Using AI to improve risk assessment and outcome prediction in lung cancer
Image Mining and ctDNA to Improve Risk Stratification and Outcome Prediction in NSCLC Applying Artificial Intelligence.
IRCCS San Raffaele · NCT06163846
This study is testing whether using artificial intelligence to analyze medical images and blood samples can help doctors better understand the risks and outcomes for people with non-small cell lung cancer.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 415 (estimated) |
| Ages | 18 Years to 70 Years |
| Sex | All |
| Sponsor | IRCCS San Raffaele (other) |
| Locations | 1 site (Milano) |
| Trial ID | NCT06163846 on ClinicalTrials.gov |
What this trial studies
This observational study aims to enhance the risk stratification and outcome prediction for patients with non-small cell lung cancer (NSCLC) by utilizing artificial intelligence techniques. It combines data from medical imaging and circulating cell-free tumor DNA (ctDNA) to identify tumor characteristics that correlate with disease stage and patient outcomes. The study hypothesizes that these combined data sources can serve as non-invasive biomarkers for disease burden and recurrence risk. By leveraging advanced image analysis methods, the research seeks to provide more accurate staging and prognostic information for lung cancer patients.
Who should consider this trial
Good fit: Ideal candidates for this study are adults over 18 years old with a new pathological diagnosis of lung cancer who have available baseline imaging and are eligible for surgery.
Not a fit: Patients who are pregnant or breastfeeding will not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to more personalized treatment plans and improved survival rates for lung cancer patients.
How similar studies have performed: While there have been preliminary studies exploring similar approaches, this specific combination of image mining and ctDNA analysis in a prospective setting is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patients with new pathological diagnosis of lung cancer, available baseline imaging (CT and FDG-PET/CT), age \> 18 years, and eligibility for surgery will be considered for inclusion. Exclusion Criteria: * pregnant or breast- feeding women.
Where this trial is running
Milano
- Irccs San Raffaele — Milano, Italy (RECRUITING)
Study contacts
- Study coordinator: Alessandra Maielli
- Email: maielli.alessandra@hsr.it
- Phone: 0226433639
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.
Conditions: Non Small Cell Lung Cancer