Concentric Tube Robotics: Non-Linear Trajectories for Epilepsy Surgery

DSpace/Manakin Repository

Concentric Tube Robotics: Non-Linear Trajectories for Epilepsy Surgery

Citable link to this page


Title: Concentric Tube Robotics: Non-Linear Trajectories for Epilepsy Surgery
Author: Oke, Isdin ORCID  0000-0001-5210-6040
Citation: Oke, Isdin. 2016. Concentric Tube Robotics: Non-Linear Trajectories for Epilepsy Surgery. Doctoral dissertation, Harvard Medical School.
Full Text & Related Files:
Abstract: Recurrent and unprovoked epilepsy seizures affect more than 50 million people worldwide. Despite advances in antiepileptic drugs, more than 30% of patients continue to demonstrate abnormal neuronal activity; at present, this is primarily treated with surgical intervention1,2. In 80% of patients with medically intractable seizures, the epileptic focus is located in the medial temporal lobe and neurosurgical treatment of these foci requires large skin incisions, extensive bone removal, and potentially harmful excision of brain tissue, several times the size of the epileptic focus3.
Minimally invasive approaches rely on straight endoscopic cannula to either deliver depth electrodes to further refine the target area or lasers to ablate the epileptogenic tissue. However, straight cannulas struggle to properly access non-linear targets such as the amydalo-hippocampal region often implicated in medial temporal lobe epilepsy. Furthermore, the cannulas must be positioned to avoid critical structures such as blood vessels and cerebrospinal fluid filled ventricles. We propose to overcome the limitations of straight cannulas by introducing curved concentric tubes to perform non-linear 3D minimally invasive trajectories.
Concentric tube robots are composed of multiple superelastic Nitinol tubes arranged telescopically4. Each segment can be independently translated and rotated giving rise to two degrees of freedom that can be modeled computationally. Parameterization of the robot characteristics in conjunction with a global pattern search optimization method can determine the optimal trajectory to achieve the greatest coverage of a target volume5. Semi-automatic segmentation of MRI images can generate surface models of target structures as well as obtain coordinates for entry points and boundary constraints. In addition, we can incorporate weighted constraints for surgically critical structures such as ventricular spaces and blood vessels.
We demonstrate that a multi-segmented concentric tube trajectory can consistently achieve a greater percent coverage of a target hippocampus than a manually defined linear trajectory. We also demonstrate that the total skull surface area from which the target can be approached increases as a function of trajectory complexity. Most interestingly, the magnitude of benefit for each additional segment was found to decay such that the greatest increase in target coverage occurs between N = 1 and N = 2 with very gradual improvement for N > 3. Results suggest that the addition of a single curved segment to a linear laser probe will dramatically increase both the target coverage and potential entry positions. Ultimately, the optimized parameters generated will serve as guidelines to fabricate a prototype concentric tube navigation system. As a novel non-linear surgical platform, concentric tube robotics promises an exciting advance in laser ablation neurosurgery.
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at
Citable link to this page:
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)


Search DASH

Advanced Search