- •PROGRESS IN BRAIN RESEARCH
- •List of Contributors
- •Preface
- •Epidemiology of primary glaucoma: prevalence, incidence, and blinding effects
- •Introduction
- •Prevalence of glaucoma
- •PAC suspect
- •PACG
- •Incidence of glaucoma
- •Blinding effects of glaucoma
- •Abbreviations
- •Acknowledgment
- •References
- •Predictive models to estimate the risk of glaucoma development and progression
- •Risk assessment in ocular hypertension and glaucoma
- •Risk factors for glaucoma development
- •Intraocular pressure
- •Corneal thickness
- •Cup/disc ratio and pattern standard deviation
- •The need for predictive models
- •Predictive models for glaucoma development
- •Predictive models for glaucoma progression
- •Limitations of predictive models
- •References
- •Intraocular pressure and central corneal thickness
- •Main text
- •References
- •Angle-closure: risk factors, diagnosis and treatment
- •Introduction
- •Mechanism
- •Other causes of angle closure
- •Risk factors
- •Age and gender
- •Ethnicity
- •Ocular biometry
- •Genetics
- •Diagnosis
- •Acute primary angle closure
- •Angle assessment in angle closure
- •Gonioscopy technique
- •Ultrasound biomicroscopy (UBM)
- •Scanning peripheral anterior chamber depth analyzer (SPAC)
- •Management
- •Acute primary angle closure
- •Medical therapy
- •Argon laser peripheral iridoplasty (ALPI)
- •Laser peripheral iridotomy (PI)
- •Lens extraction
- •Monitoring for subsequent IOP rise in eyes with APAC
- •Fellow eye of APAC
- •Chronic primary angle-closure glaucoma (CACG)
- •Laser peripheral iridotomy
- •Laser iridoplasty
- •Medical therapy
- •Trabeculectomy
- •Lens extraction
- •Combined lens extraction and trabeculectomy surgery
- •Goniosynechialysis
- •Summary
- •List of abbreviations
- •References
- •Early diagnosis in glaucoma
- •Introduction
- •History and examination
- •Quantitative tests and the diagnostic process
- •Pretest probability
- •Test validity
- •Diagnostic test performance
- •Posttest probability
- •Combing test results
- •Selective tests of visual function
- •Early glaucoma diagnosis from quantitative test results
- •Progression to make a diagnosis
- •Conclusions
- •Abbreviations
- •References
- •Monitoring glaucoma progression
- •Introduction
- •Monitoring structural damage progression
- •Monitoring functional damage progression
- •Abbreviations
- •References
- •Standard automated perimetry and algorithms for monitoring glaucoma progression
- •Standard automated perimetry
- •Global indices
- •HFA: MD, SF, PSD, CPSD
- •Octopus indices: MD, SF, CLV
- •OCTOPUS seven-in-one report (Fig. 2)
- •SAP VF assessment: full-threshold strategy
- •SAP VF defects assessment: OHTS criteria
- •SAP VF defects assessment: AGIS criteria
- •SAP VF defects assessment: CIGTS
- •Fastpac
- •Swedish interactive threshold algorithm
- •SAP VF assessment: the glaucoma staging system
- •SAP: interocular asymmetries in OHTS
- •SAP, VF progression
- •SAP: the relationship to other functional and structural diagnostic tests in glaucoma
- •SAP, FDP-Matrix
- •SAP, SWAP, HPRP, FDT
- •SAP: the relationship between function and structure
- •SAP, confocal scanning laser ophthalmoscopy, SLP-VCC
- •SAP, optical coherence tomography
- •SAP and functional magnetic resonance imaging
- •References
- •Introduction
- •Retinal ganglion cells: anatomy and function
- •Is glaucoma damage selective for any subgroup of RGCs?
