Predictive value of combined DCE-MRI perfusion parameters and clinical features nomogram for microsatellite instability in colorectal cancer.

OBJECTIVES

To develop a nomogram that combines dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion parameters, ADC values and clinical features to preoperatively identify microsatellite instability (MSI) in patients with colorectal cancer (CRC).

METHODS

This retrospective study included 63 CRC patients who underwent preoperative DCE-MRI and had immunohistochemistry results available. Two radiologists, in a double-blind manner, placed two circular regions of interests in the area with the highest perfusion intensity on the DCE-MRI perfusion map and the corresponding area on the ADC map. Perfusion parameters and ADC values were measured, and the average values from both radiologists were used for subsequent analysis. Univariate analysis was performed to identify independent risk factors for MSI. A nomogram was then constructed by combining the most significant clinical risk factors with DCE-MRI perfusion parameters. The model's performance was evaluated using receiver operating characteristic (ROC) curves. Calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC) were used to assess the nomogram's clinical utility and net benefit.

RESULTS

The nomogram prediction model, which combined PLT, LNM, K, K, iAUC, and ADC, demonstrated good predictive performance. The combined model had an AUC of 0.951 (95% CI: 0.903-0.998), an accuracy of 0.873, a sensitivity of 1.000, and a specificity of 0.818. Both the DCA and CIC demonstrated good clinical applicability and net benefit.

CONCLUSION

The nomogram method demonstrated good potential in the preoperative individualized identification of MSI status in CRC patients. This tool can assist clinicians in adopting appropriate treatment strategies and optimizing personalized stratification for CRC patients.