Armando Ugo Cavallo, Arnaldo Stanzione, Andrea Ponsiglione, Romina Trotta, Salvatore Claudio Fanni, Samuele Ghezzo, Federica Vernuccio, Michail E Klontzas, Matthaios Triantafyllou, Lorenzo Ugga, Georgios Kalarakis, Roberto Cannella, Renato Cuocolo
{"title":"前列腺癌MRI方法学放射组学评分:EuSoMII放射组学审计组倡议。","authors":"Armando Ugo Cavallo, Arnaldo Stanzione, Andrea Ponsiglione, Romina Trotta, Salvatore Claudio Fanni, Samuele Ghezzo, Federica Vernuccio, Michail E Klontzas, Matthaios Triantafyllou, Lorenzo Ugga, Georgios Kalarakis, Roberto Cannella, Renato Cuocolo","doi":"10.1007/s00330-024-11299-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the quality of radiomics research in prostate MRI for the evaluation of prostate cancer (PCa) through the assessment of METhodological RadiomICs (METRICS) score, a new scoring tool recently introduced with the goal of fostering further improvement in radiomics and machine learning methodology.</p><p><strong>Materials and methods: </strong>A literature search was conducted from July 1st, 2019, to November 30th, 2023, to identify original investigations assessing MRI-based radiomics in the setting of PCa. Seven readers with varying expertise underwent a quality assessment using METRICS. Subgroup analyses were performed to assess whether the quality score varied according to papers' categories (diagnosis, staging, prognosis, technical) and quality ratings among these latter.</p><p><strong>Results: </strong>From a total of 1106 records, 185 manuscripts were available. Overall, the average METRICS total score was 52% ± 16%. ANOVA and chi-square tests revealed no statistically significant differences between subgroups. Items with the lowest positive scores were adherence to guidelines/checklists (4.9%), handling of confounding factors (14.1%), external testing (15.1%), and the availability of data (15.7%), code (4.3%), and models (1.6%). Conversely, most studies clearly defined patient selection criteria (86.5%), employed a high-quality reference standard (89.2%), and utilized a well-described (85.9%) and clinically applicable (87%) imaging protocol as a radiomics data source.</p><p><strong>Conclusion: </strong>The quality of MRI-based radiomics research for PCa in recent studies demonstrated good homogeneity and overall moderate quality.</p><p><strong>Key points: </strong>Question To evaluate the quality of MRI-based radiomics research for PCa, assessed through the METRICS score. Findings The average METRICS total score was 52%, reflecting moderate quality in MRI-based radiomics research for PCa, with no statistically significant differences between subgroups. Clinical relevance Enhancing the quality of radiomics research can improve diagnostic accuracy for PCa, leading to better patient outcomes and more informed clinical decision-making.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"1157-1165"},"PeriodicalIF":4.7000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prostate cancer MRI methodological radiomics score: a EuSoMII radiomics auditing group initiative.\",\"authors\":\"Armando Ugo Cavallo, Arnaldo Stanzione, Andrea Ponsiglione, Romina Trotta, Salvatore Claudio Fanni, Samuele Ghezzo, Federica Vernuccio, Michail E Klontzas, Matthaios Triantafyllou, Lorenzo Ugga, Georgios Kalarakis, Roberto Cannella, Renato Cuocolo\",\"doi\":\"10.1007/s00330-024-11299-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>To evaluate the quality of radiomics research in prostate MRI for the evaluation of prostate cancer (PCa) through the assessment of METhodological RadiomICs (METRICS) score, a new scoring tool recently introduced with the goal of fostering further improvement in radiomics and machine learning methodology.</p><p><strong>Materials and methods: </strong>A literature search was conducted from July 1st, 2019, to November 30th, 2023, to identify original investigations assessing MRI-based radiomics in the setting of PCa. Seven readers with varying expertise underwent a quality assessment using METRICS. Subgroup analyses were performed to assess whether the quality score varied according to papers' categories (diagnosis, staging, prognosis, technical) and quality ratings among these latter.</p><p><strong>Results: </strong>From a total of 1106 records, 185 manuscripts were available. Overall, the average METRICS total score was 52% ± 16%. ANOVA and chi-square tests revealed no statistically significant differences between subgroups. Items with the lowest positive scores were adherence to guidelines/checklists (4.9%), handling of confounding factors (14.1%), external testing (15.1%), and the availability of data (15.7%), code (4.3%), and models (1.6%). Conversely, most studies clearly defined patient selection criteria (86.5%), employed a high-quality reference standard (89.2%), and utilized a well-described (85.9%) and clinically applicable (87%) imaging protocol as a radiomics data source.</p><p><strong>Conclusion: </strong>The quality of MRI-based radiomics research for PCa in recent studies demonstrated good homogeneity and overall moderate quality.</p><p><strong>Key points: </strong>Question To evaluate the quality of MRI-based radiomics research for PCa, assessed through the METRICS score. Findings The average METRICS total score was 52%, reflecting moderate quality in MRI-based radiomics research for PCa, with no statistically significant differences between subgroups. Clinical relevance Enhancing the quality of radiomics research can improve diagnostic accuracy for PCa, leading to better patient outcomes and more informed clinical decision-making.</p>\",\"PeriodicalId\":12076,\"journal\":{\"name\":\"European Radiology\",\"volume\":\" \",\"pages\":\"1157-1165\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Radiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00330-024-11299-x\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/12/30 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00330-024-11299-x","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/30 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Prostate cancer MRI methodological radiomics score: a EuSoMII radiomics auditing group initiative.
Objectives: To evaluate the quality of radiomics research in prostate MRI for the evaluation of prostate cancer (PCa) through the assessment of METhodological RadiomICs (METRICS) score, a new scoring tool recently introduced with the goal of fostering further improvement in radiomics and machine learning methodology.
Materials and methods: A literature search was conducted from July 1st, 2019, to November 30th, 2023, to identify original investigations assessing MRI-based radiomics in the setting of PCa. Seven readers with varying expertise underwent a quality assessment using METRICS. Subgroup analyses were performed to assess whether the quality score varied according to papers' categories (diagnosis, staging, prognosis, technical) and quality ratings among these latter.
Results: From a total of 1106 records, 185 manuscripts were available. Overall, the average METRICS total score was 52% ± 16%. ANOVA and chi-square tests revealed no statistically significant differences between subgroups. Items with the lowest positive scores were adherence to guidelines/checklists (4.9%), handling of confounding factors (14.1%), external testing (15.1%), and the availability of data (15.7%), code (4.3%), and models (1.6%). Conversely, most studies clearly defined patient selection criteria (86.5%), employed a high-quality reference standard (89.2%), and utilized a well-described (85.9%) and clinically applicable (87%) imaging protocol as a radiomics data source.
Conclusion: The quality of MRI-based radiomics research for PCa in recent studies demonstrated good homogeneity and overall moderate quality.
Key points: Question To evaluate the quality of MRI-based radiomics research for PCa, assessed through the METRICS score. Findings The average METRICS total score was 52%, reflecting moderate quality in MRI-based radiomics research for PCa, with no statistically significant differences between subgroups. Clinical relevance Enhancing the quality of radiomics research can improve diagnostic accuracy for PCa, leading to better patient outcomes and more informed clinical decision-making.
期刊介绍:
European Radiology (ER) continuously updates scientific knowledge in radiology by publication of strong original articles and state-of-the-art reviews written by leading radiologists. A well balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes ER an indispensable source for current information in this field.
This is the Journal of the European Society of Radiology, and the official journal of a number of societies.
From 2004-2008 supplements to European Radiology were published under its companion, European Radiology Supplements, ISSN 1613-3749.