- •Segregation
- •Isolation
- •FDT: rationale and perimetric techniques
- •SWAP: rationale and perimetric techniques
- •FDT: clinical data
- •SWAP: clinical data
- •Clinical data comparing FDT and SWAP
- •Conclusions
- •References
- •Scanning laser polarimetry and confocal scanning laser ophthalmoscopy: technical notes on their use in glaucoma
- •The GDx scanning laser polarimeter
- •Serial analysis
- •Limits
- •The Heidelberg retinal tomograph
- •Limits
- •Conclusions
- •References
- •The role of OCT in glaucoma management
- •Introduction
- •How OCT works
- •How OCT is performed
- •Evaluation of RNFL thickness
- •Evaluation of optic disc
- •OCT in glaucoma management
- •New perspective
- •Abbreviations
- •References
- •Introduction
- •Technology
- •Visual stimulation
- •Reproducibility and habituation of RFonh
- •Retinal neural activity as assessed from the electroretinogram (ERG)
- •The Parvo (P)- and Magno (M)-cellular pathways
- •Physiology
- •Magnitude and time course of RFonh in humans
- •Varying the parameters of the stimulus on RFonh
- •Luminance versus chromatic modulation
- •Frequency
- •Effect of pattern stimulation
- •Neurovascular coupling in humans
- •Clinical application
- •RFonh in OHT and glaucoma patients
- •Discussion
- •FLDF and neurovascular coupling in humans
- •Comments on clinical application of FLDF in glaucoma
- •Conclusions and futures directions
- •Acknowledgements
- •References
- •Advances in neuroimaging of the visual pathways and their use in glaucoma
- •Introduction
- •Conventional MR imaging and the visual pathways
- •Diffusion MR imaging
- •Functional MR imaging
- •Proton MR spectroscopy
- •References
- •Primary open angle glaucoma: an overview on medical therapy
- •Introduction
- •When to treat
- •Whom to treat
- •Genetics
- •Race
- •Ocular and systemic abnormalities
- •Tonometry and pachymetry
- •How to treat
- •Beta-blockers
- •Prostaglandins
- •Alpha-agonists
- •Carbonic anhydrase inhibitors (CAIs)
- •Myotics
- •Fixed combinations
- •References
- •The treatment of normal-tension glaucoma
- •Introduction
- •Epidemiology
- •Clinical features
- •Optic disk
- •Central corneal thickness
- •Disease course
- •Risk factors
- •Intraocular pressure
- •Local vascular factors
- •Immune mechanisms
- •Differential diagnosis
- •Diagnostic evaluation
- •Therapy
- •IOP reduction
- •Systemic medications
- •Neuroprotection
- •Noncompliance
- •Genetics of NTG
- •Abbreviations
- •References
- •The management of exfoliative glaucoma
- •Introduction
- •Epidemiology
- •Ocular and systemic associations
- •Ocular associations
- •Systemic associations
- •Pathogenesis of exfoliation syndrome
- •Mechanisms of glaucoma development
- •Management
- •Medical therapy
- •Laser surgery
- •Operative surgery
- •Future treatment of exfoliation syndrome and exfoliative glaucoma
- •Treatment directed at exfoliation material
- •References
- •Laser therapies for glaucoma: new frontiers
- •Background
- •Laser iridotomy
- •Indications
- •Contraindications
- •Patient preparation
- •Technique
- •Nd:YAG laser iridectomy
- •Argon laser iridectomy
- •Complications
- •LASER trabeculoplasty
- •Treatment technique
- •Mechanism of action
- •Indications for treatment
- •Contraindications to treatment
- •Patient preparation and postoperative follow-up
- •Complications of the treatment
- •Selective laser trabeculoplasty
- •Results
- •LASER iridoplasty
- •Indications
- •Contraindications
- •Treatment technique
- •Complications
- •LASER cyclophotocoagulation
- •Introduction
- •Indications and contraindications
- •Patient preparation
- •Transpupillary cyclophotocoagulation
- •Endoscopic cyclophotocoagulation
- •Transscleral cyclophotocoagulation
- •Transscleral noncontact cyclophotocoagulation
- •Transscleral contact cyclophotocoagulation
- •Complications
- •Excimer laser trabeculotomy
- •References
- •Modulation of wound healing during and after glaucoma surgery
- •The process of wound healing
- •Using surgical and anatomical principles to modify therapy
- •Growth factors
- •Cellular proliferation and vascularization
- •Cell motility, matrix contraction and synthesis
- •Drug delivery
- •Future directions: total scarring control and tissue regeneration
- •Acknowledgments
- •References
- •Surgical alternative to trabeculectomy
- •Introduction
- •Deep sclerectomy
- •Viscocanalostomy
- •Conclusions
- •References
- •Modern aqueous shunt implantation: future challenges
- •Background
- •Current shunts and factors affecting their function
- •Shunt-related factors
- •Surface area
- •Plate material
- •Valved versus non-valved
- •Commercially available devices
- •Comparative studies
- •Patient and ocular factors
- •Severity of glaucoma damage
- •Tolerance of topical ocular hypotensive medications
- •Aqueous hyposecretion
- •Previous ocular surgery
- •Scleral thinning
- •Patient cooperation for and tolerance of potential slit-lamp interventions
- •Future challenges
- •Predictability
- •Cataract formation
- •The long-term effect on the cornea
- •References
- •Model systems for experimental studies: retinal ganglion cells in culture
- •Mixed RGCs in culture
- •Retinal explants
- •Glial cultures
- •RGC-5 cells
- •Differentiation of RGC-5 cells
- •RGC-5 cell neurites
- •Advantages and disadvantages of culture models
- •References
- •Rat models for glaucoma research
- •Rat models for glaucoma research
- •Use of animal models for POAG
- •Suitability of the rat for models of optic nerve damage in POAG
- •Methods for measuring IOP in rats
- •General considerations for measuring IOP in rats
- •Assessing optic nerve and retina damage
- •Experimental methods of producing elevated IOP
- •Laser treatment of limbal tissues
- •Episcleral vein cautery
- •Conclusions
- •Abbreviations
- •Acknowledgements
- •References
- •Mouse genetic models: an ideal system for understanding glaucomatous neurodegeneration and neuroprotection
- •Introduction
- •The mouse as a model system
- •Mice are suitable models for studying IOP elevation in glaucoma
- •Tools for glaucoma research
- •Accurate IOP measurements are fundamental to the study of glaucoma
- •The future of IOP assessment
- •Assessment of RGC function
- •Mouse models of glaucoma
- •Primary open-angle glaucoma
- •MYOC
- •OPTN
- •Strategies for developing new models of POAG
- •Developmental glaucoma
- •Pigmentary glaucoma
- •Experimentally induced models of glaucoma
- •Mouse models to characterize processes involved in glaucomatous neurodegeneration
- •Similar patterns of glaucomatous damage occur in humans and mice
- •The lamina cribrosa is an important site of early glaucomatous damage
- •An insult occurs to the axons of RGCs within the lamina in glaucoma
- •What is the nature of the insult at the lamina?
