Optimizing electrical efficacy of leadless cardiac resynchronization therapy and leadless left ventricular septal pacing: Insights on left and right ventricular activation from electrocardiographic imaging.

Background: Leadless cardiac resynchronization therapy (CRT) is an emerging heart failure treatment. An implanted electrode delivers lateral or septal endocardial left ventricular (LV) pacing (LVP) upon detection of a right ventricular (RV) pacing stimulus from a coimplanted device, thus generating biventricular pacing (BiVP). Electrical efficacy data regarding this therapy, particularly leadless LV septal pacing (LVSP) for potential conduction system capture, are limited. Objectives: The purpose of this study was to evaluate the acute performance of leadless CRT using electrocardiographic imaging (ECGi) and assess the optimal pacing modality (OPM) of LVSP on the basis of RV and LV activation. Methods: Ten WiSE-CRT recipients underwent an ECGi study testing: RV pacing, BiVP, LVP only, and LVP with an optimized atrioventricular delay (LV-OPT). BiV, LV, and RV activation times (shortest time taken to activate 90% of the ventricles [BIVAT-90], shortest time taken to activate 95% of the LV, and shortest time taken to activate 90% of the RV) plus LV and BiV dyssynchrony index (standard deviation of LV activation times and standard deviation of all activation times) were calculated from reconstructed epicardial electrograms. The individual OPM yielding the greatest improvement from baseline was determined. Results: BiVP generated a 23.7% improvement in BiVAT-90 (P = .002). An improvement of 43.3% was observed at the OPM (P = .0001), primarily through reductions in shortest time taken to activate 90% of the RV. At the OPM, BiVAT-90 improved in patients with lateral (43.3%; P = .0001; n = 5) and septal (42.4%; P = .009; n = 5) LV implants. The OPM varied by individual. LVP and LV-OPT were mostly superior in patients with LVSP, and in those with sinus rhythm and left bundle branch block (n = 4). Conclusion: Leadless CRT significantly improves acute ECGi-derived activation and dyssynchrony metrics. Using an individualized OPM improves efficacy in selected patients. Effective LVSP is feasible, with fusion pacing at LV-OPT mitigating the potential deleterious effects on RV activation.

Left ventricular electrical delay predicts volumetric response to leadless cardiac resynchronization therapy.

BACKGROUND: Leadless left ventricular (LV) endocardial pacing is an emerging cardiac resynchronization therapy (CRT) technology. Predictors of response to leadless CRT are poorly understood. Implanting the LV endocardial pacing electrode in sites with increased electrical latency (Q-LV) may improve response rates. OBJECTIVE: The purpose of this study was to examine the association between Q-LV and echocardiographic remodeling response to leadless CRT delivered with the WiSE-CRT system. METHODS: A post hoc analysis (n = 122) of the SOLVE-CRT trial examined the relationship between LV pacing site Q-LV with rate of left ventricular end-systolic volume (LVESV) reduction >15% at 6 months. Multivariable regression analysis, adjusting for age, sex, previous CRT nonresponse, cardiomyopathy etiology, QRS morphology, and QRS duration was performed, followed by receiver operating characteristic analysis and analysis of variance by Q-LV quartile. A subgroup analysis of the ischemic cardiomyopathy cohort was undertaken. RESULTS: Complete Q-LV data were available for 122 of 153 patients (80%) in the active arms SOLVE-CRT. Overall, the 6-month LVESV response rate was 46%. Logistic regression identified Q-LV as an independent response predictor with borderline significance (adjusted odds ratio 1.015; P = .05). Analysis by Q-LV quartile demonstrated a significant improvement in response rate in quartile 4 (longest Q-LV 64%) compared to quartile 1 (shortest Q-LV 28%) (P <.01). This association was primarily driven by strong Q-LV-response correlation in patients with ischemic cardiomyopathy, demonstrated by subgroup logistic regression (adjusted odds ratio 1.034; P = .004). CONCLUSION: Increased Q-LV was associated with improved reverse remodeling following leadless CRT. Targeting LV endocardial sites of high Q-LV may deliver additional benefit compared to empirical LV electrode implantation.

Observable Atrial and Ventricular Fibrillation Episode Durations Are Conformant With a Power Law Based on System Size and Spatial Synchronization.

