Portable Multi-focal Visual Evoked Potential Diagnostics for Multiple Sclerosis/Optic Neuritis patients.

Autor:	Banijamali SMA; Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA., Versek C; NeuroFieldz Inc, Newton, MA, USA., Babinski K; Department of Neurology, Tufts University School of Medicine, Tufts Medical Center, Boston, MA, USA., Kamarthi S; Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA., Green-LaRoche D; Department of Neurology, Tufts University School of Medicine, Tufts Medical Center, Boston, MA, USA., Sridhar S; Department of Physics, Department of Bioengineering and Department of Chemical Engineering, Northeastern University, Boston, MA 02115, NeuroFieldz Inc, Newton, MA, USA.
Jazyk:	angličtina
Zdroj:	MedRxiv : the preprint server for health sciences [medRxiv] 2023 Dec 26. Date of Electronic Publication: 2023 Dec 26.
DOI:	10.1101/2023.12.26.23300405
Abstrakt:	Purpose: Multiple Sclerosis (MS) is a neuro-inflammatory disease of the Central Nervous System (CNS) in which the body's immune system attacks and destroys myelin sheath that protects nerve fibers and causes disruption in axonal signal transmission. Demyelinating Optic Neuritis (ON) is often a manifestation of MS and involves inflammation of the optic nerve. ON can cause vision loss, pain and discomfort in the eyes, and difficulties in color perception.In this study, we developed NeuroVEP, a portable, wireless diagnostic system that delivers visual stimuli through a smartphone in a headset and measures evoked potentials at the visual cortex from near the O1, Oz, O2, O9 and O10 locations on the scalp (extended 10-20 system) using custom electroencephalography (EEG) electrodes. Methods: Each test session is constituted by a short 2.5-minute full-field visual evoked potentials (ffVEP) test, followed by a 12.5-minute multifocal VEP (mfVEP) test. The ffVEP test evaluates the integrity of the visual pathway by analyzing the P1 (also known as P100) component of responses from each eye, while the mfVEP test evaluates 36 individual regions of the visual field for abnormalities. Extensive signal processing, feature extraction methods, and machine learning algorithms were explored for analyzing the mfVEP responses. The results of the ffVEP test for patients were evaluated against normative data collected from a group of subjects with normal vision. Custom visual stimuli with simulated defects were used to validate the mfVEP results which yielded 91% accuracy of classification. Results: 20 subjects, 10 controls and 10 with MS and/or ON were tested with the NeuroVEP device and a standard-of-care (SOC) VEP testing device which delivers only ffVEP stimuli. In 91% of the cases, the ffVEP results agreed between NeuroVEP and SOC device. Where available, the NeuroVEP mfVEP results were in good agreement with Humphrey Automated Perimetry visual field analysis. The lesion locations deduced from the mfVEP data were consistent with Magnetic Resonance Imaging (MRI) and Optical Coherence Tomography (OCT) findings. Conclusion: This pilot study indicates that NeuroVEP has the potential to be a reliable, portable, and objective diagnostic device for electrophysiology and visual field analysis for neuro-visual disorders.
Databáze:	MEDLINE
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