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Stability, Structure and Scale: Improvements in Multi-modal Vessel Extraction for SEEG Trajectory Planning

Zuluaga Valencia, MA; Rodionov, R; Nowell, M; Achhala, S; Zombori, G; Mendelson, AF; Cardoso, MJ; ... Ourselin, S; + view all (2015) Stability, Structure and Scale: Improvements in Multi-modal Vessel Extraction for SEEG Trajectory Planning. International Journal of Computer Assisted Radiology and Surgery , 10 (8) pp. 1227-1237. 10.1007/s11548-015-1174-5. Green open access

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Abstract

Purpose Brain vessels are among the most critical landmarks that need to be assessed for mitigating surgical risks in stereo-electroencephalography (SEEG) implantation. Intracranial haemorrhage is the most common complication associated with implantation, carrying signi cant associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice, neurosurgeons have no assistance in the planning of electrode trajectories. There is great interest in developing computer assisted planning systems that can optimise the safety pro le of electrode trajectories, maximising the distance to critical structures. This paper presents a method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving robustness and accuracy of vessel extraction within a SEEG planning system. Methods The developed method accounts for scale and vicinity of a voxel by formulating the problem within a multi-scale tensor voting framework. Feature stability is achieved through a similarity measure that evaluates the multi-modal consistency in vesselness responses. The proposed measurement allows the combination of multiple images modalities into a single image that is used within the planning system to visualise critical vessels. Results Twelve paired datasets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coe cient was 0.89 ± 0.04, representing a statistically signi cantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 ±0.03). Conclusions Multi-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.

Type: Article
Title: Stability, Structure and Scale: Improvements in Multi-modal Vessel Extraction for SEEG Trajectory Planning
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s11548-015-1174-5
Publisher version: http://dx.doi.org/10.1007/s11548-015-1174-5
Language: English
Additional information: Copyright © The Author(s) 2015. This article is published with open access at Springerlink.com. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
Keywords: Computer-assisted planning system, Vessel extraction, Depth electrode insertion, Image-guided surgery, Multi-modal segmentation.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Experimental Epilepsy
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1463456
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