Artificial Intelligence in Computed Tomography for Quantifying Lung Changes of Bronchiectasis Patients

Shanghai Jiao Tong University

Status: Not yet enrolling

Conditions: Bronchiectasis

Treatments: Other: No intervention

Study type: Observational

Funder types: Other

Identifiers

NCT05751538

AI-BE

Details and patient eligibility

About

Bronchiectasis is a chronic respiratory disease characterized by permanent bronchiectasis.The incidence and prevalence of bronchiectasis have assumed continuously grows in global. Chest computed tomography (CT) remains the imaging standard for demonstrating cystic fibrosis (CF) airway structural disease in vivo. However, visual scoring systems as an outcome measure are time consuming, require training and lack high reproducibility. Our objective was to validate a fully automated artificial intelligence (AI)-driven scoring system of CF lung disease severity.

Enrollment: 730 estimated patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients diagnosed with bronchiectasis (according to the Chinese consensus, patient's previous chest CT examination must show bronchiectasis)

Exclusion criteria

• Patients with CT data and medical records missing

Trial design

730 participants in 3 patient groups

Train dataset

Description:

This group is dedicated to developing an automated algorithm.

Treatment:

Other: No intervention

Test dataset

Description:

This group is dedicated to testing the performance of an automated algorithm.

Treatment:

Other: No intervention

Clinical Validation

Description:

This group is dedicated to assessing the clinical validity of the measurement in an independent validation cohort.

Treatment:

Other: No intervention