Published online Jun 15, 2023. doi: 10.4251/wjgo.v15.i6.1073
Peer-review started: March 9, 2023
First decision: March 22, 2023
Revised: April 2, 2023
Accepted: April 25, 2023
Article in press: April 25, 2023
Published online: June 15, 2023
Computed tomography (CT) imaging features are associated with risk stratification of gastric gastrointestinal stromal tumors (GISTs).
To determine the multi-slice CT imaging features for predicting risk stratification in patients with primary gastric GISTs.
The clinicopathological and CT imaging data for 147 patients with histologically confirmed primary gastric GISTs were retrospectively analyzed. All patients had received dynamic contrast-enhanced CT (CECT) followed by surgical resection. According to the modified National Institutes of Health criteria, 147 lesions were classified into the low malignant potential group (very low and low risk; 101 lesions) and high malignant potential group (medium and high-risk; 46 lesions). The association between malignant potential and CT characteristic features (including tumor location, size, growth pattern, contour, ulceration, cystic degeneration or necrosis, calcification within the tumor, lymphadenopathy, enhancement patterns, unenhanced CT and CECT attenuation value, and enhancement degree) was analyzed using univariate analysis. Multivariate logistic regression analysis was performed to identify significant predictors of high malignant potential. The receiver operating curve (ROC) was used to evaluate the predictive value of tumor size and the multi
There were 46 patients with high malignant potential and 101 with low-malignant potential gastric GISTs. Univariate analysis showed no significant differences in age, gender, tumor location, calcification, unenhanced CT and CECT attenuation values, and enhancement degree between the two groups (P > 0.05). However, a significant difference was observed in tumor size (3.14 ± 0.94 vs 6.63 ± 3.26 cm, P < 0.001) between the low-grade and high-grade groups. The univariate analysis further revealed that CT imaging features, including tumor contours, lesion growth patterns, ulceration, cystic degeneration or necrosis, lymphadenopathy, and contrast enhancement patterns, were associated with risk stratification (P < 0.05). According to binary logistic regression analysis, tumor size [P < 0.001; odds ratio (OR) = 26.448; 95% confidence interval (CI): 4.854-144.099)], contours (P = 0.028; OR = 7.750; 95%CI: 1.253-47.955), and mixed growth pattern (P = 0.046; OR = 4.740; 95%CI: 1.029-21.828) were independent predictors for risk stratification of gastric GISTs. ROC curve analysis for the multinomial logistic regression model and tumor size to differentiate high-malignant potential from low-malignant potential GISTs achieved a maximum area under the curve of 0.919 (95%CI: 0.863-0.975) and 0.940 (95%CI: 0.893-0.986), respectively. The tumor size cutoff value between the low and high malignant potential groups was 4.05 cm, and the sensitivity and specificity were 93.5% and 84.2%, respectively.
CT features, including tumor size, growth patterns, and lesion contours, were predictors of malignant potential for primary gastric GISTs.
Core Tip: Gastrointestinal stromal tumors (GISTs) are rare but are nevertheless the most common mesenchymal neoplasms of the gastrointestinal tract. GISTs are most frequently found in the stomach. Preoperative prediction of the malignant potential and prognosis of these GISTs is crucial for clinical decision-making. The present study identified the computed tomography (CT) imaging characteristics for predicting the malignancy risk stratification in 147 patients with primary gastric GISTs. We demonstrated that the qualitative and quantitative features of gastric GISTs on contrast-enhanced CT may be favorable for preoperative risk stratification. This may provide a simple yet effective tool for clinicians to make appropriate clinical decisions.