Deep Learning-Enhanced Noninvasive Detection of Pulmonary Hypertension and Subtypes via Chest Radiographs, Validated by Catheterization.
Zhihua Huang, Xiaolin Diao, Yanni Huo...
https://pubmed.ncbi.nlm.nih.gov/40541737Actively Recruiting
Age: 18Years +
All Genders
Healthy Volunteers
ID05566002
Artificial Intelligence-Assisted Evaluation of Pulmonary Hypertension
Led by Chinese Pulmonary Vascular Disease Research Group · Updated on 2025-04-08
2000
Participants Needed
1
Research Sites
N/A
Total Duration
On this page
AI-Summary
What this Trial Is About
Pulmonary hypertension (PH) is a complex condition with high risks if untreated. This research aims to use artificial intelligence (AI) to study and develop methods that simulate human intelligence for screening and diagnosing PH. The study focuses on combining various clinical data from patients who undergo right heart catheterization (RHC) to enhance early detection and diagnosis accuracy. The study collects routine examination data such as chest X-ray, electrocardiography, and echocardiography from patients at Fuwai Hospital. Patients undergo RHC to definitively diagnose PH based on mean pulmonary artery pressure (mPAP) levels. AI programs will be developed using these multimodal data to assist PH screening and diagnosis and to compare AI performance against conventional echocardiographic methods. Participants will have their clinical data collected during routine exams and RHC procedures. Researchers will use this information to train and validate AI algorithms. The main outcome measured is the accuracy of AI-assisted diagnosis of PH. Additional measures include sensitivity and specificity. The study aims to improve noninvasive detection tools, supporting timely diagnosis and better patient management.
CONDITIONS
Brief Title
Artificial Intelligence-assisted Evaluation of Pulmonary HYpertension
Who Can Participate
Age: 18Years +
All Genders
Healthy Volunteers
Eligibility Criteria
You may qualify if you...
- Age 18 years or older
- Patients who have previously received chest X-ray, electrocardiography, echocardiography, other routine examinations, and right heart catheterization at Fuwai Hospital, CAMS & PUMC, Beijing, China
You will not qualify if you...
- Patients who have not undergone right heart catheterization
- Poor quality of routine examinations or right heart catheterization results unsuitable for analysis
- Severe loss of results from routine examinations such as chest X-ray, electrocardiography, or echocardiography
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
1
2
3
Your Study Journey
Screening
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Diagnostic Evaluation
Duration - Up to 1 day
Participants undergo routine examinations including chest X-ray, electrocardiography, echocardiography, and right heart catheterization to collect data for artificial intelligence-assisted analysis and diagnosis of pulmonary hypertension.
1 visit (in-person)
Long-term Monitoring
Duration - Up to study completion in December 2025
Participants' collected data are used to develop and validate artificial intelligence models for the detection of pulmonary hypertension.
No additional visits; data analysis phase
Trial Site Locations
Total: 1 location
1
Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Beijing, Beijing Municipality, China, 100037
Actively Recruiting
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Research Team
Z
Zhihong Liu, MD, PhD
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
2
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Published Research Related To This Trial
Development and validation of multimodal deep learning algorithms for detecting pulmonary hypertension.
Wei Zhao, Zhihua Huang, Xiaolin Diao...
https://pubmed.ncbi.nlm.nih.gov/40205021