The characteristics of multi-slice spiral CT images of gastrointestinal stromal tumors and their application value in risk assessment

WU Binbin; HUANG Jun; HU Xiang; JIANG Jun

doi:10.12122/j.issn.1674-4500.2025.10.09

Abstract：Objective To explore the application value of multi-slice spiral CT(MSCT)in the diagnosis and risk classification of gastrointestinal stromal tumor(GIST),and analyze image features of GISTs at different risk levels.Methods From January 2019 to December 2024,104 patients with GIST admitted to China Rongtong Medical and Health Group Co.,Ltd.Anqing 116 Hospital were selected.All of the patients underwent MSCT plain scan and multi-phase enhanced scan.With surgical and pathological results as the gold standard,cases at extremely low risk and low risk were included in the low-risk group,while those at intermediate risk and high risk were included in the high-risk group.The differences in MSCT features between the two groups,and the correlation between MSCT features and risk level were analyzed.The ROC curves were used to evaluate the predictive efficacy of MSCT features for high-risk GIST,and the predictive model was clinically validated.Results Multivariate logistic regression analysis identified tumor diameter,lesion morphology,growth pattern,and ulceration as independent influencing factors for risk stratification(P<0.05).A logistic regression model was constructed based on MSCT features,and ROC curve analysis results showed that the area under the curve of the model for evaluating the risk level of GIST was 0.951(P<0.001).The sensitivity and specificity were 94.74%and 84.85%,indicating higher diagnostic efficacy.The Hosmer Lemeshow goodness of fit test was used to evaluate the calibration of the risk grading diagnostic prediction model for GIST patients,and the results showed that the fitting level of the GIST patient risk grading diagnostic prediction model was good(P=0.675,adjusted R2=0.754).Clinical verification shows that the sensitivity of this prediction model was 100%,the specificity was 88.89%,and the accuracy was 92.31%.The consistency between the prediction model and the actual clinical situation was relatively high(Kappa=0.831).Conclusion MSCT can effectively help evaluate the risk level of GIST based on features such as tumor diameter,shape,growth pattern,and ulcer.Among them,tumor diameter>5 cm,irregular shape,transmural growth,and ulcer are independent imaging indicators for predicting high-risk GIST,which provides an important basis for preoperative risk assessment in clinical practice.