by Janine Matschek, Andreas Himmel, Friedrich von Haeseler, Eric Bullinger, Martin Skalej, Rolf Findeisen
Abstract:
Mathematical models of the radiofrequency ablation enable to plan, monitor and control interventions allowing to predict and improve their outcome. A system of coupled partial differential equations suitable for planning, analysis and real time implementation is proposed to model the multipolar radiofrequency ablation under consideration of capillary blood perfusion in the spine. To address the multipolar operation, time dependent boundary conditions to the model are introduced. Accounting for the application in the spine, consisting of various tissue types, we consider spatially distributed model parameters. Since the spatially distributed parameters play a key role, analytic expressions for a sensitivity analysis are derived. Based on the model, simulations are performed underlining the quality of the approach and analysing the influence of the spatially distributed parameters.
Reference:
Mathematical Modelling and Sensitivity Analysis of Multipolar Radiofrequency Ablation in the Spine (Janine Matschek, Andreas Himmel, Friedrich von Haeseler, Eric Bullinger, Martin Skalej, Rolf Findeisen), In IFAC-PapersOnLine, volume 48, 2015.
Bibtex Entry:
@inproceedings{matschek_mathematical_2015,
	address = {Berlin},
	series = {20},
	title = {Mathematical {Modelling} and {Sensitivity} {Analysis} of {Multipolar} {Radiofrequency} {Ablation} in the {Spine}},
	volume = {48},
	abstract = {Mathematical models of the radiofrequency ablation enable to plan, monitor and control interventions allowing to predict and improve their outcome. A system of coupled partial differential equations suitable for planning, analysis and real time implementation is proposed to model the multipolar radiofrequency ablation under consideration of capillary blood perfusion in the spine. To address the multipolar operation, time dependent boundary conditions to the model are introduced. Accounting for the application in the spine, consisting of various tissue types, we consider spatially distributed model parameters. Since the spatially distributed parameters play a key role, analytic expressions for a sensitivity analysis are derived. Based on the model, simulations are performed underlining the quality of the approach and analysing the influence of the spatially distributed parameters.},
	booktitle = {{IFAC}-{PapersOnLine}},
	author = {Matschek, Janine and Himmel, Andreas and von Haeseler, Friedrich and Bullinger, Eric and Skalej, Martin and Findeisen, Rolf},
	year = {2015},
	pages = {243--248}
}