Exploring radiomics research quality scoring tools: a comparative analysis of METRICS and RQS
Burak Koçak, Tugba Akinci D’Antonoli, Renato Cuocolo
Abstract
adiomics facilitates the extraction of vast quantities of quantitative data from medical images, which can substantially aid in several diagnostic and prognostic tasks. 1 Although numerous studies have demonstrated promising results with this approach, its integration into clinical practice remains limited, necessitating additional validation for clinical application. 2A major barrier to this integration is the lack of standardization of key stages in the complex multi-step radiomic pipeline, 3 which could be assessed and enhanced through structured guidelines and quality assessment tools. [4][6][7] In 2017, Lambin et al. 8 introduced the radiomics quality score (RQS) as a methodological assessment tool to enhance the quality of radiomics studies.The RQS comprises 16 items that evaluate the entire lifecycle of radiomics research, with a total raw score ranging from -8 to +36.Although the rationale for the scores assigned to each item remains unclear, the radiomics research community has widely adopted this tool since its introduction, leading to numerous systematic reviews. 9The success of the RQS within the research community also signifies a strong desire for standardization in radiomics, despite its limitations.