A Hierarchical Laser Control Strategy for Spatially Uniform Thermal Dose Delivery in Laser-Induced Thermal Therapy

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Laser-induced hyperthermia and ablation treatments are promising modalities in oncology, ophthalmology, cardiology, urology, and dermatology, offering minimally invasive alternatives to conventional treatment approaches. Precise spatiotemporal control of laser-induced thermal energy delivery to the target, while minimizing collateral damage to surrounding healthy tissues, is the key to achieving the desired treatment efficacy. However, nonlinear bioheat transfer processes, patient-specific tissue characteristics, diverse treatment objectives, and disturbances present significant challenges in spatiotemporal laser control for achieving precise thermal dose delivery. This article introduces a novel hierarchical laser control architecture comprising two main layers: a multiobjective genetic algorithm to determine the optimal global laser irradiation strategy and a model predictive control to optimize the local thermal dose distribution. The proposed architecture was validated on the phantom and ex vivo porcine tissue. Results demonstrate the uniform and accurate spatial thermal dose delivery across various scenarios, including arbitrary target thermal dose, target treatment temperatures, target area geometries, and heterogeneous and varying biothermal properties. The significance lies in enhancing the precision and efficacy of personalized treatment in real clinical scenarios for robotic-assisted laser-induced thermal therapies, while offering a generalizable control paradigm for diverse thermal therapy modalities employing alternative heat sources.

Original languageEnglish
JournalIEEE/ASME Transactions on Mechatronics
DOIs
Publication statusPublished - Dec 2025

Keywords

  • Hyperthermia therapy
  • medical mechatronics
  • model predictive control (MPC)
  • robotics
  • thermal imaging

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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