Why the study?
Does a new C++ conjugate gradient optimizer reduce computation time for noninvasive cardiac activation time imaging compared to the previous Fortran 77 implementation?
Does a new C++ conjugate gradient optimizer reduce computation time for noninvasive cardiac activation time imaging compared to the previous Fortran 77 implementation?
A newly developed C++ conjugate gradient optimizer significantly accelerates the computation of noninvasive cardiac activation maps, making it potentially viable for clinical routine use in localizing focal arrhythmogenic substrates.
Answers are grounded in this paper and cite their sources.
Accelerates noninvasive cardiac activation mapping; leaves open whether faster computation enables routine clinical use.
OBJECTIVE: The computer model-based computation of the cardiac activation sequence in humans has been recently subject of successful clinical validation. This method is of potential interest for guiding ablation therapy of arrhythmogenic substrates. However, computation times of almost an hour are unattractive in a clinical setting. Thus, the objective is the development of a method which performs the computation in a few minutes run time. METHODS: The computationally most expensive part is the product of the lead field matrix with a matrix containing the source pattern on the cardiac surface. The particular biophysical properties of both matrices are used for speeding up this operation by more than an order of magnitude. A conjugate gradient optimizer was developed using C++ for computing the activation map. RESULTS: The software was tested on synthetic and clinical data. The increase in speed with respect to the previously used Fortran 77 implementation was a factor of 30 at a comparable quality of the results. As an additional finding the coupled regularization strategy, originally introduced for saving computation time, also reduced the sensitivity of the method to the choice of the regularization parameter. CONCLUSIONS: As it was shown for data from a WPWpatient the developed software can deliver diagnostically valuable information at a much shorter span of time than current clinical routine methods. Its main application could be the localization of focal arrhythmogenic substrates.
No takes yet. Share an insight, caveat, or question.
Pfeifer et al. (2005) studied Arrhythmogenic substrates / Wolff-Parkinson-White syndrome. C++ conjugate gradient optimizer for cardiac activation map computation vs. Fortran 77 implementation was evaluated on Computation speed (factor of 30 increase in speed).
Synapse has enriched 10 related papers. Consider them for comparative context: