April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Cataracts Classification Combining Objective and Subjective Testing by using an Adaptive-Optics Instrument
Author Affiliations & Notes
  • Guillermo M Perez
    R&D, VOPTICA SL, Murcia, Spain
  • Bart Jaeken
    R&D, VOPTICA SL, Murcia, Spain
  • Lucia Hervella
    R&D, VOPTICA SL, Murcia, Spain
  • José María Marín
    Servicio de Oftalmología, Hospital Universitario Arrixaca, Murcia, Spain
  • Pablo Artal
    Laboratorio de Optica, Universidad de Murcia, Murcia, Spain
  • Footnotes
    Commercial Relationships Guillermo Perez, VOPTICA (E), VOPTICA (I); Bart Jaeken, VOPTICA (E); Lucia Hervella, VOPTICA (E); José María Marín, None; Pablo Artal, VOPTICA (I), VOPTICA (P), VOPTICA (S)
  • Footnotes
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Investigative Ophthalmology & Visual Science April 2014, Vol.55, 2119. doi:
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      Guillermo M Perez, Bart Jaeken, Lucia Hervella, José María Marín, Pablo Artal; Cataracts Classification Combining Objective and Subjective Testing by using an Adaptive-Optics Instrument. Invest. Ophthalmol. Vis. Sci. 2014;55(13):2119.

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

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Abstract
 
Purpose
 

Different approaches have been proposed to detect and classify cataracts; from optical measurements [Artal et al. PLoS One, 2011] to subjective approaches based on the evaluation of visual performance. However, there is not yet a fully accepted standard for cataract classification. We have used an adaptive-optics instrument that combines both optical and subjective measurements, to improve this process.

 
Methods
 

A group of 52 patients with different types and degree of cataracts were tested using an adaptive-optics based instrument (AOnEye; VOPTICA SL, Murcia, Spain). It includes a Hartmann-Shack (HS) wavefront sensor, a spatial light modulator to control eye’s optics and a micro-display to present visual stimuli to the patient. From every spot of the HS images, the average intensity and the ratio of intensity in the peak and the surrounding area provides a spatially resolved map over the pupil of light transmission and diffusion. In addition global transmission and diffusion parameters were obtained for each eye by averaging the local values over a defined pupil area. On the other hand, the best corrected visual acuity (BCVA) at high (50%) and low (15%) contrast was measured in each subject in the same instrument.

 
Results
 

The spatially resolved analysis of the HS images shows different degrees and types of cataracts, based on the differences in the distribution of light transmission and diffusion. Figure shows color-coded examples of spatially resolved light transmittance and diffusion in a reference eye and three eyes with different types of cataracts. A merit function was computed for each eye by weighting the contribution of the global values of light transmission and diffusion. A cataract indicator parameter was obtained by combining the optical and visual parameters. By using this, 32 eyes were identified as cataractous in the sample of 52. The average high contrast BCVA in cataract eyes was 0.7±0.2 (1.2±0.2 in normal eyes) and the low contrast BCVA in cataract eyes was 0.3±0.1 (0.6±0.1 in normal eyes).

 
Conclusions
 

The combination, in one single instrument, of optical and visual evaluation allows a complete understanding of the degree of cataracts and their visual implications in every patient. This approach could be also used in other patients to separate accurately the origin of visual symptoms for proper management.

  
Keywords: 445 cataract • 630 optical properties • 626 aberrations  
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