Abstract
The preoperative differentiation of small gastric gastrointestinal stromal tumors (GISTs) from other submucosal lesions remains clinically challenging due to overlapping endoscopic ultrasound (EUS) features. This study aimed to develop and validate a novel risk-scoring system integrating EUS imaging and clinical characteristics to improve preoperative diagnostic accuracy for small gastric GISTs versus non-GIST submucosal tumors. We retrospectively analyzed 1303 patients with gastric submucosal tumors (SMTs), who were divided into a training cohort (n = 670), an internal validation cohort (n = 287), and an external validation cohort (n = 346). Clinical and EUS characteristics were compared between small GISTs and non-GIST SMTs. Independent predictive factors identified through multivariate logistic regression were used to construct a risk-scoring model. The model’s diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive and negative predictive values (PPV, NPV), and accuracy. Small gastric GISTs accounted for 614 cases (47.1%). Four independent predictors were identified: tumor location in the cardia/fundus (1 points), origin within the muscularis propria (2 points), hypoechoic echogenicity (1 point), and extraluminal growth pattern (2 points). The scoring system demonstrated strong discriminatory power, with AUCs of 0.776 (95%CI: 0.727–0.826) in the internal and 0.844 (95%CI: 0.805–0.884) in the external validation cohorts. Sensitivities were 0.867 (95%CI: 0.800–0.918) and 0.828 (95%CI: 0.767–0.878), and NPVs were 0.827 and 0.785, respectively. Risk stratification revealed that in the internal cohort, 17.3% of lesions were low-risk (0–2 points), 52.8% intermediate-risk (3–4 points), and 96.2% high-risk (5–6 points). Corresponding proportions in the external cohort were 21.5%, 73.9%, and 95.0%. The proposed EUS-based risk-scoring system shows robust performance in preoperatively diagnosing small gastric GISTs. It holds promise for improving clinical decision-making and optimizing treatment strategies by enabling non-invasive and accurate risk stratification.
Data availability
Data availability can be requested from the corresponding author with a reasonable justification.
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Funding
This study was supported by the Changshu Science and Technology Program (CY202339), the Suzhou Youth Science and Technology Project for the Advancement of Science, Education, and Health (KJXW2023067), Specialized Project for Clinical Key Disease Diagnosis and Treatment Technology in Suzhou (LCZX202334), and the Suzhou 23rd Batch of Science and Technology Development Plan (Clinical Trial Institution Capability Enhancement) Project (SLT 2023006).
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Conception and design: Luojie Liu, Ying Shi, and Jian Chen. Administrative support: Xiaodan Xu. Provision of study materials or patients: Yunfu Feng, Sijie Zheng, Bin He, Chao Ma, and Zhibing Wang. Collection and assembly of data: Yunfu Feng, Bin He, Zhibing Wang, and Luojie Liu. Data analysis and interpretation: Yunfu Feng and Luojie Liu. Manuscript writing: All authors. Final approval of manuscript: All authors.
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The research protocol received ethical approval from the Institutional Review Board of Changshu Hospital Affiliated to Soochow University (Approval No: L2025055), which served as the central ethics committee for this multi-center study, with additional approvals obtained from the local ethics committees of all other participating institutions. Written informed consent was obtained from all participants.
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Liu, L., Feng, Y., Zheng, S. et al. A novel risk-scoring system based on endoscopic ultrasound and clinical characteristics for the preoperative diagnosis of small gastric gastrointestinal stromal tumors. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41599-9
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DOI: https://doi.org/10.1038/s41598-026-41599-9
