Thermal dose feedback control systems applied to magnetic nanoparticle hyperthermia.

Area of Science:

• Biomedical Engineering
• Computational Modeling
• Oncology

Background:

• Clinical magnetic nanoparticle hyperthermia therapy (MNHT) demands precise energy deposition for effective tumor thermal dosing.
• Achieving a prescribed Cumulative Equivalent Minutes at 43°C (CEM43) is crucial for therapeutic success.
• Existing methods may lack the precision for optimal tumor coverage and boundary temperature control.

Purpose of the Study:

• To design and evaluate a thermal dose feedback control system for MNHT.
• To deliver prescribed CEM43 thermal doses while maintaining safety constraints (max temp < 60°C, boundary temp ~43°C).
• To investigate the efficacy of steerable, spatially confined heating for improved tumor coverage.

Main Methods:

• Integrated system dynamic and finite element analysis were employed for controller design.
• Finite element-bioheat transfer (FE-BHT) simulations were conducted on a human head computational phantom.
• Proportional-integral-derivative (PID) and model predictive control (MPC) were compared for thermal dose delivery using steerable magnetic nanoparticle (MNP) heating domains.

Main Results:

• Steerable spatially confined heating significantly improved the tumor coverage index (CI) by approximately 15%.
• Model predictive control (MPC) achieved the target 80% CI in 67 minutes, outperforming PID which took 80 minutes.
• Simulations confirmed the feasibility of automated control for delivering conformal thermal doses in MNHT.

Conclusions:

• Automated thermal dose feedback control with steerable heating is feasible for MNHT.
• MPC offers a more efficient control strategy compared to PID for achieving therapeutic goals.
• This approach enhances tumor targeting precision and improves the potential efficacy of MNHT.