retrospective review across the Scottish Breast Screening Programme.

PubMed

Sim, Y T; Litherland, J; Lindsay, E; Hendry, P; Brauer, K; Dobson, H; Cordiner, C; Gagliardi, T; Smart, L

2015-05-01

To identify factors affecting upgrade rates from B5a (non-invasive) preoperative core biopsies to invasive disease at surgery and ways to improve screening performance. This was a retrospective analysis of 1252 cases of B5a biopsies across all six Scottish Breast Screening Programmes (BSPs), ranging between 2004 and 2012. Final surgical histopathology was correlated with radiological and biopsy factors. Data were analysed using basic Microsoft Excel and standard Chi-squared test used for evaluating statistical significance. B5a upgrade rates for the units ranged from 19.2% to 29.2%, with an average of 23.6%. Mean sizes of invasive tumours were small (3-11 mm). The upgrade rate was significantly higher for cases where the main mammographic abnormality was mass, distortion, or asymmetry, compared with micro-calcification alone (33.2% versus 21.7%, p = 0.0004). The upgrade rate was significantly lower with the use of large-volume vacuum-assisted biopsy (VAB) devices than 14 G core needles (19.9% versus 26%, p = 0.013); in stereotactic than ultrasound-guided biopsies (21.2% versus 36.1%, p < 0.001). Heterogeneity of data from different centres limited evaluation of other potential factors. Upgrade rates are lower for cases with micro-calcification as the sole mammographic feature with the use of VAB devices. Nevertheless, there is variation in practice across Scottish BSPs, including first-line biopsy technique and/or device; and it is of interest that a few centres maintain low upgrade rates despite not using VAB routinely for biopsy of micro-calcification. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Randomized controlled trial of stereotactic 11-G vacuum-assisted core biopsy for the diagnosis and management of mammographic microcalcification

PubMed Central

Maxwell, Anthony J; Morris, Julie; Lim, Yit Y; Harake, MD Janick; Whiteside, Sigrid

2016-01-01

Objective: To compare the accuracy of 11-G vacuum-assisted biopsy (VAB) with 14-G core needle biopsy (CNB) to diagnose mammographic microcalcification (MM) and effect on surgical outcomes. Methods: Following ethical approval, VAB and CNB (control) were compared in a randomized prospective study for first-line diagnosis of MM and subsequent surgical outcomes in two breast-screening units. Participants gave written informed consent. Exclusions included comorbidity precluding surgery, prior ipsilateral breast cancer and lesions >40 mm requiring mastectomy as first surgical procedure. The final pathological diagnosis was compared with the initial biopsy result. Quality-of-life (QOL) questionnaires were administered at baseline, 2, 6 and 12 months. 110 participants were required to show a 25% improvement in diagnosis with VAB compared with CNB (90% power). Results: Eligibility was assessed for 787 cases; 129 females recalled from the National Health Service breast screening programme were randomized. Diagnostic accuracy of VAB was 86% and that of CNB was 84%. Using VAB, 2/14 (14.3%) cases upgraded from ductal carcinoma in situ to invasion at surgery and 3/19 (15.8%) using CNB. Following VAB 7/16 (44%) cases required repeat surgery vs 7/24 (29%) after CNB. Both groups recorded significant worsening of functional QOL measures and increased breast pain at follow-up. Conclusion: VAB and CNB were equally accurate at diagnosing MM, and no significant differences in surgical outcomes were observed. Advances in knowledge: The first randomized controlled study of VAB for diagnosis of microcalcification using digital mammography showed no difference in diagnostic accuracy of VAB and CNB, or in the proportion of participants needing repeat non-operative biopsy or second therapeutic operation to treat malignancy. PMID:26654214

Evaluation of low-energy contrast-enhanced spectral mammography images by comparing them to full-field digital mammography using EUREF image quality criteria.

PubMed

Lalji, U C; Jeukens, C R L P N; Houben, I; Nelemans, P J; van Engen, R E; van Wylick, E; Beets-Tan, R G H; Wildberger, J E; Paulis, L E; Lobbes, M B I

2015-10-01

Contrast-enhanced spectral mammography (CESM) examination results in a low-energy (LE) and contrast-enhanced image. The LE appears similar to a full-field digital mammogram (FFDM). Our aim was to evaluate LE CESM image quality by comparing it to FFDM using criteria defined by the European Reference Organization for Quality Assured Breast Screening and Diagnostic Services (EUREF). A total of 147 cases with both FFDM and LE images were independently scored by two experienced radiologists using these (20) EUREF criteria. Contrast detail measurements were performed using a dedicated phantom. Differences in image quality scores, average glandular dose, and contrast detail measurements between LE and FFDM were tested for statistical significance. No significant differences in image quality scores were observed between LE and FFDM images for 17 out of 20 criteria. LE scored significantly lower on one criterion regarding the sharpness of the pectoral muscle (p < 0.001), and significantly better on two criteria on the visualization of micro-calcifications (p = 0.02 and p = 0.034). Dose and contrast detail measurements did not reveal any physical explanation for these observed differences. Low-energy CESM images are non-inferior to FFDM images. From this perspective FFDM can be omitted in patients with an indication for CESM. • Low-energy CESM images are non-inferior to FFDM images. • Micro-calcifications are significantly more visible on LE CESM than on FFDM. • There is no physical explanation for this improved visibility of micro-calcifications. • There is no need for an extra FFDM when CESM is indicated.

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

Ghammraoui, B; M Popescu, L; Badano, A

Purpose: To investigate the ability of Coherent Scatter Computed Tomography (CSCT) to distinguish non-invasively between type I calcifications, consisting of calcium oxalate dihydrate (CO) compounds which are more often associated with benign lesions, and type II calcifications containing hydroxyapatite (HA) which are predominantly associated with malignant tumors. Methods: The coherent scatter cross sections of HA and CO were measured using an energy dispersive x-ray diffractometer. The measured cross sections were introduced into MC-GPU Monte Carlo simulation code for studying the applicability of CSCT to discriminate between the two types of microcalcifications within the whole breast. Simulations were performed on amore » virtual phantom with inserted HA and CO spots of different sizes and placed in regions of interest having different background compositions. We considered a polychromatic x-ray source and an energy resolving photon counting detector. We applied an algorithm that estimates scatter components in projection space in order to obtain material-specific images of the breast. As material components adipose, glandular, HA and CO were used. The relative contrast of HA and CO components were used for type I and type II microcalcification discrimination. Results: The reconstructed CSCT images showed material-specific component-contrast values, with the highest CO or HA component contrast corresponding generally to the actual CO or HA feature, respectively. The discrimination performance varies with the x-ray intensity, calcification size, and background composition. The results were summarized using receiver operating characteristic (ROC) analysis with the area under the curve (AUC) taken as an overall indicator of discrimination performance and showing high AUC values up to unity. Conclusion: The simulation results obtained for a uniform breast imaging phantom indicate that CSCT has potential to be used as a non-invasive method for discrimination between type I and type II microcalcifications.« less

The identification of credit card encoders by hierarchical cluster analysis of the jitters of magnetic stripes.

PubMed

Leung, S C; Fung, W K; Wong, K H

1999-01-01

The relative bit density variation graphs of 207 specimen credit cards processed by 12 encoding machines were examined first visually, and then classified by means of hierarchical cluster analysis. Twenty-nine credit cards being treated as 'questioned' samples were tested by way of cluster analysis against 'controls' derived from known encoders. It was found that hierarchical cluster analysis provided a high accuracy of identification with all 29 'questioned' samples classified correctly. On the other hand, although visual comparison of jitter graphs was less discriminating, it was nevertheless capable of giving a reasonably accurate result.

Identification of piecewise affine systems based on fuzzy PCA-guided robust clustering technique

NASA Astrophysics Data System (ADS)

Khanmirza, Esmaeel; Nazarahari, Milad; Mousavi, Alireza

2016-12-01

Hybrid systems are a class of dynamical systems whose behaviors are based on the interaction between discrete and continuous dynamical behaviors. Since a general method for the analysis of hybrid systems is not available, some researchers have focused on specific types of hybrid systems. Piecewise affine (PWA) systems are one of the subsets of hybrid systems. The identification of PWA systems includes the estimation of the parameters of affine subsystems and the coefficients of the hyperplanes defining the partition of the state-input domain. In this paper, we have proposed a PWA identification approach based on a modified clustering technique. By using a fuzzy PCA-guided robust k-means clustering algorithm along with neighborhood outlier detection, the two main drawbacks of the well-known clustering algorithms, i.e., the poor initialization and the presence of outliers, are eliminated. Furthermore, this modified clustering technique enables us to determine the number of subsystems without any prior knowledge about system. In addition, applying the structure of the state-input domain, that is, considering the time sequence of input-output pairs, provides a more efficient clustering algorithm, which is the other novelty of this work. Finally, the proposed algorithm has been evaluated by parameter identification of an IGV servo actuator. Simulation together with experiment analysis has proved the effectiveness of the proposed method.

Evaluation of position-estimation methods applied to CZT-based photon-counting detectors for dedicated breast CT

PubMed Central

Makeev, Andrey; Clajus, Martin; Snyder, Scott; Wang, Xiaolang; Glick, Stephen J.

2015-01-01

Abstract. Semiconductor photon-counting detectors based on high atomic number, high density materials [cadmium zinc telluride (CZT)/cadmium telluride (CdTe)] for x-ray computed tomography (CT) provide advantages over conventional energy-integrating detectors, including reduced electronic and Swank noise, wider dynamic range, capability of spectral CT, and improved signal-to-noise ratio. Certain CT applications require high spatial resolution. In breast CT, for example, visualization of microcalcifications and assessment of tumor microvasculature after contrast enhancement require resolution on the order of 100  μm. A straightforward approach to increasing spatial resolution of pixellated CZT-based radiation detectors by merely decreasing the pixel size leads to two problems: (1) fabricating circuitry with small pixels becomes costly and (2) inter-pixel charge spreading can obviate any improvement in spatial resolution. We have used computer simulations to investigate position estimation algorithms that utilize charge sharing to achieve subpixel position resolution. To study these algorithms, we model a simple detector geometry with a 5×5 array of 200  μm pixels, and use a conditional probability function to model charge transport in CZT. We used COMSOL finite element method software to map the distribution of charge pulses and the Monte Carlo package PENELOPE for simulating fluorescent radiation. Performance of two x-ray interaction position estimation algorithms was evaluated: the method of maximum-likelihood estimation and a fast, practical algorithm that can be implemented in a readout application-specific integrated circuit and allows for identification of a quadrant of the pixel in which the interaction occurred. Both methods demonstrate good subpixel resolution; however, their actual efficiency is limited by the presence of fluorescent K-escape photons. Current experimental breast CT systems typically use detectors with a pixel size of 194  μm, with 2×2 binning during the acquisition giving an effective pixel size of 388  μm. Thus, it would be expected that the position estimate accuracy reported in this study would improve detection and visualization of microcalcifications as compared to that with conventional detectors. PMID:26158095

Evaluation of position-estimation methods applied to CZT-based photon-counting detectors for dedicated breast CT.

PubMed

Makeev, Andrey; Clajus, Martin; Snyder, Scott; Wang, Xiaolang; Glick, Stephen J

2015-04-01

Semiconductor photon-counting detectors based on high atomic number, high density materials [cadmium zinc telluride (CZT)/cadmium telluride (CdTe)] for x-ray computed tomography (CT) provide advantages over conventional energy-integrating detectors, including reduced electronic and Swank noise, wider dynamic range, capability of spectral CT, and improved signal-to-noise ratio. Certain CT applications require high spatial resolution. In breast CT, for example, visualization of microcalcifications and assessment of tumor microvasculature after contrast enhancement require resolution on the order of [Formula: see text]. A straightforward approach to increasing spatial resolution of pixellated CZT-based radiation detectors by merely decreasing the pixel size leads to two problems: (1) fabricating circuitry with small pixels becomes costly and (2) inter-pixel charge spreading can obviate any improvement in spatial resolution. We have used computer simulations to investigate position estimation algorithms that utilize charge sharing to achieve subpixel position resolution. To study these algorithms, we model a simple detector geometry with a [Formula: see text] array of [Formula: see text] pixels, and use a conditional probability function to model charge transport in CZT. We used COMSOL finite element method software to map the distribution of charge pulses and the Monte Carlo package PENELOPE for simulating fluorescent radiation. Performance of two x-ray interaction position estimation algorithms was evaluated: the method of maximum-likelihood estimation and a fast, practical algorithm that can be implemented in a readout application-specific integrated circuit and allows for identification of a quadrant of the pixel in which the interaction occurred. Both methods demonstrate good subpixel resolution; however, their actual efficiency is limited by the presence of fluorescent [Formula: see text]-escape photons. Current experimental breast CT systems typically use detectors with a pixel size of [Formula: see text], with [Formula: see text] binning during the acquisition giving an effective pixel size of [Formula: see text]. Thus, it would be expected that the position estimate accuracy reported in this study would improve detection and visualization of microcalcifications as compared to that with conventional detectors.

Evaluation of computer-aided detection of lesions in mammograms obtained with a digital phase-contrast mammography system.

PubMed

Tanaka, Toyohiko; Nitta, Norihisa; Ohta, Shinichi; Kobayashi, Tsuyoshi; Kano, Akiko; Tsuchiya, Keiko; Murakami, Yoko; Kitahara, Sawako; Wakamiya, Makoto; Furukawa, Akira; Takahashi, Masashi; Murata, Kiyoshi

2009-12-01

A computer-aided detection (CAD) system was evaluated for its ability to detect microcalcifications and masses on images obtained with a digital phase-contrast mammography (PCM) system, a system characterised by the sharp images provided by phase contrast and by the high resolution of 25-μm-pixel mammograms. Fifty abnormal and 50 normal mammograms were collected from about 3,500 mammograms and printed on film for reading on a light box. Seven qualified radiologists participated in an observer study based on receiver operating characteristic (ROC) analysis. The average of the areas under ROC curve (AUC) values for the ROC analysis with and without CAD were 0.927 and 0.897 respectively (P = 0.015). The AUC values improved from 0.840 to 0.888 for microcalcifications (P = 0.034) and from 0.947 to 0.962 for masses (P = 0.025) respectively. The application of CAD to the PCM system is a promising approach for the detection of breast cancer in its early stages.

REAL-TIME INTRAVITAL IMAGING ESTABLISHES TUMOUR-ASSOCIATED MACROPHAGES AS THE EXTRASKELETAL TARGET OF BISPHOSPHONATE ACTION IN CANCER

PubMed Central

Junankar, Simon; Shay, Gemma; Jurczyluk, Julie; Ali, Naveid; Down, Jenny; Pocock, Nicholas; Parker, Andrew; Nguyen, Akira; Sun, Shuting; Kashemirov, Boris; McKenna, Charles E.; Croucher, Peter I.; Swarbrick, Alexander; Weilbaecher, Katherine; Phan, Tri Giang; Rogers, Michael J.

2014-01-01

Recent clinical trials have shown that bisphosphonate drugs improve breast cancer patient survival independent of their anti-resorptive effects on the skeleton. However, since bisphosphonates bind rapidly to bone mineral, the exact mechanisms of their anti-tumour action, particularly on cells outside of bone, remain unknown. Here we used real-time intravital two-photon microscopy to show extensive leakage of fluorescent bisphosphonate from the vasculature in 4T1 mouse mammary tumours, where it initially binds to areas of small, granular microcalcifications that are engulfed by tumour-associated macrophages (TAMs), but not tumour cells. Importantly, we also observed uptake of radiolabeled bisphosphonate in the primary breast tumour of a patient and showed the resected tumour to be infiltrated with TAMs and to contain similar granular microcalcifications. These data represent the first compelling in vivo evidence that bisphosphonates can target cells in tumours outside the skeleton and that their anti-tumour activity is likely to be mediated via TAMs. PMID:25312016

Characteristics of metastasis in the breast from extramammary malignancies.

PubMed

Lee, Se Kyung; Kim, Wan Wook; Kim, Sung Hoon; Hur, Sung Mo; Kim, Sangmin; Choi, Jae Hyuck; Cho, Eun Yoon; Han, Soo Yeon; Hahn, Boo-Kyung; Choe, Jun-Ho; Kim, Jung-Han; Kim, Jee Soo; Lee, Jeong Eon; Nam, Seok Jin; Yang, Jung-Hyun

2010-02-01

Breast metastasis from extramammary neoplasm is rare. We present the cases of metastasis to the breast after review of results in one institute and we want to show the difference of previous report. The surgical and pathology databases of Samsung Medical Center from November 1994 to March 2009 were investigated to identify all patients with a diagnosis of metastasis to the breast. Thirty-three patients with breast metastases from extramammary neoplasm were studied. Gastric carcinoma was most common metastatic origin in this study. There were four cases with microcalcifications in their metastatic lesions. This is the first report of microcalcification of metastatic lesions to the breast from hepatocellular carcinoma and gastric cancer. Pathologic examination and considering known clinical history may be helpful to differentiate the primary breast cancer and metastatic cancer. Metastasis to the breast from an extramammary neoplasm usually indicates disseminated metastatic disease and a poor prognosis. An accurate diagnosis of breast metastases, differentiating primary from metastatic breast carcinoma, is important for proper management.

Source Identification of PM2.5 in Steubenville, Ohio Using a Hybrid Method for Highly Time-resolved Data

EPA Science Inventory

A new source-type identification method, Reduction and Species Clustering Using Episodes (ReSCUE), was developed to exploit the temporal synchronicity between species to form clusters of species that vary together. High time-resolution (30 min) PM_2.5 sampling was condu...

SeMPI: a genome-based secondary metabolite prediction and identification web server.

PubMed

Zierep, Paul F; Padilla, Natàlia; Yonchev, Dimitar G; Telukunta, Kiran K; Klementz, Dennis; Günther, Stefan

2017-07-03

The secondary metabolism of bacteria, fungi and plants yields a vast number of bioactive substances. The constantly increasing amount of published genomic data provides the opportunity for an efficient identification of gene clusters by genome mining. Conversely, for many natural products with resolved structures, the encoding gene clusters have not been identified yet. Even though genome mining tools have become significantly more efficient in the identification of biosynthetic gene clusters, structural elucidation of the actual secondary metabolite is still challenging, especially due to as yet unpredictable post-modifications. Here, we introduce SeMPI, a web server providing a prediction and identification pipeline for natural products synthesized by polyketide synthases of type I modular. In order to limit the possible structures of PKS products and to include putative tailoring reactions, a structural comparison with annotated natural products was introduced. Furthermore, a benchmark was designed based on 40 gene clusters with annotated PKS products. The web server of the pipeline (SeMPI) is freely available at: http://www.pharmaceutical-bioinformatics.de/sempi. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Iterative local Gaussian clustering for expressed genes identification linked to malignancy of human colorectal carcinoma

PubMed Central

Wasito, Ito; Hashim, Siti Zaiton M; Sukmaningrum, Sri

2007-01-01

Gene expression profiling plays an important role in the identification of biological and clinical properties of human solid tumors such as colorectal carcinoma. Profiling is required to reveal underlying molecular features for diagnostic and therapeutic purposes. A non-parametric density-estimation-based approach called iterative local Gaussian clustering (ILGC), was used to identify clusters of expressed genes. We used experimental data from a previous study by Muro and others consisting of 1,536 genes in 100 colorectal cancer and 11 normal tissues. In this dataset, the ILGC finds three clusters, two large and one small gene clusters, similar to their results which used Gaussian mixture clustering. The correlation of each cluster of genes and clinical properties of malignancy of human colorectal cancer was analysed for the existence of tumor or normal, the existence of distant metastasis and the existence of lymph node metastasis. PMID:18305825

Iterative local Gaussian clustering for expressed genes identification linked to malignancy of human colorectal carcinoma.

PubMed

Wasito, Ito; Hashim, Siti Zaiton M; Sukmaningrum, Sri

2007-12-30

Gene expression profiling plays an important role in the identification of biological and clinical properties of human solid tumors such as colorectal carcinoma. Profiling is required to reveal underlying molecular features for diagnostic and therapeutic purposes. A non-parametric density-estimation-based approach called iterative local Gaussian clustering (ILGC), was used to identify clusters of expressed genes. We used experimental data from a previous study by Muro and others consisting of 1,536 genes in 100 colorectal cancer and 11 normal tissues. In this dataset, the ILGC finds three clusters, two large and one small gene clusters, similar to their results which used Gaussian mixture clustering. The correlation of each cluster of genes and clinical properties of malignancy of human colorectal cancer was analysed for the existence of tumor or normal, the existence of distant metastasis and the existence of lymph node metastasis.

Topic Identification and Categorization of Public Information in Community-Based Social Media

NASA Astrophysics Data System (ADS)

Kusumawardani, RP; Basri, MH

2017-01-01

This paper presents a work on a semi-supervised method for topic identification and classification of short texts in the social media, and its application on tweets containing dialogues in a large community of dwellers in a city, written mostly in Indonesian. These dialogues comprise a wealth of information about the city, shared in real-time. We found that despite the high irregularity of the language used, and the scarcity of suitable linguistic resources, a meaningful identification of topics could be performed by clustering the tweets using the K-Means algorithm. The resulting clusters are found to be robust enough to be the basis of a classification. On three grouping schemes derived from the clusters, we get accuracy of 95.52%, 95.51%, and 96.7 using linear SVMs, reflecting the applicability of applying this method for generating topic identification and classification on such data.

Experimentally determined spectral optimization for dedicated breast computed tomography.

PubMed

Prionas, Nicolas D; Huang, Shih-Ying; Boone, John M

2011-02-01

The current study aimed to experimentally identify the optimal technique factors (x-ray tube potential and added filtration material/thickness) to maximize soft-tissue contrast, microcalcification contrast, and iodine contrast enhancement using cadaveric breast specimens imaged with dedicated breast computed tomography (bCT). Secondarily, the study aimed to evaluate the accuracy of phantom materials as tissue surrogates and to characterize the change in accuracy with varying bCT technique factors. A cadaveric breast specimen was acquired under appropriate approval and scanned using a prototype bCT scanner. Inserted into the specimen were cylindrical inserts of polyethylene, water, iodine contrast medium (iodixanol, 2.5 mg/ml), and calcium hydroxyapatite (100 mg/ml). Six x-ray tube potentials (50, 60, 70, 80, 90, and 100 kVp) and three different filters (0.2 mm Cu, 1.5 mm Al, and 0.2 mm Sn) were tested. For each set of technique factors, the intensity (linear attenuation coefficient) and noise were measured within six regions of interest (ROIs): Glandular tissue, adipose tissue, polyethylene, water, iodine contrast medium, and calcium hydroxyapatite. Dose-normalized contrast to noise ratio (CNRD) was measured for pairwise comparisons among the six ROIs. Regression models were used to estimate the effect of tube potential and added filtration on intensity, noise, and CNRD. Iodine contrast enhancement was maximized using 60 kVp and 0.2 mm Cu. Microcalcification contrast and soft-tissue contrast were maximized at 60 kVp. The 0.2 mm Cu filter achieved significantly higher CNRD for iodine contrast enhancement than the other two filters (p = 0.01), but microcalcification contrast and soft-tissue contrast were similar using the copper and aluminum filters. The average percent difference in linear attenuation coefficient, across all tube potentials, for polyethylene versus adipose tissue was 1.8%, 1.7%, and 1.3% for 0.2 mm Cu, 1.5 mm Al, and 0.2 mm Sn, respectively. For water versus glandular tissue, the average percent difference was 2.7%, 3.9%, and 4.2% for the three filter types. Contrast-enhanced bCT, using injected iodine contrast medium, may be optimized for maximum contrast of enhancing lesions at 60 kVp with 0.2 mm Cu filtration. Soft-tissue contrast and microcalcification contrast may also benefit from lower tube potentials (60 kVp). The linear attenuation coefficients of water and polyethylene slightly overestimate the values of their corresponding tissues, but the reported differences may serve as guidance for dosimetry and quality assurance using tissue equivalent phantoms.

Applications of graph theory in protein structure identification

PubMed Central

2011-01-01

There is a growing interest in the identification of proteins on the proteome wide scale. Among different kinds of protein structure identification methods, graph-theoretic methods are very sharp ones. Due to their lower costs, higher effectiveness and many other advantages, they have drawn more and more researchers’ attention nowadays. Specifically, graph-theoretic methods have been widely used in homology identification, side-chain cluster identification, peptide sequencing and so on. This paper reviews several methods in solving protein structure identification problems using graph theory. We mainly introduce classical methods and mathematical models including homology modeling based on clique finding, identification of side-chain clusters in protein structures upon graph spectrum, and de novo peptide sequencing via tandem mass spectrometry using the spectrum graph model. In addition, concluding remarks and future priorities of each method are given. PMID:22165974

Examining the Effectiveness of Discriminant Function Analysis and Cluster Analysis in Species Identification of Male Field Crickets Based on Their Calling Songs

PubMed Central

Jaiswara, Ranjana; Nandi, Diptarup; Balakrishnan, Rohini

2013-01-01

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6–7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification. PMID:24086666

Identification of an unusual type II thioesterase in the dithiolopyrrolone antibiotics biosynthetic pathway

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

Zhai, Ying; Bai, Silei; Liu, Jingjing

Dithiolopyrrolone group antibiotics characterized by an electronically unique dithiolopyrrolone heterobicyclic core are known for their antibacterial, antifungal, insecticidal and antitumor activities. Recently the biosynthetic gene clusters for two dithiolopyrrolone compounds, holomycin and thiomarinol, have been identified respectively in different bacterial species. Here, we report a novel dithiolopyrrolone biosynthetic gene cluster (aut) isolated from Streptomyces thioluteus DSM 40027 which produces two pyrrothine derivatives, aureothricin and thiolutin. By comparison with other characterized dithiolopyrrolone clusters, eight genes in the aut cluster were verified to be responsible for the assembly of dithiolopyrrolone core. The aut cluster was further confirmed by heterologous expression and in-framemore » gene deletion experiments. Intriguingly, we found that the heterogenetic thioesterase HlmK derived from the holomycin (hlm) gene cluster in Streptomyces clavuligerus significantly improved heterologous biosynthesis of dithiolopyrrolones in Streptomyces albus through coexpression with the aut cluster. In the previous studies, HlmK was considered invalid because it has a Ser to Gly point mutation within the canonical Ser-His-Asp catalytic triad of thioesterases. However, gene inactivation and complementation experiments in our study unequivocally demonstrated that HlmK is an active distinctive type II thioesterase that plays a beneficial role in dithiolopyrrolone biosynthesis. - Highlights: • Cloning of the aureothricin biosynthetic gene cluster from Streptomyces thioluteus DSM 40027. • Identification of the aureothricin gene cluster by heterologous expression and in-frame gene deletion. • The heterogenetic thioesterase HlmK significantly improved dithiolopyrrolones production of the aureothricin gene cluster. • Identification of HlmK as an unusual type II thioesterase.« less

Identification and characterization of earthquake clusters: a comparative analysis for selected sequences in Italy

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2017-04-01

Identification and statistical characterization of seismic clusters may provide useful insights about the features of seismic energy release and their relation to physical properties of the crust within a given region. Moreover, a number of studies based on spatio-temporal analysis of main-shocks occurrence require preliminary declustering of the earthquake catalogs. Since various methods, relying on different physical/statistical assumptions, may lead to diverse classifications of earthquakes into main events and related events, we aim to investigate the classification differences among different declustering techniques. Accordingly, a formal selection and comparative analysis of earthquake clusters is carried out for the most relevant earthquakes in North-Eastern Italy, as reported in the local OGS-CRS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. The comparison is then extended to selected earthquake sequences associated with a different seismotectonic setting, namely to events that occurred in the region struck by the recent Central Italy destructive earthquakes, making use of INGV data. Various techniques, ranging from classical space-time windows methods to ad hoc manual identification of aftershocks, are applied for detection of earthquake clusters. In particular, a statistical method based on nearest-neighbor distances of events in space-time-energy domain, is considered. Results from clusters identification by the nearest-neighbor method turn out quite robust with respect to the time span of the input catalogue, as well as to minimum magnitude cutoff. The identified clusters for the largest events reported in North-Eastern Italy since 1977 are well consistent with those reported in earlier studies, which were aimed at detailed manual aftershocks identification. The study shows that the data-driven approach, based on the nearest-neighbor distances, can be satisfactorily applied to decompose the seismic catalog into background seismicity and individual sequences of earthquake clusters, also in areas characterized by moderate seismic activity, where the standard declustering techniques may turn out rather gross approximations. With these results acquired, the main statistical features of seismic clusters are explored, including complex interdependence of related events, with the aim to characterize the space-time patterns of earthquakes occurrence in North-Eastern Italy and capture their basic differences with Central Italy sequences.

Automated selection of BI-RADS lesion descriptors for reporting calcifications in mammograms

NASA Astrophysics Data System (ADS)

Paquerault, Sophie; Jiang, Yulei; Nishikawa, Robert M.; Schmidt, Robert A.; D'Orsi, Carl J.; Vyborny, Carl J.; Newstead, Gillian M.

2003-05-01

We are developing an automated computer technique to describe calcifications in mammograms according to the BI-RADS lexicon. We evaluated this technique by its agreement with radiologists' description of the same lesions. Three expert mammographers reviewed our database of 90 cases of digitized mammograms containing clustered microcalcifications and described the calcifications according to BI-RADS. In our study, the radiologists used only 4 of the 5 calcification distribution descriptors and 5 of the 14 calcification morphology descriptors contained in BI-RADS. Our computer technique was therefore designed specifically for these 4 calcification distribution descriptors and 5 calcification morphology descriptors. For calcification distribution, 4 linear discriminant analysis (LDA) classifiers were developed using 5 computer-extracted features to produce scores of how well each descriptor describes a cluster. Similarly, for calcification morphology, 5 LDAs were designed using 10 computer-extracted features. We trained the LDAs using only the BI-RADS data reported by the first radiologist and compared the computer output to the descriptor data reported by all 3 radiologists (for the first radiologist, the leave-one-out method was used). The computer output consisted of the best calcification distribution descriptor and the best 2 calcification morphology descriptors. The results of the comparison with the data from each radiologist, respectively, were: for calcification distribution, percent agreement, 74%, 66%, and 73%, kappa value, 0.44, 0.36, and 0.46; for calcification morphology, percent agreement, 83%, 77%, and 57%, kappa value, 0.78, 0.70, and 0.44. These results indicate that the proposed computer technique can select BI-RADS descriptors in good agreement with radiologists.

Identification and Functional Analysis of the Nocardithiocin Gene Cluster in Nocardia pseudobrasiliensis

PubMed Central

Sakai, Kanae; Komaki, Hisayuki; Gonoi, Tohru

2015-01-01

Nocardithiocin is a thiopeptide compound isolated from the opportunistic pathogen Nocardia pseudobrasiliensis. It shows a strong activity against acid-fast bacteria and is also active against rifampicin-resistant Mycobacterium tuberculosis. Here, we report the identification of the nocardithiocin gene cluster in N. pseudobrasiliensis IFM 0761 based on conserved thiopeptide biosynthesis gene sequence and the whole genome sequence. The predicted gene cluster was confirmed by gene disruption and complementation. As expected, strains containing the disrupted gene did not produce nocardithiocin while gene complementation restored nocardithiocin production in these strains. The predicted cluster was further analyzed using RNA-seq which showed that the nocardithiocin gene cluster contains 12 genes within a 15.2-kb region. This finding will promote the improvement of nocardithiocin productivity and its derivatives production. PMID:26588225

Functional clustering of time series gene expression data by Granger causality

PubMed Central

2012-01-01

Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

MASGOMAS PROJECT, New automatic-tool for cluster search on IR photometric surveys

NASA Astrophysics Data System (ADS)

Rübke, K.; Herrero, A.; Borissova, J.; Ramirez-Alegria, S.; García, M.; Marin-Franch, A.

2015-05-01

The Milky Way is expected to contain a large number of young massive (few x 1000 solar masses) stellar clusters, borne in dense cores of gas and dust. Yet, their known number remains small. We have started a programme to search for such clusters, MASGOMAS (MAssive Stars in Galactic Obscured MAssive clusterS). Initially, we selected promising candidates by means of visual inspection of infrared images. In a second phase of the project we have presented a semi-automatic method to search for obscured massive clusters that resulted in the identification of new massive clusters, like MASGOMAS-1 (with more than 10,000 solar masses) and MASGOMAS-4 (a double-cored association of about 3,000 solar masses). We have now developped a new automatic tool for MASGOMAS that allows the identification of a large number of massive cluster candidates from the 2MASS and VVV catalogues. Cluster candidates fulfilling criteria appropriated for massive OB stars are thus selected in an efficient and objective way. We present the results from this tool and the observations of the first selected cluster, and discuss the implications for the Milky Way structure.

Cellular calcium dynamics in lactation and breast cancer: From physiology to pathology

USDA-ARS?s Scientific Manuscript database

Breast cancer is the second leading cause of cancer mortality in women, estimated at nearly 40,000 deaths and more than 230,000 new cases diagnosed in the U.S. this year alone. One of the defining characteristics of breast cancer is the radiographic presence of microcalcifications. These palpable mi...

Correlative imaging reveals physiochemical heterogeneity of microcalcifications in human breast carcinomas.

PubMed

Kunitake, Jennie A M R; Choi, Siyoung; Nguyen, Kayla X; Lee, Meredith M; He, Frank; Sudilovsky, Daniel; Morris, Patrick G; Jochelson, Maxine S; Hudis, Clifford A; Muller, David A; Fratzl, Peter; Fischbach, Claudia; Masic, Admir; Estroff, Lara A

2018-04-01

Microcalcifications (MCs) are routinely used to detect breast cancer in mammography. Little is known, however, about their materials properties and associated organic matrix, or their correlation to breast cancer prognosis. We combine histopathology, Raman microscopy, and electron microscopy to image MCs within snap-frozen human breast tissue and generate micron-scale resolution correlative maps of crystalline phase, trace metals, particle morphology, and organic matrix chemical signatures within high grade ductal carcinoma in situ (DCIS) and invasive cancer. We reveal the heterogeneity of mineral-matrix pairings, including punctate apatitic particles (<2 µm) with associated trace elements (e.g., F, Na, and unexpectedly Al) distributed within the necrotic cores of DCIS, and both apatite and spheroidal whitlockite particles in invasive cancer within a matrix containing spectroscopic signatures of collagen, non-collagen proteins, cholesterol, carotenoids, and DNA. Among the three DCIS samples, we identify key similarities in MC morphology and distribution, supporting a dystrophic mineralization pathway. This multimodal methodology lays the groundwork for establishing MC heterogeneity in the context of breast cancer biology, and could dramatically improve current prognostic models. Copyright © 2017 Elsevier Inc. All rights reserved.

Initial Image Quality and Clinical Experience with New CR Digital Mammography System: A Phantom and Clinical Study

NASA Astrophysics Data System (ADS)

Gaona, Enrique; Alfonso, Beatriz Y. Álvarez; Castellanos, Gustavo Casian; Enríquez, Jesús Gabriel Franco

2008-08-01

The goal of the study was to evaluate the first CR digital mammography system (® Konica-Minolta) in Mexico in clinical routine for cancer detection in a screening population and to determine if high resolution CR digital imaging is equivalent to state-of-the-art screen-film imaging. The mammograms were evaluated by two observers with cytological or histological confirmation for BIRADS 3, 4 and 5. Contrast, exposure and artifacts of the images were evaluated. Different details like skin, retromamillary space and parenchymal structures were judged. The detectability of microcalcifications and lesions were compared and correlated to histology. The difference in sensitivity of CR Mammography (CRM) and Screen Film Mammography (SFM) was not statistically significant. However, CRM had a significantly lower recall rate, and the lesion detection was equal or superior to conventional images. There is no significant difference in the number of microcalcifications and highly suspicious calcifications were equally detected on both film-screen and digital images. Different anatomical regions were better detectable in digital than in conventional mammography.

Analysis of framelets for breast cancer diagnosis.

PubMed

Thivya, K S; Sakthivel, P; Venkata Sai, P M

2016-01-01

Breast cancer is the second threatening tumor among the women. The effective way of reducing breast cancer is its early detection which helps to improve the diagnosing process. Digital mammography plays a significant role in mammogram screening at earlier stage of breast carcinoma. Even though, it is very difficult to find accurate abnormality in prevalent screening by radiologists. But the possibility of precise breast cancer screening is encouraged by predicting the accurate type of abnormality through Computer Aided Diagnosis (CAD) systems. The two most important indicators of breast malignancy are microcalcifications and masses. In this study, framelet transform, a multiresolutional analysis is investigated for the classification of the above mentioned two indicators. The statistical and co-occurrence features are extracted from the framelet decomposed mammograms with different resolution levels and support vector machine is employed for classification with k-fold cross validation. This system achieves 94.82% and 100% accuracy in normal/abnormal classification (stage I) and benign/malignant classification (stage II) of mass classification system and 98.57% and 100% for microcalcification system when using the MIAS database.

Extragonadal germ cell tumour with the "burned out" phenomenon mimicking a retroperitioneal tumour of neurogenic origin.

PubMed

González, Rocío; Montoto Santomé, Paula; Iglesias Porto, Eva; Pérez Moreiras, M Isabel; Salem Ali, Mohammed; Mateo Cambón, Luis A; Bal Nieves, Fernando; Arija Val, J Felix

2012-12-01

To describe a case of retroperitoneal metastasis of a gonadal germ cell tumour with the "burned-out" phenomenon in a 35 year old patient with a suspected diagnosis of retroperitoneal tumour of neurogenic origin. With the clinical and radiological suspicion of retroperitoneal tumour of neurogenic origin the tumour was removed, via the retroperitoneal space. Pathology showed classic seminoma with foci of atypical or anaplastic seminoma, confined to the tissue sample. After a genital examination showing no alterations, a scrotal ultrasound was requested. This revealed a badly delimited hypoechogenic mass with microcalcifications in the left testis and a heterogeneous echostructure in the right testis, with hypoechogenic areas and some microcalcification. Bilateral orchiectomy was performed, with a pathological study compatible with residual scar tissue in the left testicle and focal findings of germ cell neoplasia, with no intratubular seminoma in the right testis. The suspicion of an extragonadal germ cell tumour with the "burned-out" phenomenon modifies the therapeutic attitude, which should begin with orchiectomy, followed by systemic chemotherapy and the surgery kept in reserve for those cases where residual malignant tissue persists.

Initial Image Quality and Clinical Experience with New CR Digital Mammography System: A Phantom and Clinical Study

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

Gaona, Enrique; Enriquez, Jesus Gabriel Franco; Alfonso, Beatriz Y. Alvarez

2008-08-11

The goal of the study was to evaluate the first CR digital mammography system ( registered Konica-Minolta) in Mexico in clinical routine for cancer detection in a screening population and to determine if high resolution CR digital imaging is equivalent to state-of-the-art screen-film imaging. The mammograms were evaluated by two observers with cytological or histological confirmation for BIRADS 3, 4 and 5. Contrast, exposure and artifacts of the images were evaluated. Different details like skin, retromamillary space and parenchymal structures were judged. The detectability of microcalcifications and lesions were compared and correlated to histology. The difference in sensitivity of CRmore » Mammography (CRM) and Screen Film Mammography (SFM) was not statistically significant. However, CRM had a significantly lower recall rate, and the lesion detection was equal or superior to conventional images. There is no significant difference in the number of microcalcifications and highly suspicious calcifications were equally detected on both film-screen and digital images. Different anatomical regions were better detectable in digital than in conventional mammography.« less

The cluster charge identification in the GEM detector for fusion plasma imaging by soft X-ray diagnostics

NASA Astrophysics Data System (ADS)

Czarski, T.; Chernyshova, M.; Malinowski, K.; Pozniak, K. T.; Kasprowicz, G.; Kolasinski, P.; Krawczyk, R.; Wojenski, A.; Zabolotny, W.

2016-11-01

The measurement system based on gas electron multiplier detector is developed for soft X-ray diagnostics of tokamak plasmas. The multi-channel setup is designed for estimation of the energy and the position distribution of an X-ray source. The focal measuring issue is the charge cluster identification by its value and position estimation. The fast and accurate mode of the serial data acquisition is applied for the dynamic plasma diagnostics. The charge clusters are counted in the space determined by 2D position, charge value, and time intervals. Radiation source characteristics are presented by histograms for a selected range of position, time intervals, and cluster charge values corresponding to the energy spectra.

The cluster charge identification in the GEM detector for fusion plasma imaging by soft X-ray diagnostics.

PubMed

Czarski, T; Chernyshova, M; Malinowski, K; Pozniak, K T; Kasprowicz, G; Kolasinski, P; Krawczyk, R; Wojenski, A; Zabolotny, W

2016-11-01

The measurement system based on gas electron multiplier detector is developed for soft X-ray diagnostics of tokamak plasmas. The multi-channel setup is designed for estimation of the energy and the position distribution of an X-ray source. The focal measuring issue is the charge cluster identification by its value and position estimation. The fast and accurate mode of the serial data acquisition is applied for the dynamic plasma diagnostics. The charge clusters are counted in the space determined by 2D position, charge value, and time intervals. Radiation source characteristics are presented by histograms for a selected range of position, time intervals, and cluster charge values corresponding to the energy spectra.

Does isolated flat epithelial atypia on vacuum-assisted breast core biopsy require surgical excision?

PubMed

Dialani, Vandana; Venkataraman, Shambhavi; Frieling, Gretchen; Schnitt, Stuart J; Mehta, Tejas S

2014-01-01

To determine whether flat epithelial atypia (FEA) found in isolation on large core vacuum-assisted biopsy (CNB) requires surgical excision. After Institutional Review Board approval, pathology reports of all patients who underwent CNB from January 1, 2005 to December 31, 2010 were reviewed. All patients with reports of isolated FEA without other atypia or in situ or invasive carcinoma were identified. Patient age, history, target on imaging, biopsy modality, and residual target post CNB noted. Histology of CNB's (blinded to surgical outcome) and subsequent surgical excisions were reviewed by a dedicated breast pathologist. Only cases with confirmed isolated FEA on review were used for data analysis. Of 2,556 CNB's performed over 6 years, 37 (1.4%) had isolated FEA confirmed on review, comprising our study population. Thirty (81%) had biopsy for calcifications on mammography and 7 (19%) for mass or non-mass like enhancement on magnetic resonance imaging. There were no US guided CNBs that met our inclusion criteria. 29 (78.4%) underwent surgical excision, 6 (16.2%) had imaging follow-up, and 2 (5.4%) were lost to follow-up. Of the 29 with surgery, 2 (6.9%) had "upgrade" to low-grade in situ carcinoma (1 ductal and 1 pleomorphic lobular), 5 (17.2%) had "change in diagnosis" to other atypia (ADH/ALH), 15 (51.7%) had additional FEA and 7 (24.2%) had benign tissue without atypia. Both "upgraded" cases had residual microcalcifications on imaging following CNB. There were no upgrades to invasive cancers. In our study, none of 29 with isolated FEA on CNB had invasive cancer on surgical excision. If there are residual microcalcifications or residual lesion after a CNB that shows isolated FEA, excision is warranted, due to the possibility of other atypia (ADH/ALH [17.2%] or DCIS [5.4%]). If there are no residual microcalcifications following CNB, imaging follow-up as an alternative to surgery may be a reasonable option. © 2014 Wiley Periodicals, Inc.

[Study on the relationship between ultrasonographic features of papillary thyroid carcinoma and central cervical lymph node metastasis].

PubMed

Wang, X Q; Wei, W; Wei, X; Xu, Y; Wang, H L; Xing, X J; Zhang, S

2018-03-23

Objective: To investigate the correlation between ultrasonographic features of papillary thyroid carcinoma and central cervical lymph node metastasis. Methods: We retrospectively analyzed 486 patients with papillary thyroid carcinoma(PTC), pathologically confirmed after surgery in Tianjin Medical University Cancer Institute & Hospital. All patients were divided into central cervical lymph node metastasis group and non-metastasis group. No lateral cervical lymph node metastasis was found in preoperative ultrasonography and postoperative pathology. The characteristics of the ultrasound was observed and analyzed. Results: 297 out of 486 patients with papillary thyroid carcinomahad central metastasis, and the other 189 cases did not. Take pathology results as a standard, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy rate of preoperative ultrasound diagnosis in PTC patients with central cervical lymph node metastasis were 35.3%, 88.6%, 83.2%, 47.4%, 56.6%, respectively. Univariate analysis showed that multi-focus, taller-than-wide, diameter>1 cm, located in the lower pole, ill-defined margin, hypoechogenicity, micro-calcification, capsule invasion more than 1/4 perimeter of papillary thyroid carcinoma were significantly associated with central cervical lymph node metastasis (all P <0.05). Multivariate analysis showed that diameter>1 cm, micro-calcification, capsule invasion more than 1/4 perimeter of papillary thyroid carcinoma became independent risk factors of central cervical neck lymph node metastasis (all P <0.05). Conclusions: Preoperative description of ultrasonographical features has important value to assess central cervical lymph node metastasis in patients with papillary thyroid carcinoma. More information could be provided for clinical treatment. When the papillary thyroid carcinoma presented as diameter>1 cm, micro-calcification, and capsule invasion more than 1/4 perimeter of, there will be a greater risk of central cervical lymph node metastasis, and we shall suggest prophylactic central lymph cervical node dissection.

Degree of Enhancement on Contrast Enhanced Spectral Mammography (CESM) and Lesion Type on Mammography (MG): Comparison Based on Histological Results

PubMed Central

Łuczyńska, Elżbieta; Niemiec, Joanna; Hendrick, Edward; Heinze, Sylwia; Jaszczyński, Janusz; Jakubowicz, Jerzy; Sas-Korczyńska, Beata; Rys, Janusz

2016-01-01

Background Contrast enhanced spectral mammography (CESM) is a new method of breast cancer diagnosis in which an iodinated contrast agent is injected and dual-energy mammography is obtained in multiple views of the breasts. The aim of this study was to compare the degree of enhancement on CESM with lesion characteristics on mammography (MG) and lesion histology in women with suspicious breast lesions. Material/Methods The degree of enhancement on CESM (absent, weak, medium, or strong) was compared to lesion characteristics on MG (mass, mass with microcalcifications, or microcalcifications alone) and histology (infiltrating carcinoma, intraductal carcinoma, or benign) to compare sensitivity of the two modalities and to establish correlations that might improve diagnostic accuracy. Results Among 225 lesions identified with CESM and MG, histological evaluation revealed 143 carcinomas (127 infiltrating, 16 intraductal) and 82 benign lesions. This is the largest cohort investigated with CESM to date. The sensitivity of CESM was higher than that of MG (100% and 90%, respectively, p=0.010). Medium or strong enhancement on CESM and the presence of a mass on MG was the most likely indictor of malignancy (55.1% p=0.002). Among benign lesions, 60% presented as enhancement on CESM (were false-positive), and most frequently as medium or weak enhancement, together with a mass on MG (53%, p=0.047). Unfortunately, the study did not find combinations of MG findings and CESM enhancement patterns that would be helpful in defining false-positive lesions. We observed systematic overestimation of maximum lesion diameter on CESM compared to histology (mean difference: 2.29 mm). Conclusions Strong or medium enhancement on CESM and mass or mass with microcalcifications on MG were strong indicators of malignant transformation. However, we found no combination of MG and CESM characteristics helpful in defining false-positive lesions. PMID:27768681

Degree of Enhancement on Contrast Enhanced Spectral Mammography (CESM) and Lesion Type on Mammography (MG): Comparison Based on Histological Results.

