A patient-specific computational study of transvenous defibrillation [segmented CT images]

The goal of this study is to assess the predictive capacity of computational models of transvenous defibrillation by comparing the results of patient-specific simulations to clinically determined defibrillation metrics. Solutions for seven patient-specific models have been completed. The 3-D models of the thorax and in situ electrodes were created from segmented CT images taken shortly after implant. Each of the 3-D models was created by defining each voxel in the segmented data set as a volume element in the computational model. The electric field distribution during defibrillation was computed using the finite volume method. The critical mass hypothesis was used to define a successful shock and to determine the defibrillation metrics from the calculated field distribution. Simulated defibrillation thresholds yielded good estimates of the clinically determined thresholds in 4 of the 7 patients examined. The model-predicted impedances correlate well with the clinical measurements. These results are promising and provide preliminary support to the potential utility of this modeling approach for patient-specific surgical planning of cardioverter defibrillator implantation and for evaluating new electrode configurations.