Clinical Value of a Computer-Aided Diagnosis System in Thyroid Nodules: Analysis of a Reading Map Competition.

We evaluated the accuracy of human and computer-aided diagnosis (CAD) in a reading map diagnosis competition for detection of thyroid cancers via ultrasonography (US). The competition comprised 33 thyroid nodule images randomly chosen between 2015 and 2017. One hundred seventy-seven contestants including one operator using CAD participated in the competition. The competition was separated into an online part and a live part. We compared the average accuracy of contestants and CAD in the detection of thyroid cancers. The accuracy of contestants and the CAD system was 60.3% and 84.8%, respectively. The accuracy of the CAD system was higher than that of the contestants with different technical titles. The areas under the curve for CAD and contestants were 0.985 (0.881-1.00) and 0.659 (0.645-0.673) (Z = 7.55, p < 0.01). The CAD system had high accuracy in this thyroid nodule reading map competition, and may be an adjuvant tool for radiologists.