-Norm Regularization in Volumetric Imaging of Cardiac Current Sources

Advances in computer vision have substantially improved our ability to analyze the structure and mechanics of the heart. In comparison, our ability to observe and analyze cardiac electrical activities is much limited. The progress to computationally reconstruct cardiac current sources from noninvasive voltage data sensed on the body surface has been hindered by the ill-posedness and the lack of a unique solution of the reconstruction problem. Common L2- and L1-norm regularizations tend to produce a solution that is either too diffused or too scattered to reflect the complex spatial structure of current source distribution in the heart. In this work, we propose a general regularization with Lp-norm () constraint to bridge the gap and balance between an overly smeared and overly focal solution in cardiac source reconstruction. In a set of phantom experiments, we demonstrate the superiority of the proposed Lp-norm method over its L1 and L2 counterparts in imaging cardiac current sources with increasing extents. Through computer-simulated and real-data experiments, we further demonstrate the feasibility of the proposed method in imaging the complex structure of excitation wavefront, as well as current sources distributed along the postinfarction scar border. This ability to preserve the spatial structure of source distribution is important for revealing the potential disruption to the normal heart excitation

Kalbin Elektriksel Aktivitesinin 3 Boyutlu Transmembran Potansiyel Dağılımları Cinsinden Girişimsiz Olarak Görüntülenmesi

TÜBİTAK EEEAG Proje01.04.2015Vücut yüzeyi potansiyel (VYP) ölçümlerinden kalpteki elektriksel kaynakların kestirilmesine ters elektrokardiografi (EKG) problemi denir. Bu yöntem, ölümcül de olabilecek kalp hastalıklarının teşhisinde ve tedavi planlamasında hekimlere yol gösterme potansiyeline sahiptir. Ancak, bu problem kötü konumlanmış bir problemdir ve ölçümlerdeki az miktarda gürültü bile sınırsız çözümler bulunmasına yol açmaktadır. Bunun üstesinden gelebilmek için literatürde, başta Tikhonov düzenlileştirmesi olmak üzere çeşitli düzenlileştirme yöntemleri uygulanmıştır. Ancak uygulanan her yöntem farklı durumlarda test edilmiştir; henüz hangi yöntemin en iyi yöntem olduğu konusunda fikir birliği sağlanamamıştır. Son zamanlarda, üç boyutlu miyokart dokusunda da detaylı bilgi verebildiği için, transmembran potansiyelleri (TMP) cinsinden ters EKG çözümleri popülerleşmiştir. Ancak henüz bu alanda az sayıda çalışma vardır ve özellikle farklı kalp aritmilerinde farklı yöntemlerin nasıl performans sergileyeceği bilinmemektedir. Bu projede temel amaç, bu açığı kapatmak, farklı elektriksel dağılımlar için literatürdeki belli başlı yöntemlerle ters EKG problemini çözmektir. Bu projede, kapsamlı bir çalışmayla, önerilen yöntemlerin performansları aynı test verisiyle ve aynı kriterler kullanılarak objektif bir şekilde karşılaştırılabilmiştir. Ayrıca farklı aritmiler için TMP benzetimleri ve buna bağlı VYPler elde edildiği için, yöntemlerin bu farklı aritmiler karşısında nasıl bir performans sergilediği de araştırılmıştır. Öncelikle Aliev-Panfilov yöntemiyle farklı kalp aktiviteleri için TMP benzetimleri yapılmış, ardından ileri EKG problemi çözülerek bu dağılımlardan VYP dağılımları bulunmuştur. Bu dağılımlar ters EKG çözümlerinde kullanılmıştır. Uygulanan beş değişik ters EKG çözüm yönteminden her durumda en başarılı yöntemin Bayesian MAP olduğu gözlenmiştir. TTLS, LTTLS ve LSQR yöntemlerinin de uyarım noktalarını ve dalga önünü bulmakta çok kötü performans sergilemediği görülmüştür. Bu proje kapsamında iki ayrı dalda daha literatüre katkı sağlanmıştır. Bunlardan ilki, fiber yönelimlerinin TMP dağılımlarına etkilerinin incelenmesidir. Başka bir kalpten aktarılan fiber yönelimini kullanmanın izotropik varsayım kullanmaktan daha doğru sonuçlar verdiği gözlenmiştir. İkinci katkı da, TMP dağılımları cinsinden FEM yöntemi ile ileri problem çözümünün doğrulamasıdır. Uygun ağ sıklığına ulaşıldığında sayısal çözümün analitik çözüme yakınsadığı gösterilmiştir.Inverse electrocardiography is the estimation of cardiac electrical sources from body surface potential (BSP) measurements. Inverse solutions can guide the physicians for diagnosis and treatment planning of lethal heart diseases. However, inverse problem is ill-posed and even small perturbations in the measurements yield unbounded errors in the solutions. To overcome this difficulty, many regularization approaches have been proposed in literature. However, these methods have been applied and tested under varying conditions in different studies; there is no consensus among researchers on the method with the best performance. Lately, solutions in terms of transmembrane potentials (TMP) have become popular, since they provide information about the electrical activity of the three dimensional myocardium. There are few studies in this area and it is still an open question how different methods will perform under different arrythmia conditions. The main goal in this project is to solve the inverse problem in terms of TMPs, using different approaches but under the same (and diverse) cardiac conditions. First, we obtained TMP distributions for various cardiac electrical activity assumptions using Aliev-Panfilov model. Then we solved the forward ECG problem to obtain the corresponding BSPs, which were later used in the inverse problem solutions. Among the five inverse approaches, Bayesian MAP estimation had the best performance under all conditions. TTLS, LTTLS and LSQR were also successful in finding the initial stimulation points and recovering the wavefront. We made contributions in two more areas in this project. The first one is our study of fiber orientation effects on TMP distributions. We found that even using fiber orientations from a different heart is much better than using the isotropic assumption. The second one is the analytical verification of the FEM based forward problem; with an appropriate mesh size, we showed that the numerical solution converges to the analytical solution

