NCT06477458

Deep Learning for Preoperative Pulmonary Assessment in Thoracic CT

Application of Deep Learning in CT Imaging of Elective Thoracic Surgery Patients: Assessing Preoperative Abnormal Pulmonary Function

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 2,000 (estimated)
• Sponsor: The First Affiliated Hospital of Guangzhou Medical University · Academic / Other
• Sex: All
• Age: 18 Years – 75 Years
• Healthy volunteers: Not accepted

Summary

The trial was designed as a single-centre, non-interventional prospective observational study to utilize deep learning technology combined with computed tomography (CT) images to precisely predict the pulmonary function indicators of thoracic surgery preoperative patients.

Detailed description

Preoperative pulmonary function tests are crucial in assessing perioperative complications or mortality risks and providing decision support for thoracic surgery. However, traditional pulmonary function assessment methods have significant limitations, including long testing durations, difficulties in patient cooperation, high false-negative rates, and numerous contraindications. Thus, our study optimized the final model based on 1500 single inspiratory phase CTs by transferring model parameters trained on 500 dual-phase respiratory CTs, enhancing its predictive capabilities for pulmonary function. This adjustment suits real-world application demands, offering more convenient, comprehensive, and personalized preoperative pulmonary function assessment support. Our study optimized the final model based on 1500 single inspiratory phase CTs by transferring model parameters trained on 500 dual-phase respiratory CTs, enhancing its predictive capabilities for pulmonary function. This adjustment suits real-world application demands, offering more convenient, comprehensive, and personalized preoperative pulmonary function assessment support.

Conditions

• Elective Thoracic Surgery
• Pulmonary Function
• Deep Learning

Interventions

Type	Name	Description
OTHER	Single inspiratory phase computed tomography.	Utilizing deep learning technology in conjunction with single inspiratory phase computed tomography images to accurately predict the pulmonary function indicators of preoperative thoracic surgery patients.
OTHER	Respiratory dual-phase computed tomography.	Utilizing deep learning technology in conjunction with respiratory dual-phase computed tomography images to accurately predict the pulmonary function indicators of preoperative thoracic surgery patients.

Timeline

• Start date: 2023-10-01
• Primary completion: 2024-09-30
• Completion: 2024-12-30
• First posted: 2024-06-27
• Last updated: 2024-06-27

Locations

1 site across 1 country: China