- •Other changes occur in the retina in glaucoma
- •PERG and complement
- •Using mouse models to develop neuroprotective strategies
- •Somal protection
- •Axonal protection
- •Erythropoietin administration
- •Radiation-based treatment
- •References
- •Clinical trials in neuroprotection
- •Introduction
- •Methods of clinical studies
- •Issues in the design and conduct of clinical trials
- •Clinical trials of neuroprotection
- •Clinical trials of neuroprotection in ophthalmology
- •Endpoints
- •Neuroprotection and glaucoma
- •Conclusions
- •Abbreviations
- •References
- •Pathogenesis of ganglion ‘‘cell death’’ in glaucoma and neuroprotection: focus on ganglion cell axonal mitochondria
- •Introduction
- •Retinal ganglion cells and mitochondria
- •Possible causes for ganglion cell death in glaucoma
- •Mitochondrial functions and apoptosis
- •Mitochondrial function enhancement and the attenuation of ganglion cell death
- •Creatine
- •Nicotinamide
- •Epigallocatechin gallate
- •Conclusion
- •References
- •Astrocytes in glaucomatous optic neuropathy
- •Introduction
- •Quiescent astrocytes
- •Reactive astrocytes in glaucoma
- •Signal transduction in glaucomatous astrocytes
- •Protein tyrosine kinases (PTKs)
- •Serine/threonine protein mitogen-activated kinases (MAPKs)
- •G protein-coupled receptors
- •Ras superfamily of small G proteins
- •Astrocyte migration in the glaucomatous optic nerve head
- •Cell adhesion of ONH astrocytes
- •Connective tissue changes in the glaucomatous optic nerve head
- •Extracellular matrix synthesis by ONH astrocytes
- •Extracellular matrix degradation by reactive astrocytes
- •Oxidative stress in ONH astrocytes
- •Conclusions
- •Acknowledgments
- •References
- •Glaucoma as a neuropathy amenable to neuroprotection and immune manipulation
- •Glaucoma as a neurodegenerative disease
- •Oxidative stress and free radicals
- •Excessive glutamate, increased calcium levels, and excitotoxicity
- •Deprivation of neurotrophins and growth factors
- •Abnormal accumulation of proteins
- •Pharmacological neuroprotection for glaucoma
- •Protection of the retinal ganglion cells involves the immune system
- •Searching for an antigen for potential glaucoma therapy
- •Concluding remarks
- •References
- •Oxidative stress and glaucoma: injury in the anterior segment of the eye
- •Introduction
- •Oxidative stress
- •Trabecular meshwork
- •IOP increase and free radicals
- •Glaucomatous cascade
- •Nitric oxide and endothelins
- •Extracellular matrix
- •Metalloproteinases
- •Other factors of interest
- •Therapeutic and preventive substances of interest in glaucoma
- •Ginkgo biloba extract
- •Green tea
- •Ginseng
- •Memantine and its derivates
- •Conclusions
- •Abbreviations
- •References
- •Conclusions on neuroprotective treatment targets in glaucoma
- •Acknowledgments
- •References
- •Involvement of the Bcl2 gene family in the signaling and control of retinal ganglion cell death
- •Introduction
- •Intrinsic apoptosis vs. extrinsic apoptosis
- •The Bcl2 family of proteins
- •The requirement of BAX for RGC soma death
- •BH3-only proteins and the early signaling of ganglion cell apoptosis
- •Conclusion
- •Abbreviations
- •Acknowledgments
- •References
- •Assessment of neuroprotection in the retina with DARC
- •Introduction
- •DARC
- •Introducing the DARC technique
- •Annexin 5-labeled apoptosis and ophthalmoloscopy
- •Detection of RGC apoptosis in glaucoma-related animal models with DARC
- •Assessment of glutamate modulation with DARC
- •Glutamate at synaptic endings
- •Glutamate excitotoxicity in glaucoma
- •Assessment of coenzyme Q10 in glaucoma-related models with DARC
- •Summary
- •Abbreviations
- •Acknowledgment
- •References
- •Potential roles of (endo)cannabinoids in the treatment of glaucoma: from intraocular pressure control to neuroprotection
- •Introduction
- •The endocannabinoid system in the eye
- •The IOP-lowering effects of endocannabinoids
- •Endocannabinoids and neuroprotection
- •Conclusions
- •References
- •Glaucoma of the brain: a disease model for the study of transsynaptic neural degeneration
- •Retinal ganglion cells, retino-geniculate neurons
- •Lateral geniculate nucleus
- •Mechanisms of RGC injury in glaucoma
- •Transsynaptic degeneration of the lateral geniculate nucleus in glaucoma
- •Neural degeneration in magno-, parvo-, and koniocellular LGN layers
- •Visual cortex in glaucoma
- •Neuropathology of glaucoma in the visual pathways in the human brain
- •Mechanisms of glaucoma damage in the central visual pathways
- •Implications of central visual system injury in glaucoma
- •Conclusion
- •Acknowledgments
- •References
- •Clinical relevance of optic neuropathy
- •Is there a remodeling of retinal circuitry?
