June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
Optimal Photovoltaic Pixels for High-Resolution Subretinal Prosthesis
Author Affiliations & Notes
  • Zhijie Charles Chen
    Electrical Engineering, Stanford University, Stanford, California, United States
  • Bing-Yi Wang
    Physics, Stanford University, Stanford, California, United States
  • Anna Kochnev Goldstein
    Electrical Engineering, Stanford University, Stanford, California, United States
  • Daniel V Palanker
    Ophthalmology, Stanford University School of Medicine, Stanford, California, United States
    Hansen Experimental Physics Laboratory, Stanford University, Stanford, California, United States
  • Footnotes
    Commercial Relationships   Zhijie Charles Chen Pixium Vision, Code P (Patent); Bing-Yi Wang Pixium Vision, Code P (Patent); Anna Kochnev Goldstein None; Daniel Palanker Pixium Vision, Code C (Consultant/Contractor), Pixium Vision, Code P (Patent)
  • Footnotes
    Support  NIH (Grants R01-EY-027786, and P30-EY-026877), DoD (Grant W81XWH-2210933), AFOSR (Grant FA9550-19-1-0402), Wu Tsai Institute of Neurosciences at Stanford, and unrestricted grant from the Research to Prevent Blindness
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 4611. doi:
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    • Get Citation

      Zhijie Charles Chen, Bing-Yi Wang, Anna Kochnev Goldstein, Daniel V Palanker; Optimal Photovoltaic Pixels for High-Resolution Subretinal Prosthesis. Invest. Ophthalmol. Vis. Sci. 2023;64(8):4611.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Photovoltaic subretinal implants PRIMA in patients with atrophic AMD provided prosthetic visual acuity up to 20/438, closely matching the maximum resolution expected with the 100μm pixels. Acuity above 20/200 requires pixels smaller than 50μm, and sufficiently deep penetration of electric field into the retina can be achieved with local return electrodes removed. However, such monopolar pixels are prone to crosstalk between neighboring electrodes, and hence low contrast. Optically controlled current steering improves the contrast but it requires a complicated pre-charging sequence. Alternatively, optimal shunt resistors within each pixel can help confine the electric field, while providing sufficient contrast and the stimulation strength.

Methods : Electric fields in the retina generated by 40μm-wide monopolar pixels, having various shunt resistors in parallel with the photodiodes, were computed using the RPSim package for 3 image projections - single pixel, Landolt C with a 48μm-wide gap, and full field. For the brightest perception, light pulses were applied at 3mW/mm2 irradiance, with 9.8ms duration and 30Hz rep. rate. To determine the optimal shunt resistance, we modeled (1) contrast of the Landolt C and (2) stimulation strength for bipolar cells, with flat pixels in the best-case and worst-case patients, and with 30μm-tall pillar electrodes that penetrate the subretinal debris layer. The values were benchmarked to the PRIMA clinical results.

Results : As the shunt resistance increased from 280kΩ (the access resistance of a pixel) to 5.6MΩ, the contrast monotonically decreased by approximately a third. For all three images, the stimulation strength first increased and then decreased, with a peak at 850kΩ significantly stronger than both ends. With such resistance, stimulation strength of the Landolt C was 7.9 times the PRIMA clinical threshold, with contrast of 75% in the best case with pillar electrodes, and 2.2 times with 38% contrast - in the worst case with flat pixels.

Conclusions : Proper shunt resistor in monopolar photovoltaic pixels enhanced the contrast by returning the current via dark neighboring pixels, while greatly improving the stimulation strength compared to bipolar pixels. For 40μm pixels, the optimal shunt resistance was found to be about 3 times the access resistance of the active electrode, independent of the projected image. Similar optimization can be performed for other pixel sizes with RPSim.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

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