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Effect of Reconstruction Parameters on the Quantitative Analysis of Chest Computed Tomography

Kim, Hyungjin MD*; Goo, Jin Mo MD, PhD*,†; Ohno, Yoshiharu MD, PhD; Kauczor, Hans-Ulrich MD§; Hoffman, Eric A. PhD; Gee, James C. PhD; van Beek, Edwin J.R. MD, PhD#

doi: 10.1097/RTI.0000000000000389
Pulmonary/Thoracic
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Quantitative features obtained from computed tomography (CT) scans are being explored for clinical applications. Various classes of quantitative features exist for chest CT including radiomics features, emphysema measurements, lung nodule volumetric measurements, dual energy quantification, and perfusion parameters. A number of research articles have shown promise in diagnosis and prognosis prediction of oncologic patients or those with diffuse lung diseases using these feature classes. Nevertheless, a prerequisite for the quantification is the evaluation of variation in measurements in terms of repeatability and reproducibility, which are distinct aspects of precision but are often not separable from each other. There are well-known sources of measurement variability including patient factors, CT acquisition (scan and reconstruction) factors, and radiologist (or measurement-related) factors. The purpose of this article is to review the effects of CT reconstruction parameters on the quantitative imaging features and efforts to correct or neutralize variations induced by those parameters.

*Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center

Cancer Research Institute, Seoul National University, Seoul, Korea

Department of Radiology, Division of Functional and Diagnostic Imaging Research, Kobe University Graduate School of Medicine, Kobe, Japan

§Department of Diagnostic and Interventional Radiology, University of Heidelberg, Translational Lung Research Center Heidelberg, Heidelberg, Germany

Departments of Radiology, Medicine and Biomedical Engineering, University of Iowa, Iowa City; IA

Department of Radiology, University of Pennsylvania, Philadelphia, PA

#Edinburgh Imaging, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, UK

Y.O. received a research grant from Canon Medical Systems. E.J.R.v.B. is a member of advisory boards of Imbio and Aidence. He is also the owner/founder of Quantitative Clinical Trials Imaging Services. The remaining authors declare no conflicts of interest.

Correspondence to: Jin Mo Goo, MD, PhD, Department of Radiology, Seoul National University College of Medicine, 101, Daehak-ro, Jongno-gu, Seoul 03080, Korea (e-mail: jmgoo@plaza.snu.ac.kr).

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