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RECRUITING
NCT07820423

Multimodal AI Predicts High-risk Pathology in Lung Cancer Associated With Cystic Airspaces

Sponsor: Central South University

View on ClinicalTrials.gov

Summary

The goal of this observational study is to develop and validate an artificial intelligence (AI)-based multimodal radiomics model that integrates preoperative CT imaging features and clinical data to predict pathological high-risk features in patients with lung cancer associated with cystic airspaces (LCCA). The main questions it aims to answer are: Can an AI-based multimodal radiomics model accurately predict pathological high-risk features in LCCA before surgery? Does the integration of CT imaging features and clinical variables improve preoperative risk stratification compared with imaging or clinical information alone?

Official title: Interpretable Multimodal Artificial Intelligence Predicts High-risk Pathology in Lung Cancer Associated With Cystic Airspaces

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

600

Start Date

2025-05-01

Completion Date

2026-12-31

Last Updated

2026-09-15

Healthy Volunteers

No

Locations (1)

The Second Xiangya Hospital of Central South University

Changsha, Hunan, China