• Brian J Bartholmai, Chi Wan Koo, Geoffrey B Johnson, Darin B White, Sushravya M Raghunath, Srinivasan Rajagopalan, Michael R Moynagh, Rebecca M Lindell, and Thomas E Hartman.
• *Department of Radiology, Division of Thoracic Radiology Departments of †Immunology ‡Biomedical Engineering and Physiology, Mayo Clinic, Rochester, MN.
• J Thorac Imaging. 2015 Mar 1; 30 (2): 139-56.

AbstractPulmonary nodules are commonly detected in computed tomography (CT) chest screening of a high-risk population. The specific visual or quantitative features on CT or other modalities can be used to characterize the likelihood that a nodule is benign or malignant. Visual features on CT such as size, attenuation, location, morphology, edge characteristics, and other distinctive "signs" can be highly suggestive of a specific diagnosis and, in general, be used to determine the probability that a specific nodule is benign or malignant. Change in size, attenuation, and morphology on serial follow-up CT, or features on other modalities such as nuclear medicine studies or MRI, can also contribute to the characterization of lung nodules. Imaging analytics can objectively and reproducibly quantify nodule features on CT, nuclear medicine, and magnetic resonance imaging. Some quantitative techniques show great promise in helping to differentiate benign from malignant lesions or to stratify the risk of aggressive versus indolent neoplasm. In this article, we (1) summarize the visual characteristics, descriptors, and signs that may be helpful in management of nodules identified on screening CT, (2) discuss current quantitative and multimodality techniques that aid in the differentiation of nodules, and (3) highlight the power, pitfalls, and limitations of these various techniques.

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