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Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative
OBJECTIVE: The main aim of the present systematic review was a comprehensive overview of the Radiomics Quality Score (RQS)–based systematic reviews to highlight common issues and challenges of radiomics research application and evaluate the relationship between RQS and review features. METHODS: The...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9935718/ https://www.ncbi.nlm.nih.gov/pubmed/36282312 http://dx.doi.org/10.1007/s00330-022-09187-3 |
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author | Spadarella, Gaia Stanzione, Arnaldo Akinci D’Antonoli, Tugba Andreychenko, Anna Fanni, Salvatore Claudio Ugga, Lorenzo Kotter, Elmar Cuocolo, Renato |
author_facet | Spadarella, Gaia Stanzione, Arnaldo Akinci D’Antonoli, Tugba Andreychenko, Anna Fanni, Salvatore Claudio Ugga, Lorenzo Kotter, Elmar Cuocolo, Renato |
author_sort | Spadarella, Gaia |
collection | PubMed |
description | OBJECTIVE: The main aim of the present systematic review was a comprehensive overview of the Radiomics Quality Score (RQS)–based systematic reviews to highlight common issues and challenges of radiomics research application and evaluate the relationship between RQS and review features. METHODS: The literature search was performed on multiple medical literature archives according to PRISMA guidelines for systematic reviews that reported radiomic quality assessment through the RQS. Reported scores were converted to a 0–100% scale. The Mann-Whitney and Kruskal-Wallis tests were used to compare RQS scores and review features. RESULTS: The literature research yielded 345 articles, from which 44 systematic reviews were finally included in the analysis. Overall, the median of RQS was 21.00% (IQR = 11.50). No significant differences of RQS were observed in subgroup analyses according to targets (oncological/not oncological target, neuroradiology/body imaging focus and one imaging technique/more than one imaging technique, characterization/prognosis/detection/other). CONCLUSIONS: Our review did not reveal a significant difference of quality of radiomic articles reported in systematic reviews, divided in different subgroups. Furthermore, low overall methodological quality of radiomics research was found independent of specific application domains. While the RQS can serve as a reference tool to improve future study designs, future research should also be aimed at improving its reliability and developing new tools to meet an ever-evolving research space. KEY POINTS: • Radiomics is a promising high-throughput method that may generate novel imaging biomarkers to improve clinical decision-making process, but it is an inherently complex analysis and often lacks reproducibility and generalizability. • The Radiomics Quality Score serves a necessary role as the de facto reference tool for assessing radiomics studies. • External auditing of radiomics studies, in addition to the standard peer-review process, is valuable to highlight common limitations and provide insights to improve future study designs and practical applicability of the radiomics models. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-09187-3. |
format | Online Article Text |
id | pubmed-9935718 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-99357182023-02-18 Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative Spadarella, Gaia Stanzione, Arnaldo Akinci D’Antonoli, Tugba Andreychenko, Anna Fanni, Salvatore Claudio Ugga, Lorenzo Kotter, Elmar Cuocolo, Renato Eur Radiol Imaging Informatics and Artificial Intelligence OBJECTIVE: The main aim of the present systematic review was a comprehensive overview of the Radiomics Quality Score (RQS)–based systematic reviews to highlight common issues and challenges of radiomics research application and evaluate the relationship between RQS and review features. METHODS: The literature search was performed on multiple medical literature archives according to PRISMA guidelines for systematic reviews that reported radiomic quality assessment through the RQS. Reported scores were converted to a 0–100% scale. The Mann-Whitney and Kruskal-Wallis tests were used to compare RQS scores and review features. RESULTS: The literature research yielded 345 articles, from which 44 systematic reviews were finally included in the analysis. Overall, the median of RQS was 21.00% (IQR = 11.50). No significant differences of RQS were observed in subgroup analyses according to targets (oncological/not oncological target, neuroradiology/body imaging focus and one imaging technique/more than one imaging technique, characterization/prognosis/detection/other). CONCLUSIONS: Our review did not reveal a significant difference of quality of radiomic articles reported in systematic reviews, divided in different subgroups. Furthermore, low overall methodological quality of radiomics research was found independent of specific application domains. While the RQS can serve as a reference tool to improve future study designs, future research should also be aimed at improving its reliability and developing new tools to meet an ever-evolving research space. KEY POINTS: • Radiomics is a promising high-throughput method that may generate novel imaging biomarkers to improve clinical decision-making process, but it is an inherently complex analysis and often lacks reproducibility and generalizability. • The Radiomics Quality Score serves a necessary role as the de facto reference tool for assessing radiomics studies. • External auditing of radiomics studies, in addition to the standard peer-review process, is valuable to highlight common limitations and provide insights to improve future study designs and practical applicability of the radiomics models. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-09187-3. Springer Berlin Heidelberg 2022-10-25 2023 /pmc/articles/PMC9935718/ /pubmed/36282312 http://dx.doi.org/10.1007/s00330-022-09187-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Imaging Informatics and Artificial Intelligence Spadarella, Gaia Stanzione, Arnaldo Akinci D’Antonoli, Tugba Andreychenko, Anna Fanni, Salvatore Claudio Ugga, Lorenzo Kotter, Elmar Cuocolo, Renato Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative |
title | Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative |
title_full | Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative |
title_fullStr | Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative |
title_full_unstemmed | Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative |
title_short | Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative |
title_sort | systematic review of the radiomics quality score applications: an eusomii radiomics auditing group initiative |
topic | Imaging Informatics and Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9935718/ https://www.ncbi.nlm.nih.gov/pubmed/36282312 http://dx.doi.org/10.1007/s00330-022-09187-3 |
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