- •Behavioral consequences of glaucoma
- •Glaucoma as a neurodegenerative disease versus neuroplasticity and adaptive changes
- •Future directions
- •Acknowledgment
- •References
- •Targeting excitotoxic/free radical signaling pathways for therapeutic intervention in glaucoma
- •Introduction
- •Channel properties of NMDA receptors correlated with excitotoxicity
- •Downstream signaling cascades after overactivation of NMDA receptors
- •Relevance of excitotoxicity to glaucoma
- •Therapeutic approaches to prevent RGC death by targeting the pathways involved in NMDA excitotoxicity
- •Drugs targeting NMDA receptors
- •Kinetics of NMDA receptor antagonists
- •Memantine
- •NitroMemantines
- •Drugs targeting downstream signaling molecules in NMDA-induced cell death pathways
- •p38 MAPK inhibitors
- •Averting caspase-mediated neurodegeneration
- •Abbreviations
- •Acknowledgments
- •References
- •Stem cells for neuroprotection in glaucoma
- •Introduction
- •Glaucoma as a model of neurodegenerative disease
- •Why use stem cells for neuroprotective therapy?
- •Stem cell sources
- •Neuroprotection by transplanted stem cells
- •Endogenous stem cells
- •Key challenges
- •Conclusion
- •Abbreviations
- •Acknowledgments
- •References
- •The relationship between neurotrophic factors and CaMKII in the death and survival of retinal ganglion cells
- •Introduction
- •Glaucoma and the RGCs
- •Are other retinal cells affected in glaucoma?
- •Retinal ischemia related glaucoma
- •Excitotoxicity and the retina
- •Signal transduction
- •NMDA receptor antagonists and CaMKII
- •Caspase-3 activation in NMDA-induced retinal cell death and its inhibition by m-AIP
- •BDNF and neuroprotection of RGCs
- •Summary and conclusions
- •Abbreviations
- •Acknowledgments
- •References
- •Evidence of the neuroprotective role of citicoline in glaucoma patients
- •Introduction
- •Patients: selection and recruitment criteria
- •Pharmacological treatment protocol
- •Methodology of visual function evaluation: electrophysiological examinations
- •PERG recordings
- •VEP recordings
- •Statistic evaluation of electrophysiological results
- •Electrophysiological (PERG and VEP) responses in OAG patients after the second period of evaluation
- •Effects of citicoline on retinal function in glaucoma patients: neurophysiological implications
- •Effects of citicoline on neural conduction along the visual pathways in glaucoma patients: neurophysiological implications
- •Possibility of neuroprotective role of citicoline in glaucoma patients
- •Conclusive remarks
- •Abbreviations
- •References
- •Neuroprotection: VEGF, IL-6, and clusterin: the dark side of the moon
- •Neuroprotection: VEGF-A, a shared growth factor
- •VEGF-A isoforms
- •VEGF-A receptors
- •Angiogenesis, mitogenesis, and endothelial survival
- •Neurotrophic and neuroprotective effect
- •Intravitreal VEGF inhibition therapy and neuroretina toxicity
- •Neuroprotection: clusterin, a multifunctional protein
- •Clusterin/ApoJ: a debated physiological role
- •Clusterin and diseases
- •Clusterin and the nervous system
- •Neuroprotection: IL-6, VEGF, clusterin, and glaucoma
- •Rational basis for the development of coenzyme Q10 as a neurotherapeutic agent for retinal protection
- •Introduction
- •Ischemia model
- •Neuroprotective effect of Coenzyme Q10 against cell loss yielded by transient ischemia in the RGC layer
- •Retinal ischemia and glutamate
- •Coenzyme Q10 minimizes glutamate increase induced by ischemia/reperfusion
- •Summary
- •Acknowledgment
- •References
- •17beta-Estradiol prevents retinal ganglion cell loss induced by acute rise of intraocular pressure in rat
- •Methods
- •Morphometric analysis
- •Microdialysis
- •Drug application
- •Statistical analysis
- •Results
- •17beta-Estradiol pretreatment minimizes RGC loss
- •Discussion
- •Acknowledgment
finding differs from other results of previous studies. Furthermore, since in this study none test type was always affected in patients with glaucoma whereas the other test types remained normal, the authors suggest that a combination of test types may be most efficient in identifying early loss and confirming the region of optic pathways affected by glaucoma (Sakata et al., 2007a, b).
These findings seem to confirm a prominent clinical role of the SAP in the diagnosis and follow-up of glaucoma. Although a true gold standard for glaucoma diagnosis is still lacking, none of the newer test types can entirely replace SAP at this time.
SAP: the relationship between function and structure
Accurate measurement of both functional and structural changes is critical in both clinical practice and clinical trials to support the diagnosis of glaucoma, and also to follow up any progression of the disease over time.
The relationship between structure and function, however, is not entirely explained.
