Artificial Intelligence in Computed Tomography for Quantifying Lung Changes of Bronchiectasis Patients
Artificial Intelligence Based on Machine Learning in Computed Tomography for Quantifying Lung Changes of Bronchiectasis Patients
1 other identifier
observational
730
1 country
1
Brief Summary
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Mar 2023
Shorter than P25 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
February 8, 2023
CompletedStudy Start
First participant enrolled
March 1, 2023
CompletedFirst Posted
Study publicly available on registry
March 2, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 30, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
December 30, 2023
CompletedMarch 2, 2023
November 1, 2022
4 months
February 8, 2023
February 20, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Correlations of the artificial intelligence-driven scores with manual scores
Correlations and comparisons of the artificial intelligence-driven scores with manual scores by thoracic radiologists on CT scans of bronchiectasis patients.
From date of inclusion until the date of final quantification, assessed up to 12 months
Secondary Outcomes (1)
Correlation of the artificial intelligence-driven scores with pulmonary function test
From date of inclusion until the date of final quantification, assessed up to 12 months
Study Arms (3)
Train dataset
This group is dedicated to developing an automated algorithm.
Test dataset
This group is dedicated to testing the performance of an automated algorithm.
Clinical Validation
This group is dedicated to assessing the clinical validity of the measurement in an independent validation cohort.
Interventions
Eligibility Criteria
Patients with bronchiectasis and clinical examination, pulmonary function test, and CT data
You may qualify if:
- Patients diagnosed with bronchiectasis (according to the Chinese consensus, patient's previous chest CT examination must show bronchiectasis)
You may not qualify if:
- Patients with CT data and medical records missing
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Ruijin Hospitallead
Study Sites (1)
Ruijin Hospital, Medical School of Shanghai Jiaotong University
Shanghai, Shanghai Municipality, 200025, China
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
February 8, 2023
First Posted
March 2, 2023
Study Start
March 1, 2023
Primary Completion
June 30, 2023
Study Completion
December 30, 2023
Last Updated
March 2, 2023
Record last verified: 2022-11