Key result
A model-based inverse imaging approach achieved an average localization error of about 1.5 mm in estimating the site of origin of reentrant arrhythmias from body surface potential maps with 5% noise.
Why the study?
Can a model-based imaging approach accurately localize the site of origin of reentrant arrhythmias from body surface potential maps?
Can a model-based imaging approach accurately localize the site of origin of reentrant arrhythmias from body surface potential maps?
A novel model-based imaging approach demonstrates feasibility in accurately localizing the site of origin of reentrant arrhythmias from noninvasive body surface potential maps in a simulation study.
We have developed a model-based imaging approach to inversely estimate the site of origin of reentrant arrhythmia from body su$ace potential maps (BSPM), with the aid of an ion-channel-level cardiac model. The reentry was successfully simulated and maintained. in the cardiac model, and the simulated ECG waveforms over the body sutj5ace corresponding to a mainrained reentry have evident characteristics of ventricular tachycardia. The present simulation results show that the present inverse imaging approach achieved an average localization error of about 1.5 mm when 5% Gaussian white noise was added ro the BSPMs. This pilot simularion study suggests the feasibiliiy of the modelbased imaging approach in localizing the site of origin of reentrant arrhythmias from noninvasive BSPMs.
No takes yet. Share an insight, caveat, or question.
Liu et al. (2005) studied Reentrant arrhythmia. Model-based inverse imaging approach was evaluated on Localization error. A model-based inverse imaging approach achieved an average localization error of about 1.5 mm in estimating the site of origin of reentrant arrhythmias from body surface potential maps with 5% noise.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: