Abstract:

Computer models of the heart can improve the understanding of the electrophysiological processes in healthy and diseased heart. They become more and more important for detailled diagnosis of arrhythmias and for optimization of therapy. Models of myocardium cells known today are described - they are based on the properties of all relevant ion channels in the cell membrane. Then it is demonstrated, how many cells can be joined to form a cell patch and how finally the complete heart can be modelled. A simpler approach is using a so called cellular automaton that allows for a significant reduction of calculation time while sacrifying some accordance to reality. Adaptive cellular automatons allow for a fast simulation with acceptable accuracy. Using them some results were gained for the simulation of typical arrhythmias, in the field of validation using an animal model and for therapy planning with RF-ablation.

Abstract:

PURPOSE: To assess respiratory motion models for coronary magnetic resonance angiography (CMRA). In this study various motion models that describe the respiration-induced 3D displacements and deformations of the main coronary arteries were compared.MATERIALS AND METHODS: Multiple high-resolution 3D coronary MR images were acquired in healthy volunteers using navigator-based respiratory gating, each depicting the coronary vessels at different respiratory motion states. In the images representing the different inspiratory states the displacements and deformations of the main coronary vessels with respect to the end-expiratory state were determined, by means of elastic registration. Several correction models (superior-inferior (SI) translation, 3D translation, and 3D affine transformation) were tested and compared with respect to their ability to map a selected inspiratory to the end-expiratory motion state.RESULTS: 3D translation was found to be superior over SI translation, which is commonly used for prospective motion correction in CMRA. The 3D affine transformation was found to be the best correction model considered in this study. Furthermore, a large intersubject variability of the model parameters was observed.CONCLUSION: The results of this study indicate that a patient-adapted 3D correction model (3D translation or better 3D affine) will considerably improve prospective motion correction in CMRA.

Abstract:

Image processing was used as a fundamental tool to derive motion information from magnetic resonance (MR) images, which was fed back into prospective respiratory motion correction during subsequent data acquisition to improve image quality in coronary MR angiography (CMRA) scans. This reduces motion artifacts in the images and, in addition, enables the usage of a broader gating window than commonly used today to increase the scan efficiency. The aim of the study reported in this paper was to find a suitable motion model to be used for respiratory motion correction in cardiac imaging and to develop a calibration procedure to adapt the motion model to the individual patient. At first, the performance of three motion models [one-dimensional translation in feet-head (FH) direction, three-dimensional (3-D) translation, and 3-D affine transformation] was tested in a small volunteer study. An elastic image registration algorithm was applied to 3-D MR images of the coronary vessels obtained at different respiratory levels. A strong intersubject variability was observed. The 3-D translation and affine transformation model were found to be superior over the conventional FH translation model used today. Furthermore, a new approach is presented, which utilizes a fast model-based image registration to extract motion information from time series of low-resolution 3-D MR images, which reflects the respiratory motion of the heart. The registration is based on a selectable global 3-D motion model (translation, rigid, or affine transformation). All 3-D MR images were registered with respect to end expiration. The resulting time series of model parameters were analyzed in combination with additionally acquired motion information from a diaphragmatic MR pencil-beam navigator to calibrate the respiratory motion model. To demonstrate the potential of a calibrated motion model for prospective motion correction in coronary imaging, the approach was tested in CMRA examinations in five volunteers.

Abstract:

Magnetic resonance imaging (MRI) is still contraindicated in patients with implanted active medical devices, as the applied radiofrequency (RF) fields can lead to significant heating of the implants and the electrodes. A head model with an implanted deep brain stimulation electrode (DBS) was exposed to a continuous RF-field similar to the excitational field used in MRI at a frequency of 64 MHz. In this study a two-step procedure for the accurate estimation of electrode-heating during MRI is presented. First the energy loss was calculated in the frequency domain during an applied RF-pulse. Then a thermodynamic algorithm taking heat transfer mechanisms into account was used. The applied method showed to be numerically stable and gave more accurate results than first calculated using a simple worst-case approximation.

Abstract:

Magnetocardiography (MCG) deals with the measurement of biomagnetic fields due to electrical excitation of the heart. The solution of the inverse problem of MCG and electrocardiography (ECG) is the reconstruction and visualization of the excitation process. The calculation is performed from MCG data recorded by multichannel systems. For a maximum of information content an optimized magnetometer arrangement is determined which is not realized at present. The information content with respect to imaging of bioelectric sources is defined by the slope of the singular values, respective the signal-to-noise ratio and the dimension of the nullspace. Reconstruction errors due to modelling errors are not taken into account in this work. The nullspace describes the set of non-detectable source patterns in MCG and ECG. A conventional commercial sensor arrangement will be compared to an improved sensor composition. Recent publications show evidence that MCG contains more or different diagnostic information in cardiac arrhythmia and infarction diagnosis than electrocardiography. Therefore, first results of a general comparison of the information content of MCG and ECG are presented.

Abstract:

Non invasive source reconstruction from Electrocardiography (ECG) and Magnetocardiography (MCG) data is a highly discussed research field. In this work we investigate mathematically the source space of the Inverse Problem of Electrocardiography with respect to the information content. Starting from the modeled source space of distributed epicardial potentials we compare several ECG electrode configurations, i.e. a 32-, 64-optimized channel electrode arrangement, that we determined for our individual torso model, the 256-lead ECG configuration which was recorded at the Ragnar Granit Instiute, Technical University of Tampere, Finland and the 128 channel system of the BioMag Laboratory, Helsinki University Central Hospital, Finland.

Abstract:

Noninvasive Imaging of the bioelectric processes on the heart using Electrocardiography (ECG) and Magnetocardiography (MCG) data is a widely discussed research topic of the recent years. The source space of ECG is compared with the source space of MCG and vice versa to investigate the difference of information content of these mapping techniques for source imaging purposes. The approach allows the calculation of the intersection and non-intersection part (the calculation of silent sources) of MCG (ECG) in comparison to ECG (MCG). The investigation was carried out on a Finite Element model which was constructed from a magnetic resonance imaging (MRI) dataset of a volunteer. Anisotropic fibre orientation was applied to myocardium to investigate its effect on the differences of the source spaces.

Abstract:

A new approach to the reconstruction of transmembrane potentials (TMP) in anisotropic finite element heart model is presented. The solution is sought in the form of 3D patches constructed by the interpolation of TMP distributions. The method is evaluated using TMP distributions generated with a cellular automaton.

Abstract:

The paper presents a simulation of the transient temperature distribution in the human body caused by induced eddy currents during magnetic resonance imaging (MRI). In a first simulation the validity of the used heat conduction equation was proven using a simple example of a cool-down-process of a sphere. Thereafter the heating of a phantom model with an implanted electrode placed in a MRI-System (active body coil) was examined. The resulting increase in temperature was compared with existing measurements. Finally the implications of the heating of the tissue are discussed based on the observed experimental and numerical results.