The relationship between structure, observed by different imaging techniques, like scanning laser polarimetry (SLP), and functions, assessed by SAP, has been investigated in various studies. With SLP with variable corneal compensation (VCC; commercially available in the GDx Nerve Fiber Analyzer; Carl Zeiss Meditec, Inc., Dublin, CA), the structure–function relationship has been shown to be curvilinear when VF sensitivity is expressed in a decibel scale.
Other studies showed that the relationship between function and structure is curvilinear for the correlations between decibel-DLS and both the number of ganglion cells and neuroretinal rim.
However, if VF differential light sensitivity is expressed in an antilog (1/Lambert) scale, function relates linearly to structure, as has been shown by Garway-Heath (Johnson et al., 2000; Harwerth et al., 2007).
On the other hand, both the OHTS and the EGPS showed that, in many eyes, structural defects develop before functional defects, whereas
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in a similar number of other eyes, functional defects develop first (with both kinds of defects developing in some eyes simultaneously). It is reasonable that diseased retinal ganglion cells begin to malfunction before dying: In this case, a decrease in differential light sensitivity can be measured without a detectable structural loss (Miglior et al., 2007).
These findings suggest that both the SAP VF and the optic disc must be monitored with equal attention, because either may show the first evidence of damage due to glaucoma. VF changes like an increase in PSD or evidence of a nasal step and/or partial arcuate defect and changes in the ONH based on stereo-photographic observation (i.e., a slight increase in C/D ratio or rim thinning) should be sought through repeat testing and correlation with other clinical results because they suggest an increased risk of developing glaucoma.
SAP, confocal scanning laser ophthalmoscopy, SLP-VCC
Retinal ganglion cell function assessed by SAP relates only slightly to measurements of neuroretinal rim area using confocal scanning laser ophthalmoscopy (CSLO) and of RNFL thickness using SLP-VCC. The curvilinearity of the relationship between function and structure is mainly due to the standard decibel scale in SAP, as previously reported (Racette et al., 2007).
On the other hand, measurements of neuroretinal rim area using CSLO compare well with measurements of RNFL thickness using SLP-VCC.
Nevertheless, a stronger structure–function relationship between RNFL retardation and SAP VF sensitivity has been found in images obtained with the GDx ECC than with the GDx VCC.
In other words, more accurate RNFL imaging may show a stronger correlation of structural imaging with SAP results (Mai et al., 2007).
SAP, optical coherence tomography
The relationship between RNFL thickness, as measured by optical coherence tomography (OCT),
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and VF sensitivity, as measured by SAP, has been evaluated in normal subjects and in patients with glaucoma. A strong curvilinear regression has been found in POAG eyes with PSD 1.9 dB and RNFL average thickness below 70 m, whereas no correlation was detectable above these values.
Other studies showed that SAP measures of VF defects and OCT measures of RNFL defects are correlated measures of glaucomatous neuropathy. They conclude that RNFL thickness may be a more sensitive measurement for early stages and perimetry a better measure for moderate- to-advanced stages of glaucoma (Ajtony et al., 2007).
Nevertheless, it has been stated that the fluctuation in thresholding of automated perimetry testing in advanced glaucoma is too large. For this reason, the magnitude of change required to have statistical confidence that the change is real often exceeds the dynamic range of the perimeter.
SAP and functional magnetic resonance imaging
A correlation between functional magnetic resonance imaging (fMRI) responses and measurements of optic disc damage for OCT (RNFL), HRT (mean height contour), and GDx (RNFL) has been recently demonstrated using a novel method for projecting VF scotomas onto the flattened cortical representation.
Cortical activity for viewing through the glaucomatous versus fellow eye was compared by alternately presenting each eye with a contrastreversing checkerboard pattern. The resultant fMRI response was then compared to interocular differences in RNFL or mean height contour for analogous regions of the VF.
Although indirectly, these findings suggest that the pattern of cortical activity in V1 may be correlated with the pattern of VF loss measured with SAP (Duncan et al., 2007).
Because perimetry is a psychophysical measure, the values of differential sensitivity obtained are not dependent on the functional architecture of the visual system alone but also on a variety of factors. Excessive pupillary constriction or dilatation,
improper refraction, lens rim artifact, and blepharoptosis, all affect luminance thresholds. Moreover, cognitive factors including learning effect, subject attention, fatigue, motivation, and response bias can influence the obtained thresholds. In addition, perimetrist’s instructions can significantly affect obtained automated perimetry thresholds (Kutzko et al., 2000).
Other authors suggest that, during perimetry, subjects who are distracted or anxious may produce VF alterations that are extremely similar to the typical nerve fiber bundle defects due to glaucoma.
SAP showed significant intertest variability in individual glaucoma patients and patients with high risk factors for developing glaucomatous damage. Therefore, it may be difficult to determine with statistical confidence whether SAP VF glaucomatous damage is present. It may be also hard to differentiate between true progression or fluctuation unless the test is repeated multiple times. Repeating the VF examination is a timeconsuming procedure not always accomplished in daily practice, despite the published evidence. A report by the American Academy of Ophthalmology (2002) on automated perimetry stated: ‘‘Although standard automated perimetry has become one of the most useful tools in the detection and management of glaucoma, there is lack of a true gold standard.’’
