Clinical applications of optical coherence tomography in the posterior pole: the 2011 José Manuel Espino Lecture - Part I

Optical Coherence Tomography Features in Fovea-Off Exudative vs Rhegmatogenous Retinal Detachment

PURPOSE

To describe the optical coherence tomography (OCT) features that can differentiate eyes with fovea-off exudative retinal detachment (ERD) vs rhegmatogenous retinal detachment (RRD), with particular attention to outer retinal corrugations (ORCs).

DESIGN

Multicenter, retrospective cross-sectional study.

METHODS

Multicenter, retrospective cross-sectional study of patients diagnosed with unilateral or bilateral fovea-off ERD or primary, acute, fovea-off RRD between 2016 and 2021. This study was performed with the approval from the Research Ethics Board at the University of Toronto and was conducted in accordance with the Declaration of Helsinki. Patients with any ERD etiology and evidence of extensive, bullous fovea-off detachment and in the RRD group: consecutive patients with acute, primary fovea-off RRD with good quality baseline SD-OCT imaging were included. Patients with exudative choroidal neovascularization from any etiology, optic nerve pit, significant media opacity, or OCT images with poor quality or low signal strength were excluded. Primary outcome was to describe the morphological features of the macula using SD-OCT in patients diagnosed with ERD vs RRD, with specific interest in ORCs.

RESULTS

One hundred sixty-one eyes (51 ERD and 110 RRD) of 154 patients were included. Fifty-one eyes with ERD presented with 1 of 15 etiologies. ERD were associated with a greater risk of having hyperreflective dots in the outer retina (92.2% vs 74.5%, P = .009), hyperreflective material and dots in the subretinal fluid (72.5% vs 34.5%, P < .001), internal limiting membrane and inner retinal undulations (70.6% vs 39.4%, P < .001), and retinal pigment epithelium undulations (44.9% vs 6.4%, P < .001) compared to RRD. RRD was associated with a greater risk of outer retinal corrugations (80% vs 0%, P < .001), intraretinal fluid (90.9% vs 41.2%, P < .001) and ellipsoid zone thickening (90% vs 66.7%, P < .001) compared to ERD.

CONCLUSION

The presence of ORCs are highly specific for RRD and absent in ERD. This is likely related to differences in the pathophysiology of the diseases process, specifically the content of the subretinal fluid. Understanding the differences in OCT morphological features of ERD vs RRD may aid with diagnosis and management.

Generative adversarial network-based deep learning approach in classification of retinal conditions with optical coherence tomography images

PURPOSE

To determine whether a deep learning approach using generative adversarial networks (GANs) is beneficial for the classification of retinal conditions with Optical coherence tomography (OCT) images.

METHODS

Our study utilized 84,452 retinal OCT images obtained from a publicly available dataset (Kermany Dataset). Employing GAN, synthetic OCT images are produced to balance classes of retinal disorders. A deep learning classification model is constructed using pretrained deep neural networks (DNNs), and outcomes are evaluated using 2082 images collected from patients who visited the Department of Ophthalmology and the Department of Endocrinology and Metabolism at the Tri-service General Hospital in Taipei from January 2017 to December 2021.

RESULTS

The highest classification accuracies accomplished by deep learning machines trained on the unbalanced dataset for its training set, validation set, fivefold cross validation (CV), Kermany test set, and TSGH test set were 97.73%, 96.51%, 97.14%, 99.59%, and 81.03%, respectively. The highest classification accuracies accomplished by deep learning machines trained on the synthesis-balanced dataset for its training set, validation set, fivefold CV, Kermany test set, and TSGH test set were 98.60%, 98.41%, 98.52%, 99.38%, and 84.92%, respectively. In comparing the highest accuracies, deep learning machines trained on the synthesis-balanced dataset outperformed deep learning machines trained on the unbalanced dataset for the training set, validation set, fivefold CV, and TSGH test set.

CONCLUSIONS

Overall, deep learning machines on a synthesis-balanced dataset demonstrated to be advantageous over deep learning machines trained on an unbalanced dataset for the classification of retinal conditions.

Optical coherence tomography: a window to the brain?

