QUANTITATIVE OPTICAL COHERENCE TOMOGRAPHY REVEALS ROD PHOTORECEPTOR DEGENERATION in EARLY DIABETIC RETINOPATHY

Le, David; Son, Taeyoon; Lim, Jennifer I.; Yao, Xincheng

doi:10.1097/iae.0000000000003473

Cited by 8 publications

(7 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, the ISe/RPE intensity ratio was determined. Our recent OCT investigation demonstrated that rods predominate in photoreceptor degradation in early DR. 9 Cones are known to dominate the central fovea. 11 As a result, normalized intensity characteristics in the central retina were not examined as the IPL cannot be determined.…”

Section: Methodsmentioning

confidence: 99%

“…8 In a recent study, we explored OCT intensity–based characteristics for different outer retinal bands, e.g., ISe and RPE. 9 It was observed that ISe-based characteristics were most sensitive for differentiating controls, people with diabetes with NoDR, and people with mild NPDR. In this study, we compare OCT and OCTA biomarkers of early DR and determine the correlation between the most sensitive OCT and OCTA characteristics.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Comparative Analysis of Oct and Oct Angiography Characteristics in Early Diabetic Retinopathy

Son

Lim³

et al. 2023

Retina

Self Cite

View full text Add to dashboard Cite

Purpose: To assess the quantitative characteristics of optical coherence tomography (OCT) and OCT angiography (OCTA) for the objective detection of early diabetic retinopathy (DR).Methods: This was a retrospective and cross-sectional study, which was carried out at a tertiary academic practice with a subspecialty. Twenty control participants, 15 people with diabetics without retinopathy (NoDR), and 22 people with mild nonproliferative diabetic retinopathy (NPDR) were included in this study. Quantitative OCT characteristics were derived from the photoreceptor hyperreflective bands, i.e., inner segment ellipsoid (ISe) and retinal pigment epithelium (RPE). OCTA characteristics, including vessel diameter index (VDI), vessel perimeter index (VPI), and vessel skeleton density (VSD), were evaluated.Results: Quantitative OCT analysis indicated that the ISe intensity was significantly trending downward with DR advancement. Comparative OCTA revealed VDI, VPI, and VSD as the most sensitive characteristics of DR. Correlation analysis of OCT and OCTA characteristics revealed weak variable correlation between the two imaging modalities.Conclusion: Quantitative OCT and OCTA analyses revealed photoreceptor and vascular distortions in early DR. Comparative analysis revealed that the OCT intensity ratio, ISe/RPE, has the best sensitivity for early DR detection. Weak variable correlation of the OCT and OCTA characteristics suggests that OCT and OCTA are providing supplementary information for DR detection and classification.

show abstract

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Comparative Analysis of Oct and Oct Angiography Characteristics in Early Diabetic Retinopathy

Son

Lim³

et al. 2023

Retina

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, gradual loss of the inner retina (ganglion cell layer‐inner plexiform layer) has been shown to independently predict long‐term progression of diabetic retinopathy in those with type II diabetes 10 . In addition to inner retinal change, a recent study showed patients with no signs of diabetic retinopathy exhibited photoreceptor change as measured by optical coherence tomography 11 . These human studies have generally been recapitulated in animal models of diabetes with both inner and outer retinal neuronal change reported.…”

Section: Introductionmentioning

confidence: 99%

Anomalies in neurovascular coupling during early diabetes: A review

Fletcher

Dixon

Mills

et al. 2022

Clinical Exper Ophthalmology

View full text Add to dashboard Cite

Diabetic retinopathy is the most feared complication for those with diabetes. Although visible vascular pathology traditionally defines the management of this condition, it is now recognised that a range of cellular changes occur in the retina from an early stage of diabetes. One of the most significant functional changes that occurs in those with diabetes is a loss of vasoregulation in response to changes in neural activity. There are several retinal cell types that are critical for mediating so‐called neurovascular coupling, including Müller cells, microglia and pericytes. Although there is a great deal of evidence that suggests that Müller cells are integral to regulating the vasculature, they only modulate part of the vascular tree, highlighting the complexity of vasoregulation within the retina. Recent studies suggest that retinal immune cells, microglia, play an important role in mediating vasoconstriction. Importantly, retinal microglia contact both the vasculature and neural synapses and induce vasoconstriction in response to neurally expressed chemokines such as fractalkine. This microglial‐dependent regulation occurs via the vasomediator angiotensinogen. Diabetes alters the way microglia regulate the retinal vasculature, by increasing angiotensinogen expression, causing capillary vasoconstriction and contributing to a loss of vascular reactivity to physiological signals. This article summarises recent studies showing changes in vascular regulation during diabetes, the potential mechanisms by which this occurs and the significance of these early changes to the progression of diabetic retinopathy.

show abstract

“…Especially in the 6 mm × 6 mm and 3 mm × 3 mm eld of views, the OCTA can provide depthresolved visualization of individual retinal layers with the capillary level resolution. Quantitative analysis of the OCTA images has been extensively studied for the objective detection and classi cation of retinal diseases [12][13][14][15][16][17] . Through the identi cation of capillary vortices in the deep capillary plexus, Xu et al 18 demonstrated how to manually distinguish retinal arteries from veins in clinical OCTA images.…”

Section: Introductionmentioning

confidence: 99%

AVA-Net: an open-source deep learning network for arterial-venous area segmentation in OCT angiography

Yao

Abtahi²,

Le³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Differential artery-vein (AV) analysis in optical coherence tomography angiography (OCTA) holds promise for early detection of eye diseases. However, currently available methods for AV analysis are limited for binary processing of retinal vasculature in OCTA, without quantitative information of vascular perfusion intensity. This study is to develop a deep learning network AVA-Net for automated AV area (AVA) segmentation in OCTA, and thus to enable quantitative AV analysis of vascular perfusion intensity. Seven new OCTA features, including arterial area (AA), venous area (VA), AVA ratio (AVAR), total perfusion intensity density (T-PID), arterial PID (A-PID), venous PID (V-PID), and arterial-venous PID ratio (AV-PIDR), have been developed and validated for early detection of diabetic retinopathy (DR). Each of these seven features was evaluated for quantitative comparison of OCTA images from healthy controls, diabetic patients without DR (NoDR), and mild DR. It was observed that the area features, i.e., AA, VA and AVAR, can reveal significant differences between the control and diabetic eyes (NoDR and mild DR), but cannot separate NoDR and mild DR from each other. Vascular perfusion parameters, including T-PID and V-PID, can differentiate mild DR from control and NoDR groups, but cannot separate control and NoDR from each other. In contrast, the AV-PIDR can disclose significant differences among all three groups, i.e., control, NoDR, and mild DR. The AVA-Net validated in this study is available on GitHub for open access.

show abstract

QUANTITATIVE OPTICAL COHERENCE TOMOGRAPHY REVEALS ROD PHOTORECEPTOR DEGENERATION in EARLY DIABETIC RETINOPATHY

Cited by 8 publications

References 37 publications

Comparative Analysis of Oct and Oct Angiography Characteristics in Early Diabetic Retinopathy

Comparative Analysis of Oct and Oct Angiography Characteristics in Early Diabetic Retinopathy

Anomalies in neurovascular coupling during early diabetes: A review

AVA-Net: an open-source deep learning network for arterial-venous area segmentation in OCT angiography

Contact Info

Product

Resources

About