Ординатура / Офтальмология / Английские материалы / Mechanisms of the Glaucomas_Shields, Tombran-Tink, Barnstable_2008

left eye of a patient with superior arcuate glaucomatous visual field loss. Although the initial hypothesis was that frequency doubling was generated by RGCs, new evidence suggests that many portions of the visual pathways contribute to the frequency-doubling effect (69).

In addition to its usefulness for evaluating the visual field status of patients, the Humphrey matrix has also been reported to be effective in screening large populations, and for evaluating the visual field status of children (70).

Flicker Perimetry

There are three types of test procedures that have primarily been used to perform flicker perimetry. The first method is known as temporal modulation perimetry (TMP) and consists of a small target whose average luminance is matched to the background. Fixed temporal flicker rates are evaluated and the amplitude (modulation) of flicker needed to detect the target is measured. A second method is critical flicker fusion (CFF), in which small stimuli of high temporal contrast are presented to measure the highest temporal frequency at which flicker can be detected. The third procedure is known as luminance pedestal flicker (LPF), where a flickering target is superimposed on a luminance increment stimulus. Each of these procedures has advantages and disadvantages, although it should be noted that any of the flicker perimetry techniques are difficult to properly implement on current commercially available perimeters. Both TMP and CFF have been reported to be more sensitive than SAP for detection of early glaucomatous visual field loss (71), and there is also evidence that they are predictive of future glaucomatous visual field deficits for SAP. A direct comparison of TMP and CFF perimetry in glaucoma patients revealed that TMP had better clinical performance than CFF perimetry (72). LPF perimetry has not been performed in many clinical patient populations. However, one component of the test procedure that may be confusing for elderly patients or those with compromised vision is the ability to separate the luminance increment (the pedestal) from the flicker, which could increase false-positive and false-negative errors, thereby increasing variability. Figure 8 presents an example of results obtained with TMP perimetry in the right eye of a glaucoma patient with a superior arcuate visual field deficit.

In general, flicker perimetry is resistant to the influence of blur and other confounding factors (73), and represents a compelling stimulus for peripheral visual fields that are responsive to rapid stimulus changes.

Motion Perimetry

There are several variations of motion perimetry that have been developed. One method evaluates the minimum displacement of a target needed to detect motion (74), another procedure evaluates the proportion of random dots that need to be moving in the same direction (motion coherence) (75), and a third procedure examines the size and localization of moving dots that are necessary to detect motion (76). For each of these procedures, it has been reported that motion perimetry can provide early and useful information pertaining to glaucomatous visual field loss. Additionally, motion is a robust visual function that is resistant to moderate changes in blur, contrast, background illumination, and other test conditions, making it a particularly suitable

clinical tool. Because clinical test procedures are most effective when they have become standardized, it would be desirable for investigators who study motion perimetry to achieve a consensus on the proper conditions to be used for motion perimetric testing so that transfer and exchange of information can be readily accomplished, protocols can be derived, methods can be standardized, and normative comparison databases can be established. Figure 9 presents an example of an inferior arcuate visual field deficit in the right eye of a glaucoma patient.

Rarebit Perimetry

A relatively new visual field test procedure is known as Rarebit perimetry, which presents short presentations of very small stimuli consisting of one or two bright dots on a dark background shown on a liquid crystal display (LCD) computer screen (77,78). The arrangement of dots is in accordance with a predetermined pattern that is designed to detect early visual field losses in glaucoma and other ocular and neurologic diseases, and the patient’s task is to indicate whether they detected one or two dots on each trial. Only limited information is currently available for Rarebit perimetry, but the preliminary results are quite encouraging (77,78). Future evaluations will help to determine the overall utility of this technique as a clinical diagnostic tool.

Multifocal Visual-Evoked Potentials

The visual-evoked potential (VEP) has been used for many years to determine the conduction status of the afferent visual pathways from the retina to primary visual cortex. Recently, a technique known as multifocal VEPs (mfVEPs) has been developed and used by several laboratories (79–82). The display for mfVEP measurement consists of a computer display that presents a circular checkerboard of high-contrast light and dark checks arranged in 60 sectors (8 × 8 checkerboard) whose size is scaled from fixation out to the periphery by a matrix of checks whose size is increased to compensate for cortical magnification of the central macular region of the visual field. The checks are counterphase flickered according to a random binary sequence that is the same for all sectors but is sequentially delayed for individual sectors of the display [see (79–82) for details]. Multiple electrodes placed on the scalp overlying primary visual cortex (V1) are used to record the synchronized neural evoked responses to the rapidly alternating checkerboard display, and elaborate statistical and mathematical procedures are employed to extract the mfVEP signal over a recording interval of approximately 10–15 min. In this manner, it is possible to obtain a local VEP for a number of individual locations throughout the visual field. Although this procedure has been termed by some as an “objective” measure (due to less-demanding response from the subject), it still necessitates appropriate interpretation and analysis on the part of the examiner and requires cooperation on the part of the subject.

