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

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 <i>MYH7</i>, <i>MYBPC3</i>, and <i>TN...

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Principais autores: Mila Glavaški, Aleksandra Ilić, Lazar Velicki
Formato: Artigo
Idioma:English
Publicado em: MDPI AG 2023-12-01
coleção:Cardiogenetics
Assuntos:
Acesso em linha:https://www.mdpi.com/2035-8148/14/1/1
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author Mila Glavaški
Aleksandra Ilić
Lazar Velicki
author_facet Mila Glavaški
Aleksandra Ilić
Lazar Velicki
author_sort Mila Glavaški
collection DOAJ
description 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 <i>MYH7</i>, <i>MYBPC3</i>, and <i>TNNT2</i>. 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 <i>MYH7</i> 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 <i>MYBPC3</i> gene (vs. variant not detected) these were the septum, left ventricle, and left ventricle/chamber; while for variants in the <i>TNNT2</i> gene (vs. variant not detected), the most discriminative structures were the septum and right ventricle.
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spelling doaj.art-afb23697d5274c658e8edbc703f164522024-03-27T13:30:17ZengMDPI AGCardiogenetics2035-82532035-81482023-12-0114112510.3390/cardiogenetics14010001Gene-Specific Discriminative Echocardiogram Findings in Hypertrophic Cardiomyopathy Determined Using Artificial Intelligence: A Pilot StudyMila Glavaški0Aleksandra Ilić1Lazar Velicki2Faculty of Medicine, University of Novi Sad, Hajduk Veljkova 3, 21000 Novi Sad, SerbiaFaculty of Medicine, University of Novi Sad, Hajduk Veljkova 3, 21000 Novi Sad, SerbiaFaculty of Medicine, University of Novi Sad, Hajduk Veljkova 3, 21000 Novi Sad, SerbiaHypertrophic 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 <i>MYH7</i>, <i>MYBPC3</i>, and <i>TNNT2</i>. 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 <i>MYH7</i> 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 <i>MYBPC3</i> gene (vs. variant not detected) these were the septum, left ventricle, and left ventricle/chamber; while for variants in the <i>TNNT2</i> gene (vs. variant not detected), the most discriminative structures were the septum and right ventricle.https://www.mdpi.com/2035-8148/14/1/1hypertrophic cardiomyopathygene<i>MYH7</i><i>MYBPC3</i><i>TNNT2</i>variant
spellingShingle Mila Glavaški
Aleksandra Ilić
Lazar Velicki
Gene-Specific Discriminative Echocardiogram Findings in Hypertrophic Cardiomyopathy Determined Using Artificial Intelligence: A Pilot Study
Cardiogenetics
hypertrophic cardiomyopathy
gene
<i>MYH7</i>
<i>MYBPC3</i>
<i>TNNT2</i>
variant
title Gene-Specific Discriminative Echocardiogram Findings in Hypertrophic Cardiomyopathy Determined Using Artificial Intelligence: A Pilot Study
title_full Gene-Specific Discriminative Echocardiogram Findings in Hypertrophic Cardiomyopathy Determined Using Artificial Intelligence: A Pilot Study
title_fullStr Gene-Specific Discriminative Echocardiogram Findings in Hypertrophic Cardiomyopathy Determined Using Artificial Intelligence: A Pilot Study
title_full_unstemmed Gene-Specific Discriminative Echocardiogram Findings in Hypertrophic Cardiomyopathy Determined Using Artificial Intelligence: A Pilot Study
title_short Gene-Specific Discriminative Echocardiogram Findings in Hypertrophic Cardiomyopathy Determined Using Artificial Intelligence: A Pilot Study
title_sort gene specific discriminative echocardiogram findings in hypertrophic cardiomyopathy determined using artificial intelligence a pilot study
topic hypertrophic cardiomyopathy
gene
<i>MYH7</i>
<i>MYBPC3</i>
<i>TNNT2</i>
variant
url https://www.mdpi.com/2035-8148/14/1/1
work_keys_str_mv AT milaglavaski genespecificdiscriminativeechocardiogramfindingsinhypertrophiccardiomyopathydeterminedusingartificialintelligenceapilotstudy
AT aleksandrailic genespecificdiscriminativeechocardiogramfindingsinhypertrophiccardiomyopathydeterminedusingartificialintelligenceapilotstudy
AT lazarvelicki genespecificdiscriminativeechocardiogramfindingsinhypertrophiccardiomyopathydeterminedusingartificialintelligenceapilotstudy