Background
To explore the potential value of S-Detect™, a high-end computer-assisted diagnosis (CAD) software system for residents-in-training.
Methods
Routine breast ultrasound (US) examinations were conducted and assessed by an experienced radiologist. Archived images of the lesions (including grayscale, color Doppler flow and elastography images) were retrospectively assessed by each of five in-training residents who were blinded to the histopathological findings and any other US diagnosis. The diagnostic performances of S-Detect™ and the five residents were measured and compared. Afterwards, category 4a lesions assessed by the residents were downgraded when classified as possibly benign by S-Detect™. The diagnostic performance of the integrated results was compared with the original results of the residents.
Results
A total of 195 focal breast lesions were consecutively enrolled, including 82 malignant lesions and 113 benign lesions. S-Detect™ presented higher specificity and area under the curve (AUC)than the residents. After combination with S-Detect™ in category 4a lesions, the specificity and AUC of the five residents were significantly improved. The intraclass correlation coefficient (ICC) of the five residents also increased after integration.
Conclusions
With the help of the CAD software, the specificity, overall diagnostic performances and interobserver agreements of the residents greatly improved. S-Detect™ can be utilized as an assistant tool for residents-in-training in classifying breast lesions.