Computer-assisted planning for a concentric tube robotic system in neurosurgery

Purpose Laser-induced thermotherapy in the brain is a minimally invasive procedure to denature tumor tissue. However, irregularly shaped brain tumors cannot be treated using existing commercial systems. Thus, we present a new concept for laser-induced thermotherapy using a concentric tube robotic sy...

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Bibliographic Details
Published in:International journal for computer assisted radiology and surgery 2019-02, Vol.14 (2), p.335-344
Main Authors: Granna, Josephine, Nabavi, Arya, Burgner-Kahrs, Jessica
Format: Article
Language:English
Subjects:
Ablation
Algorithms
Brain
Brain cancer
Brain Neoplasms - surgery
Computer Imaging
Computer Science
Configuration management
Design optimization
Design parameters
Health Informatics
Humans
Hyperthermia, Induced - methods
Imaging
Laser Therapy - methods
Lasers
Medicine
Medicine & Public Health
Multiple objective analysis
Neurosurgical Procedures - methods
Original Article
Pareto optimization
Particle swarm optimization
Pattern Recognition and Graphics
Radiology
Robotic Surgical Procedures - methods
Robots
Surgery
Surgery, Computer-Assisted - methods
Trajectories
Tumors
Vision
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Summary:Purpose Laser-induced thermotherapy in the brain is a minimally invasive procedure to denature tumor tissue. However, irregularly shaped brain tumors cannot be treated using existing commercial systems. Thus, we present a new concept for laser-induced thermotherapy using a concentric tube robotic system. The planning procedure is complex and consists of the optimal distribution of thermal laser ablations within a volume as well as design and configuration parameter optimization of the concentric tube robot. Methods We propose a novel computer-assisted planning procedure that decomposes the problem into task- and robot-specific planning and uses a multi-objective particle swarm optimization algorithm with variable length. Results The algorithm determines a Pareto-front of optimal ablation distributions for three patient datasets. It considers multiple objectives and determines optimal robot parameters for multiple trajectories to access the tumor volume. Conclusions We prove the effectiveness of our planning procedure to enable the treatment of irregularly shaped brain tumors. Multiple trajectories further increase the applicability of the procedure.
ISSN:1861-6410
1861-6429
DOI:10.1007/s11548-018-1890-8