Computer-Aided Detection in Screening CT for Pulmonary Nodules

Abstract

OBJECTIVE. Our objective was to evaluate the performance of a computer-aided detection (CAD) system for pulmonary nodule detection using low-dose screening CT images. MATERIALS AND METHODS. One hundred fifty consecutive low-dose screening CT examinations were independently evaluated by a radiologist and a CAD pulmonary nodule detection system (R2 Technology) designed to identify nodules larger than 4 mm in maximum long-axis diameter. All discrepancies between the two techniques were reviewed by one of another two radiologists working in consensus with the initial interpreting radiologist, and a “true” nodule count was determined. Detected nodules were classified by size, density, and location. The performance of the initial radiologist and the CAD system were compared. RESULTS. The radiologist detected 518 nodules and the CAD system, 934 nodules. Of the 1,106 separate nodules detected using the two techniques, 628 were classified as true nodules on consensus review. Of the true nodules present, the radiologist detected 518 (82%) of 628 nodules and the CAD, 456 (73%) of 628 nodules. All 518 radiologist-detected nodules were true nodules, and 456 (49%) of 934 of CAD-detected nodules were true nodules. The radiologist missed 110 true nodules that were only detected by CAD. In six patients, these were the only nodules detected in the examination, changing the imaging follow-up protocol. CAD identified 478 lesions that on consensus review were false-positive nodules, a rate of 3.19 (478/150) per patient. CONCLUSION. CAD detected 72.6% of true nodules and detected nodules in six (4%) patients not identified by radiologists, changing the imaging follow-up protocol of these subjects. In this study, the combined review of low-dose CT scans by both the radiologist and CAD was necessary to identify all nodules.