Ординатура / Офтальмология / Английские материалы / Ocular Neuroprotection_Levin, Polo _2003

(Grant MT-12153 and MT-13383), the FCAR-GRENE and the Vision Network of the FRSQ. Thanks are due to Olga Dembinska, Julie Racine, and Marianne Rufiange for providing some of the illustrations.

REFERENCES

1.Rosolen S, Rigaudie`re F, Lachapelle P. A practical method to obtain reproducible binocular electroretinograms in dogs. Doc Ophthalmol 2002; 105:83–92.

2.Lachapelle P, Benoit J, Dembinska O, Rojas LM, Almazan G, Chemtob S. Persistent functional and structural retinal anomalies in newborn rats exposed to hyperoxia. Can J Physiol Pharmacol 1999; 77:48–55.

3.Cayouette M, Behn D, Sendtner M, Lachapelle P, Gravel C. Functional rescue of photoreceptors in the retinal degeneration slow (rds) mouse by CNTF. J Neurosci 1998; 18:9282–9293.

4.Rosolen SG, Rigaudie`re F, Saint-Macary G, Lachapelle P. Recording the photopic electroretinogram from conscious Yucatan micropigs. Doc Ophthalmol 2000; 98: 197–205.

5.Rojas LM, McNeil R, Cabana T, Lachapelle P. Diurnal and nocturnal visual capabilities in shorebirds as a function of their feeding strategies. Brain Behav Evol 1999; 53:29–43.

6.Gorfinkel J, Lachapelle P. Maturation of the photopic b-wave and oscillatory potentials of the electroretinogram in the neonatal rabbit. Can J Ophthalmol 1990; 25: 138–144.

7.Blain L, Lachapelle P, Molotchnikoff S. The effect of acute trichloroethylene exposure on electroretinogram components. J Neurotoxicol Teratol 1990; 12:633–636.

8.Blain L, Lachapelle P. Comparative effect of chronic trichloroethylene exposure on the electroretinogram components and oscillatory potentials. Neurotoxicol 1994; 15: 627–632.

9.Dembinska O, Rojas LM, Varma DR, Chemtob S, Lachapelle P. Graded contribution of retinal maturation to the development of oxygen-induced retinopathy in rats. Invest Ophthalmol Vis Sci 2001; 42:1111–1118.

10.Reynaud X, Hansen RM, Fulton AB. Effect of prior oxygen exposure on the electroretinographic responses of infant rats. Invest Ophthalmol Vis Sci 1995; 36:2071–2079.

11.Behn D, Potter MJ. Sildenafil-mediated reduction in retinal function in heterozygous mice lacking the γ-subunit of phosphodiesterase. Invest Ophthalmol Vis Sci 2001; 42:523–527.

12.Jaissle GB, May CA, Reinhard J, Kohler K, Fauser S, Lu¨tjen-Drecoll E, Zrenner E, Seeliger MW. Evaluation of the rhodposin knockout mouse as a model of pure cone function. Invest Ophthalmol Vis Sci 2001; 42:506–513.

13.Armington JC. The Electroretinogram. New York: Academic Press, 1974.

14.Granit R. The components of the retinal action potential in mammals and their relation to the discharge in the optic nerve. J Physiol 1933; 77:207–239.

15.Marmor MF, Zrenner E. Standard for clinical electroretinography (1999 update). Doc Ophthalmol 1999; 97:143–156.

16.Hood DC, Birch DG. Assessing abnormal rod photoreceptor activity with the a- wave of the electroretinogram: applications and methods. Doc Ophthalmol 1997; 92:253–267.

17.Sieving PA, Murayama K, Naarendorp F. Push-pull model of the primate electroretinogram : a role for hyperpolarizing neurons in shaping the b-wave. Vis Neurosci 1994; 11:519–532.

18.Wachtmeister LL. Oscillatory potentials in the retina: what do they reveal. Prog Retinal Eye Res 1998; 17:485–521.

19.Lachapelle P. Evidence for an intensity-coding oscillatory potential in the human electroretinogram. Vision Res 1991; 31:767–774.

20.Lachapelle P. The effect of slow flicker on the human photopic oscillatory potentials. Vision Res 1991; 31:1851–1857.

