Actively Recruiting
Deep Learning Model Predicts Pathological Complete Response of Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunochemotherapy
Led by Tongji Hospital · Updated on 2025-07-28
300
Participants Needed
1
Research Sites
91 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
This study aims to develop and validate a deep learning model to predict pathological complete response (pCR) in patients with esophageal squamous cell carcinoma who have undergone neoadjuvant immunochemotherapy. Clinical, imaging, and pathological data from previously treated patients will be collected and analyzed. The model is expected to assist in predicting treatment outcomes and guide personalized therapeutic strategies.
CONDITIONS
Official Title
Deep Learning Model Predicts Pathological Complete Response of Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunochemotherapy
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Pathologically confirmed esophageal squamous cell carcinoma (ESCC)
- Received at least one cycle of neoadjuvant chemotherapy combined with immunotherapy
- Underwent contrast-enhanced chest CT before starting neoadjuvant treatment
- Underwent contrast-enhanced chest CT after completing neoadjuvant treatment and before surgery
You will not qualify if you...
- Diagnosis of other malignancies
- Received other anti-tumor therapies before or during neoadjuvant chemo-immunotherapy
- Incomplete clinical data
- Poor-quality CT imaging
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, Hubei, China, 430030
Actively Recruiting
Research Team
Y
Yangkai Li, MD, PhD
CONTACT
L
Lin Zhou, MSc
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
1
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