Many laboratories have reported that this procedure can provide useful visual field information for glaucoma patients and individuals suspected of developing glaucoma. Additionally, it has been reported to be a successful method of obtaining reliable visual field information in some individuals who are not able to perform routine visual field testing. Figure 10 presents an example of mfVEP results for both eyes of a patient with a relatively normal visual field for the left eye and an inferior arcuate defect for the right eye.

Fig. 9. Motion perimetry results indicating the presence of an inferior arcuate defect in the right eye of a patient with glaucomatous damage. This figure presented courtesy of Dr. Michael Wall, University of Iowa.

STRUCTURE/FUNCTION RELATIONSHIPS

The relationship between structural and functional damage that is produced by glaucoma has been a topic of inquiry for many, many years (83). Despite a tremendous number of technological advances in the measurement and evaluation of both structure and function of the optic nerve and retinal nerve fiber layer, there are several findings

Fig. 10. Multifocal visual-evoked potential (mfVEP) for both eyes of a patient with glaucomatous damage to the right eye. An inferior arcuate defect is present for the right eye, whereas the left eye results are essentially within normal limits.

that appear to have remained similar over a long time period. First, nearly all studies indicate that there is a significant relationship between structure and function for glaucomatous damage, but the magnitude of the correlation between these two variables is smaller than one would hope for (83). This means that it is important to evaluate both structure and function in glaucoma patients, and that clinical decision, treatment, and management of glaucoma patients cannot rely on using information based on either structure or function alone. Second, most investigations report that clinical observation of structural changes produced by glaucoma occur earlier and more frequently in glaucoma than do functional deficits (83). Recent studies, however, draw this conclusion into question, and technological advancements in both areas may dramatically alter this finding in the future. Third, nearly all of the studies over the past 50–75 years indicate that measures of both structure and function exhibit a considerable amount of variability, both from one person to another and from multiple examinations performed on the same person (83). A number of laboratories have made significant efforts to minimize this variability for both structure and function (11–31). Finally, although it is a vital aspect of the diagnosis, treatment, and management of glaucoma patients, determination of glaucomatous progression remains an enigma (84). Several methods are available for evaluating progression of both structure and function (84–86). However, reliable performance of these procedures on an individual basis usually requires a large number of examinations to be performed over a rather extended time period. This is undesirable from the standpoint of both the practitioner and the patient.

At the present time, however, the ability to distinguish pathology-related changes from those that are produced by factors that are not primarily related to the disease process (e.g., fatigue, learning, eye movements, cooperation) is a major challenge that has not been overcome, and attempts to address these issues have not been met with consensus among glaucoma experts.

Several laboratories have recently begun to incorporate both structural and functional measures into multivariate mathematical models in an attempt to utilize information from both sources in a more efficient manner that is clinically useful (26–31). Results to date indicate that combining both structural and functional information into a model produces results that are superior to evaluating either modality alone. However, more work will be needed to establish the specific quantitative relationships between structure and function and their clinical consequences. Hopefully, continuing work in this area will provide a better means of monitoring the status of glaucoma patients as well as provide predictive information about the likelihood of their future clinical course with glaucoma.

A number of advances have been achieved for the measurement and evaluation of structural and functional properties of the optic nerve and retinal nerve fiber layer within the past 10 years. Investigators, practitioners, and patients are all hopeful that this surge of innovation will continue or expand in future years to provide more sophisticated, accurate, and reliable methods of evaluating the status of glaucoma patients and individuals who are at risk of developing glaucoma.

REFERENCES

1.Dacey DM. Physiology, morphology and spatial densities of identified ganglion cell types in primate retina. Ciba Foundation Symposium 1994;184:12–28; discussion 28–34, 63–70.

2.Masland RH. The fundamental plan of the retina. Nature Neuroscience 2001;4:877–886.

3.Weber AJ, Kaufman PL, Hubbard WC. Morphology of single ganglion cells in the glaucomatous primate retina. Investigative Ophthalmology and Visual Science 1998;39: 2304–2320.

4.Yücel YH, Zhang Q, Gupta N, Kaufman PL, Weinreb RN. Loss of neurons in magnocellular and parvocellular layers of the lateral geniculate nucleus in glaucoma. Archives of Ophthalmology. 2000;118:378–384.

