Standard automated perimetry for glaucoma and diseases of the retina and visual pathways: Current and future perspectives.

Abstract

Static automated perimetry (SAP) remains a mainstay of functional assessment of the visual field in diseases of the visual pathway, such as glaucoma and age-related macular degeneration. The fundamental psychophysical task of responding to stimuli of different levels of contrast has remained minimally changed since its inception in the 1980s, and this is potentially the root of several unresolved issues involving the technique. Enduring issues include the optimisation of SAP parameters for maximising defect detection, the influence of subjective behaviour on the response, structure-function discordance, and ageing- and disease-related changes of the visual pathway. Addressing these issues has been a focus of our research program and is the subject of this manuscript. We will review some of the basic psychophysical principles and methods that have contributed to the development of SAP and their contributions to its output measurements. Parameters that are interrogated include stimulus size and background luminance and their modification to improve defect defection in glaucoma and age-related macular degeneration. We propose frameworks for optimising testing parameters and leveraging the results for changing clinical care. In our pursuit of optimising the structure-function relationship in the eye, several areas of research have been developed and explored, including: the reconciliation of subjective responses in perimetry; by minimising sources of biases, such as Method of Limits we have been able to equate static and kinetic perimetry outputs in relation to underlying structural loci. This also formed the basis for our clustering framework, which groups together statistically similar structural and functional test locations to maximise structure-function concordance. Throughout the manuscript, we review the scientific underpinnings of clinical measurements, framing application into real-world patients to improve clinical practice.

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