TY - JOUR
T1 - Effect of Reconstruction Parameters on the Quantitative Analysis of Chest Computed Tomography
AU - Kim, Hyungjin
AU - Goo, Jin Mo
AU - Ohno, Yoshiharu
AU - Kauczor, Hans Ulrich
AU - Hoffman, Eric A.
AU - Gee, James C.
AU - Van Beek, Edwin J.R.
N1 - Funding Information:
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.
Publisher Copyright:
© 2019 Wolters Kluwer Health, Inc. All rights reserved.
PY - 2019/3/1
Y1 - 2019/3/1
N2 - 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.
AB - 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.
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U2 - 10.1097/RTI.0000000000000389
DO - 10.1097/RTI.0000000000000389
M3 - Review article
C2 - 30802233
AN - SCOPUS:85060398018
VL - 34
SP - 92
EP - 102
JO - Journal of Thoracic Imaging
JF - Journal of Thoracic Imaging
SN - 0883-5993
IS - 2
ER -