5.Weber AJ, Chen H, Hubbard WC, Kaufman PL. Experimental glaucoma and cell size, density, and number in the primate lateral geniculate nucleus. Investigative Ophthalmology and Visual Science 2000;41:1370–1379.

6.Yücel YH, Zhang Q, Weinreb RN, Kaufman PL, Gupta N. Effects of retinal ganglion cell loss on magno-, parvo-, koniocellular pathways in the lateral geniculate nucleus and visual

cortex in glaucoma. Progress in Retinal and Eye Research 2003;22:465–481.

7. Weber AJ, Harman CD. Structure-function relations of parasol cells in the normal and glaucomatous primate retina. Investigative Ophthalmology and Visual Science

2005;46:3197–3207.

8.Quigley HA, Addicks EM, Green WR. Optic nerve damage in human glaucoma III. Quantitative correlation of nerve fiber loss and visual field defect in glaucoma, ischemic neuropathy, papilledema, and toxic neuropathy. Archives of Ophthalmology 1982;100: 135–146.

9.Kerrigan-Baumrind LA, Quigley HA, Pease ME, Kerrigan DF, Mitchell RS. Number of ganglion cells in glaucoma eyes compared with threshold visual field tests in the same persons. Investigative Ophthalmology and Visual Science 2000;41:741–748.

10.Harwerth RS, Carter-Dawson L, Shen F, Smith EL, 3rd, Crawford ML. Ganglion cell losses underlying visual field defects from experimental glaucoma. Investigative Ophthalmology and Visual Science 1999;40:2242–2250.

11.Harwerth RS, Carter-Dawson L, Smith EL, 3rd, Barnes G, Holt WF, Crawford ML. Neural losses correlated with visual losses in clinical perimetry. Investigative Ophthalmology and Visual Science 2004;45:3152–3160.

12.Harwerth RS, Crawford ML, Frishman LJ, Viswanathan S, Smith EL, 3rd, CarterDawson L. Visual field defects and neural losses from experimental glaucoma. Progress in Retinal and Eye Research 2002;21:91–125.

13.Harwerth RS, Quigley HA. Visual field defects and retinal ganglion cell losses in patients with glaucoma. Archives of Ophthalmology 2006;124:853–859.

14.Swanson WH, Felius J, Pan F. Perimetric defects and ganglion cell damage: interpreting linear relations using a two-stage neural model. Investigative Ophthalmology and Visual Science 2004;45:466–472.

15.Pan F, Swanson WH, Dul MW. Evaluation of a two-stage neural model of glaucomatous defect: an approach to reduce test-retest variability. Optometry and Vision Science 2006;83:499–511.

16.Garway-Heath DF, Caprioli J, Fitzke FW, Hitchings RA. Scaling the hill of vision: the physiological relationship between light sensitivity and ganglion cell numbers. Investigative Ophthalmology and Visual Science 2000;41:1774–1782.

17.Garway-Heath DF, Holder GE, Fitzke FW, Hitchings RA. Relationship between electrophysiological, psychophysical, and anatomical measurements in glaucoma. Investigative Ophthalmology and Visual Science 2002;43:2213–2220.

18.Garway-Heath DF, Poinoosawmy D, Fitzke FW, Hitchings RA. Mapping the visual field to the optic disc in normal tension glaucoma eyes. Ophthalmology 2000;107:1809–1815.

19.Yücel YH, Gupta N, Kalichman MW, et al. Relationship of optic disc topography to optic nerve fiber number in glaucoma. Archives of Ophthalmology 1998;116:493–497.

20.Schlottmann PG, De Cilla S, Greenfield DS, Caprioli J, Garway-Heath DF. Relationship between visual field sensitivity and retinal nerve fiber layer thickness as measured by scanning laser polarimetry. Investigative Ophthalmology and Visual Science 2004;45: 1823–1829.

21.Bowd C, Zangwill LM, Medeiros FA, et al. Structure-function relationships using confocal scanning laser ophthalmoscopy, optical coherence tomography, and scanning laser polarimetry. Investigative Ophthalmology and Visual Science 2006;47:2889–2895.

22.Gordon MO, Beiser JA, Brandt JD, et al. The Ocular Hypertension Treatment Study: baseline factors that predict the onset of primary open-angle glaucoma. Archives of Ophthalmology 2002;120:714–720; discussion 829–830.

23.Strouthedis NG, Vinciotti V, Tucker AJ, Gardiner SK, Crabb DP, Garway-Heath DF. Structure and function in glaucoma: the relationship between a functional visual field map and an anatomic retinal map. Investigative Ophthalmology and Visual Science 2006;47: 5356–5362.

