AI-Enabled Diagnosis and Prognosis of Hypertrophic Cardiomyopathy

Precision Diagnosis and Prognostic Prediction of Hypertrophic Cardiomyopathy Using Artificial Intelligence: A Multicenter Study

By harnessing artificial intelligence to decode the 12-lead electrocardiogram, the project will enable precise ECG-based phenotyping of hypertrophic cardiomyopathy-accurately classifying septal, apical, and other morphologic subtypes-while simultaneously differentiating HCM from hypertensive heart disease, aortic stenosis, and other phenocopy disorders.

Study Overview

• Status: Recruiting
• Conditions: Left Ventricular Hypertrophy; Hypertrophic Cardiomyopathy (HCM)

Detailed Description

To overcome the twin bottlenecks of late detection and poor inter-centre reproducibility, the project leverages a large, multicentre historical cohort and anchors its pipeline on the 12-lead ECG-an inexpensive, ubiquitously available signal that can be captured in any department. Using deep-learning architectures augmented with attention mechanisms, we will develop (1) a discriminative model that separates HCM from phenocopies and normal hearts, and (2) an algorithmic framework that remains stable across devices and populations. Model governance will be embedded through version-controlled releases, cloud-edge deployment, and an "offline replay" evaluation loop, producing an end-to-end evidence chain that mirrors real-world clinical workflows.

• Study Type: Observational
• Enrollment (Estimated): 15000

Contacts and Locations

• Study Contact: Name: Xiaojie Xie, MD, PhD; Phone Number: (+86)0571-87784700; Email: xiexj@zju.edu.cn

Study Locations

• China
  • Zhejiang
    • Hangzhou, Zhejiang, China, 310009
      • Recruiting
      • Second Affiliated Hospital, Zhejiang University School of Medicine
      • Contact: Xiaojie Xie, MD, PhD; Phone Number: (+86)0571-87784700; Email: xiexj@zju.edu.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

1. HCM cohort: Adults diagnosed with hypertrophic cardiomyopathy in accordance with the *2023 Chinese Guidelines for the Diagnosis and Treatment of Hypertrophic Cardiomyopathy in Adults*.
2. HCM phenocopy cohort: Adults with an LV wall thickness ≥ 13 mm at any site on echocardiography.
3. Healthy-control cohort: Adults with no history of cardiac disease and no evidence of myocardial hypertrophy on echocardiography.

Description

Inclusion Criteria:

1. Adults aged ≥ 18 years.
2. HCM cohort: Adults diagnosed with hypertrophic cardiomyopathy in accordance with the *2023 Chinese Guidelines for the Diagnosis and Treatment of Hypertrophic Cardiomyopathy in Adults*.
3. HCM phenocopy cohort: Adults with an LV wall thickness ≥ 13 mm at any site on echocardiography.
4. Healthy-control cohort: Adults with no history of cardiac disease and no evidence of myocardial hypertrophy on echocardiography.

Exclusion Criteria:

Patients from whom analyzable ECG data cannot be obtained.

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort
HCM; diagnosed with hypertrophic cardiomyopathy by echocardiography and cardiac magnetic resonance imaging
phenocopy; patients with left-ventricular hypertrophy attributable to non-hypertrophic cardiomyopathy conditions
normal control; healthy individuals without myocardial hypertrophy

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
model diagnostic performance	Model performance was evaluated using calculated metrics including accuracy, sensitivity, specificity, and the area under the ROC curve (AUC).	year 2

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
model diagnostic performance	The accuracy rate of the model's phenotype-specific classification for patients with different patterns of myocardial hypertrophy	year 2
the model's generalizability	The model's diagnostic performance on the external, multicentre validation cohort, including overall accuracy, sensitivity, specificity, and area under the ROC curve (AUC).	year 2

Collaborators and Investigators

• Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University

Study record dates

Study Major Dates

• Study Start (Actual): January 1, 2025
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): December 31, 2026

Study Registration Dates

• First Submitted: November 17, 2025
• First Submitted That Met QC Criteria: November 23, 2025
• First Posted (Estimated): December 4, 2025

Study Record Updates

• Last Update Posted (Estimated): December 4, 2025
• Last Update Submitted That Met QC Criteria: November 23, 2025
• Last Verified: January 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Aortic Valve Disease; Cardiovascular Diseases; Pathological Conditions, Anatomical; Heart Diseases; Heart Valve Diseases; Cardiomyopathies; Aortic Stenosis, Subvalvular; Aortic Valve Stenosis; Cardiomegaly; Hypertrophy; Pathological Conditions, Signs and Symptoms; Cardiomyopathy, Hypertrophic; Hypertrophy, Left Ventricular
• Other Study ID Numbers: 2024-1546

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No