The value of whole-volume ADC histogram analysis combined with ADC value in preoperatively prediction of tumor deposits in rectal cancer
Objective:To explore the value of tumoral whole-volume apparent diffusion coefficient(ADC)histogram parameters combined with ADC value in preoperative prediction of tumor deposits(TDs)in rectal cancer.Materials and Methods:The clinical and radiological data of 111 patients with pathologically confirmed rectal cancer who underwent preoperative rectal MRI examinations from June 2016 to June 2023 were retrospectively analyzed.The patients were grouped as TDs-positive group(n=30)and TDs-negative group(n=81)according to the pathological results.ROI was manually delineated on each slice of the tumor on the ADC images and histogram parameterswere obtained,including the ADC10%,ADC90%,maximum value(ADCmax),minimum value(ADCmin),mean value(ADCmean),median value(ADCmedian),kurtosis,and skewness.And the ADC value of the largest level of the tumor was measured.The differences in ADC value and ADC histogram parameters between the two groups were compared.A combined model was constructed based on factors with statistically significant differences using multivariate logistic regression analysis.Receiver operating characteristic curve(ROC)analysis was used to analyze the predictive performance of ADC value,whole-volume ADC histogram parameters,and the combined model.DeLong test was used to compare the differences of AUCs.Results:The ADC value,ADC10%,ADC90%,ADCmax,ADCmean,ADCmedian,and kurtosis were statistically different between the TDs-positive and TDs-negative groups(P<0.05).ADC90%had the highest predictive performance with an AUC of 0.778(sensitivity,80.0%;specificity,65.4%).The diagnostic performance of the combined model(AUC,0.940;sensitivity,86.7%;specificity,93.8%)was superior to that of ADC value alone(AUC,0.645)and whole-volume ADC histogram parameters(AUC ranging from 0.649 to 0.778)(P<0.05).Conclusions:Whole-volume ADC histogram parameters and the ADC value of the largest level of tumor can be used for preoperative prediction of TDs in rectal cancer,and the combined model can improve the predictive performance.
国家科技期刊平台
NSTL
万方数据
维普
