Craig Versek1, S Mohammad Ali Banijamali2, Peter Bex3, Kameran Lashkari4, Sagar Kamarthi2, Srinivas Sridhar1,5,6. 1. NeuroFieldz Inc, Newton, MA, USA. 2. Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA. 3. Department of Psychology, Northeastern University, Boston, MA, USA. 4. Department of Bioengineering, University of Massachusetts Dartmouth, Dartmouth, MA, USA. 5. Departments of Physics, Bioengineering, and Chemical Engineering, Northeastern University, Boston, MA, USA. 6. Division of Radiation Oncology, Harvard Medical School, Boston, MA, USA.
Abstract
BACKGROUND: Delayed Dark-Adapted vision Recovery (DAR) is a biomarker for Age-related Macular Degeneration (AMD), however its measurement is burdensome for patients and examiners. METHODS: In this study, we developed a portable, wireless and user-friendly system that employs a headset with a smartphone to deliver controlled photo-bleach and monocular pattern reversal stimuli, while using custom electroencephalography (EEG) electrodes and electronics in order to measure Dark-Adapted Visual Evoked Potentials (DAVEP) objectively and separately at the peripheral and central visual field. This is achieved in one comfortable 20-minute session, without requiring subject reporting. DAVEP responses post photo-bleach for up to 15 minutes were measured concurrently from both eyes in 12 AMD-patients, 1 degenerative myopia patient, and 8 controls who had no diagnosed macular vision loss. RESULTS: Robust positive polarity DAVEP responses were observed at 200-500 ms from stimulus onset to scotopic stimuli that have been seldom reported and analyzed previously. The amplitude recovery of the DAVEP response was significantly delayed in AMD patients as compared to controls. We developed DAVEP1 scores, a simple metric for DAR, which classified 90% of subject eyes correctly, indicating the presence of AMD in at least one eye of all pre-confirmed subjects with this diagnosis. CONCLUSION: We developed a user-friendly, portable VEP system and DAVEP1 metric, which show a high potential to identify DAR-deficits in AMD-patients. This novel technology could aid in early diagnosis of AMD.
BACKGROUND: Delayed Dark-Adapted vision Recovery (DAR) is a biomarker for Age-related Macular Degeneration (AMD), however its measurement is burdensome for patients and examiners. METHODS: In this study, we developed a portable, wireless and user-friendly system that employs a headset with a smartphone to deliver controlled photo-bleach and monocular pattern reversal stimuli, while using custom electroencephalography (EEG) electrodes and electronics in order to measure Dark-Adapted Visual Evoked Potentials (DAVEP) objectively and separately at the peripheral and central visual field. This is achieved in one comfortable 20-minute session, without requiring subject reporting. DAVEP responses post photo-bleach for up to 15 minutes were measured concurrently from both eyes in 12 AMD-patients, 1 degenerative myopia patient, and 8 controls who had no diagnosed macular vision loss. RESULTS: Robust positive polarity DAVEP responses were observed at 200-500 ms from stimulus onset to scotopic stimuli that have been seldom reported and analyzed previously. The amplitude recovery of the DAVEP response was significantly delayed in AMD patients as compared to controls. We developed DAVEP1 scores, a simple metric for DAR, which classified 90% of subject eyes correctly, indicating the presence of AMD in at least one eye of all pre-confirmed subjects with this diagnosis. CONCLUSION: We developed a user-friendly, portable VEP system and DAVEP1 metric, which show a high potential to identify DAR-deficits in AMD-patients. This novel technology could aid in early diagnosis of AMD.
Authors: Thomas Ach; Elen Tolstik; Jeffrey D Messinger; Anna V Zarubina; Rainer Heintzmann; Christine A Curcio Journal: Invest Ophthalmol Vis Sci Date: 2015-05 Impact factor: 4.799
Authors: Karl Csaky; Frederick Ferris; Emily Y Chew; Prashant Nair; Janet K Cheetham; Jacque L Duncan Journal: Invest Ophthalmol Vis Sci Date: 2017-07-01 Impact factor: 4.799