Despite these important caveats, recent findings validate the clinical role of SAP in glaucoma.
SAP results were correlated to structure of the visual system as measured by morphological techniques (CSLO, SLP, and OCT) and, with obvious limitations, to fMRI results.
Many other efforts are necessary to optimize SAP VF assessment: newer statistical methods, the use of MLC, and combining of SAP field data with structural data seem to be relevant ways to achieve this important result.
In particular, MLC are computational methods that enable machines to learn from experience. They were effective in VF interpretation, identification of patterns of VF loss, diagnosis of glaucoma through structural measures, and detection of progression of glaucoma. According to Bowd et al. (2008), combining OCT and SAP
measurements of healthy and early glaucomatous eyes using two types of MLC increased diagnostic performance in glaucoma is obtained.
MLC, newer thresholding algorithms strategies, more sophisticated statistic software, and better fixation monitoring seem to be promising tools in order to improve precision and accuracy of this well-known and widespread diffused method of examination in glaucoma management.
References
Ajtony, C., Balla, Z., Somoskeoy, S. and Kovacs, B. (2007) Relationship between visual field sensitivity and retinal nerve fiber layer thickness as measured by optical coherence tomography. Invest. Ophthalmol. Vis. Sci., 48(1): 258–263.
Anderson, D.R. and Patella, V.M. (1999) Automated Static Perimetry (2nd edn.). Mosby, St. Louis.
Anderson, D.R., Chauhan, B., Johnson, C., Katz, J., Patella, V.M. and Drance, S.M. (2000) Criteria for progression of glaucoma in clinical management and in outcome studies. Am. J. Ophthalmol., 130: 827–829.
Artes, P.H., Hutchison, D.M., Nicolela, M.T., LeBlanc, R.P. and Chauhan, B.C. (2005a) Threshold and variability properties of matrix frequency-doubling technology and standard automated perimetry in glaucoma. Invest. Ophthalmol. Vis. Sci., 46(7): 2451–2457.
Artes, P.H., Nicolela, M.T., LeBlanc, R.P. and Chauhan, B.C. (2005b) Visual field progression in glaucoma: total versus pattern deviation analyses. Invest. Ophthalmol. Vis. Sci., 46: 4600–4606.
Barkana, Y., Gerber, Y., Mora, R., Liebmann, J.M. and Ritch, R. (2006) Effect of eye testing order on automated perimetry results using the Swedish interactive threshold algorithm standard 24-2. Arch. Ophthalmol., 124(6): 781–784.
Bowd, C., Hao, J., Tavares, I.M., Medeiros, F.A., Zangwill, L.M., Lee, T.W., Sample, P.A., Weinreb, R.N. and Goldbaum, M.H. (2008) Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyes. Invest. Ophthalmol. Vis. Sci., 49: 945–953.
Brusini, P. and Filacorda, S. (2006) Enhanced glaucoma staging system (GSS2) for classifying functional damage in glaucoma. J. Glaucoma, 15: 40–46.
Delgado, M.F., Nguyen, N.T., Cox, T.A., Singh, K., Lee, D.A., Dueker, D.K., Fechtner, R.D., Juzych, M.S., Lin, S.C., Netland, P.A., Pastor, S.A., Schuman, J.S. and Samples, J.R.American Academy of Ophthalmology. Ophthalmic Technology Assessment Committee 2001–2002 Glaucoma Panel. (2002) Automated perimetry: a report by the American Academy of Ophthalmology. Ophthalmology, 109(12): 2362–2374.
Duncan, R.O., Sample, P.A., Weinreb, R.N., Bowd, C. and Zangwill, L.M. (2007) Retinotopic organization of primary
97
visual cortex in glaucoma: a method for comparing cortical function with damage to the optic disk. Invest. Ophthalmol. Vis. Sci., 48(2): 733–744.
European Glaucoma Prevention Study (EGPS) Group. (2002) The European Glaucoma Prevention Study: design and baseline description of the participants. Ophthalmology, 109: 1612–1621.
Ferreras, A., Polo, V., Larrosa, J.M., Pablo, L.E., Pajarin, A.B., Pueyo, V. and Honrubia, F.M. (2007) Can frequencydoubling technology and short-wavelength automated perimetries detect visual field defects before standard automated perimetry in patients with preperimetric glaucoma? J. Glaucoma, 16(4): 372–383.
Fitzke, F.W., Hitchings, R.A., Poinoosawmy, D., McNaught, A.I. and Crabb, D.P. (1996) Analysis of visual field progression in glaucoma. Br. J. Ophthalmol., 80: 40–48.
Flammer, J. (1986) The concept of visual field indices. Graefes Arch. Clin. Exp. Ophthalmol., 224(5): 389–392.
Flammer, J., Drance, S.M. and Zulauf, M. (1984) Differential light threshold, shortand long-term fluctuation in patients with glaucoma, normal controls, and patients with suspected glaucoma. Arch. Ophthalmol., 102: 704–706.
Gordon, M.O. and Kass, M.A. (1999) Ocular hypertension treatment study group. The ocular hypertension treatment study: design and baseline description of the participants. Arch. Ophthalmol., 117: 573–583.
