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. 2020 Jul;49(1):E3.
doi: 10.3171/2020.4.FOCUS20186.

A systematic review of endovascular stent-electrode arrays, a minimally invasive approach to brain-machine interfaces

Sauson Soldozy  1 , Steven Young  1 , Jeyan S Kumar  1 , Stepan Capek  1 , Daniel R Felbaum  2 , Walter C Jean  3 , Min S Park  1 , Hasan R Syed  1
Affiliations

A systematic review of endovascular stent-electrode arrays, a minimally invasive approach to brain-machine interfaces

Sauson Soldozy et al. Neurosurg Focus. 2020 Jul.

Abstract

Objective: The goal of this study was to systematically review the feasibility and safety of minimally invasive neurovascular approaches to brain-machine interfaces (BMIs).

Methods: A systematic literature review was performed using the PubMed database for studies published between 1986 and 2019. All studies assessing endovascular neural interfaces were included. Additional studies were selected based on review of references of selected articles and review articles.

Results: Of the 53 total articles identified in the original literature search, 12 studies were ultimately selected. An additional 10 articles were included from other sources, resulting in a total of 22 studies included in this systematic review. This includes primarily preclinical studies comparing endovascular electrode recordings with subdural and epidural electrodes, as well as studies evaluating stent-electrode gauge and material type. In addition, several clinical studies are also included.

Conclusions: Endovascular stent-electrode arrays provide a minimally invasive approach to BMIs. Stent-electrode placement has been shown to be both efficacious and safe, although further data are necessary to draw comparisons between subdural and epidural electrode measurements given the heterogeneity of the studies included. Greater access to deep-seated brain regions is now more feasible with stent-electrode arrays; however, further validation is needed in large clinical trials to optimize this neural interface. This includes the determination of ideal electrode material type, venous versus arterial approaches, the feasibility of deep brain stimulation, and more streamlined computational decoding techniques.

Keywords: BMI = brain-machine interface; DBS = deep brain stimulation; SNR = signal-to-noise ratio; SSS = superior sagittal sinus; SVM = support vector machine; brain-machine interface; endovascular stent-electrode; minimally invasive; neural interface.

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