Advanced Analysis of PRVEP in Anisometropic Amblyopia

Document Type: Original Paper

Authors

1 Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran

2 Iran University of Medical Sciences

3 Department of Optometry, School of Rehabilitation Science, Iran University of Medical Sciences, Tehran, Iran

4 Departments of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

Abstract

Introduction: to identify the pattern-reversal visual evoked potential (PRVEP) waveform descriptor by evaluating discrete wavelet transform (DWT) in order to optimize stimulus in the diagnosis of anisometropia amblyopia.
Materials and Methods: The PRVEP testing was performedfor 31 normal individuals and 35 patients with amblyopia. The stimuli were consisted of spatial frequencies of 1, 2, and 4 cycles per degree (cpd) and contrast levels of 100%, 50%, 25%, and 5%. The results were analyzed in the dimensions of time and time-frequency. DWT descriptor were extracted at level 7 (7P descriptor) for Haar, Daubechies 2, Daubechies 4, Symlet 5, Biorthogonal 3.5, Biorthogonal 4.4, and Coiflet 5 wavelets for 12 stimuli and compared between the two groups.  The correlation between different spatial frequencies at the same contrast level and the similarities between reconstructed signals and original waveforms were evaluated.
Results: There were a significant reduction in P100 amplitude and a significant elevation in latency among the patient group. In the patients with amblyopia, 7P descriptor decreased in all analysis except for the frequency of 4 cpd and the contrast of 5% using bior4.4. No significant correlation was observed between different frequencies at a special contrast; however, there was a significant correlation between reconstructed signals and the original ones.
Conclusion: The 7P descriptor could be used to distinguish between normal and abnormal signals in anisometropia amblyopia. Considering the results, DWT with coif5, db4, bior4.4, and bior3.5 wavelets can be utilized as a good indicator for selecting optimum stimulus.

Keywords

Main Subjects


References

 