PubMed

Łuczyńska, Elżbieta; Niemiec, Joanna; Hendrick, Edward; Heinze, Sylwia; Jaszczyński, Janusz; Jakubowicz, Jerzy; Sas-Korczyńska, Beata; Rys, Janusz

2016-10-21

BACKGROUND Contrast enhanced spectral mammography (CESM) is a new method of breast cancer diagnosis in which an iodinated contrast agent is injected and dual-energy mammography is obtained in multiple views of the breasts. The aim of this study was to compare the degree of enhancement on CESM with lesion characteristics on mammography (MG) and lesion histology in women with suspicious breast lesions. MATERIAL AND METHODS The degree of enhancement on CESM (absent, weak, medium, or strong) was compared to lesion characteristics on MG (mass, mass with microcalcifications, or microcalcifications alone) and histology (infiltrating carcinoma, intraductal carcinoma, or benign) to compare sensitivity of the two modalities and to establish correlations that might improve diagnostic accuracy. RESULTS Among 225 lesions identified with CESM and MG, histological evaluation revealed 143 carcinomas (127 infiltrating, 16 intraductal) and 82 benign lesions. This is the largest cohort investigated with CESM to date. The sensitivity of CESM was higher than that of MG (100% and 90%, respectively, p=0.010). Medium or strong enhancement on CESM and the presence of a mass on MG was the most likely indictor of malignancy (55.1% p=0.002). Among benign lesions, 60% presented as enhancement on CESM (were false-positive), and most frequently as medium or weak enhancement, together with a mass on MG (53%, p=0.047). Unfortunately, the study did not find combinations of MG findings and CESM enhancement patterns that would be helpful in defining false-positive lesions. We observed systematic overestimation of maximum lesion diameter on CESM compared to histology (mean difference: 2.29 mm). CONCLUSIONS Strong or medium enhancement on CESM and mass or mass with microcalcifications on MG were strong indicators of malignant transformation. However, we found no combination of MG and CESM characteristics helpful in defining false-positive lesions.

[Radiological control intraoperatory of a surgical piece in non palpable breast lesions].

PubMed

Ruvalcaba Limón, Eva; Espejo Fonseca, Ruby; Bautista Piña, Verónica; Madero Preciado, Luis; Capurso Garcia, Marino; Serratos Garduño, José Eduardo; Hohenstein, Fernando Guisa; Rodríguez Cuevas, Sergio

2009-09-01

nonconcrete the mammary injuries are frequent in programs of detection of breast cancer, estereotaxic or ecographic marking is required to realize its split. The intrasurgical radiation control of the surgical piece is indispensable to evaluate the margins of the mammary cancer. to determine the effectiveness of the intrasurgical radiation control of the surgical piece in nonconcrete mammary injuries to diminish the surgical reinterventions to extend margins. women with nonconcrete mammary injuries to those who biopsy by split became, previous marking and intraoperating radiation control of the surgical piece to value margins (suitable margin the same or major of 10 mm, smaller inadequate margin of 10 mm). Intrasurgical reesicion in inadequate radiological margins became. The demographic characteristics, masto-ecographics images, histopathology of the injuries and the radiological-histopatol6gica correlation of the margins studied. Cross-sectional, prospective and descriptive study. 103 patients with 113 nonconcrete mammary injuries included themselves, with age average of 51,35 (32-73) years. In all the injuries the intrasurgical radiation control became of the surgical piece. The prevalence of mammary cancer was of 28.3% (32/113), that corresponds to stellar images (42.8%), suspicious microcalcifications with density (39.2%), microcalcifications (31.2%) and nodules (20%). Of the 32 cancers, 16 had inadequate radiological margins that required intraoperating reescision; suitable histopatologic margins in 100% were obtained (16/16). The 16 (62.5%) cancers without intraoperating reescisi6n by suitable radiological margins had suitable histopatologic margins and 37.5% (6/16) inadequate ones that required surgical reinterventionn to control the margins. The discrepancy between margins was related to microcalcifications in 83.3% of the injuries. the intrasurgical radiation control of the surgical piece is effective to evaluate margins; the intrasurgical reescisión changed inadequate margins to suitable in 50% (16/32) of the cancers; only 18.7% (6/32) of the total of cases required another surgery to control the margins.

Digital mammography: comparative performance of color LCD and monochrome CRT displays.

PubMed

Samei, Ehsan; Poolla, Ananth; Ulissey, Michael J; Lewin, John M

2007-05-01

To evaluate the comparative performance of high-fidelity liquid crystal display (LCD) and cathode ray tube (CRT) devices for mammography applications, and to assess the impact of LCD viewing angle on detection accuracy. Ninety 1 k x 1 k images were selected from a database of digital mammograms: 30 without any abnormality present, 30 with subtle masses, and 30 with subtle microcalcifications. The images were used with waived informed consent, Health Insurance Portability and Accountability Act compliance, and Institutional Review Board approval. With postprocessing presentation identical to those of the commercial mammography system used, 1 k x 1 k sections of images were viewed on a monochrome CRT and a color LCD in native grayscale, and with a grayscale representative of images viewed from a 30 degrees or 50 degrees off-normal viewing angle. Randomized images were independently scored by four experienced breast radiologists for the presence of lesions using a 0-100 grading scale. To compare diagnostic performance of the display modes, observer scores were analyzed using receiver operating characteristic (ROC) and analysis of variance. For masses and microcalcifications, the detection rate in terms of the area under the ROC curve (A(z)) showed a 2% increase and a 4% decrease from CRT to LCD, respectively. However, differences were not statistically significant (P > .05). The viewing angle data showed better microcalcification detection but lower mass detection at 30 degrees viewing orientation. The overall results varied notably from observer to observer yielding no statistically discernible trends across all observers, suggesting that within the 0-50 degrees viewing angle range and in a controlled observer experiment, the variation in the contrast response of the LCD has little or no impact on the detection of mammographic lesions. Although CRTs and LCDs differ in terms of angular response, resolution, noise, and color, these characteristics seem to have little influence on the detection of mammographic lesions. The results suggest comparable performance in clinical applications of the two devices.

The threshold bootstrap clustering: a new approach to find families or transmission clusters within molecular quasispecies.

PubMed

Prosperi, Mattia C F; De Luca, Andrea; Di Giambenedetto, Simona; Bracciale, Laura; Fabbiani, Massimiliano; Cauda, Roberto; Salemi, Marco

2010-10-25

Phylogenetic methods produce hierarchies of molecular species, inferring knowledge about taxonomy and evolution. However, there is not yet a consensus methodology that provides a crisp partition of taxa, desirable when considering the problem of intra/inter-patient quasispecies classification or infection transmission event identification. We introduce the threshold bootstrap clustering (TBC), a new methodology for partitioning molecular sequences, that does not require a phylogenetic tree estimation. The TBC is an incremental partition algorithm, inspired by the stochastic Chinese restaurant process, and takes advantage of resampling techniques and models of sequence evolution. TBC uses as input a multiple alignment of molecular sequences and its output is a crisp partition of the taxa into an automatically determined number of clusters. By varying initial conditions, the algorithm can produce different partitions. We describe a procedure that selects a prime partition among a set of candidate ones and calculates a measure of cluster reliability. TBC was successfully tested for the identification of type-1 human immunodeficiency and hepatitis C virus subtypes, and compared with previously established methodologies. It was also evaluated in the problem of HIV-1 intra-patient quasispecies clustering, and for transmission cluster identification, using a set of sequences from patients with known transmission event histories. TBC has been shown to be effective for the subtyping of HIV and HCV, and for identifying intra-patient quasispecies. To some extent, the algorithm was able also to infer clusters corresponding to events of infection transmission. The computational complexity of TBC is quadratic in the number of taxa, lower than other established methods; in addition, TBC has been enhanced with a measure of cluster reliability. The TBC can be useful to characterise molecular quasipecies in a broad context.

Automated bow shock and radiation belt edge identification methods and their application for Cluster, THEMIS/ARTEMIS and Van Allen Probes data

NASA Astrophysics Data System (ADS)

Facsko, Gabor; Sibeck, David; Balogh, Tamas; Kis, Arpad; Wesztergom, Viktor

2017-04-01

The bow shock and the outer rim of the outer radiation belt are detected automatically by our algorithm developed as a part of the Boundary Layer Identification Code Cluster Active Archive project. The radiation belt positions are determined from energized electron measurements working properly onboard all Cluster spacecraft. For bow shock identification we use magnetometer data and, when available, ion plasma instrument data. In addition, electrostatic wave instrument electron density, spacecraft potential measurements and wake indicator auxiliary data are also used so the events can be identified by all Cluster probes in highly redundant way, as the magnetometer and these instruments are still operational in all spacecraft. The capability and performance of the bow shock identification algorithm were tested using known bow shock crossing determined manually from January 29, 2002 to February 3,. The verification enabled 70% of the bow shock crossings to be identified automatically. The method shows high flexibility and it can be applied to observations from various spacecraft. Now these tools have been applied to Time History of Events and Macroscale Interactions during Substorms (THEMIS)/Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) magnetic field, plasma and spacecraft potential observations to identify bow shock crossings; and to Van Allen Probes supra-thermal electron observations to identify the edges of the radiation belt. The outcomes of the algorithms are checked manually and the parameters used to search for bow shock identification are refined.

cluster trials v. 1.0

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

Mitchell, John; Castillo, Andrew

2016-09-21

This software contains a set of python modules – input, search, cluster, analysis; these modules read input files containing spatial coordinates and associated attributes which can be used to perform nearest neighbor search (spatial indexing via kdtree), cluster analysis/identification, and calculation of spatial statistics for analysis.

Detecting synchronization clusters in multivariate time series via coarse-graining of Markov chains.

PubMed

Allefeld, Carsten; Bialonski, Stephan

2007-12-01

Synchronization cluster analysis is an approach to the detection of underlying structures in data sets of multivariate time series, starting from a matrix R of bivariate synchronization indices. A previous method utilized the eigenvectors of R for cluster identification, analogous to several recent attempts at group identification using eigenvectors of the correlation matrix. All of these approaches assumed a one-to-one correspondence of dominant eigenvectors and clusters, which has however been shown to be wrong in important cases. We clarify the usefulness of eigenvalue decomposition for synchronization cluster analysis by translating the problem into the language of stochastic processes, and derive an enhanced clustering method harnessing recent insights from the coarse-graining of finite-state Markov processes. We illustrate the operation of our method using a simulated system of coupled Lorenz oscillators, and we demonstrate its superior performance over the previous approach. Finally we investigate the question of robustness of the algorithm against small sample size, which is important with regard to field applications.

A machine learning approach for ranking clusters of docked protein‐protein complexes by pairwise cluster comparison

PubMed Central

Pfeiffenberger, Erik; Chaleil, Raphael A.G.; Moal, Iain H.

2017-01-01

ABSTRACT Reliable identification of near‐native poses of docked protein–protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein–protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near‐native from incorrect clusters. The results show that our approach is able to identify clusters containing near‐native protein–protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528–543. © 2016 Wiley Periodicals, Inc. PMID:27935158

Identification of lethal cluster of genes in the yeast transcription network

NASA Astrophysics Data System (ADS)

Rho, K.; Jeong, H.; Kahng, B.

2006-05-01

Identification of essential or lethal genes would be one of the ultimate goals in drug designs. Here we introduce an in silico method to select the cluster with a high population of lethal genes, called lethal cluster, through microarray assay. We construct a gene transcription network based on the microarray expression level. Links are added one by one in the descending order of the Pearson correlation coefficients between two genes. As the link density p increases, two meaningful link densities pm and ps are observed. At pm, which is smaller than the percolation threshold, the number of disconnected clusters is maximum, and the lethal genes are highly concentrated in a certain cluster that needs to be identified. Thus the deletion of all genes in that cluster could efficiently lead to a lethal inviable mutant. This lethal cluster can be identified by an in silico method. As p increases further beyond the percolation threshold, the power law behavior in the degree distribution of a giant cluster appears at ps. We measure the degree of each gene at ps. With the information pertaining to the degrees of each gene at ps, we return to the point pm and calculate the mean degree of genes of each cluster. We find that the lethal cluster has the largest mean degree.

Identification of Staphylococcus spp. using (GTG)₅-PCR fingerprinting.

PubMed

Svec, Pavel; Pantůček, Roman; Petráš, Petr; Sedláček, Ivo; Nováková, Dana

2010-12-01

A group of 212 type and reference strains deposited in the Czech Collection of Microorganisms (Brno, Czech Republic) and covering 41 Staphylococcus species comprising 21 subspecies was characterised using rep-PCR fingerprinting with the (GTG)₅ primer in order to evaluate this method for identification of staphylococci. All strains were typeable using the (GTG)₅ primer and generated PCR products ranging from 200 to 4500 bp. Numerical analysis of the obtained fingerprints revealed (sub)species-specific clustering corresponding with the taxonomic position of analysed strains. Taxonomic position of selected strains representing the (sub)species that were distributed over multiple rep-PCR clusters was verified and confirmed by the partial rpoB gene sequencing. Staphylococcus caprae, Staphylococcus equorum, Staphylococcus sciuri, Staphylococcus piscifermentans, Staphylococcus xylosus, and Staphylococcus saprophyticus revealed heterogeneous fingerprints and each (sub)species was distributed over several clusters. However, representatives of the remaining Staphylococcus spp. were clearly separated in single (sub)species-specific clusters. These results showed rep-PCR with the (GTG)₅ primer as a fast and reliable method applicable for differentiation and straightforward identification of majority of Staphylococcus spp. Copyright © 2010 Elsevier GmbH. All rights reserved.

The cluster charge identification in the GEM detector for fusion plasma imaging by soft X-ray diagnostics

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

Czarski, T., E-mail: tomasz.czarski@ifpilm.pl; Chernyshova, M.; Malinowski, K.

2016-11-15

The measurement system based on gas electron multiplier detector is developed for soft X-ray diagnostics of tokamak plasmas. The multi-channel setup is designed for estimation of the energy and the position distribution of an X-ray source. The focal measuring issue is the charge cluster identification by its value and position estimation. The fast and accurate mode of the serial data acquisition is applied for the dynamic plasma diagnostics. The charge clusters are counted in the space determined by 2D position, charge value, and time intervals. Radiation source characteristics are presented by histograms for a selected range of position, time intervals,more » and cluster charge values corresponding to the energy spectra.« less

Scoring clustering solutions by their biological relevance.

PubMed

Gat-Viks, I; Sharan, R; Shamir, R

2003-12-12

A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering gene expression data into homogeneous groups was shown to be instrumental in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on clustering algorithms for gene expression analysis, very few works addressed the systematic comparison and evaluation of clustering results. Typically, different clustering algorithms yield different clustering solutions on the same data, and there is no agreed upon guideline for choosing among them. We developed a novel statistically based method for assessing a clustering solution according to prior biological knowledge. Our method can be used to compare different clustering solutions or to optimize the parameters of a clustering algorithm. The method is based on projecting vectors of biological attributes of the clustered elements onto the real line, such that the ratio of between-groups and within-group variance estimators is maximized. The projected data are then scored using a non-parametric analysis of variance test, and the score's confidence is evaluated. We validate our approach using simulated data and show that our scoring method outperforms several extant methods, including the separation to homogeneity ratio and the silhouette measure. We apply our method to evaluate results of several clustering methods on yeast cell-cycle gene expression data. The software is available from the authors upon request.

Chemistry Within Molecular Clusters

DTIC Science & Technology

1992-06-01

reactions, and only occur within van der Waals clusters. 23 They include the generation of (C2H4F2),>4H+ ions from 1,1- difluoroethane clusters, 4 the...of fragment ions, and identification of the molecule must be made by the characteristic fragmentation pattern. The mass spectrum of 1,1- difluoroethane

Chemistry within Molecular Clusters

DTIC Science & Technology

1992-05-29

within van der Waals clusters. 23 They include the generation of (C2H4F 2),,>4H+ ions from 1,1- difluoroethane clusters, 24 the generation of (CH 3...fragment ions, and identification of the molecule must be made by the characteristic fragmentation pattern. The mass spectrum of 1,1- difluoroethane (DFE

Seamless lesion insertion in digital mammography: methodology and reader study

NASA Astrophysics Data System (ADS)

Pezeshk, Aria; Petrick, Nicholas; Sahiner, Berkman

2016-03-01

Collection of large repositories of clinical images containing verified cancer locations is costly and time consuming due to difficulties associated with both the accumulation of data and establishment of the ground truth. This problem poses a significant challenge to the development of machine learning algorithms that require large amounts of data to properly train and avoid overfitting. In this paper we expand the methods in our previous publications by making several modifications that significantly increase the speed of our insertion algorithms, thereby allowing them to be used for inserting lesions that are much larger in size. These algorithms have been incorporated into an image composition tool that we have made publicly available. This tool allows users to modify or supplement existing datasets by seamlessly inserting a real breast mass or micro-calcification cluster extracted from a source digital mammogram into a different location on another mammogram. We demonstrate examples of the performance of this tool on clinical cases taken from the University of South Florida Digital Database for Screening Mammography (DDSM). Finally, we report the results of a reader study evaluating the realism of inserted lesions compared to clinical lesions. Analysis of the radiologist scores in the study using receiver operating characteristic (ROC) methodology indicates that inserted lesions cannot be reliably distinguished from clinical lesions.

Acquiring skill at medical image inspection: learning localized in early visual processes

NASA Astrophysics Data System (ADS)

Sowden, Paul T.; Davies, Ian R. L.; Roling, Penny; Watt, Simon J.

1997-04-01

Acquisition of the skill of medical image inspection could be due to changes in visual search processes, 'low-level' sensory learning, and higher level 'conceptual learning.' Here, we report two studies that investigate the extent to which learning in medical image inspection involves low- level learning. Early in the visual processing pathway cells are selective for direction of luminance contrast. We exploit this in the present studies by using transfer across direction of contrast as a 'marker' to indicate the level of processing at which learning occurs. In both studies twelve observers trained for four days at detecting features in x- ray images (experiment one equals discs in the Nijmegen phantom, experiment two equals micro-calcification clusters in digitized mammograms). Half the observers examined negative luminance contrast versions of the images and the remainder examined positive contrast versions. On the fifth day, observers swapped to inspect their respective opposite contrast images. In both experiments leaning occurred across sessions. In experiment one, learning did not transfer across direction of luminance contrast, while in experiment two there was only partial transfer. These findings are consistent with the contention that some of the leaning was localized early in the visual processing pathway. The implications of these results for current medical image inspection training schedules are discussed.

PepArML: A Meta-Search Peptide Identification Platform

PubMed Central

Edwards, Nathan J.

2014-01-01

The PepArML meta-search peptide identification platform provides a unified search interface to seven search engines; a robust cluster, grid, and cloud computing scheduler for large-scale searches; and an unsupervised, model-free, machine-learning-based result combiner, which selects the best peptide identification for each spectrum, estimates false-discovery rates, and outputs pepXML format identifications. The meta-search platform supports Mascot; Tandem with native, k-score, and s-score scoring; OMSSA; MyriMatch; and InsPecT with MS-GF spectral probability scores — reformatting spectral data and constructing search configurations for each search engine on the fly. The combiner selects the best peptide identification for each spectrum based on search engine results and features that model enzymatic digestion, retention time, precursor isotope clusters, mass accuracy, and proteotypic peptide properties, requiring no prior knowledge of feature utility or weighting. The PepArML meta-search peptide identification platform often identifies 2–3 times more spectra than individual search engines at 10% FDR. PMID:25663956

Improved Ultrasonic Imaging of the Breast

DTIC Science & Technology

2005-08-01

differentiation of benign and malignant lesions. This method yields high resolution images with minimal statistical variability. We have formed images in... and malignant masses often exhibit only subtle image differences. We have invented a new technique that uses modified ultrasound equipment to form...between malignant and benign lesions. The utility of ultrasound is limited because microcalcifications (MCs) are not typically visible and because benign

Improved Ultrasonic Imaging of the Breast

DTIC Science & Technology

2002-08-01

differentiation of benign and malignant lesions. This method yields high resolution images with minimal statistical variability. In this first year of... and malignant masses often exhibit only subtle image differences. We have invented a new technique that uses modified ultrasound equipment to form...between malignant and benign lesions. The utility of ultrasound is limited because microcalcifications (MCs) are not typically visible and because benign

Improved Ultrasonic Imaging of the Breast

DTIC Science & Technology

2004-08-01

differentiation of benign and malignant lesions. This method yields high resolution images with minimal statistical variability. We have formed images in... and malignant masses often exhibit only subtle image differences. We have invented a new technique that uses modified ultrasound equipment to form...between malignant and benign lesions. The utility of ultrasound is limited because microcalcifications (MCs) are not typically visible and because benign

Epithelial atypia in biopsies performed for microcalcifications. Practical considerations about 2,833 serially sectioned surgical biopsies with a long follow-up

PubMed Central

MacGrogan, Gaëtan; Mathoulin-Pélissier, Simone; Vincent-Salomon, Anne; Soubeyran, Isabelle; Picot, Véronique; Coindre, Jean-Michel; Mauriac, Louis

2007-01-01

This study analyzes the occurrence of epithelial atypia in 2,833 serially sectioned surgical breast biopsies (SB) performed for microcalcifications (median number of blocks per SB:26) and the occurrence of subsequent cancer after an initial diagnosis of epithelial atypia (median follow-up 160 months). Epithelial atypia (flat epithelial atypia, atypical ductal hyperplasia, and lobular neoplasia) were found in 971 SB, with and without a concomitant cancer in 301 (31%) and 670 (69%) SB, respectively. Thus, isolated epithelial atypia were found in 670 out of the 2,833 SB (23%). Concomitant cancers corresponded to ductal carcinomas in situ and micro-invasive (77%), invasive ductal carcinomas not otherwise specified (15%), invasive lobular carcinomas (4%), and tubular carcinomas (4%). Fifteen out of the 443 patients with isolated epithelial atypia developed a subsequent ipsilateral (n = 14) and contralateral (n = 1) invasive cancer. The high slide rating might explain the high percentages of epithelial atypia and concomitant cancers and the low percentage of subsequent cancer after a diagnosis of epithelial atypia as a single lesion. Epithelial atypia could be more a risk marker of concomitant than subsequent cancer. PMID:17551752

Epithelial atypia in biopsies performed for microcalcifications. practical considerations about 2,833 serially sectioned surgical biopsies with a long follow-up.

PubMed

de Mascarel, Isabelle; MacGrogan, Gaëtan; Mathoulin-Pélissier, Simone; Vincent-Salomon, Anne; Soubeyran, Isabelle; Picot, Véronique; Coindre, Jean-Michel; Mauriac, Louis

2007-07-01

This study analyzes the occurrence of epithelial atypia in 2,833 serially sectioned surgical breast biopsies (SB) performed for microcalcifications (median number of blocks per SB:26) and the occurrence of subsequent cancer after an initial diagnosis of epithelial atypia (median follow-up 160 months). Epithelial atypia (flat epithelial atypia, atypical ductal hyperplasia, and lobular neoplasia) were found in 971 SB, with and without a concomitant cancer in 301 (31%) and 670 (69%) SB, respectively. Thus, isolated epithelial atypia were found in 670 out of the 2,833 SB (23%). Concomitant cancers corresponded to ductal carcinomas in situ and micro-invasive (77%), invasive ductal carcinomas not otherwise specified (15%), invasive lobular carcinomas (4%), and tubular carcinomas (4%). Fifteen out of the 443 patients with isolated epithelial atypia developed a subsequent ipsilateral (n = 14) and contralateral (n = 1) invasive cancer. The high slide rating might explain the high percentages of epithelial atypia and concomitant cancers and the low percentage of subsequent cancer after a diagnosis of epithelial atypia as a single lesion. Epithelial atypia could be more a risk marker of concomitant than subsequent cancer.

Shear Wave Elastography May Add a New Dimension to Ultrasound Evaluation of Thyroid Nodules: Case Series with Comparative Evaluation

PubMed Central

Slapa, Rafal Z.; Piwowonski, Antoni; Jakubowski, Wieslaw S.; Bierca, Jacek; Szopinski, Kazimierz T.; Slowinska-Srzednicka, Jadwiga; Migda, Bartosz; Mlosek, R. Krzysztof

2012-01-01

Although elastography can enhance the differential diagnosis of thyroid nodules, its diagnostic performance is not ideal at present. Further improvements in the technique and creation of robust diagnostic criteria are necessary. The purpose of this study was to compare the usefulness of strain elastography and a new generation of elasticity imaging called supersonic shear wave elastography (SSWE) in differential evaluation of thyroid nodules. Six thyroid nodules in 4 patients were studied. SSWE yielded 1 true-positive and 5 true-negative results. Strain elastography yielded 5 false-positive results and 1 false-negative result. A novel finding appreciated with SSWE, were punctate foci of increased stiffness corresponding to microcalcifications in 4 nodules, some not visible on B-mode ultrasound, as opposed to soft, colloid-inspissated areas visible on B-mode ultrasound in 2 nodules. This preliminary paper indicates that SSWE may outperform strain elastography in differentiation of thyroid nodules with regard to their stiffness. SSWE showed the possibility of differentiation of high echogenic foci into microcalcifications and inspissated colloid, adding a new dimension to thyroid elastography. Further multicenter large-scale studies of thyroid nodules evaluating different elastographic methods are warranted. PMID:22685685

Analyser-based mammography using single-image reconstruction.

PubMed

Briedis, Dahliyani; Siu, Karen K W; Paganin, David M; Pavlov, Konstantin M; Lewis, Rob A

2005-08-07

We implement an algorithm that is able to decode a single analyser-based x-ray phase-contrast image of a sample, converting it into an equivalent conventional absorption-contrast radiograph. The algorithm assumes the projection approximation for x-ray propagation in a single-material object embedded in a substrate of approximately uniform thickness. Unlike the phase-contrast images, which have both directional bias and a bias towards edges present in the sample, the reconstructed images are directly interpretable in terms of the projected absorption coefficient of the sample. The technique was applied to a Leeds TOR[MAM] phantom, which is designed to test mammogram quality by the inclusion of simulated microcalcifications, filaments and circular discs. This phantom was imaged at varying doses using three modalities: analyser-based synchrotron phase-contrast images converted to equivalent absorption radiographs using our algorithm, slot-scanned synchrotron imaging and imaging using a conventional mammography unit. Features in the resulting images were then assigned a quality score by volunteers. The single-image reconstruction method achieved higher scores at equivalent and lower doses than the conventional mammography images, but no improvement of visualization of the simulated microcalcifications, and some degradation in image quality at reduced doses for filament features.

Introduction to Vocations: Comprehensive Middle School Program.

ERIC Educational Resources Information Center

Moldan, Carol; And Others

Specific emphasis of this handbook is on the integration of 15 career clusters into an existing curriculum for grades 7 and 8. It is intended particularly for teachers who are exploring the various occupational clusters for the identification of the various career opportunities with their students. The 15 occupational cluster topics included are:…

Cosmological constraints from X-ray all sky surveys, from CODEX to eROSITA

NASA Astrophysics Data System (ADS)

Finoguenov, A.

2017-10-01

Large area cluster cosmology has long become a multiwavelength discipline. Understanding the effect of various selections is currently the main path to improving on the validity of cluster cosmological results. Many of these results are based on the large area sample derived from RASS data. We perform wavelet detection of X-ray sources and make extensive simulations of the detection of clusters in the RASS data. We assign an optical richness to each of the 25,000 detected X-ray sources in the 10,000 square degrees of SDSS BOSS area. We show that there is no obvious separation of sources on galaxy clusters and AGN, based on distribution of systems on their richness. We conclude that previous catalogs, such as MACS, REFLEX are all subject to a complex optical selection function, in addition to an X-ray selection. We provide a complete model of identification of cluster counts are galaxy clusters, which includes chance identification, effect of AGN halo occupation distribution and the thermal emission of ICM. Finally we present the cosmological results obtained using this sample.

Optical Identifications of High-Redshift Galaxy Clusters from the Planck Sunyaev-Zeldovich Survey

NASA Astrophysics Data System (ADS)

Burenin, R. A.; Bikmaev, I. F.; Khamitov, I. M.; Zaznobin, I. A.; Khorunzhev, G. A.; Eselevich, M. V.; Afanasiev, V. L.; Dodonov, S. N.; Rubiño-Martín, J.-A.; Aghanim, N.; Sunyaev, R. A.

2018-05-01

We present the results of optical identifications and spectroscopic redshift measurements for galaxy clusters from the second Planck catalogue of Sunyaev-Zeldovich sources (PSZ2) located at high redshifts, z ≈ 0.7-0.9. We used the data of optical observations with the Russian-Turkish 1.5-mtelescope (RTT-150), the Sayan Observatory 1.6-m telescope, the Calar Alto 3.5-m telescope, and the 6-m SAO RAS telescope (BTA). The spectroscopic redshift measurements were obtained for seven galaxy clusters, including one cluster, PSZ2 G126.57+51.61, from the cosmological sample of the PSZ2 catalogue. In the central regions of two clusters, PSZ2 G069.39+68.05 and PSZ2 G087.39-34.58, we detected arcs of strong gravitational lensing of background galaxies, one of which is at redshift z = 4.262. The data presented below roughly double the number of known galaxy clusters in the second Planck catalogue of Sunyaev-Zeldovich sources at high redshifts, z ≈ 0.8.

X-ray emission from the Pleiades cluster

NASA Technical Reports Server (NTRS)

Agrawal, P. C.; Singh, K. P.; Riegler, G. R.

1983-01-01

The detection and identification of H0344+24, a new X-ray source located in the Pleiades cluster, is reported, based on observations made with HEAO A-2 low-energy detector 1 in the 0.15-3.0-keV energy band in August, 1977. The 90-percent-confidence error box for the new source is centered at 03 h 44.1 min right ascension (1950), near the center star of the 500-star Pleiades cluster, 25-eta-Tau. Since no likely galactic or extragalactic source of X-rays was found in a catalog search of the error-box region, identification of the source with the Pleiades cluster is considered secure. X-ray luminosity of the source is calculated to be about 10 to the 32nd ergs/sec, based on a distance of 125 pc. The X-ray characteristics of the Pleiades stars are discussed, and it is concluded that H0344+24 can best be explained as the integrated X-ray emission of all the B and F stars in the cluster.

Identification of new genes in a cell envelope-cell division gene cluster of Escherichia coli: cell envelope gene murG.

PubMed Central

Salmond, G P; Lutkenhaus, J F; Donachie, W D

1980-01-01

We report the identification, cloning, and mapping of a new cell envelope gene, murG. This lies in a group of five genes of similar phenotype (in the order murE murF murG murC ddl) all concerned with peptidoglycan biosynthesis. This group is in a larger cluster of at least 10 genes, all of which are involved in some way with cell envelope growth. Images PMID:6998962

Identification and characterization of near-fatal asthma phenotypes by cluster analysis.

PubMed

Serrano-Pariente, J; Rodrigo, G; Fiz, J A; Crespo, A; Plaza, V

2015-09-01

Near-fatal asthma (NFA) is a heterogeneous clinical entity and several profiles of patients have been described according to different clinical, pathophysiological and histological features. However, there are no previous studies that identify in a unbiased way--using statistical methods such as clusters analysis--different phenotypes of NFA. Therefore, the aim of the present study was to identify and to characterize phenotypes of near fatal asthma using a cluster analysis. Over a period of 2 years, 33 Spanish hospitals enrolled 179 asthmatics admitted for an episode of NFA. A cluster analysis using two-steps algorithm was performed from data of 84 of these cases. The analysis defined three clusters of patients with NFA: cluster 1, the largest, including older patients with clinical and therapeutic criteria of severe asthma; cluster 2, with an high proportion of respiratory arrest (68%), impaired consciousness level (82%) and mechanical ventilation (93%); and cluster 3, which included younger patients, characterized by an insufficient anti-inflammatory treatment and frequent sensitization to Alternaria alternata and soybean. These results identify specific asthma phenotypes involved in NFA, confirming in part previous findings observed in studies with a clinical approach. The identification of patients with a specific NFA phenotype could suggest interventions to prevent future severe asthma exacerbations. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Identification of chronic rhinosinusitis phenotypes using cluster analysis.

PubMed

Soler, Zachary M; Hyer, J Madison; Ramakrishnan, Viswanathan; Smith, Timothy L; Mace, Jess; Rudmik, Luke; Schlosser, Rodney J

2015-05-01

Current clinical classifications of chronic rhinosinusitis (CRS) have been largely defined based upon preconceived notions of factors thought to be important, such as polyp or eosinophil status. Unfortunately, these classification systems have little correlation with symptom severity or treatment outcomes. Unsupervised clustering can be used to identify phenotypic subgroups of CRS patients, describe clinical differences in these clusters and define simple algorithms for classification. A multi-institutional, prospective study of 382 patients with CRS who had failed initial medical therapy completed the Sino-Nasal Outcome Test (SNOT-22), Rhinosinusitis Disability Index (RSDI), Medical Outcomes Study Short Form-12 (SF-12), Pittsburgh Sleep Quality Index (PSQI), and Patient Health Questionnaire (PHQ-2). Objective measures of CRS severity included Brief Smell Identification Test (B-SIT), CT, and endoscopy scoring. All variables were reduced and unsupervised hierarchical clustering was performed. After clusters were defined, variations in medication usage were analyzed. Discriminant analysis was performed to develop a simplified, clinically useful algorithm for clustering. Clustering was largely determined by age, severity of patient reported outcome measures, depression, and fibromyalgia. CT and endoscopy varied somewhat among clusters. Traditional clinical measures, including polyp/atopic status, prior surgery, B-SIT and asthma, did not vary among clusters. A simplified algorithm based upon productivity loss, SNOT-22 score, and age predicted clustering with 89% accuracy. Medication usage among clusters did vary significantly. A simplified algorithm based upon hierarchical clustering is able to classify CRS patients and predict medication usage. Further studies are warranted to determine if such clustering predicts treatment outcomes. © 2015 ARS-AAOA, LLC.

Online writer identification using alphabetic information clustering

NASA Astrophysics Data System (ADS)

Tan, Guo Xian; Viard-Gaudin, Christian; Kot, Alex C.

2009-01-01

Writer identification is a topic of much renewed interest today because of its importance in applications such as writer adaptation, routing of documents and forensic document analysis. Various algorithms have been proposed to handle such tasks. Of particular interests are the approaches that use allographic features [1-3] to perform a comparison of the documents in question. The allographic features are used to define prototypes that model the unique handwriting styles of the individual writers. This paper investigates a novel perspective that takes alphabetic information into consideration when the allographic features are clustered into prototypes at the character level. We hypothesize that alphabetic information provides additional clues which help in the clustering of allographic prototypes. An alphabet information coefficient (AIC) has been introduced in our study and the effect of this coefficient is presented. Our experiments showed an increase of writer identification accuracy from 66.0% to 87.0% when alphabetic information was used in conjunction with allographic features on a database of 200 reference writers.

Machine-learned cluster identification in high-dimensional data.

PubMed

Ultsch, Alfred; Lötsch, Jörn

2017-02-01

High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the clusters, classical algorithms occasionally suggest a cluster structure in homogenously distributed data or assign data points to incorrect clusters. We analyzed whether this can be avoided by using emergent self-organizing feature maps (ESOM). Data sets with different degrees of complexity were submitted to ESOM analysis with large numbers of neurons, using an interactive R-based bioinformatics tool. On top of the trained ESOM the distance structure in the high dimensional feature space was visualized in the form of a so-called U-matrix. Clustering results were compared with those provided by classical common cluster algorithms including single linkage, Ward and k-means. Ward clustering imposed cluster structures on cluster-less "golf ball", "cuboid" and "S-shaped" data sets that contained no structure at all (random data). Ward clustering also imposed structures on permuted real world data sets. By contrast, the ESOM/U-matrix approach correctly found that these data contain no cluster structure. However, ESOM/U-matrix was correct in identifying clusters in biomedical data truly containing subgroups. It was always correct in cluster structure identification in further canonical artificial data. Using intentionally simple data sets, it is shown that popular clustering algorithms typically used for biomedical data sets may fail to cluster data correctly, suggesting that they are also likely to perform erroneously on high dimensional biomedical data. The present analyses emphasized that generally established classical hierarchical clustering algorithms carry a considerable tendency to produce erroneous results. By contrast, unsupervised machine-learned analysis of cluster structures, applied using the ESOM/U-matrix method, is a viable, unbiased method to identify true clusters in the high-dimensional space of complex data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

The smart cluster method. Adaptive earthquake cluster identification and analysis in strong seismic regions

NASA Astrophysics Data System (ADS)

Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

2017-07-01

Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010-2011 Darfield-Christchurch sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

BP network identification technology of infrared polarization based on fuzzy c-means clustering

NASA Astrophysics Data System (ADS)

Zeng, Haifang; Gu, Guohua; He, Weiji; Chen, Qian; Yang, Wei

2011-08-01

Infrared detection system is frequently employed on surveillance operations and reconnaissance mission to detect particular targets of interest in both civilian and military communities. By incorporating the polarization of light as supplementary information, the target discrimination performance could be enhanced. So this paper proposed an infrared target identification method which is based on fuzzy theory and neural network with polarization properties of targets. The paper utilizes polarization degree and light intensity to advance the unsupervised KFCM (kernel fuzzy C-Means) clustering method. And establish different material pol1arization properties database. In the built network, the system can feedback output corresponding material types of probability distribution toward any input polarized degree such as 10° 15°, 20°, 25°, 30°. KFCM, which has stronger robustness and accuracy than FCM, introduces kernel idea and gives the noise points and invalid value different but intuitively reasonable weights. Because of differences in characterization of material properties, there will be some conflicts in classification results. And D - S evidence theory was used in the combination of the polarization and intensity information. Related results show KFCM clustering precision and operation rate are higher than that of the FCM clustering method. The artificial neural network method realizes material identification, which reasonable solved the problems of complexity in environmental information of infrared polarization, and improperness of background knowledge and inference rule. This method of polarization identification is fast in speed, good in self-adaption and high in resolution.

The Clinical Relevance of Psammoma Body and Hashimoto Thyroiditis in Papillary Thyroid Carcinoma

PubMed Central

Cai, Ye-Feng; Wang, Qing-Xuan; Ni, Chun-Jue; Guo, Gui-Long; Li, Quan; Wang, Ou-Chen; Wu, Liang; Du, Hai-Yan; You, Jie; Zhang, Xiao-Hua

2015-01-01

Abstract This study aims to investigate the impact of psammoma body (PB) on papillary thyroid carcinoma (PTC), and evaluate the association among PB, Hashimoto thyroiditis (HT), and other clinicopathologic characteristics in PTC patients. We conducted a retrospective case-control study involving 1052 PTC patients who underwent total thyroidectomy or lobectomy with lymph node dissection. Psammoma body was observed in 324 out of 1052 PTC (30.8%) patients. Ultrasonographic (US) calcification (P < 0.001), multifocality of the tumor (P = 0.047), lymph node metastasis (LNM) (P < 0.001), HT (P < 0.001), and Primary tumor (T), Regional lymph nodes (N), Distant metastasis (M) staging (P = 0.001) were significantly related to the presence of PB. The presence of PB was significantly associated with US microcalcification (P < 0.001). In the subgroup with HT, compared with the patients without PB, the patients with PB exhibited a higher frequency of central LNM (54.7% vs 32.1%; P < 0.001) and US microcalcification (94.7% vs 38.8%; P < 0.001), as well as smaller tumors (0.9 ± 0.6 vs 1.3 ± 0.9 cm; P < 0.001). In the subgroup without HT, the patients with PB displayed a higher incidence of lateral LNM (25.8% vs 14.6%; P < 0.001), US microcalcification (87.3% vs 52.5%; P < 0.001), and extrathyroidal extension (47.2% vs 34.8%; P = 0.001), as well as larger tumors (1.3 ± 0.9 vs 1.0 ± 0.8 cm; P < 0.001) than without PB. Moreover, in the subgroup with PB, the PTC patients with HT showed a higher LNM (77.9% vs 57.2%; P < 0.001) and a lower frequency of extrathyroidal extension (20.0% vs 47.2%; P < 0.001) than without HT. Psammoma body is a useful predictor of aggressive tumor behavior in PTC patients. HT with PB shows more aggressive behaviors than non-HT with PB in PTC patients. PMID:26554782

The Clinical Relevance of Psammoma Body and Hashimoto Thyroiditis in Papillary Thyroid Carcinoma: A Large Case-control Study.

PubMed

Cai, Ye-Feng; Wang, Qing-Xuan; Ni, Chun-Jue; Guo, Gui-Long; Li, Quan; Wang, Ou-Chen; Wu, Liang; Du, Hai-Yan; You, Jie; Zhang, Xiao-Hua

2015-11-01

This study aims to investigate the impact of psammoma body (PB) on papillary thyroid carcinoma (PTC), and evaluate the association among PB, Hashimoto thyroiditis (HT), and other clinicopathologic characteristics in PTC patients.We conducted a retrospective case-control study involving 1052 PTC patients who underwent total thyroidectomy or lobectomy with lymph node dissection.Psammoma body was observed in 324 out of 1052 PTC (30.8%) patients. Ultrasonographic (US) calcification (P < 0.001), multifocality of the tumor (P = 0.047), lymph node metastasis (LNM) (P < 0.001), HT (P < 0.001), and Primary tumor (T), Regional lymph nodes (N), Distant metastasis (M) staging (P = 0.001) were significantly related to the presence of PB. The presence of PB was significantly associated with US microcalcification (P < 0.001). In the subgroup with HT, compared with the patients without PB, the patients with PB exhibited a higher frequency of central LNM (54.7% vs 32.1%; P < 0.001) and US microcalcification (94.7% vs 38.8%; P < 0.001), as well as smaller tumors (0.9 ± 0.6 vs 1.3 ± 0.9 cm; P < 0.001). In the subgroup without HT, the patients with PB displayed a higher incidence of lateral LNM (25.8% vs 14.6%; P < 0.001), US microcalcification (87.3% vs 52.5%; P < 0.001), and extrathyroidal extension (47.2% vs 34.8%; P = 0.001), as well as larger tumors (1.3 ± 0.9 vs 1.0 ± 0.8 cm; P < 0.001) than without PB. Moreover, in the subgroup with PB, the PTC patients with HT showed a higher LNM (77.9% vs 57.2%; P < 0.001) and a lower frequency of extrathyroidal extension (20.0% vs 47.2%; P < 0.001) than without HT.Psammoma body is a useful predictor of aggressive tumor behavior in PTC patients. HT with PB shows more aggressive behaviors than non-HT with PB in PTC patients.

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Temporary disaster debris management site identification using binomial cluster analysis and GIS.

PubMed

Grzeda, Stanislaw; Mazzuchi, Thomas A; Sarkani, Shahram

2014-04-01

An essential component of disaster planning and preparation is the identification and selection of temporary disaster debris management sites (DMS). However, since DMS identification is a complex process involving numerous variable constraints, many regional, county and municipal jurisdictions initiate this process during the post-disaster response and recovery phases, typically a period of severely stressed resources. Hence, a pre-disaster approach in identifying the most likely sites based on the number of locational constraints would significantly contribute to disaster debris management planning. As disasters vary in their nature, location and extent, an effective approach must facilitate scalability, flexibility and adaptability to variable local requirements, while also being generalisable to other regions and geographical extents. This study demonstrates the use of binomial cluster analysis in potential DMS identification in a case study conducted in Hamilton County, Indiana. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Mapping New Mobility business, innovation, and employment opportunities in Michigan : developing a data-driven graphical platform for assessing and advancing industry cluster development and entrepreneurship opportunities in urban regions : USDOT Region V

DOT National Transportation Integrated Search

2016-12-15

Across regional economic development leaders and policy makers, the concept of clustering has grown in importance as a framework for structuring economic growth and resurgence (Muro & Katz, 2010). Cluster identification is most often treated as a com...

Planck intermediate results. XXVI. Optical identification and redshifts of Planck clusters with the RTT150 telescope

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2015-09-30

In this paper, we present the results of approximately three years of observations of Planck Sunyaev-Zeldovich (SZ) sources with the Russian-Turkish 1.5 m telescope (RTT150), as a part of the optical follow-up programme undertaken by the Planck collaboration. During this time period approximately 20% of all dark and grey clear time available at the telescope was devoted to observations of Planck objects. Some observations of distant clusters were also done at the 6 m Bolshoi Telescope Alt-azimutalnyi (BTA) of the Special Astrophysical Observatory of the Russian Academy of Sciences. In total, deep, direct images of more than one hundred fieldsmore » were obtained in multiple filters. We identified 47 previously unknown galaxy clusters, 41 of which are included in the Planck catalogue of SZ sources. The redshifts of 65 Planck clusters were measured spectroscopically and 14 more were measured photometrically. We discuss the details of cluster optical identifications and redshift measurements. Finally, we also present new spectroscopic redshifts for 39 Planck clusters that were not included in the Planck SZ source catalogue and are published here for the first time.« less

Empirical Identification of Hierarchies.

ERIC Educational Resources Information Center

McCormick, Douglas; And Others

Outlining a cluster procedure which maximizes specific criteria while building scales from binary measures using a sequential, agglomerative, overlapping, non-hierarchic method results in indices giving truer results than exploratory facotr analyses or multidimensional scaling. In a series of eleven figures, patterns within cluster histories…

Towards Development of Clustering Applications for Large-Scale Comparative Genotyping and Kinship Analysis Using Y-Short Tandem Repeats.

