光谱CT多参数预测结直肠癌神经侵犯的价值OA

Objective To evaluate the clinical value of dual-layer detector spectral CT multi-parameters in predicting perineural invasion(PNI)in colorectal cancer(CRC).Methods A total of 103 patients with pathologically confirmed CRC who underwent abdominal contrast-enhanced scanning using dual-layer detector spectral CT at the First Affiliated Hospital of Zhejiang Chinese Medical University(Zhejiang Provincial Hospital of Traditional Chinese Medicine)from March 2024 to April 2025 were retrospectively enrolled.Based on PNI status,patients were divided into PNI-positive[PNI(+)](n=59)and PNI-negative[(PNI(-)](n=44)groups.CT values for monoenergetic images at 40,70,and 90 keV(CT40keV,CT70keV,CT90keV),iodine concentration(IC),effective atomic number(Zeff),electron density,and CT values of the large artery at the same level were measured in arterial and venous phases.Normalized IC(NIC)and spectral curve slope(λHu)were calculated.Spectral parameters were compared between the PNI(+)and PNI(-)groups.Binary logistic regression analysis was then used to identify independent predictors of PNI in CRC so as to construct a multi-parameter spectral prediction model.ROC curves were plotted to evaluate the diagnostic performance of individual parameters and the combined model for PNI.Results Statistically significant differences were observed between the PNI(+)and PNI(-)groups in arterial phase parameters including IC,NIC,Zeff,λHu,CT40keV,and CT70keV,as well as in venous phase parameters including IC,NIC,λHu,CT40keV,and CT90keV(all P＜0.05).Binary logistic regression analysis showed that arterial phase λHu,venous phase IC,and venous phase NIC were independent predictors of PNI in CRC(all P＜0.05).The AUC values for these individual parameters in predicting CRC PNI were 0.731,0.614,and 0.550,respectively.The combined model constructed using these parameters achieved a sensitivity of 0.804,specificity of 0.795,and an AUC of 0.845 for diagnosing PNI in CRC.Conclusion Dual-layer spectral CT multi-parameter analysis can predict PNI in CRC preoperatively,providing a novel approach for preoperative assessment.