a-pipeline-for-3d-multimodality-image-integration-computer-assisted

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Epilepsy surgery is challenging and the use of 3D multimodality image integration (3DMMI) to aid presurgical planning is well-established. Multimodality ...

UCL Institute of Neurology

StereoEEG implantation is performed in patients with epilepsy to determine the site of the seizure onset zone. Intracranial haemorrhage is the most common complication associated to implantation carrying a risk that ranges from 0.6 to 2.7%, with significant 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 the electrode trajectories. There is great interest in developing computer assisted planning systems that can optimize the safety profile of electrode trajectories, maximizing the distance to critical brain structures. In this work, we address the problem of blood vessel extraction for SEEG trajectory planning. The proposed method exploits the availability of multi-modal images within a trajectory planning system to formulate a vessel extraction framework that combines the scale and the neighbouring structure of an object. We validated the proposed method in twelve multi-modal patient image sets. The mean Dice similarity coefficient (DSC) was 0.88 ± 0.03, representing a statistically significantly improvement when compared to the semi-automated single rater, single modality segmentation protocol used in current practice (DSC = 0.78 ± 0.02).

SEEG trajectory planning: combining stability, structure and scale in vessel extraction.

We present a single-center prospective study, validating the use of 3D multimodality imaging (3 DMMI) in patients undergoing intracranial electroencephalography (IC-EEG).

Utility of 3D multimodality imaging in the implantation of intracranial electrodes in epilepsy.

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 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.

Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

To determine whether resection of areas with evidence of intense, synchronized neural firing during seizures is an accurate indicator of postoperative outcome.

Seizure localization using ictal phase-locked high gamma: A retrospective surgical outcome study.

Increased levels of asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA) are associated with cardiovascular and renal diseases. We and others have shown that both ADMA and SDMA can be Nα-acetylated to form asymmetric and symmetric Nα-acetyldimethylarginine (Ac-ADMA and Ac-SDMA). The current study further investigated this undercharacterized metabolic pathway.

Acetylation of asymmetric and symmetric dimethylarginine: an undercharacterized pathway of metabolism of endogenous methylarginines.

OBJECT The objective of this study was to evaluate the clinical utility of multitrajectory computer-assisted planning software (CAP) to plan stereoelectroencephalography (SEEG) electrode arrangements. METHODS A cohort of 18 patients underwent SEEG for evaluation of epilepsy at a single center between August 2013 and August 2014. Planning of electrodes was performed manually and stored using EpiNav software. CAP was developed as a planning tool in EpiNav. The user preselects a set of cerebral targets and optimized trajectory constraints, and then runs an automated search of potential scalp entry points and associated trajectories. Each trajectory is associated with metrics for a safety profile, derived from the minimal distance to vascular structures, and an efficacy profile, derived from the proportion of depth electrodes that are within or adjacent to gray matter. CAP was applied to the cerebral targets used in the cohort of 18 previous manually planned implantations to generate new multitrajectory implantation plans. A comparison was then undertaken for trajectory safety and efficacy. RESULTS CAP was applied to 166 electrode targets in 18 patients. There were significant improvements in both the safety profile and efficacy profile of trajectories generated by CAP compared with manual planning (p < 0.05). Three independent neurosurgeons assessed the feasibility of the trajectories generated by CAP, with 131 (78.9%) of 166 trajectories deemed suitable for implementation in clinical practice. CAP was performed in real time, with a median duration of 8 minutes for each patient, although this does not include the time taken for data preparation. CONCLUSIONS CAP is a promising tool to plan SEEG implantations. CAP provides feasible depth electrode arrangements, with quantitatively greater safety and efficacy profiles, and with a substantial reduction in duration of planning within the 3D multimodality framework.

Comparison of computer-assisted planning and manual planning for depth electrode implantations in epilepsy.

The aim of the study was the evaluation of the added value of depth to subdural electrodes in delineating epileptogenicity of focal cortical dysplasias (FCDs) and to test the Epileptogenicity Index (EI) in this setting.

Visual and semiautomated evaluation of epileptogenicity in focal cortical dysplasias - An intracranial EEG study.

Accurately characterising the brain networks involved in seizure activity may have important implications for our understanding of epilepsy. Intracranial EEG-fMRI can be used to capture focal epileptic events in humans with exquisite electrophysiological sensitivity and allows for identification of brain structures involved in this phenomenon over the entire brain. We investigated ictal BOLD networks using the simultaneous intracranial EEG-fMRI (icEEG-fMRI) in a 30 year-old male undergoing invasive presurgical evaluation with bilateral depth electrode implantations in amygdalae and hippocampi for refractory temporal lobe epilepsy. One spontaneous focal electrographic seizure was recorded. The aims of the data analysis were firstly to map BOLD changes related to the ictal activity identified on icEEG and secondly to compare different fMRI modelling approaches. Visual inspection of the icEEG showed an onset dominated by beta activity involving the right amygdala and hippocampus lasting 6.4 s (ictal onset phase), followed by gamma activity bilaterally lasting 14.8 s (late ictal phase). The fMRI data was analysed using SPM8 using two modelling approaches: firstly, purely based on the visually identified phases of the seizure and secondly, based on EEG spectral dynamics quantification. For the visual approach the two ictal phases were modelled as 'ON' blocks convolved with the haemodynamic response function; in addition the BOLD changes during the 30 s preceding the onset were modelled using a flexible basis set. For the quantitative fMRI modelling approach two models were evaluated: one consisting of the variations in beta and gamma bands power, thereby adding a quantitative element to the visually-derived models, and another based on principal components analysis of the entire spectrogram in attempt to reduce the bias associated with the visual appreciation of the icEEG. BOLD changes related to the visually defined ictal onset phase were revealed in the medial and lateral right temporal lobe. For the late ictal phase, the BOLD changes were remote from the SOZ and in deep brain areas (precuneus, posterior cingulate and others). The two quantitative models revealed BOLD changes involving the right hippocampus, amygdala and fusiform gyrus and in remote deep brain structures and the default mode network-related areas. In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum.

Article	Year
SEEG trajectory planning: combining stability, structure and scale in vessel extraction. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention\| PubMed ID: 25485435	2014
Utility of 3D multimodality imaging in the implantation of intracranial electrodes in epilepsy. Epilepsia\| PubMed ID: 25656379	2015
Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning. International journal of computer assisted radiology and surgery\| PubMed ID: 25847663	2015
Seizure localization using ictal phase-locked high gamma: A retrospective surgical outcome study. Neurology\| PubMed ID: 25972493	2015
Acetylation of asymmetric and symmetric dimethylarginine: an undercharacterized pathway of metabolism of endogenous methylarginines. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association\| PubMed ID: 26610597	2016
Comparison of computer-assisted planning and manual planning for depth electrode implantations in epilepsy. Journal of neurosurgery\| PubMed ID: 26636383	2015
Visual and semiautomated evaluation of epileptogenicity in focal cortical dysplasias - An intracranial EEG study. Epilepsy & behavior : E&B\| PubMed ID: 27060390	2016
Mapping human preictal and ictal haemodynamic networks using simultaneous intracranial EEG-fMRI. NeuroImage. Clinical\| PubMed ID: 27114897	2016

Roman Rodionov

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