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<p>Hyperthermia is increasingly recognized as an effective adjunctive therapy for cancer treatment, yet its clinical impact depends on accurate and rapid treatment planning tailored to patient anatomy. This work presents a multi-anatomical hyperthermia treatment planning framework designed for both brain and breast tumors, two clinically relevant sites with distinct anatomical and technical challenges. The proposed framework, referred to as the MATLAB-based brain and breast hyperthermia simulator, is based on the finite element method (FEM) and serves as a computationally efficient alternative to commonly used finite-difference time-domain (FDTD) platforms such as Sim4Life. The proposed framework integrates three-dimensional finite-element electromagnetic and thermal modeling with annular phased-array dipole applicators (twelve elements for brain and eight for breast), operating at 915 MHz to enable deep penetration and localized heating. A convex optimization strategy based on Second-Order Cone Programming is employed to determine phase and amplitude excitation coefficients that maximize tumor heating while suppressing unwanted hotspots in healthy tissue. Validation was performed across five tumor locations per anatomy using the Duke head model, segmented breast phantoms, and geometry-matched breast and head phantoms implemented in Sim4Life and COMSOL Multiphysics for FDTD- and FEM-based benchmarking. Quantitative evaluation using European Society of Hyperthermic Oncology recommended specific absorption rate (SAR) and temperature quality indicators demonstrates close agreement with benchmark simulations in terms of SAR focusing, thermal coverage, and peak temperature metrics. Overall, this study introduces a unified and computationally efficient FEM-based framework for brain and breast hyperthermia planning, validated against both FDTD- and FEM-based platforms.</p>

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Computational multi-anatomical framework for optimized non-invasive heating of brain and breast tumors

  • 期刊论文

  • 发表日期：

    2026年8月3日

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  • Zain Ul Abdin,
  • Youngdae Cho,
  • Dongnyoung Lee,
  • Hyoungsuk Yoo

摘要

Hyperthermia is increasingly recognized as an effective adjunctive therapy for cancer treatment, yet its clinical impact depends on accurate and rapid treatment planning tailored to patient anatomy. This work presents a multi-anatomical hyperthermia treatment planning framework designed for both brain and breast tumors, two clinically relevant sites with distinct anatomical and technical challenges. The proposed framework, referred to as the MATLAB-based brain and breast hyperthermia simulator, is based on the finite element method (FEM) and serves as a computationally efficient alternative to commonly used finite-difference time-domain (FDTD) platforms such as Sim4Life. The proposed framework integrates three-dimensional finite-element electromagnetic and thermal modeling with annular phased-array dipole applicators (twelve elements for brain and eight for breast), operating at 915 MHz to enable deep penetration and localized heating. A convex optimization strategy based on Second-Order Cone Programming is employed to determine phase and amplitude excitation coefficients that maximize tumor heating while suppressing unwanted hotspots in healthy tissue. Validation was performed across five tumor locations per anatomy using the Duke head model, segmented breast phantoms, and geometry-matched breast and head phantoms implemented in Sim4Life and COMSOL Multiphysics for FDTD- and FEM-based benchmarking. Quantitative evaluation using European Society of Hyperthermic Oncology recommended specific absorption rate (SAR) and temperature quality indicators demonstrates close agreement with benchmark simulations in terms of SAR focusing, thermal coverage, and peak temperature metrics. Overall, this study introduces a unified and computationally efficient FEM-based framework for brain and breast hyperthermia planning, validated against both FDTD- and FEM-based platforms.