AIMC Topic: Cardiomyopathy, Hypertrophic

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Prediction of Genotype Positivity in Patients With Hypertrophic Cardiomyopathy Using Machine Learning.

Circulation. Genomic and precision medicine Apr 23, 2021
BACKGROUND: Genetic testing can determine family screening strategies and has prognostic and diagnostic value in hypertrophic cardiomyopathy (HCM). However, it can also pose a significant psychosocial burden. Conventional scoring systems offer modest...
Humans Machine Learning Female Risk Factors Genotype Models, Genetic Predictive Value of Tests Genetic Testing Cardiomyopathy, Hypertrophic Aged Adult Male Middle Aged Risk Assessment
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Deep learning to diagnose cardiac amyloidosis from cardiovascular magnetic resonance.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Dec 7, 2020
BACKGROUND: Cardiovascular magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidosis (CA). Deep learning (DL) is an application of artificial intelligence that may allow to automatically analyze CMR findings and establish the...
Immunoglobulin Light-chain Amyloidosis Reproducibility of Results Aged Cardiomyopathy, Hypertrophic Aged, 80 and over Deep Learning Hypertrophy, Left Ventricular Humans Male Image Processing, Computer-Assisted Ventricular Function, Left Magnetic Resonance Imaging, Cine Predictive Value of Tests Female Amyloid Neuropathies, Familial Myocardium Ventricular Remodeling
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Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance.

The Lancet. Digital health Dec 3, 2020
BACKGROUND: Left ventricular maximum wall thickness (MWT) is central to diagnosis and risk stratification of hypertrophic cardiomyopathy, but human measurement is prone to variability. We developed an automated machine learning algorithm for MWT meas...
Risk Assessment Reproducibility of Results Magnetic Resonance Imaging Humans Heart Ventricles United Kingdom Cardiomyopathy, Hypertrophic Aged Machine Learning Observer Variation Adult Algorithms Female Male Middle Aged
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Deep learning algorithm to improve hypertrophic cardiomyopathy mutation prediction using cardiac cine images.

European radiology Nov 25, 2020
OBJECTIVES: The high variability of hypertrophic cardiomyopathy (HCM) genetic phenotypes has prompted the establishment of risk-stratification systems that predict the risk of a positive genetic mutation based on clinical and echocardiographic profil...
Humans Female Adult Heart Cardiomyopathy, Hypertrophic Magnetic Resonance Imaging, Cine Male Middle Aged Deep Learning Mutation
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Automated analysis and detection of abnormalities in transaxial anatomical cardiovascular magnetic resonance images: a proof of concept study with potential to optimize image acquisition.

The international journal of cardiovascular imaging Oct 29, 2020
The large number of available MRI sequences means patients cannot realistically undergo them all, so the range of sequences to be acquired during a scan are protocolled based on clinical details. Adapting this to unexpected findings identified early ...
Humans Neural Networks, Computer Reproducibility of Results Magnetic Resonance Imaging Predictive Value of Tests Aorta Cardiomyopathy, Dilated Pleural Effusion Image Interpretation, Computer-Assisted Cardiomyopathy, Hypertrophic Automation Proof of Concept Study
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A Shifting Paradigm in Robotic Heart Surgery: From Single-Procedure Approach to Establishing a Robotic Heart Center of Excellence.

Innovations (Philadelphia, Pa.) May 8, 2020
Lead Poisoning Nobel Prize Myocardial Bridging Pericardiectomy Atrial Fibrillation Mitral Valve Cardiomyopathy, Hypertrophic History, 21st Century Coronary Artery Bypass History, 20th Century Patient Positioning Myocardial Revascularization Congenital Abnormalities Tricuspid Valve Humans Robotic Surgical Procedures Cardiac Surgical Procedures Coronary Artery Bypass, Off-Pump Cardiac Resynchronization Therapy Endoscopy Arrhythmias, Cardiac Aortic Valve Robotics Minimally Invasive Surgical Procedures
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Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca2+ Transient Profiles.

Methods of information in medicine Feb 20, 2020
BACKGROUND:  Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previousl...
Cardiomyopathy, Hypertrophic Tropomyosin Humans Diagnosis, Differential Machine Learning Signal Processing, Computer-Assisted Algorithms Long QT Syndrome Carrier Proteins Calcium
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Three-dimensional Deep Convolutional Neural Networks for Automated Myocardial Scar Quantification in Hypertrophic Cardiomyopathy: A Multicenter Multivendor Study.

Radiology Nov 12, 2019
Background Cardiac MRI late gadolinium enhancement (LGE) scar volume is an important marker for outcome prediction in patients with hypertrophic cardiomyopathy (HCM); however, its clinical application is hindered by a lack of measurement standardizat...
Humans Adolescent Neural Networks, Computer Child Imaging, Three-Dimensional Aged, 80 and over Retrospective Studies Magnetic Resonance Imaging Young Adult Myocardium Cicatrix Female Adult Heart Reproducibility of Results Male Image Interpretation, Computer-Assisted Aged Middle Aged Cardiomyopathy, Hypertrophic
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Assessment of ventricular tachyarrhythmia in patients with hypertrophic cardiomyopathy with machine learning-based texture analysis of late gadolinium enhancement cardiac MRI.

Diagnostic and interventional imaging Nov 11, 2019
OBJECTIVE: To assess the diagnostic value of machine learning-based texture feature analysis of late gadolinium enhancement images on cardiac magnetic resonance imaging (MRI) for assessing the presence of ventricular tachyarrhythmia (VT) in patients ...
Middle Aged Contrast Media Magnetic Resonance Imaging Cardiomyopathy, Hypertrophic Gadolinium Image Enhancement Tachycardia, Ventricular Cardiac Imaging Techniques Female Aged Young Adult Adult Male Humans Machine Learning Retrospective Studies
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Improving the clinical understanding of hypertrophic cardiomyopathy by combining patient data, machine learning and computer simulations: A case study.

Morphologie : bulletin de l'Association des anatomistes Sep 27, 2019
Most patients with hypertrophic cardiomyopathy (HCM), the most common genetic cardiac disease, remain asymptomatic, but others may suffer from sudden cardiac death. A better identification of those patients at risk, together with a better understandi...
Death, Sudden, Cardiac Humans Machine Learning Heart Ventricles Clinical Decision-Making Computer Simulation Patient Selection Risk Factors Cardiomyopathy, Hypertrophic Risk Assessment Asymptomatic Diseases Electrocardiography Models, Cardiovascular Magnetic Resonance Imaging
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