24.Mardin CY, Peters A, Horn F, Junemann AG, Lausen B. Improving glaucoma diagnosis by the combination of perimetry and HRT measurements. Journal of Glaucoma 2006;15: 299–305.

25.Reus NJ, Lemij HG. Relationships between standard automated perimetry, HRT confocal scanning laser ophthalmoscopy, and GDx VCC scanning laser polarimetry. Investigative Ophthalmology and Visual Science 2005;46:4182–4188.

26.Gardiner SK, Johnson CA, Cioffi GA. Evaluation of the structure-function relationship in glaucoma. Investigative Ophthalmology and Visual Science 2005;46:3712–3717.

27.Anderson RS. The psychophysics of glaucoma: improving the structure/function relationship. Progress in Retinal and Eye Research 2006;25:79–97.

28.Harwerth RS, Carter-Dawson L, Smith EL, Crawford ML. Scaling the structure-function relationship for clinical perimetry. Acta Ophthalmologica 2005;83:448–455.

29.Artes PH, Chauhan BC. Longitudinal changes in the visual field and optic disc in glaucoma.

Progress in Retinal and Eye Research 2005;24:333–354.

30.Girkin CA. Relationship between structure of optic nerve/nerve fiber layer and functional measurements in glaucoma. Current Opinion in Ophthalmology 2004;15:96–101.

31.Shah NN, Bowd C, Medieros FA, Weinreb RN, Sample PA, Hoffmann EM, Zangwill LM. Combining structural and functional testing for detection of glaucoma. Ophthalmology 2006;113:1593–1602.

32.Greenfield DS. Stereoscopic optic disc photography. Chapter 1 (pp 3–14), in Imaging in glaucoma (Schuman JS, ed), Thoroughfare, NJ: Slack Incorporated, 1997.

33.Keltner JL, Johnson CA: Short Wavelength Automated Perimetry (SWAP) in neuroophthalmologic disorders. Archives of Ophthalmology 1995;113:475–481.

34.Zangwill L, de Souza Lima M, Weinreb RN. Confocal scanning laser ophthalmoscopy to detect glaucomatous optic neuropathy. Chapter 4 (pp 45–58), in Imaging in glaucoma (Schuman JS, ed), Thoroughfare, NJ: Slack Incorporated, 1997.

35.de Souza Lima M, Zangwill L, Weinreb RN. Scanning laser polarimetry to assess the nerve fiber layer. Chapter 6 (pp 83–94), in Imaging in glaucoma (Schuman JS, ed), Thoroughfare, NJ: Slack Incorporated, 1997.

36.Schuman JS. Optical coherence tomography for imaging and quantitation of nerve fiber layer thickness. Chapter 7 (pp 95–130), in Imaging in glaucoma (Schuman JS, ed), Thoroughfare, NJ: Slack Incorporated, 1997.

37.Bengtsson B, Olsson J, Heijl A, Rootzen H. A new generation of algorithms for computerized threshold perimetry, SITA. Acta Ophthalmologica 1997;75:368–375.

38.Bengtsson B, Heijl A, Olsson J. Evaluation of a new threshold visual field strategy, SITA, in normal subjects. Swedish Interactive Threshold Algorithm. Acta Ophthalmologica 1998;76:165–169.

39.Bengtsson B. Evaluation of a new perimetric threshold strategy, SITA, in patients with manifest and suspect glaucoma. Acta Ophthalmologica 1998;76:268–272.

40.Budenz, DL, Rhee P, Feuer WJ, McSoley J, Johnson CA, Anderson DR. Comparison of glaucomatous visual field defects using standard Full Threshold and the Swedish Interactive Threshold Algorithms (SITA Standard and SITA Fast). Archives of Ophthalmology 2002;120:1136–1141.

41.Vingrys AJ, Pianta M. A new look at threshold estimation algorithms for automated static perimetry. Optometry and Vision Science 1999;76:588–595.

42.Turpin A, McKendrick AM, Jophnson CA, Vingrys AJ. Properties of perimetric threshold estimates from full threshold, ZEST, and SITA-like strategies, as determined by computer simulation. Investigative Ophthalmology and Visual Science 2003;44:4787–4795.

43.Morales J, Weitzman ML, Gonzalez de la Rosa M. Comparison between TendencyOriented Perimetry (TOP) and Octopus threshold perimetry. Ophthalmology 2000;107: 134–142.

44.Gonzales de la Rosa M, Morales J, Dannheim F, Papst E, Papst N, Seiler TJ, Matsumoto C, Lachkar Y, Mermoud A, Prunte C. Multicenter evaluation of tendency-oriented perimetry (TOP) using the G1 grid. European Journal of Ophthalmology 2003;13:32–41.

