Diagnostic Accuracy of MRI Radiomics for Predicting KRAS Mutation in Rectal Cancer: A Systematic Review and Meta-analysis

Abstract Background KRAS mutation status is an important biomarker in rectal cancer, with implications for prognosis and treatment response. MRI-based radiomics has emerged as a non-invasive approach for predicting tumor genotypes. However, the diagnostic performance of MRI radiomics for predicting KRAS mutation status remains unclear. This study aimed to evaluate the diagnostic accuracy of MRI radiomics for predicting KRAS mutations in rectal cancer. Methods A systematic search of PubMed, Cochrane Library, Scopus, and Web of Science was performed through July 2025. Diagnostic test accuracy studies evaluating MRI-based radiomics or artificial intelligence models for predicting KRAS mutation status in adult patients with rectal cancer were included, using molecular testing as the reference standard. Risk of bias was assessed using the QUADAS-2 tool. Pooled sensitivity and specificity were estimated using a bivariate random-effects model. Results Seven studies involving 1,224 patients were included. The pooled sensitivity was 0.736 (95% CI: 0.697–0.772) and the pooled specificity was 0.645 (95% CI: 0.586–0.701). The false positive rate was 0.355 (95% CI: 0.299–0.414). The area under the hierarchical summary receiver operating characteristic curve was 0.754, with a normalized partial AUC of 0.666. Between-study heterogeneity ranged from low to moderate depending on the estimation method (I² = 8.4%–53.3%). Conclusion MRI radiomics demonstrates moderate diagnostic accuracy for predicting KRAS mutation status in rectal cancer and may serve as a promising non-invasive biomarker for preoperative molecular stratification. Further large-scale studies with external validation are required to confirm its clinical utility. Key points and Clinical relevance statement Question Can MRI radiomics noninvasively predict Kirsten rat sarcoma(KRAS) viral oncogene homolog mutation status in rectal cancer before treatment planning? Findings In seven studies including 1,224 patients, MRI radiomics showed moderate accuracy for mutation prediction, with 0.74 sensitivity and 0.65 specificity. Clinical Relevance Statement Preoperative MRI radiomics offers a noninvasive complement to tissue testing for molecular stratification in rectal cancer, supporting treatment planning and reducing the risk of underrepresenting whole-tumor heterogeneity.