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
The First Affiliated Hospital of Guangzhou Medical University
2,000 participants
Oct 1, 2023
OBSERVATIONAL
Conditions
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.
Eligibility
Inclusion Criteria6
- (1) Signing of the informed consent form;
- (2) Male or female, aged 18-75 years;
- (3) Undergoing elective thoracic surgery;
- (4) Good preoperative pulmonary function cooperation and complete reporting;
- (5) Preoperative chest single/dual phase CT scans without significant artefacts and with complete imaging;
- (6) The interval between preoperative pulmonary function and single/dual phase CT scans does not exceed one month.
Exclusion Criteria9
- (1) Poor preoperative pulmonary function cooperation or missing reports;
- (2) Preoperative chest single/dual phase CT scans exhibit significant artefacts or image omission;
- (3) The interval between preoperative pulmonary function and single/dual phase CT scans exceeds one month;
- (4) Complication with severe respiratory disorders (such as lung transplantation, pneumothorax, giant bullae, etc.);
- (5) Coexisting with other severe functional impairments;
- (6) Patients with obstructive lesions such as airway or esophageal stenosis;
- (7) Height beyond the predicted equation range (Female \< 1.45m; Male \< 1.55m);
- (8) Medication use before pulmonary function testing that does not meet the cessation guidelines;
- (9) Pulmonary function report quality graded D-F.
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Interventions
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.
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.
Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT06477458