Fast deep learning reconstruction techniques for preclinical magnetic resonance fingerprinting.

We propose a deep learning (DL) model and a hyperparameter optimization strategy to reconstruct T1 and T2 maps acquired with the magnetic resonance fingerprinting (MRF) methodology. We applied two different MRF sequence routines to acquire images of ex vivo rat brain phantoms using a 7-T preclinical scanner. Subsequently, the DL model was trained using experimental data, completely excluding the use of any theoretical MRI signal simulator. The best combination of the DL parameters was implemented by an automatic hyperparameter optimization strategy, whose key aspect is to include all the parameters to the fit, allowing the simultaneous optimization of the neural network architecture, the structure of the DL model, and the supervised learning algorithm. By comparing the reconstruction performances of the DL technique with those achieved from the traditional dictionary-based method on an independent dataset, the DL approach was shown to reduce the mean percentage relative error by a factor of 3 for T1 and by a factor of 2 for T2 , and to improve the computational time by at least a factor of 37. Furthermore, the proposed DL method enables maintaining comparable reconstruction performance, even with a lower number of MRF images and a reduced k-space sampling percentage, with respect to the dictionary-based method. Our results suggest that the proposed DL methodology may offer an improvement in reconstruction accuracy, as well as speeding up MRF for preclinical, and in prospective clinical, investigations.

CANCOL, a Computer-Assisted Annotation Tool to Facilitate Colocalization and Tracking of Immune Cells in Intravital Microscopy.

Two-photon intravital microscopy (2P-IVM) has become a widely used technique to study cell-to-cell interactions in living organisms. Four-dimensional imaging data obtained via 2P-IVM are classically analyzed by performing automated cell tracking, a procedure that computes the trajectories followed by each cell. However, technical artifacts, such as brightness shifts, the presence of autofluorescent objects, and channel crosstalking, affect the specificity of imaging channels for the cells of interest, thus hampering cell detection. Recently, machine learning has been applied to overcome a variety of obstacles in biomedical imaging. However, existing methods are not tailored for the specific problems of intravital imaging of immune cells. Moreover, results are highly dependent on the quality of the annotations provided by the user. In this study, we developed CANCOL, a tool that facilitates the application of machine learning for automated tracking of immune cells in 2P-IVM. CANCOL guides the user during the annotation of specific objects that are problematic for cell tracking when not properly annotated. Then, it computes a virtual colocalization channel that is specific for the cells of interest. We validated the use of CANCOL on challenging 2P-IVM videos from murine organs, obtaining a significant improvement in the accuracy of automated tracking while reducing the time required for manual track curation.

Electromechanical factors associated with favourable outcome in cardiac resynchronization therapy.

AIMS: Electromechanical coupling in patients receiving cardiac resynchronization therapy (CRT) is not fully understood. Our aim was to determine the best combination of electrical and mechanical substrates associated with effective CRT. METHODS AND RESULTS: Sixty-two patients were prospectively enrolled from two centres. Patients underwent 12-lead electrocardiogram (ECG), cardiovascular magnetic resonance (CMR), echocardiography, and anatomo-electromechanical mapping (AEMM). Remodelling was measured as the end-systolic volume (ΔESV) decrease at 6 months. CRT was defined effective with ΔESV ≤ -15%. QRS duration (QRSd) was measured from ECG. Area strain was obtained from AEMM and used to derive systolic stretch index (SSI) and total left-ventricular mechanical time. Total left-ventricular activation time (TLVAT) and transeptal time (TST) were derived from AEMM and ECG. Scar was measured from CMR. Significant correlations were observed between ΔESV and TST [rho = 0.42; responder: 50 (20-58) vs. non-responder: 33 (8-44) ms], TLVAT [-0.68; 81 (73-97) vs. 112 (96-127) ms], scar [-0.27; 0.0 (0.0-1.2) vs. 8.7 (0.0-19.1)%], and SSI [0.41; 10.7 (7.1-16.8) vs. 4.2 (2.9-5.5)], but not QRSd [-0.13; 155 (140-176) vs. 167 (155-177) ms]. TLVAT and SSI were highly accurate in identifying CRT response [area under the curve (AUC) > 0.80], followed by scar (AUC > 0.70). Total left-ventricular activation time (odds ratio = 0.91), scar (0.94), and SSI (1.29) were independent factors associated with effective CRT. Subjects with SSI >7.9% and TLVAT <91 ms all responded to CRT with a median ΔESV ≈ -50%, while low SSI and prolonged TLVAT were more common in non-responders (ΔESV ≈ -5%). CONCLUSION: Electromechanical measurements are better associated with CRT response than conventional ECG variables. The absence of scar combined with high SSI and low TLVAT ensures effectiveness of CRT.

