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Radiomics Quality Score 2.0: towards radiomics readiness levels and clinical translation for personalized medicine.

作者信息

Lambin Philippe, Woodruff Henry C, Mali Shruti Atul, Zhong Xian, Kuang Sheng, Lavrova Elizaveta, Khan Hamza, Lekadir Karim, Zwanenburg Alex, Deasy Joseph, Bobowicz Maciej, Marti-Bonmati Luis, Maidment Andrew, Dumontier Michel, Kinahan Paul E, Nobel J Martijn, Amirrajab Sina, Salahuddin Zohaib

机构信息

The D-Lab, Department of Precision Medicine, GROW Research Institute for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands.

Department of Radiology and Nuclear Medicine, GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, Netherlands.

出版信息

Nat Rev Clin Oncol. 2025 Sep 3. doi: 10.1038/s41571-025-01067-1.


DOI:10.1038/s41571-025-01067-1
PMID:40903523
Abstract

Radiomics is a tool for medical imaging analysis that could have a relevant role in precision oncology by offering precise quantitative support for clinical decision-making. The Radiomics Quality Score (RQS) is a tool developed to assess the rigour of radiomics studies that has now been widely adopted by researchers. Although RQS version 1.0 established a benchmark, an updated framework is required to account for evolving knowledge and ensure optimal evaluation of the quality of radiomics studies through the inclusion of fairness, explainability, rigorous quality control and harmonization. In this Review, we introduce the updated RQS 2.0, which maintains the scientific rigour of its predecessor and addresses these contemporary needs, and therefore could potentially accelerate clinical translation. Moreover, we introduce the radiomics readiness levels, inspired by the technology readiness level framework, which are integrated in RQS 2.0 and reflect nine distinct levels of incremental improvement in radiomics research with the ultimate aim of clinical implementation. We also detail anticipated future directions in radiomics, outlining a strategic vision to advance precision oncology, which is the ultimate aim of RQS 2.0.

摘要

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[3]
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[4]
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