Using deep learning to predict treatment response in lung cancer patients

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This observational study aims to evaluate a deep learning signature based on CT, PET, and whole slide imaging (WSI) to predict the complete pathological response in patients with non-small cell lung cancer (NSCLC) who have undergone neoadjuvant chemoimmunotherapy. By analyzing imaging data, the study seeks to identify patterns that correlate with successful treatment outcomes. The goal is to enhance predictive accuracy and potentially guide treatment decisions for NSCLC patients. Participants will be monitored post-surgery to assess the effectiveness of the predictive model.

Why it matters

Who can join: the full rules

Inclusion Criteria:

1. Age ranging from 20-75 years;
2. Patients who underwent curative surgery after neoadjuvant chemoimmunotherapy for NSCLC;
3. Obtained written informed consent.

Exclusion Criteria:

1. Missing image data;
2. Pathological N3 disease.

Where it's running

• Affiliated Hospital of Zunyi Medical University
  Zunyi, Guizhou, China Recruiting
• The First Affiliated Hospital of Nanchang University
  Nanchang, Jiangxi, China Recruiting
• Ningbo HwaMei Hospital
  Ningbo, Zhejiang, China Recruiting

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.