Clinical trial · Observational
Predicting Immunotherapy Response and Survival of Lung Cancer Patients Using Artificial Intelligence and Radiomics (Radiology-AI-Lung)
NCT07059923CI-TRIAL-00092047recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
CT imaging data from lung cancer (NSCLC and SCLC) patients prior to the initiation of immunotherapy (and possibly also after treatment) will be collected. The processing pipeline includes automatic tumor segmentation, radiomics feature extraction, feature selection, and construction of a classification model.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Lung Cancer (Diagnosis) | Malignant Lung Neoplasm | CURATED_EXACT | 0.85 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (3)
- measure
- Progression-free survival
- timeFrame
- 1 year
- measure
- disease-free survival
- timeFrame
- 1 year
- measure
- overall survival
- timeFrame
- 1 year
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: 1. Patients were treated for lung cancer in Wuhan Union Hospital from July 2025 to July 2026; 2. Aged \> 18 years old; 3. At least one CT scan before treatment; 4. Tissue biopsy pathological examination confirmed the diagnosis of the above tumors. Exclusion criteria: 1. Poor image quality; 2. Incomplete clinical data or loss of follow-up; 3. Presence of another primary malignancy other than lung cancer; 4. Unclear pathological diagnosis.
References
Publications (0)
Data not yet available
No reference posted for this study.