BACKGROUND: Atrial fibrillation (AF) and ventricular fibrillation (VF) episodes exhibit varying durations, with some spontaneously ending quickly while others persist. A quantitative framework to explain episode durations remains elusive. We hypothesized that observable self-terminating AF and VF episode lengths, whereby durations are known, would conform with a power law based on the ratio of system size and correlation length ([Formula: see text]. METHODS: Using data from computer simulations (2-dimensional sheet and 3-dimensional left-atrial), human ischemic VF recordings (256-electrode sock, n=12 patients), and human AF recordings (64-electrode basket-catheter, n=9 patients; 16-electrode high definition-grid catheter, n=42 patients), conformance with a power law was assessed using the Akaike information criterion, Bayesian information criterion, coefficient of determination (R2, significance=P<0.05) and maximum likelihood estimation. We analyzed fibrillatory episode durations and [Formula: see text], computed by taking the ratio between system size ([Formula: see text], chamber/simulation size) and correlation length (xi, estimated from pairwise correlation coefficients over electrode/node distance). RESULTS: In all computer models, the relationship between episode durations and [Formula: see text] was conformant with a power law (Aliev-Panfilov R2: 0.90, P<0.001; Courtemanche R2: 0.91, P<0.001; Luo-Rudy R2: 0.61, P<0.001). Observable clinical AF/VF durations were also conformant with a power law relationship (VF R2: 0.86, P<0.001; AF basket R2: 0.91, P<0.001; AF grid R2: 0.92, P<0.001). [Formula: see text] also differentiated between self-terminating and sustained episodes of AF and VF (P<0.001; all systems), as well as paroxysmal versus persistent AF (P<0.001). In comparison, other electrogram metrics showed no statistically significant differences (dominant frequency, Shannon Entropy, mean voltage, peak-peak voltage; P>0.05). CONCLUSIONS: Observable fibrillation episode durations are conformant with a power law based on system size and correlation length.

Heart Size Difference Drives Sex-Specific Response to Cardiac Resynchronization Therapy: A Post Hoc Analysis of the MORE-MPP CRT Trial.

BACKGROUND: Studies have reported that female sex predicts superior cardiac resynchronization therapy (CRT) response. One theory is that this association is related to smaller female heart size, thus increased relative dyssynchrony at a given QRS duration (QRSd). Our objective was to investigate the mechanisms of sex-specific CRT response relating to heart size, relative dyssynchrony, cardiomyopathy type, QRS morphology, and other patient characteristics. METHODS AND RESULTS: This is a post hoc analysis of the MORE-CRT MPP (More Response on Cardiac Resynchronization Therapy with Multipoint Pacing)  trial (n=3739, 28% women), with a subgroup analysis of patients with nonischemic cardiomyopathy and left bundle-branch block (n=1308, 41% women) to control for confounding characteristics. A multivariable analysis examined predictors of response to 6 months of conventional CRT, including sex and relative dyssynchrony, measured by QRSd/left ventricular end-diastolic volume (LVEDV). Women had a higher CRT response rate than men (70.1% versus 56.8%, P<0.0001). In subgroup analysis, regression analysis of the nonischemic cardiomyopathy left bundle-branch block subgroup identified QRSd/LVEDV, but not sex, as a modifier of CRT response (P<0.0039). QRSd/LVEDV was significantly higher in women (0.919) versus men (0.708, P<0.001). CRT response was 78% for female patients with QRSd/LVEDV greater than the median value, compared with 68% with QRSd/LVEDV less than the median value (P=0.012). The association between CRT response and QRSd/LVEDV was strongest at QRSd <150 ms. CONCLUSIONS: In the nonischemic cardiomyopathy left bundle-branch block population, increased relative dyssynchrony in women, who have smaller heart sizes than their male counterparts, is a driver of sex-specific CRT response, particularly at QRSd <150 ms. Women may benefit from CRT at a QRSd <130 ms, opening the debate on whether sex-specific QRSd cutoffs or QRS/LVEDV measurement should be incorporated into clinical guidelines.

Evaluation of deep learning estimation of whole heart anatomy from automated cardiovascular magnetic resonance short- and long-axis analyses in UK Biobank.

