Background and Rationale
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Gastric cancer (GC) remains a leading cause of cancer-related mortality in Europe, primarily due to late-stage diagnosis. While organized colorectal cancer (CRC) screening programs are well established, no structured gastric cancer screening strategy exists in
most European countries, particularly in intermediate-risk regions such as Portugal and Spain. As demonstrated in previous European initiatives, this gap results in missed opportunities for early detection of premalignant lesions and curable early cancers.
Conventional esophagogastroduodenoscopy (cEGD) is the diagnostic gold standard but is poorly suited for population screening due to its reliance on sedation, need for recovery facilities, increased costs, and limited patient acceptance. In contrast, new-generation ultrathin transnasal endoscopy (TNE) enables high-definition, unsedated gastric examination, with excellent safety, rapid throughput, and immediate return to normal activities. Despite widespread use in Asia, TNE has not yet been evaluated at scale as a gastric cancer screening tool in European populations.
Parallel advances in artificial intelligence (AI) offer an unprecedented opportunity to improve screening performance and efficiency. AI-based image analysis can enhance detection of subtle mucosal abnormalities, reduce interobserver variability, and provide
objective quality control. Moreover, integrating AI with clinical, demographic, and endoscopic data enables data-driven optimization of screening strategies, supporting risk-stratified and cost-effective population programs.
The VISTA trial builds directly on the epidemiological rationale, operational experience, and AI vision established in prior European translational screening initiatives. It aims to evaluate two complementary, scalable gastric cancer screening pathways within existing
healthcare infrastructures, generating high-quality evidence to inform future EU screening policies.
Primary Objectives
To evaluate the feasibility, diagnostic yield, and safety of large-scale gastric cancer screening using transnasal endoscopy compared with opportunistic conventional gastroscopy within colorectal cancer screening programs (current benchmark).
Secondary Objectives
To estimate the prevalence of gastric cancer and premalignant gastric lesions (atrophy, intestinal metaplasia, dysplasia) detected by each screening strategy.
• To assess patient tolerance, acceptability, and procedural burden of transnasal endoscopy.
• To develop and validate AI models for:
- Automated gastric image analysis and lesion detection
- Quality assessment of mucosal inspection
- Screening optimization using integrated clinical, demographic, and endoscopic data
• To generate epidemiological data supporting evidence-based gastric cancer screening strategies in intermediate-risk European populations.