First described in 1991 and introduced into clinical practice in 1996, optical coherence tomography (OCT) now has a very extensive role in many different areas of ophthalmological practice. It is non-invasive, cheap, highly reproducible, widely available and easy to perform. OCT also has a role in managing patients with neurological disorders, particularly idiopathic intracranial hypertension. This review provides an overview of the technology underlying OCT and the information it can provide that is relevant to the practising neurologist. Particular conditions discussed include papilloedema, optic disc drusen, multiple sclerosis and neuromyelitis optica, other optic neuropathies, compression of the anterior visual pathway and various neurodegenerative conditions.

Retinal biomarkers provide "insight" into cortical pharmacology and disease

The retina is an easily accessible out-pouching of the central nervous system (CNS) and thus lends itself to being a biomarker of the brain. More specifically, the presence of neuronal, vascular and blood-neural barrier parallels in the eye and brain coupled with fast and inexpensive methods to quantify retinal changes make ocular biomarkers an attractive option. This includes its utility as a biomarker for a number of cerebrovascular diseases as well as a drug pharmacology and safety biomarker for the CNS. It is a rapidly emerging field, with some areas well established, such as stroke risk and multiple sclerosis, whereas others are still in development (Alzheimer's, Parkinson's, psychological disease and cortical diabetic dysfunction). The current applications and future potential of retinal biomarkers, including potential ways to improve their sensitivity and specificity are discussed. This review summarises the existing literature and provides a perspective on the strength of current retinal biomarkers and their future potential.

Current interpretation of optical coherence tomography in the posterior pole

OBJECTIVE

To review the literature in order to describe the current nomenclature for the interpretation of retinal images of optical coherence tomography (OCT) in the macular area.

METHODS

A comprehensive literature search was conducted in the major biomedical databases since the introduction of OCT in ophthalmological field.

RESULTS

Quantitative variations of central macular thickness and proper terminology used throughout the years are directly related to the technology and equipment used.

CONCLUSIONS

The current nomenclature of normal macular architecture represented in vivo on spectral domain OCT technology provides a clear and valid anatomical interpretation that can be applied, not only in research, but also in everyday practice.

Noninvasive cross-sectional observation of three-dimensional cell sheet-tissue-fabrication by optical coherence tomography

Cell sheet engineering allows investigators/clinicians to prepare cell-dense three-dimensional (3-D) tissues, and various clinical trials with these fabricated tissues have already been performed for regenerating damaged tissues. Cell sheets are easily manipulated and 3-D tissues can be rapidly fabricated by layering the cell sheets. This study used optical coherence tomography (OCT) to noninvasively analyze the following processes: (1) adhesions between layered cell sheets, and (2) the beating and functional interaction of cardiac cell sheet-tissues for fabricating functional thicker 3-D tissues. The tight adhesions and functional couplings between layered cell sheets could be observed cross-sectionally and in real time. Importantly, the noninvasive and cross-sectional analyses of OCT make possible to fabricate 3-D tissues by confirming the adherence and functional couplings between layered cell sheets. OCT technology would contribute to cell sheet engineering and regenerative medicine.

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Development of an OCT system to noninvasively analyze three-dimensional cell sheet-tissues.

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Noninvasive and cross-sectional observation of the adhesions between layered cell sheets in detail.

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Noninvasive and cross-sectional observation of beating three-dimensional cardiac tissues.

A review of current management of vitreomacular traction and macular hole

The paper presents a review of the sequence of events of posterior vitreous detachment (PVD), vitreomacular adhesion (VMA), vitreomacular traction (VMT), and macular hole (MH) from their pathophysiological aspects, clinical features, diagnostic implications, and current management strategies. A treatment algorithm to be used in clinical practice in patients with VMA, VMT, and MH based on the presence of symptoms, visual acuity, associated epiretinal membrane, and width of the vitreous attachment is presented. Observation, pharmacologic vitreolysis with ocriplasmin, and surgical treatment are positioned as treatment options in the different steps of the therapeutic algorithm, with clear indications of the paths to be followed according to the initial presenting manifestations and the patient's clinical course.

Artifacts in optical coherence tomography

Optical coherence tomography (OCT) is now an integral part of management for numerous retinal diseases for diagnosis, treatment planning and follow up. OCT interpretation must involve the understanding of the associated artifacts. These artifacts can mislead physicians to wrong diagnosis or inappropriate management. This review article discusses the various types of artifacts in OCT scans obtained from various devices in various retinal diseases. This article would help to improve the understanding about the various artifacts and their clinical importance.