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中风影像组学研究的质量评估:推动临床应用。

Quality assessment of stroke radiomics studies: Promoting clinical application.

作者信息

Sohn Beomseok, Won So Yeon

机构信息

Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea.

Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.

出版信息

Eur J Radiol. 2023 Apr;161:110752. doi: 10.1016/j.ejrad.2023.110752. Epub 2023 Feb 24.

DOI:10.1016/j.ejrad.2023.110752
PMID:36878154
Abstract

PURPOSE

To evaluate the quality of radiomics studies on stroke using a radiomics quality score (RQS), Minimum Information for Medial AI reporting (MINIMAR) and Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) to promote clinical application.

METHODS

PubMed MEDLINE and Embase were searched to identify radiomics studies on stroke. Of 464 articles, 52 relevant original research articles were included. The RQS, MINIMAR and TRIPOD were scored to evaluate the quality of the studies by neuroradiologists.

RESULTS

Only four studies (7.7 %) performed external validation. The mean RQS was 3.2 of 36 (8.9 %), and the basic adherence rate was 24.9 %. The adherence rate was low for conducting phantom study (1.9 %), stating comparison to 'gold standard' (1.9 %), offering potential clinical utility (13.5 %) and performing cost-effectiveness analysis (1.9 %). None of the studies performed a test-retest, stated biologic correlation, conducted prospective studies, or opened codes and data to the public, resulting in low RQS. The total MINIMAR adherence rate was 47.4 %. The overall adherence rate for TRIPOD was 54.6 %, with low scores for reporting the title (2.0 %), key elements of the study setting (6.1 %), and explaining the sample size (2.0 %).

CONCLUSIONS

The overall radiomics reporting quality and reporting of published radiomics studies on stoke was suboptimal. More thorough validation and open data are needed to increase clinical applicability of radiomics studies.

摘要

目的

使用影像组学质量评分(RQS)、医学人工智能报告的最低信息(MINIMAR)和个体预后或诊断多变量预测模型的透明报告(TRIPOD)评估关于中风的影像组学研究质量,以促进临床应用。

方法

检索PubMed MEDLINE和Embase以识别关于中风的影像组学研究。在464篇文章中,纳入了52篇相关的原创研究文章。由神经放射科医生对RQS、MINIMAR和TRIPOD进行评分,以评估研究质量。

结果

仅有四项研究(7.7%)进行了外部验证。平均RQS为36分中的3.2分(8.9%),基本依从率为24.9%。进行体模研究(1.9%)、说明与“金标准”的比较(1.9%)、提供潜在临床效用(13.5%)和进行成本效益分析(1.9%)的依从率较低。没有一项研究进行重测、说明生物学相关性、开展前瞻性研究或向公众公开代码和数据,导致RQS较低。MINIMAR的总依从率为47.4%。TRIPOD的总体依从率为54.6%,在报告标题(2.0%)、研究背景的关键要素(6.1%)和解释样本量(2.0%)方面得分较低。

结论

已发表的关于中风的影像组学研究的总体报告质量欠佳。需要更全面的验证和开放数据,以提高影像组学研究的临床适用性。

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