Solving the Inverse Problem of Electrocardiography on the Endocardium Using a Single Layer Source

The inverse problem of electrocardiography consists in reconstructing cardiac electrical activity from given body surface electrocardiographic measurements. Despite tremendous progress in the field over the last decades, the solution of this problem in terms of electrical potentials on both epi- and the endocardial heart surfaces with acceptable accuracy remains challenging. This paper presents a novel numerical approach aimed at improving the solution quality on the endocardium. Our method exploits the solution representation in the form of electrical single layer densities on the myocardial surface. We demonstrate that this representation brings twofold benefits: first, the inverse problem can be solved for the physiologically meaningful single layer densities. Secondly, a conventional transfer matrix for electrical potentials can be split into two parts, one of which turned out to posess regularizing properties leading to improved endocardial reconstructions. The method was tested in-silico for ventricular pacings utilizing realistic CT-based heart and torso geometries. The proposed approach provided more accurate solution on the ventricular endocardium compared to the conventional potential-based solutions with Tikhonov regularization of the 0th, 1st, and 2nd orders. Furthermore, we show a uniform spatio-temporal behavior of the single layer densities over the heart surface, which could be conveniently employed in the regularization procedure

Functional Mapping of Three-Dimensional Electrical Activation in Ventricles

University of Minnesota Ph.D. dissertation. 2010. Major: Biomedical Engineering. Advisor: Bin He. 1 computer file (PDF); 139 pages.Ventricular arrhythmias account for nearly 400,000 deaths per year in the United States alone. Electrical mapping of the ventricular activation could facilitate the diagnosis and treatment of arrhythmias, e.g. guiding catheter ablation. To date, both direct mapping and non-contact mapping techniques have been routinely used in electrophysiology labs for obtaining the electrical activity on the endocardial surface. Non-invasive functional mapping methods are also developed to estimate the electrical activity on the epicardium or on both epicardium and endocardium from the body surface measurements. Though successful, the results using above methods are all limited on the surface of the heart and thus cannot directly characterize the cardiac events originating within the myocardial wall. Our group's goal is to develop a functional mapping method to estimate the three-dimensional cardiac electrical activity from either non-invasive body surface potential maps or minimally-invasive intracavitary potential maps, by solving the so-called "inverse problem". Hence the information under the surface of the heart could be revealed to better characterize the cardiac activation. In the present thesis study, the previously developed three-dimensional cardiac electrical imaging (3DCEI) approach has been further investigated. Its function is expanded for not only estimating the global activation sequence but also reconstructing the potential at any myocardial site throughout the ventricle. New algorithms under the 3DCEI scheme are also explored for more powerful mapping capability. The performance of the enhanced 3DCEI approach is rigorously evaluated in both control and diseased swine models when the clinical settings are mimicked. The promising results validate the feasibility of estimating detailed three-dimensional cardiac activation by using the 3DCEI approach, and suggest that 3DCEI has great potential of guiding the clinical management of cardiac arrhythmias in a more efficient way