AIMS: Standard methods of heart chamber volume estimation in cardiovascular magnetic resonance (CMR) typically utilize simple geometric formulae based on a limited number of slices. We aimed to evaluate whether an automated deep learning neural network prediction of 3D anatomy of all four chambers would show stronger associations with cardiovascular risk factors and disease than standard volume estimation methods in the UK Biobank. METHODS AND RESULTS: A deep learning network was adapted to predict 3D segmentations of left and right ventricles (LV, RV) and atria (LA, RA) at ∼1 mm isotropic resolution from CMR short- and long-axis 2D segmentations obtained from a fully automated machine learning pipeline in 4723 individuals with cardiovascular disease (CVD) and 5733 without in the UK Biobank. Relationships between volumes at end-diastole (ED) and end-systole (ES) and risk/disease factors were quantified using univariate, multivariate, and logistic regression analyses. Strength of association between deep learning volumes and standard volumes was compared using the area under the receiving operator characteristic curve (AUC). Univariate and multivariate associations between deep learning volumes and most risk and disease factors were stronger than for standard volumes (higher R2 and more significant P-values), particularly for sex, age, and body mass index. AUCs for all logistic regressions were higher for deep learning volumes than standard volumes (P < 0.001 for all four chambers at ED and ES). CONCLUSION: Neural network reconstructions of whole heart volumes had significantly stronger associations with CVD and risk factors than standard volume estimation methods in an automatic processing pipeline.

Cardiac length-dependent activation driven by force-dependent thick-filament dynamics.

The length-dependent activation (LDA) of maximum force and calcium sensitivity are established features of cardiac muscle contraction but the dominant underlying mechanisms remain to be fully clarified. Alongside the well-documented regulation of contraction via the thin filaments, experiments have identified an additional force-dependent thick-filament activation, whereby myosin heads parked in a so-called off state become available to generate force. This process produces a feedback effect that may potentially drive LDA. Using biomechanical modeling of a human left-ventricular myocyte, this study investigates the extent to which the off-state dynamics could, by itself, plausibly account for LDA, depending on the specific mathematical formulation of the feedback. We hypothesized four different models of the off-state regulatory feedback based on (A) total force, (B) active force, (C) sarcomere strain, and (D) passive force. We tested if these models could reproduce the isometric steady-state and dynamic LDA features predicted by an earlier published model of a human left-ventricle myocyte featuring purely phenomenological length dependences. The results suggest that only total-force feedback (A) is capable of reproducing the expected behaviors, but that passive tension could provide a length-dependent signal on which to initiate the feedback. Furthermore, by attributing LDA to off-state dynamics, our proposed model also qualitatively reproduces experimentally observed effects of the off-state-stabilizing drug mavacamten. Taken together, these results support off-state dynamics as a plausible primary mechanism underlying LDA.

Performance of Image-navigated and Diaphragm-navigated 3D Late Gadolinium-enhanced Cardiac MRI for the Assessment of Atrial Fibrosis.

Purpose To perform a qualitative and quantitative evaluation of the novel image-navigated (iNAV) 3D late gadolinium enhancement (LGE) cardiac MRI imaging strategy in comparison with the conventional diaphragm-navigated (dNAV) 3D LGE cardiac MRI strategy for the assessment of left atrial fibrosis in atrial fibrillation (AF). Materials and Methods In this prospective study conducted between April and September 2022, 26 consecutive participants with AF (mean age, 61 ± 11 years; 19 male) underwent both iNAV and dNAV 3D LGE cardiac MRI, with equivalent spatial resolution and timing in the cardiac cycle. Participants were randomized in the acquisition order of iNAV and dNAV. Both, iNAV-LGE and dNAV-LGE images were analyzed qualitatively using a 5-point Likert scale and quantitatively (percentage of atrial fibrosis using image intensity ratio threshold 1.2), including testing for overlap in atrial fibrosis areas by calculating Dice score. Results Acquisition time of iNAV was significantly lower compared with dNAV (4.9 ± 1.1 minutes versus 12 ± 4 minutes, P < .001, respectively). There was no evidence of a difference in image quality for all prespecified criteria between iNAV and dNAV, although dNAV was the preferred image strategy in two-thirds of cases (17/26, 65%). Quantitative assessment demonstrated that mean fibrosis scores were lower for iNAV compared with dNAV (12 ± 8% versus 20 ± 12%, P < .001). Spatial correspondence between the atrial fibrosis maps was modest (Dice similarity coefficient, 0.43 ± 0.15). Conclusion iNAV-LGE acquisition in individuals with AF was more than twice as fast as dNAV acquisition but resulted in a lower atrial fibrosis score. The differences between these two strategies might impact clinical interpretation. ©RSNA, 2024.

