title: Model-based planning and real-time predictive control for laser-induced thermal therapy.
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.
authors.affiliation: Computational Bioengineering and Control Lab, The University of Texas at San Antonio, USA. yusheng.feng@utsa.edu
authors.forename: Yusheng
authors.initials: Y
authors.lastname: Feng
authors.forename: David
authors.initials: D
authors.lastname: Fuentes
mesh_terms: D055011:Ablation Techniques; D000465:Algorithms; D003198:Computer Simulation; D003199:Computer Systems; D006801:Humans; D006979:Hyperthermia, Induced; D053685:Laser Therapy; D008297:Male; D008954:Models, Biological; D016343:Monitoring, Intraoperative / Q000379:methods*; D011471:Prostatic Neoplasms / Q000601:surgery
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