Shalom Buchbinder

Pseudoangiomatous stromal hyperplasia of the breast: sonographic features with histopathologic correlation.

Abstract:  The objective of this study was to evaluate the spectrum of sonographic findings in pseudoangiomatous stromal hyperplasia (PASH) of the breast when it presents as a tumoral mass with pathologic correlation. Breast sonogram studies of 13 patients with 13 pathologically proven PASH lesions were retrospectively reviewed. The morphologic characteristics of the lesions as seen on ultrasound were evaluated and correlated with histopathologic findings. Sonography demonstrated most lesions, 11 of 13, to be hypoechoic in echotexture. One lesion was isoechoic in echotexture, also demonstrating small internal cysts, and one was predominantly hyperechoic. Two of the 11 hypoechoic lesions also demonstrated a complex heterogeneous pattern with a central hypoechoic area and a peripheral echogenic rim. All lesions were oval in shape with the long axis of the lesion parallel to the chest wall. None of the lesions demonstrated posterior acoustic shadowing. PASH lesions of the breast have a varied sonographic appearance. Knowledge of the spectrum of morphologic features shown on sonography can be helpful in the diagnosis of this entity. 

Improved mammographic interpretation of masses using computer-aided diagnosis

Abstract. The aim of this study was to evaluate the effectiveness of computerized image enhancement, to investigate criteria for discriminating benign from malignant mammographic findings by computer-aided diagnosis (CAD), and to test the role of quantitative analysis in improving the accuracy of interpretation of mass lesions. Forty sequential mammographically detected mass lesions referred for biopsy were digitized at high resolution for computerized evaluation. A prototype CAD system which included image enhancement algorithms was used for a better visualization of the lesions. Quantitative features which characterize the spiculation were automatically extracted by the CAD system for a user-defined region of interest (ROI). Reference ranges for malignant and benign cases were acquired from data generated by 214 known retrospective cases. The extracted parameters together with the reference ranges were presented to the radiologist for the analysis of 40 prospective cases. A pattern recognition scheme based on discriminant analysis was trained on the 214 retrospective cases, and applied to the prospective cases. Accuracy of interpretation with and without the CAD system, as well as the performance of the pattern recognition scheme, were analyzed using receiver operating characteristics (ROC) curves. A significant difference (p < 0.005) was found between features extracted by the CAD system for benign and malignant cases. Specificity of the CAD-assisted diagnosis improved significantly (p < 0.02) from 14 % for the conventional assessment to 50 %, and the positive predictive value increased from 0.47 to 0.62 (p < 0.04). The area under the ROC curve (Az) increased significantly (p < 0.001) from 0.66 for the conventional assessment to 0.81 for the CAD-assisted analysis. The Az for the results of the pattern recognition scheme was higher (0.95). The results indicate that there is an improved accuracy of diagnosis with the use of the mammographic CAD system above that of the unassisted radiologist. Our findings suggest that objective quantitative features extracted from digitized mammographic findings may help in differentiating between benign and malignant masses, and can assist the radiologist in the interpretation of mass lesions.

Can the size of microcalcifications predict malignancy of clusters at mammography

RATIONALE AND OBJECTIVES The purpose of this study was to determine whether the size of mammographically detected microcalcifications is predictive of malignancy. MATERIALS AND METHODS Two hundred sixty mammograms showing clustered microcalcifications with proven diagnoses (160 malignant, 100 benign) were respectively reviewed by experienced mammographers. Lesions that were obviously benign in appearance were excluded from the study. A computer-aided diagnosis system digitized the lesions at 600 dpi, and the microcalcifications on the digital image were interactively defined by mammographers. Subsequently, three quantitative features that reflected the size of the microcalcifications-length, area, and brightness-were automatically extracted by the system. For each feature, the standard average of values obtained for individual calcifications within the cluster and the average with emphasis on extreme values (E) obtained in a single cluster were analyzed and matched with pathologic results. RESULTS In the malignant group of cases, the mean values of the standard average length and area were significantly higher (P < .0001) than the mean values in the benign group. Distribution analysis demonstrated that an average length of more than 0.41 mm was associated with malignant lesions 77% of the time, while an average length of less than 0.41 mm was associated with benign lesions 71% of the time. The mean of the average length (E) and area (E) of microcalcifications within the cluster demonstrated an even higher discriminative power when compared with the standard average length and area. The average brightness, on the other hand, showed only a low discriminative power. CONCLUSION Digital computerized analysis of mammographically detected calcifications demonstrated that the average length and area of the calcifications in benign clusters were significantly smaller than those in malignant clusters.

