Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance

Augusto, João; Davies, Rhodri H.; Bhuva, Anish; Knott, Kristopher; Seraphim, Andreas; Alfarih, Mashael; Lau, Clement; Hughes, Rebecca; Lopes, Luís Rocha; Shiwani, Hunain; Treibel, Thomas A.; Gerber, Bernhard; Hamilton-Craig, C.; Ntusi, Ntobeko; Pontone, Gianluca; Desai, Milind Y.; Greenwood, John P; Swoboda, Peter; Captur, Gabriella; Cavalcante, João L.; Bucciarelli-Ducci, Chiara; Petersen, Steffen E.; Schelbert, Erik B.; Manisty, Charlotte; Moon, James

doi:10.1016/s2589-7500(20)30267-3

Cited by 73 publications

(46 citation statements)

References 17 publications

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“…The performance of image annotation using this algorithm is equivalent to a consensus of expert human readers and achieves subpixel accuracy for cardiac segmentation ( 13 ). Myocardial wall thickness (WT) was measured along radial line segments connecting the endocardial and epicardial surfaces perpendicular to the myocardial center-line and excluding trabeculae ( Figure 1 ), an approach that also exceeds the reliability of human experts ( 14 ). Chamber volumes and mass were calculated from the segmentations according to standard post-processing guidelines ( 15 ).…”

Section: Methodsmentioning

confidence: 99%

Phenotypic Expression and Outcomes in Individuals With Rare Genetic Variants of Hypertrophic Cardiomyopathy

Marvao

McGurk

Zheng

et al. 2021

Journal of the American College of Cardiology

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Background Hypertrophic cardiomyopathy (HCM) is caused by rare variants in sarcomere-encoding genes, but little is known about the clinical significance of these variants in the general population. Objectives The goal of this study was to compare lifetime outcomes and cardiovascular phenotypes according to the presence of rare variants in sarcomere-encoding genes among middle-aged adults. Methods This study analyzed whole exome sequencing and cardiac magnetic resonance imaging in UK Biobank participants stratified according to sarcomere-encoding variant status. Results The prevalence of rare variants (allele frequency <0.00004) in HCM-associated sarcomere-encoding genes in 200,584 participants was 2.9% (n = 5,712; 1 in 35), and the prevalence of variants pathogenic or likely pathogenic for HCM (SARC-HCM-P/LP) was 0.25% (n = 493; 1 in 407). SARC-HCM-P/LP variants were associated with an increased risk of death or major adverse cardiac events compared with controls (hazard ratio: 1.69; 95% confidence interval [CI]: 1.38-2.07; P < 0.001), mainly due to heart failure endpoints (hazard ratio: 4.23; 95% CI: 3.07-5.83; P < 0.001). In 21,322 participants with both cardiac magnetic resonance imaging and whole exome sequencing, SARC-HCM-P/LP variants were associated with an asymmetric increase in left ventricular maximum wall thickness (10.9 ± 2.7 mm vs 9.4 ± 1.6 mm; P < 0.001), but hypertrophy (≥13 mm) was only present in 18.4% (n = 9 of 49; 95% CI: 9%-32%). SARC-HCM-P/LP variants were still associated with heart failure after adjustment for wall thickness (hazard ratio: 6.74; 95% CI: 2.43-18.7; P < 0.001). Conclusions In this population of middle-aged adults, SARC-HCM-P/LP variants have low aggregate penetrance for overt HCM but are associated with an increased risk of adverse cardiovascular outcomes and an attenuated cardiomyopathic phenotype. Although absolute event rates are low, identification of these variants may enhance risk stratification beyond familial disease.

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Section: Methodsmentioning

confidence: 99%

Phenotypic Expression and Outcomes in Individuals With Rare Genetic Variants of Hypertrophic Cardiomyopathy

Marvao

McGurk

Zheng

et al. 2021

Journal of the American College of Cardiology

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“…CMR data sets will be analysed by a disseminated core-lab technique as previously used in the BSCMR UK valve consortium [ 36 ]. LV structure and function including mass and wall thickness will be analyzed using a clinically validated artificial intelligence (AI) analysis platform [ 37 ]. Left atrial area and global longitudinal shortening will be similarly analyzed by further validated artificial intelligence approaches [ 38 ].…”

Section: Methodsmentioning

confidence: 99%

Demographic, multi-morbidity and genetic impact on myocardial involvement and its recovery from COVID-19: protocol design of COVID-HEART—a UK, multicentre, observational study

