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<p>Laser-induced thermotherapy (LITT) offers a minimally invasive approach to tumor ablation but requires accurate modeling of photon transport, heat deposition, and thermo-mechanical tissue response. Conventional bioheat and diffusion-based models oversimplify these interactions, especially in irregular, heterogeneous tumors. To overcome this, a Monte Carlo–Dual Reciprocity Boundary Element Method (MC-DRBEM) framework is developed, combining stochastic photon transport with nonlinear bioheat and thermoelastic stress analysis. The method efficiently handles complex geometries using boundary-only discretization and accounts for temperature-dependent properties. Validation against analytical and finite element benchmarks shows strong accuracy. Results highlight the significant role of tissue anisotropy and functional grading on stress distribution, with isotropic tissues showing highest stress sensitivity. Parametric studies further confirm the model’s robustness in predicting temperature gradients and safe ablation margins. Overall, MC-DRBEM provides a scalable, geometry-aware tool for patient-specific treatment planning in laser-based cancer therapy.</p>

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Advanced MC-DRBEM analysis of bio-thermo-mechanical model for photon transport in complex shape tumors during laser irradiation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月7日

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  • Mohamed Abdelsabour Fahmy,
  • Fahad M. Al Subhi

摘要

Laser-induced thermotherapy (LITT) offers a minimally invasive approach to tumor ablation but requires accurate modeling of photon transport, heat deposition, and thermo-mechanical tissue response. Conventional bioheat and diffusion-based models oversimplify these interactions, especially in irregular, heterogeneous tumors. To overcome this, a Monte Carlo–Dual Reciprocity Boundary Element Method (MC-DRBEM) framework is developed, combining stochastic photon transport with nonlinear bioheat and thermoelastic stress analysis. The method efficiently handles complex geometries using boundary-only discretization and accounts for temperature-dependent properties. Validation against analytical and finite element benchmarks shows strong accuracy. Results highlight the significant role of tissue anisotropy and functional grading on stress distribution, with isotropic tissues showing highest stress sensitivity. Parametric studies further confirm the model’s robustness in predicting temperature gradients and safe ablation margins. Overall, MC-DRBEM provides a scalable, geometry-aware tool for patient-specific treatment planning in laser-based cancer therapy.