The long and winding road of radiomics: learnings from two meta-analyses of the radiomics quality score
- Author(s)
- Barry, N; Kendrick, J; Molin, K; Li, S; Rowshanfarzad, P; Hassan, GM; Dowling, JA; Ong, JSL; Parizel, PM; Hofman, MS; Kocak, B; Cuocolo, R; Ebert, MA;
- Journal Title
- Physics in Medicine and Biology
- Publication Type
- Online publication before print
- Abstract
- The high-throughput extraction of radiomics features from medical images for predictive modelling holds great promise to improve the clinical management of patients. Previous meta-analyses into the radiomics quality score (RQS) applied in the literature have shown that after more than a decade of investigation, issues with workflow standardisation, model reproducibility, validation, and data accessibility persist and impede the clinical translation of radiomics-based models. These systematic findings have informed a timely review of the best practices and pitfalls to avoid within radiomics and predictive modelling, with a focus on realistic radiomics modelling in the context of limited sample sizes. Each section covers a radiomics topic that encompasses one or more RQS criteria and is broken into subsections as follows: 1) a discussion of the background and recommendations on the respective topic, 2) key findings from our meta-analyses and discovered pitfalls, and 3) a succinct list of actionable items that reflect best practice. New and emerging quality appraisal tools and the future direction of radiomics is also discussed.
- Keywords
- guidelines; imaging; precision medicine; radiomics; reproducibility; review
- Department(s)
- Cancer Imaging
- Publisher's Version
- https://doi.org/10.1088/1361-6560/ae36e0
- Open Access at Publisher's Site
https://doi.org/10.1088/1361-6560/ae36e0- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2026-01-20 12:06:11
Last Modified: 2026-01-20 12:06:31