  1. Parisi  V,  Scarale  ME,  Balducci  N,  Fresina  M,  Campos  EC.  Electrophysiological detection of delayed postretinal neural conduction in human amblyopia. Invest Ophthalmol Vis Sci. 2010 Oct 1; 51: 5041-8.
  2. Zele AJ, Pokorny J, Lee DY, Ireland D.  Anisometropic amblyopia: Spatial contrast sensitivity deficits in inferred magnocellular and parvocellular vision. Invest Ophthalmol Vis Sci. 2007 Aug 1; 48:3622–31.
  3. Polat U, Sagi D, Norcia AM.Abnormal long-range spatial inter- actions in amblyopia. Vision Res. 1997 Mar 1; 37:737–44.
  4. Hamm LM, Black J, Dai Sh, Thompson B. Global processing in amblyopia. Front Psychol. 2014 Jun 17; 5:583.
  5. Thompson D. Developmental amblyopia. In: Heckenlively JR, Arden GB,  editors. Principles and practice of clinical electrophysiology of vision. 2nd ed. Cambridge: MIT Press. 2006. p. 643-50.
  6. Sloper J. Amblyopia beyond acuity. JAAPOS. 2008; 12:3-4
  7. Press L.J, Kohl P. Vision therapy for amblyopia. In: Eye care for infants and young children. USA: Butterworth-Heineman. 1997. p. 155.
  8. Wang X, Cui D, Zheng L, Yang X, Yang H, Zeng Combination of blood oxygen level‑dependent functional magnetic resonance imaging and visual evoked potential recordings for abnormal visual cortex in two types of amblyopia. Mol Vis. 2012 Apr 11; 18: 909‑19.
  9. Miki A, Siegfried JB, Liu CSJ, Modestino EJ, Liu GT. Magno- and parvocellular visual cortex activation in anisometropic amblyopia, as studied with functional magnetic resonance imaging. Neuro-Ophthalmology. 2008 Jun 5; 32:187–93.
  10. Choi MY, Lee KM, Hwang JM, Choi DG, Lee DS, Park KH, et al. Comparison between anisometropic and strabismic amblyopia using functional magnetic resonance imaging. British Journal of Ophthalmology. 2001 Mar 28; 85:1052–6.
  11. Demer JL. Positron emission tomographic studies of cortical function in human amblyopia. Neurosci Biobehav Rev. 1993 winter; 17:469 76.
  12. Gharebaghi AH, Heidary F, Gharebaghi R, Heidary R. Mehdi-ODM.A modified digital monitoring of the occlusion therapy for amblyopia. Graefes Arch Clin Exp Ophthalmol. 2011 Jun 1; 249:945-6.
  13. Odom JV, Bach M, Brigell M. Holder GE, McCulloch DL, Mizota A, et al . ISCEV standard for clinical visual evoked potentials: (2016 update). Doc Ophthalmol. 2016 Aug 1; 133:1–9.
  14. Ridder WH, Rouse MW. Predicting potential acuities in amblyopes: predicting post therapy acuity in amblyopes. Doc Ophthalmol. 2007 May 1; 114: 135-45.
  15. De Mendonça RH, Abbruzzese S, Bagolini B, Nofroni I, Ferreira EL, Odom JV. . Visual evoked potential importance in the complex mechanism of amblyopia. Int Ophthalmol. 2013 Oct 1; 33(5):515-9.
  16. Elshazly AAEF, Walid MAE, Elzawahry R, Elsherbiny NE. Flash visual evoked potential versus pattern visual evoked potential in the diagnosis of strabismic amblyopia. Int J Ophthalmol Clin Res. 2016 Aug 1; 3: 061.
  17. Talebnejad MR, Hosseinmenni S, Jafarzadehpur E, Mirzajani A, Osroosh E. Comparison of the Wave Amplitude of Visually Evoked Potential in Amblyopic Eyes between Patients with Esotropia and Anisometropia and a Normal Group. Iran J Med Sci. 2016 Mar 1; 41(2):94-101.
  18. Hosseinmenni  S,  Talebnejad  MR,  Jafarzadehpur  E,  Mirzajani  A,  Osroosh E. P100 wave latency in anisometropic and esotropic amblyopia versus normal eyes. J Ophthalmic Vis Res. 2015 Jul-Sep; 10(3): 268-73.
  19. Oner A, Coskun M, Evereklioglu C, Dogan H. Pattern VEP is a useful technique in monitoring the effectiveness of occlusion therapy in amblyopic eyes under occlusion therapy. Doc Ophthalmol. 2004 Nov 18; 109(3):223-7.
  20. Chung W, Hong S, Lee JB, Han SH. Pattern visual evoked potential as a predictor of occlusion therapy for amblyopia. Korean J Ophthalmol. 2008 Dec 26; 22:251-4.
  21. Fahle M, Bach M. Origin of the visual evoked potentials. In: Heckenlively JR, Arden GB, editors. Principles and practice of clinical electrophysiology of vision. 2nd ed. Cambridge: MIT Press ; 2006. p. 207-34.
  22. Kothari R, Bokariya P, Singh S, Singh R. A comprehensive review on methodologies employed for visual evoked potentials. Scientifica. 2016; 2016. Doi: 10.1155/2016/9852194.
  23. Souza GS, Gomes BD, Saito CA, da Silva Filho M, Silveira LCL. Spatial luminance contrast sensitivity measured with transient VEP: comparison with psychophysics and evidence of multiple mechanisms. Invest Ophthalmol Vis Sci. 2007 Jul 1; 48(7):3396 –404.
  24. Tobimatsu S, Celesia GG. Studies of human visual pathophysiology with visual evoked potentials. Clin Neurophysiol. 2006 Jul 1; 117(7):1414 –33.
  25. Lalor EC, Foxe JJ. Visual evoked spread spectrum analysis (VESPA) responses to stimuli biased towards magnocellular and parvocellular pathways. Vision Res. 2009 Jan 1; 49(1):127‑33.
  26. Valberg A, Rudvin I. Possible contributions of magnocellular- and parvocellular-pathway cells to transient VEPs. Vis Neurosci. 1997 Jan-Feb; 14(1):1–11.
  27. Rafiee J, Rafiee MA, Prause N, Schoen MP. Wavelet basis functions in biomedical signal processing. Expert Systems with Applications. 2011 May; 38 (5):6190- 201.
  28. Akay M. Time frequency and wavelets in biomedical signal processing. IEEE Press series in biomedical Engineering. 1998.