Efficient identification of scars using heterogeneous model hierarchies.

AIMS: Detection and quantification of myocardial scars are helpful for diagnosis of heart diseases and for personalized simulation models. Scar tissue is generally characterized by a different conduction of excitation. We aim at estimating conductivity-related parameters from endocardial mapping data. Solving this inverse problem requires computationally expensive monodomain simulations on fine discretizations. We aim at accelerating the estimation by combining electrophysiology models of different complexity. METHODS AND RESULTS: Distributed parameter estimation is performed by minimizing the misfit between simulated and measured electrical activity on the endocardial surface, subject to the monodomain model and regularization. We formulate this optimization problem, including the modelling of scar tissue and different regularizations, and design an efficient solver. We consider grid hierarchies and monodomain-eikonal model hierarchies in a recursive multilevel trust-region method. With numerical examples, efficiency and estimation quality, depending on the data, are investigated. The multilevel solver is significantly faster than a comparable single level solver. Endocardial mapping data of realistic density appears to be sufficient to provide quantitatively reasonable estimates of location, size, and shape of scars close to the endocardial surface. CONCLUSION: In several situations, scar reconstruction based on eikonal and monodomain models differ significantly, suggesting the use of the more involved monodomain model for this purpose. Eikonal models can accelerate the computations considerably, enabling the use of complex electrophysiology models for estimating myocardial scars from endocardial mapping data.

Fully coupled dynamic simulations of bioprosthetic aortic valves based on an embedded strategy for fluid-structure interaction with contact.

AIMS: This work aims at presenting a fully coupled approach for the numerical solution of contact problems between multiple elastic structures immersed in a fluid flow. The key features of the computational model are (i) a fully coupled fluid-structure interaction with contact, (ii) the use of a fibre-reinforced material for the leaflets, (iii) a stent, and (iv) a compliant aortic root. METHODS AND RESULTS: The computational model takes inspiration from the immersed boundary techniques and allows the numerical simulation of the blood-tissue interaction of bioprosthetic heart valves (BHVs) as well as the contact among the leaflets. First, we present pure mechanical simulations, where blood is neglected, to assess the performance of different material properties and valve designs. Secondly, fully coupled fluid-structure interaction simulations are employed to analyse the combination of haemodynamic and mechanical characteristics. The isotropic leaflet tissue experiences high-stress values compared to the fibre-reinforced material model. Moreover, elongated leaflets show a stress concentration close to the base of the stent. We observe a fully developed flow at the systolic stage of the heartbeat. On the other hand, flow recirculation appears along the aortic wall during diastole. CONCLUSION: The presented FSI approach can be used for analysing the mechanical and haemodynamic performance of a BHV. Our study suggests that stresses concentrate in the regions where leaflets are attached to the stent and in the portion of the aortic root where the BHV is placed. The results from this study may inspire new BHV designs that can provide a better stress distribution.

Automatic reconstruction of the left atrium activation from sparse intracardiac contact recordings by inverse estimate of fibre structure and anisotropic conduction in a patient-specific model.

