Quant Imaging Med Surg. 2025 Oct 01. 15(10): 9600-9612
Background: Colorectal cancer (CRC) is among the most prevalent malignant neoplasms within the digestive system. Perineural invasion (PNI) is a significant predictor of CRC prognosis, thus the crucial need to predict PNI status prior to surgical intervention. The aim of this study was to explore the efficacy of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in predicting PNI status prior to surgery in CRC patients.
Methods: This study involved the retrospective collection of 18F-FDG PET/CT data from 116 CRC patients who received treatment at our facility between January 2016 and July 2024. All patients, including 50 in the PNI group and 66 in the non-PNI group, had a surgical pathological diagnosis of PNI. The primary CRC lesions were identified and their parameters calculated using LIFEx software. A peritumoral adipose tissue (PAT) grade was established by assessing the horizontal, vertical, and severity of PAT on CT images. Variables with statistically significant differences between groups were identified by univariate analysis, and independent risk factors for predicting PNI were obtained using multivariate logistic regression analysis. A nomogram model was then established. Each parameter's predictive efficiency was assessed using receiver operating characteristic (ROC) curve analysis, and the nomogram model's accuracy and clinical value were evaluated using calibration curves and decision curve analysis (DCA).
Results: According to univariate analysis, the PNI group and the non-PNI group differed statistically significantly in the metabolic tumor volume (MTV) 40% (P=0.027), the total lesion glycolysis (TLG) 40% (P=0.027), TLG60% (P=0.033), the coefficients of variation (CV) (P<0.001), the heterogeneity index (HF) (P=0.021), PAT grade (P=0.002), cN stage (P<0.001), and cM stage (P=0.016). The results of the multivariate logistic regression analysis identified the following variables as independent risk factors for predicting PNI: CV [odds ratio (OR) =3.128, 95% confidence interval (CI): 1.476-6.628, P=0.003], PAT grade (PAT grade 2: OR =12.016, 95% CI: 2.859-50.509, P<0.001; PAT grade 3: OR =22.417, 95% CI: 4.291-117.104, P<0.001), and cN stage (OR =4.769, 95% CI: 1.636-13.900, P=0.004). The ROC curve indicated an area under the curve (AUC) value of 0.893 (95% CI: 0.837-0.949) for the nomogram model. The internal validation concordance index (C-index) was found to be 0.861. Calibration curves and DCA demonstrated that the nomogram model exhibited both good accuracy and clinical utility.
Conclusions: 18F-FDG PET/CT demonstrated predictive value for PNI in CRC. Additionally, the CV, PAT grade, and cN stage were identified as independent risk factors for PNI. The nomogram model exhibited strong predictive performance.
Keywords: Colorectal cancer (CRC); nomogram; perineural invasion (PNI); positron emission tomography/computed tomography (PET/CT); prediction