4.7 Article

Quality of science and reporting of radiomics in oncologic studies: room for improvement according to radiomics quality score and TRIPOD statement

Journal

EUROPEAN RADIOLOGY
Volume 30, Issue 1, Pages 523-536

Publisher

SPRINGER
DOI: 10.1007/s00330-019-06360-z

Keywords

Neoplasm; Machine learning; Quality improvement; Computed tomography; Magnetic resonance imaging

Funding

  1. National Research Foundation of Korea (NRF) - Korea government (MSIP) [NRF-2017R1A2A2A05001217, NRF-2017R1C1B2007258]

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Objectives To evaluate radiomics studies according to radiomics quality score (RQS) and Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) to provide objective measurement of radiomics research. Materials and methods PubMed and Embase were searched for studies published in high clinical imaging journals until December 2018 using the terms radiomics and radiogenomics. Studies were scored against the items in the RQS and TRIPOD guidelines. Subgroup analyses were performed for journal type (clinical vs. imaging), intended use (diagnostic vs. prognostic), and imaging modality (CT vs. MRI), and articles were compared using Fisher's exact test and Mann-Whitney analysis. Results Seventy-seven articles were included. The mean RQS score was 26.1% of the maximum (9.4 out of 36). The RQS was low in demonstration of clinical utility (19.5%), test-retest analysis (6.5%), prospective study (3.9%), and open science (3.9%). None of the studies conducted a phantom or cost-effectiveness analysis. The adherence rate for TRIPOD was 57.8% (mean) and was particularly low in reporting title (2.6%), stating study objective in abstract and introduction (7.8% and 16.9%), blind assessment of outcome (14.3%), sample size (6.5%), and missing data (11.7%) categories. Studies in clinical journals scored higher and more frequently adopted external validation than imaging journals. Conclusions The overall scientific quality and reporting of radiomics studies is insufficient. Scientific improvements need to be made to feature reproducibility, analysis of clinical utility, and open science categories. Reporting of study objectives, blind assessment, sample size, and missing data is deemed to be necessary.

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