AIMS: Electric conduction in the atria is direction-dependent, being faster in fibre direction, and possibly heterogeneous due to structural remodelling. Intracardiac recordings of atrial activation may convey such information, but only with high-quality data. The aim of this study was to apply a patient-specific approach to enable such assessment even when data are scarce, noisy, and incomplete. METHODS AND RESULTS: Contact intracardiac recordings in the left atrium from nine patients who underwent ablation therapy were collected before pulmonary veins isolation and retrospectively included in the study. The Personalized Inverse Eikonal Model from cardiac Electro-Anatomical Maps (PIEMAP), previously developed, has been used to reconstruct the conductivity tensor from sparse recordings of the activation. Regional fibre direction and conduction velocity were estimated from the fitted conductivity tensor and extensively cross-validated by clustered and sparse data removal. Electrical conductivity was successfully reconstructed in all patients. Cross-validation with respect to the measurements was excellent in seven patients (Pearson correlation r > 0.93) and modest in two patients (r = 0.62 and r = 0.74). Bland-Altman analysis showed a neglectable bias with respect to the measurements and the limit-of-agreement at -22.2 and 23.0 ms. Conduction velocity in the fibre direction was 82 ± 25 cm/s, whereas cross-fibre velocity was 46 ± 7 cm/s. Anisotropic ratio was 1.91±0.16. No significant inter-patient variability was observed. Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps correctly predicted activation times in late regions in all patients (r = 0.88) and was robust to a sparser dataset (r = 0.95). CONCLUSION: Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps offers a novel approach to extrapolate the activation in unmapped regions and to assess conduction properties of the atria. It could be seamlessly integrated into existing electro-anatomic mapping systems. Personalized Inverse Eikonal model from cardiac Electro-Anatomical Maps also enables personalization of cardiac electrophysiology models.

Synergistic antiarrhythmic effect of inward rectifier current inhibition and pulmonary vein isolation in a 3D computer model for atrial fibrillation.

AIMS: Recent clinical studies showed that antiarrhythmic drug (AAD) treatment and pulmonary vein isolation (PVI) synergistically reduce atrial fibrillation (AF) recurrences after initially successful ablation. Among newly developed atrial-selective AADs, inhibitors of the G-protein-gated acetylcholine-activated inward rectifier current (IKACh) were shown to effectively suppress AF in an experimental model but have not yet been evaluated clinically. We tested in silico whether inhibition of inward rectifier current or its combination with PVI reduces AF inducibility. METHODS AND RESULTS: We simulated the effect of inward rectifier current blockade (IK blockade), PVI, and their combination on AF inducibility in a detailed three-dimensional model of the human atria with different degrees of fibrosis. IK blockade was simulated with a 30% reduction of its conductivity. Atrial fibrillation was initiated using incremental pacing applied at 20 different locations, in both atria. IK blockade effectively prevented AF induction in simulations without fibrosis as did PVI in simulations without fibrosis and with moderate fibrosis. Both interventions lost their efficacy in severe fibrosis. The combination of IK blockade and PVI prevented AF in simulations without fibrosis, with moderate fibrosis, and even with severe fibrosis. The combined therapy strongly decreased the number of fibrillation waves, due to a synergistic reduction of wavefront generation rate while the wavefront lifespan remained unchanged. CONCLUSION: Newly developed blockers of atrial-specific inward rectifier currents, such as IKAch, might prevent AF occurrences and when combined with PVI effectively supress AF recurrences in human.

Reconstruction of three-dimensional biventricular activation based on the 12-lead electrocardiogram via patient-specific modelling.

AIMS: Non-invasive imaging of electrical activation requires high-density body surface potential mapping. The nine electrodes of the 12-lead electrocardiogram (ECG) are insufficient for a reliable reconstruction with standard inverse methods. Patient-specific modelling may offer an alternative route to physiologically constraint the reconstruction. The aim of the study was to assess the feasibility of reconstructing the fully 3D electrical activation map of the ventricles from the 12-lead ECG and cardiovascular magnetic resonance (CMR). METHODS AND RESULTS: Ventricular activation was estimated by iteratively optimizing the parameters (conduction velocity and sites of earliest activation) of a patient-specific model to fit the simulated to the recorded ECG. Chest and cardiac anatomy of 11 patients (QRS duration 126-180 ms, documented scar in two) were segmented from CMR images. Scar presence was assessed by magnetic resonance (MR) contrast enhancement. Activation sequences were modelled with a physiologically based propagation model and ECGs with lead field theory. Validation was performed by comparing reconstructed activation maps with those acquired by invasive electroanatomical mapping of coronary sinus/veins (CS) and right ventricular (RV) and left ventricular (LV) endocardium. The QRS complex was correctly reproduced by the model (Pearson's correlation r = 0.923). Reconstructions accurately located the earliest and latest activated LV regions (median barycentre distance 8.2 mm, IQR 8.8 mm). Correlation of simulated with recorded activation time was very good at LV endocardium (r = 0.83) and good at CS (r = 0.68) and RV endocardium (r = 0.58). CONCLUSION: Non-invasive assessment of biventricular 3D activation using the 12-lead ECG and MR imaging is feasible. Potential applications include patient-specific modelling and pre-/per-procedural evaluation of ventricular activation.