Optimizing parameters for computer-aided diagnosis of microcalcifications at mammography.

RATIONALE AND OBJECTIVES The purpose of this study was to optimize selection of the mammographic features most useful in discriminating benign from malignant clustered microcalcifications. MATERIALS AND METHODS The computer-aided diagnosis (CAD) system automatically extracted from digitized mammograms 13 quantitative features characterizing microcalcification clusters. Archival cases (n = 134; patient age range, 31-77 years; mean age, 56.8 years) with known histopathologic results (79 malignant, 55 benign) were selected. Three radiologists at three facilities independently analyzed the microcalcifications by using the CAD system. Stepwise discriminant analysis selected the features best discriminating benign from malignant microcalcifications. A classification scheme was constructed on the basis of these optimized features, and its performance was evaluated by using receiver operating characteristic (ROC) analysis. RESULTS Six of the 13 variables extracted by the CAD system were selected by stepwise determinant analysis for generating the classification scheme, which yielded an ROC curve with an area (Az) of 0.98, specificity of 83.64%, positive predictive value of 89.53%, and accuracy of 91.79% for 98% sensitivity. When patient age was an additional variable, the schemes performance improved, but this was not statistically significant (Az = 0.98). The ROC curve of the classifier (without age as an additional variable) yielded a high Az of 0.96 for patients younger than 50 years and an even higher (P < .02) Az of 0.99 for those 50 years or older. CONCLUSION Stepwise discriminant analysis optimized performance of a classification scheme for microcalcifications by selecting six optimized features. Scheme performance was significantly (P < .02) higher for women 50 years or older, but the addition of patient age as a variable did not produce a statistically significant increase in performance.

Ruptured hepatic artery aneurysms in a patient with systemic lupus erythematosus: Case report

Spontaneous hemorrhage caused by ruptured left hepatic artery branch aneurysms occurred in a 49-year-old man with systemic lupus erythematosus Following evaluation by computerized tomography and angiography, transcatheter embolization of the left hepatic artery resulted in hemostasis. The various etiologies of hepatic artery aneurysms are discussed. This case demonstrates that systemic lupus erythematosus must be considered in the differential diagnosis of hepatic artery aneurysms and spontaneous hepatic hemorrhage.

Analysis of clustered microcalcifications by using a single numeric classifier extracted from mammographic digital images

RATIONALE AND OBJECTIVES The authors prospectively tested the performance of a single numeric classifier constructed from a discriminative analysis classification system based on automatic computer-extracted quantitative features of clustered microcalcifications. MATERIALS AND METHODS Mammographically detected clustered microcalcifications in patients who had been referred for biopsy were digitized at 600 dpi with an 8-bit gray scale. A software program was developed to extract features automatically from digitized images to describe the clustered microcalcifications quantitatively. The significance of these features was evaluated by using the Wilcoxon test, the Welch modified two-sample t test, and the two-sample Kolmogorov-Smirnov test. A discriminant analysis pattern recognition system was constructed to generate a single numeric classifier for each case, based on the extracted features. This system was trained on 137 archival known reference cases and its performance tested on 24 unknown prospective cases. The results were evaluated by using receiver operating characteristic analysis. RESULTS Thirty-seven extracted parameters demonstrated a statistically significant difference between the values for the benign and for the malignant lesions. Seven independent factors were selected to construct the classifier and to evaluate the unknown prospective cases. The area under the receiver operating characteristic curve for the prospective cases was 0.88. CONCLUSION A pattern recognition classifier based on quantitative features for clustered microcalcifications at screen-film mammography was found to perform satisfactorily. The software may be of value in the interpretation of mammographically detected microcalcifications.