45.Turpin A, Johnson CA, Spry PGD. Development of a maximum likelihood procedure for short wavelength automated perimetry (SWAP). In Perimetry Update 2000/2001 (Wall M and Mills RP, eds), The Hague: Kugler Publications, 2001, pp 139–147.

46.Johnson CA. Software upgrades for automated perimetry. Glaucoma Today 2004;2:32–34.

47.Stiles WS. Increment thresholds and the mechanisms of color vision. Documenta Ophthalmologica 1949;3:138–165.

48.Enoch JM. The two-color threshold technique of Stiles and derived component color mechanisms. In Handbook of Sensory Physiology: VII/4 - Visual Psychophysics (Jameson D and Hurvich LM, eds), Berlin: Springer-Verlag, 1072, pp 537–567.

49.Hendry SHC, Reid RC. The koniocellular pathway in primate vision. Annual Review of Neuroscience 2000;23:127–153.

50.Martin PR, White AJ, Goodchild AK, Wilder HD, Seftron AE. Evidence that blue-on cells are part of the third geniculocortical pathway in primates. European Journal of Neuroscience 1997;9:1536–1541.

51.Dacey DM, Packer OS. Color coding in the primate retina: diverse cell types and conespecific circuitry. Current Opinion in Neurobiology 2003;13:421–427.

52.Dacey DM, Lee BB. The “blue-on” opponent pathway in primate retina originates from a distinct bistratified ganglion cell type. Nature 1994;367:731–735.

53.Kitahara K, Tamaki R, Nopji J, Kandatsu A, Matsuzaki H. Extrafoveal Stiles pi mechanisms. Documenta Ophthalmologica Proceedings Series: Fifth International Visual Field Symposium, 1983, The Hague: Junk Publishers, 397–403.

54.Kranda K, King-Smith PE. What can color thresholds tell us about the underlying detection mechanisms? Ophthalmic and Physiological Optics 1984;4:101–105.

55.Johnson, CA, Adams, AJ, Casson, EJ and Brandt, JD. Blue-on-Yellow perimetry can predict the development of glaucomatous visual field loss. Archives of Ophthalmology 1993;111:645–650.

56.Johnson, CA, Adams AJ, Casson EJ, Brandt JD. Progression of early glaucomatous visual field loss for Blue-on-Yellow and standard White-on-White automated perimetry. Archives of Ophthalmology 1993;111:651–656.

57.Sample PA, Weinreb RN, Boynton RM. Acquired dyschromatopsia is glaucoma. Survey of Ophthalmology 1986;81:54–64.

58.Sample PA, Weinreb RN. Progressive visual field loss in glaucoma. Investigative Ophthalmology and Visual Science 1992;33:2068–2071.

59.Racette L, Sample PA. Short wavelength automated perimetry. Ophthalmology Clinics of North America 2003;16:227–236.

60.Demirel S, Johnson CA. Short wavelength automated perimetry (SWAP) in ophthalmic practice. Journal of the American Optometric Association 1996;67:451–456.

61.Sample PA, Johnson CA, Haegerstrom-Portnoy G, Adams AJ. Optimum parameters for short-wavelength automated perimetry. Journal of Glaucoma 1996;5:375–383.

62.Bengtsson B. A new rapid threshold algorithm for short-wavelength automated perimetry.

Investigative Ophthalmology and Visual Science 2003;44:455–461.

63.Bengtsson B, Heijl A. Normal intersubject threshold variability and normal limits of the SITA SWAP and full threshold SWAP perimetric programs. Investigative Ophthalmology and Visual Science 2003;44:5029–5034.

64.Johnson CA, Samuels SJ. Screening for glaucomatous visual field loss with frequencydoubling perimetry. Investigative Ophthalmology and Visual Science 1997;38:413–425.

65.Maddess T, Henry GH. Performance of nonlinear visual units in ocular hypertension and glaucoma. Clinical Vision Science 1992;7:371–383.

66.Anderson AJ and Johnson CA. Frequency-doubling technology perimetry. In Ophthalmology Clinics of North America (Sample PA and Girkin CA, eds), Philadelphia: W.B. Saunders, 2003;16(2):213–225.

67.Anderson AJ, Johnson CA, Fingeret M, Keltner JL, Spry PGD, Wall M, Werner JS. Characteristics of the normative database for the Humphrey matrix perimeter. Investigative Ophthalmology and Visual Science 2005;46:1540–1548.

68.Artes PH, Hutchison DM, Nicolela MT, LeBlanc RP, Chauhan BC. Threshold and variability properties of matrix frequency doubling technology and standard automated