Hall, T.A. and Owsley, C. (2005) Visual field defects and the risk of motor vehicle collisions among patients with glaucoma. Invest. Ophthalmol. Vis. Sci., 46: 4437–4441.
Harwerth, R.S., Vilupuru, A.S., Rangaswamy, N.V. and Smith III, E.L. (2007) The relationship between nerve fiber layer and perimetry measurements. Invest. Ophthalmol. Vis. Sci., 48: 763–773.
Haymes, S.A., Hutchison, D.M., McCormick, T.A., Varma, D.K., Nicolela, M.T., LeBlanc, R.P. and Chauhan, B.C. (2005) Glaucomatous visual field progression with frequencydoubling technology and standard automated perimetry in a longitudinal prospective study. Invest. Ophthalmol. Vis. Sci., 46(2): 547–554.
Heijl, A., Lindgren, G. and Lindgren, A. (1991) Extended empirical statistical package for evaluation of single and multiple fields: Statpac 2. In: Mills R.P. and Heijl A. (Eds.), Perimetry Update 1990/1991. Kugler and Ghedini, New York, pp. 303–315.
Heijl, A., Leske, M.C. and Bengtsson, B. (2002) Reduction of intraocular pressure and glaucoma progression: results from the Early Manifest Glaucoma Trial. Arch. Ophthalmol., 120: 1268–1279.
Heijl, A., Bengtsson, B., Chauhan, B.C., Lieberman, M.F., Cunliffe, I., Hyman, L., Leske, M.C. (2008) A comparison of visual field progression criteria of 3 major glaucoma trials in early manifest glaucoma trial patients. Ophthalmology, March, Epub ahead of print.
Hodapp, E., Parrish II, R.K. and Anderson, D.R. (1993) Clinical Decisions in Glaucoma. Mosby Company, St. Louis, pp. 98–114.
98
Hoffmann, E.M., Boden, C., Zangwill, L.M., Bourne, R.R., Weinreb, R.N. and Sample, P.A. (2006) Inter-eye comparison of patterns of visual field loss in patients with glaucomatous optic neuropathy. Am. J Ophthalmol., 141(4): 703–708.
Johnson, C.A., Cioffi, G.A., Liebmann, J.R., Sample, P.A., Zangwill, L.M. and Weinreb, R.N. (2000) The relationship between structural and functional alterations in glaucoma: a review. Semin. Ophthalmol., 15(4): 221–233.
Katz, J., Gilbert, D., Quigley, H.A. and Sommer, A. (1997) Estimating progression of visual field loss in glaucoma. Ophthalmology, 104: 1017–1025.
Kaufmann, H. and Flammer, J. (1989) The Bebie´ curve (cumulative defect curve) for differentiating local and diffuse visual field defects. Fortschr Ophthalmol., 86(6): 687–691.
Keltner, J.L., Johnson, C.A., Spurr, J.O. and Beck, R.W. (1993) Baseline visual field profile of optic neutris. The experience of the optic neuritis treatment trial. Optic Neurities Study Group. Arch Ophthalmol., 111(2): 231–234.
Kerrigan–Baumrind, L.A., Quigley, H.A., Pease, M.E., Kerrigan, D.F. and Mitchell, R.S. (2000) Number of ganglion cells in glaucoma eyes compared with threshold visual field tests in the same persons. Invest. Ophthalmol. Vis. Sci., 41: 741–748.
King, A.J.W., Taguri, A., Wadood, A.C. and Azuara-Blanco, A. (2002) Comparison of two fast strategies, SITA Fast and TOP, for the assessment of visual fields in glaucoma patients. Graefes Arch. Clin. Exp. Ophthalmol., 240: 481–487.
Kocak, I., Zulauf, M., Hendrickson, P. and Stumpfig, D. (1997) Evaluation of the Brusini Staging System for follow-up in glaucoma. Eur. J. Ophthalmol., 7: 345–350.
Kulze, J.C., Stewart, W.C. and Sutherland, S.E. (1990) Factors associated with a learning effect in glaucoma patients using automated perimetry. Acta Ophthalmol., 68: 681–686.
Kutzko, K.E., Brito, C.F. and Wall, M. (2000) Effect of instructions on conventional automated perimetry. Invest. Ophthalmol. Vis. Sci., 41: 2006–2013.
Leeprechanon, N., Giangiacomo, A., Fontana, H., Hoffman, D. and Caprioli, J. (2007) Frequency-doubling perimetry: comparison with standard automated perimetry to detect glaucoma. Am. J. Ophthalmol., 143(2): 263–271.
Levine, R. (2006) Asymmetries and visual field summaries as predictors of glaucoma in the ocular hypertension treatment study. Invest. Ophthalmol. Vis. Sci., 47: 3896–3903.
Lin, A.L., Hoffman, D., Gaasterland, D.E. and Caprioli, J. (2003) Neural networks to identify glaucomatous visual field progression. Am. J. Ophthalmol., 135: 49–54.
Mai, T.A., Reus, N.J. and Lemij, H.G. (2007) Structure– function relationship is stronger with enhanced corneal compensation than with variable corneal compensation in scanning laser polarimetry. Invest. Ophthalmol. Vis. Sci., 48(4): 1651–1658.
