Prediction of Coronary Artery Disease Based on Multimodal, Non-contact Information With Artificial Intelligence

Coronary Artery Disease Clinical Trial

Official title:

Development and Validation of Artificial Intelligence Prediction Models Based on Multimodal, Non-contact Captured Information in Predicting Coronary Artery Disease

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06092801
• Other study ID #: 2022-GSP-QN-10
• Status: Recruiting
• Start date: November 20, 2023
• Est. completion date: December 2024

Study information

• Verified date: January 2024
• Source: China National Center for Cardiovascular Diseases
• Contact: Shen Lin, M.D., Ph.D.
• Phone: 8610-88398027
• Email: linshen[@]fuwai.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The goal of this observational study are 1) to assess the effectiveness of modalities and/or their combination of multimodal non-contact information in predicting coronary artery disease; 2) to prospectively validate the performance of the developed artificial Intelligence models in predicting coronary artery disease.

Description:

This observational study aims to assess the effectiveness and potential mechanism of modalities of non-contact captured bio-physiological information, including facial RGB information, infrared thermography temperature information, gait information, and wearable device information, individually and/or in combination, in predicting coronary artery disease (CAD) with artificial intelligence technology.

Individuals suspected of CAD and referred for evaluation will be invited to participate in the current study for analyzing the non-contact information and association with underlying CAD status, in order to establish the most efficient artificial Intelligence modeling strategy, and prospectively validate the predictive performance of the developed artificial Intelligence models for CAD prediction.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 998
• Est. completion date: December 2024
• Est. primary completion date: December 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Suspected individuals referred to for coronary angiography or coronary computer tomography angiography.

Exclusion Criteria:

• Prior percutaneous coronary intervention (PCI)

• Prior coronary artery bypass graft (CABG)

• Undergoing confirmatory coronary evaluation as pre-operation routines for other cardiac diseases

• With artificial body alteration (e.g. cosmetic surgery, facial trauma, or make-up) that may affect the non-contact information of study interest

• Age less than 18 years old

• Other circumstances that prevent participants from cooperating with the study process

• Decline to consent for study participation

Related Conditions & MeSH terms

• Coronary Artery Disease
• Coronary Disease
• Myocardial Ischemia

Intervention

Other:
• No intervention
No intervention

Locations

Country	Name	City	State
China	Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College	Beijing	Beijing

Sponsors (1)

Lead Sponsor	Collaborator
China National Center for Cardiovascular Diseases

Country where clinical trial is conducted

China, 

References & Publications (1)

Lin S, Li Z, Fu B, Chen S, Li X, Wang Y, Wang X, Lv B, Xu B, Song X, Zhang YJ, Cheng X, Huang W, Pu J, Zhang Q, Xia Y, Du B, Ji X, Zheng Z. Feasibility of using deep learning to detect coronary artery disease based on facial photo. Eur Heart J. 2020 Dec 7;41(46):4400-4411. doi: 10.1093/eurheartj/ehaa640. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Positive predictive value (PPV) of algorithm	Positive predictive value (PPV) of algorithm in predicting coronary artery disease assessed in test group	At the end of enrollment (1 mouth)
Other	Negative predictive value (NPV)	Negative predictive value (NPV) of algorithm in predicting coronary artery disease assessed in test group	At the end of enrollment (1 mouth)
Other	Diagnostic accuracy rate	Diagnostic accuracy rate of algorithm in predicting coronary artery disease assessed in test group	At the end of enrollment (1 mouth)
Primary	Sensitivity of algorithm	Sensitivity of algorithm in predicting coronary artery disease assessed in test group	At the end of enrollment (1 mouth)
Primary	Specificity of algorithm	Sensitivity of algorithm in predicting coronary artery disease assessed in test group	At the end of enrollment (1 mouth)
Secondary	Area under receiver operating curve (AUC)	Area under receiver operating curve of algorithm in predicting coronary artery disease assessed in test group	At the end of enrollment (1 mouth)