Staging Strategies and Their Association With Prognosis and Therapy in Lung Cancer With Cystic Airspaces
NCT07066813 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 500
Last updated 2026-03-18
Summary
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?
Conditions
- Lung Cancer Associated With Cystic Airspaces
Sponsors & Collaborators
-
Central South University
lead OTHER
Eligibility
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2025-06-01
- Primary Completion
- 2026-05-31
- Completion
- 2026-07-01
Countries
- China
Study Locations
More Related Trials
-
The Establishment and Clinical Application of a Prediction Model of Lung Cancer Distant Metastasis Based on the Genomic Characteristics of Circulating Tumor Cells
NCT04568720 ·Status: UNKNOWN
-
AI-Based Prediction of Stage and Survival in Non-Small Cell Lung Cancer: A Retrospective Study
NCT07068139 ·Status: ACTIVE_NOT_RECRUITING
-
ctDNA Dynamic Monitoring and Its Role of Prognosis in Stage I NSCLS by NGS
NCT03172156 ·Status: COMPLETED
-
Independent Predictors Analysis and Model Construction of Cavitary Central Lung Cancer
NCT05278754 ·Status: UNKNOWN
-
Retrospective Analysis of Clinical and CT Features to Predict Spread Through Air Space in Stage IA Lung Adenocarcinoma
NCT06645743 ·Status: NOT_YET_RECRUITING
-
Novel Detection System for Lung Cancer Curative Effect Monitoring
NCT02666755 ·Status: UNKNOWN
-
The Role of ctDNA Testing Plus AI-based Pathology in Resectable LSCC
NCT05778253 ·Status: RECRUITING
-
Detection of Circulating Tumour Cells, Spread Through Air Space in Patients With Lung Cancer
NCT06833632 ·Status: RECRUITING
-
ctDNA Dynamic Monitoring and Its Role of Prognosis in Stage II to IIIA NSCLC by NGS
NCT03465241 ·Status: COMPLETED
-
Comparison Between Wedge Resection and Segmentectomy for Ground Glass Opacity- Dominant Stage IA NSCLC
NCT02718365 ·Status: UNKNOWN ·Phase: NA
-
Imaging-based Deep Learning for Lung Cancer Diagnosis and Staging
NCT04000620 ·Status: UNKNOWN
-
Study on Systemic and Airway Cytokines and Oxidative Stress in Lung Cancer Patients Undergoing Surgery
NCT00956852 ·Status: TERMINATED
-
The Accuracy of Targeted Lymph Node Dissection of Non-small Cell Lung Cancer Patients According to Predictive Models
NCT06768853 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Precision Diagnosis for Intraoperative Frozen Section of Early Stage Lung Cancer
NCT02941003 ·Status: UNKNOWN ·Phase: NA
-
Study of Early-stage Lung Adenocarcinoma for Early Detection and Effective Treatment Strategy
NCT01482585 ·Status: UNKNOWN
-
A Preliminary Study on the Detection of Plasma Markers in Early Diagnosis for Lung Cancer
NCT04558255 ·Status: UNKNOWN
-
A Study of Real-world Treatment Patterns and Outcomes in Chinese Advanced NSCLC Patients Who Previously Received at Least 2 Line Treatments
NCT06617390 ·Status: COMPLETED
-
Postoperative Pulmonary Function Assessment Based on Deep Learning Study
NCT07256457 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
A Study of the Gene Mutation Status in Cerebrospinal Fluid, Blood and Tumor Tissue of Non-small Cell Lung Cancer Patients With Brain Metastases
NCT03257735 ·Status: UNKNOWN
-
Image Mining and ctDNA to Improve Risk Stratification and Outcome Prediction in NSCLC Applying Artificial Intelligence.
NCT06163846 ·Status: RECRUITING
-
Factors Determine the Feasibility and Surgical Margin Quality of Sublobar Resection for Non-small Cell Lung Cancer?
NCT07005401 ·Status: COMPLETED
-
Prognostic Study of Metastases in Patients With Stage I, Stage II, or Stage III Non-small Cell Lung Cancer That Can Be Removed by Surgery
NCT00003901 ·Status: COMPLETED ·Phase: PHASE3
-
Detection Cell Free DNA in Lung Cancer Patients
NCT02738593 ·Status: UNKNOWN
-
Construction and Evaluation of the Liquid Biopsy-based Early Diagnostic Model for Lung Cancer
NCT04156360 ·Status: UNKNOWN
-
Artificial Intelligence-based Model for the Prediction of Occult Lymph Node Metastasis and Improvement of Clinical Decision-making in Non-small Cell Lung Cancer
NCT06684418 ·Status: RECRUITING