The clinical value of preoperative abdominal enhanced CT-based radiomics model for predicting Ki-67 expression level in esophagogastric junction adenocarcinoma
MA Changdong
GONG Yue
FANG Xueli
YU Shuang
MA Yan
MA Changsheng
WANG Shijiang
Abstract：Objective To investigate and improve the diagnostic performance of preoperative prediction of the Ki-67 expres-sion index using CT-based radiomics.Methods The imaging and clinicopathological data of 100 esophagogastric junction ad-enocarcinoma patients who had a Ki-67 measurement and contrast-enhanced CT scan of the abdomen were collected.According to the expression index of Ki-67,they were divided into high expression(60 cases)and low expression(40 cases).According to the ratio of 7∶3,the enrolled cases were randomly divided into the training set(70 cases)and the test set(30 cases).The univari-ate analysis was used to compare the clinical and pathological features of the high and low expression groups of Ki-67.Tumor ROIs were manually segmented on axial contrast-enhanced CT venous phase images(CE-CT).Radiomics features were extracted from axial contrast-enhanced CT venous phase images based on the training set.Then,we used 7 best radiomics features to devel-oped a radiomics signature and built a radiomics model to preoperatively predict Ki-67 expression level of the esophagogastric junction adenocarcinoma.The receiver operating characteristic curve(ROC)and area under the curve(AUC)were used to com-pare the performance of the model in the training set and the test set.The fit of the model was assessed using a calibration curve.The net benefit of the radiomics model was assessed using decision curve analysis(DCA).Results The univariate analysis showed that age,gender,CT-reported lymph node status,CEA,CA125,CA199,CA724 and the major location of the esopha-gogastric junction adenocarcinoma had no statistically significant difference between the high and low expression groups(P>0.05).A total of 7 radiomic features significantly correlated with Ki-67 levels were finally identified,and a radiomic prediction model for Ki-67 expression levels was constructed.The ROC curve showed that the AUC for preoperative prediction of Ki-67 ex-pression level with the radiomics model was 0.812 and 0.795 in the training and test sets,respectively.The calibration curve demonstrated a good fitting performance of the model,and the decision curve analysis indicated that the application of this ra-diomic model for predicting Ki-67 expression levels could yield favorable clinical benefits.Conclusion The efficiency of ab-dominal enhanced CT-based radiomics in predicting Ki-67 expression index in esophagogastric junction adenocarcinoma is ideal.
Keywords：TomographyX-ray computedRadiomicsEsophagogastric junction adenocarcinoma
Publication Date：2026-01-30
Online Publishing Date：2026-03-20(First online date of this platform, not the publication date of the document)
Pages：6( 81-86 )