All-at-once multigrid approaches for one-dimensional space-fractional diffusion equations.

We focus on a time-dependent one-dimensional space-fractional diffusion equation with constant diffusion coefficients. An all-at-once rephrasing of the discretized problem, obtained by considering the time as an additional dimension, yields a large block linear system and paves the way for parallelization. In particular, in case of uniform space-time meshes, the coefficient matrix shows a two-level Toeplitz structure, and such structure can be leveraged to build ad-hoc iterative solvers that aim at ensuring an overall computational cost independent of time. In this direction, we study the behavior of certain multigrid strategies with both semi- and full-coarsening that properly take into account the sources of anisotropy of the problem caused by the grid choice and the diffusion coefficients. The performances of the aforementioned multigrid methods reveal sensitive to the choice of the time discretization scheme. Many tests show that Crank-Nicolson prevents the multigrid to yield good convergence results, while second-order backward-difference scheme is shown to be unconditionally stable and that it allows good convergence under certain conditions on the grid and the diffusion coefficients. The effectiveness of our proposal is numerically confirmed in the case of variable coefficients too and a two-dimensional example is given.

The influence of scar on the spatio-temporal relationship between electrical and mechanical activation in heart failure patients.

AIMS: The aim of this study was to determine the relationship between electrical and mechanical activation in heart failure (HF) patients and whether electromechanical coupling is affected by scar. METHODS AND RESULTS: Seventy HF patients referred for cardiac resynchronization therapy or biological therapy underwent endocardial anatomo-electromechanical mapping (AEMM) and delayed-enhancement magnetic resonance (CMR) scans. Area strain and activation times were derived from AEMM data, allowing to correlate mechanical and electrical activation in time and space with unprecedented accuracy. Special attention was paid to the effect of presence of CMR-evidenced scar. Patients were divided into a scar (n = 43) and a non-scar group (n-27). Correlation between time of electrical and mechanical activation was stronger in the non-scar compared to the scar group [R = 0.84 (0.72-0.89) vs. 0.74 (0.52-0.88), respectively; P = 0.01]. The overlap between latest electrical and mechanical activation areas was larger in the absence than in presence of scar [72% (54-81) vs. 56% (36-73), respectively; P = 0.02], with smaller distance between the centroids of the two regions [10.7 (4.9-17.4) vs. 20.3 (6.9-29.4) % of left ventricular radius, P = 0.02]. CONCLUSION: Scar decreases the association between electrical and mechanical activation, even when scar is remote from late activated regions.

Beat-to-beat P-wave morphological variability in patients with paroxysmal atrial fibrillation: an in silico study.

AIMS: P-wave beat-to-beat morphological variability can identify patients prone to paroxysmal atrial fibrillation (AF). To date, no computational study has been carried out to mechanistically explain such finding. The aim of this study was to provide a pathophysiological explanation, by using a computer model of the human atria, of the correlation between P-wave beat-to-beat variability and the risk of AF. METHODS AND RESULTS: A physiological variability in the earliest activation site (EAS), on a beat-to-beat basis, was introduced into a computer model of the human atria by randomizing the EAS location. A methodology for generating multi-scale, spatially-correlated regions of heterogeneous conduction was developed. P-wave variability in the presence of such regions was compared with a control case. Simulations were performed with an eikonal model, for the activation map, and with the lead field approach, for P-wave computation. The methodology was eventually compared with a reference monodomain simulation. A total of 60 P-waves were simulated for each sinus node exit location (12 in total), and for each of the 15 patterns of heterogeneous conduction automatically generated by the model. A P-wave beat-to-beat variability was observed in all cases. Variability was significantly increased in presence of heterogeneous slow conducting regions, up to two-fold the variability in the control case. P-wave variability increased non-linearly with respect to the EAS variability and total area of slow conduction. Distribution of the heterogeneous conduction was more effective in increasing the variability when it surrounded the EAS locations and the fast conducting bundles. P-waves simulated by the eikonal approach compared excellently with the monodomain-based ones. CONCLUSION: P-wave variability in patients with paroxysmal AF could be explained by a variability in sinoatrial node exit location in combination with slow conducting regions.

