Diagnostic Performance of Preoperative Imaging-based Radiomics Models for Predicting Liver Metastases in Colorectal Cancer: A Systematic Review and Meta-analysis.

RATIONALE AND

OBJECTIVES

To evaluate the diagnostic performance of preoperative computed tomography (CT) and magnetic resonance imaging (MRI)-based radiomics models in detecting liver metastases in patients with colorectal cancer (CRC).

MATERIALS AND

METHODS

Following PRISMA 2020 guidelines, we systematically searched major databases up to July 2025. Study selection, data extraction, and quality assessment (Radiomics Quality Score and QUADAS-2) were performed independently. Separate bivariate random-effects meta-analyses were conducted for prognostic (metachronous) and diagnostic (synchronous) predictions.

RESULTS

Twenty studies (3765 patients) were included in the systematic review. Twenty studies were included in the systematic review. Of these, 18 studies were included in the quantitative meta-analysis. For predicting metachronous metastases (13 studies), the pooled AUC was 0.83 (95% CI: 0.73-0.90), although significant publication bias suggested that this estimate may be optimistically inflated. For the detection of synchronous metastases (five studies), the pooled AUC was 0.85 (95% CI: 0.76-0.91). Heterogeneity was moderate to substantial. However, significant publication bias was detected for prognostic models (Deeks' test, P < 0.001), suggesting that these pooled estimates may be optimistically inflated.

CONCLUSION

Radiomics has the potential to predict metachronous and detect synchronous liver metastases in CRC. However, methodological weaknesses (mean Radiomics Quality Score ∼48%), geographic bias, and publication bias limit this evidence. Multinational validation is required before clinical application of the findings.