21.Lachapelle P. Analysis of the photopic electroretinogram recorded before and after dark-adaptation. Can J Ophthalmol 1987; 22:354–361.

22.Peachey NS, Alexander KR, Fishman GA, Derlacki DJ. Properties of the human cone system electroretinogram during light adaptation. Appl Optics 1989; 28:1145– 1150.

23.Lachapelle P, Blain L, Quigley MG, Polomeno RC, Molotchnikoff S. The effect of diphenylhydantoin on the electroretinogram. Doc Ophthalmol 1990; 73:359–368.

24.Guite´ P, Lachapelle P. The effect of 2-amino-4-phosphonobutyric acid on the oscillatory potentials of the electroretinogram. Doc Ophthalmol 1990; 75:125–133.

25.Lachapelle P. The human suprathreshold photopic oscillatory potentials: Method of analysis and clinical illustration. Doc Ophthalmol 1994; 88:1–25.

26.Lachapelle P, Benoit J, Rousseau S, McKerral M, Polomeno RC, Little JM, Koenekoop R. Evidence supportive of a functional discrimination between photopic oscillatory potentials as revealed with cone and rod mediated retinopathies. Doc Ophthalmol 1998; 95:35–54.

27.Rousseau S, McKerral M, Lachapelle P. The i-wave: bridging flash and pattern electroretinography. EEG Clin Neurophysiol (suppl) 1996; 46:167–173.

28.Lachapelle P. A possible contribution of the optic nerve to the photopic oscillatory potentials. Clin Vision Sci 1990; 5:421–426.

29.Gouras P, Mackay CJ. Detecting early postchiasmatic visually evoked responses. Clin Vision Sci 1988; 3:119–124.

30.Dawson WW, Trick GL, Litzkow CA. Improved electrode for electroretinography. Invest Ophthalmol 1979; 18:988–991.

31.He´bert M, Vaegan, Lachapelle P. Reproducibility of ERG responses obtained with the DTL electrode. Vision Res 1999; 39:1069–1070.

32.Gouras P. Electroretinography: some basic principles. Invest Ophthalmol 1970; 9: 557–569.

33.Lachapelle P, Blain L. A new speculum electrode for electroretinography. J Neurosci Methods. 1990; 32:245–249.

34.Lachapelle P, Benoit J, Little JM, Lachapelle B. Recording the oscillatory potentials with the DTL electrode. Doc Ophthalmol 1993; 83:119–130.

35.Lachapelle P, Rufiange M, Dembinska O. A physiological basis for definition of the ISCEV ERG standard flash (SF) based on the photopic hill. Doc Ophthalmol 2001; 102:157–162.

36.Wali N, Leguire LE. The photopic hill: a new phenomenon of the light adapted electroretinogram. Doc Ophthalmol 1992; 80:335–342.

37.Lachapelle P, Benoit J, Blain L, Guite´ P, Roy MS. The oscillatory potentials in response to stimuli of photopic intensities delivered in dark-adaptation: an explanation for the conditioning flash effect. Vision Res 1990; 30:503–513.

38.Peachey NS, Alexander KR, Fishman GA. Rod and cone system contributions to oscillatory potentials: an explanation for the conditioning flash effect. Vision Res 1987; 27:859–866.

39.Rousseau S, Lachapelle P. Origin of the oscillatory potentials recorded at the onset of dark adaptation. Doc Ophthalmol 1999; 99:135–150.

40.Naka KI, Rushton WAH. S-potentials from colour units in the retina of fish (cyprinidae). J Physiol 1966; 185:536–555.

41.He´bert M, Lachapelle P, Dumont M. Reproducibility of Naka-Rushton parameters derived from electroretinograms recorded with DTL electrodes. Doc Ophthalmol 1996; 91:333–342.

42.Nagata M. Studies on the photopic ERG of the human retina. Jpn J Ophthalmol 1963; 7:96–124.

43.Seiple W, Holopigian K. The OFF response of the human electroretinogram does not contribute to the brief flash b-wave. Vis Neurosci 1994; 11:667–673.

44.Gouras P, Mackay CJ, Ivert L, Mittl RN, Neuwirth J, Eggers H. Computer-assisted spectral electroretinography in vitrectomy patients. Ophthalmology 1985; 92:83– 90.

