Radiomics for predicting perineural invasion status in rectal cancer
Mou Li, Yumei Jin, Yongchang Zhang, Yali Zhao, Chencui Huang, Shengmei Liu, Bin Song
Abstract
BACKGROUND: Perineural invasion (PNI), as a key pathological feature of tumor spread, has emerged as an independent prognostic factor in patients with rectal cancer (RC). The preoperative stratification of RC patients according to PNI status is beneficial for individualized treatment and improved prognosis. However, the preoperative evaluation of PNI status is still challenging. AIM: To establish a radiomics model for evaluating PNI status preoperatively in RC patients. METHODS: = 14) methods to form 84 classifiers. The best performing classifier was then selected to establish Rad-score. Finally, the clinicoradiological model (combined model) was developed by combining Rad-score with clinical factors. These models for predicting PNI were compared using receiver operating characteristic curve (ROC) analysis and area under the ROC curve (AUC). RESULTS: = 0.045 in the validation cohort). CONCLUSION: The combined model incorporating Rad-score and clinical factors can provide an individualized evaluation of PNI status and help clinicians guide individualized treatment of RC patients.