Radiomics Quality Score 2.0: towards radiomics readiness levels and clinical translation for personalized medicine
- PMID: 40903523
- DOI: 10.1038/s41571-025-01067-1
Radiomics Quality Score 2.0: towards radiomics readiness levels and clinical translation for personalized medicine
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.
© 2025. Springer Nature Limited.
Conflict of interest statement
Competing interests: P.L. has received grants and sponsored research agreements from Convert Pharmaceuticals SA, LivingMed Biotech srl and Radiomics SA; has received presenter fees and/or reimbursement of travel costs or consultancy fees (all in cash or in kind) from AstraZeneca, BHV srl and Roche; holds or has held minority shares in Bactam srl, Convert Pharmaceuticals SA, Comunicare SA, LivingMed Biotech srl and Radiomics SA; is a co-inventor on two issued patents with royalties on radiomics (PCT/NL2014/050248 and PCT/NL2014/050728) licensed to Radiomics SA, one issued patent on mtDNA (PCT/EP2014/059089) licensed to ptTheragnostic/DNAmito, one granted patent on LSRT (PCT/P126537PC00, US patent no. 12,102,842) licensed to Varian, one issued patent on prodrugs (WO2019EP64112) without royalties, one non-issued, non-licensed patent on deep learning radiomics (N2024889) and three non-patented inventions (software) licensed to Health Innovation Ventures, ptTheragnostic/DNAmito and Radiomics SA. P.L. confirms that none of these disclosures are related to the current manuscript and none of the above entities were involved in the preparation of this Review. H.C.W. owns minority shares in Radiomics SA, and confirms that this entity was not involved in the preparation of this manuscript. All other authors declare no competing interests.
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