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AI-enabled Screening and Diagnosis of Cardiomyopathies Using Coronary CTA

NCT06748261 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 5000

Last updated 2024-12-27

No results posted yet for this study

Summary

The goal of this observational and diagnostic study is to develop and validate an artificial intelligence assisted approach for coronary computer tomography angiography-(CCTA)-based screening and diagnosis of cardiomyopathies in patients with suspected coronary artery diseases. This study aims to develop a computerized CCTA interpretation using artificial intelligence for multi-label classification task to assist cardiomyopathy diagnosis in the clinical workflow.

Conditions

  • Cardiovascular Diseases
  • Hypertrophic Cardiomyopathy (HCM)
  • Dilated Cardiomyopathy (DCM)
  • Restrictive Cardiomyopathy
  • Amyloid Cardiomyopathy
  • Ischemic Cardiomyopathy
  • Arrhythmogenic Right Ventricular Cardiomyopathy
  • Myocarditis
  • Cardiomyopathies

Interventions

DIAGNOSTIC_TEST

CCTAI model

Using a derivative sub-cohort, the investigators aim to first develop an CCTA-based AI-assisted (CCTAI) screening model to distinguish patients with cardiac abnormalities from those normal controls. Second, the investigators target at developing a CCTAI diagnostic model with multi-classification output of cardiomyopathy diagnosis. Both models will be tested in internal validation cohort and external validation cohort.

Sponsors & Collaborators

  • Shanghai Zhongshan Hospital

    lead OTHER

Principal Investigators

  • Chenguang Li, MD, PhD · Fudan University

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-12-30
Primary Completion
2025-06-30
Completion
2025-12-30

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Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06748261 on ClinicalTrials.gov