Reconstructing the electrical dynamics on the heart

Rüchardt, Baltasar

dc.contributor.advisor	Parlitz, Ulrich Apl. Prof. Dr.
dc.contributor.author	Rüchardt, Baltasar
dc.date.accessioned	2022-11-09T15:49:17Z
dc.date.available	2022-11-16T00:50:11Z
dc.date.issued	2022-11-09
dc.identifier.uri	http://resolver.sub.uni-goettingen.de/purl?ediss-11858/14331
dc.identifier.uri	http://dx.doi.org/10.53846/goediss-9545
dc.language.iso	eng	de
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.subject.ddc	571.4	de
dc.title	Reconstructing the electrical dynamics on the heart	de
dc.type	doctoralThesis	de
dc.contributor.referee	Parlitz, Ulrich Apl. Prof. Dr.
dc.date.examination	2022-07-21	de
dc.description.abstracteng	The heart is an electro-mechanical system. In 2010 about 4.25 million people died from cardiac arrhythmias. Immediate treatment in case of fibrillation is to shock the heart electrically with high energy to reset the electrical system. However high energy shocks cause severe side effects: the heart tissue is damaged, patients develop anxiety and panic disorders. To reduce these side effects low energy defibrillation methods are developed in the research group biomedical physics (RGBMP) at the Max Planck Institute for Dynamics and Self-Organization. Low energy defibrillation is researched in-vivo and ex-vivo using extracted hearts in Langendorff perfusion. In these experiments the current used for defibrillation is drastically reduced, therefore it is important to understand where the current employed interacts with the heart. For this thesis I rebuilt the experimental setups including shock electrodes and ECG-measurement panels of the RGBMP in-silico using the software Gmsh for computer augmented design (and subsequent computational mesh generation). I extracted the anatomical features of the torso, the heart and the heart muscle's fibre orientation from medical image data and I combined both to create geometrical models of the in-vivo and ex-vivo experiments. I implemented a numerical framework to calculate the current flow in these models and conducted simulation studies together with Master student Simon Wassing. We found out that the ratio of the total current that interacts with the heart is between 8% and 15% of the total current depending on the heart size. Also the positioning of the heart with respect to the electrodes changes the current. We found out that by lowering the heart from a centralised position of the heart between the electrodes in z direction the current flowing through the heart can be increased by up to 20%. Patients with a high risk of cardiac fibrillation usually are under pharmaceutical treatment. If this fails ablation therapy is applied. In ablation therapy parts of the heart are burned either by heat or by cold to stabilize the electrical system in the heart to reduce the probability of arrhythmias. A method called inverse ECG or ECG imaging is researched worldwide to provide information about the properties of the heart tissue to identify the regions to burn. I extended the numerical framework with a method for cardiac electric dynamics, potential reconstruction, diffusion of the potential into the vicinity of the bath and ECG signal integration. The source of the ECG signals is a potential distribution at the outside of the heart. They are referenced against other ECG electrodes to handle that fact that potentials are only defined up to a constant. This can be interpreted as the ECG signal being referenced against a spatial mean. I have found that the spatial mean adds fluctuation to an ECG electrode's signal that is caused by the reference electrodes in a simplified model. To avoid these fluctuations I developed a concept which references against a temporal mean. Comparison of the signals in the simple model shows that the time referenced ECG follows the (in the simulation available) source of the ECG signal better than the spatially-referenced signal. In the context of inverse ECG the reconstructed source has to be compared to the true source to verify the reconstruction. I showed in a simplified model that the Euclidean distance measure quantifies the distance between states very close in time as large and I have proposed an alternative time-based distance measure. First results show that the time-based distance measure I used based on a model for an excitable cell do not provide a better distance measure but in the corresponding outlook I conclude that future work should try employing oscillator model equations. Lastly I found from personal experience the lack of a concept how to think of scientific work and classified it as completing scientific activities. I developed a file system structure that reflects this in order to foster reproducibility and traceability of scientific activities.	de
dc.contributor.coReferee	Wörgötter, Florentin Prof. Dr.
dc.subject.eng	biomedical physics	de
dc.subject.eng	heart	de
dc.subject.eng	physics	de
dc.subject.eng	finite element method	de
dc.subject.eng	langendorff perfusion	de
dc.subject.eng	reproducibility	de
dc.subject.eng	scientific work concepts	de
dc.subject.eng	heart failure	de
dc.subject.eng	simulations	de
dc.subject.eng	electrocardiogram	de
dc.subject.eng	inverse ecg	de
dc.subject.eng	gmsh	de
dc.identifier.urn	urn:nbn:de:gbv:7-ediss-14331-5
dc.affiliation.institute	Göttinger Graduiertenschule für Neurowissenschaften, Biophysik und molekulare Biowissenschaften (GGNB)	de
dc.subject.gokfull	Biologie (PPN619462639)	de
dc.description.embargoed	2022-11-16	de
dc.identifier.ppn	1821399560
dc.identifier.orcid	0000-0002-3857-7767	de
dc.notes.confirmationsent	Confirmation sent 2022-11-10T06:15:01	de

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Das Dokument erscheint in:

GGNB - Göttinger Graduiertenzentrum für Neurowissenschaften, Biophysik und molekulare Biowissenschaften [1114]
GGNB - Göttingen Graduate Center for Neurosciences, Biophysics and Molecular Biosciences

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