TY - JOUR
T1 - Pulmonary nodule characterization, including computer analysis and quantitative features
AU - Bartholmai, Brian J.
AU - Koo, Chi Wan
AU - Johnson, Geoffrey B.
AU - White, Darin B.
AU - Raghunath, Sushravya M.
AU - Rajagopalan, Srinivasan
AU - Moynagh, Michael R.
AU - Lindell, Rebecca M.
AU - Hartman, Thomas E.
N1 - Publisher Copyright:
Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.
PY - 2015/3/6
Y1 - 2015/3/6
N2 - Pulmonary 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.
AB - Pulmonary 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.
KW - attenuation
KW - computed tomography
KW - computer-Aided diagnosis
KW - lung cancer
KW - margin
KW - pulmonary nodules
KW - quantitative imaging
KW - screening
KW - shape
KW - size
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U2 - 10.1097/RTI.0000000000000137
DO - 10.1097/RTI.0000000000000137
M3 - Article
C2 - 25658478
AN - SCOPUS:84924145865
SN - 0883-5993
VL - 30
SP - 139
EP - 156
JO - Journal of thoracic imaging
JF - Journal of thoracic imaging
IS - 2
ER -