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Cardiomyopathy III: Hypertrophic Cardiomyopathy

Cardiomyopathy III: Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy, or HCM, is an autosomal dominant genetic disorder characterized by asymmetric left ventricular hypertrophy without ventricular dilation. It is more common in men and is typically diagnosed in young, athletic adults.EtiologyHCM is primarily genetic and is caused by mutations in genes encoding sarcomeric proteins. Researchers have identified over 1400 mutations across at least 11 different genes. Among these, the most frequently occurring mutations are found in the...

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Related Experiment Video

Updated: Sep 12, 2025

Ultrasonic Assessment of Myocardial Microstructure

Ultrasonic Assessment of Myocardial Microstructure

Published on: January 14, 2014

Echocardiographic Texture Analysis Using Machine Learning for Predicting Myocardial Fibrosis in Hypertrophic

Guizi Liang¹, Ziyu Peng², Jie Hu¹

¹Department of Ultrasound Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.

Ultrasound in Medicine & Biology

|August 5, 2025

Summary

This summary is machine-generated.

A new machine learning model using echocardiographic myocardial texture can identify cardiac fibrosis in hypertrophic cardiomyopathy patients. This non-invasive screening tool reduces contrast use and aids resource-limited hospitals.

Keywords:

Echocardiography imaging Fibrosis Hypertrophy Machine learning Texture analysis

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High-frequency High-resolution Echocardiography: First Evidence on Non-invasive Repeated Measure of Myocardial Strain, Contractility, and Mitral Regurgitation in the Ischemia-reperfused Murine Heart

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Published on: July 9, 2010

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Last Updated: Sep 12, 2025

Ultrasonic Assessment of Myocardial Microstructure

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Published on: January 14, 2014

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

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Published on: May 24, 2021

High-frequency High-resolution Echocardiography: First Evidence on Non-invasive Repeated Measure of Myocardial Strain, Contractility, and Mitral Regurgitation in the Ischemia-reperfused Murine Heart

High-frequency High-resolution Echocardiography: First Evidence on Non-invasive Repeated Measure of Myocardial Strain, Contractility, and Mitral Regurgitation in the Ischemia-reperfused Murine Heart

Published on: July 9, 2010

Area of Science:

Cardiology
Medical Imaging
Artificial Intelligence

Background:

Myocardial fibrosis is a key feature of hypertrophic cardiomyopathy (HCM).
Accurate detection of myocardial fibrosis often requires contrast-enhanced cardiac magnetic resonance imaging (CE-CMR).
CE-CMR is expensive and not widely accessible, particularly in resource-limited settings.

Purpose of the Study:

To develop a low-cost, non-invasive screening model for myocardial fibrosis in HCM patients.
To utilize echocardiographic myocardial texture analysis and machine learning.
To reduce unnecessary contrast agent use and improve screening efficiency.

Main Methods:

149 HCM patients (105 LGE-positive) were analyzed.
Data split into training (60%) and test (40%) sets.
Logistic regression identified predictive features; 10 machine learning models were built using radiomics scores.
Cost-sensitive learning and cross-validation were applied.
Extreme tree algorithm created radiomics, echocardiographic (E), and combined models for performance evaluation.

Main Results:

The combined model achieved an AUC of 0.91 in the test set.
Sensitivity was 0.81, specificity 0.83, and F1 score 0.85 for detecting LGE-positive patients.
The combined model demonstrated superior calibration and net benefit compared to radiomic and E-only models.

Conclusions:

Machine learning-based myocardial texture analysis shows promise as a non-invasive tool for predicting myocardial fibrosis in HCM.
This approach is particularly suitable for screening applications.
The model offers an efficient and potentially cost-effective alternative to traditional imaging methods.