PubMed

Seman, Ali; Sapawi, Azizian Mohd; Salleh, Mohd Zaki

2015-06-01

Y-chromosome short tandem repeats (Y-STRs) are genetic markers with practical applications in human identification. However, where mass identification is required (e.g., in the aftermath of disasters with significant fatalities), the efficiency of the process could be improved with new statistical approaches. Clustering applications are relatively new tools for large-scale comparative genotyping, and the k-Approximate Modal Haplotype (k-AMH), an efficient algorithm for clustering large-scale Y-STR data, represents a promising method for developing these tools. In this study we improved the k-AMH and produced three new algorithms: the Nk-AMH I (including a new initial cluster center selection), the Nk-AMH II (including a new dominant weighting value), and the Nk-AMH III (combining I and II). The Nk-AMH III was the superior algorithm, with mean clustering accuracy that increased in four out of six datasets and remained at 100% in the other two. Additionally, the Nk-AMH III achieved a 2% higher overall mean clustering accuracy score than the k-AMH, as well as optimal accuracy for all datasets (0.84-1.00). With inclusion of the two new methods, the Nk-AMH III produced an optimal solution for clustering Y-STR data; thus, the algorithm has potential for further development towards fully automatic clustering of any large-scale genotypic data.

Bruker Biotyper Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry System for Identification of Nocardia, Rhodococcus, Kocuria, Gordonia, Tsukamurella, and Listeria Species

PubMed Central

Lee, Tai-Fen; Du, Shin-Hei; Teng, Shih-Hua; Liao, Chun-Hsing; Sheng, Wang-Hui; Teng, Lee-Jene

2014-01-01

We evaluated whether the Bruker Biotyper matrix-associated laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) system provides accurate species-level identifications of 147 isolates of aerobically growing Gram-positive rods (GPRs). The bacterial isolates included Nocardia (n = 74), Listeria (n = 39), Kocuria (n = 15), Rhodococcus (n = 10), Gordonia (n = 7), and Tsukamurella (n = 2) species, which had all been identified by conventional methods, molecular methods, or both. In total, 89.7% of Listeria monocytogenes, 80% of Rhodococcus species, 26.7% of Kocuria species, and 14.9% of Nocardia species (n = 11, all N. nova and N. otitidiscaviarum) were correctly identified to the species level (score values, ≥2.0). A clustering analysis of spectra generated by the Bruker Biotyper identified six clusters of Nocardia species, i.e., cluster 1 (N. cyriacigeorgica), cluster 2 (N. brasiliensis), cluster 3 (N. farcinica), cluster 4 (N. puris), cluster 5 (N. asiatica), and cluster 6 (N. beijingensis), based on the six peaks generated by ClinProTools with the genetic algorithm, i.e., m/z 2,774.477 (cluster 1), m/z 5,389.792 (cluster 2), m/z 6,505.720 (cluster 3), m/z 5,428.795 (cluster 4), m/z 6,525.326 (cluster 5), and m/z 16,085.216 (cluster 6). Two clusters of L. monocytogenes spectra were also found according to the five peaks, i.e., m/z 5,594.85, m/z 6,184.39, and m/z 11,187.31, for cluster 1 (serotype 1/2a) and m/z 5,601.21 and m/z 11,199.33 for cluster 2 (serotypes 1/2b and 4b). The Bruker Biotyper system was unable to accurately identify Nocardia (except for N. nova and N. otitidiscaviarum), Tsukamurella, or Gordonia species. Continuous expansion of the MALDI-TOF MS databases to include more GPRs is necessary. PMID:24759706

Comparison of identification methods for oral asaccharolytic Eubacterium species.

PubMed

Wade, W G; Slayne, M A; Aldred, M J

1990-12-01

Thirty one strains of oral, asaccharolytic Eubacterium spp. and the type strains of E. brachy, E. nodatum and E. timidum were subjected to three identification techniques--protein-profile analysis, determination of metabolic end-products, and the API ATB32A identification kit. Five clusters were obtained from numerical analysis of protein profiles and excellent correlations were seen with the other two methods. Protein profiles alone allowed unequivocal identification.

Identifying technical aliases in SELDI mass spectra of complex mixtures of proteins

PubMed Central

2013-01-01

Background Biomarker discovery datasets created using mass spectrum protein profiling of complex mixtures of proteins contain many peaks that represent the same protein with different charge states. Correlated variables such as these can confound the statistical analyses of proteomic data. Previously we developed an algorithm that clustered mass spectrum peaks that were biologically or technically correlated. Here we demonstrate an algorithm that clusters correlated technical aliases only. Results In this paper, we propose a preprocessing algorithm that can be used for grouping technical aliases in mass spectrometry protein profiling data. The stringency of the variance allowed for clustering is customizable, thereby affecting the number of peaks that are clustered. Subsequent analysis of the clusters, instead of individual peaks, helps reduce difficulties associated with technically-correlated data, and can aid more efficient biomarker identification. Conclusions This software can be used to pre-process and thereby decrease the complexity of protein profiling proteomics data, thus simplifying the subsequent analysis of biomarkers by decreasing the number of tests. The software is also a practical tool for identifying which features to investigate further by purification, identification and confirmation. PMID:24010718

Aftershock identification problem via the nearest-neighbor analysis for marked point processes

NASA Astrophysics Data System (ADS)

Gabrielov, A.; Zaliapin, I.; Wong, H.; Keilis-Borok, V.

2007-12-01

The centennial observations on the world seismicity have revealed a wide variety of clustering phenomena that unfold in the space-time-energy domain and provide most reliable information about the earthquake dynamics. However, there is neither a unifying theory nor a convenient statistical apparatus that would naturally account for the different types of seismic clustering. In this talk we present a theoretical framework for nearest-neighbor analysis of marked processes and obtain new results on hierarchical approach to studying seismic clustering introduced by Baiesi and Paczuski (2004). Recall that under this approach one defines an asymmetric distance D in space-time-energy domain such that the nearest-neighbor spanning graph with respect to D becomes a time- oriented tree. We demonstrate how this approach can be used to detect earthquake clustering. We apply our analysis to the observed seismicity of California and synthetic catalogs from ETAS model and show that the earthquake clustering part is statistically different from the homogeneous part. This finding may serve as a basis for an objective aftershock identification procedure.

OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes

PubMed Central

Li, Li; Stoeckert, Christian J.; Roos, David S.

2003-01-01

The identification of orthologous groups is useful for genome annotation, studies on gene/protein evolution, comparative genomics, and the identification of taxonomically restricted sequences. Methods successfully exploited for prokaryotic genome analysis have proved difficult to apply to eukaryotes, however, as larger genomes may contain multiple paralogous genes, and sequence information is often incomplete. OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs. This method performs similarly to the INPARANOID algorithm when applied to two genomes, but can be extended to cluster orthologs from multiple species. OrthoMCL clusters are coherent with groups identified by EGO, but improved recognition of “recent” paralogs permits overlapping EGO groups representing the same gene to be merged. Comparison with previously assigned EC annotations suggests a high degree of reliability, implying utility for automated eukaryotic genome annotation. OrthoMCL has been applied to the proteome data set from seven publicly available genomes (human, fly, worm, yeast, Arabidopsis, the malaria parasite Plasmodium falciparum, and Escherichia coli). A Web interface allows queries based on individual genes or user-defined phylogenetic patterns (http://www.cbil.upenn.edu/gene-family). Analysis of clusters incorporating P. falciparum genes identifies numerous enzymes that were incompletely annotated in first-pass annotation of the parasite genome. PMID:12952885

Diffuse gliomas with FGFR3-TACC3 fusion have characteristic histopathological and molecular features.

PubMed

Bielle, Franck; Di Stefano, Anna-Luisa; Meyronet, David; Picca, Alberto; Villa, Chiara; Bernier, Michèle; Schmitt, Yohann; Giry, Marine; Rousseau, Audrey; Figarella-Branger, Dominique; Maurage, Claude-Alain; Uro-Coste, Emmanuelle; Lasorella, Anna; Iavarone, Antonio; Sanson, Marc; Mokhtari, Karima

2017-10-04

Adult glioblastomas, IDH-wildtype represent a heterogeneous group of diseases. They are resistant to conventional treatment by concomitant radiochemotherapy and carry a dismal prognosis. The discovery of oncogenic gene fusions in these tumors has led to prospective targeted treatments, but identification of these rare alterations in practice is challenging. Here, we report a series of 30 adult diffuse gliomas with an in frame FGFR3-TACC3 oncogenic fusion (n = 27 WHO grade IV and n = 3 WHO grade II) as well as their histological and molecular features. We observed recurrent morphological features (monomorphous ovoid nuclei, nuclear palisading and thin parallel cytoplasmic processes, endocrinoid network of thin capillaries) associated with frequent microcalcifications and desmoplasia. We report a constant immunoreactivity for FGFR3, which is a valuable method for screening for the FGFR3-TACC3 fusion with 100% sensitivity and 92% specificity. We confirmed the associated molecular features (typical genetic alterations of glioblastoma, except the absence of EGFR amplification, and an increased frequency of CDK4 and MDM2 amplifications). FGFR3 immunopositivity is a valuable tool to identify gliomas that are likely to harbor the FGFR3-TACC3 fusion for inclusion in targeted therapeutic trials. © 2017 International Society of Neuropathology.

Reliability of Automated Biochemical Identification of Burkholderia pseudomallei Is Regionally Dependent

PubMed Central

Podin, Yuwana; Kaestli, Mirjam; McMahon, Nicole; Hennessy, Jann; Ngian, Hie Ung; Wong, Jin Shyan; Mohana, Anand; Wong, See Chang; William, Timothy; Mayo, Mark; Baird, Robert W.

2013-01-01

Misidentifications of Burkholderia pseudomallei as Burkholderia cepacia by Vitek 2 have occurred. Multidimensional scaling ordination of biochemical profiles of 217 Malaysian and Australian B. pseudomallei isolates found clustering of misidentified B. pseudomallei isolates from Malaysian Borneo. Specificity of B. pseudomallei identification in Vitek 2 and potentially other automated identification systems is regionally dependent. PMID:23784129

Reliability of automated biochemical identification of Burkholderia pseudomallei is regionally dependent.

PubMed

Podin, Yuwana; Kaestli, Mirjam; McMahon, Nicole; Hennessy, Jann; Ngian, Hie Ung; Wong, Jin Shyan; Mohana, Anand; Wong, See Chang; William, Timothy; Mayo, Mark; Baird, Robert W; Currie, Bart J

2013-09-01

Misidentifications of Burkholderia pseudomallei as Burkholderia cepacia by Vitek 2 have occurred. Multidimensional scaling ordination of biochemical profiles of 217 Malaysian and Australian B. pseudomallei isolates found clustering of misidentified B. pseudomallei isolates from Malaysian Borneo. Specificity of B. pseudomallei identification in Vitek 2 and potentially other automated identification systems is regionally dependent.

Identification of Youngsters with Emotional Disabilities.

ERIC Educational Resources Information Center

Smith, Carl R.

A clarification of the identification process for emotionally disturbed children is presented. Traditional definitions of emotional disturbance (ED) are explored and four behavioral clusters within traditional definitions are presented. The four are withdrawal from social interaction (autism), unsatisfactory interpersonal relationships,…

Serial Clustering of North Atlantic Cyclones and Wind Storms: A New Identification Base and Sensitivity to Intensity and Intra-Seasonal Variability

NASA Astrophysics Data System (ADS)

Leckebusch, G. C.; Kirchner-Bossi, N. O.; Befort, D. J.; Ulbrich, U.

2015-12-01

Time-clustered mid-latitude winter storms are responsible for a large portion of the overall windstorm-related damage in Europe. Thus, its study entails a high meteorological interest, while its outcome can result in a crucial utility for the (re)insurance industry. In addition to existing cyclone-based studies, here we use an event identification approach based on surface near wind speeds only, to investigate windstorm clustering and compare it to cyclone clustering. Specifically, cyclone and windstorm tracks are identified for winter 1979-2013 (Oct-Mar), to perform two sensitivity analyses on event-clustering in the North Atlantic using ERA-Interim Reanalysis. First, the link between clustering and cyclone intensity is analysed and compared to windstorms. Secondly, the sensitivity of clustering on intra-seasonal time scales is investigated, for both cyclones and windstorms. The wind-based approach reveals additional regions of clustering over Western Europe, which could be related to extreme damages, showing the added value of investigating wind field derived tracks in addition to that of cyclone tracks. Previous studies indicate a higher degree of clustering for stronger cyclones. However, our results show that this assumption is not always met. Although a positive relationship is confirmed for the clustering centre located over Iceland, clustering off the coast of the Iberian Peninsula behaves opposite. Even though this region shows the highest clustering, most of its signal is due to cyclones with intensities below the 70th percentile of the Laplacian of MSLP. Results on the sensitivity of clustering to the time of the winter season (Oct-Mar) show a temporal evolution of the clustering patterns, for both windstorms and cyclones. Compared to all cyclones, clustering of windstorms and strongest cyclones culminate around February, while all cyclone clustering peak in December to January.

3-D Ultrasound Vascularity Assessment for Breast Cancer Diagnosis

DTIC Science & Technology

2000-09-01

circumscribed mass with no microcalcifications. Final pathologic studies revealed carcinosarcoma (half ductal, half chondrosarcoma ). (a) Lateral-axial...Prostate 2 0 0 2 Angiosarcoma 0 0 2 2 Chondrosarcoma 0 1 0 1 Nasopharyngeal tumor 0 0 1 1 Hemangioendothelioma 0 0 1 1 Renal tumor 1 0 2 3 Baseline...patient with metastatic rendered copper deficient. Table 2 summarizes the clinical chondrosarcoma secondary to radiation treatment for breast course of

Painless thyroiditis associated to thyroid carcinoma: role of initial ultrasonography evaluation.

PubMed

Valentini, Raisa Bressan; Macedo, Bruno Mussoi de; Izquierdo, Rogério Friedrich; Meyer, Erika Laurini Souza

2016-04-01

Even though it is a rare event, most associations of thyroid carcinoma with subacute thyroiditis described in the literature are related to its granulomatous form (Quervain's thyroiditis). We present a patient with subacute lymphocytic thyroiditis (painless thyroiditis) and papillary thyroid cancer that was first suspected in an initial ultrasound evaluation. A 30-year old female patient who was referred to the emergency room due to hyperthyroidism symptoms was diagnosed with painless thyroiditis established by physical examination and laboratory findings. With the presence of a palpable painless thyroid nodule an ultrasound was prescribed and the images revealed a suspicious thyroid nodule, microcalcification focus in the heterogeneous thyroid parenquima and cervical lymphadenopathy. Fine needle aspiration biopsy was taken from this nodule; cytology was assessed for compatibility with papillary thyroid carcinoma. Postsurgical pathology evaluation showed a multicentric papillary carcinoma and lymphocytic infiltration. Subacute thyroiditis, regardless of type, may produce transitory ultrasound changes that obscure the coexistence of papillary carcinoma. Due to this, initial thyroid ultrasound evaluation should be delayed until clinical recovery. We recommended a thyroid ultrasound exam for initial evaluation of painless thyroiditis, particularly in patients with palpable thyroid nodule. Further cytological examination is recommended in cases presenting with suspect thyroid nodule and/or non-nodular hypoechoic (> 1 cm) or heterogeneous areas with microcalcification focus.

Novel insights in ultrasound evaluation of thyroid gland in children with papillary thyroid carcinoma.

PubMed

Janus, Dominika; Wojcik, Malgorzata; Kalicka-Kasperczyk, Anna; Drabik, Grazyna; Wyrobek, Lukasz; Wedrychowicz, Anna; Starzyk, Jerzy B

2017-10-01

The coincidence of autoimmune thyroiditis (AIT) in patients with papillary thyroid carcinoma (PTC) is ranging between 10 and 58% in the general population. In the present study retrospective ultrasound, clinical and autoimmune assessment of 24 patients diagnosed with papillary thyroid carcinoma between 2000-2016 was performed. The coexistence of PTC and AIT was found in 50% of patients with PTC. Patients were divided into two groups. PTC AIT (+) group involved 12 children at the mean age 14.9 years (range 11-20 years, 9 girls) and PTC AIT (-) 12 children at the mean age 12.9 years (range 7-18 years, 5 girls). Papillary thyroid microcarcinoma (PTMC) was diagnosed in 6 patients (in 5 with AIT). US characteristics of PTC was heterogenous: hypoechogenic with/without increased vascularisation, normoechogenic with halo, with/without microcalcifications. In 70% PTC AIT (+) and in all PTC AIT (-) patients ultrasound analysis revealed that the thyroid tissue of the whole gland was normoechogenic. Local metastases in lymph nodes were found in 40% of PTMC AIT (+). Lack of increased vascularization and microcalcifications and presence of``halo`in the nodule does not exclude malignancy. Due to the presence of lymph node involvement in PTMC in all children with PTC total thyroidectomy should be performed with lymph nodes verification.

Correlating the ground truth of mammographic histology with the success or failure of imaging.

PubMed

Tot, Tibor

2005-02-01

Detailed and systematic mammographic-pathologic correlation is essential for evaluation of the advantages and disadvantages of mammography as an imaging method as well as for establishing the role of additional methods or alternatives. Two- and three-dimensional large section histopathology represents an ideal tool for this correlation. This kind of interdisciplinary approach ("mammographic histology") is slowly but irrevocably becoming accepted as the new golden standard in diagnosing breast abnormalities. In this review, upon summarizing the theoretical background and our practical experience in routine diagnostic use of these advantageous techniques, we report on the accuracy of the preoperative radiological diagnosis. As compared to the final diagnostic outcome, stellate lesions on the mammogram and microcalcifications of casting type indicate malignancy with very high accuracy while predicting malignancy in cases of powdery and crushed stone type microcalcifications is problematic. The extent of the disease is regularly underestimated on the mammogram by the radiologist. Combining different radiological signs, and comparing repeated static images taken in regular intervals in screening or postoperative follow-up, the mammographer may type and grade the lesions properly in a considerable number of cases. Regular mammographic-pathologic correlation may increase the specificity and sensitivity of mammographic diagnosis. This correlation is essential for establishing the proper pre- and postoperative histological diagnosis, too.

Cancer Transcriptome Dataset Analysis: Comparing Methods of Pathway and Gene Regulatory Network-Based Cluster Identification.

PubMed

Nam, Seungyoon

2017-04-01

Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets. Network clustering is useful, but depends on the network topology in and of itself. Notably, the performance of different network-generating tools for network cluster (NC) identification has been little investigated to date. Hence, using gastric cancer (GC) transcriptomic datasets, we compared two algorithms for generating pathway versus gene regulatory network-based NCs, showing that the pathway-based approach better agrees with a reference set of cancer-functional contexts. Finally, by applying pathway-based NC identification to GC transcriptome datasets, we describe cancer NCs that associate with candidate therapeutic targets and biomarkers in GC. These observations collectively inform future research on cancer transcriptomics, drug discovery, and rational development of new analysis tools for optimal harnessing of omics data.

Religious and national group identification in adolescence: a study among three religious groups in Mauritius.

PubMed

Ng Tseung-Wong, Caroline; Verkuyten, Maykel

2013-01-01

Religious group identification is an important but understudied social identity. The present study investigates religious group identification among adolescents of different faiths (Hindu, Muslim, Christian) living in multicultural Mauritius. It further explores how religious and national group identities come together among religious majority and minority adolescents. For three age groups (11 to 19 years, N = 2152) we examined the strength of adolescents' religious and national group identification, the associations between these two identities, and the relationships to global self-esteem. Across age and religious group, participants reported stronger identification with their religious group than with the nation. Identification with both categories declined with age, with the exception of Muslims, whose strong religious identification was found across adolescence. The association between religious and national identification was positive, albeit stronger for the majority group of Hindus and for early adolescents. We examined the manner in which religious and national identities come together using a direct self-identification measure and by combining the separate continuous measures of identification. Four distinct clusters of identification (predominant religious identifiers, dual identifiers, neutrals, and separate individuals) that were differently associated with global self-esteem were found. Dual identifiers reported the highest level of global self-esteem. The clusters of identification did not fully correspond to the findings for the direct self-identification measure. The results are discussed in terms of the meaning of dual identity and the positive manner in which adolescents can manage their multiple identities while taking into account the ideological framework in which those identities are played out.

Cluster Analysis of the Yale Global Tic Severity Scale (YGTSS): Symptom Dimensions and Clinical Correlates in an Outpatient Youth Sample

ERIC Educational Resources Information Center

Kircanski, Katharina; Woods, Douglas W.; Chang, Susanna W.; Ricketts, Emily J.; Piacentini, John C.

2010-01-01

Tic disorders are heterogeneous, with symptoms varying widely both within and across patients. Exploration of symptom clusters may aid in the identification of symptom dimensions of empirical and treatment import. This article presents the results of two studies investigating tic symptom clusters using a sample of 99 youth (M age = 10.7, 81% male,…

Identification of lithofacies using Kohonen self-organizing maps

USGS Publications Warehouse

Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.

2002-01-01

Lithofacies identification is a primary task in reservoir characterization. Traditional techniques of lithofacies identification from core data are costly, and it is difficult to extrapolate to non-cored wells. We present a low-cost automated technique using Kohonen self-organizing maps (SOMs) to identify systematically and objectively lithofacies from well log data. SOMs are unsupervised artificial neural networks that map the input space into clusters in a topological form whose organization is related to trends in the input data. A case study used five wells located in Appleton Field, Escambia County, Alabama (Smackover Formation, limestone and dolomite, Oxfordian, Jurassic). A five-input, one-dimensional output approach is employed, assuming the lithofacies are in ascending/descending order with respect to paleoenvironmental energy levels. To consider the possible appearance of new logfacies not seen in training mode, which may potentially appear in test wells, the maximum number of outputs is set to 20 instead of four, the designated number of lithosfacies in the study area. This study found eleven major clusters. The clusters were compared to depositional lithofacies identified by manual core examination. The clusters were ordered by the SOM in a pattern consistent with environmental gradients inferred from core examination: bind/boundstone, grainstone, packstone, and wackestone. This new approach predicted lithofacies identity from well log data with 78.8% accuracy which is more accurate than using a backpropagation neural network (57.3%). The clusters produced by the SOM are ordered with respect to paleoenvironmental energy levels. This energy-related clustering provides geologists and petroleum engineers with valuable geologic information about the logfacies and their interrelationships. This advantage is not obtained in backpropagation neural networks and adaptive resonance theory neural networks. ?? 2002 Elsevier Science Ltd. All rights reserved.

Broad spectrum antibiotic compounds and use thereof

DOEpatents

Koglin, Alexander; Strieker, Matthias

2016-07-05

The discovery of a non-ribosomal peptide synthetase (NRPS) gene cluster in the genome of Clostridium thermocellum that produces a secondary metabolite that is assembled outside of the host membrane is described. Also described is the identification of homologous NRPS gene clusters from several additional microorganisms. The secondary metabolites produced by the NRPS gene clusters exhibit broad spectrum antibiotic activity. Thus, antibiotic compounds produced by the NRPS gene clusters, and analogs thereof, their use for inhibiting bacterial growth, and methods of making the antibiotic compounds are described.

[The occurrence of Echinococcus multilocularis in red foxes in lower Saxony: identification of a high risk area by spatial epidemiological cluster analysis].

PubMed

Berke, Olaf; von Keyserlingk, Michael; Broll, Susanne; Kreienbrock, Lothar

2002-01-01

There is considerable interest in the spatial distribution of Echinococcus multilocularis in red foxes (Vulpes vulpes L.), because this parasite causes the zoonoses of alveolar echinococcosis which is potentially of high fatality rate. High risk areas are known from France, Switzerland and the Swabian Alb in Germany for a long time. In this work, the spatial scan statistic is introduced as an instrument for identification and localisation of high risk areas, so called disease clusters in spatial epidemiology. The use of the spatial scan statistic along with data about the distribution of the parasite in 5365 red foxes in Lower Saxony, that were collected during 1991 to 1997, led to the identification of another high risk area. The relative risk for this disease cluster is approximated by RR = 5.03 (CI0.95(RR) = [4.27; 6.58]) for the period of 1991 to 1994 and by RR = 4.45 (CI0.95(RR) = [3.53; 5.59]) for the period of 1994 to 1997, respectively.

Estimating sensitivity and specificity for technology assessment based on observer studies.

PubMed

Nishikawa, Robert M; Pesce, Lorenzo L

2013-07-01

The goal of this study was to determine the accuracy and precision of using scores from a receiver operating characteristic rating scale to estimate sensitivity and specificity. We used data collected in a previous study that measured the improvements in radiologists' ability to classify mammographic microcalcification clusters as benign or malignant with and without the use of a computer-aided diagnosis scheme. Sensitivity and specificity were estimated from the rating data from a question that directly asked the radiologists their biopsy recommendations, which was used as the "truth," because it is the actual recall decision, thus it is their subjective truth. By thresholding the rating data, sensitivity and specificity were estimated for different threshold values. Because of interreader and intrareader variability, estimated sensitivity and specificity values for individual readers could be as much as 100% in error when using rating data compared to using the biopsy recommendation data. When pooled together, the estimates using thresholding the rating data were in good agreement with sensitivity and specificity estimated from the recommendation data. However, the statistical power of the rating data estimates was lower. By simply asking the observer his or her explicit recommendation (eg, biopsy or no biopsy), sensitivity and specificity can be measured directly, giving a more accurate description of empirical variability and the power of the study can be maximized. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.

Identification of the first diphenyl ether gene cluster for pestheic acid biosynthesis in plant endophyte Pestalotiopsis fici.

PubMed

Xu, Xinxin; Liu, Ling; Zhang, Fan; Wang, Wenzhao; Li, Jinyang; Guo, Liangdong; Che, Yongsheng; Liu, Gang

2014-01-24

The diphenyl ether pestheic acid was isolated from the endophytic fungus Pestalotiopsis fici, which is proposed to be the biosynthetic precursor of the unique chloropupukeananes. The pestheic acid biosynthetic gene (pta) cluster was identified in the fungus through genome scanning. Sequence analysis revealed that this gene cluster encodes a nonreducing polyketide synthase, a number of modification enzymes, and three regulators. Gene disruption and intermediate analysis demonstrated that the biosynthesis proceeded through formation of the polyketide backbone, cyclization of a polyketo acid to a benzophenone, chlorination, and formation of the diphenyl ether skeleton through oxidation and hydrolyzation. A dihydrogeodin oxidase gene, ptaE, was essential for diphenyl ether formation, and ptaM encoded a flavin-dependent halogenase catalyzing chlorination in the biosynthesis. Identification of the pta cluster laid the foundation to decipher the genetic and biochemical mechanisms involved in the pathway. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

NASA Technical Reports Server (NTRS)

Mitra, Sunanda; Pemmaraju, Surya

1992-01-01

Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

Cluster Analysis of Longidorus Species (Nematoda: Longidoridae), a New Approach in Species Identification

PubMed Central

Ye, Weimin; Robbins, R. T.

2004-01-01

Hierarchical cluster analysis based on female morphometric character means including body length, distance from vulva opening to anterior end, head width, odontostyle length, esophagus length, body width, tail length, and tail width were used to examine the morphometric relationships and create dendrograms for (i) 62 populations belonging to 9 Longidorus species from Arkansas, (ii) 137 published Longidorus species, and (iii) 137 published Longidorus species plus 86 populations of 16 Longidorus species from Arkansas and various other locations by using JMP 4.02 software (SAS Institute, Cary, NC). Cluster analysis dendograms visually illustrated the grouping and morphometric relationships of the species and populations. It provided a computerized statistical approach to assist by helping to identify and distinguish species, by indicating morphometric relationships among species, and by assisting with new species diagnosis. The preliminary species identification can be accomplished by running cluster analysis for unknown species together with the data matrix of known published Longidorus species. PMID:19262809

Identification and manipulation of the pleuromutilin gene cluster from Clitopilus passeckerianus for increased rapid antibiotic production

NASA Astrophysics Data System (ADS)

Bailey, Andy M.; Alberti, Fabrizio; Kilaru, Sreedhar; Collins, Catherine M.; de Mattos-Shipley, Kate; Hartley, Amanda J.; Hayes, Patrick; Griffin, Alison; Lazarus, Colin M.; Cox, Russell J.; Willis, Christine L.; O'Dwyer, Karen; Spence, David W.; Foster, Gary D.

2016-05-01

Semi-synthetic derivatives of the tricyclic diterpene antibiotic pleuromutilin from the basidiomycete Clitopilus passeckerianus are important in combatting bacterial infections in human and veterinary medicine. These compounds belong to the only new class of antibiotics for human applications, with novel mode of action and lack of cross-resistance, representing a class with great potential. Basidiomycete fungi, being dikaryotic, are not generally amenable to strain improvement. We report identification of the seven-gene pleuromutilin gene cluster and verify that using various targeted approaches aimed at increasing antibiotic production in C. passeckerianus, no improvement in yield was achieved. The seven-gene pleuromutilin cluster was reconstructed within Aspergillus oryzae giving production of pleuromutilin in an ascomycete, with a significant increase (2106%) in production. This is the first gene cluster from a basidiomycete to be successfully expressed in an ascomycete, and paves the way for the exploitation of a metabolically rich but traditionally overlooked group of fungi.

Variability in research ethics review of cluster randomized trials: a scenario-based survey in three countries

PubMed Central

2014-01-01

Background Cluster randomized trials (CRTs) present unique ethical challenges. In the absence of a uniform standard for their ethical design and conduct, problems such as variability in procedures and requirements by different research ethics committees will persist. We aimed to assess the need for ethics guidelines for CRTs among research ethics chairs internationally, investigate variability in procedures for research ethics review of CRTs within and among countries, and elicit research ethics chairs’ perspectives on specific ethical issues in CRTs, including the identification of research subjects. The proper identification of research subjects is a necessary requirement in the research ethics review process, to help ensure, on the one hand, that subjects are protected from harm and exploitation, and on the other, that reviews of CRTs are completed efficiently. Methods A web-based survey with closed- and open-ended questions was administered to research ethics chairs in Canada, the United States, and the United Kingdom. The survey presented three scenarios of CRTs involving cluster-level, professional-level, and individual-level interventions. For each scenario, a series of questions was posed with respect to the type of review required (full, expedited, or no review) and the identification of research subjects at cluster and individual levels. Results A total of 189 (35%) of 542 chairs responded. Overall, 144 (84%, 95% CI 79 to 90%) agreed or strongly agreed that there is a need for ethics guidelines for CRTs and 158 (92%, 95% CI 88 to 96%) agreed or strongly agreed that research ethics committees could be better informed about distinct ethical issues surrounding CRTs. There was considerable variability among research ethics chairs with respect to the type of review required, as well as the identification of research subjects. The cluster-cluster and professional-cluster scenarios produced the most disagreement. Conclusions Research ethics committees identified a clear need for ethics guidelines for CRTs and education about distinct ethical issues in CRTs. There is disagreement among committees, even within the same countries, with respect to key questions in the ethics review of CRTs. This disagreement reflects variability of opinion and practices pointing toward possible gaps in knowledge, and supports the need for explicit guidelines for the ethical conduct and review of CRTs. PMID:24495542

Morphology delimits more species than molecular genetic clusters of invasive Pilosella

USDA-ARS?s Scientific Manuscript database

Premise of the study: Reliable identifications of invasive species are essential for effective management. Several species of Pilosella (syn. Hieracium, Asteraceae) hawkweeds invade North America, where unreliable identification hinders their control. Here we ask (i) do morphological traits dependab...

Chaos theory perspective for industry clusters development

NASA Astrophysics Data System (ADS)

Yu, Haiying; Jiang, Minghui; Li, Chengzhang

2016-03-01

Industry clusters have outperformed in economic development in most developing countries. The contributions of industrial clusters have been recognized as promotion of regional business and the alleviation of economic and social costs. It is no doubt globalization is rendering clusters in accelerating the competitiveness of economic activities. In accordance, many ideas and concepts involve in illustrating evolution tendency, stimulating the clusters development, meanwhile, avoiding industrial clusters recession. The term chaos theory is introduced to explain inherent relationship of features within industry clusters. A preferred life cycle approach is proposed for industrial cluster recessive theory analysis. Lyapunov exponents and Wolf model are presented for chaotic identification and examination. A case study of Tianjin, China has verified the model effectiveness. The investigations indicate that the approaches outperform in explaining chaos properties in industrial clusters, which demonstrates industrial clusters evolution, solves empirical issues and generates corresponding strategies.

Structure-sequence based analysis for identification of conserved regions in proteins

DOEpatents

Zemla, Adam T; Zhou, Carol E; Lam, Marisa W; Smith, Jason R; Pardes, Elizabeth

2013-05-28

Disclosed are computational methods, and associated hardware and software products for scoring conservation in a protein structure based on a computationally identified family or cluster of protein structures. A method of computationally identifying a family or cluster of protein structures in also disclosed herein.

Identification and functional analysis of the aspergillic acid gene cluster in Aspergillus flavus

USDA-ARS?s Scientific Manuscript database

Aspergillus flavus can colonize important food staples and produces aflatoxins, toxic and carcinogenic secondary metabolites. In silico analysis of the A. flavus genome revealed 56 gene clusters encoding for secondary metabolites. How these many of these metabolites affect fungal development, surviv...

Evaluation of protein spectra cluster analysis for Streptococcus spp. identification from various swine clinical samples.

PubMed

Matajira, Carlos E C; Moreno, Luisa Z; Gomes, Vasco T M; Silva, Ana Paula S; Mesquita, Renan E; Doto, Daniela S; Calderaro, Franco F; de Souza, Fernando N; Christ, Ana Paula G; Sato, Maria Inês Z; Moreno, Andrea M

2017-03-01

Traditional microbiological methods enable genus-level identification of Streptococcus spp. isolates. However, as the species of this genus show broad phenotypic variation, species-level identification or even differentiation within the genus is difficult. Herein we report the evaluation of protein spectra cluster analysis for the identification of Streptococcus species associated with disease in swine by means of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). A total of 250 S. suis-like isolates obtained from pigs with clinical signs of encephalitis, arthritis, pneumonia, metritis, and urinary or septicemic infection were studied. The isolates came from pigs in different Brazilian states from 2001 to 2014. The MALDI-TOF MS analysis identified 86% (215 of 250) as S. suis and 14% (35 of 250) as S. alactolyticus, S. dysgalactiae, S. gallinaceus, S. gallolyticus, S. gordonii, S. henryi, S. hyointestinalis, S. hyovaginalis, S. mitis, S. oralis, S. pluranimalium, and S. sanguinis. The MALDI-TOF MS identification was confirmed in 99.2% of the isolates by 16S rDNA sequencing, with MALDI-TOF MS misidentifying 2 S. pluranimalium as S. hyovaginalis. Isolates were also tested by a biochemical automated system that correctly identified all isolates of 8 of the 10 species in the database. Neither the isolates of the 3 species not in the database ( S. gallinaceus, S. henryi, and S. hyovaginalis) nor the isolates of 2 species that were in the database ( S. oralis and S. pluranimalium) could be identified. The topology of the protein spectra cluster analysis appears to sustain the species phylogenetic similarities, further supporting identification by MALDI-TOF MS examination as a rapid and accurate alternative to 16S rDNA sequencing.

Computational identification of developmental enhancers:conservation and function of transcription factor binding-site clustersin drosophila melanogaster and drosophila psedoobscura

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

Berman, Benjamin P.; Pfeiffer, Barret D.; Laverty, Todd R.

2004-08-06

The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene, and assayedmore » embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. Measuring conservation of sequence features closely linked to function--such as binding-site clustering--makes better use of comparative sequence data than commonly used methods that examine only sequence identity.« less

1 H-NMR with Multivariate Analysis for Automobile Lubricant Comparison.

PubMed

Kim, Siwon; Yoon, Dahye; Lee, Dong-Kye; Yoon, Changshin; Kim, Suhkmann

2017-07-01

Identification of suspected automobile-related lubricants could provide valuable information in forensic cases. We examined that automobile lubricants might exhibit the chemometric characteristics to their individual usages. To compare the degree of clustering in the plots, we co-plotted general industrial oils that were highly dissimilar with automobile lubricants in additive compositions. 1 H-NMR spectroscopy was used with multivariate statistics as a tool for grouping, clustering, and identification of automobile lubricants in laboratory conditions. We analyzed automobile lubricants including automobile engine oils, automobile transmission oils, automobile gear oils, and motorcycle oils. In contrast to the general industrial oils, automobile lubricants showed relatively high tendencies of clustering to their usages. Our pilot study demonstrated that the comparison of known and questioned samples to their usages might be possible in forensic fields. © 2017 American Academy of Forensic Sciences.

Exploring Relations Between BCG & Cluster Properties in the SPectroscopic IDentification of eROSITA Sources Survey from 0.05 < z < 0.3

NASA Astrophysics Data System (ADS)

Furnell, Kate E.; Collins, Chris A.; Kelvin, Lee S.; Clerc, Nicolas; Baldry, Ivan K.; Finoguenov, Alexis; Erfanianfar, Ghazaleh; Comparat, Johan; Schneider, Donald P.

2018-04-01

We present a sample of 329 low to intermediate redshift (0.05 < z < 0.3) brightest cluster galaxies (BCGs) in X-ray selected clusters from the SPectroscopic IDentification of eRosita Sources (SPIDERS) survey, a spectroscopic survey within Sloan Digital Sky Survey-IV (SDSS-IV). We define our BCGs by simultaneous consideration of legacy X-ray data from ROSAT, maximum likelihood outputs from an optical cluster-finder algorithm and visual inspection. Using SDSS imaging data, we fit Sérsic profiles to our BCGs in three bands (g, r, i) with SIGMA, a GALFIT-based software wrapper. We examine the reliability of our fits by running our pipeline on ˜104 psf-convolved model profiles injected into 8 random cluster fields; we then use the results of this analysis to create a robust subsample of 198 BCGs. We outline three cluster properties of interest: overall cluster X-ray luminosity (LX), cluster richness as estimated by REDMAPPER (λ) and cluster halo mass (M200), which is estimated via velocity dispersion. In general, there are significant correlations with BCG stellar mass between all three environmental properties, but no significant trends arise with either Sérsic index or effective radius. There is no major environmental dependence on the strength of the relation between effective radius and BCG stellar mass. Stellar mass therefore arises as the most important factor governing BCG morphology. Our results indicate that our sample consists of a large number of relaxed, mature clusters containing broadly homogeneous BCGs up to z ˜ 0.3, suggesting that there is little evidence for much ongoing structural evolution for BCGs in these systems.

Secure and Fair Cluster Head Selection Protocol for Enhancing Security in Mobile Ad Hoc Networks

PubMed Central

Paramasivan, B.; Kaliappan, M.

2014-01-01

Mobile ad hoc networks (MANETs) are wireless networks consisting of number of autonomous mobile devices temporarily interconnected into a network by wireless media. MANETs become one of the most prevalent areas of research in the recent years. Resource limitations, energy efficiency, scalability, and security are the great challenging issues in MANETs. Due to its deployment nature, MANETs are more vulnerable to malicious attack. The secure routing protocols perform very basic security related functions which are not sufficient to protect the network. In this paper, a secure and fair cluster head selection protocol (SFCP) is proposed which integrates security factors into the clustering approach for achieving attacker identification and classification. Byzantine agreement based cooperative technique is used for attacker identification and classification to make the network more attack resistant. SFCP used to solve this issue by making the nodes that are totally surrounded by malicious neighbors adjust dynamically their belief and disbelief thresholds. The proposed protocol selects the secure and energy efficient cluster head which acts as a local detector without imposing overhead to the clustering performance. SFCP is simulated in network simulator 2 and compared with two protocols including AODV and CBRP. PMID:25143986

Secure and fair cluster head selection protocol for enhancing security in mobile ad hoc networks.

PubMed

Paramasivan, B; Kaliappan, M

2014-01-01

Mobile ad hoc networks (MANETs) are wireless networks consisting of number of autonomous mobile devices temporarily interconnected into a network by wireless media. MANETs become one of the most prevalent areas of research in the recent years. Resource limitations, energy efficiency, scalability, and security are the great challenging issues in MANETs. Due to its deployment nature, MANETs are more vulnerable to malicious attack. The secure routing protocols perform very basic security related functions which are not sufficient to protect the network. In this paper, a secure and fair cluster head selection protocol (SFCP) is proposed which integrates security factors into the clustering approach for achieving attacker identification and classification. Byzantine agreement based cooperative technique is used for attacker identification and classification to make the network more attack resistant. SFCP used to solve this issue by making the nodes that are totally surrounded by malicious neighbors adjust dynamically their belief and disbelief thresholds. The proposed protocol selects the secure and energy efficient cluster head which acts as a local detector without imposing overhead to the clustering performance. SFCP is simulated in network simulator 2 and compared with two protocols including AODV and CBRP.

Identification of a Pantoea Biosynthetic Cluster That Directs the Synthesis of an Antimicrobial Natural Product

PubMed Central

Walterson, Alyssa M.; Smith, Derek D. N.; Stavrinides, John

2014-01-01

Fire Blight is a destructive disease of apple and pear caused by the enteric bacterial pathogen, Erwinia amylovora. E. amylovora initiates infection by colonizing the stigmata of apple and pear trees, and entering the plants through natural openings. Epiphytic populations of the related enteric bacterium, Pantoea, reduce the incidence of disease through competition and antibiotic production. In this study, we identify an antibiotic from Pantoea ananatis BRT175, which is effective against E. amylovora and select species of Pantoea. We used transposon mutagenesis to create a mutant library, screened approximately 5,000 mutants for loss of antibiotic production, and recovered 29 mutants. Sequencing of the transposon insertion sites of these mutants revealed multiple independent disruptions of an 8.2 kb cluster consisting of seven genes, which appear to be coregulated. An analysis of the distribution of this cluster revealed that it was not present in any other of our 115 Pantoea isolates, or in any of the fully sequenced Pantoea genomes, and is most closely related to antibiotic biosynthetic clusters found in three different species of Pseudomonas. This identification of this biosynthetic cluster highlights the diversity of natural products produced by Pantoea. PMID:24796857

Leveraging long sequencing reads to investigate R-gene clustering and variation in sugar beet

USDA-ARS?s Scientific Manuscript database

Host-pathogen interactions are of prime importance to modern agriculture. Plants utilize various types of resistance genes to mitigate pathogen damage. Identification of the specific gene responsible for a specific resistance can be difficult due to duplication and clustering within R-gene families....

Accounting Cluster Demonstration Program at Aloha High School. Final Report.

ERIC Educational Resources Information Center

Beaverton School District 48, OR.

A model high school accounting cluster program was planned, developed, implemented, and evaluated in the Beaverton, Oregon, school district. The curriculum was developed with the help of representatives from the accounting occupations in the Portland metropolitan area. Through management interviews, identification of on-the job requirements, and…

Bruker biotyper matrix-assisted laser desorption ionization-time of flight mass spectrometry system for identification of Nocardia, Rhodococcus, Kocuria, Gordonia, Tsukamurella, and Listeria species.

PubMed

Hsueh, Po-Ren; Lee, Tai-Fen; Du, Shin-Hei; Teng, Shih-Hua; Liao, Chun-Hsing; Sheng, Wang-Hui; Teng, Lee-Jene

2014-07-01

We evaluated whether the Bruker Biotyper matrix-associated laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) system provides accurate species-level identifications of 147 isolates of aerobically growing Gram-positive rods (GPRs). The bacterial isolates included Nocardia (n = 74), Listeria (n = 39), Kocuria (n = 15), Rhodococcus (n = 10), Gordonia (n = 7), and Tsukamurella (n = 2) species, which had all been identified by conventional methods, molecular methods, or both. In total, 89.7% of Listeria monocytogenes, 80% of Rhodococcus species, 26.7% of Kocuria species, and 14.9% of Nocardia species (n = 11, all N. nova and N. otitidiscaviarum) were correctly identified to the species level (score values, ≥ 2.0). A clustering analysis of spectra generated by the Bruker Biotyper identified six clusters of Nocardia species, i.e., cluster 1 (N. cyriacigeorgica), cluster 2 (N. brasiliensis), cluster 3 (N. farcinica), cluster 4 (N. puris), cluster 5 (N. asiatica), and cluster 6 (N. beijingensis), based on the six peaks generated by ClinProTools with the genetic algorithm, i.e., m/z 2,774.477 (cluster 1), m/z 5,389.792 (cluster 2), m/z 6,505.720 (cluster 3), m/z 5,428.795 (cluster 4), m/z 6,525.326 (cluster 5), and m/z 16,085.216 (cluster 6). Two clusters of L. monocytogenes spectra were also found according to the five peaks, i.e., m/z 5,594.85, m/z 6,184.39, and m/z 11,187.31, for cluster 1 (serotype 1/2a) and m/z 5,601.21 and m/z 11,199.33 for cluster 2 (serotypes 1/2b and 4b). The Bruker Biotyper system was unable to accurately identify Nocardia (except for N. nova and N. otitidiscaviarum), Tsukamurella, or Gordonia species. Continuous expansion of the MALDI-TOF MS databases to include more GPRs is necessary. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

An improved K-means clustering algorithm in agricultural image segmentation

NASA Astrophysics Data System (ADS)

Cheng, Huifeng; Peng, Hui; Liu, Shanmei

Image segmentation is the first important step to image analysis and image processing. In this paper, according to color crops image characteristics, we firstly transform the color space of image from RGB to HIS, and then select proper initial clustering center and cluster number in application of mean-variance approach and rough set theory followed by clustering calculation in such a way as to automatically segment color component rapidly and extract target objects from background accurately, which provides a reliable basis for identification, analysis, follow-up calculation and process of crops images. Experimental results demonstrate that improved k-means clustering algorithm is able to reduce the computation amounts and enhance precision and accuracy of clustering.

Identification and classification of hubs in brain networks.

PubMed

Sporns, Olaf; Honey, Christopher J; Kötter, Rolf

2007-10-17

Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles.

