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Deep Learning Model Predicts Pathological Complete Response of Esophageal Squamous Cell Carcinoma Following Neoadjuvant Immunochemotherapy

Recruitingn/aAges 18 Years - anyAllTongji Hospital
NCT07088354 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

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.

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📋 Eligibility rules (as published)
Inclusion Criteria: 1. Pathologically confirmed esophageal squamous cell carcinoma (ESCC). 2. Received at least one cycle of neoadjuvant chemotherapy combined with immunotherapy. 3. Underwent contrast-enhanced chest CT before initiation of neoadjuvant treatment. 4. Underwent contrast-enhanced chest CT after completion of neoadjuvant treatment and prior to surgery. Exclusion Criteria: 1. Diagnosis of other malignancies. 2. Received other anti-tumor therapies before or during neoadjuvant chemo-immunotherapy. 3. Incomplete clinical data. 4. Poor-quality CT imaging.
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What it tests

  • The high-throughput extraction of large amounts of quantitative image features from medical images
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Where

1 site
Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, China
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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