July 2019
Volume 60, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2019
Quantifying nystagmus in patients with Achromatopsia using image-based tracking with AOSLO
Author Affiliations & Notes
  • Thomas Kane
    Institute of Ophthalmology, UCL, London, United Kingdom
    Moorfields Eye Hospital, United Kingdom
  • Navjit Singh
    Institute of Ophthalmology, UCL, London, United Kingdom
    Moorfields Eye Hospital, United Kingdom
  • Michalis Georgiou
    Institute of Ophthalmology, UCL, London, United Kingdom
    Moorfields Eye Hospital, United Kingdom
  • Alfredo Dubra
    Department of Ophthalmology, Stanford University, Palo Alto, California, United States
  • Michel Michaelides
    Institute of Ophthalmology, UCL, London, United Kingdom
    Moorfields Eye Hospital, United Kingdom
  • Angelos Kalitzeos
    Institute of Ophthalmology, UCL, London, United Kingdom
    Moorfields Eye Hospital, United Kingdom
  • Footnotes
    Commercial Relationships   Thomas Kane, None; Navjit Singh, None; Michalis Georgiou, None; Alfredo Dubra, Boston Micromachines (C), MeiraGTx (C), US Patent 8,226,236 (P); Michel Michaelides, MeiraGTx (C); Angelos Kalitzeos, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 4605. doi:
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      Thomas Kane, Navjit Singh, Michalis Georgiou, Alfredo Dubra, Michel Michaelides, Angelos Kalitzeos; Quantifying nystagmus in patients with Achromatopsia using image-based tracking with AOSLO. Invest. Ophthalmol. Vis. Sci. 2019;60(9):4605.

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

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Abstract

Purpose : Adaptive Optics Scanning Light Ophthalmoscopy (AOSLO) allows non-invasive recording of image sequences of photoreceptors. We seek to explore the potential of eye-tracking subjects with Achromatopsia (ACHM) using these sequences, and observe the dominant fixational movements: drift, microsaccades, and pendular nystagmus.

Methods : Twenty-five 1.5° field of view AOSLO image sequences of 150 frames each (recorded at 16.6 fps) from ten eyes of ten subjects with CNGB3-associated ACHM were selected post-acquisition based on image sharpness and contrast, and a varying degree of clinically diagnosed nystagmus: absent (n=3), mild (n=4), moderate (n=1), severe (n=2). Two eyes from two unaffected individuals naïve to AOSLO imaging were included for comparison.
All study participants were asked to follow a stationary fixation target used to steer fixation around the fovea. All frames in each image sequence were registered with respect to a reference frame chosen by ARFS [1], with some frames being rejected by ARFS due to blur and distortion during a saccade. Image-based eye movement estimation data extracted from the registration software where then used to derive metrics, including mean displacement and its standard deviation.

Results : An average of 97 frames per video were selected (the rest rejected by ARFS during a saccade). The difference between the traces of eyes with nystagmus was evident when these were visualized next to those from the control subjects (see Figure 1). The table in Figure 2 summarising the results, shows that the metrics correlate with the clinical severity of the nystagmus.

Conclusions : Harnessing eye movement information from readily available, previously acquired AOSLO image sequences provides objective quantification of different levels of nystagmus in an ACHM cohort, and may be valuable in the assessment of change over time and potential response to intervention.

[1] PMID: 28392976

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

 

Comparing the tracing of fixation (magenta), and displacement from the origin over time (blue), of an eye with no nystagmus, with an ACHM affected eye with severe nystagmus. Three example videos from the twenty-five analysed are shown.

Comparing the tracing of fixation (magenta), and displacement from the origin over time (blue), of an eye with no nystagmus, with an ACHM affected eye with severe nystagmus. Three example videos from the twenty-five analysed are shown.

 

Mean movement of fixation over 25 videos.

Mean movement of fixation over 25 videos.

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