Study on computer-aided diagnosis of hepatic MR imaging and mammography

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

Zhang Xuejun

2005-04-01

It is well known that the liver is an organ easily attacked by diseases. The purpose of this study is to develop a computer-aided diagnosis (CAD) scheme for helping radiologists to differentiate hepatic diseases more efficiently. Our software named LIVERANN integrated the magnetic resonance (MR) imaging findings with different pulse sequences to classify the five categories of hepatic diseases by using the artificial neural network (ANN) method. The intensity and homogeneity within the region of interest (ROI) delineated by a radiologist were automatically calculated to obtain numerical data by the program for input signals to the ANN. Outputs were themore » five pathological categories of hepatic diseases (hepatic cyst, hepatocellular carcinoma, dysplasia in cirrhosis, cavernous hemangioma, and metastasis). The experiment demonstrated a testing accuracy of 93% from 80 patients. In order to differentiate the cirrhosis from normal liver, the volume ratio of left to whole (LTW) was proposed to quantify the degree of cirrhosis by three-dimensional (3D) volume analysis. The liver region was firstly extracted from computed tomography (CT) or MR slices based on edge detection algorithms, and then separated into left lobe and right lobe by the hepatic umbilical fissure. The volume ratio of these two parts showed that the LTW ratio in the liver was significantly improved in the differentiation performance, with (25.6%{+-}4.3%) in cirrhosis versus the normal liver (16.4%{+-}5.4%). In addition, the application of the ANN method for detecting clustered microcalcifications in masses on mammograms was described here as well. A new structural ANN, so-called a shift-invariant artificial neural network (SIANN), was integrated with our triple-ring filter (TRF) method in our CAD system. As the result, the sensitivity of detecting clusters was improved from 90% by our previous TRF method to 95% by using both SIANN and TRF.« less

Citrullinemia type I, classical variant. Identification of ASS-p~G390R (c.1168G>A) mutation in families of a limited geographic area of Argentina: a possible population cluster.

PubMed

Laróvere, Laura E; Angaroni, Celia J; Antonozzi, Sandra L; Bezard, Miriam B; Shimohama, Mariko; de Kremer, Raquel Dodelson

2009-07-01

Citrullinemia type I (CTLN1) is an urea cycle defect caused by mutations in the argininosuccinate synthetase gene. We report the first identification in Argentina of patients with CTLN1 in a limited geographic area. Molecular analysis in patient/relatives included PCR, sequencing and restriction enzyme assay. The studied families showed the same mutation: ASS~p.G390R, associated with the early-onset/severe phenotype. We postulate a possible population cluster. A program to know the carrier frequency in that population is in progress.

Identification and DUS Testing of Rice Varieties through Microsatellite Markers.

PubMed

Pourabed, Ehsan; Jazayeri Noushabadi, Mohammad Reza; Jamali, Seyed Hossein; Moheb Alipour, Naser; Zareyan, Abbas; Sadeghi, Leila

2015-01-01

Identification and registration of new rice varieties are very important to be free from environmental effects and using molecular markers that are more reliable. The objectives of this study were, first, the identification and distinction of 40 rice varieties consisting of local varieties of Iran, improved varieties, and IRRI varieties using PIC, and discriminating power, second, cluster analysis based on Dice similarity coefficient and UPGMA algorithm, and, third, determining the ability of microsatellite markers to separate varieties utilizing the best combination of markers. For this research, 12 microsatellite markers were used. In total, 83 polymorphic alleles (6.91 alleles per locus) were found. In addition, the variation of PIC was calculated from 0.52 to 0.9. The results of cluster analysis showed the complete discrimination of varieties from each other except for IR58025A and IR58025B. Moreover, cluster analysis could detect the most of the improved varieties from local varieties. Based on the best combination of markers analysis, five pair primers together have shown the same results of all markers for detection among all varieties. Considering the results of this research, we can propose that microsatellite markers can be used as a complementary tool for morphological characteristics in DUS tests.

Identification of Clusters of Foot Pain Location in a Community Sample.

PubMed

Gill, Tiffany K; Menz, Hylton B; Landorf, Karl B; Arnold, John B; Taylor, Anne W; Hill, Catherine L

2017-12-01

To identify foot pain clusters according to pain location in a community-based sample of the general population. This study analyzed data from the North West Adelaide Health Study. Data were obtained between 2004 and 2006, using computer-assisted telephone interviewing, clinical assessment, and self-completed questionnaire. The location of foot pain was assessed using a diagram during the clinical assessment. Hierarchical cluster analysis was undertaken to identify foot pain location clusters, which were then compared in relation to demographics, comorbidities, and podiatry services utilization. There were 558 participants with foot pain (mean age 54.4 years, 57.5% female). Five clusters were identified: 1 with predominantly arch and ball pain (26.8%), 1 with rearfoot pain (20.9%), 1 with heel pain (13.3%), and 2 with predominantly forefoot, toe, and nail pain (28.3% and 10.7%). Each cluster was distinct in age, sex, and comorbidity profile. Of the two clusters with predominantly forefoot, toe, and nail pain, one of them had a higher proportion of men and those classified as obese, had diabetes mellitus, and used podiatry services (30%), while the other was comprised of a higher proportion of women who were overweight and reported less use of podiatry services (17.5%). Five clusters of foot pain according to pain location were identified, all with distinct age, sex, and comorbidity profiles. These findings may assist in the identification of individuals at risk for developing foot pain and in the development of targeted preventive strategies and treatments. © 2017, American College of Rheumatology.

Extending a Tandem Mass Spectral Library to Include MS2 Spectra of Fragment Ions Produced In-Source and MSn Spectra.

PubMed

Yang, Xiaoyu; Neta, Pedatsur; Stein, Stephen E

2017-11-01

Tandem mass spectral library searching is finding increased use as an effective means of determining chemical identity in mass spectrometry-based omics studies. We previously reported on constructing a tandem mass spectral library that includes spectra for multiple precursor ions for each analyte. Here we report our method for expanding this library to include MS 2 spectra of fragment ions generated during the ionization process (in-source fragment ions) as well as MS 3 and MS 4 spectra. These can assist the chemical identification process. A simple density-based clustering algorithm was used to cluster all significant precursor ions from MS 1 scans for an analyte acquired during an infusion experiment. The MS 2 spectra associated with these precursor ions were grouped into the same precursor clusters. Subsequently, a new top-down hierarchical divisive clustering algorithm was developed for clustering the spectra from fragmentation of ions in each precursor cluster, including the MS 2 spectra of the original precursors and of the in-source fragments as well as the MS n spectra. This algorithm starts with all the spectra of one precursor in one cluster and then separates them into sub-clusters of similar spectra based on the fragment patterns. Herein, we describe the algorithms and spectral evaluation methods for extending the library. The new library features were demonstrated by searching the high resolution spectra of E. coli extracts against the extended library, allowing identification of compounds and their in-source fragment ions in a manner that was not possible before. Graphical Abstract ᅟ.

Computer Aided Detection of Microcalcifications Utilizing Texture Analysis

DTIC Science & Technology

1995-12-01

encouraging results using features derived from the first moment of the power spectrum of the region[13]. Chitre, et al. and Kocur have made use of...are largely concentrated around the main diagonal. For the example C matrix in Figure 3.11, the ASM value is 0.0972. Previous work by Kocur [17] and...Patterson AFB OH, 1994. BIB-1 16. Hoffmeister, Jeffery W. Personal interviews, May-Nov 1995. Aerospace Physician. AL/CFHV, Wright-Patterson AFB,OH. 17. Kocur

Transient Fourier holography with bacteriorhodopsin films for breast cancer diagnostics

NASA Astrophysics Data System (ADS)

Rao, Devulapalli; Kothapalli, Sri-Rajasekar; Wu, Pengfei; Yelleswarapu, Chandra

X-ray mammography is the current gold standard for breast cancer screening. Microcalcifications and other features which are helpful to the radiologist for early diagnostics are often buried in the noise generated by the surrounding dense tissue. So image processing techniques are required to enhance these important features to improve the sensitivity of detection. An innovative technique is demonstrated for recording a hologram of the mammogram. It is recorded on a thin polymer film of Bacteriorhodopsin (bR) as photo induced isomerization grating containing the interference pattern between the object beam containing the Fourier spatial frequency components of the mammogram and a reference beam. The hologram contains all the enhanced features of the mammogram. A significant innovation of the technique is that the enhanced components in the processed image can be viewed by the radiologist in time scale. A technician can record the movie and when the radiologist looks at the movie at his convenience, freezing the frame as and when desired, he would see the microcalcifications as the brightest and last long in time. He would also observe lesions with intensity decreasing as their size increases. The same bR film can be used repeatedly for recording holograms with different mammograms. The technique is versatile and a different frequency band can be chosen to be optimized by changing the reference beam intensity. The experimental arrangement can be used for mammograms in screen film or digital format.

Analysis of classifiers performance for classification of potential microcalcification

NASA Astrophysics Data System (ADS)

M. N., Arun K.; Sheshadri, H. S.

2013-07-01

Breast cancer is a significant public health problem in the world. According to the literature early detection improve breast cancer prognosis. Mammography is a screening tool used for early detection of breast cancer. About 10-30% cases are missed during the routine check as it is difficult for the radiologists to make accurate analysis due to large amount of data. The Microcalcifications (MCs) are considered to be important signs of breast cancer. It has been reported in literature that 30% - 50% of breast cancer detected radio graphically show MCs on mammograms. Histologic examinations report 62% to 79% of breast carcinomas reveals MCs. MC are tiny, vary in size, shape, and distribution, and MC may be closely connected to surrounding tissues. There is a major challenge using the traditional classifiers in the classification of individual potential MCs as the processing of mammograms in appropriate stage generates data sets with an unequal amount of information for both classes (i.e., MC, and Not-MC). Most of the existing state-of-the-art classification approaches are well developed by assuming the underlying training set is evenly distributed. However, they are faced with a severe bias problem when the training set is highly imbalanced in distribution. This paper addresses this issue by using classifiers which handle the imbalanced data sets. In this paper, we also compare the performance of classifiers which are used in the classification of potential MC.

Microcalcifications in breast cancer: novel insights into the molecular mechanism and functional consequence of mammary mineralisation

PubMed Central

Cox, R F; Hernandez-Santana, A; Ramdass, S; McMahon, G; Harmey, J H; Morgan, M P

2012-01-01

Background: Mammographic microcalcifications represent one of the most reliable features of nonpalpable breast cancer yet remain largely unexplored and poorly understood. Methods: We report a novel model to investigate the in vitro mineralisation potential of a panel of mammary cell lines. Primary mammary tumours were produced by implanting tumourigenic cells into the mammary fat pads of female BALB/c mice. Results: Hydroxyapatite (HA) was deposited only by the tumourigenic cell lines, indicating mineralisation potential may be associated with cell phenotype in this in vitro model. We propose a mechanism for mammary mineralisation, which suggests that the balance between enhancers and inhibitors of physiological mineralisation are disrupted. Inhibition of alkaline phosphatase and phosphate transport prevented mineralisation, demonstrating that mineralisation is an active cell-mediated process. Hydroxyapatite was found to enhance in vitro tumour cell migration, while calcium oxalate had no effect, highlighting potential consequences of calcium deposition. In addition, HA was also deposited in primary mammary tumours produced by implanting the tumourigenic cells into the mammary fat pads of female BALB/c mice. Conclusion: This work indicates that formation of mammary HA is a cell-specific regulated process, which creates an osteomimetic niche potentially enhancing breast tumour progression. Our findings point to the cells mineralisation potential and the microenvironment regulating it, as a significant feature of breast tumour development. PMID:22233923

Effect of spatial noise of medical grade Liquid Crystal Displays (LCD) on the detection of micro-calcification

NASA Astrophysics Data System (ADS)

Roehrig, Hans; Fan, Jiahua; Dallas, William J.; Krupinski, Elizabeth A.; Johnson, Jeffrey

2009-08-01

This presentation describes work in progress that is the result of an NIH SBIR Phase 1 project that addresses the wide- spread concern for the large number of breast-cancers and cancer victims [1,2]. The primary goal of the project is to increase the detection rate of microcalcifications as a result of the decrease of spatial noise of the LCDs used to display the mammograms [3,4]. Noise reduction is to be accomplished with the aid of a high performance CCD camera and subsequent application of local-mean equalization and error diffusion [5,6]. A second goal of the project is the actual detection of breast cancer. Contrary to the approach to mammography, where the mammograms typically have a pixel matrix of approximately 1900 x 2300 pixels, otherwise known as FFDM or Full-Field Digital Mammograms, we will only use sections of mammograms with a pixel matrix of 256 x 256 pixels. This is because at this time, reduction of spatial noise on an LCD can only be done on relatively small areas like 256 x 256 pixels. In addition, judging the efficacy for detection of breast cancer will be done using two methods: One is a conventional ROC study [7], the other is a vision model developed over several years starting at the Sarnoff Research Center and continuing at the Siemens Corporate Research in Princeton NJ [8].

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

PubMed

Karnan, M; Thangavel, K

2007-07-01

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

IDENTIFICATION OF CANDIDATE HOUSES FOR NORTH FLORIDA PORTION OF THE FLORIDA RADON MITIGATION PROJECT

EPA Science Inventory

The report gives results of a study to locate candidate houses for a proposed radon mitigation research and demonstration project in North Florida. he effort involved: 1) identification of target geographical areas, 2) radon monitoring in identified clusters, and 3) house charact...

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

PubMed

Knutson, Stacy T; Westwood, Brian M; Leuthaeuser, Janelle B; Turner, Brandon E; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D; Harper, Angela F; Brown, Shoshana D; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C; Fetrow, Jacquelyn S

2017-04-01

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Computational identification of developmental enhancers:conservation and function of transcription factor binding-site clustersin drosophila melanogaster and drosophila psedoobscura

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

Berman, Benjamin P.; Pfeiffer, Barret D.; Laverty, Todd R.

2004-08-06

Background The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. Results We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene,more » and assayed embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. Conclusions Measuring conservation of sequence features closely linked to function - such as binding-site clustering - makes better use of comparative sequence data than commonly used methods that examine only sequence identity.« less

Pathway of Contagion: The Identification of a Youth Suicide Cluster

ERIC Educational Resources Information Center

Zenere, Frank J.

2008-01-01

As a school psychologist and crisis management specialist for Miami-Dade County Public Schools, a member of the NASP National Emergency Assistance Team, and an independent consultant, the author has provided postvention services following the suicides of over 50 students, including several suicide clusters. Providing assistance in the aftermath of…

Identification of a trichothecene gene cluster and description of the harzianum A biosynthesis pathway in the fungus Trichoderma arundinaceum

USDA-ARS?s Scientific Manuscript database

Trichothecenes are sesquiterpenes that act like mycotoxins. Their biosynthesis has been mainly studied in the fungal genera Fusarium, where most of the biosynthetic genes (tri) are grouped in a cluster regulated by ambient conditions and regulatory genes. Unexpectedly, few studies are available abou...

Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

PubMed

Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

2014-05-01

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

New atlas of open star clusters

NASA Astrophysics Data System (ADS)

Seleznev, Anton F.; Avvakumova, Ekaterina; Kulesh, Maxim; Filina, Julia; Tsaregorodtseva, Polina; Kvashnina, Alvira

2017-11-01

Due to numerous new discoveries of open star clusters in the last two decades, astronomers need an easy-touse resource to get visual information on the relative position of clusters in the sky. Therefore we propose a new atlas of open star clusters. It is based on a table compiled from the largest modern cluster catalogues. The atlas shows the positions and sizes of 3291 clusters and associations, and consists of two parts. The first contains 108 maps of 12 by 12 degrees with an overlapping of 2 degrees in three strips along the Galactic equator. The second one is an online web application, which shows a square field of an arbitrary size, either in equatorial coordinates or in galactic coordinates by request. The atlas is proposed for the sampling of clusters and cluster stars for further investigation. Another use is the identification of clusters among overdensities in stellar density maps or among stellar groups in images of the sky.

A Comparative Evaluation of Anomaly Detection Algorithms for Maritime Video Surveillance

DTIC Science & Technology

2011-01-01

of k-means clustering and the k- NN Localized p-value Estimator ( KNN -LPE). K-means is a popular distance-based clustering algorithm while KNN -LPE...implemented the sparse cluster identification rule we described in Section 3.1. 2. k-NN Localized p-value Estimator ( KNN -LPE): We implemented this using...Average Density ( KNN -NAD): This was implemented as described in Section 3.4. Algorithm Parameter Settings The global and local density-based anomaly

Vertebra identification using template matching modelmp and K-means clustering.

PubMed

Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

2014-03-01

Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

Salmonella enterica Pulsed-Field Gel Electrophoresis Clusters, Minnesota, USA, 2001–2007

PubMed Central

Hedberg, Craig W.; Meyer, Stephanie; Boxrud, David J.; Smith, Kirk E.

2010-01-01

We determined characteristics of Salmonella enterica pulsed-field gel electrophoresis clusters that predict their being solved (i.e., that result in identification of a confirmed outbreak). Clusters were investigated by the Minnesota Department of Health by using a dynamic iterative model. During 2001–2007, a total of 43 (12.5%) of 344 clusters were solved. Clusters of >4 isolates were more likely to be solved than clusters of 2 isolates. Clusters in which the first 3 case isolates were received at the Minnesota Department of Health within 7 days were more likely to be solved than were clusters in which the first 3 case isolates were received over a period >14 days. If resources do not permit investigation of all S. enterica pulsed-field gel electrophoresis clusters, investigation of clusters of >4 cases and clusters in which the first 3 case isolates were received at a public health laboratory within 7 days may improve outbreak investigations. PMID:21029524

Mapping Emission from Clusters of CdSe/ZnS Nanoparticles

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

Ryan, Duncan P.; Goodwin, Peter M.; Sheehan, Chris J.

In this paper, we have carried out correlated super-resolution and SEM imaging studies of clusters of CdSe/ZnS nanoparticles containing up to ten particles to explore how the fluorescence behavior of these clusters depends on the number of particles, the specific cluster geometry, the shell thickness, and the technique used to produce the clusters. The total emission yield was less than proportional to the number of particles in the clusters for both thick and thin shells. With super-resolution imaging, the emission center of the cluster could be spatially resolved at distance scales on the order of the cluster size. The intrinsicmore » fluorescence intermittency of the nanoparticles altered the emission distribution across the cluster, which enabled the identification of relative emission intensities of individual particles or small groups of particles within the cluster. Finally, for clusters undergoing interparticle energy transfer, donor/acceptor pairs and regions where energy was funneled could be identified.« less

Mapping Emission from Clusters of CdSe/ZnS Nanoparticles

DOE PAGES

Ryan, Duncan P.; Goodwin, Peter M.; Sheehan, Chris J.; ...

2018-01-24

In this paper, we have carried out correlated super-resolution and SEM imaging studies of clusters of CdSe/ZnS nanoparticles containing up to ten particles to explore how the fluorescence behavior of these clusters depends on the number of particles, the specific cluster geometry, the shell thickness, and the technique used to produce the clusters. The total emission yield was less than proportional to the number of particles in the clusters for both thick and thin shells. With super-resolution imaging, the emission center of the cluster could be spatially resolved at distance scales on the order of the cluster size. The intrinsicmore » fluorescence intermittency of the nanoparticles altered the emission distribution across the cluster, which enabled the identification of relative emission intensities of individual particles or small groups of particles within the cluster. Finally, for clusters undergoing interparticle energy transfer, donor/acceptor pairs and regions where energy was funneled could be identified.« less

Screening and characterization of phosphate solubilizing bacteria from isolate of thermophilic bacteria

NASA Astrophysics Data System (ADS)

Yulianti, Evy; Rakhmawati, Anna

2017-08-01

The aims of this study were to select bacteria that has the ability to dissolve phosphate from thermophilic bacteria isolates after the Merapi eruption. Five isolates of selected bacteria was characterized and continued with identification. Selection was done by using a pikovskaya selective medium. Bacterial isolates were grown in selective medium and incubated for 48 hours at temperature of 55 ° C. Characterization was done by looking at the cell and colony morphology, physiological and biochemical properties. Identification was done with the Profile Matching method based on the reference genus Oscillospira traced through Bergey's Manual of Determinative Bacteriology. Dendogram was created based on similarity index SSM. The results showed there were 14 isolates of bacteria that were able to dissolve phosphate indicated by a clear zone surrounding the bacterial colony on selective media. Five isolates were selected with the largest clear zone. Isolates D79, D92, D110a, D135 and D75 have different characters. The result of phenotypic characters identification with Genus Oscillospira profile has a percentage of 100% similarity to isolate D92 and D110a; 92.31% for isolates D79, and 84.6% for isolates D75 and D135. Dendogram generated from average linkage algorithm / UPGMA using the Simple Matching Coefficient (SSM) algorithms showed, isolate thermophilic bacteria D75 and D135 are combined together to form cluster 1. D110a and D92 form a sub cluster A. Sub cluster A and D79 form cluster 2

Identification of microRNA-mRNA modules using microarray data.

PubMed

Jayaswal, Vivek; Lutherborrow, Mark; Ma, David D F; Yang, Yee H

2011-03-06

MicroRNAs (miRNAs) are post-transcriptional regulators of mRNA expression and are involved in numerous cellular processes. Consequently, miRNAs are an important component of gene regulatory networks and an improved understanding of miRNAs will further our knowledge of these networks. There is a many-to-many relationship between miRNAs and mRNAs because a single miRNA targets multiple mRNAs and a single mRNA is targeted by multiple miRNAs. However, most of the current methods for the identification of regulatory miRNAs and their target mRNAs ignore this biological observation and focus on miRNA-mRNA pairs. We propose a two-step method for the identification of many-to-many relationships between miRNAs and mRNAs. In the first step, we obtain miRNA and mRNA clusters using a combination of miRNA-target mRNA prediction algorithms and microarray expression data. In the second step, we determine the associations between miRNA clusters and mRNA clusters based on changes in miRNA and mRNA expression profiles. We consider the miRNA-mRNA clusters with statistically significant associations to be potentially regulatory and, therefore, of biological interest. Our method reduces the interactions between several hundred miRNAs and several thousand mRNAs to a few miRNA-mRNA groups, thereby facilitating a more meaningful biological analysis and a more targeted experimental validation.

(GTG)5 MSP-PCR fingerprinting as a technique for discrimination of wine associated yeasts?

PubMed

Ramírez-Castrillón, Mauricio; Mendes, Sandra Denise Camargo; Inostroza-Ponta, Mario; Valente, Patricia

2014-01-01

In microbiology, identification of all isolates by sequencing is still unfeasible in small research laboratories. Therefore, many yeast diversity studies follow a screening procedure consisting of clustering the yeast isolates using MSP-PCR fingerprinting, followed by identification of one or a few selected representatives of each cluster by sequencing. Although this procedure has been widely applied in the literature, it has not been properly validated. We evaluated a standardized protocol using MSP-PCR fingerprinting with the primers (GTG)5 and M13 for the discrimination of wine associated yeasts in South Brazil. Two datasets were used: yeasts isolated from bottled wines and vineyard environments. We compared the discriminatory power of both primers in a subset of 16 strains, choosing the primer (GTG)5 for further evaluation. Afterwards, we applied this technique to 245 strains, and compared the results with the identification obtained by partial sequencing of the LSU rRNA gene, considered as the gold standard. An array matrix was constructed for each dataset and used as input for clustering with two methods (hierarchical dendrograms and QAPGrid layout). For both yeast datasets, unrelated species were clustered in the same group. The sensitivity score of (GTG)5 MSP-PCR fingerprinting was high, but specificity was low. As a conclusion, the yeast diversity inferred in several previous studies may have been underestimated and some isolates were probably misidentified due to the compliance to this screening procedure.

(GTG)5 MSP-PCR Fingerprinting as a Technique for Discrimination of Wine Associated Yeasts?

PubMed Central

Inostroza-Ponta, Mario; Valente, Patricia

2014-01-01

In microbiology, identification of all isolates by sequencing is still unfeasible in small research laboratories. Therefore, many yeast diversity studies follow a screening procedure consisting of clustering the yeast isolates using MSP-PCR fingerprinting, followed by identification of one or a few selected representatives of each cluster by sequencing. Although this procedure has been widely applied in the literature, it has not been properly validated. We evaluated a standardized protocol using MSP-PCR fingerprinting with the primers (GTG)5 and M13 for the discrimination of wine associated yeasts in South Brazil. Two datasets were used: yeasts isolated from bottled wines and vineyard environments. We compared the discriminatory power of both primers in a subset of 16 strains, choosing the primer (GTG)5 for further evaluation. Afterwards, we applied this technique to 245 strains, and compared the results with the identification obtained by partial sequencing of the LSU rRNA gene, considered as the gold standard. An array matrix was constructed for each dataset and used as input for clustering with two methods (hierarchical dendrograms and QAPGrid layout). For both yeast datasets, unrelated species were clustered in the same group. The sensitivity score of (GTG)5 MSP-PCR fingerprinting was high, but specificity was low. As a conclusion, the yeast diversity inferred in several previous studies may have been underestimated and some isolates were probably misidentified due to the compliance to this screening procedure. PMID:25171185

IDENTIFICATION OF MEMBERS IN THE CENTRAL AND OUTER REGIONS OF GALAXY CLUSTERS

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

Serra, Ana Laura; Diaferio, Antonaldo, E-mail: serra@ph.unito.it

2013-05-10

The caustic technique measures the mass of galaxy clusters in both their virial and infall regions and, as a byproduct, yields the list of cluster galaxy members. Here we use 100 galaxy clusters with mass M{sub 200} {>=} 10{sup 14} h {sup -1} M{sub Sun} extracted from a cosmological N-body simulation of a {Lambda}CDM universe to test the ability of the caustic technique to identify the cluster galaxy members. We identify the true three-dimensional members as the gravitationally bound galaxies. The caustic technique uses the caustic location in the redshift diagram to separate the cluster members from the interlopers. Wemore » apply the technique to mock catalogs containing 1000 galaxies in the field of view of 12 h {sup -1} Mpc on a side at the cluster location. On average, this sample size roughly corresponds to 180 real galaxy members within 3r{sub 200}, similar to recent redshift surveys of cluster regions. The caustic technique yields a completeness, the fraction of identified true members, f{sub c} = 0.95 {+-} 0.03, within 3r{sub 200}. The contamination, the fraction of interlopers in the observed catalog of members, increases from f{sub i}=0.020{sup +0.046}{sub -0.015} at r{sub 200} to f{sub i}=0.08{sup +0.11}{sub -0.05} at 3r{sub 200}. No other technique for the identification of the members of a galaxy cluster provides such large completeness and small contamination at these large radii. The caustic technique assumes spherical symmetry and the asphericity of the cluster is responsible for most of the spread of the completeness and the contamination. By applying the technique to an approximately spherical system obtained by stacking the individual clusters, the spreads decrease by at least a factor of two. We finally estimate the cluster mass within 3r{sub 200} after removing the interlopers: for individual clusters, the mass estimated with the virial theorem is unbiased and within 30% of the actual mass; this spread decreases to less than 10% for the spherically symmetric stacked cluster.« less

Backscattering analysis of high frequency ultrasonic imaging for ultrasound-guided breast biopsy

NASA Astrophysics Data System (ADS)

Cummins, Thomas; Akiyama, Takahiro; Lee, Changyang; Martin, Sue E.; Shung, K. Kirk

2017-03-01

A new ultrasound-guided breast biopsy technique is proposed. The technique utilizes conventional ultrasound guidance coupled with a high frequency embedded ultrasound array located within the biopsy needle to improve the accuracy in breast cancer diagnosis.1 The array within the needle is intended to be used to detect micro- calcifications indicative of early breast cancers such as ductal carcinoma in situ (DCIS). Backscattering analysis has the potential to characterize tissues to improve localization of lesions. This paper describes initial results of the application of backscattering analysis of breast biopsy tissue specimens and shows the usefulness of high frequency ultrasound for the new biopsy related technique. Ultrasound echoes of ex-vivo breast biopsy tissue specimens were acquired by using a single-element transducer with a bandwidth from 41 MHz to 88 MHz utilizing a UBM methodology, and the backscattering coefficients were calculated. These values as well as B-mode image data were mapped in 2D and matched with each pathology image for the identification of tissue type for the comparison to the pathology images corresponding to each plane. Microcalcifications were significantly distinguished from normal tissue. Adenocarcinoma was also successfully differentiated from adipose tissue. These results indicate that backscattering analysis is able to quantitatively distinguish tissues into normal and abnormal, which should help radiologists locate abnormal areas during the proposed ultrasound-guided breast biopsy with high frequency ultrasound.

Chapter 7. Cloning and analysis of natural product pathways.

PubMed

Gust, Bertolt

2009-01-01

The identification of gene clusters of natural products has lead to an enormous wealth of information about their biosynthesis and its regulation, and about self-resistance mechanisms. Well-established routine techniques are now available for the cloning and sequencing of gene clusters. The subsequent functional analysis of the complex biosynthetic machinery requires efficient genetic tools for manipulation. Until recently, techniques for the introduction of defined changes into Streptomyces chromosomes were very time-consuming. In particular, manipulation of large DNA fragments has been challenging due to the absence of suitable restriction sites for restriction- and ligation-based techniques. The homologous recombination approach called recombineering (referred to as Red/ET-mediated recombination in this chapter) has greatly facilitated targeted genetic modifications of complex biosynthetic pathways from actinomycetes by eliminating many of the time-consuming and labor-intensive steps. This chapter describes techniques for the cloning and identification of biosynthetic gene clusters, for the generation of gene replacements within such clusters, for the construction of integrative library clones and their expression in heterologous hosts, and for the assembly of entire biosynthetic gene clusters from the inserts of individual library clones. A systematic approach toward insertional mutation of a complete Streptomyces genome is shown by the use of an in vitro transposon mutagenesis procedure.

Use of phylogenetical analysis to predict susceptibility of pathogenic Candida spp. to antifungal drugs.

PubMed

Maheux, Andrée F; Sellam, Adnane; Piché, Yves; Boissinot, Maurice; Pelletier, René; Boudreau, Dominique K; Picard, François J; Trépanier, Hélène; Boily, Marie-Josée; Ouellette, Marc; Roy, Paul H; Bergeron, Michel G

2016-12-01

Successful treatment of a Candida infection relies on 1) an accurate identification of the pathogenic fungus and 2) on its susceptibility to antifungal drugs. In the present study we investigated the level of correlation between phylogenetical evolution and susceptibility of pathogenic Candida spp. to antifungal drugs. For this, we compared a phylogenetic tree, assembled with the concatenated sequences (2475-bp) of the ATP2, TEF1, and TUF1 genes from 20 representative Candida species, with published minimal inhibitory concentrations (MIC) of the four principal antifungal drug classes commonly used in the treatment of candidiasis: polyenes, triazoles, nucleoside analogues, and echinocandins. The phylogenetic tree revealed three distinct phylogenetic clusters among Candida species. Species within a given phylogenetic cluster have generally similar susceptibility profiles to antifungal drugs and species within Clusters II and III were less sensitive to antifungal drugs than Cluster I species. These results showed that phylogenetical relationship between clusters and susceptibility to several antifungal drugs could be used to guide therapy when only species identification is available prior to information pertaining to its resistance profile. An extended study comprising a large panel of clinical samples should be conducted to confirm the efficiency of this approach in the treatment of candidiasis. Copyright © 2016. Published by Elsevier B.V.

Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae).

PubMed

Van Cann, Joannes; Virgilio, Massimiliano; Jordaens, Kurt; De Meyer, Marc

2015-01-01

Previous attempts to resolve the Ceratitis FAR complex (Ceratitis fasciventris, Ceratitis anonae, Ceratitis rosa, Diptera, Tephritidae) showed contrasting results and revealed the occurrence of five microsatellite genotypic clusters (A, F1, F2, R1, R2). In this paper we explore the potential of wing morphometrics for the diagnosis of FAR morphospecies and genotypic clusters. We considered a set of 227 specimens previously morphologically identified and genotyped at 16 microsatellite loci. Seventeen wing landmarks and 6 wing band areas were used for morphometric analyses. Permutational multivariate analysis of variance detected significant differences both across morphospecies and genotypic clusters (for both males and females). Unconstrained and constrained ordinations did not properly resolve groups corresponding to morphospecies or genotypic clusters. However, posterior group membership probabilities (PGMPs) of the Discriminant Analysis of Principal Components (DAPC) allowed the consistent identification of a relevant proportion of specimens (but with performances differing across morphospecies and genotypic clusters). This study suggests that wing morphometrics and PGMPs might represent a possible tool for the diagnosis of species within the FAR complex. Here, we propose a tentative diagnostic method and provide a first reference library of morphometric measures that might be used for the identification of additional and unidentified FAR specimens.

Identification of cephalopod species from the North and Baltic Seas using morphology, COI and 18S rDNA sequences

NASA Astrophysics Data System (ADS)

Gebhardt, Katharina; Knebelsberger, Thomas

2015-09-01

We morphologically analyzed 79 cephalopod specimens from the North and Baltic Seas belonging to 13 separate species. Another 29 specimens showed morphological features of either Alloteuthis mediaor Alloteuthis subulata or were found to be in between. Reliable identification features to distinguish between A. media and A. subulata are currently not available. The analysis of the DNA barcoding region of the COI gene revealed intraspecific distances (uncorrected p) ranging from 0 to 2.13 % (average 0.1 %) and interspecific distances between 3.31 and 22 % (average 15.52 %). All species formed monophyletic clusters in a neighbor-joining analysis and were supported by bootstrap values of ≥99 %. All COI haplotypes belonging to the 29 Alloteuthis specimens were grouped in one cluster. Neither COI nor 18S rDNA sequences helped to distinguish between the different Alloteuthis morphotypes. For species identification purposes, we recommend the use of COI, as it showed higher bootstrap support of species clusters and less amplification and sequencing failure compared to 18S. Our data strongly support the assumption that the genus Alloteuthis is only represented by a single species, at least in the North Sea. It remained unclear whether this species is A. subulata or A. media. All COI sequences including important metadata were uploaded to the Barcode of Life Data Systems and can be used as reference library for the molecular identification of more than 50 % of the cephalopod fauna known from the North and Baltic Seas.

Thin-layer chromatographic identification of Chinese propolis using chemometric fingerprinting.

PubMed

Tang, Tie-xin; Guo, Wei-yan; Xu, Ye; Zhang, Si-ming; Xu, Xin-jun; Wang, Dong-mei; Zhao, Zhi-min; Zhu, Long-ping; Yang, De-po

2014-01-01

Poplar tree gum has a similar chemical composition and appearance to Chinese propolis (bee glue) and has been widely used as a counterfeit propolis because Chinese propolis is typically the poplar-type propolis, the chemical composition of which is determined mainly by the resin of poplar trees. The discrimination of Chinese propolis from poplar tree gum is a challenging task. To develop a rapid thin-layer chromatographic (TLC) identification method using chemometric fingerprinting to discriminate Chinese propolis from poplar tree gum. A new TLC method using a combination of ammonia and hydrogen peroxide vapours as the visualisation reagent was developed to characterise the chemical profile of Chinese propolis. Three separate people performed TLC on eight Chinese propolis samples and three poplar tree gum samples of varying origins. Five chemometric methods, including similarity analysis, hierarchical clustering, k-means clustering, neural network and support vector machine, were compared for use in classifying the samples based on their densitograms obtained from the TLC chromatograms via image analysis. Hierarchical clustering, neural network and support vector machine analyses achieved a correct classification rate of 100% in classifying the samples. A strategy for TLC identification of Chinese propolis using chemometric fingerprinting was proposed and it provided accurate sample classification. The study has shown that the TLC identification method using chemometric fingerprinting is a rapid, low-cost method for the discrimination of Chinese propolis from poplar tree gum and may be used for the quality control of Chinese propolis. Copyright © 2014 John Wiley & Sons, Ltd.

Draft genome sequence of Streptomyces sp. strain SS, which produces a series of uridyl peptide antibiotic sansanmycins.

PubMed

Wang, Lifei; Xie, Yunying; Li, Qinglian; He, Ning; Yao, Entai; Xu, Hongzhang; Yu, Ying; Chen, Ruxian; Hong, Bin

2012-12-01

Streptomyces sp. SS produces a series of uridyl peptide antibiotic sansanmycins. Here, we present a draft genome sequence of Streptomyces sp. SS containing the biosynthetic gene cluster for the antibiotics. The identification of the biosynthetic gene cluster of sansanmycins may provide further insight into biosynthetic mechanisms for uridyl peptide antibiotics.

Documentation for the machine-readable version of a table of Redshifts for Abell clusters (Sarazin, Rood and Struble 1982)

NASA Technical Reports Server (NTRS)

Warren, W. H., Jr.

1983-01-01

The machine readable catalog is described. The machine version contains the same data as the published table, which includes a second file with the notes. The computerized data files are prepared at the Astronomical Data Center. Detected discrepancies and cluster identifications based on photometric estimators are included.

Identification of genes induced in proteoid roots of white lupin under nitrogen and phosphorus deprivation, with functional characterization of a formamidase

USDA-ARS?s Scientific Manuscript database

White lupin (Lupinus albus L.) is considered a model system for understanding plant acclimation to nutrient deficiency. It acclimates to phosphorus (P) and iron (Fe) deficiency by the development of short, densely clustered lateral roots called proteoid (or cluster) roots; proteoid-root development ...

Optimization of Tomosynthesis Imaging for Improved Mass and Microcalcification Detection in the Breast

DTIC Science & Technology

2009-04-01

reviewed Journal Articles 1. D. Xia, L. Yu , E. Y. Sidky, Y. Zou, N. Zuo, and X. Pan: Noise properties of chord-image reconstruction, IEEE Transaction...on Medical Imaging 26, pp. 1328-1344, 2007. Conference Proceeding Articles 1. D. Xia, E. Y. Sidky, L. Yu , and X. Pan: Noise properties in helical...positions distributed over a surface, Proc. SPIE, Vol. 6913, pp. 69132A, 2008. 11. D. Xia, L. Yu , E. Y. Sidky, Y. Zou, N. Zuo, and X. Pan: Noise properties

Acoustic Inverse Scattering for Breast Cancer Microcalcification Detection. Addendum

DTIC Science & Technology

2011-12-01

the center. To conserve space, few are shown here. A graph comparing the spatial location and the error in reconstruction will follow...following graphs show the error in reconstruction as a function of position of the object along the x-axis, y-axis and the diagonal in the fourth quadrant of...the well-known Kirchhoff – Poisson formulas (see, e.g., Refs. [33,34]) allow one to rep- resent the solution p(x,t) in terms of the spherical means

Evaluation of the Gini Coefficient in Spatial Scan Statistics for Detecting Irregularly Shaped Clusters

PubMed Central

Kim, Jiyu; Jung, Inkyung

2017-01-01

Spatial scan statistics with circular or elliptic scanning windows are commonly used for cluster detection in various applications, such as the identification of geographical disease clusters from epidemiological data. It has been pointed out that the method may have difficulty in correctly identifying non-compact, arbitrarily shaped clusters. In this paper, we evaluated the Gini coefficient for detecting irregularly shaped clusters through a simulation study. The Gini coefficient, the use of which in spatial scan statistics was recently proposed, is a criterion measure for optimizing the maximum reported cluster size. Our simulation study results showed that using the Gini coefficient works better than the original spatial scan statistic for identifying irregularly shaped clusters, by reporting an optimized and refined collection of clusters rather than a single larger cluster. We have provided a real data example that seems to support the simulation results. We think that using the Gini coefficient in spatial scan statistics can be helpful for the detection of irregularly shaped clusters. PMID:28129368

Prospective associations between socio-economic status and dietary patterns in European children: the Identification and Prevention of Dietary- and Lifestyle-induced Health Effects in Children and Infants (IDEFICS) Study.

PubMed

Fernández-Alvira, Juan Miguel; Börnhorst, Claudia; Bammann, Karin; Gwozdz, Wencke; Krogh, Vittorio; Hebestreit, Antje; Barba, Gianvincenzo; Reisch, Lucia; Eiben, Gabriele; Iglesia, Iris; Veidebaum, Tomas; Kourides, Yannis A; Kovacs, Eva; Huybrechts, Inge; Pigeot, Iris; Moreno, Luis A

2015-02-14

Exploring changes in children's diet over time and the relationship between these changes and socio-economic status (SES) may help to understand the impact of social inequalities on dietary patterns. The aim of the present study was to describe dietary patterns by applying a cluster analysis to 9301 children participating in the baseline (2-9 years old) and follow-up (4-11 years old) surveys of the Identification and Prevention of Dietary- and Lifestyle-induced Health Effects in Children and Infants Study, and to describe the cluster memberships of these children over time and their association with SES. We applied the K-means clustering algorithm based on the similarities between the relative frequencies of consumption of forty-two food items. The following three consistent clusters were obtained at baseline and follow-up: processed (higher frequency of consumption of snacks and fast food); sweet (higher frequency of consumption of sweet foods and sweetened drinks); healthy (higher frequency of consumption of fruits, vegetables and wholemeal products). Children with higher-educated mothers and fathers and the highest household income were more likely to be allocated to the healthy cluster at baseline and follow-up and less likely to be allocated to the sweet cluster. Migrants were more likely to be allocated to the processed cluster at baseline and follow-up. Applying the cluster analysis to derive dietary patterns at the two time points allowed us to identify groups of children from a lower socio-economic background presenting persistently unhealthier dietary profiles. This finding reflects the need for healthy eating interventions specifically targeting children from lower socio-economic backgrounds.

Globular cluster x-ray sources

PubMed Central

Pooley, David

2010-01-01

Globular clusters and x-ray astronomy have a long and fruitful history. Uhuru and OSO-7 revealed highly luminous (> 1036 ergs-1) x-ray sources in globular clusters, and Einstein and ROSAT revealed a larger population of low-luminosity (< 1033 ergs-1) x-ray sources. It was realized early on that the high-luminosity sources were low-mass x-ray binaries in outburst and that they were orders of magnitude more abundant per unit mass in globular clusters than in the rest of the galaxy. However, the low-luminosity sources proved difficult to classify. Many ideas were put forth—low-mass x-ray binaries in quiescence (qLMXBs), cataclysmic variables (CVs), active main-sequence binaries (ABs), and millisecond pulsars (MSPs)—but secure identifications were scarce. In ROSAT observations of 55 clusters, about 25 low-luminosity sources were found. Chandra has now observed over 80 Galactic globular clusters, and these observations have revealed over 1,500 x-ray sources. The superb angular resolution has allowed for many counterpart identifications, providing clues to the nature of this population. It is a heterogeneous mix of qLMXBs, CVs, ABs, and MSPs, and it has been shown that the qLMXBs and CVs are both, in part, overabundant like the luminous LMXBs. The number of x-ray sources in a cluster correlates very well with its encounter frequency. This points to dynamical formation scenarios for the x-ray sources and shows them to be excellent tracers of the complicated internal dynamics. The relation between the encounter frequency and the number of x-ray sources has been used to suggest that we have misunderstood the dynamical states of globular clusters. PMID:20404204

Comprehensive Biothreat Cluster Identification by PCR/Electrospray-Ionization Mass Spectrometry

PubMed Central

Sampath, Rangarajan; Mulholland, Niveen; Blyn, Lawrence B.; Massire, Christian; Whitehouse, Chris A.; Waybright, Nicole; Harter, Courtney; Bogan, Joseph; Miranda, Mary Sue; Smith, David; Baldwin, Carson; Wolcott, Mark; Norwood, David; Kreft, Rachael; Frinder, Mark; Lovari, Robert; Yasuda, Irene; Matthews, Heather; Toleno, Donna; Housley, Roberta; Duncan, David; Li, Feng; Warren, Robin; Eshoo, Mark W.; Hall, Thomas A.; Hofstadler, Steven A.; Ecker, David J.

2012-01-01

Technology for comprehensive identification of biothreats in environmental and clinical specimens is needed to protect citizens in the case of a biological attack. This is a challenge because there are dozens of bacterial and viral species that might be used in a biological attack and many have closely related near-neighbor organisms that are harmless. The biothreat agent, along with its near neighbors, can be thought of as a biothreat cluster or a biocluster for short. The ability to comprehensively detect the important biothreat clusters with resolution sufficient to distinguish the near neighbors with an extremely low false positive rate is required. A technological solution to this problem can be achieved by coupling biothreat group-specific PCR with electrospray ionization mass spectrometry (PCR/ESI-MS). The biothreat assay described here detects ten bacterial and four viral biothreat clusters on the NIAID priority pathogen and HHS/USDA select agent lists. Detection of each of the biothreat clusters was validated by analysis of a broad collection of biothreat organisms and near neighbors prepared by spiking biothreat nucleic acids into nucleic acids extracted from filtered environmental air. Analytical experiments were carried out to determine breadth of coverage, limits of detection, linearity, sensitivity, and specificity. Further, the assay breadth was demonstrated by testing a diverse collection of organisms from each biothreat cluster. The biothreat assay as configured was able to detect all the target organism clusters and did not misidentify any of the near-neighbor organisms as threats. Coupling biothreat cluster-specific PCR to electrospray ionization mass spectrometry simultaneously provides the breadth of coverage, discrimination of near neighbors, and an extremely low false positive rate due to the requirement that an amplicon with a precise base composition of a biothreat agent be detected by mass spectrometry. PMID:22768032

Identification of Clusters that Condition Resistance to Anthracnose in the Common Bean Differential Cultivars AB136 and MDRK.

PubMed

Campa, Ana; Trabanco, Noemí; Ferreira, Juan José

2017-12-01

The correct identification of the anthracnose resistance systems present in the common bean cultivars AB136 and MDRK is important because both are included in the set of 12 differential cultivars proposed for use in classifying the races of the anthracnose causal agent, Colletrotrichum lindemuthianum. In this work, the responses against seven C. lindemuthianum races were analyzed in a recombinant inbred line population derived from the cross AB136 × MDRK. A genetic linkage map of 100 molecular markers distributed across the 11 bean chromosomes was developed in this population to locate the gene or genes conferring resistance against each race, based on linkage analyses and χ 2 tests of independence. The identified anthracnose resistance genes were organized in clusters. Two clusters were found in AB136: one located on linkage group Pv07, which corresponds to the anthracnose resistance cluster Co-5, and the other located at the end of linkage group Pv11, which corresponds to the Co-2 cluster. The presence of resistance genes at the Co-5 cluster in AB136 was validated through an allelism test conducted in the F 2 population TU × AB136. The presence of resistance genes at the Co-2 cluster in AB136 was validated through genetic dissection using the F 2:3 population ABM3 × MDRK, in which it was directly mapped to a genomic position between 46.01 and 47.77 Mb of chromosome Pv11. In MDRK, two independent clusters were identified: one located on linkage group Pv01, corresponding to the Co-1 cluster, and the second located on LG Pv04, corresponding to the Co-3 cluster. This report enhances the understanding of the race-specific Phaseolus vulgaris-C. lindemuthianum interactions and will be useful in breeding programs.

Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research was to combine machine-learning (ML) algorithms with traditional regression techniques by utilising self-reported medical symptoms to identify and describe clusters of individuals with increased rates of depression from a large cross-sectional community based population epidemiological study. A multi-staged methodology utilising ML and traditional statistical techniques was performed using the community based population National Health and Nutrition Examination Study (2009-2010) (N = 3,922). A Self-organised Mapping (SOM) ML algorithm, combined with hierarchical clustering, was performed to create participant clusters based on 68 medical symptoms. Binary logistic regression, controlling for sociodemographic confounders, was used to then identify the key clusters of participants with higher levels of depression (PHQ-9≥10, n = 377). Finally, a Multiple Additive Regression Tree boosted ML algorithm was run to identify the important medical symptoms for each key cluster within 17 broad categories: heart, liver, thyroid, respiratory, diabetes, arthritis, fractures and osteoporosis, skeletal pain, blood pressure, blood transfusion, cholesterol, vision, hearing, psoriasis, weight, bowels and urinary. Five clusters of participants, based on medical symptoms, were identified to have significantly increased rates of depression compared to the cluster with the lowest rate: odds ratios ranged from 2.24 (95% CI 1.56, 3.24) to 6.33 (95% CI 1.67, 24.02). The ML boosted regression algorithm identified three key medical condition categories as being significantly more common in these clusters: bowel, pain and urinary symptoms. Bowel-related symptoms was found to dominate the relative importance of symptoms within the five key clusters. This methodology shows promise for the identification of conditions in general populations and supports the current focus on the potential importance of bowel symptoms and the gut in mental health research.

Characterisation of the paralytic shellfish toxin biosynthesis gene clusters in Anabaena circinalis AWQC131C and Aphanizomenon sp. NH-5.

PubMed

Mihali, Troco K; Kellmann, Ralf; Neilan, Brett A

2009-03-30

Saxitoxin and its analogues collectively known as the paralytic shellfish toxins (PSTs) are neurotoxic alkaloids and are the cause of the syndrome named paralytic shellfish poisoning. PSTs are produced by a unique biosynthetic pathway, which involves reactions that are rare in microbial metabolic pathways. Nevertheless, distantly related organisms such as dinoflagellates and cyanobacteria appear to produce these toxins using the same pathway. Hypothesised explanations for such an unusual phylogenetic distribution of this shared uncommon metabolic pathway, include a polyphyletic origin, an involvement of symbiotic bacteria, and horizontal gene transfer. We describe the identification, annotation and bioinformatic characterisation of the putative paralytic shellfish toxin biosynthesis clusters in an Australian isolate of Anabaena circinalis and an American isolate of Aphanizomenon sp., both members of the Nostocales. These putative PST gene clusters span approximately 28 kb and contain genes coding for the biosynthesis and export of the toxin. A putative insertion/excision site in the Australian Anabaena circinalis AWQC131C was identified, and the organization and evolution of the gene clusters are discussed. A biosynthetic pathway leading to the formation of saxitoxin and its analogues in these organisms is proposed. The PST biosynthesis gene cluster presents a mosaic structure, whereby genes have apparently transposed in segments of varying size, resulting in different gene arrangements in all three sxt clusters sequenced so far. The gene cluster organizational structure and sequence similarity seems to reflect the phylogeny of the producer organisms, indicating that the gene clusters have an ancient origin, or that their lateral transfer was also an ancient event. The knowledge we gain from the characterisation of the PST biosynthesis gene clusters, including the identity and sequence of the genes involved in the biosynthesis, may also afford the identification of these gene clusters in dinoflagellates, the cause of human mortalities and significant financial loss to the tourism and shellfish industries.

Characterisation of the paralytic shellfish toxin biosynthesis gene clusters in Anabaena circinalis AWQC131C and Aphanizomenon sp. NH-5

PubMed Central

Mihali, Troco K; Kellmann, Ralf; Neilan, Brett A

2009-01-01

Background Saxitoxin and its analogues collectively known as the paralytic shellfish toxins (PSTs) are neurotoxic alkaloids and are the cause of the syndrome named paralytic shellfish poisoning. PSTs are produced by a unique biosynthetic pathway, which involves reactions that are rare in microbial metabolic pathways. Nevertheless, distantly related organisms such as dinoflagellates and cyanobacteria appear to produce these toxins using the same pathway. Hypothesised explanations for such an unusual phylogenetic distribution of this shared uncommon metabolic pathway, include a polyphyletic origin, an involvement of symbiotic bacteria, and horizontal gene transfer. Results We describe the identification, annotation and bioinformatic characterisation of the putative paralytic shellfish toxin biosynthesis clusters in an Australian isolate of Anabaena circinalis and an American isolate of Aphanizomenon sp., both members of the Nostocales. These putative PST gene clusters span approximately 28 kb and contain genes coding for the biosynthesis and export of the toxin. A putative insertion/excision site in the Australian Anabaena circinalis AWQC131C was identified, and the organization and evolution of the gene clusters are discussed. A biosynthetic pathway leading to the formation of saxitoxin and its analogues in these organisms is proposed. Conclusion The PST biosynthesis gene cluster presents a mosaic structure, whereby genes have apparently transposed in segments of varying size, resulting in different gene arrangements in all three sxt clusters sequenced so far. The gene cluster organizational structure and sequence similarity seems to reflect the phylogeny of the producer organisms, indicating that the gene clusters have an ancient origin, or that their lateral transfer was also an ancient event. The knowledge we gain from the characterisation of the PST biosynthesis gene clusters, including the identity and sequence of the genes involved in the biosynthesis, may also afford the identification of these gene clusters in dinoflagellates, the cause of human mortalities and significant financial loss to the tourism and shellfish industries. PMID:19331657

Genomic characterization of a new endophytic Streptomyces kebangsaanensis identifies biosynthetic pathway gene clusters for novel phenazine antibiotic production

PubMed Central

Remali, Juwairiah; Sarmin, Nurul ‘Izzah Mohd; Ng, Chyan Leong; Tiong, John J.L.; Aizat, Wan M.; Keong, Loke Kok

2017-01-01

Background Streptomyces are well known for their capability to produce many bioactive secondary metabolites with medical and industrial importance. Here we report a novel bioactive phenazine compound, 6-((2-hydroxy-4-methoxyphenoxy) carbonyl) phenazine-1-carboxylic acid (HCPCA) extracted from Streptomyces kebangsaanensis, an endophyte isolated from the ethnomedicinal Portulaca oleracea. Methods The HCPCA chemical structure was determined using nuclear magnetic resonance spectroscopy. We conducted whole genome sequencing for the identification of the gene cluster(s) believed to be responsible for phenazine biosynthesis in order to map its corresponding pathway, in addition to bioinformatics analysis to assess the potential of S. kebangsaanensis in producing other useful secondary metabolites. Results The S. kebangsaanensis genome comprises an 8,328,719 bp linear chromosome with high GC content (71.35%) consisting of 12 rRNA operons, 81 tRNA, and 7,558 protein coding genes. We identified 24 gene clusters involved in polyketide, nonribosomal peptide, terpene, bacteriocin, and siderophore biosynthesis, as well as a gene cluster predicted to be responsible for phenazine biosynthesis. Discussion The HCPCA phenazine structure was hypothesized to derive from the combination of two biosynthetic pathways, phenazine-1,6-dicarboxylic acid and 4-methoxybenzene-1,2-diol, originated from the shikimic acid pathway. The identification of a biosynthesis pathway gene cluster for phenazine antibiotics might facilitate future genetic engineering design of new synthetic phenazine antibiotics. Additionally, these findings confirm the potential of S. kebangsaanensis for producing various antibiotics and secondary metabolites. PMID:29201559

A simple algorithm for the identification of clinical COPD phenotypes.

PubMed

Burgel, Pierre-Régis; Paillasseur, Jean-Louis; Janssens, Wim; Piquet, Jacques; Ter Riet, Gerben; Garcia-Aymerich, Judith; Cosio, Borja; Bakke, Per; Puhan, Milo A; Langhammer, Arnulf; Alfageme, Inmaculada; Almagro, Pere; Ancochea, Julio; Celli, Bartolome R; Casanova, Ciro; de-Torres, Juan P; Decramer, Marc; Echazarreta, Andrés; Esteban, Cristobal; Gomez Punter, Rosa Mar; Han, MeiLan K; Johannessen, Ane; Kaiser, Bernhard; Lamprecht, Bernd; Lange, Peter; Leivseth, Linda; Marin, Jose M; Martin, Francis; Martinez-Camblor, Pablo; Miravitlles, Marc; Oga, Toru; Sofia Ramírez, Ana; Sin, Don D; Sobradillo, Patricia; Soler-Cataluña, Juan J; Turner, Alice M; Verdu Rivera, Francisco Javier; Soriano, Joan B; Roche, Nicolas

2017-11-01

This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses.Data from 2409 COPD patients of French/Belgian COPD cohorts were analysed using cluster analysis resulting in the identification of subgroups, for which clinical relevance was determined by comparing 3-year all-cause mortality. Classification and regression trees (CARTs) were used to develop an algorithm for allocating patients to these subgroups. This algorithm was tested in 3651 patients from the COPD Cohorts Collaborative International Assessment (3CIA) initiative.Cluster analysis identified five subgroups of COPD patients with different clinical characteristics (especially regarding severity of respiratory disease and the presence of cardiovascular comorbidities and diabetes). The CART-based algorithm indicated that the variables relevant for patient grouping differed markedly between patients with isolated respiratory disease (FEV 1 , dyspnoea grade) and those with multi-morbidity (dyspnoea grade, age, FEV 1 and body mass index). Application of this algorithm to the 3CIA cohorts confirmed that it identified subgroups of patients with different clinical characteristics, mortality rates (median, from 4% to 27%) and age at death (median, from 68 to 76 years).A simple algorithm, integrating respiratory characteristics and comorbidities, allowed the identification of clinically relevant COPD phenotypes. Copyright ©ERS 2017.

Identification and DUS Testing of Rice Varieties through Microsatellite Markers

PubMed Central

Pourabed, Ehsan; Jazayeri Noushabadi, Mohammad Reza; Jamali, Seyed Hossein; Moheb Alipour, Naser; Zareyan, Abbas; Sadeghi, Leila

2015-01-01

Identification and registration of new rice varieties are very important to be free from environmental effects and using molecular markers that are more reliable. The objectives of this study were, first, the identification and distinction of 40 rice varieties consisting of local varieties of Iran, improved varieties, and IRRI varieties using PIC, and discriminating power, second, cluster analysis based on Dice similarity coefficient and UPGMA algorithm, and, third, determining the ability of microsatellite markers to separate varieties utilizing the best combination of markers. For this research, 12 microsatellite markers were used. In total, 83 polymorphic alleles (6.91 alleles per locus) were found. In addition, the variation of PIC was calculated from 0.52 to 0.9. The results of cluster analysis showed the complete discrimination of varieties from each other except for IR58025A and IR58025B. Moreover, cluster analysis could detect the most of the improved varieties from local varieties. Based on the best combination of markers analysis, five pair primers together have shown the same results of all markers for detection among all varieties. Considering the results of this research, we can propose that microsatellite markers can be used as a complementary tool for morphological characteristics in DUS tests. PMID:25755666

Clustering stock market companies via chaotic map synchronization

NASA Astrophysics Data System (ADS)

Basalto, N.; Bellotti, R.; De Carlo, F.; Facchi, P.; Pascazio, S.

2005-01-01

A pairwise clustering approach is applied to the analysis of the Dow Jones index companies, in order to identify similar temporal behavior of the traded stock prices. To this end, the chaotic map clustering algorithm is used, where a map is associated to each company and the correlation coefficients of the financial time series to the coupling strengths between maps. The simulation of a chaotic map dynamics gives rise to a natural partition of the data, as companies belonging to the same industrial branch are often grouped together. The identification of clusters of companies of a given stock market index can be exploited in the portfolio optimization strategies.

Characterizing X-ray Sources in the Rich Open Cluster NGC 7789 Using XMM-Newton

NASA Astrophysics Data System (ADS)

Farner, William; Pooley, David

2018-01-01

It is well established that globular clusters exhibit a correlation between their population of exotic binaries and their rate of stellar encounters, but little work has been done to characterize this relationship in rich open clusters. X-ray observations are the most efficient means to find various types of close binaries, and optical (and radio) identifications can provide secure source classifications. We report on an observation of the rich open cluster NGC 7789 using the XMM-Newton observatory. We present the X-ray and optical imaging data, source lists, and preliminary characterization of the sources based on their X-ray and multiwavelength properties.

The cluster-cluster correlation function. [of galaxies

NASA Technical Reports Server (NTRS)

Postman, M.; Geller, M. J.; Huchra, J. P.

1986-01-01

The clustering properties of the Abell and Zwicky cluster catalogs are studied using the two-point angular and spatial correlation functions. The catalogs are divided into eight subsamples to determine the dependence of the correlation function on distance, richness, and the method of cluster identification. It is found that the Corona Borealis supercluster contributes significant power to the spatial correlation function to the Abell cluster sample with distance class of four or less. The distance-limited catalog of 152 Abell clusters, which is not greatly affected by a single system, has a spatial correlation function consistent with the power law Xi(r) = 300r exp -1.8. In both the distance class four or less and distance-limited samples the signal in the spatial correlation function is a power law detectable out to 60/h Mpc. The amplitude of Xi(r) for clusters of richness class two is about three times that for richness class one clusters. The two-point spatial correlation function is sensitive to the use of estimated redshifts.

Discrimination of Scedosporium prolificans against Pseudallescheria boydii and Scedosporium apiospermum by semiautomated repetitive sequence-based PCR.

PubMed

Steinmann, J; Schmidt, D; Buer, J; Rath, P-M

2011-07-01

The laboratory identification of Pseudallescheria and Scedosporium isolates at the species level is important for clinical and epidemiological purposes. This study used semiautomated repetitive sequence-based polymerase chain reaction (rep-PCR) to identify Pseudallescheria/Scedosporium. Reference strains of Pseudallescheria boydii (n = 12), Scedosporium prolificans (n = 8), Scedosporium apiospermum (n = 9), and clinical/environmental isolates (P. boydii, 7; S. prolificans, 7; S. apiospermum, 7) were analyzed by rep-PCR. All clinical isolates were identified by morphological and phenotypic characteristics and by sequence analysis. Species identification of reference strains was based on the results of available databases. Rep-PCR studies were also conducted with various molds to differentiate Pseudallescheria/Scedosporium spp. from other commonly encountered filamentous fungi. All tested Pseudallescheria/Scedosporium isolates were distinguishable from the other filamentous fungi. All Scedosporium prolificans strains clustered within the cutoff of 85%, and species identification by rep-PCR showed an agreement of 100% with sequence analysis. However, several isolates of P. boydii and S. apiospermum did not cluster within the 85% cutoff with the same species by rep-PCR. Although the identification of P. boydii and S. apiospermum was not correct, the semiautomated rep-PCR system is a promising tool for the identification of S. prolificans isolates.

DNA barcoding reveal patterns of species diversity among northwestern Pacific molluscs

PubMed Central

Sun, Shao’e; Li, Qi; Kong, Lingfeng; Yu, Hong; Zheng, Xiaodong; Yu, Ruihai; Dai, Lina; Sun, Yan; Chen, Jun; Liu, Jun; Ni, Lehai; Feng, Yanwei; Yu, Zhenzhen; Zou, Shanmei; Lin, Jiping

2016-01-01

This study represents the first comprehensive molecular assessment of northwestern Pacific molluscs. In total, 2801 DNA barcodes belonging to 569 species from China, Japan and Korea were analyzed. An overlap between intra- and interspecific genetic distances was present in 71 species. We tested the efficacy of this library by simulating a sequence-based specimen identification scenario using Best Match (BM), Best Close Match (BCM) and All Species Barcode (ASB) criteria with three threshold values. BM approach returned 89.15% true identifications (95.27% when excluding singletons). The highest success rate of congruent identifications was obtained with BCM at 0.053 threshold. The analysis of our barcode library together with public data resulted in 582 Barcode Index Numbers (BINs), 72.2% of which was found to be concordantly with morphology-based identifications. The discrepancies were divided in two groups: sequences from different species clustered in a single BIN and conspecific sequences divided in one more BINs. In Neighbour-Joining phenogram, 2,320 (83.0%) queries fromed 355 (62.4%) species-specific barcode clusters allowing their successful identification. 33 species showed paraphyletic and haplotype sharing. 62 cases are represented by deeply diverged lineages. This study suggest an increased species diversity in this region, highlighting taxonomic revision and conservation strategy for the cryptic complexes. PMID:27640675

Identify High-Quality Protein Structural Models by Enhanced K-Means.

PubMed

Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

Identify High-Quality Protein Structural Models by Enhanced K-Means

PubMed Central

Li, Haiou; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K-means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K-means clustering (SK-means), whereas the other employs squared distance to optimize the initial centroids (K-means++). Our results showed that SK-means and K-means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K-means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK-means and K-means++ demonstrated substantial improvements relative to results from SPICKER and classical K-means. PMID:28421198

Novel layered clustering-based approach for generating ensemble of classifiers.

PubMed

Rahman, Ashfaqur; Verma, Brijesh

2011-05-01

This paper introduces a novel concept for creating an ensemble of classifiers. The concept is based on generating an ensemble of classifiers through clustering of data at multiple layers. The ensemble classifier model generates a set of alternative clustering of a dataset at different layers by randomly initializing the clustering parameters and trains a set of base classifiers on the patterns at different clusters in different layers. A test pattern is classified by first finding the appropriate cluster at each layer and then using the corresponding base classifier. The decisions obtained at different layers are fused into a final verdict using majority voting. As the base classifiers are trained on overlapping patterns at different layers, the proposed approach achieves diversity among the individual classifiers. Identification of difficult-to-classify patterns through clustering as well as achievement of diversity through layering leads to better classification results as evidenced from the experimental results.

Steps Toward Understanding Mitochondrial Fe/S Cluster Biogenesis.

PubMed

Melber, Andrew; Winge, Dennis R

2018-01-01

Iron-sulfur clusters (Fe/S clusters) are essential cofactors required throughout the clades of biology for performing a myriad of unique functions including nitrogen fixation, ribosome assembly, DNA repair, mitochondrial respiration, and metabolite catabolism. Although Fe/S clusters can be synthesized in vitro and transferred to a client protein without enzymatic assistance, biology has evolved intricate mechanisms to assemble and transfer Fe/S clusters within the cellular environment. In eukaryotes, the foundation of all cellular clusters starts within the mitochondria. The focus of this review is to detail the mitochondrial Fe/S biogenesis (ISC) pathway along with the Fe/S cluster transfer steps necessary to mature Fe/S proteins. New advances in our understanding of the mitochondrial Fe/S biogenesis machinery will be highlighted. Additionally, we will address various experimental approaches that have been successful in the identification and characterization of components of the ISC pathway. © 2018 Elsevier Inc. All rights reserved.

Preparation and high-resolution microscopy of gold cluster labeled nucleic acid conjugates and nanodevices

PubMed Central

Powell, Richard D.; Hainfeld, James F.

2013-01-01

Nanogold and undecagold are covalently linked gold cluster labels which enable the identification and localization of biological components with molecular precision and resolution. They can be prepared with different reactivities, which means they can be conjugated to a wide variety of molecules, including nucleic acids, at specific, unique sites. The location of these sites can be synthetically programmed in order to preserve the binding affinity of the conjugate and impart novel characteristics and useful functionality. Methods for the conjugation of undecagold and Nanogold to DNA and RNA are discussed, and applications of labeled conjugates to the high-resolution microscopic identification of binding sites and characterization of biological macromolecular assemblies are described. In addition to providing insights into their molecular structure and function, high-resolution microscopic methods also show how Nanogold and undecagold conjugates can be synthetically assembled, or self-assemble, into supramolecular materials to which the gold cluster labels impart useful functionality. PMID:20869258

Dual-energy in mammography: feasibility study

NASA Astrophysics Data System (ADS)

Jafroudi, Hamid; Lo, Shih-Chung B.; Li, Huai; Steller Artz, Dorothy E.; Freedman, Matthew T.; Mun, Seong K.

1996-04-01

The purpose of this work is to examine the feasibility of dual-energy techniques to enhance the detection of microcalcifications in digital mammography. The digital mammography system used in this study consists of two different mammography systems; one is the conventional mammography system with molybdenum target and Mo filtration and the other is the clinical version of a low dose x-ray system with tungsten target and aluminum filtration. The low dose system is optimized for screen-film mammography with a highly efficient scatter rejection device built by Fischer Imaging Systems for evaluation at NIH. The system was designed by the University of Southern California based on multiparameter optimization techniques. Prototypes of this system have been constructed and evaluated at the Center for Devices and Radiological Health. The digital radiography system is based on the Fuji 9000 computed radiography (CR) system which uses a storage phosphor imaging plate as the receptor. High resolution plates (HR-V) are used in this study. Dual-energy is one technique to reduce the structured noise associated with the complexity of the background of normal anatomy surrounding a lesion. This can be done by taking the advantage of the x-ray attenuation characteristics of two different structures such as soft tissue and bone in chest radiography. We have applied this technique to the detection of microcalcifications in mammography. The overall system performance based on this technique is evaluated. Results presented are based on the evaluation of phantom images.

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

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

Using MRI to detect and differentiate calcium oxalate and calcium hydroxyapatite crystals in air-bubble-free phantom

PubMed Central

Mustafi, Devkumar; Fan, Xiaobing; Peng, Bo; Foxley, Sean; Palgen, Jeremy; Newstead, Gillian M.

2015-01-01

Calcium oxalate (CaOX) crystals and calcium hydroxyapatite (CaHA) crystals were commonly associated with breast benign and malignant lesions, respectively. In this research, CaOX (n = 6) and CaHA (n = 6) crystals in air-bubble-free agarose phantom were studied and characterized by using MRI at 9.4 Tesla scanner. Calcium micro-crystals sizes ranged from 200 – 500 microns were made with either 99% pure CaOX or CaHA powder and embedded in agar to mimic the dimensions and calcium content of breast microcalcifications in vivo. MRI data were acquired with high spatial resolution T2-weighted (T2W) images and gradient echo images with five different echo times (TEs). The crystals areas were determined by setting the threshold relative to agarose signal. The ratio of crystals areas were calculated by the measurements from gradient echo images divided by T2W images. Then the ratios as a function of TE were fitted with the radical function. The results showed that the blooming artifacts due to magnetic susceptibility between agar and CaHA crystals were more than twice as large as the susceptibility in CaOX crystals (p < 0.05). In addition, larger bright rings were observed on gradient echo images around CaHA crystals compared to CaOX crystals. Our results suggest that MRI may provide useful information regarding breast microcalcifications by evaluating the apparent area of crystals ratios obtained between gradient echo and T2W images. PMID:26392170

Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings.

PubMed

Mordang, Jan-Jurre; Gubern-Mérida, Albert; Bria, Alessandro; Tortorella, Francesco; den Heeten, Gerard; Karssemeijer, Nico

2017-04-01

Computer-aided detection (CADe) systems for mammography screening still mark many false positives. This can cause radiologists to lose confidence in CADe, especially when many false positives are obviously not suspicious to them. In this study, we focus on obvious false positives generated by microcalcification detection algorithms. We aim at reducing the number of obvious false-positive findings by adding an additional step in the detection method. In this step, a multiclass machine learning method is implemented in which dedicated classifiers learn to recognize the patterns of obvious false-positive subtypes that occur most frequently. The method is compared to a conventional two-class approach, where all false-positive subtypes are grouped together in one class, and to the baseline CADe system without the new false-positive removal step. The methods are evaluated on an independent dataset containing 1,542 screening examinations of which 80 examinations contain malignant microcalcifications. Analysis showed that the multiclass approach yielded a significantly higher sensitivity compared to the other two methods (P < 0.0002). At one obvious false positive per 100 images, the baseline CADe system detected 61% of the malignant examinations, while the systems with the two-class and multiclass false-positive reduction step detected 73% and 83%, respectively. Our study showed that by adding the proposed method to a CADe system, the number of obvious false positives can decrease significantly (P < 0.0002). © 2017 American Association of Physicists in Medicine.

A new texture descriptor based on local micro-pattern for detection of architectural distortion in mammographic images

NASA Astrophysics Data System (ADS)

de Oliveira, Helder C. R.; Moraes, Diego R.; Reche, Gustavo A.; Borges, Lucas R.; Catani, Juliana H.; de Barros, Nestor; Melo, Carlos F. E.; Gonzaga, Adilson; Vieira, Marcelo A. C.

2017-03-01

This paper presents a new local micro-pattern texture descriptor for the detection of Architectural Distortion (AD) in digital mammography images. AD is a subtle contraction of breast parenchyma that may represent an early sign of breast cancer. Due to its subtlety and variability, AD is more difficult to detect compared to microcalcifications and masses, and is commonly found in retrospective evaluations of false-negative mammograms. Several computer-based systems have been proposed for automatic detection of AD, but their performance are still unsatisfactory. The proposed descriptor, Local Mapped Pattern (LMP), is a generalization of the Local Binary Pattern (LBP), which is considered one of the most powerful feature descriptor for texture classification in digital images. Compared to LBP, the LMP descriptor captures more effectively the minor differences between the local image pixels. Moreover, LMP is a parametric model which can be optimized for the desired application. In our work, the LMP performance was compared to the LBP and four Haralick's texture descriptors for the classification of 400 regions of interest (ROIs) extracted from clinical mammograms. ROIs were selected and divided into four classes: AD, normal tissue, microcalcifications and masses. Feature vectors were used as input to a multilayer perceptron neural network, with a single hidden layer. Results showed that LMP is a good descriptor to distinguish AD from other anomalies in digital mammography. LMP performance was slightly better than the LBP and comparable to Haralick's descriptors (mean classification accuracy = 83%).

Validation of a digital mammographic unit model for an objective and highly automated clinical image quality assessment.

PubMed

Perez-Ponce, Hector; Daul, Christian; Wolf, Didier; Noel, Alain

2013-08-01

In mammography, image quality assessment has to be directly related to breast cancer indicator (e.g. microcalcifications) detectability. Recently, we proposed an X-ray source/digital detector (XRS/DD) model leading to such an assessment. This model simulates very realistic contrast-detail phantom (CDMAM) images leading to gold disc (representing microcalcifications) detectability thresholds that are very close to those of real images taken under the simulated acquisition conditions. The detection step was performed with a mathematical observer. The aim of this contribution is to include human observers into the disc detection process in real and virtual images to validate the simulation framework based on the XRS/DD model. Mathematical criteria (contrast-detail curves, image quality factor, etc.) are used to assess and to compare, from the statistical point of view, the cancer indicator detectability in real and virtual images. The quantitative results given in this paper show that the images simulated by the XRS/DD model are useful for image quality assessment in the case of all studied exposure conditions using either human or automated scoring. Also, this paper confirms that with the XRS/DD model the image quality assessment can be automated and the whole time of the procedure can be drastically reduced. Compared to standard quality assessment methods, the number of images to be acquired is divided by a factor of eight. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

Single Cell Genome Amplification Accelerates Identification of the Apratoxin Biosynthetic Pathway from a Complex Microbial Assemblage

PubMed Central

Grindberg, Rashel V.; Ishoey, Thomas; Brinza, Dumitru; Esquenazi, Eduardo; Coates, R. Cameron; Liu, Wei-ting; Gerwick, Lena; Dorrestein, Pieter C.; Pevzner, Pavel; Lasken, Roger; Gerwick, William H.

2011-01-01

Filamentous marine cyanobacteria are extraordinarily rich sources of structurally novel, biomedically relevant natural products. To understand their biosynthetic origins as well as produce increased supplies and analog molecules, access to the clustered biosynthetic genes that encode for the assembly enzymes is necessary. Complicating these efforts is the universal presence of heterotrophic bacteria in the cell wall and sheath material of cyanobacteria obtained from the environment and those grown in uni-cyanobacterial culture. Moreover, the high similarity in genetic elements across disparate secondary metabolite biosynthetic pathways renders imprecise current gene cluster targeting strategies and contributes sequence complexity resulting in partial genome coverage. Thus, it was necessary to use a dual-method approach of single-cell genomic sequencing based on multiple displacement amplification (MDA) and metagenomic library screening. Here, we report the identification of the putative apratoxin. A biosynthetic gene cluster, a potent cancer cell cytotoxin with promise for medicinal applications. The roughly 58 kb biosynthetic gene cluster is composed of 12 open reading frames and has a type I modular mixed polyketide synthase/nonribosomal peptide synthetase (PKS/NRPS) organization and features loading and off-loading domain architecture never previously described. Moreover, this work represents the first successful isolation of a complete biosynthetic gene cluster from Lyngbya bouillonii, a tropical marine cyanobacterium renowned for its production of diverse bioactive secondary metabolites. PMID:21533272

Validation of MALDI-TOF MS for rapid classification and identification of lactic acid bacteria, with a focus on isolates from traditional fermented foods in Northern Vietnam.

PubMed

Doan, N T L; Van Hoorde, K; Cnockaert, M; De Brandt, E; Aerts, M; Le Thanh, B; Vandamme, P

2012-10-01

To evaluate the potential use of MALDI-TOF MS for fast and reliable classification and identification of lactic acid bacteria (LAB) from traditional fermented foods. A total of 119 strains of LAB from fermented meat (nem chua) were analysed with both (GTG)(5)-PCR fingerprinting and MALDI-TOF MS. Cluster analysis of the profiles revealed five species represented by a single isolate both in (GTG)(5)-PCR and in MALDI-TOF MS; five species grouped alike for (GTG)(5)-PCR and for MALDI-TOF MS; however, differences in minimal similarity between the delineated (GTG)(5)-PCR and MALDI-TOF MS clusters could be observed; three species showed more heterogeneity in their MALDI-TOF MS profiles compared to their (GTG)(5)-PCR profiles; two species, each represented by a single MALDI-TOF cluster, were subdivided in the corresponding (GTG)(5)-PCR dendrogram. As proof of the identification potential of MALDI-TOF MS, LAB diversity from one fermented mustard sample was analysed using MALDI-TOF MS. PheS gene sequencing was used for validation. MALDI-TOF MS is a powerful, fast, reliable and cost-effective technique for the identification of LAB associated with the production of fermented foods. Food LAB can be identified using MALDI-TOF MS, and its application could possibly be extended to other food matrices and/or other food-derived micro-organisms. © 2012 The Authors. Letters in Applied Microbiology © 2012 The Society for Applied Microbiology.

Study of cluster behavior in the riser of CFB by the DSMC method

NASA Astrophysics Data System (ADS)

Liu, H. P.; Liu, D. Y.; Liu, H.

2010-03-01

The flow behaviors of clusters in the riser of a two-dimensional (2D) circulating fluidized bed was numerically studied based on the Euler-Lagrangian approach. Gas turbulence was modeled by means of Large Eddy Simulation (LES). Particle collision was modeled by means of the direct simulation Monte Carlo (DSMC) method. Clusters' hydrodynamic characteristics are obtained using a cluster identification method proposed by sharrma et al. (2000). The descending clusters near the wall region and the up- and down-flowing clusters in the core were studied separately due to their different flow behaviors. The effects of superficial gas velocity on the cluster behavior were analyzed. Simulated results showed that near wall clusters flow downward and the descent velocity is about -45 cm/s. The occurrence frequency of the up-flowing cluster is higher than that of down-flowing cluster in the core of riser. With the increase of superficial gas velocity, the solid concentration and occurrence frequency of clusters decrease, while the cluster axial velocity increase. Simulated results were in agreement with experimental data. The stochastic method used in present paper is feasible for predicting the cluster flow behavior in CFBs.

New natural products isolated from Metarhizium robertsii ARSEF 23 by chemical screening and identification of the gene cluster through engineered biosynthesis in Aspergillus nidulans A1145.

PubMed

Kato, Hiroki; Tsunematsu, Yuta; Yamamoto, Tsuyoshi; Namiki, Takuya; Kishimoto, Shinji; Noguchi, Hiroshi; Watanabe, Kenji

2016-07-01

To rapidly identify novel natural products and their associated biosynthetic genes from underutilized and genetically difficult-to-manipulate microbes, we developed a method that uses (1) chemical screening to isolate novel microbial secondary metabolites, (2) bioinformatic analyses to identify a potential biosynthetic gene cluster and (3) heterologous expression of the genes in a convenient host to confirm the identity of the gene cluster and the proposed biosynthetic mechanism. The chemical screen was achieved by searching known natural product databases with data from liquid chromatographic and high-resolution mass spectrometric analyses collected on the extract from a target microbe culture. Using this method, we were able to isolate two new meroterpenes, subglutinols C (1) and D (2), from an entomopathogenic filamentous fungus Metarhizium robertsii ARSEF 23. Bioinformatics analysis of the genome allowed us to identify a gene cluster likely to be responsible for the formation of subglutinols. Heterologous expression of three genes from the gene cluster encoding a polyketide synthase, a prenyltransferase and a geranylgeranyl pyrophosphate synthase in Aspergillus nidulans A1145 afforded an α-pyrone-fused uncyclized diterpene, the expected intermediate of the subglutinol biosynthesis, thereby confirming the gene cluster to be responsible for the subglutinol biosynthesis. These results indicate the usefulness of our methodology in isolating new natural products and identifying their associated biosynthetic gene cluster from microbes that are not amenable to genetic manipulation. Our method should facilitate the natural product discovery efforts by expediting the identification of new secondary metabolites and their associated biosynthetic genes from a wider source of microbes.

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

D.E.--Fashion Merchandising. Fiber and Fabric Identification. Kit No. 46. Instructor's Manual [and] Student Learning Activity Guide.

ERIC Educational Resources Information Center

Vaughan, Ellen C.

An instructor's manual and student activity guide on fiber and fabric identification are provided in this set of prevocational education materials which focuses on the vocational area of distributive education (fashion merchandising). (This set of materials is one of ninety-two prevocational education sets arranged around a cluster of seven…

Identification of Neoceratitis asiatica (Becker) (Diptera: Tephritidae) based on morphological characteristics and DNA barcode.

PubMed

Guo, Shaokun; He, Jia; Zhao, Zihua; Liu, Lijun; Gao, Liyuan; Wei, Shuhua; Guo, Xiaoyu; Zhang, Rong; Li, Zhihong

2017-12-12

Neoceratitis asiatica (Becker), which especially infests wolfberry (Lycium barbarum L.), could cause serious economic losses every year in China, especially to organic wolfberry production. In some important wolfberry plantings, it is difficult and time-consuming to rear the larvae or pupae to adults for morphological identification. Molecular identification based on DNA barcode is a solution to the problem. In this study, 15 samples were collected from Ningxia, China. Among them, five adults were identified according to their morphological characteristics. The utility of mitochondrial DNA (mtDNA) cytochrome c oxidase I (COI) gene sequence as DNA barcode in distinguishing N. asiatica was evaluated by analysing Kimura 2-parameter distances and phylogenetic trees. There were significant differences between intra-specific and inter-specific genetic distances according to the barcoding gap analysis. The uncertain larval and pupal samples were within the same cluster as N. asiatica adults and formed sister cluster to N. cyanescens. A combination of morphological and molecular methods enabled accurate identification of N. asiatica. This is the first study using DNA barcode to identify N. asiatica and the obtained DNA sequences will be added to the DNA barcode database.

Modified algorithm for mineral identification in LWIR hyperspectral imagery

NASA Astrophysics Data System (ADS)

Yousefi, Bardia; Sojasi, Saeed; Liaigre, Kévin; Ibarra Castanedo, Clemente; Beaudoin, Georges; Huot, François; Maldague, Xavier P. V.; Chamberland, Martin

2017-05-01

The applications of hyperspectral infrared imagery in the different fields of research are significant and growing. It is mainly used in remote sensing for target detection, vegetation detection, urban area categorization, astronomy and geological applications. The geological applications of this technology mainly consist in mineral identification using in airborne or satellite imagery. We address a quantitative and qualitative assessment of mineral identification in the laboratory conditions. We strive to identify nine different mineral grains (Biotite, Diopside, Epidote, Goethite, Kyanite, Scheelite, Smithsonite, Tourmaline, Quartz). A hyperspectral camera in the Long Wave Infrared (LWIR, 7.7-11.8 ) with a LW-macro lens providing a spatial resolution of 100 μm, an infragold plate, and a heating source are the instruments used in the experiment. The proposed algorithm clusters all the pixel-spectra in different categories. Then the best representatives of each cluster are chosen and compared with the ASTER spectral library of JPL/NASA through spectral comparison techniques, such as Spectral angle mapper (SAM) and Normalized Cross Correlation (NCC). The results of the algorithm indicate significant computational efficiency (more than 20 times faster) as compared to previous algorithms and have shown a promising performance for mineral identification.

Comparison of expression of secondary metabolite biosynthesis cluster genes in Aspergillus flavus, A. parasiticus, and A. oryzae.

PubMed

Ehrlich, Kenneth C; Mack, Brian M

2014-06-23

Fifty six secondary metabolite biosynthesis gene clusters are predicted to be in the Aspergillus flavus genome. In spite of this, the biosyntheses of only seven metabolites, including the aflatoxins, kojic acid, cyclopiazonic acid and aflatrem, have been assigned to a particular gene cluster. We used RNA-seq to compare expression of secondary metabolite genes in gene clusters for the closely related fungi A. parasiticus, A. oryzae, and A. flavus S and L sclerotial morphotypes. The data help to refine the identification of probable functional gene clusters within these species. Our results suggest that A. flavus, a prevalent contaminant of maize, cottonseed, peanuts and tree nuts, is capable of producing metabolites which, besides aflatoxin, could be an underappreciated contributor to its toxicity.

Comparison of Expression of Secondary Metabolite Biosynthesis Cluster Genes in Aspergillus flavus, A. parasiticus, and A. oryzae

PubMed Central

Ehrlich, Kenneth C.; Mack, Brian M.

2014-01-01

Fifty six secondary metabolite biosynthesis gene clusters are predicted to be in the Aspergillus flavus genome. In spite of this, the biosyntheses of only seven metabolites, including the aflatoxins, kojic acid, cyclopiazonic acid and aflatrem, have been assigned to a particular gene cluster. We used RNA-seq to compare expression of secondary metabolite genes in gene clusters for the closely related fungi A. parasiticus, A. oryzae, and A. flavus S and L sclerotial morphotypes. The data help to refine the identification of probable functional gene clusters within these species. Our results suggest that A. flavus, a prevalent contaminant of maize, cottonseed, peanuts and tree nuts, is capable of producing metabolites which, besides aflatoxin, could be an underappreciated contributor to its toxicity. PMID:24960201

Prediction, Detection, and Validation of Isotope Clusters in Mass Spectrometry Data

PubMed Central

Treutler, Hendrik; Neumann, Steffen

2016-01-01

Mass spectrometry is a key analytical platform for metabolomics. The precise quantification and identification of small molecules is a prerequisite for elucidating the metabolism and the detection, validation, and evaluation of isotope clusters in LC-MS data is important for this task. Here, we present an approach for the improved detection of isotope clusters using chemical prior knowledge and the validation of detected isotope clusters depending on the substance mass using database statistics. We find remarkable improvements regarding the number of detected isotope clusters and are able to predict the correct molecular formula in the top three ranks in 92% of the cases. We make our methodology freely available as part of the Bioconductor packages xcms version 1.50.0 and CAMERA version 1.30.0. PMID:27775610

Digital Signal Processing Based on a Clustering Algorithm for Ir/Au TES Microcalorimeter

NASA Astrophysics Data System (ADS)

Zen, N.; Kunieda, Y.; Takahashi, H.; Hiramoto, K.; Nakazawa, M.; Fukuda, D.; Ukibe, M.; Ohkubo, M.

2006-02-01

In recent years, cryogenic microcalorimeters using their superconducting transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy resolution of superconducting transition edge sensors (TES), several correction methods have been developed. Among them, a clustering method based on digital signal processing has recently been proposed. In this paper, we applied the clustering method to Ir/Au bilayer TES. This method resulted in almost a 10% improvement in the energy resolution. Conversely, from the point of view of imaging X-ray spectroscopy, we applied the clustering method to pixellated Ir/Au-TES devices. We will thus show how a clustering method which sorts signals by their shapes is also useful for position identification

Toda Systems, Cluster Characters, and Spectral Networks

NASA Astrophysics Data System (ADS)

Williams, Harold

2016-11-01

We show that the Hamiltonians of the open relativistic Toda system are elements of the generic basis of a cluster algebra, and in particular are cluster characters of nonrigid representations of a quiver with potential. Using cluster coordinates defined via spectral networks, we identify the phase space of this system with the wild character variety related to the periodic nonrelativistic Toda system by the wild nonabelian Hodge correspondence. We show that this identification takes the relativistic Toda Hamiltonians to traces of holonomies around a simple closed curve. In particular, this provides nontrivial examples of cluster coordinates on SL n -character varieties for n > 2 where canonical functions associated to simple closed curves can be computed in terms of quivers with potential, extending known results in the SL 2 case.

Secondary ion mass spectra of gold super clusters up to 140000 Dalton

NASA Astrophysics Data System (ADS)

Feld, H.; Leute, A.; Rading, D.; Benninghoven, A.; Schmid, G.

1990-03-01

The bombardment of a two-shell gold complex (Au55(PPh3)12Cl6) with 10 keV Xe+-ions results in the formation of secondary ion masses up to 140000 u. These are by far the largest secondary ions observed under primary particle bombardment. The detection and identification of these ions with a Time-Of-Flight Secondary Ion Mass Spectrometer (TOF-SIMS) gives important information about the behavior of naked full-shell clusters. Au13 particles, generated from the Au55 cluster, serve as building blocks for a series of super-clusters up to (Au13)55. The results for keV-ion bombardment are compared to those for MeV-ion bombardment.

The effect of billboard design specifications on driving: A pilot study.

PubMed

Marciano, Hadas; Setter, Pe'erly

2017-07-01

Decades of research on the effects of advertising billboards on road accident rates, driver performance, and driver visual scanning behavior, has produced no conclusive findings. We suggest that road safety researchers should shift their focus and attempt to identify the billboard characteristics that are most distracting to drivers. This line of research may produce concrete guidelines for permissible billboards that would be likely to reduce the influence of the billboards on road safety. The current study is a first step towards this end. A pool of 161 photos of real advertising billboards was used as stimuli within a triple task paradigm designed to simulate certain components of driving. Each trial consisted of one ongoing tracking task accompanied by two additional concurrent tasks: (1) billboard observation task; and (2) circle color change identification task. Five clusters of billboards, identified by conducting a cluster analysis of their graphic content, were used as a within variable in one-way ANOVAs conducted on performance level data collected from the multiple tasks. Cluster 5, labeled Loaded Billboards, yielded significantly deteriorated performance on the tracking task. Cluster 4, labeled Graphical Billboards, yielded deteriorated performance primarily on the color change identification task. Cluster 3, labeled Minimal Billboards, had no effect on any of these tasks. We strongly recommend that these clusters be systematically explored in experiments involving additional real driving settings, such as driving simulators and field studies. This will enable validation of the current results and help incorporate them into real driving situations. Copyright © 2017. Published by Elsevier Ltd.

Technical Considerations for Red Marking Ink Use When Interpreting Specimen Radiographs: Case Report.

PubMed

Brice, Matthew E; Gossweiler, Marisa; Bennett, Larry

2017-03-01

Artifacts are universal across all imaging modalities, varying in their conspicuity and significance. In this report three patients with pathology-proven breast cancer who had densities masquerading as microcalcifications at the resection margins of the lumpectomy specimens, but had negative microscopic margins, will be discussed. It was determined that these pseudocalcifications were the result of ink precipitates from a commonly utilized tissue marking dye. This artifact was further evaluated and reproduced by utilizing a boneless chicken breast as a phantom. © RSNA, 2016.

Flat epithelial atypia of the breast.

PubMed

Nasser, Selim M

2009-01-01

"Flat epithelial atypia" is the adopted term by the WHO working group on breast tumor referring to an early neoplastic breast lesion affecting the terminal duct-lobular units. Pathologists have described this lesion under a variety of names including columnar cell lesions and low-grade clinging carcinoma in situ. It is usually encountered on breast biopsies performed for mammographically-identified microcalcifications. Because of its relatively frequent association with carcinomas, its recognition in biopsy specimens is important. This review will focus on the histopathologic features, differential diagnosis, biologic potential, clinical significance and management of this lesion.

Congenital Zika Virus Infection Induces Severe Spinal Cord Injury.

PubMed

Ramalho, Fernando S; Yamamoto, Aparecida Y; da Silva, Luis L; Figueiredo, Luiz T M; Rocha, Lenaldo B; Neder, Luciano; Teixeira, Sara R; Apolinário, Letícia A; Ramalho, Leandra N Z; Silva, Deisy M; Coutinho, Conrado M; Melli, Patrícia P; Augusto, Marlei J; Santoro, Ligia B; Duarte, Geraldo; Mussi-Pinhata, Marisa M

2017-08-15

We report 2 fatal cases of congenital Zika virus (ZIKV) infection. Brain anomalies, including atrophy of the cerebral cortex and brainstem, and cerebellar aplasia were observed. The spinal cord showed architectural distortion, severe neuronal loss, and microcalcifications. The ZIKV proteins and flavivirus-like particles were detected in cytoplasm of spinal neurons, and spinal cord samples were positive for ZIKV RNA. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Two worlds collide: Image analysis methods for quantifying structural variation in cluster molecular dynamics

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

Steenbergen, K. G., E-mail: kgsteen@gmail.com; Gaston, N.

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement formore » a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.« less

Hybrid approach of selecting hyperparameters of support vector machine for regression.

PubMed

Jeng, Jin-Tsong

2006-06-01

To select the hyperparameters of the support vector machine for regression (SVR), a hybrid approach is proposed to determine the kernel parameter of the Gaussian kernel function and the epsilon value of Vapnik's epsilon-insensitive loss function. The proposed hybrid approach includes a competitive agglomeration (CA) clustering algorithm and a repeated SVR (RSVR) approach. Since the CA clustering algorithm is used to find the nearly "optimal" number of clusters and the centers of clusters in the clustering process, the CA clustering algorithm is applied to select the Gaussian kernel parameter. Additionally, an RSVR approach that relies on the standard deviation of a training error is proposed to obtain an epsilon in the loss function. Finally, two functions, one real data set (i.e., a time series of quarterly unemployment rate for West Germany) and an identification of nonlinear plant are used to verify the usefulness of the hybrid approach.

Iterative Stable Alignment and Clustering of 2D Transmission Electron Microscope Images

PubMed Central

Yang, Zhengfan; Fang, Jia; Chittuluru, Johnathan; Asturias, Francisco J.; Penczek, Pawel A.