45.Weleber RG. The effect of age on the human cone and rod ganzfeld electroretinogram. Invest Ophthalmol Vis Sci 1981; 20:392–399.

46.Birch DG, Berson EL, Sanberg MA. Diurnal rhythm in the human rod ERG. Invest Ophthalmol Vis Sci 1984; 25:236–238.

47.Maffei L, Fiorentini A, Bisti S, Holla¨nder H. Pattern ERG in the monkey after section of the optic nerve. Exp Brain Res 1985; 59:423–425.

48.Hood DC. Assessing retinal function with the multifocal technique. Prog Retinal Eye Res 2000; 19:607–46.

49.Sutter EE, Tran D. The field topography of ERG component in man-I. The photopic luminance response. Vision Res 1992; 32:433–466.

50.Curcio CA, Sloan Jr. KR, Kalina RE, Hendrickson AE. Human photoreceptor topography. J Comp Neurol 1990; 292:497–523.

51.Sutter E. The interpretation of multifocal binary kernels. Doc Ophthalmol 2000; 100:49–75.

* obviously best test

1–4: Ranking best test to worst test ? not yet known

their ability to detect the small changes in visual outcome that are expected in these trials. I will review the advantages and disadvantages of each test (summarized in Table 1) and highlight areas of research needed to correct the disadvantages.

II. CANDIDATE VISUAL FUNCTION TESTS

Measures of visual function include electrophysiology, visual acuity, and various other psychophysical measures targeted at peripheral retina. Electrophysiological measures, although promising [2–4], still need modification and continued study to determine if they will be useful for detecting the subtle changes over time required for assessing neuroprotection. In addition, the commercially available

testing equipment (VERIS, Tomey, Nagoya, Japan) is not currently present in many of the centers and offices participating in the clinical trials.

Visual acuity may be a useful outcome measure for studies of macular degeneration or optic neuropathies that affect foveal function, but it is not the measure of choice for primary open angle glaucoma because the central macula is spared until the later stages of the disease. Currently, perimetry remains the measure of choice for studies of glaucoma progression. This review will discuss the rationale for different perimetric techniques and the potential for following change in clinical trials of neuroprotection. The focus will be on commercially available tests with standardized procedures. The advantages and disadvantages of each are summarized in Table 1.

Ganglion cells and their axons, which form the optic nerve, are the primary sites of damage due to glaucoma. There are roughly 1.25 million ganglion cells in the human retina with a minimum of 22 subtypes [5]. The three major ganglion cell types—magnocellular, parvocellular, and small-bistratified—compose up to 90% of all retinal ganglion cells in macaque and human eyes. Each of the three ganglion cell types has distinctive features that have been used in devising tests to detect and follow loss of vision due to glaucoma (Fig. 1). In addition, the morphological differences among these three cell types may indicate that one type is more amenable to neuroprotection than another, and appropriate measures of each subtype could be crucial to determining if this is the case.

A. Psychophysical Tests of Peripheral Visual Field

1. Standard Achromatic Automated Perimetry

Standard achromatic automated perimetry (SAP) is the most commonly used version of perimetry for clinical diagnosis as well as in clinical trials. SAP utilizes a small (0.47°) 200 ms flash of white light as the target presented on a dim background (10 cd/m2 or 31.5 asb). The target is randomly presented to several locations (54 in program 24-2 and 76 in program 30-2) using a Humphrey Visual Field Analyzer II (Humphrey Instruments, Dublin, CA). Similar test patterns are available on Octopus perimeters (Interzeag AG, Zurich, Switzerland). Results in this section will focus on those obtained with the Humphrey unit.

While a virtual congruence between visual field damage and loss of optic nerve fibers has been assumed, significant damage to the ganglion cells may occur before the disease can be recognized by visual field abnormalities [6,7]. By the time visual field loss is initially detected by Goldmann kinetic perimetry, 40% to 50% of retinal ganglion cells may have suffered irreversible damage [6]. Before SAP first demonstrates abnormalities, 20 to 40% of ganglion cells may be lost [8,9]. These findings spurred several studies designed to find more sensitive measures of vision loss, measures that target specific subtypes of retinal ganglion cells.

