Effect of reconstruction parameters on the quantitative analysis of chest computed tomography

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 perf...

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Hauptverfasser: Kim, Hyungjin (VerfasserIn) , Kauczor, Hans-Ulrich (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: March 1, 2019
In: Journal of thoracic imaging
Year: 2019, Jahrgang: 34, Heft: 2, Pages: 92-102
ISSN:1536-0237
DOI:10.1097/RTI.0000000000000389
Online-Zugang:Verlag, Volltext: https://doi.org/10.1097/RTI.0000000000000389
Verlag, Volltext: https://journals.lww.com/thoracicimaging/Abstract/2019/03000/Effect_of_Reconstruction_Parameters_on_the.4.aspx
Volltext
Verfasserangaben:Hyungjin Kim, Jin Mo Goo, Yoshiharu Ohno, Hans-Ulrich Kauczor, Eric A. Hoffman, James C. Gee, Edwin J.R. van Beek

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520 |a 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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