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Measurement of cone dark adaptation: a comparison of four psychophysical methods

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Abstract

Purpose

Dark adaptometry is an important clinical tool for the diagnosis of a range of conditions, including age-related macular degeneration. In order to identify the most robust, clinically applicable technique for the measurement of cone dark adaptation, the repeatability and agreement of four psychophysical methods were assessed.

Methods

Data were obtained from 31 healthy adults on two occasions, using four psychophysical methods. Participants’ pupils were dilated, and 96 % of cone photopigment was bleached before threshold was monitored in the dark using one of the techniques, selected at random. This procedure was repeated for each of the remaining methods. An exponential recovery function was fitted to all threshold recovery data. The coefficient of repeatability (CoR) was calculated to assess the repeatability of the methods, and a repeated-measures analysis of variance was used to compare mean recovery parameters.

Results

All four methods demonstrated a similar level of intersession repeatability for measurement of cone recovery, yielding CoRs between 1.18 and 1.56 min. There were no statistically significant differences in estimates of mean time constant of cone recovery (cone τ) between the four methods (p = 0.488); however, significant differences between initial and final cone thresholds were reported (p < 0.005).

Conclusions

All of the techniques were capable of monitoring the rapid changes in visual threshold that occur during cone dark adaptation, and the repeatability of the techniques was similar. This indicates that despite the respective advantages and disadvantages of these psychophysical techniques, all four methods would be suitable for measuring cone dark adaptation in clinical practice.

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References

  1. Moore AT, Fitzke FW, Kemp CM, Arden GB, Keen TJ, Inglehearn CF, Bhattacharya SS, Bird AC (1992) Abnormal dark adaptation kinetics in autosomal dominant sector retinitis pigmentosa due to rod opsin mutation. Br J Ophthalmol 76:465–469

    Article  CAS  PubMed  Google Scholar 

  2. Sandberg MA, Pawlyk BS, Berson EL (1999) Acuity recovery and cone pigment regeneration after a bleach in patients with retinitis pigmentosa and rhodopsin mutations. Invest Ophthalmol Vis Sci 40:2457–2461

    CAS  PubMed  Google Scholar 

  3. Petzold A, Plant GT (2006) Clinical disorders affecting mesopic vision. Ophthalmic Physiol Opt 26:326–341

    Article  PubMed  Google Scholar 

  4. Steinmetz RL, Polkinghorne PC, Fitzke FW, Kemp CM, Bird AC (1992) Abnormal dark adaptation and rhodopsin kinetics in Sorsbys fundus dystrophy. Invest Ophthalmol Vis Sci 33:1633–1636

    CAS  PubMed  Google Scholar 

  5. Cideciyan AV, Pugh EN, Lamb TD, Huang YJ, Jacobson SG (1997) Plateaux during dark adaptation in Sorsby’s fundus dystrophy and vitamin A deficiency. Invest Ophthalmol Vis Sci 38:1786–1794

    CAS  PubMed  Google Scholar 

  6. Kemp CM, Jacobson SG, Faulkner DJ, Walt RW (1988) Visual function and rhodopsin levels in humans with vitamin A deficiency. Exp Eye Res 46:185–197

    Article  CAS  PubMed  Google Scholar 

  7. Phipps JA, Yee P, Fletcher EL, Vingrys AJ (2006) Rod photoreceptor dysfunction in diabetes: activation, deactivation, and dark adaptation. Invest Ophthalmol Vis Sci 47:3187–3194

    Article  PubMed  Google Scholar 

  8. Newsome DA, Negreiro M (2009) Reproducible measurement of macular light flash recovery time using a novel device can indicate the presence and worsening of macular diseases. Curr Eye Res 34:162–170

    Article  PubMed  Google Scholar 

  9. Owsley C, Jackson GR, White M, Feist R, Edwards D (2001) Delays in rod-mediated dark adaptation in early age-related maculopathy. Ophthalmology 108:1196–1202

    Article  CAS  PubMed  Google Scholar 

  10. Phipps JA, Guymer RH, Vingrys AJ (2003) Loss of cone function in age-related maculopathy. Invest Ophthalmol Vis Sci 44:2277–2283

