A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of breast masses on ultrasound: Added value for the inexperienced breast radiologist

Abstract

To evaluate the value of the computer-aided diagnosis (CAD) program applied to diagnostic breast ultrasonography (US) based on operator experience.US images of 100 breast masses from 91 women over 2 months (from May to June 2015) were collected and retrospectively analyzed. Three less experienced and 2 experienced breast imaging radiologists analyzed the US features of the breast masses without and with CAD according to the Breast Imaging Reporting and Data System (BI-RADS) lexicon and categories. We then compared the diagnostic performance between the experienced and less experienced radiologists and analyzed the interobserver agreement among the radiologists.Of the 100 breast masses, 41 (41%) were malignant and 59 (59%) were benign. Compared with the experienced radiologists, the less experienced radiologists had significantly improved negative predictive value (86.7%-94.7% vs 53.3%-76.2%, respectively) and area under receiver operating characteristics curve (0.823-0.839 vs 0.623-0.759, respectively) with CAD assistance (all P < .05). In contrast, experienced radiologists had significantly improved specificity (52.5% and 54.2% vs 66.1% and 66.1%) and positive predictive value (55.6% and 58.5% vs 64.9% and 64.9%, respectively) with CAD assistance (all P < .05). Interobserver variability of US features and final assessment by categories were significantly improved and moderate agreement was seen in the final assessment after CAD combination regardless of the radiologist's experience.CAD is a useful additional diagnostic tool for breast US in all radiologists, with benefits differing depending on the radiologist's level of experience. In this study, CAD improved the interobserver agreement and showed acceptable agreement in the characterization of breast masses.

Figure 1

A. The grayscale ultrasound image in a 57-year-old woman with incidentally detected breast mass on screening examination shows an indistinct irregular heterogeneous hypoechoic mass (arrows) at the 9 o’clock position in the left breast that was diagnosed as breast imaging reporting and data system (BI-RADS) category 3, 4a, and 3, respectively, by less experienced radiologists and 4a and 4b, respectively, by experienced radiologists. B. After review of the CAD application, (where the conclusion was “possibly malignant”), each reviewer recategorized the mass as 4a, 4a, 4b, 4b, and 4c, respectively; core biopsy confirmed the lesion as ductal carcinoma in situ. CAD = computer-aided diagnosis.

Figure 2

A. The grayscale ultrasound image in a 35-year-old woman with a palpable lesion in her right breast, shows an indistinct oval hypoechoic mass (arrow) at the 9 o’clock position in the left breast that was diagnosed as breast imaging reporting and data system (BI-RADS) category 4a, 4a, and 4a, respectively, by 3 fellowship-trained radiologists, and as category 4a and 3, respectively, by experienced radiologists. B. After review of the CAD application, (where the conclusion was “possibly benign”), each reviewer recategorized the mass as 4a, 3, 3, 3, and 3, respectively; core biopsy finally confirmed the mass as fibroadenoma. CAD = computer-aided diagnosis.