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Recruiting NCT07354295

Integrating Multimodal AI to Predict Treatment Response and Refine Risk Stratification in Esophageal Cancer (Radiogenomics-Esophagus)

Trial Parameters

Condition Esophageal Cancer
Sponsor Shu Peng
Study Type OBSERVATIONAL
Phase N/A
Enrollment 1,500
Sex ALL
Min Age N/A
Max Age N/A
Start Date 2025-07-26
Completion 2030-09-30

Brief Summary

This AI-driven model leverages multimodal data-such as radiomics, pathomics, genomics, and broader multi-omics profiles-to capture complementary aspects of tumor biology and predict treatment response and prognosis.

Eligibility Criteria

Inclusion Criteria: 1. Histopathologically diagnosed esophageal cancer 2. Complete baseline clinical data available (including demographic characteristics, ECOG performance score, TNM staging, etc.) 3. No other primary malignant tumors 4. Provision of informed consent 5. Availability of pre-treatment CT imaging Exclusion Criteria: 1. Imaging data quality insufficient for analysis 2. Presence of another primary malignant tumor 3. Severe systemic disease

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