Sex dimorphism in the myocardial response to aortic stenosis

Objectives: The goal of this study was to explore sex differences in myocardial remodeling in aortic stenosis (AS) by using echocardiography, cardiac magnetic resonance (CMR), and biomarkers. Background: AS is a disease of both valve and left ventricle (LV). Sex differences in LV remodeling are reported in AS and may play a role in disease phenotyping. Methods: This study was a prospective assessment of patients awaiting surgical valve replacement for severe AS using echocardiography, the 6-min walking test, biomarkers (high-sensitivity troponin T and N-terminal pro-brain natriuretic peptide), and CMR with late gadolinium enhancement and extracellular volume fraction, which dichotomizes the myocardium into matrix and cell volumes. LV remodeling was categorized into normal geometry, concentric remodeling, concentric hypertrophy, and eccentric hypertrophy

Precision measurement of cardiac structure and function in cardiovascular magnetic resonance using machine learning

BACKGROUND: Measurement of cardiac structure and function from images (e.g. volumes, mass and derived parameters such as left ventricular (LV) ejection fraction [LVEF]) guides care for millions. This is best assessed using cardiovascular magnetic resonance (CMR), but image analysis is currently performed by individual clinicians, which introduces error. We sought to develop a machine learning algorithm for volumetric analysis of CMR images with demonstrably better precision than human analysis. METHODS: A fully automated machine learning algorithm was trained on 1923 scans (10 scanner models, 13 institutions, 9 clinical conditions, 60,000 contours) and used to segment the LV blood volume and myocardium. Performance was quantified by measuring precision on an independent multi-site validation dataset with multiple pathologies with n = 109 patients, scanned twice. This dataset was augmented with a further 1277 patients scanned as part of routine clinical care to allow qualitative assessment of generalization ability by identifying mis-segmentations. Machine learning algorithm ('machine') performance was compared to three clinicians ('human') and a commercial tool (cvi42, Circle Cardiovascular Imaging). FINDINGS: Machine analysis was quicker (20 s per patient) than human (13 min). Overall machine mis-segmentation rate was 1 in 479 images for the combined dataset, occurring mostly in rare pathologies not encountered in training. Without correcting these mis-segmentations, machine analysis had superior precision to three clinicians (e.g. scan-rescan coefficients of variation of human vs machine: LVEF 6.0% vs 4.2%, LV mass 4.8% vs. 3.6%; both P < 0.05), translating to a 46% reduction in required trial sample size using an LVEF endpoint. CONCLUSION: We present a fully automated algorithm for measuring LV structure and global systolic function that betters human performance for speed and precision

Reverse myocardial remodeling following valve replacement in patients with aortic stenosis

Background Left ventricular (LV) hypertrophy, a key process in human cardiac disease, results from cellular (hypertrophy) and extracellular matrix expansion (interstitial fibrosis). Objectives This study sought to investigate whether human myocardial interstitial fibrosis in aortic stenosis (AS) is plastic and can regress

Sex dimorphism in the myocardial response to aortic stenosis

Objectives: The goal of this study was to explore sex differences in myocardial remodeling in aortic stenosis (AS) by using echocardiography, cardiac magnetic resonance (CMR), and biomarkers. Background: AS is a disease of both valve and left ventricle (LV). Sex differences in LV remodeling are reported in AS and may play a role in disease phenotyping. Methods: This study was a prospective assessment of patients awaiting surgical valve replacement for severe AS using echocardiography, the 6-min walking test, biomarkers (high-sensitivity troponin T and N-terminal pro-brain natriuretic peptide), and CMR with late gadolinium enhancement and extracellular volume fraction, which dichotomizes the myocardium into matrix and cell volumes. LV remodeling was categorized into normal geometry, concentric remodeling, concentric hypertrophy, and eccentric hypertrophy