The relative role of patient physiology and device optimisation in cardiac resynchronisation therapy: A computational modelling study

Abstract

Cardiac resynchronisation therapy (CRT) is an established treatment for heart failure, however the effective selection of patients and optimisation of therapy remain controversial. While extensive research is ongoing, it remains unclear whether improvements in patient selection or therapy planning offers a greater opportunity for the improvement of clinical outcomes. This computational study investigates the impact of both physiological conditions that guide patient selection and the optimisation of pacing lead placement on CRT outcomes. A multi-scale biophysical model of cardiac electromechanics was developed and personalised to patient data in three patients. These models were separated into components representing cardiac anatomy, pacing lead location, myocardial conductivity and stiffness, afterload, active contraction and conduction block for each individual, and recombined to generate a cohort of 648 virtual patients. The effect of these components on the change in total activation time of the ventricles (ΔTAT) and acute haemodynamic response (AHR) was analysed. The pacing site location was found to have the largest effect on ΔTAT and AHR. Secondary effects on ΔTAT and AHR were found for functional conduction block and cardiac anatomy. The simulation results highlight a need for a greater emphasis on therapy optimisation in order to achieve the best outcomes for patients.

Biophysical Modeling to Determine the Optimization of Left Ventricular Pacing Site and AV/VV Delays in the Acute and Chronic Phase of Cardiac Resynchronization Therapy

“…All patients underwent magnetic resonance imaging (MRI) within 3 months prior to device implantation as a part of standard clinical practice. Segmentations of the 3‐dimensional (3D) whole heart and contrast‐enhanced MR images were used to personalize the cardiac anatomy and scar regions in the models prior to sustained pacing (ACUTE models) . The changes in the cardiac geometry after chronic CRT were represented in the models by deforming the ACUTE models to match segmentations from 2D and 3D echocardiography performed after sustained CRT (CHRONIC models) (see Supplementary Material).…”

“…The volume transients were normalized with regard to the end diastolic volume of the LV. Volume transients were registered to the invasive pressure measurements using simultaneously recorded ECG to generate PV loops at ACUTE and CHRONIC time points, as described previously …”

Personalised Biophysical Model to Optimise Left Ventricle Pacing Location for Cardiac Resynchronisation Therapy Over Time

“…Patient specific meshes were fitted to the segmentations for the patient at the two time points, before and after sustained pacing. Regions of scar tissue were segmented from gadolinium enhanced MR images and mapped to the meshes [9]. Rulebased fiber orientations, based on cadaveric and canine data, varying along the transmural, apical-basal and between the left and right ventricles were assigned to the meshes as previously described in [10].…”

“…The location of the pacing leads on the patient meshes were modeled based on the image registration of the X-ray and MR images [12]. The patient model was personalized by fitting the time taken for the electrical activation over the ventricles to the QRS duration measured before and after sustained pacing with AAI and/or DDD-BiV pacing [9].…”

The opportunities and challenges for biophysical modelling of beneficial and adverse drug actions on the heart

“…Multi-scale biophysical models can also evaluate the relative importance of available data sets 26 . This requires that the model first be validated (in as much as it should consistently predict whole organ effects of drugs of differing molecular specificity and selectivity).…”