Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Mar;33(3):1884-1894.
doi: 10.1007/s00330-022-09187-3. Epub 2022 Oct 25.

Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative

Gaia Spadarella  1 , Arnaldo Stanzione  2 , Tugba Akinci D'Antonoli  3 , Anna Andreychenko  4 , Salvatore Claudio Fanni  5 , Lorenzo Ugga  1 , Elmar Kotter  6 , Renato Cuocolo  7   8
Affiliations

Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative

Gaia Spadarella et al. Eur Radiol. 2023 Mar.

Abstract

Objective: The main aim of the present systematic review was a comprehensive overview of the Radiomics Quality Score (RQS)-based systematic reviews to highlight common issues and challenges of radiomics research application and evaluate the relationship between RQS and review features.

Methods: The literature search was performed on multiple medical literature archives according to PRISMA guidelines for systematic reviews that reported radiomic quality assessment through the RQS. Reported scores were converted to a 0-100% scale. The Mann-Whitney and Kruskal-Wallis tests were used to compare RQS scores and review features.

Results: The literature research yielded 345 articles, from which 44 systematic reviews were finally included in the analysis. Overall, the median of RQS was 21.00% (IQR = 11.50). No significant differences of RQS were observed in subgroup analyses according to targets (oncological/not oncological target, neuroradiology/body imaging focus and one imaging technique/more than one imaging technique, characterization/prognosis/detection/other).

Conclusions: Our review did not reveal a significant difference of quality of radiomic articles reported in systematic reviews, divided in different subgroups. Furthermore, low overall methodological quality of radiomics research was found independent of specific application domains. While the RQS can serve as a reference tool to improve future study designs, future research should also be aimed at improving its reliability and developing new tools to meet an ever-evolving research space.

Key points: • Radiomics is a promising high-throughput method that may generate novel imaging biomarkers to improve clinical decision-making process, but it is an inherently complex analysis and often lacks reproducibility and generalizability. • The Radiomics Quality Score serves a necessary role as the de facto reference tool for assessing radiomics studies. • External auditing of radiomics studies, in addition to the standard peer-review process, is valuable to highlight common limitations and provide insights to improve future study designs and practical applicability of the radiomics models.

Keywords: Big data; Diagnostic imaging; Radiomics; Radiomics quality score; Systematic review.

PubMed Disclaimer

Conflict of interest statement

Renato Cuocolo serves as an editorial board member of European Radiology and European Radiology Experimental.

Figures

Fig. 1
Fig. 1
The literature research flow diagram. Adapted from: The PRISMA 2020 statement: an updated guideline for reporting systematic reviews [19]
Fig. 2
Fig. 2
Bar plot reporting the mean RQS percentage score by year of publication
Fig. 3
Fig. 3
Mean of RQS percentage score of each review included in this study
Fig. 4
Fig. 4
RQS percentage score for different review subgroups
Fig. 5
Fig. 5
Box plot depicting the distribution of RQS percentage score by aim of the studies included in the systematic reviews
See this image and copyright information in PMC

References

    1. Pinto dos Santos D, Dietzel M, Baessler B. A decade of radiomics research: are images really data or just patterns in the noise? Eur Radiol. 2021;31:1–4. doi: 10.1007/s00330-020-07108-w. - DOI - PMC - PubMed
    1. Song J, Yin Y, Wang H, et al. A review of original articles published in the emerging field of radiomics. Eur J Radiol. 2020;127:108991. doi: 10.1016/j.ejrad.2020.108991. - DOI - PubMed
    1. Bera K, Braman N, Gupta A, et al. Predicting cancer outcomes with radiomics and artificial intelligence in radiology. Nat Rev Clin Oncol. 2022;19:132–146. doi: 10.1038/s41571-021-00560-7. - DOI - PMC - PubMed
    1. La Greca S-EA, Vuong D, Tschanz F, et al. Systematic review on the association of radiomics with tumor biological endpoints. Cancers (Basel) 2021;13:3015. doi: 10.3390/cancers13123015. - DOI - PMC - PubMed
    1. Qi Y, Zhao T, Han M (2022) The application of radiomics in predicting gene mutations in cancer. Eur Radiol. 10.1007/s00330-021-08520-6 - PubMed

Publication types