Abstract
PurposeBrain 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 significantly 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 profile 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.MethodsThe 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.ResultsTwelve paired data sets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coefficient was 0.89pm 0.04, representing a statistically significantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 pm 0.03).ConclusionsMulti-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.
Highlights
The primary goal of epilepsy surgery is to remove the epileptogenic zone, the minimum amount of cortex that must be resected to produce seizure freedom [3,16]
As the epileptogenic zone may not be associated with a clear structural abnormality, intracranial electrodes must be used to record the area of the brain where seizures start, known as the seizure-onset zone (SOZ) [3]
We present a novel method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving the robustness and accuracy of vessel extraction within a computer-assisted SEEG planning system [19]
Summary
The primary goal of epilepsy surgery is to remove the epileptogenic zone, the minimum amount of cortex that must be resected to produce seizure freedom [3,16]. As the epileptogenic zone may not be associated with a clear structural abnormality, intracranial electrodes must be used to record the area of the brain where seizures start, known as the seizure-onset zone (SOZ) [3]. Int J CARS (2015) 10:1227–1237 phy (SEEG) is the recording of the brain electrical activity by depth electrodes implanted into the brain parenchyma to precisely identify the SOZ. To reduce the risk of this and other associated complications, it is necessary to identify electrode trajectories with adequate cortical coverage that pass through safe avascular planes. This is done through pre-operative SEEG planning
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