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Critical Reviews™ in Biomedical Engineering
SJR: 0.207 SNIP: 0.376 CiteScore™: 0.79

ISSN Druckformat: 0278-940X
ISSN Online: 1943-619X

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Critical Reviews™ in Biomedical Engineering

DOI: 10.1615/CritRevBiomedEng.v38.i1.70
pages 79-100

Laser-Induced Thermal Therapy for Tumor Ablation

R. Jason Stafford
Departments of Imaging Physics, The University of Texas M. D. Anderson Cancer Center, USA
David Fuentes
Departments of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, USA
Andrew A. Elliott
Departments of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, USA
Jeffrey S. Weinberg
Departments of Neurosurgery, The University of Texas M.D. Anderson Cancer Center, USA
Kamran Ahrar
Departments of Diagnostic Radiology, The University of Texas M.D. Anderson Cancer Center, USA


Image-guided ablation of tumors is assuming an increasingly important role in many oncology services as a minimally invasive alternative to conventional surgical interventions for patients who are not good candidates for surgery. Laser-induced thermal therapy (LITT) is a percutaneous tumor-ablation technique that utilizes high-power lasers placed interstitially in the tumor to deliver therapy. Multiple laser fibers can be placed into the treatment volume and, unlike other interstitial heating techniques, can be fired simultaneously to rapidly treat large volumes of tissue. Modern systems utilize small, compact, high-power laser diode systems with actively cooled applicators to help keep tissue from charring during procedures. Additionally, because this approach to thermal therapy is easily made magnetic resonance (MR) compatible, the incorporation of magnetic resonance imaging (MRI) for treatment planning, targeting, monitoring, and verification has helped to expand the number of applications in which LITT can be applied safely and effectively. We provide an overview of the clinically used technology and algorithms that provide the foundations for current state-of-the-art MR-guided LITT (MRgLITT), including procedures in the brain, liver, bone, and prostate as examples. In addition to advances in imaging and delivery, such as the incorporation of nanotechnology, next-generation MRgLITT systems are anticipated to incorporate an increasing presence of in silico-based modeling of MRgLITT procedures to provide human-assisted computational tools for planning, MR model-assisted temperature monitoring, thermal-dose assessment, and optimal control.

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