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Repeatability of Multiparametric Prostate MRI Radiomics Features
In this study we assessed the repeatability of radiomics features on small prostate tumors using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI). The premise of radiomics is that quantitative image-based features can serve as biomarkers for detecting and characterizing disease. For su...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602944/ https://www.ncbi.nlm.nih.gov/pubmed/31263116 http://dx.doi.org/10.1038/s41598-019-45766-z |
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author | Schwier, Michael van Griethuysen, Joost Vangel, Mark G. Pieper, Steve Peled, Sharon Tempany, Clare Aerts, Hugo J. W. L. Kikinis, Ron Fennessy, Fiona M. Fedorov, Andriy |
author_facet | Schwier, Michael van Griethuysen, Joost Vangel, Mark G. Pieper, Steve Peled, Sharon Tempany, Clare Aerts, Hugo J. W. L. Kikinis, Ron Fennessy, Fiona M. Fedorov, Andriy |
author_sort | Schwier, Michael |
collection | PubMed |
description | In this study we assessed the repeatability of radiomics features on small prostate tumors using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI). The premise of radiomics is that quantitative image-based features can serve as biomarkers for detecting and characterizing disease. For such biomarkers to be useful, repeatability is a basic requirement, meaning its value must remain stable between two scans, if the conditions remain stable. We investigated repeatability of radiomics features under various preprocessing and extraction configurations including various image normalization schemes, different image pre-filtering, and different bin widths for image discretization. Although we found many radiomics features and preprocessing combinations with high repeatability (Intraclass Correlation Coefficient > 0.85), our results indicate that overall the repeatability is highly sensitive to the processing parameters. Neither image normalization, using a variety of approaches, nor the use of pre-filtering options resulted in consistent improvements in repeatability. We urge caution when interpreting radiomics features and advise paying close attention to the processing configuration details of reported results. Furthermore, we advocate reporting all processing details in radiomics studies and strongly recommend the use of open source implementations. |
format | Online Article Text |
id | pubmed-6602944 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66029442019-07-14 Repeatability of Multiparametric Prostate MRI Radiomics Features Schwier, Michael van Griethuysen, Joost Vangel, Mark G. Pieper, Steve Peled, Sharon Tempany, Clare Aerts, Hugo J. W. L. Kikinis, Ron Fennessy, Fiona M. Fedorov, Andriy Sci Rep Article In this study we assessed the repeatability of radiomics features on small prostate tumors using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI). The premise of radiomics is that quantitative image-based features can serve as biomarkers for detecting and characterizing disease. For such biomarkers to be useful, repeatability is a basic requirement, meaning its value must remain stable between two scans, if the conditions remain stable. We investigated repeatability of radiomics features under various preprocessing and extraction configurations including various image normalization schemes, different image pre-filtering, and different bin widths for image discretization. Although we found many radiomics features and preprocessing combinations with high repeatability (Intraclass Correlation Coefficient > 0.85), our results indicate that overall the repeatability is highly sensitive to the processing parameters. Neither image normalization, using a variety of approaches, nor the use of pre-filtering options resulted in consistent improvements in repeatability. We urge caution when interpreting radiomics features and advise paying close attention to the processing configuration details of reported results. Furthermore, we advocate reporting all processing details in radiomics studies and strongly recommend the use of open source implementations. Nature Publishing Group UK 2019-07-01 /pmc/articles/PMC6602944/ /pubmed/31263116 http://dx.doi.org/10.1038/s41598-019-45766-z Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Schwier, Michael van Griethuysen, Joost Vangel, Mark G. Pieper, Steve Peled, Sharon Tempany, Clare Aerts, Hugo J. W. L. Kikinis, Ron Fennessy, Fiona M. Fedorov, Andriy Repeatability of Multiparametric Prostate MRI Radiomics Features |
title | Repeatability of Multiparametric Prostate MRI Radiomics Features |
title_full | Repeatability of Multiparametric Prostate MRI Radiomics Features |
title_fullStr | Repeatability of Multiparametric Prostate MRI Radiomics Features |
title_full_unstemmed | Repeatability of Multiparametric Prostate MRI Radiomics Features |
title_short | Repeatability of Multiparametric Prostate MRI Radiomics Features |
title_sort | repeatability of multiparametric prostate mri radiomics features |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602944/ https://www.ncbi.nlm.nih.gov/pubmed/31263116 http://dx.doi.org/10.1038/s41598-019-45766-z |
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