Neural network emulation of the human ventricular cardiomyocyte action potential for more efficient computations in pharmacological studies.

Computer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimental data can become a significant computational burden. To mitigate the computational burden, the present study introduces a neural network (NN) that emulates the AP for given maximum conductances of selected ion channels, pumps, and exchangers. Its applicability in pharmacological studies was tested on synthetic and experimental data. The NN emulator potentially enables massive speed-ups compared to regular simulations and the forward problem (find drugged AP for pharmacological parameters defined as scaling factors of control maximum conductances) on synthetic data could be solved with average root-mean-square errors (RMSE) of 0.47 mV in normal APs and of 14.5 mV in abnormal APs exhibiting early afterdepolarizations (72.5% of the emulated APs were alining with the abnormality, and the substantial majority of the remaining APs demonstrated pronounced proximity). This demonstrates not only very fast and mostly very accurate AP emulations but also the capability of accounting for discontinuities, a major advantage over existing emulation strategies. Furthermore, the inverse problem (find pharmacological parameters for control and drugged APs through optimization) on synthetic data could be solved with high accuracy shown by a maximum RMSE of 0.22 in the estimated pharmacological parameters. However, notable mismatches were observed between pharmacological parameters estimated from experimental data and distributions obtained from the Comprehensive in vitro Proarrhythmia Assay initiative. This reveals larger inaccuracies which can be attributed particularly to the fact that small tissue preparations were studied while the emulator was trained on single cardiomyocyte data. Overall, our study highlights the potential of NN emulators as powerful tool for an increased efficiency in future quantitative systems pharmacology studies.

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations.

Cardiac digital twins provide a physics and physiology informed framework to deliver personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs. Artificial Intelligence-based methods can make the creation of fast and accurate whole-heart digital twins feasible. We use Latent Neural Ordinary Differential Equations (LNODEs) to learn the pressure-volume dynamics of a heart failure patient. Our surrogate model is trained from 400 simulations while accounting for 43 parameters describing cell-to-organ cardiac electromechanics and cardiovascular hemodynamics. LNODEs provide a compact representation of the 3D-0D model in a latent space by means of an Artificial Neural Network that retains only 3 hidden layers with 13 neurons per layer and allows for numerical simulations of cardiac function on a single processor. We employ LNODEs to perform global sensitivity analysis and parameter estimation with uncertainty quantification in 3 hours of computations, still on a single processor.

A three-dimensional left atrial motion estimation from retrospective gated computed tomography: application in heart failure patients with atrial fibrillation.

Background: A reduced left atrial (LA) strain correlates with the presence of atrial fibrillation (AF). Conventional atrial strain analysis uses two-dimensional (2D) imaging, which is, however, limited by atrial foreshortening and an underestimation of through-plane motion. Retrospective gated computed tomography (RGCT) produces high-fidelity three-dimensional (3D) images of the cardiac anatomy throughout the cardiac cycle that can be used for estimating 3D mechanics. Its feasibility for LA strain measurement, however, is understudied. Aim: The aim of this study is to develop and apply a novel workflow to estimate 3D LA motion and calculate the strain from RGCT imaging. The utility of global and regional strains to separate heart failure in patients with reduced ejection fraction (HFrEF) with and without AF is investigated. Methods: A cohort of 30 HFrEF patients with (n = 9) and without (n = 21) AF underwent RGCT prior to cardiac resynchronisation therapy. The temporal sparse free form deformation image registration method was optimised for LA feature tracking in RGCT images and used to estimate 3D LA endocardial motion. The area and fibre reservoir strains were calculated over the LA body. Universal atrial coordinates and a human atrial fibre atlas enabled the regional strain calculation and the fibre strain calculation along the local myofibre orientation, respectively. Results: It was found that global reservoir strains were significantly reduced in the HFrEF + AF group patients compared with the HFrEF-only group patients (area strain: 11.2 ± 4.8% vs. 25.3 ± 12.6%, P = 0.001; fibre strain: 4.5 ± 2.0% vs. 15.2 ± 8.8%, P = 0.001), with HFrEF + AF patients having a greater regional reservoir strain dyssynchrony. All regional reservoir strains were reduced in the HFrEF + AF patient group, in whom the inferior wall strains exhibited the most significant differences. The global reservoir fibre strain and LA volume + posterior wall reservoir fibre strain exceeded LA volume alone and 2D global longitudinal strain (GLS) for AF classification (area-under-the-curve: global reservoir fibre strain: 0.94 ± 0.02, LA volume + posterior wall reservoir fibre strain: 0.95 ± 0.02, LA volume: 0.89 ± 0.03, 2D GLS: 0.90 ± 0.03). Conclusion: RGCT enables 3D LA motion estimation and strain calculation that outperforms 2D strain metrics and LA enlargement for AF classification. Differences in regional LA strain could reflect regional myocardial properties such as atrial fibrosis burden.

