Using the MRI-ADC and clinicopathological feature nomogram to Predict microsatellite instability status in colorectal carcinomas

Motivation: Given that microsatellite instability (MSI) detection often involves invasive pathological biopsies, it is of paramount importance to find a non-invasive, individualized detection technology for accurately and effectively predicting the MSI status of colorectal cancer (CRC) patients prior to surgery. This approach could mitigate the limitations associated with biopsies and enhance the treatment of CRC patients. Goal(s): To investigate the value of MRI-ADC mean values and clinicopathological features in predicting MSI in colorectal cancer. Approach: The ADC model and ADC-clinicopathologic nomogram model were established by using MRI-ADC parameters and clinicopathological features. Results: The combined ADC-clinicopathological nomogram model was the best predictor of CRC MSI. Impact: Pathological testing for MSI status is often invasive and comes with a higher risk of complications. In contrast, the ADC-clinical combined nomogram model provides a noninvasive, comprehensive tool for preoperative prediction of CRC MSI and for guiding clinical treatment decisions.