Development of a novel computer-aided diagnosis system for automatic discrimination of malignant from benign solitary pulmonary nodules on thin-section dynamic computed tomography.

OBJECTIVES: As an application of the computer-aided diagnosis of solitary pulmonary nodules (SPNs), 3-dimensional contrast-enhanced (CE) dynamic helical computed tomography (HCT) was performed to evaluate temporal changes in the internal structure of nodules to differentiate between benign nodules (BNs) and malignant nodules (MNs). METHODS: There were 62 SPNs (35 MNs and 27 BNs) included in this study. Scanning (2-mm collimation) was performed before and 2 and 4 minutes after CE dynamic HCT. The CT data were sent to a computer, and the pixels inside the nodule were characterized in terms of 3 parameters (attenuation, shape index, and curvedness value). RESULTS: Based on the CT data at 4 (MN: 1.81-27.1, BN: -42.8 to -3.29) minutes after CE-dynamic HCT, a score of 0 or higher can be assumed to indicate an MN. CONCLUSIONS: Three-dimensional computer-aided diagnosis of the internal structure of SPNs using CE dynamic HCT was found to be effective for differentiating between BNs and MNs.