Using Gaussian process for velocity reconstruction after coronary stenosis applicable in positron emission particle tracking: An in-silico study.

Accurate velocity reconstruction is essential for assessing coronary artery disease. We propose a Gaussian process method to reconstruct the velocity profile using the sparse data of the positron emission particle tracking (PEPT) in a biological environment, which allows the measurement of tracer particle velocity to infer fluid velocity fields. We investigated the influence of tracer particle quantity and detection time interval on flow reconstruction accuracy. Three models were used to represent different levels of stenosis and anatomical complexity: a narrowed straight tube, an idealized coronary bifurcation with stenosis, and patient-specific coronary arteries with a stenotic left circumflex artery. Computational fluid dynamics (CFD), particle tracking, and the Gaussian process of kriging were employed to simulate and reconstruct the pulsatile flow field. The study examined the error and uncertainty in velocity profile reconstruction after stenosis by comparing particle-derived flow velocity with the CFD solution. Using 600 particles (15 batches of 40 particles) released in the main coronary artery, the time-averaged error in velocity reconstruction ranged from 13.4% (no occlusion) to 161% (70% occlusion) in patient-specific anatomy. The error in maximum cross-sectional velocity at peak flow was consistently below 10% in all cases. PEPT and kriging tended to overestimate area-averaged velocity in higher occlusion cases but accurately predicted maximum cross-sectional velocity, particularly at peak flow. Kriging was shown to be useful to estimate the maximum velocity after the stenosis in the absence of negative near-wall velocity.

Heart size disparity drives sex-specific response to cardiac resynchronization therapy: a post-hoc analysis of the MORE-MPP CRT trial.

Background: Studies have reported that female sex predicts superior cardiac resynchronization therapy (CRT) response. One theory is that this association is related to smaller female heart size, thus increased "relative dyssynchrony" at given QRS durations (QRSd). Objective: To investigate the mechanisms of sex-specific CRT response relating to heart size, relative dyssynchrony, cardiomyopathy type, QRS morphology, and other patient characteristics. Methods: A post-hoc analysis of the MORE-CRT MPP trial (n=3739, 28% female), with a sub-group analysis of patients with non-ischaemic cardiomyopathy (NICM) and left bundle branch block (LBBB) (n=1308, 41% female) to control for confounding characteristics. A multivariable analysis examined predictors of response to 6 months of conventional CRT, including sex and relative dyssynchrony, measured by QRSd/LVEDV (left ventricular end-diastolic volume). Results: Females had a higher CRT response rate than males (70.1% vs. 56.8%, p<0.0001). Subgroup analysis: Regression analysis of the NICM LBBB subgroup identified QRSd/LVEDV, but not sex, as a modifier of CRT response (p<0.0039). QRSd/LVEDV was significantly higher in females (0.919) versus males (0.708, p<0.001). CRT response was 78% for female patients with QRSd/LVEDV>median value, compared to 68% < median value (p=0.012). Association between CRT response and QRSd/LVEDV was strongest at QRSd<150ms. Conclusions: In the NICM LBBB population, increased relative dyssynchrony in females, who have smaller heart sizes than their male counterparts, is a driver of sex-specific CRT response, particularly at QRSd <150ms. Females may benefit from CRT at a QRSd <130ms, opening the debate on whether sex-specific QRSd cut-offs or QRS/LVEDV measurement should be incorporated into clinical guidelines.

Cost-effectiveness analysis of leadless cardiac resynchronization therapy.

BACKGROUND: The Wireless Stimulation Endocardially for CRT (WiSE-CRT) system is a novel technology used to treat patients with dyssynchronous heart failure (HF) by providing leadless cardiac resynchronization therapy (CRT). Observational studies have demonstrated its safety and efficacy profile, however, the treatment cost-effectiveness has not previously been examined. METHODS: A cost-effectiveness evaluation of the WiSE-CRT System was performed using a cohort-based economic model adopting a "proportion in state" structure. In addition to the primary analysis, scenario analyses and sensitivity analyses were performed to test for uncertainty in input parameters. Outcomes were quantified in terms of quality-adjusted life year (QALY) differences. RESULTS: The primary analysis demonstrated that treatment with the WiSE-CRT system is likely to be cost-effective over a lifetime horizon at a QALY reimbursement threshold of £20 000, with a net monetary benefit (NMB) of £3781 per QALY. Cost-effectiveness declines at time horizons shorter than 10 years. Sensitivity analyses demonstrated that average system battery life had the largest impact on potential cost-effectiveness. CONCLUSION: Within the model limitations, these findings support the use of WiSE-CRT in indicated patients from an economic standpoint. However, improving battery technology should be prioritized to maximize cost-effectiveness in times when health services are under significant financial pressures.

Computational Modelling Enabling In Silico Trials for Cardiac Physiologic Pacing.

Conduction system pacing (CSP) has the potential to achieve physiological-paced activation by pacing the ventricular conduction system. Before CSP is adopted in standard clinical practice, large, randomised, and multi-centre trials are required to investigate CSP safety and efficacy compared to standard biventricular pacing (BVP). Furthermore, there are unanswered questions about pacing thresholds required to achieve optimal pacing delivery while preventing device battery draining, and about which patient groups are more likely to benefit from CSP rather than BVP. In silico studies have been increasingly used to investigate mechanisms underlying changes in cardiac function in response to pathologies and treatment. In the context of CSP, they have been used to improve our understanding of conduction system capture to optimise CSP delivery and battery life, and noninvasively compare different pacing methods on different patient groups. In this review, we discuss the in silico studies published to date investigating different aspects of CSP delivery.

Managing arrhythmia in cardiac resynchronisation therapy.

Arrhythmia is an extremely common finding in patients receiving cardiac resynchronisation therapy (CRT). Despite this, in the majority of randomised trials testing CRT efficacy, patients with a recent history of arrhythmia were excluded. Most of our knowledge into the management of arrhythmia in CRT is therefore based on arrhythmia trials in the heart failure (HF) population, rather than from trials dedicated to the CRT population. However, unique to CRT patients is the aim to reach as close to 100% biventricular pacing (BVP) as possible, with HF outcomes greatly influenced by relatively small changes in pacing percentage. Thus, in comparison to the average HF patient, there is an even greater incentive for controlling arrhythmia, to achieve minimal interference with the effective delivery of BVP. In this review, we examine both atrial and ventricular arrhythmias, addressing their impact on CRT, and discuss the available evidence regarding optimal arrhythmia management in this patient group. We review pharmacological and procedural-based approaches, and lastly explore novel ways of harnessing device data to guide treatment of arrhythmia in CRT.

Guided implantation of a leadless left ventricular endocardial electrode and acoustic transmitter using computed tomography anatomy, dynamic perfusion and mechanics, and predicted activation pattern.

