AUTHOR=Finlay Malcolm C., Xu Lei , Taggart Peter , Hanson Ben , Lambiase Pier TITLE=Bridging the gap between computation and clinical biology: validation of cable theory in humans JOURNAL=Frontiers in Physiology VOLUME=4 YEAR=2013 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2013.00213 DOI=10.3389/fphys.2013.00213 ISSN=1664-042X ABSTRACT=

Introduction: Computerized simulations of cardiac activity have significantly contributed to our understanding of cardiac electrophysiology, but techniques of simulations based on patient-acquired data remain in their infancy. We sought to integrate data acquired from human electrophysiological studies into patient-specific models, and validated this approach by testing whether electrophysiological responses to sequential premature stimuli could be predicted in a quantitatively accurate manner.

Methods: Eleven patients with structurally normal hearts underwent electrophysiological studies. Semi-automated analysis was used to reconstruct activation and repolarization dynamics for each electrode. This S₂ extrastimuli data was used to inform individualized models of cardiac conduction, including a novel derivation of conduction velocity restitution. Activation dynamics of multiple premature extrastimuli were then predicted from this model and compared against measured patient data as well as data derived from the ten-Tusscher cell-ionic model.

Results: Activation dynamics following a premature S₃ were significantly different from those after an S₂. Patient specific models demonstrated accurate prediction of the S₃ activation wave, (Pearson's R² = 0.90, median error 4%). Examination of the modeled conduction dynamics allowed inferences into the spatial dispersion of activation delay. Further validation was performed against data from the ten-Tusscher cell-ionic model, with our model accurately recapitulating predictions of repolarization times (R² = 0.99).

Conclusions: Simulations based on clinically acquired data can be used to successfully predict complex activation patterns following sequential extrastimuli. Such modeling techniques may be useful as a method of incorporation of clinical data into predictive models.