Development and Application of AI-Based Therapeutic Strategies for Esophageal Cancer Integrating Multimodal Imaging and Digital Pathology

The purpose of this clinical study is to conduct a multi-center, big data study to create a neural network decision model for predicting treatment efficacy and prognosis based on multi-modal, multi-temporal imaging features combined with tumor microenvironment scores. It will also use various model interpretation techniques to clarify the role and mechanism of key biomarkers or strongly associated biomarker groups in treatment efficacy and prognosis. Ultimately, it aims to achieve the research and application of AI treatment strategies combining multi-modal imaging and digital pathology to guide clinicians in the personalized treatment strategies for patients with esophageal squamous cell carcinoma.

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Key information

Conditions

Esophageal Cancer Digestive System Diseases Digestive System Neoplasms Esophageal Diseases Esophageal Neoplasms Gastrointestinal Diseases Gastrointestinal Neoplasms Head and Neck Neoplasms Neoadjuvant Therapy Neoplasms Neoplasms by Site

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Aged 18-70 years;
Histologically confirmed esophageal carcinoma by biopsy;
No prior antitumor therapy received.

Exclusion criteria

Contraindications to MRI examination;
Poor compliance with antitumor therapy;
Unwillingness to participate in the study;
Image quality inadequate for diagnostic requirements.

Treatment and study plan

Primary outcomes

Pathological Complete Response (pCR) Rate

Time frame: January 2025 - December 2027

The proportion of patients achieving pathological complete response (ypT0 ypN0) after neoadjuvant therapy.
Overall Survival (OS)

Time frame: January 2025 - December 2027

The time from treatment initiation to death from any cause.
Event-Free Survival (EFS)

Time frame: January 2025 - December 2027

The time from treatment initiation to disease progression, recurrence, new primary cancer, or death.
Disease-Free Survival (DFS)

Time frame: January 2025 - December 2027

The time from curative-intent surgery to disease recurrence or death.

Study contacts

Contact information is provided by the study sponsor or research team.

Jinrong Qu

CONTACT

[email protected]

(86) 0371-65587595

Sponsors and collaborators

Lead sponsor

Henan Cancer Hospital

Other Gov

Collaborators

Guangdong Provincial People's Hospital
Xinyang Central Hospital

Registry information

Important dates

Study start: 2025
Primary completion: 2027
Study completion: 2027
First posted: Oct 2, 2025
Registry last updated: Oct 2, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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