2012-01-01

SUMMARY Identification of homogeneous subsets of images in a macromolecular electron microscopy (EM) image data set is a critical step in single-particle analysis. The task is handled by iterative algorithms, whose performance is compromised by the compounded limitations of image alignment and K-means clustering. Here we describe an approach, iterative stable alignment and clustering (ISAC) that, relying on a new clustering method and on the concepts of stability and reproducibility, can extract validated, homogeneous subsets of images. ISAC requires only a small number of simple parameters and, with minimal human intervention, can eliminate bias from two-dimensional image clustering and maximize the quality of group averages that can be used for ab initio three-dimensional structural determination and analysis of macromolecular conformational variability. Repeated testing of the stability and reproducibility of a solution within ISAC eliminates heterogeneous or incorrect classes and introduces critical validation to the process of EM image clustering. PMID:22325773

Computational gene expression profiling under salt stress reveals patterns of co-expression

PubMed Central

Sanchita; Sharma, Ashok

2016-01-01

Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

Two worlds collide: image analysis methods for quantifying structural variation in cluster molecular dynamics.

PubMed

Steenbergen, K G; Gaston, N

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

Fourier transform infrared isotopic studies on novel metal-carbon clusters trapped in argon matrix environments

NASA Astrophysics Data System (ADS)

Bates, Sarah Anne

The characterization of the vibrational spectra and structures of small metal-carbon (MnCm) clusters is important to the detection of astrophysical species and may elucidate the bonding and growth mechanisms of metallocarbohedrenes, or metcars. Additionally, transition metal-carbon clusters have applications in modern materials science as catalysts for nanomaterial formation. A new experimental apparatus for the preparation of MnC m clusters has been designed and constructed, incorporating a new closed cycle refrigeration system, a chamber for the deposition of samples, associated vacuum system, and a fully automated mechanism to simultaneously translate and rotate carbon and metal rods during laser ablation. A new technique for fabricating carbon rods has been developed to expedite carbon rod production and to facilitate the formation of the MnC m clusters studied. Fourier transform infrared (FTIR) investigations have been done for the first time on transition metal-carbon clusters. The molecular clusters were formed by trapping the products from dual laser ablation of metal and carbon rods in solid Ar at ˜10 K. Comparing FTIR measurements of vibrational fundamentals and 13C isotopic shifts with the predictions of density functional theory (DFT) calculations has enabled the identification of five novel metal-carbon molecules, establishing their ground state geometries and permitting the assignment of vibrational fundamentals, including the nu 1(sigma) modes of (5pi) linear CrC3, ( 2Delta) linear CoC3, and (2pi) linear CuC3 at 1789.5, 1918.2, and 1830.0 cm-1, respectively, the nu3(sigmau)=1624.0 and nu 4(sigmau)=528.3 cm-1 modes of (1Sigmag+) linear AlC3Al, and the nu2(sigma)=1210.9 cm -1 mode of linear AlC3. Evidence for the tentative identification of the nu1(a1)=1554.3 cm-1 mode of (3B1) fanlike CrC4 and the nu4(sigmau)=1987.3 cm-1 mode of (1Sigmag +) linear AlC4Al is also presented. All FTIR measurements of vibrational frequencies and 13C shifts are in very good agreement with DFT predictions, resulting in the first identification of vibrational fundamentals and the characterization of molecular geometries for these species specifically and for transition metal-carbon clusters in general. A catalog of potential VnCm absorptions has also been developed to aid in future vanadium-carbon studies.

Mass spectrometric identification of intermediates in the O2-driven [4Fe-4S] to [2Fe-2S] cluster conversion in FNR

PubMed Central

Crack, Jason C.; Thomson, Andrew J.

2017-01-01

The iron-sulfur cluster containing protein Fumarate and Nitrate Reduction (FNR) is the master regulator for the switch between anaerobic and aerobic respiration in Escherichia coli and many other bacteria. The [4Fe-4S] cluster functions as the sensory module, undergoing reaction with O2 that leads to conversion to a [2Fe-2S] form with loss of high-affinity DNA binding. Here, we report studies of the FNR cluster conversion reaction using time-resolved electrospray ionization mass spectrometry. The data provide insight into the reaction, permitting the detection of cluster conversion intermediates and products, including a [3Fe-3S] cluster and persulfide-coordinated [2Fe-2S] clusters [[2Fe-2S](S)n, where n = 1 or 2]. Analysis of kinetic data revealed a branched mechanism in which cluster sulfide oxidation occurs in parallel with cluster conversion and not as a subsequent, secondary reaction to generate [2Fe-2S](S)n species. This methodology shows great potential for broad application to studies of protein cofactor–small molecule interactions. PMID:28373574

A Proteomic Approach to Investigating Gene Cluster Expression and Secondary Metabolite Functionality in Aspergillus fumigatus

PubMed Central

Owens, Rebecca A.; Hammel, Stephen; Sheridan, Kevin J.; Jones, Gary W.; Doyle, Sean

2014-01-01

A combined proteomics and metabolomics approach was utilised to advance the identification and characterisation of secondary metabolites in Aspergillus fumigatus. Here, implementation of a shotgun proteomic strategy led to the identification of non-redundant mycelial proteins (n = 414) from A. fumigatus including proteins typically under-represented in 2-D proteome maps: proteins with multiple transmembrane regions, hydrophobic proteins and proteins with extremes of molecular mass and pI. Indirect identification of secondary metabolite cluster expression was also achieved, with proteins (n = 18) from LaeA-regulated clusters detected, including GliT encoded within the gliotoxin biosynthetic cluster. Biochemical analysis then revealed that gliotoxin significantly attenuates H2O2-induced oxidative stress in A. fumigatus (p>0.0001), confirming observations from proteomics data. A complementary 2-D/LC-MS/MS approach further elucidated significantly increased abundance (p<0.05) of proliferating cell nuclear antigen (PCNA), NADH-quinone oxidoreductase and the gliotoxin oxidoreductase GliT, along with significantly attenuated abundance (p<0.05) of a heat shock protein, an oxidative stress protein and an autolysis-associated chitinase, when gliotoxin and H2O2 were present, compared to H2O2 alone. Moreover, gliotoxin exposure significantly reduced the abundance of selected proteins (p<0.05) involved in de novo purine biosynthesis. Significantly elevated abundance (p<0.05) of a key enzyme, xanthine-guanine phosphoribosyl transferase Xpt1, utilised in purine salvage, was observed in the presence of H2O2 and gliotoxin. This work provides new insights into the A. fumigatus proteome and experimental strategies, plus mechanistic data pertaining to gliotoxin functionality in the organism. PMID:25198175

Sequence-related amplified polymorphism (SRAP) marker as a new method for identification of endophytic fungi from Taxus.

PubMed

Ren, Na; Liu, Jiajia; Yang, Dongliang; Chen, Jianhua; Luan, Mingbao; Hong, Juan

2012-01-01

A total of 20 endophytic fungi stains were classified into four groups using traditional morphological identification method, and were studied for genetic diversity by sequence-related amplified polymorphism (SRAP) technique. Genomic DNA (deoxyribonucleic acid) of these strains was extracted with CTAB method. SRAP analysis was done with 24 pairs of primers. All strains could be uniquely distinguished with 584 bands and 446 polymorphism bands which generated 76.4% of polymorphic ratio. Unweighted pair-group method with arithmetical averages cluster analysis enabled construction of a dendrogram for estimating genetic distances between different strains. All strains, which were just divided into four groups by traditional morphology identification, were clustered into four major groups at GS = 0.603 and further separated into eight sub-groups at GS = 0.921. Dendrogram also revealed a large genetic variation in 20 strains; different primer combinations allowed them distinctly distinguished one from others with relatively low genetic similarity. The results show that the SRAP technology is more efficient than traditional morphology identification. It is found that SRAP markers could more really reflect the genetic diversity of endophytic fungi strains from Taxus, and also could be used as a method for identification of endophytic fungi from Taxus. It also suggests that SRAP can be used to establish foundation for further screening of taxol-producing endophytic fungi strains which can produce high levels of paclitaxel.

A genome-wide analysis of the flax (Linum usitatissimum L.) dirigent protein family: from gene identification and evolution to differential regulation

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

Corbin, Cyrielle; Drouet, Samantha; Markulin, Lucija

Identification of DIR encoding genes in flax genome. Analysis of phylogeny, gene/protein structures and evolution. Identification of new conserved motifs linked to biochemical functions. Investigation of spatio-temporal gene expression and response to stress. Dirigent proteins (DIRs) were discovered during 8-8' lignan biosynthesis studies, through identification of stereoselective coupling to afford either (+)- or (-)-pinoresinols from E-coniferyl alcohol. DIRs are also involved or potentially involved in terpenoid, allyl/propenyl phenol lignan, pterocarpan and lignin biosynthesis. DIRs have very large multigene families in different vascular plants including flax, with most still of unknown function. DIR studies typically focus on a small subset ofmore » genes and identification of biochemical/physiological functions. Herein, a genome-wide analysis and characterization of the predicted flax DIR 44-membered multigene family was performed, this species being a rich natural grain source of 8-8' linked secoisolariciresinol-derived lignan oligomers. All predicted DIR sequences, including their promoters, were analyzed together with their public gene expression datasets. Expression patterns of selected DIRs were examined using qPCR, as well as through clustering analysis of DIR gene expression. These analyses further implicated roles for specific DIRs in (-)-pinoresinol formation in seed-coats, as well as (+)-pinoresinol in vegetative organs and/or specific responses to stress. Phylogeny and gene expression analysis segregated flax DIRs into six distinct clusters with new cluster-specific motifs identified. We propose that these findings can serve as a foundation to further systematically determine functions of DIRs, i.e. other than those already known in lignan biosynthesis in flax and other species. Given the differential expression profiles and inducibility of the flax DIR family, we provisionally propose that some DIR genes of unknown function could be involved in different aspects of secondary cell wall biosynthesis and plant defense.« less

A genome-wide analysis of the flax (Linum usitatissimum L.) dirigent protein family: from gene identification and evolution to differential regulation.

PubMed

Corbin, Cyrielle; Drouet, Samantha; Markulin, Lucija; Auguin, Daniel; Lainé, Éric; Davin, Laurence B; Cort, John R; Lewis, Norman G; Hano, Christophe

2018-05-01

Identification of DIR encoding genes in flax genome. Analysis of phylogeny, gene/protein structures and evolution. Identification of new conserved motifs linked to biochemical functions. Investigation of spatio-temporal gene expression and response to stress. Dirigent proteins (DIRs) were discovered during 8-8' lignan biosynthesis studies, through identification of stereoselective coupling to afford either (+)- or (-)-pinoresinols from E-coniferyl alcohol. DIRs are also involved or potentially involved in terpenoid, allyl/propenyl phenol lignan, pterocarpan and lignin biosynthesis. DIRs have very large multigene families in different vascular plants including flax, with most still of unknown function. DIR studies typically focus on a small subset of genes and identification of biochemical/physiological functions. Herein, a genome-wide analysis and characterization of the predicted flax DIR 44-membered multigene family was performed, this species being a rich natural grain source of 8-8' linked secoisolariciresinol-derived lignan oligomers. All predicted DIR sequences, including their promoters, were analyzed together with their public gene expression datasets. Expression patterns of selected DIRs were examined using qPCR, as well as through clustering analysis of DIR gene expression. These analyses further implicated roles for specific DIRs in (-)-pinoresinol formation in seed-coats, as well as (+)-pinoresinol in vegetative organs and/or specific responses to stress. Phylogeny and gene expression analysis segregated flax DIRs into six distinct clusters with new cluster-specific motifs identified. We propose that these findings can serve as a foundation to further systematically determine functions of DIRs, i.e. other than those already known in lignan biosynthesis in flax and other species. Given the differential expression profiles and inducibility of the flax DIR family, we provisionally propose that some DIR genes of unknown function could be involved in different aspects of secondary cell wall biosynthesis and plant defense.

Selection of fragrance for cosmetic cream containing olive oil.

PubMed

Parente, María Emma; Gámbaro, Adriana; Boinbaser, Lucía; Roascio, Antonella

2014-01-01

Perceptions of essences for potential use in the development of a line of cosmetic emulsions containing olive oil were studied. Six cream samples prepared with six essences selected in a preliminary study were evaluated for overall liking and intention to purchase by a 63-women sample. A check-all-that-apply (CATA) question consisting of 32 terms was used to gather information about consumer perceptions of fragrance, affective associations, effects on the skin, price, target market, zones of application, and occasions of use. Hierarchical cluster analysis led to the identification of two consumer clusters with different frequency of use of face creams. The two clusters assigned different overall liking scores to the samples and used the CATA terms differently to describe them. A fragrance with jasmine as its principal note was selected for further development of cosmetic creams, as it was awarded the highest overall liking scores by respondents of the two clusters, and was significantly associated with cosmetic features including nourishing, moisturizing, softening, with a delicious and mild smell, and with a natural image, as well as being considered suitable for face and body creams. The use of CATA questions enabled the rapid identification of attributes associated by respondents with a cosmetic cream's fragrance, in addition to contributing relevant information for the definition of marketing and communication strategies.

Identification of genetically diverse genotypes for photoperiod insensitivity in soybean using RAPD markers.

PubMed

Singh, R K; Bhatia, V S; Yadav, Sanjeev; Athale, Rashmi; Lakshmi, N; Guruprasad, K N; Chauhan, G S

2008-10-01

Most of the Indian soybean varieties were found to be highly sensitive to photoperiod, which limits their cultivation in only localized area. Identification of genetically diverse source of photoperiod insensitive would help to broaden the genetic base for this trait. Present study was undertaken with RAPD markers for genetic diversity estimation in 44 accessions of soybean differing in response to photoperiod sensitivity. The selected twenty-five RAPD primers produced a total of 199 amplicons, which generated 89.9 % polymorphism. The number of amplification products ranged from 2 to 13 for different primers. The polymorphism information content ranged from 0.0 for monomorphic loci to 0.5 with an average of 0.289. Genetic diversity between pairs of genotypes was 37.7% with a range of 3.9 to 71.6%. UPGMA cluster analysis placed all the accessions of soybean into four major clusters. No discernable geographical patterns were observed in clustering however; the smaller groups corresponded well with pedigree. Mantel's test (r = 0.915) indicates very good fit for clustering pattern. Two genotypes, MACS 330 and 111/2/1939 made a very divergent group from other accessions of soybean and highly photoperiod insensitive that may be potential source for broadening the genetic base of soybean for this trait.

Development of an Identification Procedure for a Large Urban School Corporation: "Identifying Culturally Diverse and Academically Gifted Elementary Students"

ERIC Educational Resources Information Center

Pierce, Rebecca L.; Adams, Cheryll M.; Neumeister, Kristie L. Speirs; Cassady, Jerrell C.; Dixon, Felicia A.; Cross, Tracy L.

2006-01-01

This paper describes the identification process of a Priority One Jacob K. Javits grant, Clustering Learners Unlocks Equity (Project CLUE), a university-school partnership. Project CLUE uses a "sift-down model" to cast the net widely as the talent pool of gifted second-grade students is formed. The model is based on standardized test scores, a…

Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)

NASA Technical Reports Server (NTRS)

McIntosh, Dawn

2006-01-01

This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search

Construcción de un catálogo de cúmulos de galaxias en proceso de colisión

NASA Astrophysics Data System (ADS)

de los Ríos, M.; Domínguez, M. J.; Paz, D.

2015-08-01

In this work we present first results of the identification of colliding galaxy clusters in galaxy catalogs with redshift measurements (SDSS, 2DF), and introduce the methodology. We calibrated a method by studying the merger trees of clusters in a mock catalog based on a full-blown semi-analytic model of galaxy formation on top of the Millenium cosmological simulation. We also discuss future actions for studding our sample of colliding galaxy clusters, including x-ray observations and mass reconstruction obtained by using weak gravitational lenses.

Application of clustering for customer segmentation in private banking

NASA Astrophysics Data System (ADS)

Yang, Xuan; Chen, Jin; Hao, Pengpeng; Wang, Yanbo J.

2015-07-01

With fierce competition in banking industry, more and more banks have realised that accurate customer segmentation is of fundamental importance, especially for the identification of those high-value customers. In order to solve this problem, we collected real data about private banking customers of a commercial bank in China, conducted empirical analysis by applying K-means clustering technique. When determine the K value, we propose a mechanism that meet both academic requirements and practical needs. Through K-means clustering, we successfully segmented the customers into three categories, and features of each group have been illustrated in details.

A Context-sensitive Approach to Anonymizing Spatial Surveillance Data: Impact on Outbreak Detection

PubMed Central

Cassa, Christopher A.; Grannis, Shaun J.; Overhage, J. Marc; Mandl, Kenneth D.

2006-01-01

Objective: The use of spatially based methods and algorithms in epidemiology and surveillance presents privacy challenges for researchers and public health agencies. We describe a novel method for anonymizing individuals in public health data sets by transposing their spatial locations through a process informed by the underlying population density. Further, we measure the impact of the skew on detection of spatial clustering as measured by a spatial scanning statistic. Design: Cases were emergency department (ED) visits for respiratory illness. Baseline ED visit data were injected with artificially created clusters ranging in magnitude, shape, and location. The geocoded locations were then transformed using a de-identification algorithm that accounts for the local underlying population density. Measurements: A total of 12,600 separate weeks of case data with artificially created clusters were combined with control data and the impact on detection of spatial clustering identified by a spatial scan statistic was measured. Results: The anonymization algorithm produced an expected skew of cases that resulted in high values of data set k-anonymity. De-identification that moves points an average distance of 0.25 km lowers the spatial cluster detection sensitivity by less than 4% and lowers the detection specificity less than 1%. Conclusion: A population-density–based Gaussian spatial blurring markedly decreases the ability to identify individuals in a data set while only slightly decreasing the performance of a standardly used outbreak detection tool. These findings suggest new approaches to anonymizing data for spatial epidemiology and surveillance. PMID:16357353

Multicolor CCD photometry of the open cluster NGC 752

NASA Astrophysics Data System (ADS)

Bartašiūtė, Stanislava; Janusz, Robert; Boyle, Richard P.; Philip, A. G. Davis; Deveikis, Viktoras

2010-01-01

We obtained CCD observations of the open cluster NGC 752 with the 1.8m Vatican Advanced Technology Telescope (Mt. Graham, Arizona) with a 4K CCD camera and eight intermediate-band filters of the Stromvil (Strömgren + Vilnius) system. Four 12‧ × 12‧ fields were observed, covering the central part of the cluster. The good-quality multicolor data made it possible to obtain precise estimates of distance moduli, metallicity and foreground reddening for individual stars down to the limiting magnitude, V = 17.5, enabling photometric identification of faint cluster members. The new observations provide an extension of the lower main sequence to three magnitudes beyond the previous (photographic) limit. A relatively small number of photometric members identified at fainter magnitudes seems to be indicative of actual dissolution of the cluster from the low-mass end.

Dark matter dynamics in Abell 3827: new data consistent with standard cold dark matter

NASA Astrophysics Data System (ADS)

Massey, Richard; Harvey, David; Liesenborgs, Jori; Richard, Johan; Stach, Stuart; Swinbank, Mark; Taylor, Peter; Williams, Liliya; Clowe, Douglas; Courbin, Frédéric; Edge, Alastair; Israel, Holger; Jauzac, Mathilde; Joseph, Rémy; Jullo, Eric; Kitching, Thomas D.; Leonard, Adrienne; Merten, Julian; Nagai, Daisuke; Nightingale, James; Robertson, Andrew; Romualdez, Luis Javier; Saha, Prasenjit; Smit, Renske; Tam, Sut-Ieng; Tittley, Eric

2018-06-01

We present integral field spectroscopy of galaxy cluster Abell 3827, using Atacama Large Millimetre Array (ALMA) and Very Large Telescope/Multi-Unit Spectroscopic Explorer. It reveals an unusual configuration of strong gravitational lensing in the cluster core, with at least seven lensed images of a single background spiral galaxy. Lens modelling based on Hubble Space Telescope imaging had suggested that the dark matter associated with one of the cluster's central galaxies may be offset. The new spectroscopic data enable better subtraction of foreground light, and better identification of multiple background images. The inferred distribution of dark matter is consistent with being centred on the galaxies, as expected by Λ cold dark matter. Each galaxy's dark matter also appears to be symmetric. Whilst, we do not find an offset between mass and light (suggestive of self-interacting dark matter) as previously reported, the numerical simulations that have been performed to calibrate Abell 3827 indicate that offsets and asymmetry are still worth looking for in collisions with particular geometries. Meanwhile, ALMA proves exceptionally useful for strong lens image identifications.

Personality based clusters as predictors of aviator attitudes and performance

NASA Technical Reports Server (NTRS)

Gregorich, Steve; Helmreich, Robert L.; Wilhelm, John A.; Chidester, Thomas

1989-01-01

The feasibility of identification of personality-based population clusters was investigated along with the relationships of these subpopulations to relevant attitude and performance measures. The results of instrumental and expressive personality tests, using the Personal Characteristics Inventory (PCI) test battery and the Cockpit Management Attitudes Questionnaire, suggest that theoretically meaningful subpopulations exist among aviators, and that these groupings are useful in understanding of personality factors acting as moderator variables in the determination of aviator attitudes and performance. Out of the three clusters most easily described in terms of their relative elevations on the PCI subscales ('the right stuff', the 'wrong stuff', and the 'no stuff'), the members of the right stuff cluster tended to have more desirable patterns of responses along relevant attitudinal dimensions.

All pure flat atypical atypia lesions of the breast diagnosed using percutaneous vacuum-assisted breast biopsy do not need surgical excision.

PubMed

Ouldamer, Lobna; Poisson, Elodie; Arbion, Flavie; Bonneau, Carole; Vildé, Anne; Body, Gilles; Michenet, Patrick

2018-04-14

The purposes of this study were to evaluate the outcome of women with pure flat atypical atypia (FEA) diagnosed at vacuum-assisted breast biopsy (VABB) targeting microcalcifications and to determine whether clinical, radiological and pathologic parameters are able to predict which lesions will be upgraded to malignancy. 2414 cases of consecutive VABB for microcalcifications using VA 8-, 10- or 11-Gauge stereotactically guided core biopsy performed between January 2005 and December 2011 from two french breast cancer centers were evaluated. Data of women with VABB-diagnosed pure FEA who underwent either excisional surgery or mammographic follow-up were analyzed. Cases with mass lesions or ipsilateral cancers were excluded. Two pathologists (FA,PM) reviewed the results of procedures performed. Clinical, radiological, as well as histological criteria have been studied in order to determine the correlation between these factors and carcinoma underestimation. This study included 70 cases of pure FEA. Twenty women underwent surgical excision and 50 had clinical and mammographic surveillance only. In three women FEA was upgraded to breast cancer on excision. Clinical and mammographic follow-up for a mean of 56 months ± 27 in the group without excision showed two cancers in the same breast (Intermediate grade DCIS, and invasive ductal carcinoma 84 and 48 months respectively after VABB). Three factors were significantly predictive of underestimation or occurence of cancer for pure FEA when the radiologic lesions are calcifications: age≥ 57 years, radiologic size >10 mm and number of FEA foci ≥4. Copyright © 2018. Published by Elsevier Ltd.

Ultrasound-guided cable-free 13-gauge vacuum-assisted biopsy of non-mass breast lesions

PubMed Central

Seo, Jiwoon; Jang, Mijung; Yun, Bo La; Lee, Soo Hyun; Kim, Eun-Kyu; Kang, Eunyoung; Park, So Yeon; Moon, Woo Kyung; Choi, Hye Young; Kim, Bohyoung

2017-01-01

Purpose To compare the outcomes of ultrasound-guided core biopsy for non-mass breast lesions by the novel 13-gauge cable-free vacuum-assisted biopsy (VAB) and by the conventional 14-gauge semi-automated core needle biopsy (CCNB). Materials and methods Our institutional review board approved this prospective study, and all patients provided written informed consent. Among 1840 ultrasound-guided percutaneous biopsies performed from August 2013 to December 2014, 145 non-mass breast lesions with suspicious microcalcifications on mammography or corresponding magnetic resonance imaging finding were subjected to 13-gauge VAB or 14-gauge CCNB. We evaluated the technical success rates, average specimen numbers, and tissue sampling time. We also compared the results of percutaneous biopsy and final surgical pathologic diagnosis to analyze the rates of diagnostic upgrade or downgrade. Results Ultrasound-guided VAB successfully targeted and sampled all lesions, whereas CCNB failed to demonstrate calcification in four (10.3%) breast lesions with microcalcification on specimen mammography. The mean sampling time were 238.6 and 170.6 seconds for VAB and CCNB, respectively. No major complications were observed with either method. Ductal carcinoma in situ (DCIS) and atypical ductal hyperplasia (ADH) lesions were more frequently upgraded after CCNB (8/23 and 3/5, respectively) than after VAB (2/26 and 0/4, respectively P = 0.028). Conclusion Non-mass breast lesions were successfully and accurately biopsied using cable-free VAB. The underestimation rate of ultrasound-detected non-mass lesion was significantly lower with VAB than with CCNB. Trial registration CRiS KCT0002267. PMID:28628656

Use of contrast-enhanced spectral mammography for intramammary cancer staging: preliminary results.

PubMed

Blum, Katrin S; Rubbert, Christian; Mathys, Britta; Antoch, Gerald; Mohrmann, Svjetlana; Obenauer, Silvia

2014-11-01

To prospectively evaluate and compare the accuracy of contrast-enhanced spectral mammography (CESM) and ultrasound (US) in size measurement of breast cancer with histologic tumor sizes as gold standard. Twenty women aged between 40-73 years (mean age, 57 ± 10 years) with histologically proven invasive ductal/lobular carcinomas were included in the study. Agreement between imaging tumor size (CESM and US) and histopathologic tumor size was evaluated with Bland-Altman analysis. Stereotactically guided vacuum biopsy was performed in four patients after CESM. Two independent reviewers described artifacts of CESM. Motion artifacts did not occur in the study. CESM-specific artifacts caused by scattered radiation mostly occurred in oblique view of CESM. Background enhancement of breast tissue was seen in four patients. Mean difference of tumor sizes was 0.3 mm (6.34%) between CESM and histology and -2.2 mm (-7.59%) between US and histology. Limits of agreement ranged from -18.9 to 19.48 mm for CESM and from -17.1 to 12.7 mm with US. Especially smaller tumors with a size <23 mm were measured more precisely with CESM. Enhancement of breast tissue around microcalcifications correlated with abnormalities. CESM is accurate in size measurements of small breast tumors. On average CESM leads to a slight overestimation of tumor size, whereas US tends to underestimate tumor size. Assessment of the breast tissue can be limited by the scattered radiation artifact and background enhancement of breast tissue. CESM seems to be helpful in the characterization of breast tissue around microcalcifications. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Impact of full field digital mammography on the classification and mammographic characteristics of interval breast cancers.

PubMed

Knox, Mark; O'Brien, Angela; Szabó, Endre; Smith, Clare S; Fenlon, Helen M; McNicholas, Michelle M; Flanagan, Fidelma L

2015-06-01

Full field digital mammography (FFDM) is increasingly replacing screen film mammography (SFM) in breast screening programs. Interval breast cancers are an issue in all screening programs and the purpose of our study is to assess the impact of FFDM on the classification of interval breast cancers at independent blind review and to compare the mammographic features of interval cancers at FFDM and SFM. This study included 138 cases of interval breast cancer, 76 following an FFDM screening examination and 62 following screening with SFM. The prior screening mammogram was assessed by each of five consultant breast radiologists who were blinded to the site of subsequent cancer. Subsequent review of the diagnostic mammogram was performed and cases were classified as missed, minimal signs, occult or true interval. Mammographic features of the interval cancer at diagnosis and any abnormality identified on the prior screening mammogram were recorded. The percentages of cancers classified as missed at FFDM and SFM did not differ significantly, 10.5% (8 of 76) at FFDM and 8.1% (5 of 62) at SFM (p=.77). There were significantly less interval cancers presenting as microcalcifications (alone or in association with another abnormality) following screening with FFDM, 16% (12 of 76) than following a SFM examination, 32% (20 of 62) (p=.02). Interval breast cancers continue to pose a problem at FFDM. The switch to FFDM has changed the mammographic presentation of interval breast cancer, with less interval cancers presenting in association with microcalcifications. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Prediction of occult invasive disease in ductal carcinoma in situ using computer-extracted mammographic features

NASA Astrophysics Data System (ADS)

Shi, Bibo; Grimm, Lars J.; Mazurowski, Maciej A.; Marks, Jeffrey R.; King, Lorraine M.; Maley, Carlo C.; Hwang, E. Shelley; Lo, Joseph Y.

2017-03-01

Predicting the risk of occult invasive disease in ductal carcinoma in situ (DCIS) is an important task to help address the overdiagnosis and overtreatment problems associated with breast cancer. In this work, we investigated the feasibility of using computer-extracted mammographic features to predict occult invasive disease in patients with biopsy proven DCIS. We proposed a computer-vision algorithm based approach to extract mammographic features from magnification views of full field digital mammography (FFDM) for patients with DCIS. After an expert breast radiologist provided a region of interest (ROI) mask for the DCIS lesion, the proposed approach is able to segment individual microcalcifications (MCs), detect the boundary of the MC cluster (MCC), and extract 113 mammographic features from MCs and MCC within the ROI. In this study, we extracted mammographic features from 99 patients with DCIS (74 pure DCIS; 25 DCIS plus invasive disease). The predictive power of the mammographic features was demonstrated through binary classifications between pure DCIS and DCIS with invasive disease using linear discriminant analysis (LDA). Before classification, the minimum redundancy Maximum Relevance (mRMR) feature selection method was first applied to choose subsets of useful features. The generalization performance was assessed using Leave-One-Out Cross-Validation and Receiver Operating Characteristic (ROC) curve analysis. Using the computer-extracted mammographic features, the proposed model was able to distinguish DCIS with invasive disease from pure DCIS, with an average classification performance of AUC = 0.61 +/- 0.05. Overall, the proposed computer-extracted mammographic features are promising for predicting occult invasive disease in DCIS.

Identification of beer-spoilage bacteria using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Wieme, Anneleen D; Spitaels, Freek; Aerts, Maarten; De Bruyne, Katrien; Van Landschoot, Anita; Vandamme, Peter

2014-08-18

Applicability of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for identification of beer-spoilage bacteria was examined. To achieve this, an extensive identification database was constructed comprising more than 4200 mass spectra, including biological and technical replicates derived from 273 acetic acid bacteria (AAB) and lactic acid bacteria (LAB), covering a total of 52 species, grown on at least three growth media. Sequence analysis of protein coding genes was used to verify aberrant MALDI-TOF MS identification results and confirmed the earlier misidentification of 34 AAB and LAB strains. In total, 348 isolates were collected from culture media inoculated with 14 spoiled beer and brewery samples. Peak-based numerical analysis of MALDI-TOF MS spectra allowed a straightforward species identification of 327 (94.0%) isolates. The remaining isolates clustered separately and were assigned through sequence analysis of protein coding genes either to species not known as beer-spoilage bacteria, and thus not present in the database, or to novel AAB species. An alternative, classifier-based approach for the identification of spoilage bacteria was evaluated by combining the identification results obtained through peak-based cluster analysis and sequence analysis of protein coding genes as a standard. In total, 263 out of 348 isolates (75.6%) were correctly identified at species level and 24 isolates (6.9%) were misidentified. In addition, the identification results of 50 isolates (14.4%) were considered unreliable, and 11 isolates (3.2%) could not be identified. The present study demonstrated that MALDI-TOF MS is well-suited for the rapid, high-throughput and accurate identification of bacteria isolated from spoiled beer and brewery samples, which makes the technique appropriate for routine microbial quality control in the brewing industry. Copyright © 2014 Elsevier B.V. All rights reserved.

A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures

PubMed Central

Chen, Yun; Yang, Hui

2016-01-01

In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering. PMID:27966581

A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures.

PubMed

Chen, Yun; Yang, Hui

2016-12-14

In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering.

Comprehensive assessment of cancer missense mutation clustering in protein structures.

PubMed

Kamburov, Atanas; Lawrence, Michael S; Polak, Paz; Leshchiner, Ignaty; Lage, Kasper; Golub, Todd R; Lander, Eric S; Getz, Gad

2015-10-06

Large-scale tumor sequencing projects enabled the identification of many new cancer gene candidates through computational approaches. Here, we describe a general method to detect cancer genes based on significant 3D clustering of mutations relative to the structure of the encoded protein products. The approach can also be used to search for proteins with an enrichment of mutations at binding interfaces with a protein, nucleic acid, or small molecule partner. We applied this approach to systematically analyze the PanCancer compendium of somatic mutations from 4,742 tumors relative to all known 3D structures of human proteins in the Protein Data Bank. We detected significant 3D clustering of missense mutations in several previously known oncoproteins including HRAS, EGFR, and PIK3CA. Although clustering of missense mutations is often regarded as a hallmark of oncoproteins, we observed that a number of tumor suppressors, including FBXW7, VHL, and STK11, also showed such clustering. Beside these known cases, we also identified significant 3D clustering of missense mutations in NUF2, which encodes a component of the kinetochore, that could affect chromosome segregation and lead to aneuploidy. Analysis of interaction interfaces revealed enrichment of mutations in the interfaces between FBXW7-CCNE1, HRAS-RASA1, CUL4B-CAND1, OGT-HCFC1, PPP2R1A-PPP2R5C/PPP2R2A, DICER1-Mg2+, MAX-DNA, SRSF2-RNA, and others. Together, our results indicate that systematic consideration of 3D structure can assist in the identification of cancer genes and in the understanding of the functional role of their mutations.

Comprehensive assessment of cancer missense mutation clustering in protein structures

PubMed Central

Kamburov, Atanas; Lawrence, Michael S.; Polak, Paz; Leshchiner, Ignaty; Lage, Kasper; Golub, Todd R.; Lander, Eric S.; Getz, Gad

2015-01-01

Large-scale tumor sequencing projects enabled the identification of many new cancer gene candidates through computational approaches. Here, we describe a general method to detect cancer genes based on significant 3D clustering of mutations relative to the structure of the encoded protein products. The approach can also be used to search for proteins with an enrichment of mutations at binding interfaces with a protein, nucleic acid, or small molecule partner. We applied this approach to systematically analyze the PanCancer compendium of somatic mutations from 4,742 tumors relative to all known 3D structures of human proteins in the Protein Data Bank. We detected significant 3D clustering of missense mutations in several previously known oncoproteins including HRAS, EGFR, and PIK3CA. Although clustering of missense mutations is often regarded as a hallmark of oncoproteins, we observed that a number of tumor suppressors, including FBXW7, VHL, and STK11, also showed such clustering. Beside these known cases, we also identified significant 3D clustering of missense mutations in NUF2, which encodes a component of the kinetochore, that could affect chromosome segregation and lead to aneuploidy. Analysis of interaction interfaces revealed enrichment of mutations in the interfaces between FBXW7-CCNE1, HRAS-RASA1, CUL4B-CAND1, OGT-HCFC1, PPP2R1A-PPP2R5C/PPP2R2A, DICER1-Mg2+, MAX-DNA, SRSF2-RNA, and others. Together, our results indicate that systematic consideration of 3D structure can assist in the identification of cancer genes and in the understanding of the functional role of their mutations. PMID:26392535

Low physical activity as a key differentiating factor in the potential high-risk profile for depressive symptoms in older adults.

PubMed

Holmquist, Sofie; Mattsson, Sabina; Schele, Ingrid; Nordström, Peter; Nordström, Anna

2017-09-01

The identification of potential high-risk groups for depression is of importance. The purpose of the present study was to identify high-risk profiles for depressive symptoms in older individuals, with a focus on functional performance. The population-based Healthy Ageing Initiative included 2,084 community-dwelling individuals (49% women) aged 70. Explorative cluster analysis was used to group participants according to functional performance level, using measures of basic mobility skills, gait variability, and grip strength. Intercluster differences in depressive symptoms (measured by the Geriatric Depression Scale [GDS]-15), physical activity (PA; measured objectively with the ActiGraph GT3X+), and a rich set of covariates were examined. The cluster analysis yielded a seven-cluster solution. One potential high-risk cluster was identified, with overrepresentation of individuals with GDS scores >5 (15.1 vs. 2.7% expected; relative risk = 6.99, P < .001); the prevalence of depressive symptoms was significantly lower in the other clusters (all P < .01). The potential high-risk cluster had significant overrepresentations of obese individuals (39.7 vs. 17.4% expected) and those with type 2 diabetes (24.7 vs. 8.5% expected), and underrepresentation of individuals who fulfilled the World Health Organization's PA recommendations (15.6 vs. 59.1% expected; all P < .01), as well as low levels of functional performance. The present study provided a potential high-risk profile for depressive symptoms among elderly community-dwelling individuals, which included low levels functional performance combined with low levels of PA. Including PA in medical screening of the elderly may aid in identification of potential high-risk individuals for depressive symptoms. © 2017 Wiley Periodicals, Inc.

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

DOE PAGES

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; ...

2013-01-01

Background . The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective . To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods . The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expertmore » knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results . The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions . Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

PubMed Central

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Varnum, Susan M.; Brown, Joseph N.; Riensche, Roderick M.; Adkins, Joshua N.; Jacobs, Jon M.; Hoidal, John R.; Scholand, Mary Beth; Pounds, Joel G.; Blackburn, Michael R.; Rodland, Karin D.; McDermott, Jason E.

2013-01-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification. PMID:24223463

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

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

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.

2013-10-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integratedmore » into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

Lesion identification using unified segmentation-normalisation models and fuzzy clustering

PubMed Central

Seghier, Mohamed L.; Ramlackhansingh, Anil; Crinion, Jenny; Leff, Alexander P.; Price, Cathy J.

2008-01-01

In this paper, we propose a new automated procedure for lesion identification from single images based on the detection of outlier voxels. We demonstrate the utility of this procedure using artificial and real lesions. The scheme rests on two innovations: First, we augment the generative model used for combined segmentation and normalization of images, with an empirical prior for an atypical tissue class, which can be optimised iteratively. Second, we adopt a fuzzy clustering procedure to identify outlier voxels in normalised gray and white matter segments. These two advances suppress misclassification of voxels and restrict lesion identification to gray/white matter lesions respectively. Our analyses show a high sensitivity for detecting and delineating brain lesions with different sizes, locations, and textures. Our approach has important implications for the generation of lesion overlap maps of a given population and the assessment of lesion-deficit mappings. From a clinical perspective, our method should help to compute the total volume of lesion or to trace precisely lesion boundaries that might be pertinent for surgical or diagnostic purposes. PMID:18482850

Steganalysis feature improvement using expectation maximization

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M.; Peterson, Gilbert L.; Agaian, Sos S.

2007-04-01

Images and data files provide an excellent opportunity for concealing illegal or clandestine material. Currently, there are over 250 different tools which embed data into an image without causing noticeable changes to the image. From a forensics perspective, when a system is confiscated or an image of a system is generated the investigator needs a tool that can scan and accurately identify files suspected of containing malicious information. The identification process is termed the steganalysis problem which focuses on both blind identification, in which only normal images are available for training, and multi-class identification, in which both the clean and stego images at several embedding rates are available for training. In this paper an investigation of a clustering and classification technique (Expectation Maximization with mixture models) is used to determine if a digital image contains hidden information. The steganalysis problem is for both anomaly detection and multi-class detection. The various clusters represent clean images and stego images with between 1% and 10% embedding percentage. Based on the results it is concluded that the EM classification technique is highly suitable for both blind detection and the multi-class problem.

DMINDA: an integrated web server for DNA motif identification and analyses

PubMed Central

Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

2014-01-01

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. PMID:24753419

Automated modal parameter estimation using correlation analysis and bootstrap sampling

NASA Astrophysics Data System (ADS)

Yaghoubi, Vahid; Vakilzadeh, Majid K.; Abrahamsson, Thomas J. S.

2018-02-01

The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods have been developed to automate this procedure. The common approach is to identify models with different orders and cluster similar modes together. However, most proposed methods based on this approach suffer from high-dimensional optimization problems in either the estimation or clustering step. To overcome this problem, this study presents an algorithm for autonomous modal parameter estimation in which the only required optimization is performed in a three-dimensional space. To this end, a subspace-based identification method is employed for the estimation and a non-iterative correlation-based method is used for the clustering. This clustering is at the heart of the paper. The keys to success are correlation metrics that are able to treat the problems of spatial eigenvector aliasing and nonunique eigenvectors of coalescent modes simultaneously. The algorithm commences by the identification of an excessively high-order model from frequency response function test data. The high number of modes of this model provides bases for two subspaces: one for likely physical modes of the tested system and one for its complement dubbed the subspace of noise modes. By employing the bootstrap resampling technique, several subsets are generated from the same basic dataset and for each of them a model is identified to form a set of models. Then, by correlation analysis with the two aforementioned subspaces, highly correlated modes of these models which appear repeatedly are clustered together and the noise modes are collected in a so-called Trashbox cluster. Stray noise modes attracted to the mode clusters are trimmed away in a second step by correlation analysis. The final step of the algorithm is a fuzzy c-means clustering procedure applied to a three-dimensional feature space to assign a degree of physicalness to each cluster. The proposed algorithm is applied to two case studies: one with synthetic data and one with real test data obtained from a hammer impact test. The results indicate that the algorithm successfully clusters similar modes and gives a reasonable quantification of the extent to which each cluster is physical.

The use of the temporal scan statistic to detect methicillin-resistant Staphylococcus aureus clusters in a community hospital.

PubMed

Faires, Meredith C; Pearl, David L; Ciccotelli, William A; Berke, Olaf; Reid-Smith, Richard J; Weese, J Scott

2014-07-08

In healthcare facilities, conventional surveillance techniques using rule-based guidelines may result in under- or over-reporting of methicillin-resistant Staphylococcus aureus (MRSA) outbreaks, as these guidelines are generally unvalidated. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting MRSA clusters, validate clusters using molecular techniques and hospital records, and determine significant differences in the rate of MRSA cases using regression models. Patients admitted to a community hospital between August 2006 and February 2011, and identified with MRSA>48 hours following hospital admission, were included in this study. Between March 2010 and February 2011, MRSA specimens were obtained for spa typing. MRSA clusters were investigated using a retrospective temporal scan statistic. Tests were conducted on a monthly scale and significant clusters were compared to MRSA outbreaks identified by hospital personnel. Associations between the rate of MRSA cases and the variables year, month, and season were investigated using a negative binomial regression model. During the study period, 735 MRSA cases were identified and 167 MRSA isolates were spa typed. Nine different spa types were identified with spa type 2/t002 (88.6%) the most prevalent. The temporal scan statistic identified significant MRSA clusters at the hospital (n=2), service (n=16), and ward (n=10) levels (P ≤ 0.05). Seven clusters were concordant with nine MRSA outbreaks identified by hospital staff. For the remaining clusters, seven events may have been equivalent to true outbreaks and six clusters demonstrated possible transmission events. The regression analysis indicated years 2009-2011, compared to 2006, and months March and April, compared to January, were associated with an increase in the rate of MRSA cases (P ≤ 0.05). The application of the temporal scan statistic identified several MRSA clusters that were not detected by hospital personnel. The identification of specific years and months with increased MRSA rates may be attributable to several hospital level factors including the presence of other pathogens. Within hospitals, the incorporation of the temporal scan statistic to standard surveillance techniques is a valuable tool for healthcare workers to evaluate surveillance strategies and aid in the identification of MRSA clusters.

Identification and analysis of evolutionary selection pressures acting at the molecular level in five forkhead subfamilies.

PubMed

Fetterman, Christina D; Rannala, Bruce; Walter, Michael A

2008-09-24

Members of the forkhead gene family act as transcription regulators in biological processes including development and metabolism. The evolution of forkhead genes has not been widely examined and selection pressures at the molecular level influencing subfamily evolution and differentiation have not been explored. Here, in silico methods were used to examine selection pressures acting on the coding sequence of five multi-species FOX protein subfamily clusters; FoxA, FoxD, FoxI, FoxO and FoxP. Application of site models, which estimate overall selection pressures on individual codons throughout the phylogeny, showed that the amino acid changes observed were either neutral or under negative selection. Branch-site models, which allow estimated selection pressures along specified lineages to vary as compared to the remaining phylogeny, identified positive selection along branches leading to the FoxA3 and Protostomia clades in the FoxA cluster and the branch leading to the FoxO3 clade in the FoxO cluster. Residues that may differentiate paralogs were identified in the FoxA and FoxO clusters and residues that differentiate orthologs were identified in the FoxA cluster. Neutral amino acid changes were identified in the forkhead domain of the FoxA, FoxD and FoxP clusters while positive selection was identified in the forkhead domain of the Protostomia lineage of the FoxA cluster. A series of residues under strong negative selection adjacent to the N- and C-termini of the forkhead domain were identified in all clusters analyzed suggesting a new method for refinement of domain boundaries. Extrapolation of domains among cluster members in conjunction with selection pressure information allowed prediction of residue function in the FoxA, FoxO and FoxP clusters and exclusion of known domain function in residues of the FoxA and FoxI clusters. Consideration of selection pressures observed in conjunction with known functional information allowed prediction of residue function and refinement of domain boundaries. Identification of residues that differentiate orthologs and paralogs provided insight into the development and functional consequences of paralogs and forkhead subfamily composition differences among species. Overall we found that after gene duplication of forkhead family members, rapid differentiation and subsequent fixation of amino acid changes through negative selection has occurred.

Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2018-01-01

The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure. To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances. Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study region. The territorial heterogeneity of earthquakes clustering is in good agreement with spatial variability of scaling parameters identified by the USLE. In particular, the fractal dimension is higher to the west (about 1.2-1.4), suggesting a spatially more distributed seismicity, compared to the eastern parte of the investigated territory, where fractal dimension is very low (about 0.8-1.0).

Characterization of the CPAP-treated patient population in Catalonia

PubMed Central

Gavaldá, Ricard; Teixidó, Ivan; Woehrle, Holger; Rué, Montserrat; Solsona, Francesc; Escarrabill, Joan; Colls, Cristina; García-Altés, Anna; de Batlle, Jordi; Sánchez de-la-Torre, Manuel

2017-01-01

There are different phenotypes of obstructive sleep apnoea (OSA), many of which have not been characterised. Identification of these different phenotypes is important in defining prognosis and guiding the therapeutic strategy. The aim of this study was to characterise the entire population of continuous positive airway pressure (CPAP)-treated patients in Catalonia and identify specific patient profiles using cluster analysis. A total of 72,217 CPAP-treated patients who contacted the Catalan Health System (CatSalut) during the years 2012 and 2013 were included. Six clusters were identified, classified as “Neoplastic patients” (Cluster 1, 10.4%), “Metabolic syndrome patients” (Cluster 2, 27.7%), “Asthmatic patients” (Cluster 3, 5.8%), “Musculoskeletal and joint disorder patients” (Cluster 4, 10.3%), “Patients with few comorbidities” (Cluster 5, 35.6%) and “Oldest and cardiac disease patients” (Cluster 6, 10.2%). Healthcare facility use and mortality were highest in patients from Cluster 1 and 6. Conversely, patients in Clusters 2 and 4 had low morbidity, mortality and healthcare resource use. Our findings highlight the heterogeneity of CPAP-treated patients, and suggest that OSA is associated with a different prognosis in the clusters identified. These results suggest the need for a comprehensive and individualised approach to CPAP treatment of OSA. PMID:28934303

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

PubMed Central

Macropol, Kathy; Can, Tolga; Singh, Ambuj K

2009-01-01

Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL), and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters. PMID:19740439

ApiEST-DB: analyzing clustered EST data of the apicomplexan parasites.

