Abstract:

Biventricular pacing (BVP) could be improved by identifying the patient-specific optimal electrode positions. Body surface potential map (BSPM) is a non-invasive technique for obtaining the electrophysiology and pathology of a patient. The study proposes the use of BSPM as input for an automated non-invasive strategy based on a personalized computer model of the heart, to identify the patient pathology and specific optimal treatment with BVP devices. The anatomy of a patient suffering from left bundle branch block and myocardial infarction is extracted from a series of MR data sets. The clinical measurements of BSPM are used to parameterize the computer model of the heart to represent the individual pathology. Cardiac electrophysiology is simulated with ten Tusscher cell model and excitation propagation is calculated with adaptive cellular automaton, at physiological and pathological conduction levels. The optimal electrode configurations are identified by evaluating the QRS error between healthy and pathology case with/without pacing. Afterwards, the simulated ECGs for optimal pacing are compared to the post-implantation clinically measured ECGs. Both simulation and clinical optimization methods identified the right ventricular (RV) apex and the LV posterolateral regions as being the optimal electrode configuration for the patient. The QRS duration is reduced both in measured and simulated ECG after implantation with 20 and 14%, respectively. The optimized electrode positions found by simulation are comparable to the ones used in hospital. The similarity in QRS duration reduction between measured and simulated ECG signals indicates the success of the method. The computer model presented in this work is a suitable tool to investigate individual pathologies. The personalized model could assist therapy planning of BVP in patients with congestive heart failure. The proposed method could be used as prototype for further clinically oriented investigations of computerized optimization of biventricular pacing.

Abstract:

An improvement of biventricular pacing (BVP) could be possible by detecting the patient specific optimal pacemaker parameters. Body surface potential map (BSPM) is used to obtain the electrophysiology and pathology of an individual patient non-invasively. The clinical measurements of BSPM are used to parameterize the computer model of the heart to represent the individual pathology. The computer model of the heart is used to simulate the dyssynchrony of the ventricles and myocardial infarction (MI). Cardiac electrophysiology is simulated with ten Tusscher cell model, while excitation propagation is intended with adaptive cellular automaton at physiological and pathological conduction stages. The optimal electrode configurations are identified by minimizing the QRS duration error of healthy and pathology case with/without pacing between pre and post-implantation. Afterwards, the simulated ECGs for optimal pacing are compared to the post implantation clinically measured ECGs. The optimal electrode positions found by simulation are comparable to the ones meausured in hospital. The QRS duration reduction error between measured and simulated 12 ECG signals are similar with a constant offset of 15 ms. The personalized model present in this research is an effective tool for therapy planning of BVP in patients with congestive heart failure.

Abstract:

BACKGROUND: The efficacy of cardiac resynchronization therapy through biventricular pacing (BVP) has been demonstrated by numerous studies in patients suffering from congestive heart failure. In order to achieve a guideline for optimal treatment with BVP devices, an automated non-invasive strategy based on a computer model of the heart is presented. MATERIALS AND METHODS: The presented research investigates an off-line optimization algorithm regarding electrode positioning and timing delays. The efficacy of the algorithm is demonstrated in four patients suffering from left bundle branch block (LBBB) and myocardial infarction (MI). The computer model of the heart was used to simulate the LBBB in addition to several MI allocations according to the different left ventricular subdivisions introduced by the American Heart Association. Furthermore, simulations with reduced interventricular conduction velocity were performed in order to model interventricular excitation conduction delay. More than 800,000 simulations were carried out by adjusting a variety of 121 pairs of atrioventricular and interventricular delays and 36 different electrode positioning set-ups. Additionally, three different conduction velocities were examined. The optimization measures included the minimum root mean square error (E(RMS)) between physiological, pathological and therapeutic excitation, and also the difference of QRS-complex duration. Both of these measures were computed automatically. RESULTS: Depending on the patient's pathology and conduction velocity, a reduction of E(RMS) between physiological and therapeutic excitation could be reached. For each patient and pathology, an optimal pacing electrode pair was determined. The results demonstrated the importance of an individual adjustment of BVP parameters to the patient's anatomy and pathology. CONCLUSION: 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.

Abstract:

Reduced cardiac output, dysfunction of the conduction system, atrio-ventricular block, bundle branch blocks and remodeling of the chambers are results of congestive heart failure (CHF). Biventricular pacing as Cardiac Resynchronization Therapy (CRT) is a recognized therapy for the treatment of heart failure. The present paper investigates an automated non-invasive strategy to optimize CRT with respect to electrode positioning and timing delays based on a complex threedimensional computer model of the human heart. The anatomical model chosen for this study was the segmented data set of the Visible Man and a set of patient data with dilated ventricles and left bundle branch block. The excitation propagation and intra-ventricular conduction were simulated with Ten Tusscher electrophysiological cell model and adaptive cellular automaton. The pathologies simulated were a total atrioventricular (AV) block and a left bundle branch block (LBBB) in conjunction with reduced interventricular conduction velocities. The simulated activation times of different myocytes in the healthy and diseased heart model are compared in terms of root mean square error. The outcomes of the investigation show that the positioning of the electrodes, with respect to proper timing delay influences the efficiency of the resynchronization therapy. The proposed method may assist the surgeon in therapy planning.