    Article  PubMed  Google Scholar 

  11. Binns AM, Margrain TH (2007) Evaluating retinal function in age-related maculopathy with the ERG photostress test. Invest Ophthalmol Vis Sci 48:2806–2813

    Article  PubMed  Google Scholar 

  12. Owsley C, McGwin G Jr, Jackson GR, Kallies K, Clark M (2007) Cone- and rod-mediated dark adaptation impairment in age-related maculopathy. Ophthalmology 114:1728–1735

    Article  PubMed  Google Scholar 

  13. Dimitrov PN, Guymer RH, Zele AJ, Anderson AJ, Vingrys AJ (2008) Measuring rod and cone dynamics in age-related maculopathy. Invest Ophthalmol Vis Sci 49:55–65

    Article  PubMed  Google Scholar 

  14. Gaffney AJ, Binns AM, Margrain TH (2011) The topography of cone dark adaptation deficits in age-related maculopathy. Optom Vis Sci 88:1080–1087

    Article  PubMed  Google Scholar 

  15. Dimitrov PN, Robman LD, Varsamidis M, Aung KZ, Makeyeva GA, Guymer RH, Vingrys AJ (2011) Visual function tests as potential biomarkers in age-related macular degeneration. Invest Ophthalmol Vis Sci 52:9457–9469

    Article  PubMed  Google Scholar 

  16. Brown B, Kitchin JL (1983) Dark adaptation and the acuity/luminance response in senile macular degeneration (SMD). Am J Opt Physiol Opt 60:645–650

    Article  CAS  Google Scholar 

  17. Eisner A, Fleming SA, Klein ML, Mauldin WM (1987) Sensitivities in older eyes with good acuity: eyes whose fellow eye has exudative AMD. Invest Ophthalmol Vis Sci 28:1832–1837

    CAS  PubMed  Google Scholar 

  18. Eisner A, Stoumbos VD, Klein ML, Fleming SA (1991) Relations between fundus appearance and function—eyes whose fellow eye has exudative age-related macular degeneration. Invest Ophthalmol Vis Sci 32:8–20

    CAS  PubMed  Google Scholar 

  19. Owen CG, Jarrar Z, Wormald R, Cook DG, Fletcher AE, Rudnick AR (2012) The estimated prevalence and incidence of late stage age related macular degeneration in the UK. Br J Ophthalmol 96:752–756

    Article  PubMed Central  PubMed  Google Scholar 

  20. Pascolini D, Mariotti SP (2012) Global estimates of visual impairment: 2010. Br J Ophthalmol 96:614–618

    Article  PubMed  Google Scholar 

  21. Hecht S, Haig C, Chase AM (1937) The influence of light adaptation on subsequent dark adaptation of the eye. J Gen Physiol 20:831–850

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  22. Hollins M, Alpern M (1973) Dark adaptation and visual pigment regeneration in human cones. J Gen Physiol 62:430–447

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  23. Hecht S, Shlaer S (1938) An adaptometer for measuring human dark adaptation. J Opt Soc Am 28:269–275

    Article  Google Scholar 

  24. Goldstein EB (1975) Design for a dark adaptometer. Behav Res Meth Instrum 7:277–280

    Article  Google Scholar 

  25. Henson DB, Allen MJ (1977) A new dark adaptometer. Am J Opt Physiol Opt 54:641–644

    Article  CAS  Google Scholar 

  26. Friedburg C, Sharpe LT, Beuel S, Zrenner E (1998) A computer-controlled system for measuring dark adaptation and other psychophysical functions. Graefes Arch Clin Exp Ophthalmol 236:31–40

    Article  CAS  PubMed  Google Scholar 

  27. Jackson GR, Owsley C, McGwin G (1999) Aging and dark adaptation. Vision Res 39:3975–3982

    Article  CAS  PubMed  Google Scholar 

  28. Peters AY, Locke KG, Birch DG (2000) Comparison of the Goldmann–Weekers dark adaptometer and LKC technologies scotopic sensitivity tester-1. Doc Ophthalmol 101:1–9

