Review ArticlesQuantitative Computed Tomography Imaging Biomarkers in the Diagnosis and Management of Lung CancerKim, Hyungjin MD*†‡; Park, Chang Min MD, PhD*†§; Goo, Jin Mo MD, PhD*†§; Wildberger, Joachim E. MD, PhD∥; Kauczor, Hans-Ulrich MD¶Author Information From the *Department of Radiology, College of Medicine, and †Institute of Radiation Medicine, Medical Research Center, Seoul National University, Seoul; ‡Aerospace Medical Group, Air Force Education and Training Command, Jinju City; §Cancer Research Institute, Seoul National University, Seoul, South Korea; ║Department of Radiology, Maastricht University Medical Center, Maastricht, the Netherlands; and ¶Department of Diagnostic and Interventional Radiology, University of Heidelberg, Heidelberg, Germany. Received for publication February 1, 2015; and accepted for publication, after revision, February 5, 2015. Conflicts of interest and sources of funding: none declared. Correspondence to: Jin Mo Goo, MD, PhD, Department of Radiology, College of Medicine, Seoul National University, 101, Daehak-ro, Jongno-gu, Seoul 110-744, South Korea. E-mail: email@example.com. Investigative Radiology: September 2015 - Volume 50 - Issue 9 - p 571-583 doi: 10.1097/RLI.0000000000000152 Buy Metrics Abstract Tumor diameter has traditionally been used as a standard metric in terms of diagnosis and prognosis prediction of lung cancer. However, recent advances in imaging techniques and data analyses have enabled novel quantitative imaging biomarkers that can characterize disease status more comprehensively and/or predict tumor behavior more precisely. The most widely used imaging modality for lung tumor assessment is computed tomography. Therefore, we focused on computed tomography imaging biomarkers such as tumor volume and mass, ground-glass opacities, perfusion parameters, as well as texture features in this review. Herein, we first appraised the conventional 1- or 2-dimensional measurement with brief discussion on their limits and then introduced the potential imaging biomarkers with emphasis on the current understanding of their clinical usefulness with respect to the malignancy differentiation, treatment response monitoring, and patient outcome prediction. Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.