Performance Evaluation of Artificial Intelligence Screening Model in Coronary Heart Disease Detection

NCT06658600 | Active Not Recruiting DMC

• 1 other identifier: DeepCHD
• Study Type: interventional
• Target: 900
• Locations: 1 country
• Sites: 3

Brief Summary

To determine whether an integrated AI decision support can save time and improve accuracy of assessment of obstructive coronary heart disease (CHD), the investigators are conducting a randomized controlled study of AI guided measurements of obstructive CHD probability compared to clinical assessment in preliminary evaluations by physicians.

Conditions

Coronary Heart Disease

Keywords

obstructive coronary heart disease; retinal images; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Diagnostic Accuracy of Participants with Obstructive Coronary Heart Disease

  Whether AI-guided decision support improves the diagnostic accuracy of obstructive coronary heart disease (CHD) to a greater extent than standard clinical assessments (RF-CL), both compared to clinical intuition. All participants of the case records had underwent CT angiography or invasive angiography. The diagnostic accuracy, sensitivity and specificity will be compared across groups.

  Through study completion, an average of 1 week

Secondary Outcomes (1)

• Time Consumed by Physician Readers to Provide the Diagnosis Impression of Obstructive Coronary Heart Disease.

  Through study completion, an average of 1 week

Study Arms (2)

Guideline-Based Group (Guideline Group)

ACTIVE COMPARATOR

Physicians use a RF-CL table (risk factor weighted clinical likelihood table) to calculate the probability of obstructive CHD. This approach aligns with current clinical guidelines to assist in decision-making.

Other: Physician readers will be assisted with RF-CL table to calculate the probability of obstructive coronary heart disease

AI-Assisted Group (AI Group)

EXPERIMENTAL

Physicians receive CHD probability estimates and diagnostic recommendations from an AI model based on retinal photographs. The AI tool provides individualized obstructive CHD probabilities, leveraging retinal biomarkers associated with cardiovascular risk.

Other: Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease

Interventions

Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease OTHER

Physician readers will be assisted with AI-derived probability and diagnosis of obstructive coronary heart disease. The AI tool provides individualized obstructive CHD probabilities and diagnosis, leveraging retinal biomarkers associated with cardiovascular risk.

AI-Assisted Group (AI Group)

Physician readers will be assisted with RF-CL table to calculate the probability of obstructive coronary heart disease OTHER

Physicians use a RF-CL table (risk factor weighted clinical likelihood table) to calculate the probability of obstructive CHD.

Guideline-Based Group (Guideline Group)

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Individuals with symptoms of coronary heart disease
• Age range: 18-75 years old
• Can accept and cooperate with the examination and potential follow-up work after being selected for clinical trials

You may not qualify if:

• Severe hypertension (\>180/110mmHg)
• Complex arrhythmia (atrial fibrillation, atrial flutter, frequent premature beats)
• Severe lung disease and chest malformation or surgery patients
• Acute myocardial infarction occurring less than 3 months ago
• Individuals with severe liver and kidney dysfunction and electrolyte imbalance

Sponsors & Collaborators

• Tsinghua University: lead
• Shanghai Jiao Tong University Affiliated Sixth People's Hospital: collaborator
• Shanghai Health and Medical Center: collaborator

Study Sites (3)

Tsinghua University

Beijing, Beijing Municipality, 100084, China

Location

Shanghai Health and Medical Center

Shanghai, Shanghai Municipality, 200000, China

Location

Shanghai Sixth People's Hospital

Shanghai, Shanghai Municipality, 200000, China

Location

MeSH Terms

Conditions

Coronary Disease

Condition Hierarchy (Ancestors)

Myocardial Ischemia; Heart Diseases; Cardiovascular Diseases; Vascular Diseases

Study Officials

• Tien Yin Wong, PhD

  Tsinghua University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Purpose: SCREENING
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: October 22, 2024
• First Posted: October 26, 2024
• Study Start: January 10, 2025
• Primary Completion: April 1, 2025
• Study Completion: May 1, 2025
• Last Updated: April 8, 2025

Record last verified: 2025-04

Data Sharing

• IPD Sharing: Will not share

Locations

CN (3)