title: Quantitative ultrasound analysis for classification of BI-RADS category 3 breast masses.
abstract: The accuracy of an ultrasound (US) computer-aided diagnosis (CAD) system was evaluated for the classification of BI-RADS category 3, probably benign masses. The US database used in this study contained 69 breast masses (21 malignant and 48 benign masses) that at blinded retrospective interpretation were assigned to BI-RADS category 3 by at least one of five radiologists. For computer-aided analysis, multiple morphology (shape, orientation, margin, lesions boundary, and posterior acoustic features) and texture (echo patterns) features based on BI-RADS lexicon were implemented, and the binary logistic regression model was used for classification. The receiver operating characteristic curve analysis was used for statistical analysis. The area under the curve (Az) of morphology, texture, and combined features were 0.90, 0.75, and 0.95, respectively. The combined features achieved the best performance and were significantly better than using texture features only (0.95 vs. 0.75, p value = 0.0163). The cut-off point at the sensitivity of 86 % (18/21), 95 % (20/21), and 100 % (21/21) achieved the specificity of 90 % (43/48), 73 % (35/48), and 33 % (16/48), respectively. In conclusion, the proposed CAD system has the potential to be used in upgrading malignant masses misclassified as BI-RADS category 3 on US by the radiologists.
authors.affiliation: Department of Radiology, Seoul National University Hospital, Seoul, South Korea.
authors.forename: Woo Kyung
authors.initials: WK
authors.lastname: Moon
authors.forename: Chung-Ming
authors.initials: CM
authors.lastname: Lo
authors.forename: Jung Min
authors.initials: JM
authors.lastname: Chang
authors.forename: Chiun-Sheng
authors.initials: CS
authors.lastname: Huang
authors.forename: Jeon-Hor
authors.initials: JH
authors.lastname: Chen
authors.forename: Ruey-Feng
authors.initials: RF
authors.lastname: Chang
mesh_terms: D000328:Adult; D000368:Aged; D001940:Breast / Q000473:pathology; D001941:Breast Diseases / Q000145:classification / Q000000981:diagnostic imaging / Q000473:pathology; D001943:Breast Neoplasms / Q000145:classification* / Q000000981:diagnostic imaging* / Q000473:pathology; D015331:Cohort Studies; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003937:Diagnosis, Differential; D005069:Evaluation Studies as Topic; D005260:Female; D006801:Humans; D008875:Middle Aged; D015999:Multivariate Analysis; D009361:Neoplasm Invasiveness / Q000473:pathology; D009367:Neoplasm Staging; D011230:Precancerous Conditions / Q000145:classification / Q000000981:diagnostic imaging* / Q000473:pathology; D012372:ROC Curve; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D013624:Taiwan; D016217:Ultrasonography, Mammary / Q000379:methods*