BACKGROUND: The WiSE-CRT System (EBR systems, Sunnyvale, CA) permits leadless left ventricular pacing. Currently, no intraprocedural guidance is used to target optimal electrode placement while simultaneously guiding acoustic transmitter placement in close proximity to the electrode to ensure adequate power delivery. OBJECTIVE: The purpose of this study was to assess the use of computed tomography (CT) anatomy, dynamic perfusion and mechanics, and predicted activation pattern to identify both the optimal electrode and transmitter locations. METHODS: A novel CT protocol was developed using preprocedural imaging and simulation to identify target segments (TSs) for electrode implantation, with late electrical and mechanical activation, with ≥5 mm wall thickness without perfusion defects. Modeling of the acoustic intensity from different transmitter implantation sites to the TSs was used to identify the optimal transmitter location. During implantation, TSs were overlaid on fluoroscopy to guide optimal electrode location that were evaluated by acute hemodynamic response (AHR) by measuring the maximal rate of left ventricular pressure rise with biventricular pacing. RESULTS: Ten patients underwent the implantation procedure. The transmitter could be implanted within the recommended site on the basis of preprocedural analysis in all patients. CT identified a mean of 4.8 ± 3.5 segments per patient with wall thickness < 5 mm. During electrode implantation, biventricular pacing within TSs resulted in a significant improvement in AHR vs non-TSs (25.5% ± 8.8% vs 12.9% ± 8.6%; P < .001). Pacing in CT-identified scar resulted in either failure to capture or minimal AHR improvement. The electrode was targeted to the TSs in all patients and was implanted in the TSs in 80%. CONCLUSION: Preprocedural imaging and modeling data with intraprocedural guidance can successfully guide WiSE-CRT electrode and transmitter implantation to allow optimal AHR and adequate power delivery.

Cell to whole organ global sensitivity analysis on a four-chamber heart electromechanics model using Gaussian processes emulators.

Cardiac pump function arises from a series of highly orchestrated events across multiple scales. Computational electromechanics can encode these events in physics-constrained models. However, the large number of parameters in these models has made the systematic study of the link between cellular, tissue, and organ scale parameters to whole heart physiology challenging. A patient-specific anatomical heart model, or digital twin, was created. Cellular ionic dynamics and contraction were simulated with the Courtemanche-Land and the ToR-ORd-Land models for the atria and the ventricles, respectively. Whole heart contraction was coupled with the circulatory system, simulated with CircAdapt, while accounting for the effect of the pericardium on cardiac motion. The four-chamber electromechanics framework resulted in 117 parameters of interest. The model was broken into five hierarchical sub-models: tissue electrophysiology, ToR-ORd-Land model, Courtemanche-Land model, passive mechanics and CircAdapt. For each sub-model, we trained Gaussian processes emulators (GPEs) that were then used to perform a global sensitivity analysis (GSA) to retain parameters explaining 90% of the total sensitivity for subsequent analysis. We identified 45 out of 117 parameters that were important for whole heart function. We performed a GSA over these 45 parameters and identified the systemic and pulmonary peripheral resistance as being critical parameters for a wide range of volumetric and hemodynamic cardiac indexes across all four chambers. We have shown that GPEs provide a robust method for mapping between cellular properties and clinical measurements. This could be applied to identify parameters that can be calibrated in patient-specific models or digital twins, and to link cellular function to clinical indexes.

A systematic review of cardiac in-silico clinical trials.

Computational models of the heart are now being used to assess the effectiveness and feasibility of interventions through in-silico clinical trials (ISCTs). As the adoption and acceptance of ISCTs increases, best practices for reporting the methodology and analysing the results will emerge. Focusing in the area of cardiology, we aim to evaluate the types of ISCTs, their analysis methods and their reporting standards. To this end, we conducted a systematic review of cardiac ISCTs over the period of 1 January 2012-1 January 2022, following the preferred reporting items for systematic reviews and meta-analysis (PRISMA). We considered cardiac ISCTs of human patient cohorts, and excluded studies of single individuals and those in which models were used to guide a procedure without comparing against a control group. We identified 36 publications that described cardiac ISCTs, with most of the studies coming from the US and the UK. In 75% of the studies, a validation step was performed, although the specific type of validation varied between the studies. ANSYS FLUENT was the most commonly used software in 19% of ISCTs. The specific software used was not reported in 14% of the studies. Unlike clinical trials, we found a lack of consistent reporting of patient demographics, with 28% of the studies not reporting them. Uncertainty quantification was limited, with sensitivity analysis performed in only 19% of the studies. In 97% of the ISCTs, no link was provided to provide easy access to the data or models used in the study. There was no consistent naming of study types with a wide range of studies that could potentially be considered ISCTs. There is a clear need for community agreement on minimal reporting standards on patient demographics, accepted standards for ISCT cohort quality control, uncertainty quantification, and increased model and data sharing.