The use of an interactive software program for quantitative characterization of microcalcifications on digitized film-screen mammograms.

RATIONALE AND OBJECTIVES Mammography is relatively nonspecific for the early detection of breast cancer. This study evaluates the accuracy of mammographic interpretation using quantitative features characterizing microcalcifications, which are extracted by a computerized system. METHODS A computer-aided diagnosis (CAD) system enabling digitization of film-screen mammograms and automatic feature extraction was developed. A classification scheme (discriminant analysis) based on these features was constructed and trained on 217 cases with known pathology. The diagnostic performance of the classification scheme was tested against the radiologists conventional interpretation on 45 additional cases of microcalcifications, each analyzed independently by four radiologists. RESULTS The sensitivity of the CAD system analysis (95.7%) was significantly better than that of conventional interpretation (84.8%). The positive predictive value of interpretation increased significantly, as did the area under the receiver operating characteristic curve. CONCLUSIONS This classification scheme for microcalcifications, based on quantitative features characterizing the lesion, significantly improved the accuracy of mammographic interpretation.

Role of US-Guided Fine-Needle Aspiration with On-Site Cytopathologic Evaluation in Management of Nonpalpable Breast Lesions

RATIONALE AND OBJECTIVES The purpose of this study was to evaluate the accuracy of ultrasound (US)-guided fine-needle aspiration (FNA), with radiographic follow-up or surgical excision, in conjunction with on-site cytopathologic support in the management of nonpalpable breast lesions. MATERIALS AND METHODS The findings of 266 consecutive mammographically or sonographically identified, nonpalpable lesions (228 patients) that underwent US-guided FNA were examined retrospectively. Clustered microcalcifications did not undergo biopsy with this method. Patients who underwent follow-up excisional biopsy or mammography with a duration of at least 24 months were included in the study. RESULTS In all, 117 lesions met criteria for inclusion, of which 85 (73%) were diagnosed as benign at cytopathologic evaluation and underwent mammographic follow-up of at least 24 months (range, 24-67 months; mean, 36 months). Thirty-two lesions (27%) had either malignant or atypical cytopathologic findings, for which surgery was recommended. Eleven (9%) of the 32 had malignant cytopathologic findings from initial US-guided FNA, which were confirmed at surgical excision. The remaining 21 lesions (18%) were diagnosed as atypical on the basis of US-guided FNA results. Of these, 18 lesions underwent excisional biopsy: Two were diagnosed as carcinoma (not otherwise specified), and 16 were diagnosed with a variety of benign disorders. The remaining three patients with atypical lesions chose mammographic follow-up rather than surgical diagnosis, and their conditions have remained stable for more than 24 months. Of the 85 benign cases, one changed during follow-up (12 months) and underwent repeat biopsy, with malignancy noted. The sensitivity of US-guided FNA in identifying malignant lesions was 93% (13 of 14), and the specificity of a benign finding was 100% (102 of 102). The positive and negative predictive values of US-guided FNA supported by on-site cytopathologic evaluation were 100% (13 of 13) and 99% (102 of 103), respectively. CONCLUSION Supported by appropriately trained on-site cytopathologists and in conjunction with follow-up mammography, US-guided FNA appears to be efficacious in the management of patients with abnormal radiographic findings. It is quick, relatively inexpensive, and minimally invasive, and, in the presence of competent cytopathologists, should be the modality of choice.

Interactive Quantitative Characterization of Micro-Calcifications on Digitized Film-Screen Mammograms

Early detection of breast cancer through the use of mammography has been shown to be effective in reducing mortality from the disease [1],[2]. The presence of clustered micro-calcifications on a mammogram is a sensitive but non-specific indicator of malignancy. In order to find the relatively small number of malignancies present among clustered micro-calcifications, many women are referred for biopsies. The increased number of biopsies increases the overall cost of screening for breast cancer, and raises a barrier to its implementation [3]. In addition, the morbidity, both psychological and physical, is not inconsequential.