Background: Advanced low rectal cancer has a non-negligible risk of lateral pelvic lymph node (LPLN) metastasis (LPLNM) and lateral local recurrence (LR) after neoadjuvant (chemo)radiotherapy and total mesorectal excision. LPLN dissection (LPLND) reduces LR but increases postoperative complications and sexual/urinary dysfunction. Objective: The aim of this study was to develop a new radiomics-based prediction model for LPLNM in patients with rectal cancer. Methods: A total of 247 patients with rectal cancer and enlarged LPLNs treated by (chemo)radiotherapy and LPLND were enrolled in this retrospective, multicenter study. LPLN radiomic features were extracted from pretreatment portal venous-phase computed tomography images. A radiomics score of LPLN was constructed based on the least absolute shrinkage and selection operator regression in a primary cohort of 175 patients. Model performance was assessed in terms of discrimination, calibration, and decision curve analysis, and was externally validated in 72 patients. Results: The radiomics score showed significantly better discrimination compared with pretreatment short-axis diameter measurements in both the primary (area under the curve [AUC] 0.91 vs. 0.83, p = 0.0015) and validation (AUC 0.90 vs. 0.80, p = 0.0298) cohorts. Decision curve analysis also indicated the superiority of the radiomics score. In a subanalysis of patients with a short-axis diameter ≥ 7 mm, the radiomics nomogram, incorporating the radiomics score and LPLN shrinkage to ≤ 4 mm, had better discrimination compared with a model incorporating only LPLN shrinkage in both cohorts. Conclusions: Radiomics-based prediction modeling provides individualized risk estimation of LPLNM in rectal cancer patients treated with (chemo)radiotherapy, and outperforms measurements of pretreatment LPLN diameter.
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