PubMed

Li, Li; Crabtree, Jonathan; Fischer, Steve; Pinney, Deborah; Stoeckert, Christian J; Sibley, L David; Roos, David S

2004-01-01

ApiEST-DB (http://www.cbil.upenn.edu/paradbs-servlet/) provides integrated access to publicly available EST data from protozoan parasites in the phylum Apicomplexa. The database currently incorporates a total of nearly 100,000 ESTs from several parasite species of clinical and/or veterinary interest, including Eimeria tenella, Neospora caninum, Plasmodium falciparum, Sarcocystis neurona and Toxoplasma gondii. To facilitate analysis of these data, EST sequences were clustered and assembled to form consensus sequences for each organism, and these assemblies were then subjected to automated annotation via similarity searches against protein and domain databases. The underlying relational database infrastructure, Genomics Unified Schema (GUS), enables complex biologically based queries, facilitating validation of gene models, identification of alternative splicing, detection of single nucleotide polymorphisms, identification of stage-specific genes and recognition of phylogenetically conserved and phylogenetically restricted sequences.

Differential equations as a tool for community identification.

PubMed

Krawczyk, Małgorzata J

2008-06-01

We consider the task of identification of a cluster structure in random networks. The results of two methods are presented: (i) the Newman algorithm [M. E. J. Newman and M. Girvan, Phys. Rev. E 69, 026113 (2004)]; and (ii) our method based on differential equations. A series of computer experiments is performed to check if in applying these methods we are able to determine the structure of the network. The trial networks consist initially of well-defined clusters and are disturbed by introducing noise into their connectivity matrices. Further, we show that an improvement of the previous version of our method is possible by an appropriate choice of the threshold parameter beta . With this change, the results obtained by the two methods above are similar, and our method works better, for all the computer experiments we have done.

Inferring time-varying network topologies from gene expression data.

PubMed

Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas

2007-01-01

Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.

Geographic origin and individual assignment of Shorea platyclados (Dipterocarpaceae) for forensic identification

PubMed Central

Diway, Bibian; Khoo, Eyen

2017-01-01

The development of timber tracking methods based on genetic markers can provide scientific evidence to verify the origin of timber products and fulfill the growing requirement for sustainable forestry practices. In this study, the origin of an important Dark Red Meranti wood, Shorea platyclados, was studied by using the combination of seven chloroplast DNA and 15 short tandem repeats (STRs) markers. A total of 27 natural populations of S. platyclados were sampled throughout Malaysia to establish population level and individual level identification databases. A haplotype map was generated from chloroplast DNA sequencing for population identification, resulting in 29 multilocus haplotypes, based on 39 informative intraspecific variable sites. Subsequently, a DNA profiling database was developed from 15 STRs allowing for individual identification in Malaysia. Cluster analysis divided the 27 populations into two genetic clusters, corresponding to the region of Eastern and Western Malaysia. The conservativeness tests showed that the Malaysia database is conservative after removal of bias from population subdivision and sampling effects. Independent self-assignment tests correctly assigned individuals to the database in an overall 60.60−94.95% of cases for identified populations, and in 98.99−99.23% of cases for identified regions. Both the chloroplast DNA database and the STRs appear to be useful for tracking timber originating in Malaysia. Hence, this DNA-based method could serve as an effective addition tool to the existing forensic timber identification system for ensuring the sustainably management of this species into the future. PMID:28430826

Identification of Cronobacter species by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry with an optimized analysis method.

PubMed

Wang, Qi; Zhao, Xiao-Juan; Wang, Zi-Wei; Liu, Li; Wei, Yong-Xin; Han, Xiao; Zeng, Jing; Liao, Wan-Jin

2017-08-01

Rapid and precise identification of Cronobacter species is important for foodborne pathogen detection, however, commercial biochemical methods can only identify Cronobacter strains to genus level in most cases. To evaluate the power of mass spectrometry based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF MS) for Cronobacter species identification, 51 Cronobacter strains (eight reference and 43 wild strains) were identified by both MALDI-TOF MS and 16S rRNA gene sequencing. Biotyper RTC provided by Bruker identified all eight reference and 43 wild strains as Cronobacter species, which demonstrated the power of MALDI-TOF MS to identify Cronobacter strains to genus level. However, using the Bruker's database (6903 main spectra products) and Biotyper software, the MALDI-TOF MS analysis could not identify the investigated strains to species level. When MALDI-TOF MS analysis was performed using the combined in-house Cronobacter database and Bruker's database, bin setting, and unweighted pair group method with arithmetic mean (UPGMA) clustering, all the 51 strains were clearly identified into six Cronobacter species and the identification accuracy increased from 60% to 100%. We demonstrated that MALDI-TOF MS was reliable and easy-to-use for Cronobacter species identification and highlighted the importance of establishing a reliable database and improving the current data analysis methods by integrating the bin setting and UPGMA clustering. Copyright © 2017. Published by Elsevier B.V.

Ion composition in a noctilucent cloud

NASA Technical Reports Server (NTRS)

Goldberg, R. A.; Witt, G.

1976-01-01

Ion composition at mesospheric altitudes was measured and compared between high and mid-latitude sites under summer daytime conditions. Rocket-borne measurements were made with pumped quadrupole ion mass spectrometers. The mid-latitude data were obtained at Wallops Island, Virginia on June 30, 1973, at 1510 LMT. Large quantities of hydronium cluster ions were observed through 109+, with maximum concentrations at 55+ and 73+. Also, cluster ions of nitric oxide were observed through 84+. The high latitude launch occurred at Kiruna, Sweden on August 2, 1973, at 0700 LMT following visual sighting of a noctilucent cloud on the prior evening. The data near mesopause shows cluster ions, but also a preponderance of heavy ions between 90 and 145 AMU, with groupings 18 AMU apart but unrelated to the more typical cluster ions. One possible set of consistent identifications leads to iron and iron oxide hydrates. These results may suggest the presence of metallic particulates and ions which form hydrated clusters ions.

Identification and growth characteristics of pink pigmented oxidative bacteria, Methylobacterium mesophilicum and biovars isolated from chlorinated and raw water supplies.

PubMed

O'Brien, J R; Murphy, J M

1993-01-01

Pink pigmented bacteria were isolated from a blood bank water purification unit, a municipal town water supply (tap water), and an island (untreated) ground water source. A total of thirteen strains including two reference strains of pink pigmented bacteria were compared in a numerical phenotypic study using 119 binary characters. Three clusters were derived, one major cluster of eleven strains was subdivided into two sub-clusters on the basis of methanol utilization. Five strains were facultative methylotrophs and were classified as Methylobacterium mesophilicum biovar 1. The other six strains did not utilize methanol, but on the basis of high phenotypic similarity of 83.6% were classified as M. mesophilicum biovar 2. The single reference strain comprising cluster 2 Pseudomonas extorquens NCIB 9399 was assigned to the genus Methylobacterium and classified as M. extorquens. Cluster 3 was the single reference strain Rhizobium CB 376.

Identification of the low-energy excitations in a quantum critical system

NASA Astrophysics Data System (ADS)

Heitmann, Tom; Lamsal, Jagat; Watson, Shannon; Erwin, Ross; Chen, Wangchun; Zhao, Yang; Montfrooij, Wouter

2017-05-01

We have identified low-energy magnetic excitations in a doped quantum critical system by means of polarized neutron scattering experiments. The presence of these excitations could explain why Ce(Fe0.76Ru0.24)2Ge2 displays dynamical scaling in the absence of local critical behavior or long-range spin-density wave criticality. The low-energy excitations are associated with the reorientations of the superspins of fully ordered, isolated magnetic clusters that form spontaneously upon lowering the temperature. The system houses both frozen clusters and dynamic clusters, as predicted by Hoyos and Vojta [Phys. Rev. B 74, 140401(R) (2006)].

Early warning signals of desertification transitions in semiarid ecosystems

NASA Astrophysics Data System (ADS)

Corrado, Raffaele; Cherubini, Anna Maria; Pennetta, Cecilia

2014-12-01

The identification of early warning signals for regime shifts in ecosystems is of crucial importance given their impact in terms of economic and social effects. We present here the results of a theoretical study on the desertification transition in semiarid ecosystems under external stress. We performed numerical simulations based on a stochastic cellular automaton model, and we studied the dynamics of the vegetation clusters in terms of percolation theory, assumed as an effective tool for analyzing the geometrical properties of the clusters. Focusing on the role played by the strength of external stresses, measured by the mortality rate m , we followed the progressive degradation of the ecosystem for increasing m , identifying different stages: first, the fragmentation transition occurring at relatively low values of m , then the desertification transition at higher mortality rates, and finally the full desertification transition corresponding to the extinction of the vegetation and the almost complete degradation of the soil, attained at the maximum value of m . For each transition we calculated the spanning probabilities as functions of m and the percolation thresholds according to different spanning criteria. The identification of the different thresholds is proposed as an useful tool for monitoring the increasing degradation of real-world finite-size systems. Moreover, we studied the time fluctuations of the sizes of the biggest clusters of vegetated and nonvegetated cells over the entire range of mortality values. The change of sign in the skewness of the size distributions, occurring at the fragmentation threshold for the biggest vegetation cluster and at the desertification threshold for the nonvegetated cluster, offers new early warning signals for desertification. Other new and robust indicators are given by the maxima of the root-mean-square deviation of the distributions, which are attained respectively inside the fragmentation interval, for the vegetated biggest cluster, and inside the desertification interval, for the nonvegetated cluster.

Early warning signals of desertification transitions in semiarid ecosystems.

PubMed

Corrado, Raffaele; Cherubini, Anna Maria; Pennetta, Cecilia

2014-12-01

The identification of early warning signals for regime shifts in ecosystems is of crucial importance given their impact in terms of economic and social effects. We present here the results of a theoretical study on the desertification transition in semiarid ecosystems under external stress. We performed numerical simulations based on a stochastic cellular automaton model, and we studied the dynamics of the vegetation clusters in terms of percolation theory, assumed as an effective tool for analyzing the geometrical properties of the clusters. Focusing on the role played by the strength of external stresses, measured by the mortality rate m, we followed the progressive degradation of the ecosystem for increasing m, identifying different stages: first, the fragmentation transition occurring at relatively low values of m, then the desertification transition at higher mortality rates, and finally the full desertification transition corresponding to the extinction of the vegetation and the almost complete degradation of the soil, attained at the maximum value of m. For each transition we calculated the spanning probabilities as functions of m and the percolation thresholds according to different spanning criteria. The identification of the different thresholds is proposed as an useful tool for monitoring the increasing degradation of real-world finite-size systems. Moreover, we studied the time fluctuations of the sizes of the biggest clusters of vegetated and nonvegetated cells over the entire range of mortality values. The change of sign in the skewness of the size distributions, occurring at the fragmentation threshold for the biggest vegetation cluster and at the desertification threshold for the nonvegetated cluster, offers new early warning signals for desertification. Other new and robust indicators are given by the maxima of the root-mean-square deviation of the distributions, which are attained respectively inside the fragmentation interval, for the vegetated biggest cluster, and inside the desertification interval, for the nonvegetated cluster.

Identification of cognitive profiles among women considering BRCA1/2 testing through the utilisation of cluster analytic techniques.

PubMed

Roussi, Pagona; Sherman, Kerry A; Miller, Suzanne M; Hurley, Karen; Daly, Mary B; Godwin, Andrew; Buzaglo, Joanne S; Wen, Kuang-Yi

2011-10-01

Based on the cognitive-social health information processing model, we identified cognitive profiles of women at risk for breast and ovarian cancer. Prior to genetic counselling, participants (N = 171) completed a study questionnaire concerning their cognitive and affective responses to being at genetic risk. Using cluster analysis, four cognitive profiles were generated: (a) high perceived risk/low coping; (b) low value of screening/high expectancy of cancer; (c) moderate perceived risk/moderate efficacy of prevention/low informativeness of test result; and (d) high efficacy of prevention/high coping. The majority of women in Clusters One, Two and Three had no personal history of cancer, whereas Cluster Four consisted almost entirely of women affected with cancer. Women in Cluster One had the highest number of affected relatives and experienced higher levels of distress than women in the other three clusters. These results highlight the need to consider the psychological profile of women undergoing genetic testing when designing counselling interventions and messages.

Onto-clust--a methodology for combining clustering analysis and ontological methods for identifying groups of comorbidities for developmental disorders.

PubMed

Peleg, Mor; Asbeh, Nuaman; Kuflik, Tsvi; Schertz, Mitchell

2009-02-01

Children with developmental disorders usually exhibit multiple developmental problems (comorbidities). Hence, such diagnosis needs to revolve on developmental disorder groups. Our objective is to systematically identify developmental disorder groups and represent them in an ontology. We developed a methodology that combines two methods (1) a literature-based ontology that we created, which represents developmental disorders and potential developmental disorder groups, and (2) clustering for detecting comorbid developmental disorders in patient data. The ontology is used to interpret and improve clustering results and the clustering results are used to validate the ontology and suggest directions for its development. We evaluated our methodology by applying it to data of 1175 patients from a child development clinic. We demonstrated that the ontology improves clustering results, bringing them closer to an expert generated gold-standard. We have shown that our methodology successfully combines an ontology with a clustering method to support systematic identification and representation of developmental disorder groups.

Exploring spatial evolution of economic clusters: A case study of Beijing

NASA Astrophysics Data System (ADS)

Yang, Zhenshan; Sliuzas, Richard; Cai, Jianming; Ottens, Henk F. L.

2012-10-01

An identification of economic clusters and analysing their changing spatial patterns is important for understanding urban economic space dynamics. Previous studies, however, suffer from limitations as a consequence of using fixed geographically areas and not combining functional and spatial dynamics. The paper presents an approach, based on local spatial statistics and the case of Beijing to understand the spatial clustering of industries that are functionally interconnected by common or complementary patterns of demand or supply relations. Using register data of business establishments, it identifies economic clusters and analyses their pattern based on postcodes at different time slices during the period 1983-2002. The study shows how the advanced services occupy the urban centre and key sub centres. The Information and Communication Technology (ICT) cluster is mainly concentrated in the north part of the city and circles the urban centre, and the main manufacturing clusters are evolved in the key sub centers. This type of outcomes improves understanding of urban-economic dynamics, which can support spatial and economic planning.

Holographic optical coherence imaging of tumor spheroids

NASA Astrophysics Data System (ADS)

Yu, P.; Mustata, M.; Turek, J. J.; French, P. M. W.; Melloch, M. R.; Nolte, D. D.

2003-07-01

We present depth-resolved coherence-domain images of living tissue using a dynamic holographic semiconductor film. An AlGaAs photorefractive quantum-well device is used in an adaptive interferometer that records coherent backscattered (image-bearing) light from inside rat osteogenic sarcoma tumor spheroids up to 1 mm in diameter in vitro. The data consist of sequential holographic image frames at successive depths through the tumor represented as a visual video "fly-through." The images from the tumor spheroids reveal heterogeneous structures presumably caused by necrosis and microcalcifications characteristic of human tumors in their early avascular growth.

An image processing pipeline to detect and segment nuclei in muscle fiber microscopic images.

PubMed

Guo, Yanen; Xu, Xiaoyin; Wang, Yuanyuan; Wang, Yaming; Xia, Shunren; Yang, Zhong

2014-08-01

Muscle fiber images play an important role in the medical diagnosis and treatment of many muscular diseases. The number of nuclei in skeletal muscle fiber images is a key bio-marker of the diagnosis of muscular dystrophy. In nuclei segmentation one primary challenge is to correctly separate the clustered nuclei. In this article, we developed an image processing pipeline to automatically detect, segment, and analyze nuclei in microscopic image of muscle fibers. The pipeline consists of image pre-processing, identification of isolated nuclei, identification and segmentation of clustered nuclei, and quantitative analysis. Nuclei are initially extracted from background by using local Otsu's threshold. Based on analysis of morphological features of the isolated nuclei, including their areas, compactness, and major axis lengths, a Bayesian network is trained and applied to identify isolated nuclei from clustered nuclei and artifacts in all the images. Then a two-step refined watershed algorithm is applied to segment clustered nuclei. After segmentation, the nuclei can be quantified for statistical analysis. Comparing the segmented results with those of manual analysis and an existing technique, we find that our proposed image processing pipeline achieves good performance with high accuracy and precision. The presented image processing pipeline can therefore help biologists increase their throughput and objectivity in analyzing large numbers of nuclei in muscle fiber images. © 2014 Wiley Periodicals, Inc.

Amplified fragment length polymorphism of Streptococcus suis strains correlates with their profile of virulence-associated genes and clinical background.

PubMed

Rehm, Thomas; Baums, Christoph G; Strommenger, Birgit; Beyerbach, Martin; Valentin-Weigand, Peter; Goethe, Ralph

2007-01-01

Amplified fragment length polymorphism (AFLP) typing was applied to 116 Streptococcus suis isolates with different clinical backgrounds (invasive/pneumonia/carrier/human) and with known profiles of virulence-associated genes (cps1, -2, -7 and -9, as well as mrp, epf and sly). A dendrogram was generated that allowed identification of two clusters (A and C) with different subclusters (A1, A2, C1 and C2) and two heterogeneous groups of strains (B and D). For comparison, three strains from each AFLP subcluster and group were subjected to multilocus sequence typing (MLST) analysis. The closest relationship and lowest diversity were found for patterns clustering within AFLP subcluster A1, which corresponded with sequence type (ST) complex 1. Strains within subcluster A1 were mainly invasive cps1 and mrp+ epf+ (or epf*) sly+ cps2+ strains of porcine or human origin. A new finding of this study was the clustering of invasive mrp* cps9 isolates within subcluster A2. MLST analysis suggested that A2 correlates with a single ST complex (ST87). In contrast to A1 and A2, subclusters C1 and C2 contained mainly pneumonia isolates of genotype cps7 or cps2 and epf- sly-. In conclusion, this study demonstrates that AFLP allows identification of clusters of S. suis strains with clinical relevance.

High-Resolution Metabolic Phenotyping of Genetically and Environmentally Diverse Potato Tuber Systems. Identification of Phenocopies

PubMed Central

Roessner, Ute; Willmitzer, Lothar; Fernie, Alisdair R.

2001-01-01

We conducted a comprehensive metabolic phenotyping of potato (Solanum tuberosum L. cv Desiree) tuber tissue that had been modified either by transgenesis or exposure to different environmental conditions using a recently developed gas chromatography-mass spectrometry profiling protocol. Applying this technique, we were able to identify and quantify the major constituent metabolites of the potato tuber within a single chromatographic run. The plant systems that we selected to profile were tuber discs incubated in varying concentrations of fructose, sucrose, and mannitol and transgenic plants impaired in their starch biosynthesis. The resultant profiles were then compared, first at the level of individual metabolites and then using the statistical tools hierarchical cluster analysis and principal component analysis. These tools allowed us to assign clusters to the individual plant systems and to determine relative distances between these clusters; furthermore, analyzing the loadings of these analyses enabled identification of the most important metabolites in the definition of these clusters. The metabolic profiles of the sugar-fed discs were dramatically different from the wild-type steady-state values. When these profiles were compared with one another and also with those we assessed in previous studies, however, we were able to evaluate potential phenocopies. These comparisons highlight the importance of such an approach in the functional and qualitative assessment of diverse systems to gain insights into important mediators of metabolism. PMID:11706160

Clustering and Filtering Tandem Mass Spectra Acquired in Data-Independent Mode

NASA Astrophysics Data System (ADS)

Pak, Huisong; Nikitin, Frederic; Gluck, Florent; Lisacek, Frederique; Scherl, Alexander; Muller, Markus

2013-12-01

Data-independent mass spectrometry activates all ion species isolated within a given mass-to-charge window ( m/z) regardless of their abundance. This acquisition strategy overcomes the traditional data-dependent ion selection boosting data reproducibility and sensitivity. However, several tandem mass (MS/MS) spectra of the same precursor ion are acquired during chromatographic elution resulting in large data redundancy. Also, the significant number of chimeric spectra and the absence of accurate precursor ion masses hamper peptide identification. Here, we describe an algorithm to preprocess data-independent MS/MS spectra by filtering out noise peaks and clustering the spectra according to both the chromatographic elution profiles and the spectral similarity. In addition, we developed an approach to estimate the m/z value of precursor ions from clustered MS/MS spectra in order to improve database search performance. Data acquired using a small 3 m/z units precursor mass window and multiple injections to cover a m/z range of 400-1400 was processed with our algorithm. It showed an improvement in the number of both peptide and protein identifications by 8 % while reducing the number of submitted spectra by 18 % and the number of peaks by 55 %. We conclude that our clustering method is a valid approach for data analysis of these data-independent fragmentation spectra. The software including the source code is available for the scientific community.

Computational genomic identification and functional reconstitution of plant natural product biosynthetic pathways

PubMed Central

2016-01-01

Covering: 2003 to 2016 The last decade has seen the first major discoveries regarding the genomic basis of plant natural product biosynthetic pathways. Four key computationally driven strategies have been developed to identify such pathways, which make use of physical clustering, co-expression, evolutionary co-occurrence and epigenomic co-regulation of the genes involved in producing a plant natural product. Here, we discuss how these approaches can be used for the discovery of plant biosynthetic pathways encoded by both chromosomally clustered and non-clustered genes. Additionally, we will discuss opportunities to prioritize plant gene clusters for experimental characterization, and end with a forward-looking perspective on how synthetic biology technologies will allow effective functional reconstitution of candidate pathways using a variety of genetic systems. PMID:27321668

Preliminary Cluster Analysis For Several Representatives Of Genus Kerivoula (Chiroptera: Vespertilionidae) in Borneo

NASA Astrophysics Data System (ADS)

Hasan, Noor Haliza; Abdullah, M. T.

2008-01-01

The aim of the study is to use cluster analysis on morphometric parameters within the genus Kerivoula to produce a dendrogram and to determine the suitability of this method to describe the relationship among species within this genus. A total of 15 adult male individuals from genus Kerivoula taken from sampling trips around Borneo and specimens kept at the zoological museum of Universiti Malaysia Sarawak were examined. A total of 27 characters using dental, skull and external body measurements were recorded. Clustering analysis illustrated the grouping and morphometric relationships between the species of this genus. It has clearly separated each species from each other despite the overlapping of measurements of some species within the genus. Cluster analysis provides an alternative approach to make a preliminary identification of a species.

Revealing the first uridyl peptide antibiotic biosynthetic gene cluster and probing pacidamycin biosynthesis.

PubMed

Rackham, Emma J; Grüschow, Sabine; Goss, Rebecca J M

2011-01-01

There is an urgent need for new antibiotics with resistance continuing to emerge toward existing classes. The pacidamycin antibiotics possess a novel scaffold and exhibit unexploited bioactivity rendering them attractive research targets. We recently reported the first identification of a biosynthetic cluster encoding uridyl peptide antibiotic assembly and the engineering of pacidamycin biosynthesis into a heterologous host. We report here our methods toward identifying the biosynthetic cluster. Our initial experiments employed conventional methods of probing a cosmid library using PCR and Southern blotting, however it became necessary to adopt a state-of-the-art genome scanning  and in silico hybridization approach  to pin point the cluster. Here we describe our "real" and "virtual" probing methods and contrast the benefits and pitfalls of each approach. 

Empirical entropic contributions in computational docking: evaluation in APS reductase complexes.

PubMed

Chang, Max W; Belew, Richard K; Carroll, Kate S; Olson, Arthur J; Goodsell, David S

2008-08-01

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments. 2008 Wiley Periodicals, Inc.

Finding clusters of similar events within clinical incident reports: a novel methodology combining case based reasoning and information retrieval

PubMed Central

Tsatsoulis, C; Amthauer, H

2003-01-01

A novel methodological approach for identifying clusters of similar medical incidents by analyzing large databases of incident reports is described. The discovery of similar events allows the identification of patterns and trends, and makes possible the prediction of future events and the establishment of barriers and best practices. Two techniques from the fields of information science and artificial intelligence have been integrated—namely, case based reasoning and information retrieval—and very good clustering accuracies have been achieved on a test data set of incident reports from transfusion medicine. This work suggests that clustering should integrate the features of an incident captured in traditional form based records together with the detailed information found in the narrative included in event reports. PMID:14645892

Assessment of Social Vulnerability Identification at Local Level around Merapi Volcano - A Self Organizing Map Approach

NASA Astrophysics Data System (ADS)

Lee, S.; Maharani, Y. N.; Ki, S. J.

2015-12-01

The application of Self-Organizing Map (SOM) to analyze social vulnerability to recognize the resilience within sites is a challenging tasks. The aim of this study is to propose a computational method to identify the sites according to their similarity and to determine the most relevant variables to characterize the social vulnerability in each cluster. For this purposes, SOM is considered as an effective platform for analysis of high dimensional data. By considering the cluster structure, the characteristic of social vulnerability of the sites identification can be fully understand. In this study, the social vulnerability variable is constructed from 17 variables, i.e. 12 independent variables which represent the socio-economic concepts and 5 dependent variables which represent the damage and losses due to Merapi eruption in 2010. These variables collectively represent the local situation of the study area, based on conducted fieldwork on September 2013. By using both independent and dependent variables, we can identify if the social vulnerability is reflected onto the actual situation, in this case, Merapi eruption 2010. However, social vulnerability analysis in the local communities consists of a number of variables that represent their socio-economic condition. Some of variables employed in this study might be more or less redundant. Therefore, SOM is used to reduce the redundant variable(s) by selecting the representative variables using the component planes and correlation coefficient between variables in order to find the effective sample size. Then, the selected dataset was effectively clustered according to their similarities. Finally, this approach can produce reliable estimates of clustering, recognize the most significant variables and could be useful for social vulnerability assessment, especially for the stakeholder as decision maker. This research was supported by a grant 'Development of Advanced Volcanic Disaster Response System considering Potential Volcanic Risk around Korea' [MPSS-NH-2015-81] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea. Keywords: Self-organizing map, Component Planes, Correlation coefficient, Cluster analysis, Sites identification, Social vulnerability, Merapi eruption 2010

Genetic Diversity of the fliC Genes Encoding the Flagellar Antigen H19 of Escherichia coli and Application to the Specific Identification of Enterohemorrhagic E. coli O121:H19.

PubMed

Beutin, Lothar; Delannoy, Sabine; Fach, Patrick

2015-06-15

Enterohemorrhagic Escherichia coli (EHEC) O121:H19 belong to a specific clonal type distinct from other classical EHEC and major enteropathogenic E. coli groups and is regarded as one of the major EHEC serogroups involved in severe infections in humans. Sequencing of the fliC genes associated with the flagellar antigen H19 (fliCH19) revealed the genetic diversity of the fliCH19 gene sequences in E. coli. A cluster analysis of 12 fliCH19 sequences, 4 from O121 and 8 from non-O121 E. coli strains, revealed five different genotypes. All O121:H19 strains fell into one cluster, whereas a second cluster was formed by five non-O121:H19 strains. Cluster 1 and cluster 2 strains differ by 27 single nucleotide exchanges in their fliCH19 genes (98.5% homology). Based on allele discrimination of the fliCH19 genes, a real-time PCR test was designed for specific identification of EHEC O121:H19. The O121 fliCH19 PCR tested negative in 73 E. coli H19 strains that belonged to serogroups other than O121, including 28 different O groups, O-nontypeable H19, and O-rough:H19 strains. The O121 fliCH19 PCR reacted with all 16 tested O121:H19 strains and 1 O-rough:H19 strain which was positive for the O121 wzx gene. A cross-reaction was observed only with E. coli H32 strains which share sequence similarities in the target region of the O121 fliCH19 PCR. The combined use of O-antigen genotyping (O121 wzx) and the detection of O121 fliCH19 allele type contributes to improving the identification and molecular serotyping of EHEC O121:H19 motile and nonmotile strains and variants of these strains lacking stx genes. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Genetic Diversity of the fliC Genes Encoding the Flagellar Antigen H19 of Escherichia coli and Application to the Specific Identification of Enterohemorrhagic E. coli O121:H19

PubMed Central

Beutin, Lothar; Delannoy, Sabine

2015-01-01

Enterohemorrhagic Escherichia coli (EHEC) O121:H19 belong to a specific clonal type distinct from other classical EHEC and major enteropathogenic E. coli groups and is regarded as one of the major EHEC serogroups involved in severe infections in humans. Sequencing of the fliC genes associated with the flagellar antigen H19 (fliCH19) revealed the genetic diversity of the fliCH19 gene sequences in E. coli. A cluster analysis of 12 fliCH19 sequences, 4 from O121 and 8 from non-O121 E. coli strains, revealed five different genotypes. All O121:H19 strains fell into one cluster, whereas a second cluster was formed by five non-O121:H19 strains. Cluster 1 and cluster 2 strains differ by 27 single nucleotide exchanges in their fliCH19 genes (98.5% homology). Based on allele discrimination of the fliCH19 genes, a real-time PCR test was designed for specific identification of EHEC O121:H19. The O121 fliCH19 PCR tested negative in 73 E. coli H19 strains that belonged to serogroups other than O121, including 28 different O groups, O-nontypeable H19, and O-rough:H19 strains. The O121 fliCH19 PCR reacted with all 16 tested O121:H19 strains and 1 O-rough:H19 strain which was positive for the O121 wzx gene. A cross-reaction was observed only with E. coli H32 strains which share sequence similarities in the target region of the O121 fliCH19 PCR. The combined use of O-antigen genotyping (O121 wzx) and the detection of O121 fliCH19 allele type contributes to improving the identification and molecular serotyping of EHEC O121:H19 motile and nonmotile strains and variants of these strains lacking stx genes. PMID:25862232

A Feasibility Study of View-independent Gait Identification

DTIC Science & Technology

2012-03-01

ice skates . For walking, the footprint records for single pixels form clusters that are well separated in space and time. (Any overlap of contact...Pattern Recognition 2007, 1-8. Cheng M-H, Ho M-F & Huang C-L (2008), "Gait Analysis for Human Identification Through Manifold Learning and HMM... Learning and Cybernetics 2005, 4516-4521 Moeslund T B & Granum E (2001), "A Survey of Computer Vision-Based Human Motion Capture", Computer Vision

Sleep stages identification in patients with sleep disorder using k-means clustering

NASA Astrophysics Data System (ADS)

Fadhlullah, M. U.; Resahya, A.; Nugraha, D. F.; Yulita, I. N.

2018-05-01

Data mining is a computational intelligence discipline where a large dataset processed using a certain method to look for patterns within the large dataset. This pattern then used for real time application or to develop some certain knowledge. This is a valuable tool to solve a complex problem, discover new knowledge, data analysis and decision making. To be able to get the pattern that lies inside the large dataset, clustering method is used to get the pattern. Clustering is basically grouping data that looks similar so a certain pattern can be seen in the large data set. Clustering itself has several algorithms to group the data into the corresponding cluster. This research used data from patients who suffer sleep disorders and aims to help people in the medical world to reduce the time required to classify the sleep stages from a patient who suffers from sleep disorders. This study used K-Means algorithm and silhouette evaluation to find out that 3 clusters are the optimal cluster for this dataset which means can be divided to 3 sleep stages.

Moving Object Localization Based on UHF RFID Phase and Laser Clustering

PubMed Central

Fu, Yulu; Wang, Changlong; Liang, Gaoli; Zhang, Hua; Ur Rehman, Shafiq

2018-01-01

RFID (Radio Frequency Identification) offers a way to identify objects without any contact. However, positioning accuracy is limited since RFID neither provides distance nor bearing information about the tag. This paper proposes a new and innovative approach for the localization of moving object using a particle filter by incorporating RFID phase and laser-based clustering from 2d laser range data. First of all, we calculate phase-based velocity of the moving object based on RFID phase difference. Meanwhile, we separate laser range data into different clusters, and compute the distance-based velocity and moving direction of these clusters. We then compute and analyze the similarity between two velocities, and select K clusters having the best similarity score. We predict the particles according to the velocity and moving direction of laser clusters. Finally, we update the weights of the particles based on K clusters and achieve the localization of moving objects. The feasibility of this approach is validated on a Scitos G5 service robot and the results prove that we have successfully achieved a localization accuracy up to 0.25 m. PMID:29522458

Radio emission in the directions of cD and related galaxies in poor clusters. III. VLA observations at 20 cm

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

Burns, J.O.; White, R.A.; Hough, D.H.

1981-01-01

VLA radio maps and optical identifications of a sample of sources in the directions of 21 Yerkes poor cluster fields are presented. The majority of the cluster radio sources are associated with the dominant D or cD galaxies (approx.70%). Our analysis of dominant galaxies in rich and poor clusters indicates that these giant galaxies are much more often radio emitters (approx.25% of cD's are radio active in the poor clusters), have steeper radio spectra, and have simpler radio morphologies (i.e., double or other linear structure) than other less bright ellipticals. A strong continuum of radio properties in cD galaxies ismore » seen from rich to poor clusters. We speculate that the location of these dominant galaxies at the cluster centers (i.e., at the bottom of a deep, isolated gravitational potential well) is the crucial factor in explaining their multifrequency activity. We briefly discuss galaxy cannibalism and gas infall models as fueling mechanisms for the observed radio and x-ray emission.« less

Radio emission in the directions of cD and related galaxies in poor clusters. III - VLA observations at 20 cm

NASA Technical Reports Server (NTRS)

Burns, J. O.; White, R. A.; Hough, D. H.

1981-01-01

VLA radio maps and optical identifications of a sample of sources in the directions of 21 Yerkes poor cluster fields are presented. The majority of the cluster radio sources are associated with the dominant D or cD galaxies (approximately 70 percent). Our analysis of dominant galaxies in rich and poor clusters indicates that these giant galaxies are much more often radio emitters (approximately 25 percent of cD's are radio active in the poor clusters), have steeper radio spectra, and have simpler radio morphologies (i.e., double or other linear structure) than other less bright ellipticals. A strong continuum of radio properties in cD galaxies is seen from rich to poor clusters. It is speculated that the location of these dominant galaxies at the cluster centers (i.e., at the bottom of a deep, isolated gravitational potential well) is the crucial factor in explaining their multifrequency activity. Galaxy cannibalism and gas infall models as fueling mechanisms for the observed radio and X-ray emission are discussed

Personality Patterns Among Correctional Officer Applicants

ERIC Educational Resources Information Center

Holland, Terrill R.; And Others

1976-01-01

The MMPI profiles of 359 correctional officer applicants were cluster analyzed, which resulted in the identification of five relatively homogeneous subgroups. The implications of the findings for occupationally adaptive and maladaptive correctional officer behavior were discussed. (Editor)

Identification and Characterization of Memecylon Species Using Isozyme Profiling

PubMed Central

Bharathi, T. R.; Sekhar, Shailasree; Geetha, N.; Niranjana, S. R.; Prakash, H. S.

2017-01-01

Background: The protein/isozyme fingerprint is useful in differentiating the species and acts as a biochemical marker for identification and systematic studies of medicinal plant species. Objective: In the present study, protein and isozyme profiles for peroxidase, esterase, acid phosphatase, polyphenol oxidase, alcohol dehydrogenase, and alkaline phosphatase of five species of Memecylon (Melastomataceae), Memecylon umbellatum, Memecylon edule, Memecylon talbotianum, Memecylon malabaricum, and Memecylon wightii were investigated. Materials and Methods: Fresh leaves were used to prepare crude enzyme extract for analyzing the five enzymes isozyme variations. Separation of isozymes was carried out using polyacrylamide gel electrophoresis (PAGE) and the banding patterns of protein were scored. Pair-wise comparisons of genotypes, based on the presence or absence of unique and shared polymorphic products, were used to regenerate similarity coefficients. The similarity coefficients were then used to construct dendrograms, using the unweighted pair group method with arithmetic averages. Results: A total of 50 bands with various Rf values and molecular weight were obtained through PAGE analysis. Among the five Memecylon species, more number of bands was produced in M. wightii and less number of bands was observed in M. edule. The results of similarity indices grouped M. malabaricum and M. wightii in one cluster with 98% similarity and M. umbellatum, M. edule, and M. talbotianum are grouped in another cluster with 79% similarity showing close genetic similarities which is in accordance with the morphological identification of Memecylon species. Conclusion: The protein/isozyme fingerprint is useful in differentiating the species and acts as a biochemical marker for identification of Memecylon species. SUMMARY Biochemical characterization of Memecylon species was evaluated by SDS-PAGE of extracted protein and isozyme profiling on native PAGE.After electrophoresis, each gel was stained with specific stains. Genetic distance relationships were evaluated based on the banding patterns of protein on isozymes.Unique banding pattern of esterase, peroxidase, acid phosphatase, alcohol dehydrogenase and polyphenol oxidase are observed in all the five species of Memecylon, which represent the fingerprint of Memecylon species.SDS-PAGE and isozyme profiling of five Memecylon species revealed that M. malabaricum and M. wightii grouped in one cluster and M. umbellatum, M. edule and M. talbotianum grouped in another cluster showing close genetic similarities which is in accordance with the morphological identification of Memecylon species.This is the first report on the comparison of protein and isozyme profile of five different Memecylon species. Abbreviations Used: SDS-PAGE: Sodium docecyl sulfate polyacrylamide gel electrophoresis; NTSYS PC2: Numerical taxonomy system, version 2.2 for Windows XP, Vista, Win7, Win 8 and Win10 including 64 bit PMID:29263637

Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma.

PubMed

Youroukova, Vania M; Dimitrova, Denitsa G; Valerieva, Anna D; Lesichkova, Spaska S; Velikova, Tsvetelina V; Ivanova-Todorova, Ekaterina I; Tumangelova-Yuzeir, Kalina D

2017-06-01

Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms. To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters. Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters. We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma. Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.

A Clustering Algorithm for Ecological Stream Segment Identification from Spatially Extensive Digital Databases

NASA Astrophysics Data System (ADS)

Brenden, T. O.; Clark, R. D.; Wiley, M. J.; Seelbach, P. W.; Wang, L.

2005-05-01

Remote sensing and geographic information systems have made it possible to attribute variables for streams at increasingly detailed resolutions (e.g., individual river reaches). Nevertheless, management decisions still must be made at large scales because land and stream managers typically lack sufficient resources to manage on an individual reach basis. Managers thus require a method for identifying stream management units that are ecologically similar and that can be expected to respond similarly to management decisions. We have developed a spatially-constrained clustering algorithm that can merge neighboring river reaches with similar ecological characteristics into larger management units. The clustering algorithm is based on the Cluster Affinity Search Technique (CAST), which was developed for clustering gene expression data. Inputs to the clustering algorithm are the neighbor relationships of the reaches that comprise the digital river network, the ecological attributes of the reaches, and an affinity value, which identifies the minimum similarity for merging river reaches. In this presentation, we describe the clustering algorithm in greater detail and contrast its use with other methods (expert opinion, classification approach, regular clustering) for identifying management units using several Michigan watersheds as a backdrop.

An exploration into study design for biomarker identification: issues and recommendations.

PubMed

Hall, Jacqueline A; Brown, Robert; Paul, Jim

2007-01-01

Genomic profiling produces large amounts of data and a challenge remains in identifying relevant biological processes associated with clinical outcome. Many candidate biomarkers have been identified but few have been successfully validated and make an impact clinically. This review focuses on some of the study design issues encountered in data mining for biomarker identification with illustrations of how study design may influence the final results. This includes issues of clinical endpoint use and selection, power, statistical, biological and clinical significance. We give particular attention to study design for the application of supervised clustering methods for identification of gene networks associated with clinical outcome and provide recommendations for future work to increase the success of identification of clinically relevant biomarkers.

Cultivar identification and genetic relationship of pineapple (Ananas comosus) cultivars using SSR markers.

PubMed

Lin, Y S; Kuan, C S; Weng, I S; Tsai, C C

2015-11-25

The genetic relationships among 27 pineapple [Ananas comosus (L.) Merr.] cultivars and lines were examined using 16 simple sequence repeat (SSR) markers. The number of alleles per locus of the SSR markers ranged from 2 to 6 (average 3.19), for a total of 51 alleles. Similarity coefficients were calculated on the basis of 51 amplified bands. A dendrogram was created according to the 16 SSR markers by the unweighted pair-group method. The banding patterns obtained from the SSR primers allowed most of the cultivars and lines to be distinguished, with the exception of vegetative clones. According to the dendrogram, the 27 pineapple cultivars and lines were clustered into three main clusters and four individual clusters. As expected, the dendrogram showed that derived cultivars and lines are closely related to their parental cultivars; the genetic relationships between pineapple cultivars agree with the genealogy of their breeding history. In addition, the analysis showed that there is no obvious correlation between SSR markers and morphological characters. In conclusion, SSR analysis is an efficient method for pineapple cultivar identification and can offer valuable informative characters to identify pineapple cultivars in Taiwan.

Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

NASA Astrophysics Data System (ADS)

Palumbo, Francesco; D'Enza, Alfonso Iodice

The attention towards binary data coding increased consistently in the last decade due to several reasons. The analysis of binary data characterizes several fields of application, such as market basket analysis, DNA microarray data, image mining, text mining and web-clickstream mining. The paper illustrates two different approaches exploiting a profitable combination of clustering and dimensionality reduction for the identification of non-trivial association structures in binary data. An application in the Association Rules framework supports the theory with the empirical evidence.

Identification of sea ice types in spaceborne synthetic aperture radar data

NASA Technical Reports Server (NTRS)

Kwok, Ronald; Rignot, Eric; Holt, Benjamin; Onstott, R.

1992-01-01

This study presents an approach for identification of sea ice types in spaceborne SAR image data. The unsupervised classification approach involves cluster analysis for segmentation of the image data followed by cluster labeling based on previously defined look-up tables containing the expected backscatter signatures of different ice types measured by a land-based scatterometer. Extensive scatterometer observations and experience accumulated in field campaigns during the last 10 yr were used to construct these look-up tables. The classification approach, its expected performance, the dependence of this performance on radar system performance, and expected ice scattering characteristics are discussed. Results using both aircraft and simulated ERS-1 SAR data are presented and compared to limited field ice property measurements and coincident passive microwave imagery. The importance of an integrated postlaunch program for the validation and improvement of this approach is discussed.

A Spacecraft Electrical Characteristics Multi-Label Classification Method Based on Off-Line FCM Clustering and On-Line WPSVM

PubMed Central

Li, Ke; Liu, Yi; Wang, Quanxin; Wu, Yalei; Song, Shimin; Sun, Yi; Liu, Tengchong; Wang, Jun; Li, Yang; Du, Shaoyi

2015-01-01

This paper proposes a novel multi-label classification method for resolving the spacecraft electrical characteristics problems which involve many unlabeled test data processing, high-dimensional features, long computing time and identification of slow rate. Firstly, both the fuzzy c-means (FCM) offline clustering and the principal component feature extraction algorithms are applied for the feature selection process. Secondly, the approximate weighted proximal support vector machine (WPSVM) online classification algorithms is used to reduce the feature dimension and further improve the rate of recognition for electrical characteristics spacecraft. Finally, the data capture contribution method by using thresholds is proposed to guarantee the validity and consistency of the data selection. The experimental results indicate that the method proposed can obtain better data features of the spacecraft electrical characteristics, improve the accuracy of identification and shorten the computing time effectively. PMID:26544549

Geographic clustering of elderly people with above-norm anthropometric measurements and blood chemistry.

PubMed

Mena, Carlos; Fuentes, Eduardo; Ormazábal, Yony; Palomo, Iván

2017-05-11

The global percentage of people over 60 is strongly increasing and estimated to exceed 20% by 20,150, which means that there will be an increase in many pathological conditions related to aging. Mapping of the location of aging people and identification of their needs can be extremely valuable from a social-economic point of view. Participants in this study were 148 randomly selected adults from Talca City, Chile aged 60-74 at baseline. Geographic information systems (GIS) analyses were performed using ArcGIS software through its module Spatial Autocorrelation. In this study, we demonstrated that elderly people show geographic clustering according to above-norm results of anthropometric measurements and blood chemistry. The spatial identifications found would facilitate exploring the impact of treatment programmes in communities where many aging people live, thereby improving their quality of life as well as reducing overall costs.

MapReduce implementation of a hybrid spectral library-database search method for large-scale peptide identification.

PubMed

Kalyanaraman, Ananth; Cannon, William R; Latt, Benjamin; Baxter, Douglas J

2011-11-01

A MapReduce-based implementation called MR-MSPolygraph for parallelizing peptide identification from mass spectrometry data is presented. The underlying serial method, MSPolygraph, uses a novel hybrid approach to match an experimental spectrum against a combination of a protein sequence database and a spectral library. Our MapReduce implementation can run on any Hadoop cluster environment. Experimental results demonstrate that, relative to the serial version, MR-MSPolygraph reduces the time to solution from weeks to hours, for processing tens of thousands of experimental spectra. Speedup and other related performance studies are also reported on a 400-core Hadoop cluster using spectral datasets from environmental microbial communities as inputs. The source code along with user documentation are available on http://compbio.eecs.wsu.edu/MR-MSPolygraph. ananth@eecs.wsu.edu; william.cannon@pnnl.gov. Supplementary data are available at Bioinformatics online.

Towards the identification of plant and animal binders on Australian stone knives.

PubMed

Blee, Alisa J; Walshe, Keryn; Pring, Allan; Quinton, Jamie S; Lenehan, Claire E

2010-07-15

There is limited information regarding the nature of plant and animal residues used as adhesives, fixatives and pigments found on Australian Aboriginal artefacts. This paper reports the use of FTIR in combination with the chemometric tools principal component analysis (PCA) and hierarchical clustering (HC) for the analysis and identification of Australian plant and animal fixatives on Australian stone artefacts. Ten different plant and animal residues were able to be discriminated from each other at a species level by combining FTIR spectroscopy with the chemometric data analysis methods, principal component analysis (PCA) and hierarchical clustering (HC). Application of this method to residues from three broken stone knives from the collections of the South Australian Museum indicated that two of the handles of knives were likely to have contained beeswax as the fixative whilst Spinifex resin was the probable binder on the third. Copyright 2010 Elsevier B.V. All rights reserved.

