Radiomics feature robustness as measured using an MRI phantom

Abstract Radiomics involves high-throughput extraction of large numbers of quantitative features from medical images and analysis of these features to predict patients’ outcome and support clinical decision-making. However, radiomics features are sensitive to several factors, including scanning prot...

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Autores principales:	Joonsang Lee, Angela Steinmann, Yao Ding, Hannah Lee, Constance Owens, Jihong Wang, Jinzhong Yang, David Followill, Rachel Ger, Dennis MacKin, Laurence E. Court
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/54192feb84fc48fc863463a32b264999
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spelling	oai:doaj.org-article:54192feb84fc48fc863463a32b2649992021-12-02T10:54:31ZRadiomics feature robustness as measured using an MRI phantom10.1038/s41598-021-83593-32045-2322https://doaj.org/article/54192feb84fc48fc863463a32b2649992021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83593-3https://doaj.org/toc/2045-2322Abstract Radiomics involves high-throughput extraction of large numbers of quantitative features from medical images and analysis of these features to predict patients’ outcome and support clinical decision-making. However, radiomics features are sensitive to several factors, including scanning protocols. The purpose of this study was to investigate the robustness of magnetic resonance imaging (MRI) radiomics features with various MRI scanning protocol parameters and scanners using an MRI radiomics phantom. The variability of the radiomics features with different scanning parameters and repeatability measured using a test–retest scheme were evaluated using the coefficient of variation and intraclass correlation coefficient (ICC) for both T1- and T2-weighted images. For variability measures, the features were categorized into three groups: large, intermediate, and small variation. For repeatability measures, the average T1- and T2-weighted image ICCs for the phantom (0.963 and 0.959, respectively) were higher than those for a healthy volunteer (0.856 and 0.849, respectively). Our results demonstrated that various radiomics features are dependent on different scanning parameters and scanners. The radiomics features with a low coefficient of variation and high ICC for both the phantom and volunteer can be considered good candidates for MRI radiomics studies. The results of this study will assist current and future MRI radiomics studies.Joonsang LeeAngela SteinmannYao DingHannah LeeConstance OwensJihong WangJinzhong YangDavid FollowillRachel GerDennis MacKinLaurence E. CourtNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Joonsang Lee Angela Steinmann Yao Ding Hannah Lee Constance Owens Jihong Wang Jinzhong Yang David Followill Rachel Ger Dennis MacKin Laurence E. Court Radiomics feature robustness as measured using an MRI phantom
description	Abstract Radiomics involves high-throughput extraction of large numbers of quantitative features from medical images and analysis of these features to predict patients’ outcome and support clinical decision-making. However, radiomics features are sensitive to several factors, including scanning protocols. The purpose of this study was to investigate the robustness of magnetic resonance imaging (MRI) radiomics features with various MRI scanning protocol parameters and scanners using an MRI radiomics phantom. The variability of the radiomics features with different scanning parameters and repeatability measured using a test–retest scheme were evaluated using the coefficient of variation and intraclass correlation coefficient (ICC) for both T1- and T2-weighted images. For variability measures, the features were categorized into three groups: large, intermediate, and small variation. For repeatability measures, the average T1- and T2-weighted image ICCs for the phantom (0.963 and 0.959, respectively) were higher than those for a healthy volunteer (0.856 and 0.849, respectively). Our results demonstrated that various radiomics features are dependent on different scanning parameters and scanners. The radiomics features with a low coefficient of variation and high ICC for both the phantom and volunteer can be considered good candidates for MRI radiomics studies. The results of this study will assist current and future MRI radiomics studies.
format	article
author	Joonsang Lee Angela Steinmann Yao Ding Hannah Lee Constance Owens Jihong Wang Jinzhong Yang David Followill Rachel Ger Dennis MacKin Laurence E. Court
author_facet	Joonsang Lee Angela Steinmann Yao Ding Hannah Lee Constance Owens Jihong Wang Jinzhong Yang David Followill Rachel Ger Dennis MacKin Laurence E. Court
author_sort	Joonsang Lee
title	Radiomics feature robustness as measured using an MRI phantom
title_short	Radiomics feature robustness as measured using an MRI phantom
title_full	Radiomics feature robustness as measured using an MRI phantom
title_fullStr	Radiomics feature robustness as measured using an MRI phantom
title_full_unstemmed	Radiomics feature robustness as measured using an MRI phantom
title_sort	radiomics feature robustness as measured using an mri phantom
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/54192feb84fc48fc863463a32b264999
work_keys_str_mv	AT joonsanglee radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT angelasteinmann radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT yaoding radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT hannahlee radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT constanceowens radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT jihongwang radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT jinzhongyang radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT davidfollowill radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT rachelger radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT dennismackin radiomicsfeaturerobustnessasmeasuredusinganmriphantom AT laurenceecourt radiomicsfeaturerobustnessasmeasuredusinganmriphantom
_version_	1718396469665333248

Radiomics feature robustness as measured using an MRI phantom

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