Macular imaging with optical coherence tomography in glaucoma

Mohammadzadeh, Vahid; Fatehi, Nima; Yarmohammadi, Adeleh; Lee, Jiwoong; Sharifipour, Farideh; Daneshvar, Ramin; Caprioli, Joseph; Nouri‐Mahdavi, Kouros

doi:10.1016/j.survophthal.2020.03.002

Cited by 51 publications

(45 citation statements)

References 406 publications

(693 reference statements)

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“…The loss of RGCs and their axons are the hallmarks of neurodegenerative processes in glaucoma [ 2 ]. OCT has optimized and revolutionized the structural assessment of glaucoma and is the imaging modality of choice for glaucoma diagnostics [ 3 ]. It offers insights into RGC degeneration in glaucoma at two main retinal sites: (i) peripapillary retina and (ii) macula.…”

Section: Oct In Glaucomamentioning

confidence: 99%

“…Both peripapillary and inner macular thickness might also have a critical role in the timely identification of glaucoma progression to implement therapy and avert permanent visual loss. However, many studies demonstrated the beneficial role of either GCC or GCIPL over pRNFL in monitoring glaucoma—see reviews [ 3 , 9 ]. At preperimetric and suspect glaucomatous stages, it was reported that patients with abnormal or borderline baseline GCC focal loss volume had a fourfold higher risk for glaucoma conversion over 6 years period [ 10 ].…”

Section: Oct In Glaucomamentioning

confidence: 99%

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Non-invasive electrophysiology in glaucoma, structure and function—a review

Al-Nosairy

Hoffmann

Bach

2021

Eye

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Glaucoma, its early diagnosis, and monitoring of interventions remain an ongoing challenge. We here review developments in functional assessment and its relation to morphology, evaluating recent insights in electrophysiology in glaucoma and highlighting how glaucoma research and diagnostics benefit from combined approaches of OCT and electrophysiological investigations. After concise overviews of OCT and non-invasive electrophysiology in glaucoma, we evaluate commonalities and complementarities of OCT and electrophysiology for our understanding of glaucoma. As a specific topic, the dynamic range (floor effects) of the various techniques is discussed.

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Section: Oct In Glaucomamentioning

confidence: 99%

Section: Oct In Glaucomamentioning

confidence: 99%

Non-invasive electrophysiology in glaucoma, structure and function—a review

Al-Nosairy

Hoffmann

Bach

2021

Eye

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“…[3][4][5][6][7][8] Macular optical coherence tomography (OCT) is an essential tool for the evaluation of central retinal ganglion cells (RGC). [9][10][11][12][13][14] There is now evidence supporting the utility of macular OCT imaging for detection of glaucoma progression, especially in later stages of glaucoma. 2,10,[15][16][17] Most prior studies of macular thickness changes over time have used global outcome measures or thickness measurements in hemiretinal regions.…”

Section: Introductionmentioning

confidence: 99%

Estimating Ganglion Cell Complex Rates of Change With Bayesian Hierarchical Models

Mohammadzadeh

Zadeh

et al. 2021

Trans. Vis. Sci. Tech.

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Develop a hierarchical longitudinal regression model for estimating local rates of change of macular ganglion cell complex (GCC) measurements with optical coherence tomography (OCT). Methods:We enrolled 112 eyes with four or more macular OCT images and ≥2 years of follow-up. GCC thickness measurements within central 6 × 6 superpixels were extracted from macular volume scans. We fit data from each superpixel separately with several hierarchical Bayesian random-effects models. Models were compared with the Watanabe-Akaike information criterion. For our preferred model, we estimated population and individual slopes and intercepts (baseline thickness) and their correlation.Results: Mean (SD) follow-up time and median (interquartile range) baseline 24-2 visual field mean deviation were 3.6 (0.4) years and −6.8 (−12.2 to −4.3) dB, respectively. The random intercepts and slopes model with random residual variance was the preferred model. While more individual and population negative slopes were observed in the paracentral and papillomacular superpixels, superpixels in the superotemporal and inferior regions displayed the highest correlation between baseline thickness and rates of change (r = -0.43 to -0.50 for the top five correlations). Conclusions:A Bayesian linear hierarchical model with random intercepts/slopes and random variances is an optimal initial model for estimating GCC slopes at population and individual levels. This novel model is an efficient method for estimating macular rates of change and probability of glaucoma progression locally. Translational Relevance:The proposed Bayesian hierarchical model can be applied to various macular outcomes from different OCT devices and to superpixels of variable sizes to estimate local rates of change and progression probability.

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“…Optical Coherence Tomography (OCT) is a non-invasive, relatively inexpensive imaging technique which is based on low-coherence interferometry and captures high-resolution multi-dimensional images from biological tissue especially the retina 1 . Macular OCT images are widely used to assist ophthalmologists in diagnosing ocular deformities such as Diabetic Macular Edema (DME), Age-Related Macular Degeneration, glaucoma and retinal vascular accidents 2 , 3 . In addition to that, their interesting applications in diagnosis and effective treatment of neurodegenerative diseases like Multiple Sclerosis and Neuromyelitis Optica has attracted the neurologists 4 .…”

Section: Introductionmentioning

confidence: 99%

Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images

Montazerin

Sajjadifar

Pour

et al. 2021

Sci Rep

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Given the capacity of Optical Coherence Tomography (OCT) imaging to display structural changes in a wide variety of eye diseases and neurological disorders, the need for OCT image segmentation and the corresponding data interpretation is latterly felt more than ever before. In this paper, we wish to address this need by designing a semi-automatic software program for applying reliable segmentation of 8 different macular layers as well as outlining retinal pathologies such as diabetic macular edema. The software accommodates a novel graph-based semi-automatic method, called “Livelayer” which is designed for straightforward segmentation of retinal layers and fluids. This method is chiefly based on Dijkstra’s Shortest Path First (SPF) algorithm and the Live-wire function together with some preprocessing operations on the to-be-segmented images. The software is indeed suitable for obtaining detailed segmentation of layers, exact localization of clear or unclear fluid objects and the ground truth, demanding far less endeavor in comparison to a common manual segmentation method. It is also valuable as a tool for calculating the irregularity index in deformed OCT images. The amount of time (seconds) that Livelayer required for segmentation of Inner Limiting Membrane, Inner Plexiform Layer–Inner Nuclear Layer, Outer Plexiform Layer–Outer Nuclear Layer was much less than that for the manual segmentation, 5 s for the ILM (minimum) and 15.57 s for the OPL–ONL (maximum). The unsigned errors (pixels) between the semi-automatically labeled and gold standard data was on average 2.7, 1.9, 2.1 for ILM, IPL–INL, OPL–ONL, respectively. The Bland–Altman plots indicated perfect concordance between the Livelayer and the manual algorithm and that they could be used interchangeably. The repeatability error was around one pixel for the OPL–ONL and < 1 for the other two. The unsigned errors between the Livelayer and the manual algorithm was 1.33 for ILM and 1.53 for Nerve Fiber Layer–Ganglion Cell Layer in peripapillary B-Scans. The Dice scores for comparing the two algorithms and for obtaining the repeatability on segmentation of fluid objects were at acceptable levels.

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Macular imaging with optical coherence tomography in glaucoma

Cited by 51 publications

References 406 publications

Non-invasive electrophysiology in glaucoma, structure and function—a review

Non-invasive electrophysiology in glaucoma, structure and function—a review

Estimating Ganglion Cell Complex Rates of Change With Bayesian Hierarchical Models

Livelayer: a semi-automatic software program for segmentation of layers and diabetic macular edema in optical coherence tomography images

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