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A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility
OBJECTIVES: We aimed to present the state of the art of CT- and MRI-based radiomics in the context of ovarian cancer (OC), with a focus on the methodological quality of these studies and the clinical utility of these proposed radiomics models. METHODS: Original articles investigating radiomics in OC...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Vienna
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10317928/ https://www.ncbi.nlm.nih.gov/pubmed/37395888 http://dx.doi.org/10.1186/s13244-023-01464-z |
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author | Huang, Meng-Lin Ren, Jing Jin, Zheng-Yu Liu, Xin-Yu He, Yong-Lan Li, Yuan Xue, Hua-Dan |
author_facet | Huang, Meng-Lin Ren, Jing Jin, Zheng-Yu Liu, Xin-Yu He, Yong-Lan Li, Yuan Xue, Hua-Dan |
author_sort | Huang, Meng-Lin |
collection | PubMed |
description | OBJECTIVES: We aimed to present the state of the art of CT- and MRI-based radiomics in the context of ovarian cancer (OC), with a focus on the methodological quality of these studies and the clinical utility of these proposed radiomics models. METHODS: Original articles investigating radiomics in OC published in PubMed, Embase, Web of Science, and the Cochrane Library between January 1, 2002, and January 6, 2023, were extracted. The methodological quality was evaluated using the radiomics quality score (RQS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Pairwise correlation analyses were performed to compare the methodological quality, baseline information, and performance metrics. Additional meta-analyses of studies exploring differential diagnoses and prognostic prediction in patients with OC were performed separately. RESULTS: Fifty-seven studies encompassing 11,693 patients were included. The mean RQS was 30.7% (range − 4 to 22); less than 25% of studies had a high risk of bias and applicability concerns in each domain of QUADAS-2. A high RQS was significantly associated with a low QUADAS-2 risk and recent publication year. Significantly higher performance metrics were observed in studies examining differential diagnosis; 16 such studies as well as 13 exploring prognostic prediction were included in a separate meta-analysis, which revealed diagnostic odds ratios of 25.76 (95% confidence interval (CI) 13.50–49.13) and 12.55 (95% CI 8.38–18.77), respectively. CONCLUSION: Current evidence suggests that the methodological quality of OC-related radiomics studies is unsatisfactory. Radiomics analysis based on CT and MRI showed promising results in terms of differential diagnosis and prognostic prediction. CRITICAL RELEVANCE STATEMENT: Radiomics analysis has potential clinical utility; however, shortcomings persist in existing studies in terms of reproducibility. We suggest that future radiomics studies should be more standardized to better bridge the gap between concepts and clinical applications. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-023-01464-z. |
format | Online Article Text |
id | pubmed-10317928 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Vienna |
record_format | MEDLINE/PubMed |
spelling | pubmed-103179282023-07-05 A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility Huang, Meng-Lin Ren, Jing Jin, Zheng-Yu Liu, Xin-Yu He, Yong-Lan Li, Yuan Xue, Hua-Dan Insights Imaging Critical Review OBJECTIVES: We aimed to present the state of the art of CT- and MRI-based radiomics in the context of ovarian cancer (OC), with a focus on the methodological quality of these studies and the clinical utility of these proposed radiomics models. METHODS: Original articles investigating radiomics in OC published in PubMed, Embase, Web of Science, and the Cochrane Library between January 1, 2002, and January 6, 2023, were extracted. The methodological quality was evaluated using the radiomics quality score (RQS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Pairwise correlation analyses were performed to compare the methodological quality, baseline information, and performance metrics. Additional meta-analyses of studies exploring differential diagnoses and prognostic prediction in patients with OC were performed separately. RESULTS: Fifty-seven studies encompassing 11,693 patients were included. The mean RQS was 30.7% (range − 4 to 22); less than 25% of studies had a high risk of bias and applicability concerns in each domain of QUADAS-2. A high RQS was significantly associated with a low QUADAS-2 risk and recent publication year. Significantly higher performance metrics were observed in studies examining differential diagnosis; 16 such studies as well as 13 exploring prognostic prediction were included in a separate meta-analysis, which revealed diagnostic odds ratios of 25.76 (95% confidence interval (CI) 13.50–49.13) and 12.55 (95% CI 8.38–18.77), respectively. CONCLUSION: Current evidence suggests that the methodological quality of OC-related radiomics studies is unsatisfactory. Radiomics analysis based on CT and MRI showed promising results in terms of differential diagnosis and prognostic prediction. CRITICAL RELEVANCE STATEMENT: Radiomics analysis has potential clinical utility; however, shortcomings persist in existing studies in terms of reproducibility. We suggest that future radiomics studies should be more standardized to better bridge the gap between concepts and clinical applications. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-023-01464-z. Springer Vienna 2023-07-03 /pmc/articles/PMC10317928/ /pubmed/37395888 http://dx.doi.org/10.1186/s13244-023-01464-z Text en © The Author(s) 2023 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 | Critical Review Huang, Meng-Lin Ren, Jing Jin, Zheng-Yu Liu, Xin-Yu He, Yong-Lan Li, Yuan Xue, Hua-Dan A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility |
title | A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility |
title_full | A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility |
title_fullStr | A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility |
title_full_unstemmed | A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility |
title_short | A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility |
title_sort | systematic review and meta-analysis of ct and mri radiomics in ovarian cancer: methodological issues and clinical utility |
topic | Critical Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10317928/ https://www.ncbi.nlm.nih.gov/pubmed/37395888 http://dx.doi.org/10.1186/s13244-023-01464-z |
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