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Imaging characteristics and discrimination model development for early gastric cancer using multi-spectral CT
Wei-Na Jing1,2, Xiao-Cun Xing1,2, Fei-Fan Chen1,2
1Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University, 37 Guoxue Lane, Chengdu, 610041, Sichuan, China.
Surgical Endoscopy
|June 16, 2026
Summary
Multi-spectral CT (MSCT) shows promise for early gastric cancer (EGC) detection. A new model integrating MSCT imaging parameters significantly improves EGC identification, offering a valuable tool for clinical diagnosis.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Early detection of gastric cancer is crucial for patient survival.
- Endoscopy with biopsy is the current standard but is invasive.
- Computed tomography (CT) has limitations in detecting early gastric cancer (EGC).
Purpose of the Study:
- To identify characteristic imaging indicators of EGC using multi-spectral CT (MSCT).
- To develop and validate a diagnostic model for EGC based on MSCT findings.
Main Methods:
- Retrospective analysis of MSCT data from 141 patients with 144 lesions.
- Utilized receiver operating characteristic analysis and LASSO regression for model construction.
- External validation of the model using data from 51 EGC patients.
Main Results:
- MSCT showed significantly higher CT and effective atomic number (Effective-Z) values in EGC lesions compared to normal mucosa.
- Individual imaging parameters had limited discrimination efficacy.
- A multivariate model integrating multiple parameters achieved an AUC > 0.90 in all validation sets.
Conclusions:
- MSCT offers significant advantages for evaluating EGC.
- An integrated imaging parameter model can effectively enhance EGC discrimination.
- This approach provides a new reference for clinical practice in EGC diagnosis.