Effect of Na+-channel blockade on the three-dimensional substrate of atrial fibrillation in a model of endo-epicardial dissociation and transmural conduction.

AIMS: Atrial fibrillation (AF) is a progressive arrhythmia characterized by structural alterations that increase its stability. Both clinical and experimental studies showed a concomitant loss of antiarrhythmic drug efficacy in later stages of AF. The mechanisms underlying this loss of efficacy are not well understood. We hypothesized that structural remodelling may explain this reduced efficacy by making the substrate more three-dimensional. To investigate this, we simulated the effect of sodium (Na+)-channel block on AF in a model of progressive transmural uncoupling. METHODS AND RESULTS: In a computer model consisting of two cross-connected atrial layers, with realistic atrial membrane behaviour, structural remodelling was simulated by reducing the number of connections between the layers. 100% of endo-epicardial connectivity represented a healthy atrium. At various degrees of structural remodelling, we assessed the effect of 60% sodium channel block on AF stability, endo-epicardial electrical activity dissociation (EED), and fibrillatory conduction pattern complexity quantified by number of waves, phase singularities (PSs), and transmural conduction ('breakthrough', BT). Sodium channel block terminated AF in non-remodelled but not in remodelled atria. The temporal excitable gap (EG) and AF cycle length increased at all degrees of remodelling when compared with control. Despite an increase of EED and EG, sodium channel block decreased the incidence of BT because of transmural conduction block. Sodium channel block decreased the number of waves and PSs in normal atrium but not in structurally remodelled atrium. CONCLUSION: This simple atrial model explains the loss of efficacy of sodium channel blockers in terminating AF in the presence of severe structural remodelling as has been observed experimentally and clinically. Atrial fibrillation termination in atria with moderate structural remodelling in the presence of sodium channel block is caused by reduction of AF complexity. With more severe structural remodelling, sodium channel block fails to promote synchronization of the two layers of the model.

A left bundle branch block activation sequence and ventricular pacing influence voltage amplitudes: an in vivo and in silico study.

AIMS: The aim of this study was to investigate the influence of the activation sequence on voltage amplitudes by evaluating regional voltage differences during a left bundle branch block (LBBB) activation sequence vs. a normal synchronous activation sequence and by evaluating pacing-induced voltage differences. METHODS AND RESULTS: Twenty-one patients and three computer models without scar were studied. Regional voltage amplitudes were evaluated in nine LBBB patients who underwent endocardial electro-anatomic mapping (EAM). Pacing-induced voltage differences were evaluated in 12 patients who underwent epicardial EAM during intrinsic rhythm and right ventricular (RV) pacing. Three computer models customized for LBBB patients were created. Changes in voltage amplitudes after an LBBB (intrinsic), a normal synchronous, an RV pacing, and a left ventricular pacing activation sequence were assessed in the computer models. Unipolar voltage amplitudes in patients were approximately 4.5 mV (4.4-4.7 mV, ∼33%) lower in the septum when compared with other segments. A normal synchronous activation sequence in the computer models normalized voltage amplitudes in the septum. Pacing-induced differences were larger in electrograms with higher voltage amplitudes during intrinsic rhythm and furthermore larger and more variable at the epicardium [mean absolute difference: 3.6-6.2 mV, 40-53% of intrinsic value; interquartile range (IQR) differences: 53-63% of intrinsic value] compared to the endocardium (mean absolute difference: 3.3-3.8 mV, 28-30% of intrinsic value; IQR differences: 37-40% of intrinsic value). CONCLUSION: In patients and computer models without scar, lower septal unipolar voltage amplitudes are exclusively associated with an LBBB activation sequence. Pacing substantially affects voltage amplitudes, particularly at the epicardium.

Impact of mechanical deformation on pseudo-ECG: a simulation study.

