Dataset Information

Computer-assisted planning for minimally invasive anterior two-thirds laser corpus callosotomy: A feasibility study with probabilistic tractography validation.

ABSTRACT:

Background

Anterior two-thirds corpus callosotomy is an effective palliative neurosurgical procedure for drug-refractory epilepsy that is most commonly used to treat drop-attacks. Laser interstitial thermal therapy is a novel stereotactic ablative technique that has been utilised as a minimally invasive alternative to resective and disconnective open neurosurgery. Case series have reported success in performing laser anterior two-thirds corpus callosotomy. Computer-assisted planning algorithms may help to automate and optimise multi-trajectory planning for this procedure.

Objective

To undertake a simulation-based feasibility study of computer-assisted corpus callostomy planning in comparison with expert manual plans in the same patients.

Methods

Ten patients were selected from a prospectively maintained database. Patients had previously undergone diffusion-weighted imaging and digital subtraction angiography as part of routine SEEG care. Computer-assisted planning was performed using the EpiNav™ platform and compared to manually planned trajectories from two independent blinded experts. Estimated ablation cavities were used in conjunction with probabilistic tractography to simulate the expected extent of interhemispheric disconnection.

Results

Computer-assisted planning resulted in significantly improved trajectory safety metrics (risk score and minimum distance to vasculature) compared to blinded external expert manual plans. Probabilistic tractography revealed residual interhemispheric connectivity in 1/10 cases following computer-assisted planning compared to 4/10 and 2/10 cases with manual planning.

Conclusion

Computer-assisted planning successfully generates multi-trajectory plans capable of LITT anterior two-thirds corpus callosotomy. Computer-assisted planning may provide a means of standardising trajectory planning and serves as a potential new tool for optimising trajectories. A prospective validation study is now required to determine if this translates into improved patient outcomes.

SUBMITTER: Vakharia VN

PROVIDER: S-EPMC6994706 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Computer-assisted planning for minimally invasive anterior two-thirds laser corpus callosotomy: A feasibility study with probabilistic tractography validation.

Vakharia Vejay N VN Sparks Rachel E RE Vos Sjoerd B SB Bezchlibnyk Yarema Y Mehta Ashesh D AD Willie Jon T JT Wu Chengyuan C Sharan Ashwini A Ourselin Sebastien S Duncan John S JS

NeuroImage. Clinical 20200113

<h4>Background</h4>Anterior two-thirds corpus callosotomy is an effective palliative neurosurgical procedure for drug-refractory epilepsy that is most commonly used to treat drop-attacks. Laser interstitial thermal therapy is a novel stereotactic ablative technique that has been utilised as a minimally invasive alternative to resective and disconnective open neurosurgery. Case series have reported success in performing laser anterior two-thirds corpus callosotomy. Computer-assisted planning algo ...[more]

PMID: 31982679

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Project description:ObjectivesThis study aimed to investigate the functional network effects of corpus callosotomy (CC), a well-recognized palliative surgical therapy for patients with Lennox-Gastaut syndrome (LGS). Specifically, we sought to gain insight into the effects of CC on LGS remission, based on brain networks in LGS by calculating network metrics and evaluating by network measures before and after surgery.MethodsElectroencephalographic recordings made during preoperative and 3-month postoperative states in 14 patients with LGS who had undergone successful CC were retrospectively analyzed. First, undirected correlation matrices were constituted for the mathematical expression of functional networks. Then, we plotted these networks to analyze the effects of CC on connectivity. In addition, conventional local and global network measures were applied to evaluate differences in network topology between preoperative and postoperative states.ResultsIn the preoperative state, hubs were mainly distributed around the paramedian regions. After CC, the hubs moved from the paramedian regions to the dual-hemisphere and even the lateral regions. Thus, the general connectivity state became more homogeneous, which was verified by network plots and statistical analysis of local measures. The results of global network measures indicated a decreased clustering coefficient in the delta band, decreased characteristic path length in both the delta and gamma bands, and increased global efficiency in the gamma band.ConclusionOur results showed a consistent variation in the global brain network that converted to a small-world topology with an optimal balance of functional integration and segregation of the network. Such changes were positively correlated with satisfactory surgery results, which could be interpreted as being indicative of LGS recovery process after CC. For patients with refractory LGS along with no focal epileptogenic zone findings, which were not suitable for the resective surgical therapy, our results verified that CC could work as an effective surgical treatment option.

Project description:PURPOSE:This study aimed to use graph theoretical analysis of anatomical covariance derived from structural MRI to reveal how the gray matter connectivity pattern is altered after corpus callosotomy (CC). MATERIALS AND METHODS:We recruited 21 patients with epilepsy who had undergone CC. Enrollment criteria were applied: (1) no lesion identified on brain MRI; (2) no history of other brain surgery; and (3) age not younger than 3 years and not older than 18 years at preoperative MRI evaluation. The most common epilepsy syndrome was Lennox-Gastaut syndrome (11 patients). For voxel-based morphometry, the normalized gray matter images of pre-CC and post-CC patients were analyzed with SPM12 (voxel-level threshold of p<0.05 [familywise error-corrected]). Secondly, the images of both groups were subjected to graph theoretical analysis using the Graph Analysis Toolbox with SPM8. Each group was also compared with 32 age- and sex-matched control patients without brain diseases. RESULTS:Comparisons between the pre- and post-CC groups revealed a significant reduction in seizure frequency with no change in mean intelligence quotient/developmental quotient levels. There was no relationship among the three groups in global network metrics or in targeted attack. A regional comparison of betweenness centrality revealed decreased connectivity to and from the right middle cingulate gyri and medial side of the right superior frontal gyrus and a partial shift in the distribution of betweenness centrality hubs to the normal location. Significantly lower resilience to random failure was found after versus before CC and versus controls (p = 0.0450 and p = 0.0200, respectively). CONCLUSION:Graph theoretical analysis of anatomical covariance derived from structural imaging revealed two neural network effects of resection associated with seizure reduction: the reappearance of a structural network comparable to that in healthy children and reduced connectivity along the median line, including the middle cingulate gyrus.

Project description:In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human.

Dataset Information

Computer-assisted planning for minimally invasive anterior two-thirds laser corpus callosotomy: A feasibility study with probabilistic tractography validation.

Background

Objective

Methods

Results

Conclusion

Publications

Computer-assisted planning for minimally invasive anterior two-thirds laser corpus callosotomy: A feasibility study with probabilistic tractography validation.

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