Anterior temporal lobectomy

Schaller, Karl; Cabrilo, Ivan

doi:10.1007/s00701-015-2640-0

Cited by 28 publications

(24 citation statements)

References 9 publications

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“…This wound was copiously irrigated and closed. The anterior temporal lobectomy was then performed as described [39]. Briefly, a temporal craniotomy is performed flush with the middle fossa.…”

Section: B Removal Of the Neuropace Device And Anterior Temporal Lobmentioning

confidence: 99%

Long-Term Surface Electrode Impedance Recordings Associated with Gliosis for a Closed-Loop Neurostimulation Device

Sillay

Ondoma

Wingeier³

et al. 2018

Ann Neurosci

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Background: Closed-loop neurostimulation is a novel alternative therapy for medically intractable focal epilepsy for patients who are not candidates for surgical resection of a seizure focus. Electrodes for this system can be implanted either within the brain parenchyma or in the subdural space. The electrodes then serve the dual role of detecting seizures and delivering an electrical signal aimed at aborting seizure activity. The Responsive Neurostimulation (RNS®) system (Neuropace, Mountain View, CA, USA) is an FDA-approved implantable device designed for this purpose. Objective: One of the challenges of the brain machine interface devices is the potential for implanted neurostimulator devices to induce progressive gliosis, apart from that associated with the minimal trauma at implantation. Gliosis has the potential to alter impedances over time, thereby affecting the clinical efficacy of these devices, and also poses a challenge to the prospects of in vivo repositioning of depth electrodes. We present a clinical case with 3-year follow-up and pathology. Methods: Single-case, retrospective review within a randomized trial with specific minimum follow-up and impedance measurements. Results: Impedance changes in the surface electrode over time were observed. Surgical pathological findings revealed significant gliosis in the leptomeninges of the cortices. Conclusion: We report, for the first time, long-term impedance recordings from a surface electrode associated with pathologic findings of gliosis at the Neuropace device-tissue interface in a patient who was enrolled in the multicenter RNS System Pivotal Clinical Investigation. Further study is required to elucidate the temporal relationship of pathological findings over time. Impedance changes were more complex than can be explained by a progressive or transient pathological mechanism. Further effort is required to elucidate the relationship between impedance change and seizure event capture.

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Section: B Removal Of the Neuropace Device And Anterior Temporal Lobmentioning

confidence: 99%

Long-Term Surface Electrode Impedance Recordings Associated with Gliosis for a Closed-Loop Neurostimulation Device

Sillay

Ondoma

Wingeier³

et al. 2018

Ann Neurosci

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“…These patients were diagnosed as focal unilateral TLE by a comprehensive preoperative assessment, including seizure history and semiology, neurological examination, 3-Tesla magnetic resonance imaging (MRI), scalp electroencephalography, invasive electroencephalography. All patients were from Xuanwu hospital in Beijing and underwent anterior temporal lobectomy including hippocampus (Schaller and Cabrilo, 2016 ). The results of at least 1 year follow-up indicated that these patients achieved seizure free status (Engel class IA).…”

Section: Resultsmentioning

confidence: 99%

Partial Least Square Aided Beamforming Algorithm in Magnetoencephalography Source Imaging

Yin

Zhang

et al. 2018

Front. Neurosci.

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Beamforming techniques have played a prominent role in source imaging in neuroimaging and in locating epileptogenic zones. However, existing vector-beamformers are sensitive to noise on localization of epileptogenic zones. In this study, partial least square (PLS) was used to aid the minimum variance beamforming approach for source imaging with magnetoencephalography (MEG) arrays, and verified its effectiveness in simulated data and epilepsy data. First, PLS was employed to extract the components of the MEG arrays by maximizing the covariance between a linear combination of the predictors and the class variable. Noise was then removed by reconstructing the MEG arrays based on those components. The minimum variance beamforming method was used to estimate a source model. Simulations with a realistic head model and varying noise levels indicated that the proposed approach can provide higher spatial accuracy than other well-known beamforming methods. For real MEG recordings in 10 patients with temporal lobe epilepsy, the ratios of the number of spikes localized in the surgical excised region to the total number of spikes using the proposed method were higher than that of the dipole fitting method. These localization results using the proposed method are more consistent with the clinical evaluation. The proposed method may provide a new imaging marker for localization of epileptogenic zones.

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“…According to all of these examination results, the preoperative assessment conclusion was given by Beijing epilepsy center expert group members. Then, all of those patients also underwent anterior temporal lobectomy [ 37 ] for focal epilepsy at Xuan Wu Hospital Capital Medical University (XWHCMU) between January 2013 and January 2016, which included at least one year of postoperative follow-up. The follow-up results showed that all of those patients were free of disabling seizures (Engel class IA) after surgery.…”

Section: Resultsmentioning

confidence: 99%

Deep Source Localization with Magnetoencephalography Based on Sensor Array Decomposition and Beamforming

Lin

Yang

et al. 2017

Sensors

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In recent years, the source localization technique of magnetoencephalography (MEG) has played a prominent role in cognitive neuroscience and in the diagnosis and treatment of neurological and psychological disorders. However, locating deep brain activities such as in the mesial temporal structures, especially in preoperative evaluation of epilepsy patients, may be more challenging. In this work we have proposed a modified beamforming approach for finding deep sources. First, an iterative spatiotemporal signal decomposition was employed for reconstructing the sensor arrays, which could characterize the intrinsic discriminant features for interpreting sensor signals. Next, a sensor covariance matrix was estimated under the new reconstructed space. Then, a well-known vector beamforming approach, which was a linearly constraint minimum variance (LCMV) approach, was applied to compute the solution for the inverse problem. It can be shown that the proposed source localization approach can give better localization accuracy than two other commonly-used beamforming methods (LCMV, MUSIC) in simulated MEG measurements generated with deep sources. Further, we applied the proposed approach to real MEG data recorded from ten patients with medically-refractory mesial temporal lobe epilepsy (mTLE) for finding epileptogenic zone(s), and there was a good agreement between those findings by the proposed approach and the clinical comprehensive results.

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Anterior temporal lobectomy

Abstract: Knowledge of the temporomesial anatomy, including neurovascular structures around the brainstem, is essential to keep this procedure safe and effective.

Cited by 28 publications

References 9 publications

Long-Term Surface Electrode Impedance Recordings Associated with Gliosis for a Closed-Loop Neurostimulation Device

Long-Term Surface Electrode Impedance Recordings Associated with Gliosis for a Closed-Loop Neurostimulation Device

Partial Least Square Aided Beamforming Algorithm in Magnetoencephalography Source Imaging

Deep Source Localization with Magnetoencephalography Based on Sensor Array Decomposition and Beamforming

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