Application of the fastest route algorithm in the interactive simulation of the effect of local ischemia on the ECG

Dam, Peter M. van; Oostendorp, Thom F.; Oosterom, A. van

doi:10.1007/s11517-008-0391-2

Cited by 46 publications

(36 citation statements)

References 25 publications

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“…Thus there has been considerable recent effort towards devising more effective initializations [2], [14]–[18]. The Fastest Route Algorithm (FRA) [2] is one such initialization method that has been reported to be particularly effective.…”

Section: Introductionmentioning

confidence: 99%

“…In settings where pathology may be present, however, regions of the heart with tissue damage or genetic abnormalities may have TMPs with different (typically lower) amplitudes, for example due to ischemia, Brugada syndrome, or arrhythmogenic right ventricular dysplasia/cardiomyopathy [18]–[24]. When available for segmentation, MRI or X-ray CT images of the heart may allow identification of such regions, but this imaging may not always be available, or it may not be possible to determine the true amplitudes, or such regions may be missed in the images or appear only after the time of imaging.…”

Section: Introductionmentioning

confidence: 99%

“…The FRA is an initialization method for the NLLS problem which we use in our experiments to explain the results of the robustness analysis method proposed in the sequel [18]. The FRA produces an initialization for the NLLS problem by synthesizing wavefront propagation patterns originating from one or more foci and choosing the most suitable one.…”

Section: Introductionmentioning

confidence: 99%

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Identifying Model Inaccuracies and Solution Uncertainties in Noninvasive Activation-Based Imaging of Cardiac Excitation Using Convex Relaxation

Erem

Dam

Brooks

2014

IEEE Trans. Med. Imaging

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Noninvasive imaging of cardiac electrical function has begun to move towards clinical adoption. Here we consider one common formulation of the problem, in which the goal is to estimate the spatial distribution of electrical activation times during a cardiac cycle. We address the challenge of understanding the robustness and uncertainty of solutions to this formulation. This formulation poses a non-convex, non-linear least squares optimization problem. We show that it can be relaxed to be convex, at the cost of some degree of physiological realism of the solution set, and that this relaxation can be used as a framework to study model inaccuracy and solution uncertainty. We present two examples, one using data from a healthy human subject and the other synthesized with the ECGSIM software package. In the first case, we consider uncertainty in the initial guess and regularization parameter. In the second case, we mimic the presence of an ischemic zone in the heart in a way which violates a model assumption. We show that the convex relaxation allows understanding of spatial distribution of parameter sensitivity in the first case, and identification of model violation in the second.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identifying Model Inaccuracies and Solution Uncertainties in Noninvasive Activation-Based Imaging of Cardiac Excitation Using Convex Relaxation

Erem

Dam

Brooks

2014

IEEE Trans. Med. Imaging

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“…As far as we know, the only work that included a (nonpatient-specific) Purkinje network for the study of the ischemia is [10], where the authors studied the effect of such a network on the propagation of arrhythmias. Instead, in [3,42], surrogate models of the PF have been considered, by using a variable-in-space conduction velocity on the endocardium. Table II for subject 1 clearly show the big improvement when the patient-specific network is used to compute the activation times on the endocardium.…”

Section: Resultsmentioning

confidence: 99%

Computational generation of the Purkinje network driven by clinical measurements: The case of pathological propagations

Palamara

Vergara

Catanzariti

et al. 2014

Numer Methods Biomed Eng

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To properly describe the electrical activity of the left ventricle, it is necessary to model the Purkinje fibers, responsible for the fast and coordinate ventricular activation, and their interaction with the muscular propagation. The aim of this work is to propose a methodology for the generation of a patient-specific Purkinje network driven by clinical measurements of the activation times related to pathological propagations. In this case, one needs to consider a strongly coupled problem between the network and the muscle, where the feedback from the latter to the former cannot be neglected as in a normal propagation. We apply the proposed strategy to data acquired on three subjects, one of them suffering from muscular conduction problems owing to a scar and the other two with a muscular pre-excitation syndrome (Wolff-Parkinson-White). To assess the accuracy of the proposed method, we compare the results obtained by using the patient-specific Purkinje network generated by our strategy with the ones obtained by using a non-patient-specific network. The results show that the mean absolute errors in the activation time is reduced for all the cases, highlighting the importance of including a patient-specific Purkinje network in computational models.

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“…An initial earliest node is selected by choosing the resulting wavefront, as determined by the estimated propagation pattern which would follow from a signal triggering activation at that node, whose predicted body surface potentials (BSPs) have the highest correlation with the data. Wavefronts arising from later breakthroughs are then also considered and combined node-wise by retaining the activation time of the first wavefront to arrive [5], [6]. The emphasis of this method is on choosing an initialization with physiologically-plausible propagation behavior that is consistent with the measured BSPs.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the criteria of activation-based inverse electrocardiography using convex optimization

Erem

Dam

Brooks

2011

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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In inverse electrocardiography (ECG), the problem of finding activation times on the heart noninvasively from body surface potentials is typically formulated as a nonlinear least squares optimization problem. Current solutions rely on iterative algorithms which are sensitive to the presence of local minima. As a result, improved initialization approaches for this problem have been of considerable interest. However, in experiments conducted on a subject with Wolff-Parkinson-White syndrome, we have observed that there may be a mismatch between favorable solutions of the optimization problem and solutions with the desired physiological characteristics. In this work, we use a method based on a convex optimization framework to explore the solution space and analyze whether the optimization criteria target their intended objective.

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Application of the fastest route algorithm in the interactive simulation of the effect of local ischemia on the ECG

Cited by 46 publications

References 25 publications

Identifying Model Inaccuracies and Solution Uncertainties in Noninvasive Activation-Based Imaging of Cardiac Excitation Using Convex Relaxation

Identifying Model Inaccuracies and Solution Uncertainties in Noninvasive Activation-Based Imaging of Cardiac Excitation Using Convex Relaxation

Computational generation of the Purkinje network driven by clinical measurements: The case of pathological propagations

Analysis of the criteria of activation-based inverse electrocardiography using convex optimization

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