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Criteria for the translation of radiomics into clinically useful tests

Computer-extracted tumour characteristics have been incorporated into medical imaging computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an extension of CAD involving high-throughput computer-extracted quantitative characterization of healthy or pathological structu...

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Autores principales: Huang, Erich P., O’Connor, James P. B., McShane, Lisa M., Giger, Maryellen L., Lambin, Philippe, Kinahan, Paul E., Siegel, Eliot L., Shankar, Lalitha K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707172/
https://www.ncbi.nlm.nih.gov/pubmed/36443594
http://dx.doi.org/10.1038/s41571-022-00707-0
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author Huang, Erich P.
O’Connor, James P. B.
McShane, Lisa M.
Giger, Maryellen L.
Lambin, Philippe
Kinahan, Paul E.
Siegel, Eliot L.
Shankar, Lalitha K.
author_facet Huang, Erich P.
O’Connor, James P. B.
McShane, Lisa M.
Giger, Maryellen L.
Lambin, Philippe
Kinahan, Paul E.
Siegel, Eliot L.
Shankar, Lalitha K.
author_sort Huang, Erich P.
collection PubMed
description Computer-extracted tumour characteristics have been incorporated into medical imaging computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an extension of CAD involving high-throughput computer-extracted quantitative characterization of healthy or pathological structures and processes as captured by medical imaging, interest in such computer-extracted measurements has increased substantially. However, despite the thousands of radiomic studies, the number of settings in which radiomics has been successfully translated into a clinically useful tool or has obtained FDA clearance is comparatively small. This relative dearth might be attributable to factors such as the varying imaging and radiomic feature extraction protocols used from study to study, the numerous potential pitfalls in the analysis of radiomic data, and the lack of studies showing that acting upon a radiomic-based tool leads to a favourable benefit–risk balance for the patient. Several guidelines on specific aspects of radiomic data acquisition and analysis are already available, although a similar roadmap for the overall process of translating radiomics into tools that can be used in clinical care is needed. Herein, we provide 16 criteria for the effective execution of this process in the hopes that they will guide the development of more clinically useful radiomic tests in the future.
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spelling pubmed-97071722022-11-29 Criteria for the translation of radiomics into clinically useful tests Huang, Erich P. O’Connor, James P. B. McShane, Lisa M. Giger, Maryellen L. Lambin, Philippe Kinahan, Paul E. Siegel, Eliot L. Shankar, Lalitha K. Nat Rev Clin Oncol Review Article Computer-extracted tumour characteristics have been incorporated into medical imaging computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an extension of CAD involving high-throughput computer-extracted quantitative characterization of healthy or pathological structures and processes as captured by medical imaging, interest in such computer-extracted measurements has increased substantially. However, despite the thousands of radiomic studies, the number of settings in which radiomics has been successfully translated into a clinically useful tool or has obtained FDA clearance is comparatively small. This relative dearth might be attributable to factors such as the varying imaging and radiomic feature extraction protocols used from study to study, the numerous potential pitfalls in the analysis of radiomic data, and the lack of studies showing that acting upon a radiomic-based tool leads to a favourable benefit–risk balance for the patient. Several guidelines on specific aspects of radiomic data acquisition and analysis are already available, although a similar roadmap for the overall process of translating radiomics into tools that can be used in clinical care is needed. Herein, we provide 16 criteria for the effective execution of this process in the hopes that they will guide the development of more clinically useful radiomic tests in the future. Nature Publishing Group UK 2022-11-28 2023 /pmc/articles/PMC9707172/ /pubmed/36443594 http://dx.doi.org/10.1038/s41571-022-00707-0 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Review Article
Huang, Erich P.
O’Connor, James P. B.
McShane, Lisa M.
Giger, Maryellen L.
Lambin, Philippe
Kinahan, Paul E.
Siegel, Eliot L.
Shankar, Lalitha K.
Criteria for the translation of radiomics into clinically useful tests
title Criteria for the translation of radiomics into clinically useful tests
title_full Criteria for the translation of radiomics into clinically useful tests
title_fullStr Criteria for the translation of radiomics into clinically useful tests
title_full_unstemmed Criteria for the translation of radiomics into clinically useful tests
title_short Criteria for the translation of radiomics into clinically useful tests
title_sort criteria for the translation of radiomics into clinically useful tests
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707172/
https://www.ncbi.nlm.nih.gov/pubmed/36443594
http://dx.doi.org/10.1038/s41571-022-00707-0
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