Figure 1 An oversimplified schematic depicting the separation of visual pathways serving different visual functions from cones through to the LGN. Cones are depicted by triangles at the top. Their inputs are combined at the retinal ganglion cell level to form the blue-yellow opponent on ganglion cell (small bistratified), the redgreen opponent ganglion cell (midget), which also handles high resolution tasks, and the achromatic black-white opponent cells (parasol). The axons from each type of ganglion cell project to a different region in the lateral geniculate nucleus (LGN) and that is how they get their other names, koniocellular ganglion cell, parvocellular ganglion cells, and magnocellular ganglion cells. The visual functions preferred by each ganglion cell are listed at the bottom of each pathway. Each pathway can handle other visual functions, but not as efficiently as it does those listed beneath it.

It can be argued that SAP is nonspecific for ganglion cell type, and detection of a white flash of light can be mediated through many types of retinal ganglion cells. This allows a redundancy at a given retinal location. Meaning if one type of ganglion cell is damaged, but the others are not, the signal can still be detected. Each of the tests described below, on the other hand, attempts to evaluate one type of visual function as a surrogate for isolating a specific ganglion cell subtype (see Fig. 1). If successful, this means that when the subtype of ganglion cell under test is damaged, the other subtypes can not easily detect the target. This has been referred to as reduced redundancy [10,11].

2. Short-Wavelength Automated Perimetry

Short-wavelength automated perimetry (SWAP) is a modification of SAP available on the Humphrey visual field analyzer and the Octopus perimeter utilizing the same test programs as SAP [12]. SWAP utilizes a 440 nm, narrow band, 1.8° target at 200 ms duration on a bright 100 cd/m2 yellow background to selectively test the short-wavelength sensitive pathway. The test provides a dynamic range of approximately 35 dB and 15 dB of isolation before the next most sensitive mechanism can detect the target, most likely the middle-wavelength sensitive pathway [12,13].

At the ganglion cell level, the patient’s response to this test is mediated by the small bistratified blue-yellow ganglion cells. Their dendritic field size, soma size, and axon size are slightly smaller than that of the magnocellular cells in humans [14]. Small bistratified ganglion cells are fewer in number and compose 6–10% of ganglion cells in peripheral retina [14]. The small bistratified cells receive their input from the blue-cone bipolar cells [15]. These cells respond in a sustained manner and have blue-yellow color opponency. They prefer shortwavelength stimuli, which are stressed in SWAP by adapting rods and the other two cone inputs using the bright yellow background. The key word here is “prefer.” For example, ganglion cells that prefer high temporal frequencies can respond to lower temporal frequencies under certain stimulus conditions, but their maximal response will be in the higher temporal frequency range and they will be more sensitive than the other ganglion cell types to these stimuli.

SWAP has more than 13 years of longitudinal evaluation and has been shown by several independent studies to be a more effective test than SAP for early detection of glaucoma-related field loss [16–18]. SWAP also identifies progression 1–3 years prior to detection by standard visual fields [19–21], and works well in advanced cases not complicated by the presence of cataracts [22]. Although SWAP has higher test-retest variability than SAP, and more than is desirable for long-term follow-up for progression of glaucomatous vision loss [23, 24], it has consistently been shown superior to SAP for identifying progression [20,21].

3. High-Pass Resolution Perimetry

It was originally thought that SWAP was testing blue-yellow ganglion cells that pass through the parvocellular pathways of vision. Since SWAP was developed, it has been determined that the blue-yellow ganglion cells responsible for processing the stimuli of SWAP are most likely not parvocellular, but are the small bistratified ganglion cells whose axons project to the interlaminar layers of the lateral geniculate nucleus of the thalamus [14,25–27]. Parvocellular ganglion cells are the most numerous, making up about 70% of the total. These cells are

also referred to as midget ganglion cells. These cells are distributed throughout the retina, and they have the smallest cell bodies, axons, and dendritic field sizes of the three types [14]. These cells handle acuity and resolution tasks. They prefer stimuli with low temporal frequencies and high spatial frequencies, along with color [28].

