Computed Tomography-Based Radiomics Model to Preoperatively Predict Microsatellite Instability Status in Colorectal Cancer: A Multicenter Study - Li, Zhi; Zhong, Qi; Zhang, Liang; Wang, Minhong; Xiao, Wenbo; Cui, Feng; Yu, Fang; Huang, Chencui; Feng, Zhan (Frontiers in Oncology, 2021)
Objectives To establish and validate a combined radiomics model based on radiomics features and clinical characteristics, and to predict microsatellite instability (MSI) status in colorectal cancer (CRC) patients preoperatively. Methods A total of 368 patients from four hospitals, who underwent preoperative contrast-enhanced CT examination, were included in this study. The data of 226 patients, who were from a single hospital, were used as the training dataset. The data of 142 patients from the other three hospitals were used as an independent validation dataset. The regions of interest were drawn on the portal phase of contrast-enhanced CT images. The filtered radiomics features and clinical characteristicswere combined.A total of 15 different discrimination models were constructed based on a feature selection strategy from a pool of 3 feature selection methods and a classifier from a pool of 5 classification algorithms. The generalization capability of each model was evaluated in an external validation set. A model with a higher area under the curve(AUC) value from the training set and without a significant decrease during external validation was final selected. Results The logistic regression model using the mutual information(MI) dimensionality reduction method was final selected with an AUCvalue of 0.79 for the training set and 0.73 for the external validation set to predicting MSI. Conclusion The established combined radiomics model has the potential to predict MSI status in CRC patients preoperatively. Key Words ComputedTomography; Logistic regression; Microsatellite instability; Colorectal cancer