Gorecka

McCann

Berry

et al. 2021

Journal of Cardiovascular Magnetic Resonance

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Background Although coronavirus disease 2019 (COVID-19) is primarily a respiratory illness, myocardial injury is increasingly reported and associated with adverse outcomes. However, the pathophysiology, extent of myocardial injury and clinical significance remains unclear. Methods COVID-HEART is a UK, multicentre, prospective, observational, longitudinal cohort study of patients with confirmed COVID-19 and elevated troponin (sex-specific > 99th centile). Baseline assessment will be whilst recovering in-hospital or recently discharged, and include cardiovascular magnetic resonance (CMR) imaging, quality of life (QoL) assessments, electrocardiogram (ECG), serum biomarkers and genetics. Assessment at 6-months includes repeat CMR, QoL assessments and 6-min walk test (6MWT). The CMR protocol includes cine imaging, T1/T2 mapping, aortic distensibility, late gadolinium enhancement (LGE), and adenosine stress myocardial perfusion imaging in selected patients. The main objectives of the study are to: (1) characterise the extent and nature of myocardial involvement in COVID-19 patients with an elevated troponin, (2) assess how cardiac involvement and clinical outcome associate with recognised risk factors for mortality (age, sex, ethnicity and comorbidities) and genetic factors, (3) evaluate if differences in myocardial recovery at 6 months are dependent on demographics, genetics and comorbidities, (4) understand the impact of recovery status at 6 months on patient-reported QoL and functional capacity. Discussion COVID-HEART will provide detailed characterisation of cardiac involvement, and its repair and recovery in relation to comorbidity, genetics, patient-reported QoL measures and functional capacity. Clinical Trial registration: ISRCTN 58667920. Registered 04 August 2020.

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“…Artificial intelligence-based myocardial texture analysis was suggested as a means of differentiating hypertrophic cardiomyopathy from hypertensive heart disease and uremic cardiomyopathy [ 33 ]. Artificial intelligence models have also previously been shown to augment the detection of cardiac amyloidosis and assist in the diagnosis and risk stratification of patients with hypertrophic cardiomyopathy [ 34 , 35 , 36 ]. The role of AI in assessment of patients with increased wall thickness including patients with possible FD is ongoing in our echocardiography laboratory.…”

Section: Diagnosis Of Fabry Cardiomyopathymentioning

confidence: 99%

Fabry Cardiomyopathy: Current Practice and Future Directions

Yim

Yau

Yeung

et al. 2021

Cells

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Fabry disease (FD) is an X-linked lysosomal storage disorder caused by mutations in the galactosidase A (GLA) gene that result in deficient galactosidase A enzyme and subsequent accumulation of glycosphingolipids throughout the body. The result is a multi-system disorder characterized by cutaneous, corneal, cardiac, renal, and neurological manifestations. Increased left ventricular wall thickness represents the predominant cardiac manifestation of FD. As the disease progresses, patients may develop arrhythmias, advanced conduction abnormalities, and heart failure. Cardiac biomarkers, point-of-care dried blood spot testing, and advanced imaging modalities including echocardiography with strain imaging and magnetic resonance imaging (MRI) with T1 mapping now allow us to detect Fabry cardiomyopathy much more effectively than in the past. While enzyme replacement therapy (ERT) has been the mainstay of treatment, several promising therapies are now in development, making early diagnosis of FD even more crucial. Ongoing initiatives involving artificial intelligence (AI)-empowered interpretation of echocardiographic images, point-of-care dried blood spot testing in the echocardiography laboratory, and widespread dissemination of point-of-care ultrasound devices to community practices to promote screening may lead to more timely diagnosis of FD. Fabry disease should no longer be considered a rare, untreatable disease, but one that can be effectively identified and treated at an early stage before the development of irreversible end-organ damage.

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Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance

Cited by 73 publications

References 17 publications

Phenotypic Expression and Outcomes in Individuals With Rare Genetic Variants of Hypertrophic Cardiomyopathy

Phenotypic Expression and Outcomes in Individuals With Rare Genetic Variants of Hypertrophic Cardiomyopathy

Demographic, multi-morbidity and genetic impact on myocardial involvement and its recovery from COVID-19: protocol design of COVID-HEART—a UK, multicentre, observational study

Fabry Cardiomyopathy: Current Practice and Future Directions

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