An optimal electrode position, atrio-ventricular (AV) and interventricular (VV) delay in cardiac resynchronization therapy (CRT) improves its success. An optimization strategy does not yet exist. A computer model of the Visible Man and a patient heart was used to simulate an atrio-ventricular and a left bundle branch block with 0%, 20% and 40% reduction in interventricular conduction velocity, respectively. The minimum error between physiological excitation and pathology/therapy was automatically computed for 12 different electrode positions. AV and VV delay timing was adjusted accordingly. The results show the importance of individually adjusting the electrode position as well as the timing delays to the patient's anatomy and pathology, which is in accordance with current clinical studies. The presented methods and strategy offer the opportunity to carry out non-invasive, automatic optimization of CRT preoperatively. The model is subject to validation in future clinical studies.
A model-based approach to noninvasively determine the location and size of the infarction scar is proposed, that in addition helps to estimate the risk of arrhythmias.The approach is based on the optimization of an electrophysiological heart model with an introduced infarction scar to fit the multichannel ECG measured on the surface of the patient's thorax. This model delivers the distributions of transmembrane voltages (TMV) within the ventricles during a single heart cycle.The forward problem of electrocardiography is solved in order to obtain the simulated ECG of the patient. This ECG is compared with the measured one, the difference is used as the criterion for optimization of model parameters, which include the site and size of infarction scar. IntroductionMortality of patients in the immediate postinfarction period, as well as during the first year after myocardial infarction, is most often due to sudden death from ventricular fibrillation [1]. Thus the development of a cardiac model, which would allow to estimate the probability of arrhythmia for a specific patient, must include a correct implementation of ischemia and/or infarction.The aim of this work is to build a model of the patient's heart that contains infarction scar. It is optimized until the simulated multichannel ECG is as near as possible to the measured one. It is assumed that the location and size of infarction obtained in this manner corresponds to the real one. Taking part in the PhysioNet Challenge 2007 [2] should prove or disprove this assumption.Within the scope of the Challenge, 4 data sets were proposed for patients suffering from different infarctions. Each of the data sets contained anatomical information about the heart and the locations of 352 electrodes on the surface of the patient's thorax. Corresponding 352-channel ECGs were also provided. The first two data sets were considered as training and contained the information about the parameters of infarction scar. The main task of the Challenge consisted in the estimation of location and size of infarction scar for the latter two patients based on the pro- Figure 1. Model of the heart used in this work. Atria, ventricles and excitation conduction system are shown. vided data. Methods Cellular automatonA cellular automaton based model of the heart is employed in this work. The anatomy of the heart has been taken from the Visible Male Project [3]. The cardiac geometry is defined on a regular mesh with the resolution of 1 × 1 × 1 mm 3 . This model contains ventricles and atria, sinus and AV-nodes. An excitation conduction system is generated as a tree-shaped structure, with two branches going from the AV-node towards the apex of both ventricles, afterwards giving rise to multiple branches of Purkinje fibers connected to the ventricular endocardium through a large amount of junctions (see figure 1).The cellular automaton is implemented as follows. If an excitation appears in some voxel, it is transferred to all the neighboring voxels containing excitable tissue. The velocity o...