AIMS: Electrophysiological simulations may help to investigate causes and possible treatments of ventricular conduction disturbances. Most electrophysiological models do not take into account that the heart moves during the cardiac cycle. We used an electro-mechanical model to study the effect of mechanical deformation on the results of electrophysiological simulations. METHODS AND RESULTS: Pseudo-electrocardiogram (ECG) were generated from the propagation of electrical signals in tissue slabs undergoing active mechanical deformation. We used the mono-domain equation for electrophysiology with the Bueno-Orovio ionic model and a fully incompressible Guccione-Costa hyperelastic law for the mechanics with the Nash-Panfilov model for the active force. We compared a purely electrophysiological approach (PE) with mono-directional (MD) and bi-directional (BD) electromechanical coupling strategies. The numerical experiments showed that BD and PE simulations led to different S- and T-waves. Mono-directional simulations generally approximated the BD ones, unless fibres were oriented along one short axis of the slab. When present, notching in the QRS-complex was larger in MD than in BD simulations. CONCLUSIONS: Tissue deformation has to be taken into account when estimating the S- and T-wave of the ECG in electrophysiological simulations.

Changes in P-wave morphology after pulmonary vein isolation: insights from computer simulations.

AIMS: Apparently conflicting clinical measurements of P-wave duration (PWD) pre- vs. post-ablation have been reported. To assist the interpretation of these clinical data, we used a computer model of the atria and torso to simulate P waves before and after pulmonary vein (PV) isolation. METHODS AND RESULTS: Twenty ablation patterns were designed (segmental or ipsilateral ablation; five distances to PV sleeves; addition of a roof line or not). Possible PV reconnections were introduced as gaps in the ablation lines. PWD and area were measured during sinus rhythm in vectorcardiogram (VCG) magnitude signals and on the 16-lead ECG before and after ablation, and after PV reconnection. After PV isolation, biatrial activation time was prolonged by 0-5 ms without and by 48±5 ms with roof line. Yet PWD was shortened in lead V3 and V4 by up to 15 ms. The effect of ablation on P-wave morphology was stronger when larger PV areas were isolated. Segmental and ipsilateral PV isolation led to concordant results. P-wave area increased in V1 and decreased in V6. Changes in PWD and area on the VCG were sensitive to the threshold used for detecting the end of the P wave. The occurrence of PV reconnection was best identified on leads V3, V4, and V9. CONCLUSION: PV isolation and reconnection induced measurable changes on the 16-lead ECG that might be used to improve patient follow-up after ablation.

Segmentation of the left ventricular endocardium from magnetic resonance images by using different statistical shape models.

We evaluate in this paper different strategies for the construction of a statistical shape model (SSM) of the left ventricle (LV) to be used for segmentation in cardiac magnetic resonance (CMR) images. From a large database of LV surfaces obtained throughout the cardiac cycle from 3D echocardiographic (3DE) LV images, different LV shape models were built by varying the considered phase in the cardiac cycle and the registration procedure employed for surface alignment. Principal component analysis was computed to describe the statistical variability of the SSMs, which were then deformed by applying an active shape model (ASM) approach to segment the LV endocardium in CMR images of 45 patients. Segmentation performance was evaluated by comparing LV volumes derived by ASM segmentation with different SSMs and those obtained by manual tracing, considered as a reference. A high correlation (r(2)>0.92) was found in all cases, with better results when using the SSM models comprising more than one frame of the cardiac cycle.

Molecular Determinants for Unphosphorylated STAT3 Dimerization Determined by Integrative Modeling.

Signal transducer and activator of transcription factors (STATs) are proteins that can translocate into the nucleus, bind DNA, and activate gene transcription. STAT proteins play a crucial role in cell proliferation, apoptosis, and differentiation. The prevalent view is that STAT proteins are able to form dimers and bind DNA only upon phosphorylation of specific tyrosine residues in the transactivation domain. However, this paradigm has been questioned recently by the observation of dimers of unphosphorylated STATs (USTATs) by X-ray, Förster resonance energy transfer, and site-directed mutagenesis. A more complex picture of the dimerization process and of the role of the dimers is, thus, emerging. Here we present an integrated modeling study of STAT3, a member of the STAT family of utmost importance in cancer development and therapy, in which we combine available experimental data with several computational methodologies such as homology modeling, protein-protein docking, and molecular dynamics to build reliable atomistic models of USTAT3 dimers. The models generated with the integrative approach presented here were then validated by performing computational alanine scanning for all the residues in the protein-protein interface. These results confirmed the experimental observation of the importance of some of these residues (in particular Leu78 and Asp19) in the USTAT3 dimerization process. Given the growing importance of USTAT3 dimers in several cellular pathways, our models provide an important tool for studying the effects of pathological mutations at the molecular and/or atomistic level, and in the rational design of new inhibitors of dimerization.