Doctor of Philosophy

dissertationInverse Electrocardiography (ECG) aims to noninvasively estimate the electrophysiological activity of the heart from the voltages measured at the body surface, with promising clinical applications in diagnosis and therapy. The main challenge of this emerging technique lies in its mathematical foundation: an inverse source problem governed by partial differential equations (PDEs) which is severely ill-conditioned. Essential to the success of inverse ECG are computational methods that reliably achieve accurate inverse solutions while harnessing the ever-growing complexity and realism of the bioelectric simulation. This dissertation focuses on the formulation, optimization, and solution of the inverse ECG problem based on finite element methods, consisting of two research thrusts. The first thrust explores the optimal finite element discretization specifically oriented towards the inverse ECG problem. In contrast, most existing discretization strategies are designed for forward problems and may become inappropriate for the corresponding inverse problems. Based on a Fourier analysis of how discretization relates to ill-conditioning, this work proposes refinement strategies that optimize approximation accuracy o f the inverse ECG problem while mitigating its ill-conditioning. To fulfill these strategies, two refinement techniques are developed: one uses hybrid-shaped finite elements whereas the other adapts high-order finite elements. The second research thrust involves a new methodology for inverse ECG solutions called PDE-constrained optimization, an optimization framework that flexibly allows convex objectives and various physically-based constraints. This work features three contributions: (1) fulfilling optimization in the continuous space, (2) formulating rigorous finite element solutions, and (3) fulfilling subsequent numerical optimization by a primal-dual interiorpoint method tailored to the given optimization problem's specific algebraic structure. The efficacy o f this new method is shown by its application to localization o f cardiac ischemic disease, in which the method, under realistic settings, achieves promising solutions to a previously intractable inverse ECG problem involving the bidomain heart model. In summary, this dissertation advances the computational research of inverse ECG, making it evolve toward an image-based, patient-specific modality for biomedical research

Non-Invasive Electrocardiographic Imaging of Ventricular Activities: Data-Driven and Model-Based Approaches

Die vorliegende Arbeit beleuchtet ausgewählte Aspekte der Vorwärtsmodellierung, so zum Beispiel die Simulation von Elektro- und Magnetokardiogrammen im Falle einer elektrisch stillen Ischämie sowie die Anpassung der elektrischen Potentiale unter Variation der Leitfähigkeiten. Besonderer Fokus liegt auf der Entwicklung neuer Regularisierungsalgorithmen sowie der Anwendung und Bewertung aktuell verwendeter Methoden in realistischen in silico bzw. klinischen Studien

Non-Invasive Electrocardiographic Mapping of Arrhythmia and Arrhythmogenic substrate in the Human Ventricle.

PhD Theses.The ablation of ventricular tachycardia often involves mapping when the arrhythmia is ongoing. This is often limited by haemodynamic instability. Non-invasive electrocardiographic mapping (ECGI) may aid in the mapping process by allowing expedient localisation. However, insufficient testing of this technology against ground truth data has been conducted. Furthermore, the system could have utility in detection of arrhythmogenic substrate. Current clinical practice uses echocardiography to risk stratify patients for implantation of intracardiac defibrillators (ICDs). Invasive epicardial electrogram data was collected in 8 patients. Activation and repolarisation times were compared to ECGI derived data showing modest correlation. A detailed analysis of ventricular tachycardia sites of origin in the heart was elucidated using validated electrophysiological techniques. These were compared to ECGI derived data in 18 patients, showing better accuracy than the 12 lead ECG with a resolution of ~2.2cm suggesting it may be a useful adjunctive tool in mapping unstable VT. ECGI derived data collected during sinus rhythm was compared to invasive electrogram maps in 16 patients. The capacity of ECGI to localise scar showed modest accuracy. ECGI and Cardiac MRI scans were performed in 21 patients with cardiac amyloidosis. ECGI showed cardiac amyloidosis to be associated with both ventricular conduction and repolarization abnormalities, supporting the hypothesis that arrhythmic mechanisms may be linked to mortality in this condition