If we wish to include a test more likely to be detected by the parvocellular pathway, we can look to High-Pass Resolution Perimetry. This test is a resolution task. High-pass resolution visual fields were developed by Lars Frisen, M.D., and are tested using the Ophthimus High-Pass Resolution Perimeter (HighTech Vision, Malmo¨, Sweden) [29]. The test presents spatially filtered rings across 50 test locations in a 30° visual field. Fourteen different ring step sizes are used, with the smallest subtending 0.8° visual angle and each successive larger ring size spaced 0.1 log units apart. Thresholds are designated as the smallest ring size that can be resolved by the patient. The ring targets consist of a dark border (15 cd/m2) surrounding a light core (25 cd/m2) and are designed such that the space-average luminance across the ring target is equiluminant with the background of the display (20 cd/m2). In this manner, resolution rather than detection thresholds are measured and the target is both seen and resolved instantaneously or not seen at all.

High-Pass Resolution Perimetry was found to be comparable to standard fields for detecting vision loss [30] and superior for identifying change over time [31]. It is a very patient-friendly test, taking about 5 min and giving feedback for correct responses. The major drawback to its acceptance is the lack of standardization across test units.

4. Frequency-Doubling Technology Perimetry

Frequency-doubling technology perimetry (FDT) [32,33] is based on the fre- quency-doubling illusion [34,35], which occurs when viewing a counterphased grating with a low spatial frequency and a high temporal rate. Above threshold, the percept is double the spatial frequency of the actual physical grating [35]. This illusion has been attributed to a subset of the magnocellular ganglion cells, which are nonlinear in their response properties [36].

Magnocellular ganglion cells are fewer in number and compose about 8– 10% of the ganglion cell population. These cells are also referred to as parasol ganglion cells. These cells are distributed across the retina, and compared to the parvocellular cells they have larger cell bodies, axons, and dendritic field sizes with consequently larger receptive field center sizes. The magnocellular cells’ axons project to the magnocellular layers of the lateral geniculate nucleus [37]. They respond in a transient fashion to visual stimulation, and their axons have a relatively faster conduction velocity compared to the other two cell types [38– 41]. These cells prefer stimuli with high temporal frequencies, low spatial fre-

quencies, and motion. There is some debate about whether FDT at threshold is measuring a small subset of nonlinear magnocellular cells (estimated at about 3% of the ganglion cells), or if the target is more likely detectable due to its flicker component [42–44] by the full complement of magnocellular cells (still only about 10% of the population). At threshold, the percept is not always of a grating, either perceptually doubled or veridical, but sometimes is described as a “shimmering” or “flickering” [45,46]. Either way, early evidence has shown the test is sensitive to early glaucomatous defects and correlates well with SAP for mean defect [32,47–51].

Frequency-doubling perimetry is measured with a new instrument, the Humphrey FDT Visual Field Instrument using Welch-Allyn Frequency doubling technology (Skaneateles Falls, NY). The targets consist of a 0.25 cycle per degree sinusoidal grating that undergoes 25 Hz counterphase flicker. The test uses a modified binary search staircase threshold procedure to measure the contrast needed for detection of the stimulus. Each grating target is a square subtending about 10° in diameter. Targets are presented in one of 17 test areas located within the central 20° radius of visual field (program C-20). With a shift in fixation point location, the range can be extended to 30° and two additional locations in the nasal step area (program N-30).

FDT has some advantages over SAP and SWAP. The test time is about one-half of the time required for a full threshold 24-2 field, primarily due to the smaller number of test locations used. The results are less affected by blur, pupil size differences if always greater than 2 mm diameter, or bifocal correction [52], and it has lower test-retest variability than SAP [53]. It is similar to SAP and SWAP in that statistical analysis packages can be developed to give global indices, such as MD and PSD, and pattern deviation probability plots can be derived. The major drawback to FDT for clinical trials that look for change over time is that it is too new to have longitudinal data. We do not yet know if the small number of test locations will provide sufficient resolution for following change over time. Johnson and colleagues are currently working on a modification of the test to increase the number of test targets [54]. While this may improve the test ability to detect change over time, it will also increase the test time.

The advantages and disadvantages of each test are summarized in Table 1. If a test is obviously the best, an asterisk denotes it. For example, SAP has the most extensive normative database and FDT is least affected by changes in pupil size. If the tests could be ranked, they are ranked from best (1) to worst

(4). For example, SWAP has been found more useful than SAP for a variety of eye diseases but it is most affected by lens opacities. If we do not yet know something it is indicated by a ?. For example, we do not know if FDT will be good for following change over time because it is too new for extensive longitudinal studies.

These advantages and disadvantages have had some influence on whether