bioRxiv Science⌕ Search

Biology subjects

Margara, F.

Publications and source records attributed to Margara, F..

2 recordsLinked to original sources

Calibration and validation strategy for electromechanical cardiac digital twins

State-of-the-art cardiac electromechanical modelling and simulation form the basis for recent developments in cardiac Digital Twin technologies. However, a comprehensive evaluation of electromechanical models at cellular, tissue, and organ level has yet to be performed that addresses both ECG and pressure-volume biomarkers. Such an evaluation would build credibility for applications of cardiac Digital Twins in clinical research and therapy development. We aimed to follow ASME V&V40 standards for calibration, validation, and sensitivity analysis of ventricular electromechanical models under healthy conditions, to progress towards the Digital Twin vision. We performed a multi-scaled review of ventricular electromechanics and compiled a dataset for calibration and validation incorporating ECG, pressure-volume, displacement, and strain biomarkers. When applied to a biventricular multiscale model, we achieved healthy calibrated values for the QRS duration (89 ms), QT interval (360 ms), left ventricular ejection fraction (LVEF) (51 %), peak systolic pressure (14 kPa), end diastolic (105 mL) and end systolic volumes (51 mL), peak ejection flow rate (180 mL/ms). Model validation was performed by comparison to displacement and strain biomarkers including systolic atrioventricular plane displacement (1.5 cm), systolic fibre strain (-0.18) and longitudinal strain (-0.15). Sensitivity analysis of model parameters at cellular and ventricular scales was also performed to inform model calibration and as a first step towards uncertainty quantification. We quantified the effects of variability in ionic conductance, mechanical stiffness, cross-bridge cycling dynamics, and systemic circulation on action potential and active tension dynamics at the cellular scale, and on ECG, pressure-volume, displacement, and strain biomarkers at the ventricular scale. Simulations showed that the relationship between healthy LVEF and T wave biomarkers was primarily underpinned by variability in L-type calcium channel conductance and SERCA activity through multi-scale effects. In this study, we provide a systematic framework for credibility assessment of cardiac electromechanical models based on both ECG and mechanical biomarkers, as a foundational step towards the cardiac Digital Twin vision.

bioengineering↗

Human iPSC-CMs and in-silico technologies define mechanisms and accelerate targeted pharmacogenetics in hypertrophic cardiomyopathy

Cardiomyopathies have unresolved genotype-phenotype relationships and lack disease-specific treatments. Here we identify genotype-specific pathomechanisms and therapeutic targets combining experimental hiPSC-CM modelling and human-based cardiac electromechanical in-silico modelling and simulation bridging from specific mutations to clinical biomarkers. We select hypertrophic cardiomyopathy as a challenge for this approach and study genetic variations that mutate proteins of the thick (MYH7R403Q/+) and thin filaments (TNNT2R92Q/+, TNNI3R21C/+) of the cardiac sarcomere. We show that destabilisation of myosin super relaxation drives disease in MYH7R403Q/+ with secondary effects on thin filament activation, which are corrected by Mavacamten. Thin filament variants TNNT2R92Q/+ and TNNI3R21C/+ share calcium regulation-related pathomechanisms, for which Mavacamten provides incomplete salvage. We define the ideal characteristics of a novel thin filament-targeting compound and show its efficacy in-silico. We demonstrate that hybrid human-based hiPSC-CM and in-silico studies accelerate pathomechanism discovery and classification testing, improving clinical interpretation of genetic variants, and directing rational therapeutic targeting and design.

bioengineering↗