Gene-Specific Discriminative Echocardiogram Findings in Hypertrophic Cardiomyopathy Determined Using Artificial Intelligence: A Pilot Study

Author:

Glavaški Mila1ORCID,Ilić Aleksandra12,Velicki Lazar12ORCID

Affiliation:

1. Faculty of Medicine, University of Novi Sad, Hajduk Veljkova 3, 21000 Novi Sad, Serbia

2. Institute of Cardiovascular Diseases Vojvodina, Put Doktora Goldmana 4, 21204 Sremska Kamenica, Serbia

Abstract

Hypertrophic cardiomyopathy (HCM) is among the most common forms of cardiomyopathies, with a prevalence of 1:200 to 1:500 people. HCM is caused by variants in genes encoding cardiac sarcomeric proteins, of which a majority reside in MYH7, MYBPC3, and TNNT2. Up to 40% of the HCM cases do not have any known HCM variant. Genotype–phenotype associations in HCM remain incompletely understood. This study involved two visits of 46 adult patients with a confirmed diagnosis of HCM. In total, 174 genes were analyzed on the Next-Generation Sequencing platform, and transthoracic echocardiography was performed. Gene-specific discriminative echocardiogram findings were identified using the computer vision library Fast AI. This was accomplished with the generation of deep learning models for the classification of ultrasonic images based on the underlying genotype and a later analysis of the most decisive image regions. Gene-specific echocardiogram findings were identified: for variants in the MYH7 gene (vs. variant not detected), the most discriminative structures were the septum, left ventricular outflow tract (LVOT) segment, anterior wall, apex, right ventricle, and mitral apparatus; for variants in MYBPC3 gene (vs. variant not detected) these were the septum, left ventricle, and left ventricle/chamber; while for variants in the TNNT2 gene (vs. variant not detected), the most discriminative structures were the septum and right ventricle.

Funder

Autonomous Province of Vojvodina

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences,General Environmental Science

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