  29. Chui C.K. An Introduction to Wavelets. San Diego: Academic Press;. 1992.
  30. Drissi H, Regragui F, Antoine JP, Bennouna M. Wavelet transform analysis of visual evoked potentials: some preliminary results. ITBM-RBM. 2000 Apr 1; 21(2):84-91.
  31. Ulyana V. Borodina, Rubin R. Aliev. Wavelet spectra of visual evoked potentials: time course of delta, theta, alpha and beta bands, Neurocomputing. 2013 Dec 1; 121:551-5.
  32. Thie J, Sriram P, Klistorner A, Graham ST. Gaussian wavelet transform and classifier to reliably estimate latency of multifocal visual evoked potentials (mfVEP). Vis Res. 2012 Jan 1; 52(1): 79-87.
  33. Zhang JH, Janschek K, Bohme JF, Zeng YJ. Multi-resolution dyadic wavelet denoising approach for extraction of visual evoked potentials in the brain. IEE Proc.-Vis. Image Signal Process. 2004 Jun 1; 151(3):180-6.
  34. Sivakumar R, Hema B, Karir P, Nithyaklyani N. Denoising of transient VEP signals using wavelet transform. J. Eng. Appl. Sci. 2006 Oct; 1(3): 242-7.
  35. Akbari M, Azmi R. Automatic classification of visual evoked potentials based on wavelet analysis and support vector machine. Proceedings of the 6th International Advanced Technologies Symposium (IATS'11); 2011 May 16-18; Elazığ, Turkey: Firat University; 2011.P 227-30.
  36. Hamzaoui E, Regragui F.  Discrimination of visual evoked potentials using image processing of their time-scale representations. Procedia Technology. 2014 Nov 1; 17:359-67.
  37. Almurshedi A, Khamim Ismail A, Skottun BC, Skoyles JR. Signal refinement: Principal component analysis and wavelet transform of visual evoked response. Res. J. App. Sci. Eng. Technol. 2015 Jan 15; 9(2): 106-12.
  38. Quiroga RQ. Obtaining single stimulus evoked potentials with wavelet denoising. Physica D. 2000; 145(3-4):278-92.
  39. Heidari H, Einalou Z. SSVEP extraction applying wavelet transform and decision tree with bays classification. ICNSJ. 2017 summer; 4 (3):91-7.
  40. Heravian J, Daneshvar R, Dashti F, Azimi A, Ostadi Moghaddam H, et al.  Simultaneous pattern visual evoked potential and pattern electroretinogram in strabismic and anisometropic amblyopia. Iran Red Crescent Med J. 2011 Jan 1; 13(1):21-6.
  41. Urbuch D, Gur M, Pratt H, Peled R. Time domain analysis of VEPs detection of waveform abnormalities in multiple sclerosis. Invest Ophthalmol Vis Sci. 1986 Sep 1; 27(9):1379-84.
  42. Barboni MTS, Nagy BV, Martin CMG, Bonci DMO, Hauzman E, Aher A, et al. L-/M-cone opponency in visual evoked potentials of human cortex. Journal of Vision. 2017 Aug 1; 17(9):20, 1-12
  43. Regan D. Fourier analysis of evoked potentials: some methods based on Fourier analysis. In Visual Evoked Potentials in Man: New Developments, Desmedt JE. Oxford: Clarendon Press. 1997; 110-20.
  44. Trick GL, Trobe JD, Dawson WW, Trick LR, McFadden C. Power spectral analysis of visual evoked potentials in multiple sclerosis. Curr Eye Res. 1984 Oct 1; 3(10):1179-86.
  45. Mallat SG. A wavelet tour of signal processing the sparse way. 3rded. Houston: Academic Press. 2009.
  46. Addison PS. The illustrated wavelet transform handbook: introductory theory and applications in science, engineering, medicine and finance. CRC press. 2002.
  47. Gauvin M, Lina JM, Lachapelle P. Advance in ERG analysis: From peak time and amplitude to frequency, power, and energy. BioMed Res Int. 2014 Jul 1; 1-11.
  48. Gauvin M, Little JM, Lina JM, Lachapelle P. Functional decomposition of the human ERG based on the discrete wavelet transform. J Vis. 2015 Dec 31; 15(16):1-22.
  49. Ellemberg D, Hammarrenger B, Lepore F, Roy MS, Guillemot JP. Contrast dependency of VEPs as a function of spatial frequency: the parvocellular and magnocellular contributions to human VEPs. Spatial Vision. 2001 May 11; 15(1): 99–111.
  50. Foxe JJ, Strugstad EC, Sehatpour P, Molholm S, Pasieka W, Schroeder ChE, et al. Parvocellular and magnocellular contributions to initial generators of the visual evoked potential: High-density electrical mapping of the "C1" component. Brain Topogr. 2008 Sep 11; 21:11–21.
  51. Kwak HW, Kin SM. Evaluation of clinically applied visual evoked potential (VEP) in ophthalmological and neurological disease. Kor. J. Ophthalmol. 1987 Jun; 1(1):26-30.
  52. Zele AJ, Wood JM, Girgenti CC. Magnocellular and parvocellular pathway mediated luminance contrast discrimination in amblyopia. Vision Research. 2010 May 12; 50:969–76.
  53. Shan Y, Moster, ML, Roemer RA, Siegfried JB. Abnormal function of the parvocellular visual system in anisometropic amblyopia. Journal of Pediatric Ophthalmology and Strabismus. 2000 March 1; 37: 73–8.
  54. Skottun BC, Skoyles JR. The parvocellular system an amblyopia. Neuro-Ophthalmology. 2008; 32:177-8.
  55. Skottun BC, Skoyles JR. On identifying magnocellular and parvocellular responses on the basis of contrast-response functions. Schizophrenia Bulletin. 2011 Jan 1; 37 (1): 23–6.
  56. Campos EC, Prampolini MR, Gulli R. Contrast sensitivity differences between strabismic and anisometropic amblyopia: objective correlate by means of visual evoked responses. Doc ophthalmol. 1984 Aug 15; 58:45-50.