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

RECRUITINGSponsored by Tongji Hospital
Actively Recruiting
SponsorTongji Hospital
Started2025-03-01
Est. completion2026-06-01
Eligibility
Age18 Years+
Healthy vol.Accepted
View on ClinicalTrials.gov →

NCT07088354

Summary

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.

Eligibility

Age: 18 Years+Healthy volunteers accepted
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.

Conditions5

CancerDeep LearningEsophageal Squamous Cell CarcinomaNeoadjuvant ImmunochemotherapyPathological Complete Response

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