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Background: Relationships between right ventricular (RV) and left ventricular (LV) shape and function may be useful in determining optimal timing for pulmonary valve replacement in patients with repaired tetralogy of Fallot (rTOF). However, these are multivariate and difficult to quantify. We aimed to quantify variations in biventricular shape associated with pulmonary regurgitant volume (PRV) in rTOF using a biventricular atlas.
Methods: In this cross-sectional retrospective study, a biventricular shape model was customized to cardiovascular magnetic resonance (CMR) images from 88 rTOF patients (median age 16, inter-quartile range 11.8-24.3 years). Morphometric scores quantifying biventricular shape at end-diastole and end-systole were computed using principal component analysis. Multivariate linear regression was used to quantify biventricular shape associations with PRV, corrected for age, sex, height, and weight. Regional associations were confirmed by univariate correlations with distances and angles computed from the models, as well as global systolic strains computed from changes in arc length from end-diastole to end-systole.
Results: PRV was significantly associated with 5 biventricular morphometric scores, independent of covariates, and accounted for 12.3% of total shape variation (p < 0.05). Increasing PRV was associated with RV dilation and basal bulging, in conjunction with decreased LV septal-lateral dimension (LV flattening) and systolic septal motion towards the RV (all p < 0.05). Increased global RV radial, longitudinal, circumferential and LV radial systolic strains were significantly associated with increased PRV (all p < 0.05).
Conclusion: A biventricular atlas of rTOF patients quantified multivariate relationships between left-right ventricular morphometry and wall motion with pulmonary regurgitation. Regional RV dilation, LV reduction, LV septal-lateral flattening and increased RV strain were all associated with increased pulmonary regurgitant volume. Morphometric scores provide simple metrics linking mechanisms for structural and functional alteration with important clinical indices.
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http://dx.doi.org/10.1186/s12968-021-00780-x | DOI Listing |
J Cardiovasc Magn Reson
December 2024
Harvard Medical School, Boston, MA; Department of Cardiology, Boston Children's Hospital. Electronic address:
Background: Patients with hypoplastic left ventricles (LV) who undergo volume-loading procedures (recruitment, biventricular (BIV) repair) are at risk for adverse outcomes including heart failure and death. We investigated pre-BIV LV shape as a predictor of outcome after BIV repair in patients with hypoplastic LVs.
Methods: Baseline and post-recruitment cardiac MRI and CT data were analyzed in patients with hypoplastic LV (< 50 ml/m).
Nat Commun
November 2024
William Harvey Research Institute, Queen Mary University London, Charterhouse Square, London, UK.
APL Mach Learn
September 2024
Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California 94158, USA.
Electrical waves in the heart form rotating spiral or scroll waves during life-threatening arrhythmias, such as atrial or ventricular fibrillation. The wave dynamics are typically modeled using coupled partial differential equations, which describe reaction-diffusion dynamics in excitable media. More recently, data-driven generative modeling has emerged as an alternative to generate spatio-temporal patterns in physical and biological systems.
View Article and Find Full Text PDFEur J Prev Cardiol
September 2024
Heart Centre, Department of Cardiology, Amsterdam University Medical Centers, AMC, Amsterdam.
Aims: To quantitatively analyse exercise-induced cardiac remodeling (EICR) data in female athletes.
Methods: This scoping review included from the databases Medline, Embase, and Google Scholar, peer-reviewed original English-language articles on female athlete-populations aged ≥18 years containing data on electrocardiography (ECG), echocardiography or cardiac magnetic resonance (CMR), and excluded athletes with cardiovascular conditions. From the extracted ECG data, we calculated prevalence percentages, and from the imaging data we compared the results with the upper reference limits of the general female population (URL).
Biomech Model Mechanobiol
October 2024
Department of Mathematics and Statistics, McGill University, Montreal, QC, Canada.
Biomechanics-based patient-specific modeling is a promising approach that has proved invaluable for its clinical potential to assess the adversities caused by ischemic heart disease (IHD). In the present study, we propose a framework to find the passive material properties of the myocardium and the unloaded shape of cardiac ventricles simultaneously in patients diagnosed with ischemic cardiomyopathy (ICM). This was achieved by minimizing the difference between the simulated and the target end-diastolic pressure-volume relationships (EDPVRs) using black-box Bayesian optimization, based on the finite element analysis (FEA).
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