Is there still need for microelectrode recording now the subthalamic nucleus can be well visualized with high field and ultrahigh MR imaging?

Kocabıcak, Ersoy; Alptekin, Onur; Ackermans, Linda; Kubben, Pieter; Kuijf, Mark L.; Kurt, Erkan; Esselink, Rianne A.J.; Temel, Yasin

doi:10.3389/fnint.2015.00046

Cited by 18 publications

(14 citation statements)

References 30 publications

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“…Despite advances in magnetic resonance imaging (MRI) technology and a better understanding of the relationship between an MRI and MER, MER evaluation remains the most widely used localization technique [3], [4]. The MER provides a high temporal resolution (< 1 ms) of the brain's neural activity in the close vicinity to the microelectrode [5].…”

Section: Introductionmentioning

confidence: 99%

Identification of Microrecording Artifacts with Wavelet Analysis and Convolutional Neural Network: An Image Recognition Approach

Klempíř

Krupička

Bakštein

et al. 2019

Measurement Science Review

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Deep brain stimulation (DBS) is an internationally accepted form of treatment option for selected patients with Parkinson’s disease and dystonia. Intraoperative extracellular microelectrode recordings (MER) are considered as the standard electrophysiological method for the precise positioning of the DBS electrode into the target brain structure. Pre-processing of MERs is a key phase in clinical analysis, with intraoperative microelectrode recordings being prone to several artifact groups (up to 25 %). The aim of this methodological article is to provide a convolutional neural network (CNN) processing pipeline for the detection of artifacts in an MER. We applied continuous wavelet transform (CWT) to generate an over-complete time–frequency representation. We demonstrated that when attempting to find artifacts in an MER, the new CNN + CWT provides a high level of accuracy (ACC = 88.1 %), identifies individual classes of artifacts (ACC = 75.3 %) and also offers artifact time onset detail, which can lead to a reduction in false positives/negatives. In summary, the presented methodology is capable of identifying and removing various artifacts in a comprehensive database of MER and represents a substantial improvement over the existing methodology. We believe that this approach will assist in the proposal of interesting clinical hypotheses and will have neurologically relevant effects.

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Section: Introductionmentioning

confidence: 99%

Identification of Microrecording Artifacts with Wavelet Analysis and Convolutional Neural Network: An Image Recognition Approach

Klempíř

Krupička

Bakštein

et al. 2019

Measurement Science Review

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“…7 However, even with the best available imaging techniques for displaying brain anatomy in vivo, the peri-STN area is still poorly visualized. 25,30,46,49 Several approaches have been described to optimize STN targeting. DBS centers predominantly use the con-cept of a "2-stage method" for accurate and clinically effective positioning of electrodes.…”

Section: Discussionmentioning

confidence: 99%

Microsurgical anatomy of the subthalamic nucleus: correlating fiber dissection results with 3-T magnetic resonance imaging using neuronavigation

Güngör

Baydin

Holanda

et al. 2019

Journal of Neurosurgery

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OBJECTIVE Despite the extensive use of the subthalamic nucleus (STN) as a deep brain stimulation (DBS) target, unveiling the extensive functional connectivity of the nucleus, relating its structural connectivity to the stimulation-induced adverse effects, and thus optimizing the STN targeting still remain challenging. Mastering the 3D anatomy of the STN region should be the fundamental goal to achieve ideal surgical results, due to the deep-seated and obscure position of the nucleus, variable shape and relatively small size, oblique orientation, and extensive structural connectivity. In the present study, the authors aimed to delineate the 3D anatomy of the STN and unveil the complex relationship between the anatomical structures within the STN region using fiber dissection technique, 3D reconstructions of high-resolution MRI, and fiber tracking using diffusion tractography utilizing a generalized q-sampling imaging (GQI) model. METHODS Fiber dissection was performed in 20 hemispheres and 3 cadaveric heads using the Klingler method. Fiber dissections of the brain were performed from all orientations in a stepwise manner to reveal the 3D anatomy of the STN. In addition, 3 brains were cut into 5-mm coronal, axial, and sagittal slices to show the sectional anatomy. GQI data were also used to elucidate the connections among hubs within the STN region. RESULTS The study correlated the results of STN fiber dissection with those of 3D MRI reconstruction and tractography using neuronavigation. A 3D terrain model of the subthalamic area encircling the STN was built to clarify its anatomical relations with the putamen, globus pallidus internus, globus pallidus externus, internal capsule, caudate nucleus laterally, substantia nigra inferiorly, zona incerta superiorly, and red nucleus medially. The authors also describe the relationship of the medial lemniscus, oculomotor nerve fibers, and the medial forebrain bundle with the STN using tractography with a 3D STN model. CONCLUSIONS This study examines the complex 3D anatomy of the STN and peri-subthalamic area. In comparison with previous clinical data on STN targeting, the results of this study promise further understanding of the structural connections of the STN, the exact location of the fiber compositions within the region, and clinical applications such as stimulation-induced adverse effects during DBS targeting.

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“…In another study, Reck et al calculated the central trajectory implantation rate to be 73% in 22 patients with PD when DBS of the STN was performed (19). In our previous study, we reported a central trajectory implantation rate of ~70% using a combination of direct and indirect targeting methods (14). Toda et al reported that the implant rate of permanent DBS electrodes to the central trajectory was 81% in their series in which a 3T MRI machine was used.…”

Section: A B C Dmentioning

confidence: 93%

Microelectrode recording for deep brain stimulation of the subthalamic nucleus in patients with advanced parkinson’s disease: advantage or loss of time?

Kocabıcak¹,

Alptekin²,

Aygün³

et al. 2019

Turkish Neurosurgery

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AIM: To investigate the effect of using microelectrode recording (MER) on the length of time required to carry out a deep brain stimulation (DBS) procedure of the subthalamic nucleus in patients with Parkinson's disease (PD). MATERIAL and METHODS: The time required to include MER in the DBS operation was calculated for the first and second sides in 24 patients with PD. The number of microelectrodes used on each trajectory for the first and second sides, and the percentage of permanent electrodes implanted on each trajectory for the first and second sides, were quantified. RESULTS: The average times taken to use MER were 23.4 ± 6.2 minutes, 17.4 ± 6.5 minutes, and 41.2 ± 6.3 minutes for the first side, second side and total procedure, respectively. In 75% of patients, the permanent electrode was implanted at the planned target site for the first side, and in 61% of patients for the second side. CONCLUSION: MER extends the time required to carry out the DBS procedure. However, during surgery, it provides real-time information on the electrodes' neurophysiological locations and helps the surgical team choose an alternative target if the planned target does not produce satisfying results.

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Is there still need for microelectrode recording now the subthalamic nucleus can be well visualized with high field and ultrahigh MR imaging?

Cited by 18 publications

References 30 publications

Identification of Microrecording Artifacts with Wavelet Analysis and Convolutional Neural Network: An Image Recognition Approach

Identification of Microrecording Artifacts with Wavelet Analysis and Convolutional Neural Network: An Image Recognition Approach

Microsurgical anatomy of the subthalamic nucleus: correlating fiber dissection results with 3-T magnetic resonance imaging using neuronavigation

Microelectrode recording for deep brain stimulation of the subthalamic nucleus in patients with advanced parkinson’s disease: advantage or loss of time?

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