Heterogeneity of ion channel properties within human ventricular tissue determines the sequence of repolarization under healthy conditions. In this computational study, the impact of different extend of electrophysiological heterogeneity in both human ventricles on the ECG was investigated by a forward calculation of the cardiac electrical signals on the body surface. The gradients ranged from solely transmural, interventricular and apico-basal up to full combination of these variations. As long interventricular heterogeneities were neglected, the transmural gradient generated a positive T wave that was increased when apico-basal variations were considered. Inclusion of interventricular changes necessitated the incorporation of both transmural and apico-basal heterogeneities to reproduce the positive T wave. IntroductionMore than 100 years after Einthoven's first measurement of the human ECG, there are still discussions about the genesis of the T wave in the body surface ECG. The same polarity of T wave and QRS complex must be due to an altered global repolarization versus activation sequence within the tissue. This effect is mainly caused by heterogeneities within the heart influencing the intrinsic electrophysiological properties of the cardiomyocytes. Transmural, apico-basal, and interventricular heterogeneities have been observed in human ventricular tissue [1].Transmural dispersion was shown in different ion channel properties across the human ventricular wall. The transient outward current I to is significantly larger in epicardial than in endocardial cells in the human right and left ventricle (RV, LV) [2,3,4,5]. Furthermore, the rate-dependent properties of I to are varying transmurally in the human LV. The time course of recovery from inactivation is clearly faster in epicardial than in endocardial cells [4]. Measurements of ventricular variations of the delayed rectifier current I Ks and the sodium-calcium exchanger current I NaCa were only conducted on larger animals but not on human cardiomyocytes. The mean value of I Ks in canine M cells was about half of endocardial cells which in turn developed 92 % of the epicardial value [6]. I NaCa was large in M and epicardial but significantly smaller in endocardial canine LV myocytes [7].Current measurements during a voltage step to +60 mV revealed that human mean epicardial I to in the RV is 88 % of its value in the LV whereas endocardial differences between both ventricles were only marginal [2,3]. Interventricular steady-state inactivation and rate of recovery of I to were similar in canine [8]. Mean value of I Ks in canine M cells was nearly doubled in the RV compared to the LV [8].Concerning apico-basal variations only a few experiments were conducted in large animals. Mainly the density of I Ks varied in the left epicardial layers in canine [9].In this computational study different setups of heterogeneously distributed ion channel characteristics within both ventricles of the Visible Man dataset were investigated. Configurations ranged from hom...
The congenital long-QT syndrome is commonly associated with a high risk for polymorphic ventricular tachy-cardia and sudden cardiac death. This is probably due to an intensification of the intrinsic heterogeneities present in ventricular myocardium. Increasing the electrophysiological heterogeneities amplifies the dispersion of repolarization which directly affects the morphology of the T wave in the ECG. The aim of this work is to investigate the effects of LQT2, a specific subtype of the long-QT syndrome (LQTS), on the Body Surface Potential Maps (BSPM) and the ECG. In this context a three-dimensional, heterogeneous model of the human ventricles is used to simulate both physiological and pathological excitation propagation. The results are used as input for the forward calculation of the BSPM and ECG. Characteristic QT prolongation is simulated correctly. The main goal of this study is to prepare and evaluate a simulation environment that can be used prospectivley to find features in the ECG or the BSPM that are characteristic for the LQTS. Such features might be used to facilitate the identification of LQTS patients.
BACKGROUND AND PURPOSE:Previous articles have demonstrated that carotid artery plaques may have enhancement after administration of contrast material. The purpose of this study was to evaluate the effect of enhancement in carotid artery classification.
The distributions of transmembrane voltage (TMV) within the cardiac tissue are linearly connected with the patient's body surface potential maps (BSPMs) at every time instant. The matrix describing the relation between the respective distributions is referred to as the transfer matrix. This matrix can be employed to carry out forward calculations in order to find the BSPM for any given distribution of TMV inside the heart. Its inverse can be used to reconstruct the cardiac activity non-invasively, which can be an important diagnostic tool in the clinical practice. The computation of this matrix using the finite element method can be quite time-consuming. In this work, a method is proposed allowing to speed up this process by computing an approximate transfer matrix instead of the precise one. The method is tested on three realistic anatomical models of real-world patients. It is shown that the computation time can be reduced by 50% without loss of accuracy.
This work proposes a novel non-invasive optimization algorithm to find the best electrode positioning sites and timing delays for BVP in patients with LBBB and MI. This algorithm can be used to plan an optimal therapy for an individual patient.
The approach to solve the inverse problem of electrocardiography presented here is using a computer model of the individual heart of a patient. It is based on a 3D-MRI dataset. Electrophysiologically important tissue classes are incorporated using rules. Source distributions inside the heart are simulated using a cellular automaton. Finite Element Method is used to calculate the corresponding body surface potential map. Characteristic parameters like duration and amplitude of transmembrane potential or velocity of propagation are optimized for selected tissue classes or regions in the heart so that simulated data fit to the measured data. This way the source distribution and its time course of an individual patient can be reconstructed.
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