Using deep learning to predict treatment response in lung cancer patients
An Integration of a Computed Tomography/Positron Emission Tomography/Whole Slide Image (CT/PET/WSI) Based Deep Learning Signature for Predicting Complete Pathological Response to Neoadjuvant Chemoimmunotherapy in Non-small Cell Lung Cancer: A Multicenter Study
This study is testing if a new computer program can help predict how well lung cancer patients will respond to treatment before their surgery.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 100 (estimated) |
| Ages | 20 Years to 75 Years |
| Sex | All |
| Sponsor | Shanghai Pulmonary Hospital, Shanghai, China Academic / other |
| Locations | 3 sites (Zunyi, Guizhou and 2 other locations) |
| Trial ID | NCT05925751 on ClinicalTrials.gov |
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.
Who should consider this trial
Good fit: Ideal candidates for this study are adults aged 20-75 who have undergone curative surgery following neoadjuvant chemoimmunotherapy for NSCLC.
Not a fit: Patients with missing image data or those diagnosed with pathological N3 disease may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to more personalized treatment plans for lung cancer patients, improving their chances of achieving a complete response to therapy.
How similar studies have performed: While the use of deep learning in medical imaging is gaining traction, this specific application in predicting treatment response for NSCLC is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
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 this trial is running
Zunyi, Guizhou and 2 other locations
- 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)
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.