Abstract:

The loss of cardiac pump function accounts for a significant increase in both mortality and morbidity in Western society, where there is currently a one in four lifetime risk, and costs associated with acute and long-term hospital treatments are accelerating. The significance of cardiac disease has motivated the application of state-of-the-art clinical imaging techniques and functional signal analysis to aid diagnosis and clinical planning. Measurements of cardiac function currently provide high-resolution datasets for characterizing cardiac patients. However, the clinical practice of using population-based metrics derived from separate image or signal-based datasets often indicates contradictory treatments plans owing to inter-individual variability in pathophysiology. To address this issue, the goal of our work, demonstrated in this study through four specific clinical applications, is to integrate multiple types of functional data into a consistent framework using multi-scale computational modelling.

Abstract:

Tikhonov methods usually lead to solutions of low amplitude that are distributed around zero. When reconstructing transmembrane voltages (TMVs) in the myocardium, the signal is therefore often not in the physiological range of between around -80mV and 10mV. In this article, we propose an adjusted Tikhonov method that reconstructs TMVs in the correct range, given an estimate of one polarized node in the heart and an estimated set of nodes that have depolarized in the preceding time step. It is shown that when feeding the reconstructed TMVs into a simple cellular automaton recursively, and when using the computed excitation propagation as a prior for the Tikhonov method, it is possible to reconstruct the excitation propagation throughout the ventricular myocardium. The method requires an estimate of the region of initial activation.

Abstract:

# BackgroundMethods for the non-invasive imaging of atrial activation times could provide cardiologists with valuable information on pathological excitation conduction patterns, e.g. for treatment planning.In this study, the source representation functions used in the critical times method (Greensite et al. 1997) are expanded with a range adjustment to generate more accurate activation time maps from ECG measurements.# Materials and methodsExcitation conduction in the atria was simulated for various excitation origins with a cellular automaton. Body surface potential maps were obtained from forward calculations using a bidomain approach.As introduced in Greensite et al. 1995, the method of critical times can be used to quantitatively localize critical point locations and times, and to reconstruct surface activation in a qualitative manner. To this end, all atrial surface nodes were treated as critical points and the corresponding critical times were reconstructed using the zero-crossing method by Greensite, which is the subtraction of the two representation functions.For the heart surface nodes, it was observed that the minuend representation function in the zero-crossing term is often by magnitudes greater than the subtrahend. For the minuend to not dominate the subtrahend before the desired zero-crossing, which is supposed to occur at the time of depolarization, the minuend was therefore weighted with a sigmoid function and normalized to the range of the subtrahend.# ResultsAtrial activation times were reconstructed with both the zero-crossing method by Greensite and the sigmoid-weighted zero-crossing. Two effects were observed. The overall reconstruction quality of the established method improves in the presence of 30dB additive white Gaussian noise. This effect results from a gradual offset that is imposed on the reconstructed critical times under these circumstances (see Huiskamp and Greensite 1997). Second, it could be shown that a significant reduction of reconstruction error can be achieved in the absence of noise with the sigmoid-weighted adaptation of the formula.# ConclusionWith the newly introduced sigmoidal normalization, the quality of reconstruction can be improved significantly if noise levels are below 30dB. Clinical studies need to be made in order to validate the method and assess its performance in a realistic environment.

Abstract:

A method to reconstruct integrals of transmembrane voltages in the heart from measured integrals of Body Surface Potential Maps (BSPM) is proposed. It is applied to localize the origin of premature beats in the heart (extrasystoles). In contrast to other proposals no specific assumption about the slope of the transmembrane voltage during depolarization is made, in particular it must not be a step function. This way the non-linear problem of localizing ectopic foci based on activation times is translated into a linear inverse problem. A Maximum-A-Posteriori (MAP) estimator is applied to solve the ill-posed linear inverse problem. Successful localization of ventricular extrasystoles is demonstrated using computer simulations. Even endocardial, midmyocardial and epicardial foci can be separated.

Abstract:

The objective of personalised modelling of the atria is to improve comprehension of the etiology of atrial arrhythmias, to enable specific diagnosis and to optimise therapy. We start with CT or MR datasets and use adapted segmentation procedures to build a patient-specific 3D-model of the atria. Then we include fibre direction based on the rules of atrial anatomy. Work in progress is also considering late enhancement MRI in order to add areas of fibrotic tissue. Next we can use BSPM data of the P-wave and solve the inverse problem of ECG to get a hypothesis about the spread of depolarisation. Finally we use intracardiac catheter signals (e.g. using a circular catheter) to measure direction and conduction velocity of depolarisation waves (sinus rhythm, atrial flutter, or following stimulation). All this is integrated into a personalised model of the atria of an individual patient. Our next goal will be to properly add ablation lines into the model.The research leading to these results has partly received funding from the European Communitys Seventh Framework Programme (FP7/2007-2013) under grant agreement n 224495 (euHeart project).

Abstract:

A framework for step-by-step personalization of a computational model of human atria is presented. Beginning with anatomical modeling based on CT or MRI data, next fiber structure is superimposed using a rule-based method. If available, late-enhancement-MRI images can be considered in order to mark fibrotic tissue. A first estimate of individual electrophysiology is gained from BSPM data solving the inverse problem of ECG. A final adjustment of electrophysiology is realized using intracardiac measurements. The framework is applied using several patient data. First clinical application will be computer assisted planning of RF-ablation for treatment of atrial flutter and atrial fibrillation.

Abstract:

The early detection of myocardial ischemia is an essential lever for its successful treatment. We investigated an ECG monitoring system with 3 electrodes. Optimal electrode positions are determined using a cellular automaton. The spatially heterogeneous effects of myocardial ischemia were modeled by altering 4 electrophysiological parameters: action potential amplitude and duration, conduction velocity as well as resting membrane voltage. Both, transmural heterogeneity and the influence of the border zone were considered in the simulations on three patient models. The detection of myocardial ischemia is based on ST segment deviation from the physiological case. The signals used to find the best electrode positions comprise ischemic regions with different transmural extents in all 17 AHA segments. We show which ischemic ECGs can be detected given a realistic signal-to-noise ratio, false positive rate and maximum response time of the system.