Pulmonary Nodules: Automated Detection on CT Images with Morphologic Matching Algorithm—Preliminary Results

Abstract

Institutional review board approval was obtained. Informed patient consent was not required for this retrospective study, which involved review of previously obtained image data. Patient confidentiality was protected; the study was compliant with the Health Insurance Portability and Accountability Act. An automated pulmonary nodule detection program that takes advantage of three-dimensional volumetric data was developed and tested with multi-detector row computed tomographic (CT) images from 20 patients (13 men, seven women; age range, 40-75 years) with pulmonary nodules. A total of 164 nodules 3 mm in diameter and larger were detected by two radiologists in consensus and were used as a reference standard to evaluate the computer-aided detection (CAD) program. The CAD algorithm was structured to process nodules that were categorized into three types: isolated, juxtapleural, and juxtavascular. Overall sensitivity for nodule detection with the CAD program was 95.1% (156 of 164 nodules). The sensitivity according to nodule size was 91.2% (52 of 57 nodules) for nodules 3 mm to less than 5 mm and 97.2% (104 of 107 nodules) for nodules 5 mm and larger. The number of false-positive detections per patient was 6.9 for false nodule structures 3 mm and larger and 4.0 for false nodule structures 5 mm and larger.