The implementation and first in vivo results of a novel coronary magnetic resonance angiography (MRA) protocol allowing simultaneous acquisition of multiple geometrically independent 3D imaging stacks are presented. Each imaging stack is acquired in a separate cardiac phase using an individual magnetization preparation and navigator-based gating and prospective motion correction. Each stack covers one of the main coronary vessels. Thus, an improvement of scan efficiency was achieved, which was used in this study to reduce total scan time at standard image quality. Experiments performed in healthy volunteers and in patients using a two-stack approach yielded a total scan time reduction of 50% with an image quality equivalent to standard single-stack coronary MRA.
M. A. Golombeck, M. Tabbert, and O. Dössel. Numerische Berechnung elektromagnetischer Felder in einem Oberkörperphantom mit Elektroden bei der Magnetresonanztomographie. In Biomedizinische Technik, vol. 46-1, pp. 464-465, 2001
The inverse problem of electrocardiology might provide a powerful clinical investigation method for visualising the electrical activity of the heart. To use this method one requires accurate models of the human torso and heart. The objective of this work was to create an accurate model of the human ventricles including the valves from images recorded using Magnetic Resonance Imaging (MRI). This model is used as a "generic" model, and is adapted to a given individual with a host mesh fit to spatially registered Ultrasound (US) images.
O. Skipa, F. B. Sachse, C. D. Werner, and O. Dössel. Simulation study of the effect of Modelling errors on the solution of the inverse cardiac source imaging problem using realistic source patterns. In Proc. Computers in Cardiology, vol. 28, pp. 41-44, 2001
The effect of the modelling errors on the solution of the inverseproblem of electrocardiographyis investigated. The electrocardiographicsignal is simulated using ajnite element model of human torso and realistic source patterns gained with a cellular automaton. Noise is added to simulated measurementsand the inverseproblem is solved. Modelling errors consist offalse conductivity assumptions, changed anisotropy ratio of skeletal muscles and geometric errors. The effect of modeling errors on optimal regulariza- tion parameter determination is investigated. The changes in muscle anisotropy and heart position are shown to have the highest effect on reconstructed epicardial potentials. CRESO and L-curve criteria for optimal regularization parameter estimation are compared.