Josephine Granna1, Arya Nabavi2, Jessica Burgner-Kahrs3. 1. Laboratory for Continuum Robotics, Leibniz Universität Hannover, Hanover, Germany. granna@lkr.uni-hannover.de. 2. International Neuroscience Institute, Image Guided Neurosurgical Therapy, Hanover, Germany. 3. Laboratory for Continuum Robotics, Leibniz Universität Hannover, Hanover, Germany.
Abstract
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.
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.
Authors: Evan S McCreedy; Ruida Cheng; Paul F Hemler; Anand Viswanathan; Bradford J Wood; Matthew J McAuliffe Journal: IEEE Trans Inf Technol Biomed Date: 2006-07
Authors: David B Comber; Jonathon E Slightam; Vito R Gervasi; Joseph S Neimat; Eric J Barth Journal: IEEE Trans Robot Date: 2016-01-19 Impact factor: 5.567