Prostate cancer MRI methodological radiomics score: a EuSoMII radiomics auditing group initiative

Objectives

To evaluate the quality of radiomics research in prostate MRI for the evaluation of prostate cancer (PCa) through the assessment of METhodological RadiomICs (METRICS) score, a new scoring tool recently introduced with the goal of fostering further improvement in radiomics and machine learning methodology.

Materials and methods

A literature search was conducted from July 1st, 2019, to November 30th, 2023, to identify original investigations assessing MRI-based radiomics in the setting of PCa. Seven readers with varying expertise underwent a quality assessment using METRICS. Subgroup analyses were performed to assess whether the quality score varied according to papers’ categories (diagnosis, staging, prognosis, technical) and quality ratings among these latter.

Results

From a total of 1106 records, 185 manuscripts were available. Overall, the average METRICS total score was 52% ± 16%. ANOVA and chi-square tests revealed no statistically significant differences between subgroups. Items with the lowest positive scores were adherence to guidelines/checklists (4.9%), handling of confounding factors (14.1%), external testing (15.1%), and the availability of data (15.7%), code (4.3%), and models (1.6%). Conversely, most studies clearly defined patient selection criteria (86.5%), employed a high-quality reference standard (89.2%), and utilized a well-described (85.9%) and clinically applicable (87%) imaging protocol as a radiomics data source.

Conclusion

The quality of MRI-based radiomics research for PCa in recent studies demonstrated good homogeneity and overall moderate quality.

Key Points

Question To evaluate the quality of MRI-based radiomics research for PCa, assessed through the METRICS score.

Findings The average METRICS total score was 52%, reflecting moderate quality in MRI-based radiomics research for PCa, with no statistically significant differences between subgroups.

Clinical relevance Enhancing the quality of radiomics research can improve diagnostic accuracy for PCa, leading to better patient outcomes and more informed clinical decision-making.