    Article  CAS  PubMed  Google Scholar 

  29. Jackson GR, Felix T, Owsley C (2006) The scotopic sensitivity tester-1 and the detection of early age-related macular degeneration. Ophthalmic Physiol Opt 26:431–437

    Article  PubMed  Google Scholar 

  30. Jackson GR, Edwards JG (2008) A short-duration dark adaptation protocol for assessment of age-related maculopathy. J Ocul Biol Dis Infor 1:7–11

    Article  PubMed Central  PubMed  Google Scholar 

  31. Minassian DC, Reidy A, Lightstone A, Desai P (2011) Modelling the prevalence of age-related macular degeneration (2010–2020) in the UK: expected impact of anti-vascular endothelial growth factor (VEGF) therapy. Br J Ophthalmol 95:1433–1436

    Article  PubMed  Google Scholar 

  32. Mitchell P, Korobelnik JF, Lanzetta P, Holz FG, Prunte C, Schmidt-Erfurth U, Tano Y, Wolf S (2010) Ranibizumab (Lucentis) in neovascular age-related macular degeneration: evidence from clinical trials. Br J Ophthalmol 94:2–13

    Article  CAS  PubMed  Google Scholar 

  33. Heier JS, Brown DM, Chong V, Korobelnik JF, Kaiser PK, Nguyen QD, Kirchhof B, Ho A, Ogura Y, Yancopoulos GD, Stahl N, Vitti R, Berliner AJ, Soo Y, Anderesi M, Groetzbach G, Sommerauer B, Sandbrink R, Simader C, Schmidt-Erfurth U (2012) Intravitreal aflibercept (VEGF Trap-Eye) in wet age-related macular degeneration. Ophthalmology 119:2537–2548

    Article  PubMed  Google Scholar 

  34. Dieterle P, Gordon E (1956) Standard curve and physiological limits of dark adaptation by means of the Goldmann–Weekers adaptometer. Br J Ophthalol 40:652–655

    Article  CAS  Google Scholar 

  35. Hall JL (1981) Hybrid adaptive procedure for estimation of psychometric functions. J Acoust Soc Am 69:1763–1769

    Article  CAS  PubMed  Google Scholar 

  36. Treutwein B (1995) Adaptive psychophysical procedures. Vision Res 35:2503–2522

    CAS  PubMed  Google Scholar 

  37. Green DM, Swets JA (1966) Signal detection theory and psychophysics. Wiley, New York

  38. Sekuler R, Blake R (2006) Perception, 5th edn. McGraw-Hill, London

  39. Metha AB, Vingrys AJ, Badcock DR (1993) Calibration of a color monitor for visual psychophysics. Behav Res Meth Instrum Comp 25:371–383

    Article  Google Scholar 

  40. Brainard DH, Pelli DG, Robson T (2001) Display characterization. In: Hornak J (ed) The encyclopaedia of imaging science and technology, vol 18. Wiley, Hoboken, NJ, pp 172–188

    Google Scholar 

  41. McGwin G Jr, Jackson GR, Owsley C (1999) Using nonlinear regression to estimate parameters of dark adaptation. Behav Res Methods Instrum Comp 31:712–717

    Article  Google Scholar 

  42. Paupoo AA, Mahroo OA, Friedburg C, Lamb TD (2000) Human cone photoreceptor responses measured by the electroretinogram a-wave during and after exposure to intense illumination. J Physiol 529(Pt 2):469–482

    Article  CAS  PubMed  Google Scholar 

  43. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310

    Article  CAS  PubMed  Google Scholar 

  44. Gaffney AJ, Binns AM, Margrain TH (2011) The repeatability of the Goldmann–Weekers adaptometer for measuring cone adaptation. Doc Ophthalmol 122:71–75

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This study was funded by a research grant from the College of Optometrists, UK. The authors would like to thank Laura Smith for her help with data collection.

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Correspondence to Allannah J. Gaffney.

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Gaffney, A.J., Binns, A.M. & Margrain, T.H. Measurement of cone dark adaptation: a comparison of four psychophysical methods. Doc Ophthalmol 128, 33–41 (2014). https://doi.org/10.1007/s10633-013-9418-6

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  • DOI: https://doi.org/10.1007/s10633-013-9418-6

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