An evidence-based approach to the routine use of optical coherence tomography

Angelica Ly, Jack Phu, Paula Katalinic, Michael Kalloniatis, Angelica Ly, Jack Phu, Paula Katalinic, Michael Kalloniatis

Abstract

Optical coherence tomography is an imaging technology that has revolutionised the detection, assessment and management of ocular disease. It is now a mainstream technology in clinical practice and is performed by non-specialised personnel in some settings. This article provides a clinical perspective on the implications of that movement and describes best practice using multimodal imaging and an evidence-based approach. Practical, illustrative guides on the interpretation of optical coherence tomography are provided for three major diseases of the ocular fundus, in which optical coherence tomography is often crucial to management: age-related macular degeneration, diabetic retinopathy and glaucoma. Topics discussed include: cross-sectional and longitudinal signs in ocular disease, so-called 'red-green' disease whereby clinicians rely on machine/statistical comparisons for diagnosis in managing treatment-naïve patients, and the utility of optical coherence tomography angiography and machine learning.

Keywords: age-related macular degeneration; diabetic retinopathy; glaucoma; imaging; screening.

© 2018 The Authors. Clinical and Experimental Optometry published by John Wiley & Sons Australia, Ltd on behalf of Optometry Australia.

Figures

Figure 1
Figure 1
A: Optical coherence tomography (OCT) signs of age‐related macular degeneration (AMD). Drusen or elevations of the retinal pigment epithelium (RPE)/Bruch's membrane complex, hyper‐reflective foci in the outer retina and subretinal drusenoid deposits are key risk factors for progression, typical of intermediate AMD, and may be identified using OCT data acquired from a single patient attendance. In contrast, atrophy (in this instance, complete thinning of the outer nuclear layer and dropout of the ellipsoid zone and RPE with and without outer retinal tubulation; yellow arrowhead), incommensurate sub‐ or intra‐retinal fluid (appearing as optically empty spaces) and subretinal hyper‐reflective material represent OCT signs of advanced AMD. B: Four eyes illustrating the clinical application of OCT for change analysis in AMD. Each row shows a common sequence of events that precede progression to advanced disease: (i) the emergence of hyper‐reflective foci overlying drusen followed by pigment migration, (ii) confluence of drusen over time followed by regression, (iii) emergence of hyper‐reflective foci followed by the development of nascent geographic atrophy, (iv) shallow drusenoid pigment epithelial detachment with eventual development of drusen substructures and intra‐retinal fluid; examination dates appear at the bottom of each image.
Figure 2
Figure 2
A: Case images illustrating the emerging application of optical coherence tomography angiography (OCT‐A) in age‐related macular degeneration (AMD). B: Examples of green disease (false negatives) that is cases where the internal limiting membrane (ILM)‐retinal pigment epithelium (RPE) thickness values fall within normal range despite the presence of significant AMD signs, reflecting that the injudicious reliance on macular thickness measurements is not recommended. C: Case example of OCT‐rendered red disease (false positives) at the macula.
Figure 3
Figure 3
A: Drusen regression and B: drusen subtypes, especially reticular pseudodrusen or calcified drusen, represent significant risk factors for progression in age‐related macular degeneration (AMD) and are better followed using en face imaging methods and a multimodal imaging approach. C: Mimicking disorders and mixed presentations of disease are also better identified using an evidence‐based, multimodal imaging approach.
Figure 4
Figure 4
A: Key signs of diabetic retinopathy (DR) as they appear using optical coherence tomography (OCT) data attained at a single visit. Dilated fundus examination forms the basis of grading DR but is being increasingly supplemented by OCT to assist in differential diagnosis. B: OCT‐A (angiography) signs of DR. As pictured, microaneurysms may take on a range of shapes varying from nodular to earlobe‐like.
Figure 5
Figure 5
A: Case images illustrating the application of optical coherence tomography (OCT) for change analysis in diabetic retinopathy (DR). Note that the early detection of subtle cases such as these may be best appreciated using the retinal thickness maps. B: Green disease whereby other imaging modalities reveal consistent evidence of diabetic macular oedema although the normative analysis (left) using Cirrus OCT classifies all thickness values as within normal limits. Abbreviations: as with Figures 1, 2, 3, 4.
Figure 6
Figure 6
A: Cross‐sectional and B: progression data acquired using Cirrus HD‐OCT (optical coherence tomography) in a case of pre‐perimetric glaucoma. Abbreviations: as with Figures 1, 2, 3, 4, 5; HFA, Humphrey visual field analyser; RNFL, retinal nerve fibre layer; TSNIT, temporal superior nasal inferior temporal.
Figure 7
Figure 7
A: Optical coherence tomography angiography (OCT‐A) for evaluating anomalies in vascular perfusion, and B: anterior segment (AS) OCT for adjunctive assessment of the angle. C, D: Examples of glaucoma‐related green and red disease (false negatives and false positives), respectively. Abbreviations: as with Figures 1, 2, 3, 4, 5, 6; GCIPL, ganglion cell inner plexiform layer.
Figure 8
Figure 8
Case images illustrating the usefulness of optical coherence tomography (OCT) for differential diagnoses relating to glaucoma, including A: high myopia, B: retinal vascular occlusions, C: optic neuritis, and D: acquired optic disc pit. Abbreviations: as with Figures 1, 2, 3, 4, 5, 6, 7.
Figure 9
Figure 9
Demonstrative example of a semi‐automated strategy for integrating results of multiple imaging modalities. In this instance, a computational approach (unsupervised clustering) has been applied to the combination of infrared, autofluorescence and green scanning laser ophthalmoscopy findings to classify lesions in age‐related macular degeneration (AMD).174 A: Colour fundus photograph, cropped and masked to include the macular area only and B: corresponding classified image using this ‘pattern recognition approach’. Each distinct colour corresponds to a specific anatomical structure, as indicated by the figure legend. C: The class corresponding to drusen may then be outlined as a reflection of overall drusen load, which is an established risk factor for progression in AMD. D: Although colour fundus photography is the current standard of care in AMD grading, an additional optical coherence tomography (OCT) line scan has been provided to illustrate the drusen and pigmentary abnormalities. The same approach may also be applied for change analysis, that is for the surveillance of drusen load over time.174 FAF, fundus autofluorescence; IR, infrared.

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