基于MRI表观扩散系数联合临床参数的列线图模型术前预测胃癌脉管浸润的价值OA

Objective To explore the value of a nomogram model based on MRI apparent diffusion coefficient(ADC)combined with clinical parameters for the noninvasive preoperative prediction of lymphovascular invasion(LVI)in gastric cancer.Methods Clinical and imaging data of 196 patients with surgically and pathologically confirmed gastric cancer were retrospectively collected,including age,sex,carcinoembryonic antigen(CEA),carbohydrate antigen 19-9(CA19-9),LVI status,American Joint Committee on Cancer(AJCC)stage,TNM stage,and Borrmann classification.Patients were randomly divided into a training set(136 cases)and a validation set(60 cases)at a ratio of 7∶3.According to pathological LVI status,the training set was further divided into an LVI-positive group(68 cases)and an LVI-negative group(68 cases).MRI images were analyzed in the picture archiving and communication system(PACS),and ADC parameters including minimum ADC value(ADCmin),mean ADC value(ADCmean),and maximum ADC value(ADCmax)were recorded.Relative ADC values(rADCmin,rADCmean,and rADCmax)were also calculated.Independent-samples t test,Mann-Whitney U test,Chi-square test,and Fisher's exact test were used to compare differences between the two groups.Variables with statistically significant differences were included in multivariate logistic regression analysis using the backward stepwise method to identify independent predictors of LVI and construct a nomogram model.The predictive performance of the model was evaluated using the area under the receiver operating characteristic curve(AUC).The Hosmer-Lemeshow test and calibration curves were used to assess goodness-of-fit and calibration of the model,and decision curve analysis(DCA)was used to evaluate the clinical utility of the model.Results Multivariate logistic regression analysis showed that CA19-9,AJCC stage,and ADCmin were independent predictors of LVI in gastric cancer(all P<0.05),and a nomogram prediction model was constructed based on these variables.ROC curve analysis showed that the nomogram model achieved good predictive performance for LVI in both the training and validation sets,with AUCs of 0.820 and 0.821,respectively.In the training set,the sensitivity,specificity,and accuracy of the model for predicting gastric cancer LVI were 61.8%,94.1%,and 77.9%,respectively.The calibration curves and Hosmer-Lemeshow test demonstrated good model fit.DCA confirmed that the model provided clinical net benefit across a wide range of threshold probabilities.Conclusion The nomogram prediction model based on CA19-9,AJCC stage,and ADCmin can accurately and noninvasively predict the risk of LVI in gastric cancer preoperatively and may provide a basis for individualized treatment decision-making.