Marra, G. and Flammer, J. (1991) The learning and fatigue effect in automated perimetry. Graefes Arch. Clin. Exp. Ophthalmol., 229: 501–504.
McGwin, G., Jr., Xie, A., Mays, A., Joiner, W., DeCarlo, K.D., Newkirk, M.R., Gardiner, S.K., Demirel, S. and Johnson,
C.A. (2006) Assessment of false positives with the Humphrey Field Analyzer II Perimeter with the SITA algorithm. Invest. Ophthalmol. Vis. Sci., 47: 4632–4637.
Miglior, S., Torri, V., Zeyen, T., Pfeiffer, N., Vaz, J.C. and Adamsons, I.EGPS Group. (2007) Intercurrent factors associated with the development of open-angle glaucoma in the European glaucoma prevention study. Am. J. Ophthalmol., 144(2): 266–275.
Mikelberg, F.S. and Drance, S.M. (1984) The mode of progression of visual field defects in glaucoma. Am. J. Ophthalmol., 98: 443–445.
Musch, D.C., Lishter, P.R., Guire, K.E. and Standardi, C.L.CIGTS Study Group. (1999) The collaborative initial glaucoma treatment study. Ophthalmology, 106: 653–662.
Musch, D.C., Gillespie, B.W., Motyka, B.M., Niziol, L.M., Mills, R.P. and Lichter, P.R.on behalf of the CIGTS Study Group. (2005) Converting to SITA-standard from fullthreshold visual field testing in the follow-up phase of a clinical trial. Invest. Ophthalmol. Vis. Sci., 46: 2755–2759.
Nouri-Mahdavi, K., Brigatti, L., Weitzman, M. and Caprioli, J. (1997) Comparison of methods to detect visual field progression in glaucoma. Ophthalmology, 104: 1228–1236.
Park, H.J. and Youn, D.H. (1994) Quantitative analysis of changes of automated perimetric thresholds after pupillary dilation and induced myopia in normal subjects. Korean J. Ophthalmol., 8: 53–60.
Paetzold, H.A., Vonthein, R., Krapp, E., Rauscher, S. and Schiefer, U. (2007) Age-dependent normative values for differential luminance sensitivity in automated static perimetry using the Octopus 101. Acta Ophthalmol. Scand., 7.
Patel, A., Wollstein, G., Ishikawa, H. and Schuman, J.S. (2007) Comparison of visual field defects using matrix perimetry and standard achromatic perimetry. Ophthalmology, 114(3): 480–487.
Pierre-Filho, P.T., Schimiti, R.B., de Vasconcellos, J.P. and Costa, V.P. (2006) Sensitivity and specificity of frequencydoubling technology, tendency-oriented perimetry, SITA Standard and SITA Fast perimetry in perimetrically inexperienced individual. Acta Ophthalmol. Scand., 84(3): 345–350.
Racette, L., Medeiros, F.A., Bowd, C., Zangwill, L.M., Weinreb, R.N. and Sample, P.A. (2007) The impact of the perimetric measurement scale, sample composition, and statistical method on the structure-function relationship in glaucoma. J. Glaucoma, 16(8): 676–684.
Sakata, LM., Deleon-Ortega, J., Arthur, S.N., Monheit, B.E. and Girkin, C.A. (2007a) Detecting visual function abnormalities using the Swedish interactive threshold algorithm and matrix perimetry in eyes with glaucomatous appearance of the optic disc. Arch. Ophthalmol., 125(3): 340–345.
Sakata, L.M., DeLeo´n-Ortega, J. and Girkin, C.A. (2007b) Selective perimetry in glaucoma diagnosisCurr. Opin. Ophthalmol., 18(2): 115–121., Review.
Spry, P.G.D. and Johnson, C.A. (2002) Identification of progressive glaucomatous visual field loss. Surv. Ophthalmol., 47: 158–173.
The Advanced Glaucoma Intervention Study (AGIS): 1. (1994) Study design and methods and baseline characteristics of study patients. Control Clin. Trials, 15(4): 299–325.
Vesti, E., Johnson, C.A. and Chauhan, B.C. (2003) Comparison of different methods for detecting glaucomatous visual field progression. Invest. Ophthalmol. Vis. Sci., 44: 3873–3879.
Walsh, T.J. (1990) Visual Fields. Examination and Interpretation. American Academy of Ophthalmology, San Francisco.
Weber, J. and Caprioli, J. (2000) Atlas of Computerized Perimetry. WB Saunders Comp, Philadelphia, pp. 215–231.
99
Wild, J.M., Pacey, I.E., Hancock, S.A. and Cunliffe, I.A. (1999a) Between-algorithm, between-individual differences in normal perimetric sensitivity: full threshold, FASTPAC, and SITA Swedish Interactive Threshold algorithm. Invest. Ophthalmol. Vis. Sci., 40: 1152–1161.
Wild, J.M., Pacey, I.E., O’Neill, E.C. and Cunliffe, I.A. (1999b) The SITA perimetric threshold algorithms in glaucoma. Invest. Ophthalmol. Vis. Sci., 40: 1998–2009.
Zalta, A.H. (1989) Lens rim artifact in automated threshold perimetry. Ophthalmology, 96: 1302–1311.