Staging Strategies and Their Association With Prognosis and Therapy in Lung Cancer With Cystic Airspaces
Recruiting now
Conditions studied: Lung Cancer Associated With Cystic Airspaces
In brief
The goal of this observational study is to determine the most accurate tumor size measurement method for T-staging and prognostic assessment in lung cancer with cystic airspaces (LCCA). The main questions it aims to answer are: * What is the optimal T-staging approach for accurately classifying lung cancer with cystic airspaces （LCCA) and predicting patient outcomes? * How do imaging features of cystic lesions correlate with their pathological characteristics? * What is the relationship between imaging features of cystic airspace-associated lesions and patient prognosis? * Can optimizing the T-staging method improve clinical decision-making in patients with LCCA?
Key facts
- Study ID
- NCT07066813
- Run by
- Central South University
- People needed
- 500
- Starts
- 2025-06-01
- Expected to finish
- 2026-07-01
- Last updated by the study team
- 2026-07-08
Who can join
Age: any. Sex: any. Healthy volunteers: not accepted.
You may qualify if…
- Histologically confirmed non-small cell lung cancer (NSCLC), as verified by biopsy or postoperative pathological examination;
- Patients who have undergone surgical lung resection;
- Patients with complete preoperative chest CT imaging data;
- Preoperative chest CT showing a well-defined gas-containing (air-filled) cystic component within the tumor.
You may not qualify if…
- History of pulmonary diseases that could produce cystic lung lesions (e.g., tuberculosis, pulmonary fungal infections, bullae, emphysema, Lymphangioleiomyomatosis [LAM], or Birt-Hogg-Dubé [BHD] syndrome);
- Systemic anti-tumor therapies, including chemotherapy, radiotherapy, or targeted therapies (such as monoclonal antibodies, small-molecule tyrosine kinase inhibitors, among others), were administered prior to enrollment;
- Patients with concurrent other malignancies;
- Patients with missing or poor-quality preoperative chest CT imaging data.
Where it is running
- The Second Xiangya Hospital of Central South University — Changsha, Hunan, China (enrolling)
Full record on ClinicalTrials.gov
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