June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Adaptive optics and psychophysical measures for anatomical and functional cone patterns association in normal subjects
Author Affiliations & Notes
  • Ieva Sliesoraityte
    Institut de la Vision, Paris, France
  • Saddek Mohand-Said
    Institut de la Vision, Paris, France
  • Victoria Ganem
    Institut de la Vision, Paris, France
  • Jose Sahel
    Institut de la Vision, Paris, France
  • Footnotes
    Commercial Relationships Ieva Sliesoraityte, None; Saddek Mohand-Said, None; Victoria Ganem, None; Jose Sahel, UPMC/Essilor (P), Second Sight (F)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 1513. doi:
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      Ieva Sliesoraityte, Saddek Mohand-Said, Victoria Ganem, Jose Sahel; Adaptive optics and psychophysical measures for anatomical and functional cone patterns association in normal subjects. Invest. Ophthalmol. Vis. Sci. 2013;54(15):1513.

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

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Abstract

Purpose: to investigate anatomical and functional cone patterns association in normal subjects using adaptive optics (AO) and psychophysical measures.

Methods: 30 healthy normal subjects’ eyes (age mean 34.9 ± 10.7 years) underwent en-face AO imaging (Imagine Eyes, Orsay, France) at superior, inferior, nasal and temporal retinal quadrants within 4 degrees eccentricities from fovea. The AO cone photoreceptors quantity was registered and then correlated with photoreceptors’ thickness within the quadrant in the same retinal site assessed using spectral-domain optical coherence tomography scans (Spectralis, Heidelberg, Germany). Functional cone patterns were evaluated in co-mapped retinal quadrants using psychophysical measures, i.e. sensitivity in microperimetry (Nidek MP-1, Padova, Italy), contraction/dilatation amplitude in pupillography (F2D, AMTech, Dosenheim, Germany) and then correlated with anatomical cones features. In addition, the dataset consisted of 750 inputs used for an artificial neural network to estimate anatomical and functional cone patterns. The probability of the correct automatically assessed anatomical and functional cone patterns was evaluated.

Results: anatomical and functional cone patterns in co-mapped retinal sites were significantly positively associated as r=0.79 (p=0.012), r=0.85 (p=0.022), r=0.81 (p=0.045) and r=0.89 (p=0.015) in superior, inferior, nasal and temporal retinal quadrants in normal subjects, respectively. The probability of the correct automatically assessed anatomical and functional cone patterns using artificial neural network was 0.86 (95% Confidence interval (CI) 0.82, 0.90), 0.95 (95% CI 0.93, 0.96), 0.88 (95% CI 0.85, 0.90) and 0.96 (95% CI 0.95, 0.98) within superior, inferior, nasal and temporal retinal quadrants, respectively (p<0.01).

Conclusions: The sensitivity of cones significantly decreases with a reduction of cone density and thickness within co-mapped retinal sites in normal subjects. The artificial neural network allows reliable estimation of the spatial distribution of cones anatomical and functional loss in an individual subject. This provides with important clues that anatomical and functional cone patterns based on adaptive optics and psychophysical measures could be used as an endpoint for therapeutic effect evaluation in retinal degenerations.

Keywords: 550 imaging/image analysis: clinical • 648 photoreceptors • 688 retina  
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