<p>This work introduces a new application of the Fractional Dual-Phase-Lag (FDPL) bioheat model to simulate thermo-electrical neuromodulation of epileptic cortex tissue. The FDPL model includes both phase-lag phenomena and fractional-order time derivatives to model non-Fourier, memory-dependent heat conduction in brain tissue under coupled optical and electrical stimulation. A Boundary Element Method (BEM) solution is developed via dual reciprocity to accurately model the spatiotemporal temperature development under realistic boundary conditions, including blood perfusion and nanoparticle-enhanced absorption. Numerical simulations contrast thermal responses for different phase-lag times, blood perfusion rates, and fractional orders. The model confirms localized heating with minimal collateral thermal spread, and Arrhenius-based damage analysis verifies the stimulation within safe, reversible bounds. Parametric analyses highlight the effect of biophysical and operational parameters on thermal outcomes. The proposed model is computationally efficient, clinically flexible, and has excellent potential for planning safe and effective neuromodulation therapy in epilepsy treatment.</p>

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Fractional Dual-Phase-Lag bioheat modeling with boundary elements for Patient-Specific Thermo-Electrical neuromodulation of epileptic cortex

  • Mohamed Abdelsabour Fahmy,
  • Fahad M. Al Subhi

摘要

This work introduces a new application of the Fractional Dual-Phase-Lag (FDPL) bioheat model to simulate thermo-electrical neuromodulation of epileptic cortex tissue. The FDPL model includes both phase-lag phenomena and fractional-order time derivatives to model non-Fourier, memory-dependent heat conduction in brain tissue under coupled optical and electrical stimulation. A Boundary Element Method (BEM) solution is developed via dual reciprocity to accurately model the spatiotemporal temperature development under realistic boundary conditions, including blood perfusion and nanoparticle-enhanced absorption. Numerical simulations contrast thermal responses for different phase-lag times, blood perfusion rates, and fractional orders. The model confirms localized heating with minimal collateral thermal spread, and Arrhenius-based damage analysis verifies the stimulation within safe, reversible bounds. Parametric analyses highlight the effect of biophysical and operational parameters on thermal outcomes. The proposed model is computationally efficient, clinically flexible, and has excellent potential for planning safe and effective neuromodulation therapy in epilepsy treatment.