Model-based planning and real-time predictive control for laser-induced thermal therapy

Yusheng Feng, David Fuentes

Research output: Contribution to journalReview articlepeer-review

41 Scopus citations

Abstract

In this article, the major idea and mathematical aspects of model-based planning and real-time predictive control for laser-induced thermal therapy (LITT) are presented. In particular, a computational framework and its major components developed by authors in recent years are reviewed. The framework provides the backbone for not only treatment planning but also real-time surgical monitoring and control with a focus on MR thermometry enabled predictive control and applications to image-guided LITT, or MRgLITT. Although this computational framework is designed for LITT in treating prostate cancer, it is further applicable to other thermal therapies in focal lesions induced by radio-frequency (RF), microwave and high-intensity-focused ultrasound (HIFU). Moreover, the model-based dynamic closed-loop predictive control algorithms in the framework, facilitated by the coupling of mathematical modelling and computer simulation with real-time imaging feedback, has great potential to enable a novel methodology in thermal medicine. Such technology could dramatically increase treatment efficacy and reduce morbidity.

Original languageEnglish (US)
Pages (from-to)751-761
Number of pages11
JournalInternational Journal of Hyperthermia
Volume27
Issue number8
DOIs
StatePublished - Dec 2011

Keywords

  • Bioheat transfer
  • Finite element modelling
  • Laser-induced thermal therapy
  • MR temperature imaging
  • Real-time control

ASJC Scopus subject areas

  • Physiology
  • Physiology (medical)
  • Cancer Research

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