Abstract:

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.

Abstract:

Es wird eine Methode beschrieben, wie medizinische Bilder des Herzens modellbasiert mit EKG-Daten verknüpft werden können, um damit zu einer spezifischen Diagnostik und zu einer besseren Therapieplanung in der Kardiologie zu gelangen. Zunächst wird aus MRT- oder CT-Bildern des Patienten die Geometrie seines Herzens ermittelt. Elektrokardiographische Messungen an der Körperoberfläche (EKG oder Body Surface Potential Mapping) und aus dem Inneren des Herzens (intracardial mapping) werden aufgenommen und die Orte der Messung in den Bilddatensatz eingetragen (registration). Ein elektrophysiologisches Computermodell vom Herzen des Patienten wird mit Hilfe der elektrophysiologischen Messdaten iterativ angepasst. Schließlich entsteht im Computer ein virtuelles Herz des Patienten, welches sowohl die Geometrie als auch die Elektrophysiologie wiedergibt. Ein Modell der Vorhöfe hat beispielsweise das Potenzial, die Ursachen von Vorhofflimmern zu erkennen und die Radiofrequenz-Ablationsstrategie zu optimieren. Ein Modell der Ventrikel des Herzens kann helfen, genetisch bedingte Rhythmusstörungen besser zu verstehen oder auch die Parameter bei der kardialen Resynchronisationstherapie zu optimieren. Die Modellierung des Herzens mit einem Infarktgebiet könnte die elektrophysiologischen Auswirkungen des Infarktes beschreiben und die Risikostratifizierung für gefährliche ventrikuläre Arrhythmien unterstützen oder die Erfolgsrate bei ventrikulären Ablationen erhöhen.

Abstract:

Electrode positions and timing delays influence the efficacy of biventricular pacing (BVP). Accordingly, the study focus is on BVP optimization, using a detailed three-dimensional electrophysiological model of the human heart, adapted to patient specific anatomy and pathophysiology. The research is effectuated on ten heart models with left bundle branch block and myocardial infarction derived from magnetic resonance and computer tomography data. Cardiac electrical activity is simulated with ten Tusscher cell model and adaptive cellular automaton, at physiological and pathological conduction levels. The optimization methods are based on a comparison between the electrical response of the healthy and diseased heart models, measured in terms of root mean square error (ERMS) of the excitation front and QRS duration error (EQRS). Intra- and inter-method associations of the pacing electrodes and timing delays variables were analyzed with statistical methods, i.e. t-test for dependent data, one-way ANOVA for electrode pairs and Pearson model for equivalent parameters from the two optimization methods. The results indicate that lateral left ventricle and upper or middle septal area are frequently (60% of cases) the optimal position of the left and right electrode, respectively. Statistical analysis proves that the two optimization methods are in good agreement. In conclusion, a non-invasive pre-operative BVP optimization strategy based on computer simulations can be used to identify the most beneficial patient specific electrode configuration and timing delays.

Abstract:

Many studies conducted on patients suffering from congestive heart failure have shown the efficacy of cardiac resynchronization therapy (CRT). The presented research investigates an off-line optimization algorithm based on different electrode positioning and timing delays. A computer model of the heart was used to simulate left bundle branch block (LBBB), myocardial infarction (MI) and reduction of intraventricular conduction velocity in order to customize the patient symptom. The optimization method evaluates the error between the healthy heart and pathology with/without pacing in terms of activation time and QRS length. Additionally, a torso model of the patient is extracted to compute the body surface potential map (BSPM) and to simulate the ECG with Wilson leads to validate the results obtained by the electrophysiological heart model optimization.

Abstract:

Congestive heart failure (CHF) is affecting more than 15 million people in the western population with an increasing number. Biventricular pacing as Cardiac Resynchronization Therapy (CRT) is a recognized therapy for the treatment of heart failure. The present paper investigates the optimal pacing sites and stimuli delays for stimulation, based on a complex three-dimensional computer model of the human heart. The anatomical features were derived from the Visible Man data set. The excitation propagation and intraventricular conduction were simulated with Ten Tusscher electrophysiological cell model and an adaptive cellular automaton. Biventricular pacing in AV block III and LBBB with different interventricular conduction delays were investigated. The simulated activation times of different myocytes in the healthy and diseased heart model are compared in terms of root mean square error (ERMS). The outcomes of the investigation underline that the positioning of the electrodes considering a proper atrioventricular and intraventricular delay influences the efficiency of the resynchronization therapy. The results of this optimization strategy may assist the surgeon in therapy planning.

Abstract:

After mathematical modeling of the healthy heart now modeling of diseases comes into the focus of research. Modeling of arrhythmias already shows a large degree of realism. This offers the chance of more detailed diagnosis and computer assisted therapy planning. Options for genetic diseases (channelopathies like Long-QT-syndrome), infarction and infarction-induced ventricular fibrillation, atrial fibrillation (AF) and cardiac resynchronization therapy are demonstrated.