Year: 2011
Type: review
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: Yusheng Feng, David Fuentes
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
Awards: MRTI Guided Integrative Model for Cancer Treatment, Integrating High Performance Computing in Research and Education for Simulation, Visualization and Real-Time Prediction, Prospective 3-D Treatment Planning for MR-Guided Laser Induced Thermal Therapy Pr, G5962125885, Collaborative Research: DDDAS-TMRP: Dynamic Data-Driven System for Laser Treatment of Cancer, Medical Physics Training Grant for Image-Guided Therapy Research
OpenAlex ID: W2168652875