Algorithm to determine the percolation largest component in interconnected networks.

PubMed

Schneider, Christian M; Araújo, Nuno A M; Herrmann, Hans J

2013-04-01

Interconnected networks have been shown to be much more vulnerable to random and targeted failures than isolated ones, raising several interesting questions regarding the identification and mitigation of their risk. The paradigm to address these questions is the percolation model, where the resilience of the system is quantified by the dependence of the size of the largest cluster on the number of failures. Numerically, the major challenge is the identification of this cluster and the calculation of its size. Here, we propose an efficient algorithm to tackle this problem. We show that the algorithm scales as O(NlogN), where N is the number of nodes in the network, a significant improvement compared to O(N(2)) for a greedy algorithm, which permits studying much larger networks. Our new strategy can be applied to any network topology and distribution of interdependencies, as well as any sequence of failures.

VizieR Online Data Catalog: Spitzer photometry of globulars in 2 galaxies (Spitler+, 2008)

NASA Astrophysics Data System (ADS)

Spitler, L. R.; Forbes, D. A.; Beasley, M. A.

2010-06-01

Catalogues are described in Spitler et al. (2008MNRAS.389.1150S) All photometry is corrected for Galactic dust extinction and are on the Vega photometric system. NGC 5128 optical photometry is from Peng et al. (2004ApJS..150..367P), as compiled in Woodley et al. (2007AJ....134..494W). Globular cluster identification numbers are from Woodley et al. (2007, Cat. J/AJ/134/494). NGC 4594 optical photometry is from Spitler et al. (2006AJ....132.1593S) updated with new aperture corrections as described in Harris et al. (2010MNRAS.401.1965H). Identification number, globular cluster half-light radii and the assumed distance modulus for the half-light radii are from Spitler et al. (2006, Cat. J/AJ/132/1593). A ultra-compact dwarf galaxy is included in this catalogue with ID="ucd" (see also Hau et al. 2009MNRAS.394L..97H). (2 data files).

Genome-wide identification of physically clustered genes suggests chromatin-level co-regulation in male reproductive development in Arabidopsis thaliana

PubMed Central

Reimegård, Johan; Kundu, Snehangshu; Pendle, Ali; Irish, Vivian F.; Shaw, Peter

2017-01-01

Abstract Co-expression of physically linked genes occurs surprisingly frequently in eukaryotes. Such chromosomal clustering may confer a selective advantage as it enables coordinated gene regulation at the chromatin level. We studied the chromosomal organization of genes involved in male reproductive development in Arabidopsis thaliana. We developed an in-silico tool to identify physical clusters of co-regulated genes from gene expression data. We identified 17 clusters (96 genes) involved in stamen development and acting downstream of the transcriptional activator MS1 (MALE STERILITY 1), which contains a PHD domain associated with chromatin re-organization. The clusters exhibited little gene homology or promoter element similarity, and largely overlapped with reported repressive histone marks. Experiments on a subset of the clusters suggested a link between expression activation and chromatin conformation: qRT-PCR and mRNA in situ hybridization showed that the clustered genes were up-regulated within 48 h after MS1 induction; out of 14 chromatin-remodeling mutants studied, expression of clustered genes was consistently down-regulated only in hta9/hta11, previously associated with metabolic cluster activation; DNA fluorescence in situ hybridization confirmed that transcriptional activation of the clustered genes was correlated with open chromatin conformation. Stamen development thus appears to involve transcriptional activation of physically clustered genes through chromatin de-condensation. PMID:28175342

Orchiectomy for suspected microscopic tumor in patients with anti-Ma2-associated encephalitis.

PubMed

Mathew, R M; Vandenberghe, R; Garcia-Merino, A; Yamamoto, T; Landolfi, J C; Rosenfeld, M R; Rossi, J E; Thiessen, B; Dropcho, E J; Dalmau, J

2007-03-20

To report the presence of microscopic neoplasms of the testis in men with anti-Ma2-associated encephalitis (Ma2-encephalitis) and to discuss the clinical implications. Orchiectomy specimens were examined using immunohistochemistry with Ma2 and Oct4 antibodies. Among 25 patients with Ma2-encephalitis younger than 50 years, 19 had germ-cell tumors, and 6 had no evidence of cancer. These 6 patients underwent orchiectomy because they fulfilled five criteria: 1) demonstration of anti-Ma2 antibodies in association with MRI or clinical features compatible with Ma2-encephalitis, 2) life-threatening or progressive neurologic deficits, 3) age < 50 years, 4) absence of other tumors, and 5) new testicular enlargement or risk factors for germ-cell tumors, mainly cryptorchidism or ultrasound evidence of testicular microcalcifications. All orchiectomy specimens showed intratubular-germ cell neoplasms unclassified type (IGCNU) and other abnormalities including microcalcifications, atrophy, fibrosis, inflammatory infiltrates, or hypospermatogenesis. Ma2 was expressed by neoplastic cells in three of three patients examined. Even though most patients had severe neurologic deficits at the time of orchiectomy (median progression of symptoms, 10 months), 4 had partial improvement and prolonged stabilization (8 to 84 months, median 22.5 months) and two did not improve after the procedure. In young men with Ma2-encephalitis, 1) the disorder should be attributed to a germ-cell neoplasm of the testis unless another Ma2-expressing tumor is found, 2) negative tumor markers, ultrasound, body CT, or PET do not exclude an intratubular germ-cell neoplasm of the testis, and 3) if no tumor is found, the presence of the five indicated criteria should prompt consideration of orchiectomy.

Orchiectomy for suspected microscopic tumor in patients with anti-Ma2-associated encephalitis

PubMed Central

Mathew, R.M.; Vandenberghe, R.; Garcia-Merino, A.; Yamamoto, T.; Landolfi, J.C.; Rosenfeld, M.R.; Rossi, J.E.; Thiessen, B.; Dropcho, E.J.; Dalmau, J.

2007-01-01

Objective: To report the presence of microscopic neoplasms of the testis in men with anti-Ma2-associated encephalitis (Ma2-encephalitis) and to discuss the clinical implications. Methods: Orchiectomy specimens were examined using immunohistochemistry with Ma2 and Oct4 antibodies. Results: Among 25 patients with Ma2-encephalitis younger than 50 years, 19 had germ-cell tumors, and 6 had no evidence of cancer. These 6 patients underwent orchiectomy because they fulfilled five criteria: 1) demonstration of anti-Ma2 antibodies in association with MRI or clinical features compatible with Ma2-encephalitis, 2) life-threatening or progressive neurologic deficits, 3) age < 50 years, 4) absence of other tumors, and 5) new testicular enlargement or risk factors for germ-cell tumors, mainly cryptorchidism or ultrasound evidence of testicular microcalcifications. All orchiectomy specimens showed intratubular-germ cell neoplasms unclassified type (IGCNU) and other abnormalities including microcalcifications, atrophy, fibrosis, inflammatory infiltrates, or hypospermatogenesis. Ma2 was expressed by neoplastic cells in three of three patients examined. Even though most patients had severe neurologic deficits at the time of orchiectomy (median progression of symptoms, 10 months), 4 had partial improvement and prolonged stabilization (8 to 84 months, median 22.5 months) and two did not improve after the procedure. Conclusions: In young men with Ma2-encephalitis, 1) the disorder should be attributed to a germ-cell neoplasm of the testis unless another Ma2-expressing tumor is found, 2) negative tumor markers, ultrasound, body CT, or PET do not exclude an intratubular germ-cell neoplasm of the testis, and 3) if no tumor is found, the presence of the five indicated criteria should prompt consideration of orchiectomy. PMID:17151337

Vacuum-assisted stereotactic breast biopsy in the diagnosis and management of suspicious microcalcifications

PubMed Central

Esen, Gül; Tutar, Burçin; Uras, Cihan; Calay, Zerrin; İnce, Ümit; Tutar, Onur

2016-01-01

PURPOSE We aimed to present our biopsy method and retrospectively evaluate the results, upgrade rate, and follow-up findings of stereotactic vacuum-assisted breast biopsy (VABB) procedures performed in our clinic. METHODS Two hundred thirty-four patients with mammographically detected nonpalpable breast lesions underwent VABB using a 9 gauge biopsy probe and prone biopsy table. A total of 195 patients (median age 53 years, range 32–80 years) with 198 microcalcification-only lesions with a follow-up of at least one year were included in the study. The location of the lesion relative to the needle was determined from the postfire images, and unlike the conventional technique, tissue retrieval was predominantly performed from that location, followed by a complete 360° rotation, if needed. RESULTS The median core number was 8.5. Biopsy results revealed 135 benign, 24 atypical, and 39 malignant lesions. The total upgrade rate at surgery was 7.7% (6.1% for ductal carcinomas in situ and 10.5% for atypical lesions). Patients with benign lesions were followed up for a median period of 27.5 months, with no interval change. At the follow-up, scar formation was seen in 23 patients (17%); three of the scars were remarkable for resembling a malignancy. CONCLUSION Our biposy method is fast and practical, and it is easily tolerated by patients without compromising accuracy. Patients with a diagnosis of atypia still need to undergo a diagnostic surgical procedure and those with a malignancy need to undergo curative surgery, even if the lesion is totally excised at biopsy. VABB may leave a scar in the breast tissue, which may resemble a malignancy, albeit rarely. PMID:27306660

Clinical practice guidelines from the French College of Gynecologists and Obstetricians (CNGOF): benign breast tumors - short text.

PubMed

Lavoué, Vincent; Fritel, Xavier; Antoine, Martine; Beltjens, Françoise; Bendifallah, Sofiane; Boisserie-Lacroix, Martine; Boulanger, Loic; Canlorbe, Geoffroy; Catteau-Jonard, Sophie; Chabbert-Buffet, Nathalie; Chamming's, Foucauld; Chéreau, Elisabeth; Chopier, Jocelyne; Coutant, Charles; Demetz, Julie; Guilhen, Nicolas; Fauvet, Raffaele; Kerdraon, Olivier; Laas, Enora; Legendre, Guillaume; Mathelin, Carole; Nadeau, Cédric; Naggara, Isabelle Thomassin; Ngô, Charlotte; Ouldamer, Lobna; Rafii, Arash; Roedlich, Marie-Noelle; Seror, Jérémy; Séror, Jean-Yves; Touboul, Cyril; Uzan, Catherine; Daraï, Emile

2016-05-01

Screening with breast ultrasound in combination with mammography is needed to investigate a clinical breast mass (Grade B), colored single-pore breast nipple discharge (Grade C), or mastitis (Grade C). The BI-RADS system is recommended for describing and classifying abnormal breast imaging findings. For a breast abscess, a percutaneous biopsy is recommended in the case of a mass or persistent symptoms (Grade C). For mastalgia, when breast imaging is normal, no MRI or breast biopsy is recommended (Grade C). Percutaneous biopsy is recommended for a BI-RADS category 4-5 mass (Grade B). For persistent erythematous nipple or atypical eczema lesions, a nipple biopsy is recommended (Grade C). For distortion and asymmetry, a vacuum core-needle biopsy is recommended due to the risk of underestimation by simple core-needle biopsy (Grade C). For BI-RADS category 4-5 microcalcifications without any ultrasound signal, a minimum 11-G vacuum core-needle biopsy is recommended (Grade B). In the absence of microcalcifications on radiography cores additional samples are recommended (Grade B). For atypical ductal hyperplasia, atypical lobular hyperplasia, lobular carcinoma in situ, flat epithelial atypia, radial scar and mucocele with atypia, surgical excision is commonly recommended (Grade C). Expectant management is feasible after multidisciplinary consensus. For these lesions, when excision margins are not clear, no new excision is recommended except for LCIS characterized as pleomorphic or with necrosis (Grade C). For grade 1 phyllodes tumor, surgical resection with clear margins is recommended. For grade 2 phyllodes tumor, 10mm margins are recommended (Grade C). For papillary breast lesions without atypia, complete disappearance of the radiological signal is recommended (Grade C). For papillary breast lesions with atypia, complete surgical excision is recommended (Grade C). Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Deep learning and three-compartment breast imaging in breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Drukker, Karen; Huynh, Benjamin Q.; Giger, Maryellen L.; Malkov, Serghei; Avila, Jesus I.; Fan, Bo; Joe, Bonnie; Kerlikowske, Karla; Drukteinis, Jennifer S.; Kazemi, Leila; Pereira, Malesa M.; Shepherd, John

2017-03-01

We investigated whether deep learning has potential to aid in the diagnosis of breast cancer when applied to mammograms and biologic tissue composition images derived from three-compartment (3CB) imaging. The dataset contained diagnostic mammograms and 3CB images (water, lipid, and protein content) of biopsy-sampled BIRADS 4 and 5 lesions in 195 patients. In 58 patients, the lesion manifested as a mass (13 malignant vs. 45 benign), in 87 as microcalcifications (19 vs. 68), and in 56 as (focal) asymmetry or architectural distortion (11 vs. 45). Six patients had both a mass and calcifications. For each mammogram and corresponding 3CB images, a 128x128 region of interest containing the lesion was selected by an expert radiologist and used directly as input to a deep learning method pretrained on a very large independent set of non-medical images. We used a nested leave-one-out-by-case (patient) model selection and classification protocol. The area under the ROC curve (AUC) for the task of distinguishing between benign and malignant lesions was used as performance metric. For the cases with mammographic masses, the AUC increased from 0.83 (mammograms alone) to 0.89 (mammograms+3CB, p=.162). For the microcalcification and asymmetry/architectural distortion cases the AUC increased from 0.84 to 0.91 (p=.116) and from 0.61 to 0.87 (p=.006), respectively. Our results indicate great potential for the application of deep learning methods in the diagnosis of breast cancer and additional knowledge of the biologic tissue composition appeared to improve performance, especially for lesions mammographically manifesting as asymmetries or architectural distortions.

Hydrophobically Modified Glycol Chitosan Nanoparticles for Targeting Breast Cancer Microcalcification Using Alendronate Probes

NASA Astrophysics Data System (ADS)

Vishnu, Kamalakannan

In 2016, invasive breast cancer was diagnosed in about 246,660 women and 2,600 men. An additional 61,000 new cases of in situ breast cancer was diagnosed in women. Microcalcifications are most common abnormalities detected by mammography for breast cancer, present in about 30% of all malignant breast lesions. Tumor specific biomarkers are used for targeting these abnormalities. Nanoparticles with multimodal and combinatorial therapies and conjunction of bio-ligands for specific molecular targeting using surface modifications effectually deliver a variety of drugs and are simultaneously used to image tumor progression. Alendronate, a germinal bisphosphonate conjugation as a targeting ligand would improve the nanoparticle's direct binding to hydroxyapatite (HA) mimicking calcified spots in breast cancer lesions. In this study, the hydrophobically modified glycol chitosan (HGC) micelle was modified with alendronate surface functionalization using a biotin-avidin interaction to improve the nanomicelle's calcification targeting ability. Biotinylated, avidinlyated hydrophobically modified iv glycol chitosan particles were linked to biotinylated alendronate via a strong biotin-avidin linkage. Cyanine 3, a red fluorescent dye was conjugated to the amine groups on HGC for visualization of micelles. The size of the nanoparticles measured was 254.0 +/- 0.43 nm and 209.7 +/- 1.0 nm for Cy3- BHGCA and Cy3-BHGCA-BALN nanoparticles respectively. The average surface charge was measured to be +26.9 +/- 0.19 mV and +27.68 +/- 0.20 mV for Cy3-BHGCA and Cy3-BHGCA- BALN nanoparticles respectively. Binding affinity using hydroxyapatite (HA) revealed that both Cy3 BHGCA BALN and Cy3 BHGCA nanoparticles displayed 95% binding in 24 hours. However, the biotin quenched nanoparticle Cy3 BHGCAB displayed 68% binding in 24 hours. The synthesis and binding chemistry was verified using Fourier transform infrared spectroscopy (FTIR).

Characterization and identification of microorganisms by FT-IR microspectrometry

NASA Astrophysics Data System (ADS)

Ngo-Thi, N. A.; Kirschner, C.; Naumann, D.

2003-12-01

We report on a novel FT-IR approach for microbial characterization/identification based on a light microscope coupled to an infrared spectrometer which offers the possibility to acquire IR-spectra of microcolonies containing only few hundred cells. Microcolony samples suitable for FT-IR microspectroscopic measurements were obtained by a replica technique with a stamping device that transfers spatially accurate cells of microcolonies growing on solid culture plates to a special, IR-transparent or reflecting stamping plate. High quality spectra could be recorded either by applying the transmission/absorbance or the reflectance/absorbance mode of the infrared microscope. Signal to noise ratios higher than 1000 were obtained for microcolonies as small as 40 μm in diameter. Reproducibility levels were established that allowed species and strain identification. The differentiation and classification capacity of the FT-IR microscopic technique was tested for different selected microorganisms. Cluster and factor analysis methods were used to evaluate the complex spectral data. Excellent discrimination between bacteria and yeasts, and at the same time Gram-negative and Gram-positive bacterial strains was obtained. Twenty-two selected strains of different species within the genus Staphylococcus were repetitively measured and could be grouped into correct species cluster. Moreover, the results indicated that the method allows also identifications at the subspecies level. Additionally, the new approach allowed spectral mapping analysis of single colonies which provided spatially resolved characterization of growth heterogeneity within complex microbial populations such as colonies.

(GTG)(5)-PCR fingerprinting of lactobacilli isolated from cervix of healthy women.

PubMed

Svec, P; Sedláček, I; Chrápavá, M; Vandamme, P

2011-01-01

A group of lactobacilli isolated from the cervix of 31 healthy women was characterized by (GTG)(5)-polymerase chain reaction (PCR) fingerprinting in order to evaluate this method for identification of vaginal lactobacilli. Obtained fingerprints were compared with profiles available in an in-house database of the CCM bacteria collection covering type and reference strains of multiple lactic acid bacteria including lactobacilli. Selected strains representing individual clusters were further identified by pheS gene sequencing. In total, six lactobacillus species were found among lactobacilli isolated from the cervix of healthy women. The (GTG)(5)-PCR method identified Lactobacillus gasseri (11 strains), Lactobacillus fermentum (one), and some of the Lactobacillus jensenii strains (eight out of 11), but failed to identify the remaining strains, including the Lactobacillus crispatus (18), Lactobacillus mucosae (one), and Lactobacillus vaginalis (one) species. L. jensenii strains were distributed over two fingerprint clusters. The majority of samples was dominated by one (GTG)(5)-PCR type. The rep-PCR fingerprinting using the (GTG)(5) primer allowed straightforward identification of many, but not all, isolates. This method has been shown to be a useful tool for fast screening and grouping of vaginal lactobacilli, but its combination with another identification method is needed to obtain reliable identification results. In addition, Lactobacillus acidophilus was not shown to be the most common inhabitant of the female genital tract as generally assumed.

A comparison of heuristic and model-based clustering methods for dietary pattern analysis.

PubMed

Greve, Benjamin; Pigeot, Iris; Huybrechts, Inge; Pala, Valeria; Börnhorst, Claudia

2016-02-01

Cluster analysis is widely applied to identify dietary patterns. A new method based on Gaussian mixture models (GMM) seems to be more flexible compared with the commonly applied k-means and Ward's method. In the present paper, these clustering approaches are compared to find the most appropriate one for clustering dietary data. The clustering methods were applied to simulated data sets with different cluster structures to compare their performance knowing the true cluster membership of observations. Furthermore, the three methods were applied to FFQ data assessed in 1791 children participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants) Study to explore their performance in practice. The GMM outperformed the other methods in the simulation study in 72 % up to 100 % of cases, depending on the simulated cluster structure. Comparing the computationally less complex k-means and Ward's methods, the performance of k-means was better in 64-100 % of cases. Applied to real data, all methods identified three similar dietary patterns which may be roughly characterized as a 'non-processed' cluster with a high consumption of fruits, vegetables and wholemeal bread, a 'balanced' cluster with only slight preferences of single foods and a 'junk food' cluster. The simulation study suggests that clustering via GMM should be preferred due to its higher flexibility regarding cluster volume, shape and orientation. The k-means seems to be a good alternative, being easier to use while giving similar results when applied to real data.

A proximity-based graph clustering method for the identification and application of transcription factor clusters.

PubMed

Spadafore, Maxwell; Najarian, Kayvan; Boyle, Alan P

2017-11-29

Transcription factors (TFs) form a complex regulatory network within the cell that is crucial to cell functioning and human health. While methods to establish where a TF binds to DNA are well established, these methods provide no information describing how TFs interact with one another when they do bind. TFs tend to bind the genome in clusters, and current methods to identify these clusters are either limited in scope, unable to detect relationships beyond motif similarity, or not applied to TF-TF interactions. Here, we present a proximity-based graph clustering approach to identify TF clusters using either ChIP-seq or motif search data. We use TF co-occurrence to construct a filtered, normalized adjacency matrix and use the Markov Clustering Algorithm to partition the graph while maintaining TF-cluster and cluster-cluster interactions. We then apply our graph structure beyond clustering, using it to increase the accuracy of motif-based TFBS searching for an example TF. We show that our method produces small, manageable clusters that encapsulate many known, experimentally validated transcription factor interactions and that our method is capable of capturing interactions that motif similarity methods might miss. Our graph structure is able to significantly increase the accuracy of motif TFBS searching, demonstrating that the TF-TF connections within the graph correlate with biological TF-TF interactions. The interactions identified by our method correspond to biological reality and allow for fast exploration of TF clustering and regulatory dynamics.

Algorithms development for the GEM-based detection system

NASA Astrophysics Data System (ADS)

Czarski, T.; Chernyshova, M.; Malinowski, K.; Pozniak, K. T.; Kasprowicz, G.; Kolasinski, P.; Krawczyk, R.; Wojenski, A.; Zabolotny, W.

2016-09-01

The measurement system based on GEM - Gas Electron Multiplier detector - is developed for soft X-ray diagnostics of tokamak plasmas. The multi-channel setup is designed for estimation of the energy and the position distribution of an Xray source. The focal measuring issue is the charge cluster identification by its value and position estimation. The fast and accurate mode of the serial data acquisition is applied for the dynamic plasma diagnostics. The charge clusters are counted in the space determined by 2D position, charge value and time intervals. Radiation source characteristics are presented by histograms for a selected range of position, time intervals and cluster charge values corresponding to the energy spectra.

A faint field-galaxy redshift survey in quasar fields

NASA Technical Reports Server (NTRS)

Yee, Howard K. C.; Ellingson, Erica

1993-01-01

Quasars serve as excellent markers for the identification of high-redshift galaxies and galaxy clusters. In past surveys, nearly 20 clusters of Abell richness class 1 or richer associated with quasars in the redshift range 0.2 less than z less than 0.8 were identified. In order to study these galaxy clusters in detail, a major redshift survey of faint galaxies in these fields using the CFHT LAMA/MARLIN multi-object spectroscopy system was carried out. An equally important product in such a survey is the redshifts of the field galaxies not associated with the quasars. Some preliminary results on field galaxies from an interim set of data from our redshift survey in quasar fields are presented.

Iris recognition using image moments and k-means algorithm.

PubMed

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%.

Iris Recognition Using Image Moments and k-Means Algorithm

PubMed Central

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%. PMID:24977221

Uncovering production of specialized metabolites by Streptomyces argillaceus: Activation of cryptic biosynthesis gene clusters using nutritional and genetic approaches.

PubMed

Becerril, Adriana; Álvarez, Susana; Braña, Alfredo F; Rico, Sergio; Díaz, Margarita; Santamaría, Ramón I; Salas, José A; Méndez, Carmen

2018-01-01

Sequencing of Streptomyces genomes has revealed they harbor a high number of biosynthesis gene cluster (BGC), which uncovered their enormous potentiality to encode specialized metabolites. However, these metabolites are not usually produced under standard laboratory conditions. In this manuscript we report the activation of BGCs for antimycins, carotenoids, germicidins and desferrioxamine compounds in Streptomyces argillaceus, and the identification of the encoded compounds. This was achieved by following different strategies, including changing the growth conditions, heterologous expression of the cluster and inactivating the adpAa or overexpressing the abrC3 global regulatory genes. In addition, three new carotenoid compounds have been identified.

Dynamic Fuzzy Model Development for a Drum-type Boiler-turbine Plant Through GK Clustering

NASA Astrophysics Data System (ADS)

Habbi, Ahcène; Zelmat, Mimoun

2008-10-01

This paper discusses a TS fuzzy model identification method for an industrial drum-type boiler plant using the GK fuzzy clustering approach. The fuzzy model is constructed from a set of input-output data that covers a wide operating range of the physical plant. The reference data is generated using a complex first-principle-based mathematical model that describes the key dynamical properties of the boiler-turbine dynamics. The proposed fuzzy model is derived by means of fuzzy clustering method with particular attention on structure flexibility and model interpretability issues. This may provide a basement of a new way to design model based control and diagnosis mechanisms for the complex nonlinear plant.

Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

DOEpatents

Moody, Daniela; Wohlberg, Brendt

2018-01-02

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.

PubMed

Rennard, Stephen I; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K; Vestbo, Jørgen; Miller, Bruce E; Bakke, Per; Celli, Bartolomé; Calverley, Peter M A; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D; Lomas, David A; MacNee, William; Wouters, Emiel F M; Yates, Julie C; Coca, Ignacio; Agustí, Alvar

2015-03-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

Spatial heterogeneity in the Mediterranean Biodiversity Hotspot affects barcoding accuracy of its freshwater fishes.

PubMed

Geiger, M F; Herder, F; Monaghan, M T; Almada, V; Barbieri, R; Bariche, M; Berrebi, P; Bohlen, J; Casal-Lopez, M; Delmastro, G B; Denys, G P J; Dettai, A; Doadrio, I; Kalogianni, E; Kärst, H; Kottelat, M; Kovačić, M; Laporte, M; Lorenzoni, M; Marčić, Z; Özuluğ, M; Perdices, A; Perea, S; Persat, H; Porcelotti, S; Puzzi, C; Robalo, J; Šanda, R; Schneider, M; Šlechtová, V; Stoumboudi, M; Walter, S; Freyhof, J

2014-11-01

Incomplete knowledge of biodiversity remains a stumbling block for conservation planning and even occurs within globally important Biodiversity Hotspots (BH). Although technical advances have boosted the power of molecular biodiversity assessments, the link between DNA sequences and species and the analytics to discriminate entities remain crucial. Here, we present an analysis of the first DNA barcode library for the freshwater fish fauna of the Mediterranean BH (526 spp.), with virtually complete species coverage (498 spp., 98% extant species). In order to build an identification system supporting conservation, we compared species determination by taxonomists to multiple clustering analyses of DNA barcodes for 3165 specimens. The congruence of barcode clusters with morphological determination was strongly dependent on the method of cluster delineation, but was highest with the general mixed Yule-coalescent (GMYC) model-based approach (83% of all species recovered as GMYC entity). Overall, genetic morphological discontinuities suggest the existence of up to 64 previously unrecognized candidate species. We found reduced identification accuracy when using the entire DNA-barcode database, compared with analyses on databases for individual river catchments. This scale effect has important implications for barcoding assessments and suggests that fairly simple identification pipelines provide sufficient resolution in local applications. We calculated Evolutionarily Distinct and Globally Endangered scores in order to identify candidate species for conservation priority and argue that the evolutionary content of barcode data can be used to detect priority species for future IUCN assessments. We show that large-scale barcoding inventories of complex biotas are feasible and contribute directly to the evaluation of conservation priorities. © 2014 John Wiley & Sons Ltd.

Photothermal confocal multicolor microscopy of nanoparticles and nanodrugs in live cells

PubMed Central

Nedosekin, Dmitry A.; Foster, Stephen; Nima, Zeid A.; Biris, Alexandru S.; Galanzha, Ekaterina I.; Zharov, Vladimir P.

2018-01-01

Growing biomedical applications of non-fluorescent nanoparticles (NPs) for molecular imaging, disease diagnosis, drug delivery, and theranostics require new tools for real-time detection of nanomaterials, drug nano-carriers and NP-drug conjugates (nanodrugs) in complex biological environments without additional labeling. Photothermal (PT) microscopy (PTM) has an enormous potential for absorption-based identification and quantification of non-fluorescent molecules and NPs at a single molecule and 1.4 nm gold NP level. Recently, we have developed confocal PTM providing three-dimensional (3-D) mapping and spectral identification of multiple chromophores and fluorophores in live cells. Here, we summarize recent advances in the application of confocal multicolor PTM for 3-D visualization of single and clustered NPs, alone and in individual cells. In particular, we demonstrate identification of functionalized magnetic and gold-silver NPs, as well as graphene and carbon nanotubes in cancer cells and among blood cells. The potentials to use PTM for super-resolution imaging (down to 50nm), real-time NP tracking, guidance of PT nanotherapy and multiplex cancer markers targeting, as well as analysis of nonlinear PT phenomena and amplification of nanodrug efficacy through NP clustering and nanobubble formation are also discussed. PMID:26133539

Comparative Chemometric Analysis for Classification of Acids and Bases via a Colorimetric Sensor Array.

PubMed

Kangas, Michael J; Burks, Raychelle M; Atwater, Jordyn; Lukowicz, Rachel M; Garver, Billy; Holmes, Andrea E

2018-02-01

With the increasing availability of digital imaging devices, colorimetric sensor arrays are rapidly becoming a simple, yet effective tool for the identification and quantification of various analytes. Colorimetric arrays utilize colorimetric data from many colorimetric sensors, with the multidimensional nature of the resulting data necessitating the use of chemometric analysis. Herein, an 8 sensor colorimetric array was used to analyze select acid and basic samples (0.5 - 10 M) to determine which chemometric methods are best suited for classification quantification of analytes within clusters. PCA, HCA, and LDA were used to visualize the data set. All three methods showed well-separated clusters for each of the acid or base analytes and moderate separation between analyte concentrations, indicating that the sensor array can be used to identify and quantify samples. Furthermore, PCA could be used to determine which sensors showed the most effective analyte identification. LDA, KNN, and HQI were used for identification of analyte and concentration. HQI and KNN could be used to correctly identify the analytes in all cases, while LDA correctly identified 95 of 96 analytes correctly. Additional studies demonstrated that controlling for solvent and image effects was unnecessary for all chemometric methods utilized in this study.

DMINDA: an integrated web server for DNA motif identification and analyses.

PubMed

Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

2014-07-01

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Highly efficient classification and identification of human pathogenic bacteria by MALDI-TOF MS.

PubMed

Hsieh, Sen-Yung; Tseng, Chiao-Li; Lee, Yun-Shien; Kuo, An-Jing; Sun, Chien-Feng; Lin, Yen-Hsiu; Chen, Jen-Kun

2008-02-01

Accurate and rapid identification of pathogenic microorganisms is of critical importance in disease treatment and public health. Conventional work flows are time-consuming, and procedures are multifaceted. MS can be an alternative but is limited by low efficiency for amino acid sequencing as well as low reproducibility for spectrum fingerprinting. We systematically analyzed the feasibility of applying MS for rapid and accurate bacterial identification. Directly applying bacterial colonies without further protein extraction to MALDI-TOF MS analysis revealed rich peak contents and high reproducibility. The MS spectra derived from 57 isolates comprising six human pathogenic bacterial species were analyzed using both unsupervised hierarchical clustering and supervised model construction via the Genetic Algorithm. Hierarchical clustering analysis categorized the spectra into six groups precisely corresponding to the six bacterial species. Precise classification was also maintained in an independently prepared set of bacteria even when the numbers of m/z values were reduced to six. In parallel, classification models were constructed via Genetic Algorithm analysis. A model containing 18 m/z values accurately classified independently prepared bacteria and identified those species originally not used for model construction. Moreover bacteria fewer than 10(4) cells and different species in bacterial mixtures were identified using the classification model approach. In conclusion, the application of MALDI-TOF MS in combination with a suitable model construction provides a highly accurate method for bacterial classification and identification. The approach can identify bacteria with low abundance even in mixed flora, suggesting that a rapid and accurate bacterial identification using MS techniques even before culture can be attained in the near future.

Genetic diversity of Mycobacterium tuberculosis from Guadalajara, Mexico and identification of a rare multidrug resistant Beijing genotype.

PubMed

Flores-Treviño, Samantha; Morfín-Otero, Rayo; Rodríguez-Noriega, Eduardo; González-Díaz, Esteban; Pérez-Gómez, Héctor R; Bocanegra-García, Virgilio; Vera-Cabrera, Lucio; Garza-González, Elvira

2015-01-01

Determining the genetic diversity of M. tuberculosis strains allows identification of the distinct Mycobacterium tuberculosis genotypes responsible for tuberculosis in different regions. Several studies have reported the genetic diversity of M. tuberculosis strains in Mexico, but little information is available from the state of Jalisco. Therefore, the aim of this study was to determine the genetic diversity of Mycobacterium tuberculosis clinical isolates from Western Mexico. Sixty-eight M. tuberculosis isolates were tested for susceptibility to first-line drugs using manual Mycobacteria Growth Indicator Tube method and genotyped using spoligotyping and IS6110-restriction fragment length polymorphism (RFLP) pattern analyses. Forty-seven (69.1%) isolates were grouped into 10 clusters and 21 isolates displayed single patterns by spoligotyping. Three of the 21 single patterns corresponded to orphan patterns in the SITVITWEB database, and 1 new type that contained 2 isolates was created. The most prevalent lineages were T (38.2%), Haarlem (17.7%), LAM (17.7%), X (7.4%), S (5.9%), EAI (1.5%) and Beijing (1.5%). Six (12.8%) of the clustered isolates were MDR, and type 406 of the Beijing family was among the MDR isolates. Seventeen (26.2%) isolates were grouped into 8 clusters and 48 isolates displayed single patterns by IS6110-RFLP. Combination of IS6110-RFLP and spoligotyping reduced the clustering rate to 20.0%. The results show that T, Haarlem, and LAM are predominant lineages among clinical isolates of M. tuberculosis in Guadalajara, Mexico. Clustering rates indicated low transmission of MDR strains. We detected a rare Beijing genotype, SIT406, which was a highly resistant strain. This is the first report of this Beijing genotype in Latin America.

Genetic Diversity of Mycobacterium tuberculosis from Guadalajara, Mexico and Identification of a Rare Multidrug Resistant Beijing Genotype

PubMed Central

Flores-Treviño, Samantha; Morfín-Otero, Rayo; Rodríguez-Noriega, Eduardo; González-Díaz, Esteban; Pérez-Gómez, Héctor R.; Bocanegra-García, Virgilio; Vera-Cabrera, Lucio; Garza-González, Elvira

2015-01-01

Determining the genetic diversity of M. tuberculosis strains allows identification of the distinct Mycobacterium tuberculosis genotypes responsible for tuberculosis in different regions. Several studies have reported the genetic diversity of M. tuberculosis strains in Mexico, but little information is available from the state of Jalisco. Therefore, the aim of this study was to determine the genetic diversity of Mycobacterium tuberculosis clinical isolates from Western Mexico. Sixty-eight M. tuberculosis isolates were tested for susceptibility to first-line drugs using manual Mycobacteria Growth Indicator Tube method and genotyped using spoligotyping and IS6110-restriction fragment length polymorphism (RFLP) pattern analyses. Forty-seven (69.1%) isolates were grouped into 10 clusters and 21 isolates displayed single patterns by spoligotyping. Three of the 21 single patterns corresponded to orphan patterns in the SITVITWEB database, and 1 new type that contained 2 isolates was created. The most prevalent lineages were T (38.2%), Haarlem (17.7%), LAM (17.7%), X (7.4%), S (5.9%), EAI (1.5%) and Beijing (1.5%). Six (12.8%) of the clustered isolates were MDR, and type 406 of the Beijing family was among the MDR isolates. Seventeen (26.2%) isolates were grouped into 8 clusters and 48 isolates displayed single patterns by IS6110-RFLP. Combination of IS6110-RFLP and spoligotyping reduced the clustering rate to 20.0%. The results show that T, Haarlem, and LAM are predominant lineages among clinical isolates of M. tuberculosis in Guadalajara, Mexico. Clustering rates indicated low transmission of MDR strains. We detected a rare Beijing genotype, SIT406, which was a highly resistant strain. This is the first report of this Beijing genotype in Latin America. PMID:25695431

Event Networks and the Identification of Crime Pattern Motifs

PubMed Central

2015-01-01

In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

Identification of multiply charged proteins and amino acid clusters by liquid nitrogen assisted spray ionization mass spectrometry.

PubMed

Kumar Kailasa, Suresh; Hasan, Nazim; Wu, Hui-Fen

2012-08-15

The development of liquid nitrogen assisted spray ionization mass spectrometry (LNASI MS) for the analysis of multiply charged proteins (insulin, ubiquitin, cytochrome c, α-lactalbumin, myoglobin and BSA), peptides (glutathione, HW6, angiotensin-II and valinomycin) and amino acid (arginine) clusters is described. The charged droplets are formed by liquid nitrogen assisted sample spray through a stainless steel nebulizer and transported into mass analyzer for the identification of multiply charged protein ions. The effects of acids and modifier volumes for the efficient ionization of the above analytes in LNASI MS were carefully investigated. Multiply charged proteins and amino acid clusters were effectively identified by LNASI MS. The present approach can effectively detect the multiply charged states of cytochrome c at 400 nM. A comparison between LNASI and ESI, CSI, SSI and V-EASI methods on instrumental conditions, applied temperature and observed charge states for the multiply charged proteins, shows that the LNASI method produces the good quality spectra of amino acid clusters at ambient conditions without applied any electric field and heat. To date, we believe that the LNASI method is the most simple, low cost and provided an alternative paradigm for production of multiply charged ions by LNASI MS, just as ESI-like ions yet no need for applying any electrical field and it could be operated at low temperature for generation of highly charged protein/peptide ions. Copyright © 2012 Elsevier B.V. All rights reserved.

VizieR Online Data Catalog: M33 molecular clouds and young stellar clusters (Corbelli+, 2017)

NASA Astrophysics Data System (ADS)

Corbelli, E.; Braine, J.; Bandiera, R.; Brouillet, N.; Combes, F.; Druard, C.; Gratier, P.; Mata, J.; Schuster, K.; Xilouris, M.; Palla, F.

2017-04-01

Table 5 : Physical parameters for the 566 molecular clouds identified through the IRAM 30m CO J=2-1 survey of the star forming disk of M33. For each cloud the cloud type and the following properties are listed: celestial coordinates, galactocentric radius, cloud deconvolved effective radius and its uncertainty, CO(2-1) line velocity dispersion from CPROPS and its uncertainty, line velocity dispersion from a Gaussian fit, CO luminous mass and its uncertainty, and virial mass from a Gaussian fit. In the last column the identification number of the young stellar cluster candidates associated with the molecular cloud are listed. Notes: We identify up to four young stellar cluster candidates (YSCCs) associated with each molecular cloud and we list them according to the identification number of Sharma et al. (2011, Cat. J/A+A/545/A96) given also in Table 6. Table 6 : Physical parameters for the 630 young stellar cluster candidates identified via their mid-infrared emission in the star forming disk of M33. For each YSCC we list the type of source, the identified number of the molecular clouds associated with it (if any) and the corresponding cloud classes. In addition, for each YSCC we give the celestial coordinates, the bolometric, total infrared, FUV and Halpha luminosities, the estimated mass and age, the visual extinction, the galactocentric radius, the source size, and its flux at 24μm. (2 data files).

Submegabase Clusters of Unstable Tandem Repeats Unique to the Tla Region of Mouse T Haplotypes

PubMed Central

Uehara, H.; Ebersole, T.; Bennett, D.; Artzt, K.

1990-01-01

We describe here the identification and genomic organization of mouse t haplotype-specific elements (TSEs) 7.8 and 5.8 kb in length. The TSEs exist as submegabase-long clusters of tandem repeats localized in the Tla region of the major histocompatibility complex of all t haplotype chromosomes examined. In contrast, no such clusters were detected among 12 inbred strains of Mus musculus and other Mus species; thus, clusters of TSEs represent the first absolutely qualitative difference between t haplotypes and wild-type chromosomes. Pulsed field gel electrophoresis shows that the number of clusters, and the number of repeats in each cluster are extremely variable. Dramatic quantitative differences of TSEs uniquely distinguish every independent t haplotype from any other. The complete nucleotide sequence of one 7.8-kb TSE reveals significant homology to the ETn (a major transcript in the early embryo of the mouse), and some homologies to intracisternal A-particles and the mammary tumor virus env gene. Apart from the diagnostic relevance to t haplotypes, evolutionary and functional significances are discussed with respect to chromosome structure and genetic recombination. PMID:2076812

Structure and formation of highly luminescent protein-stabilized gold clusters† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc05086k

PubMed Central

Chevrier, D. M.; Thanthirige, V. D.; Luo, Z.; Driscoll, S.; Cho, P.; MacDonald, M. A.; Yao, Q.; Guda, R.; Xie, J.; Johnson, E. R.; Chatt, A.; Zheng, N.

2018-01-01

Highly luminescent gold clusters simultaneously synthesized and stabilized by protein molecules represent a remarkable category of nanoscale materials with promising applications in bionanotechnology as sensors. Nevertheless, the atomic structure and luminescence mechanism of these gold clusters are still unknown after several years of developments. Herein, we report findings on the structure, luminescence and biomolecular self-assembly of gold clusters stabilized by the large globular protein, bovine serum albumin. We highlight the surprising identification of interlocked gold-thiolate rings as the main gold structural unit. Importantly, such gold clusters are in a rigidified state within the protein scaffold, offering an explanation for their highly luminescent character. Combined free-standing cluster synthesis (without protecting protein scaffold) with rigidifying and un-rigidifying experiments, were designed to further verify the luminescence mechanism and gold atomic structure within the protein. Finally, the biomolecular self-assembly process of the protein-stabilized gold clusters was elucidated by time-dependent X-ray absorption spectroscopy measurements and density functional theory calculations. PMID:29732064

Dietary patterns and sarcopenia in an urban African American and White population in the United States.

PubMed

Fanelli Kuczmarski, Marie; Mason, Marc A; Beydoun, May A; Allegro, Deanne; Zonderman, Alan B; Evans, Michele K

2013-01-01

The primary objective of this cross-sectional study was to characterize dietary patterns of African Americans and Whites, 30 to 64 years, examined in the Healthy Aging in Neighborhoods of Diversity across the Life Span study. Other objectives of the study were to evaluate micronutrient adequacy of each pattern and to determine the association of diet with sarcopenia. Cluster analysis was used to determine patterns and mean adequacy ratio (MAR) to determine adequacy of 15 micronutrients. Ten clusters were identified: sandwich, sweet drink, pizza, poultry, frozen meal, dessert, alcoholic drink, bread, starchy vegetables, and pasta/rice dish. MAR ranged from 69 for the sweet drink cluster to 82 for the pasta/rice dish cluster. Sarcopenia was present in 6.4% of the sample, ranging from 1.5% in the poultry cluster to 14.1% in the alcoholic drink cluster. This study is the first to report an association between diet and sarcopenia in people younger than 65 years. The identification of presarcopenia has important implications for dietary interventions that might delay age-associated loss of lean mass.

Evidence for an extensive intracluster medium from radio observations of distant Abell clusters

NASA Technical Reports Server (NTRS)

Hanisch, R. J.; Ulmer, M. P.

1985-01-01

Observations have been made of 18 distance class 5 and 6 Abell clusters of galaxies using the VLA in its 'C' configuration at a frequency of 1460 MHz. Half of the clusters in the sample are confirmed or probable sources of X-ray emission. All the detected radio sources with flux densities above 10 mJy are reported, and information is provided concerning the angular extent of the sources, as well as the most likely optical identification. The existence of an extensive intracluster medium is inferred by identifying extended/distorted radio sources with galaxies whose apparent magnitudes are consistent with their being cluster members and that are at projected distances of 3-4 Abell radii (6-8 Mpc) from the nearest cluster center. By requiring that the radio sources are confined by the ambient medium, the ambient density is calculated and the total cluster mass is estimated. As a sample calculation, a wide-angle-tail radio source some 5 Mpc from the center of Abell 348 is used to estimate these quantities.

Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species

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

Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna

Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated themore » identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.« less

A [4Fe-4S]-Fe(CO)(CN)-l-cysteine intermediate is the first organometallic precursor in [FeFe] hydrogenase H-cluster bioassembly

NASA Astrophysics Data System (ADS)

Rao, Guodong; Tao, Lizhi; Suess, Daniel L. M.; Britt, R. David

2018-05-01

Biosynthesis of the [FeFe] hydrogenase active site (the 'H-cluster') requires the interplay of multiple proteins and small molecules. Among them, the radical S-adenosylmethionine enzyme HydG, a tyrosine lyase, has been proposed to generate a complex that contains an Fe(CO)2(CN) moiety that is eventually incorporated into the H-cluster. Here we describe the characterization of an intermediate in the HydG reaction: a [4Fe-4S][(Cys)Fe(CO)(CN)] species, 'Complex A', in which a CO, a CN- and a cysteine (Cys) molecule bind to the unique 'dangler' Fe site of the auxiliary [5Fe-4S] cluster of HydG. The identification of this intermediate—the first organometallic precursor to the H-cluster—validates the previously hypothesized HydG reaction cycle and provides a basis for elucidating the biosynthetic origin of other moieties of the H-cluster.

Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species

DOE PAGES

Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna; ...

2015-04-09

Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated themore » identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.« less

Automatic script identification from images using cluster-based templates

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

Hochberg, J.; Kerns, L.; Kelly, P.

We have developed a technique for automatically identifying the script used to generate a document that is stored electronically in bit image form. Our approach differs from previous work in that the distinctions among scripts are discovered by an automatic learning procedure, without any handson analysis. We first develop a set of representative symbols (templates) for each script in our database (Cyrillic, Roman, etc.). We do this by identifying all textual symbols in a set of training documents, scaling each symbol to a fixed size, clustering similar symbols, pruning minor clusters, and finding each cluster`s centroid. To identify a newmore » document`s script, we identify and scale a subset of symbols from the document and compare them to the templates for each script. We choose the script whose templates provide the best match. Our current system distinguishes among the Armenian, Burmese, Chinese, Cyrillic, Ethiopic, Greek, Hebrew, Japanese, Korean, Roman, and Thai scripts with over 90% accuracy.« less

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets

PubMed Central

Griss, Johannes; Perez-Riverol, Yasset; Lewis, Steve; Tabb, David L.; Dianes, José A.; del-Toro, Noemi; Rurik, Marc; Walzer, Mathias W.; Kohlbacher, Oliver; Hermjakob, Henning; Wang, Rui; Vizcaíno, Juan Antonio

2016-01-01

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra. PMID:27493588