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.
Conference Contributions (1)
C. Nagel, N. Pilia, L. Unger, and O. Dössel. Performance of Different Atrial Conduction Velocity Estimation Algorithms Improves with Knowledge about the Depolarization Pattern. In Current Directions in Biomedical Engineering, vol. 5(1) , pp. 101-104, 2019
Quantifying the atrial conduction velocity (CV) reveals important information for targeting critical arrhythmia sites that initiate and sustain abnormal electrical pathways, e.g. during atrial flutter. The knowledge about the local CV distribution on the atrial surface thus enhances clinical catheter ablation procedures by localizing pathological propagation paths to be eliminated during the intervention. Several algorithms have been proposed for estimating the CV. All of them are solely based on the local activation times calculated from electroanatomical mapping data. They deliver false values for the CV if applied to regions near scars or wave collisions. We propose an extension to all approaches by including a distinct preprocessing step. Thereby, we first identify scars and wave front collisions and provide this information for the CV estimation algorithm. In addition, we provide reliable CV values even in the presence of noise. We compared the performance of the Triangulation, the Polynomial Fit and the Radial Basis Functions approach with and without the inclusion of the aforementioned preprocessing step. The evaluation was based on different activation patterns simulated on a 2D synthetic triangular mesh with different levels of noise added. The results of this study demonstrate that the accuracy of the estimated CV does improve when knowledge about the depolarization pattern is included. Over all investigated test cases, the reduction of the mean velocity error quantified to at least 25 mm/s for the Radial Basis Functions, 14 mm/s for the Polynomial Fit and 14 mm/s for the Triangulation approach compared to their respective implementations without the preprocessing step. Given the present results, this novel approach can contribute to a more accurate and reliable CV estimation in a clinical setting and thus improve the success of radio-frequency ablation to treat cardiac arrhythmias.
C. Nagel. Robust conduction velocity estimation for a clinical setting. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT). Masterarbeit. 2019
The standard procedure for treating supraventricular tachycardia, like e.g. atrial flutter (AFlut), is radiofrequency ablation (RFA). During an electrophysiological study, intra- cardiac electrograms are measured on the endocardial surface of the atria to monitor the electrical propagation pathways. The mapping system automatically processes the recorded electrograms and thus generates local activation time (LAT) maps. LAT maps provide the basis for the identification of pathological excitation pathways to be blocked during the intervention by creating an ablation line. Besides visually evaluating the LAT maps, the calculation of the conduction velocity (CV) can contribute to quantitatively and robustly identify slow conducting tissue areas classified as arrythmogenic and part of the abnormal excitation pathway. Several different algorithms have already been proposed for computing the CV. However, all of them reported as suitable for the clinical practice are solely based on LAT maps output by the mapping system. They deliver false CV estimates when applied to regions near scars or wave collisions. In this thesis, a CV estimation routine based on measured intracardiac electrograms is elabo- rated. Thereby, LAT maps of clinically acquired electrogram recordings were reconstructed providing the input to the CV computation to follow in a subsequent processing step. For this purpose, the Radial Basis Functions (RBF), the Polynomial Fit, and the Triangulation algorithms were extended to ensure that no excitation was modeled through fibrotic tissue. Furthermore, these methods were improved so that reliable CV values could be obtained in the presence of noise and wave front collisions. The algorithms were evaluated on simulated 2D and 3D test cases with different noise amplitudes added and were applied to clinical mapping data hereafter. The correlation coefficients between the reconstructed LAT maps and the ones generated by the clinical mapping system ranged from 51.6% to 98.6% for all clinical data sets. Looking into the original electrogram signals, the reason for the few LAT maps with low correlation coefficients could be revealed. Among all simulated 2D test cases with a signal to noise ratio of 30dB, the relative velocity error was smaller than 3.1%, 2.7% and 9.4% for the RBF, the Polynomial Fit and the Triangulation approach, respectively. Furthermore, the RBF and the Triangulation algorithm yielded plausible CV estimates in a realistic range for all clinically acquired mapping data. Given the present results, the proposed CV estimation routine succeeds at addressing the major drawbacks of the existing algorithms and can thus contribute to a more robust CV assessment during electroanatomical mapping procedures to enhance the diagnosis and treatment of cardiac arrhythmias.