An in-silico analysis of the effect of heart position and orientation on the ECG morphology and vectorcardiogram parameters in patients with heart failure and intraventricular conduction defects.

AIM: The aim of this study was to investigate the influence of geometrical factors on the ECG morphology and vectorcardiogram (VCG) parameters. METHODS: Patient-tailored models based on five heart-failure patients with intraventricular conduction defects (IVCDs) were created. The heart was shifted up to 6 cm to the left, right, up, and down and rotated ±30° around the anteroposterior axis. Precordial electrodes were shifted 3 cm down. RESULTS: Geometry modifications strongly altered ECG notching/slurring and intrinsicoid deflection time. Maximum VCG parameter changes were small for QRS duration (-6% to +10%) and QRS-T angle (-6% to +3%), but considerable for QRS amplitude (-36% to +59%), QRS area (-37% to +42%), T-wave amplitude (-41% to +36%), and T-wave area (-42% to +33%). CONCLUSION: The position of the heart with respect to the electrodes is an important factor determining notching/slurring and voltage-dependent parameters and therefore must be considered for accurate diagnosis of IVCDs.

Patient-specific modelling of cardiac electrophysiology in heart-failure patients.

AIMS: Left-ventricular (LV) conduction disturbances are common in heart-failure patients and a left bundle-branch block (LBBB) electrocardiogram (ECG) type is often seen. The precise cause of this pattern is uncertain and is probably variable between patients, ranging from proximal interruption of the left bundle branch to diffuse distal conduction disease in the working myocardium. Using realistic numerical simulation methods and patient-tailored model anatomies, we investigated different hypotheses to explain the observed activation order on the LV endocardium, electrogram morphologies, and ECG features in two patients with heart failure and LBBB ECG. METHODS AND RESULTS: Ventricular electrical activity was simulated using reaction-diffusion models with patient-specific anatomies. From the simulated action potentials, ECGs and cardiac electrograms were computed by solving the bidomain equation. Model parameters such as earliest activation sites, tissue conductivity, and densities of ionic currents were tuned to reproduce the measured signals. Electrocardiogram morphology and activation order could be matched simultaneously. Local electrograms matched well at some sites, but overall the measured waveforms had deeper S-waves than the simulated waveforms. CONCLUSION: Tuning a reaction-diffusion model of the human heart to reproduce measured ECGs and electrograms is feasible and may provide insights in individual disease characteristics that cannot be obtained by other means.

The time-dependent biomechanical behaviour of the periodontal ligament--an in vitro experimental study in minipig mandibular two-rooted premolars.

The aim of the present work was to evaluate the biomechanical behaviour of the periodontal ligament (PDL) with respect to force development with different controlled loading velocities. For this purpose, an in vitro experimental study was performed on 18 minipig jaw segments. Displacements with variable increasing loading time were applied to one premolar crown of each jaw segment into the linguobuccal direction through a force sensor provided by a specialized biomechanical set-up. The predefined displacement values to be achieved were 0.1 and 0.2 mm. Each of the given displacement increments was applied on the specimens with a linear displacement increase employing the following time spans: 5, 10, 20, 30, 60, 120, 300, 450, and 600 seconds. Force values were measured during load application to register force/displacement diagrams and after the maximum displacement was reached force decay was monitored for a period of 600 seconds. Force/time curves for each tooth were plotted according to the data obtained. Diagrams of the maximum force values obtained from these plots and the force at the end of each measurement were extracted for all teeth. Forces at the point when maximum displacement was reached ranged from 0.5 to 2.5 N for the 0.1 mm activation and showed extreme variation with the specimens. The factor of volume and surface area of the individual roots were evaluated and found not to be responsible for these deviations. A comparable behaviour was recorded for the 0.2 mm deflection, however, on a higher force level. The results show that the force development at different displacement velocities is complex and dominated by the PDL biomechanical characteristics.