Clinical trial · Observational
DeepComp for Prediction of Gastric Cancer Postoperative Complications (DeepComp-Prospective)
A Prospective, Multicenter, Observational Study Validating the Multimodal Deep Learning Radiomics Model (DeepComp) for Preoperative Prediction of Major Postoperative Complications in Patients With Gastric Cancer
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Gastric cancer is a leading cause of cancer-related mortality, and radical surgery remains the primary treatment. However, postoperative complications are common and can significantly impact patient recovery and quality of life. Currently, doctors lack precise tools to accurately predict which patients are at high risk for developing severe complications before surgery. This study aims to validate a novel artificial intelligence (AI) model called "DeepComp." The DeepComp model integrates clinical data with advanced radiomic features derived from routine preoperative CT scans. Specifically, it analyzes both the tumor characteristics and the patient's body composition (including skeletal muscle and fat distribution) to assess physiological reserve. In this prospective, multicenter observational study, researchers will enroll patients scheduled for gastric cancer surgery across five medical centers. The DeepComp model will be used to predict the risk of moderate-to-severe postoperative complications (Clavien-Dindo grade II or higher). These predictions will then be compared with the actual clinical outcomes observed 30 days after surgery. The goal is to determine the accuracy and reliability of the DeepComp model in a real-world clinical setting, potentially providing a powerful tool for personalized surgical risk assessment.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Gastric Cancer (Diagnosis) | Malignant Gastric Neoplasm | CURATED_BROADER | 0.80 |
| Postoperative Complications | — | UNRESOLVED | — |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (1)
- label
- Gastric Cancer Surgery Cohort
- description
- Patients diagnosed with gastric cancer who are scheduled to undergo radical gastrectomy (open, laparoscopic, or robotic). All participants will receive standard preoperative contrast-enhanced CT scans. The DeepComp AI model will be applied to these scans to predict the risk of postoperative complications.
Primary outcomes (2)
- measure
- Incidence of Major Postoperative Complications (Clavien-Dindo Grade ≥ II)
- timeFrame
- Postoperative 30 days
- description
- Postoperative complications will be graded according to the Clavien-Dindo classification system. Major complications are defined as Grade II or higher, which require pharmacological treatment, surgical/endoscopic/radiological intervention, or life-threatening complications (including death). The occurrence of these events will be recorded and compared with the model's preoperative predictions.
- measure
- Human-AI Collaborative Diagnostic Performance in Gastric Cancer Surgery: Accuracy and Observer Agreement
- timeFrame
- From preoperative assessment through 30 days post-surgery
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 85 Years
Show eligibility criteria text
Inclusion Criteria: Age ≥ 18 years. Histologically confirmed gastric adenocarcinoma. Scheduled for elective radical gastrectomy (open, laparoscopic, or robotic) with curative intent. Standard preoperative contrast-enhanced abdominal CT scans (venous phase) performed within 14 days prior to surgery. Willingness to sign informed consent. Exclusion Criteria: Emergency surgery due to perforation, obstruction, or massive bleeding. Intraoperative findings of distant metastasis (Stage IV) or unresectable disease preventing R0 resection. Concurrent or previous malignant tumors within the last 5 years (except gastric cancer). Pregnancy or lactation. Severe metallic artifacts on CT images preventing radiomic analysis.
References
Publications (0)
Data not yet available