Spectral Domain Optical Coherence Tomography Features and Classification Systems for Diabetic Macular Edema: A Review

Validation of a deep learning model for the automated detection and quantification of cystoid macular oedema on optical coherence tomography in patients with retinitis pigmentosa

PURPOSE

Accurate assessment of cystoid macular oedema (CMO) in patients with retinitis pigmentosa (RP) on spectral-domain optical coherence tomography (SD-OCT) is crucial for tracking disease progression and may serve as a therapeutic endpoint. Manual CMO segmentation is labour-intensive and prone to variability, making artificial intelligence (AI) an appealing solution to improve accuracy and efficiency. This study aimed to validate a deep learning (DL) model for automated CMO detection and quantification on SD-OCT scans in patients with RP.

METHODS

A segmentation model based on the no-new-Unet (nnU-Net) architecture was trained on 112 OCT volumes from the RETOUCH dataset (70 for training, 42 for validation). The model was externally tested on 37 SD-OCT scans from RP patients, with annotations from three expert graders. Performance was assessed using the Dice similarity coefficient and intraclass correlation coefficient (ICC).

RESULTS

For randomly selected central B-scans, the model achieved a mean Dice score of 0.889 ± 0.002 standard deviation (SD), while observers scored 0.878 ± 0.007 SD. The ICC for the model was 0.945 ± 0.014 SD, compared to 0.979 ± 0.008 SD for observers. On manually chosen central B-scans, Dice scores were 0.936 ± 0.005 SD for the model and 0.946 ± 0.012 SD for observers, with ICC values of 0.964 ± 0.011 SD and 0.981 ± 0.011 SD, respectively.

CONCLUSIONS

This DL model reliably segments CMO in RP, achieving performance comparable to human graders. It can enhance the efficiency and precision of CMO quantification, reducing variability in clinical practice and trials.

Quantifying the Characteristics of Diabetic Retinopathy in Macular Optical Coherence Tomography Angiography Images: A Few-Shot Learning and Explainable Artificial Intelligence Approach

BACKGROUND

Early detection and accurate staging of diabetic retinopathy (DR) are important to prevent vision loss. Optical coherence tomography angiography (OCTA) images provide detailed insights into the retinal vasculature, revealing intricate changes that occur as DR progresses. However, interpreting these complex images requires significant expertise and is often time-intensive. Deep learning techniques have the potential to automate DR analysis. However, they typically require large datasets for effective training. To address the challenge of limited data in this emerging imaging field, a combined approach using few-shot learning (FSL) and self-attention mechanisms within explainable AI (XAI) was explored.

OBJECTIVE

To investigate and evaluate the potential of an FSL-self-attention XAI approach to improve the accuracy of DR staging classification using OCTA images.

METHODS

A total of 206 OCTA images, comprising 104 non-proliferative diabetic retinopathy (NPDR) and 102 proliferative diabetic retinopathy (PDR) cases, were analyzed using the FSL method. Three pre-trained networks (ResNet-50, DenseNet-161, and MobileNet-v2) were employed, with the top-performing model subsequently integrated with the Match-Them-Up Network (MTUNet) to provide explainable interpretations using a self-attention mechanism. The performance of the models was evaluated by applying standard metrics, including accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC-ROC). The performance of the MTUNet model is assessed by calculating pattern-matching scores for PDR and NPDR classes.

RESULTS

The ResNet-50 pre-trained model in FSL demonstrated the best overall performance, achieving an accuracy of 76.17%, a sensitivity of 81.83%, a specificity of 70.5%, and 0.82 AUC in classifying DR stages. MTUNet provided pattern-matching scores of 0.77 and 0.75 for PDR and NPDR classes, respectively.

CONCLUSIONS

FSL and self-attention mechanisms in XAI offer promising approaches for accurate DR stage classification, especially in data-limited scenarios. This could potentially facilitate early DR detection and inform clinical decision-making.

Hybrid deep learning models for the screening of Diabetic Macular Edema in optical coherence tomography volumes

Several studies published so far used highly selective image datasets from unclear sources to train computer vision models and that may lead to overestimated results, while those studies conducted in real-life remain scarce. To avoid image selection bias, we stacked convolutional and recurrent neural networks (CNN-RNN) to analyze complete optical coherence tomography (OCT) cubes in a row and predict diabetic macular edema (DME), in a real-world diabetic retinopathy screening program. A retrospective cohort study was carried out. Throughout 4-years, 5314 OCT cubes from 4408 subjects who attended to the diabetic retinopathy (DR) screening program were included. We arranged twenty-two (22) pre-trained CNNs in parallel with a bidirectional RNN layer stacked at the bottom, allowing the model to make a prediction for the whole OCT cube. The staff of retina experts built a ground truth of DME later used to train a set of these CNN-RNN models with different configurations. For each trained CNN-RNN model, we performed threshold tuning to find the optimal cut-off point for binary classification of DME. Finally, the best models were selected according to sensitivity, specificity, and area under the receiver operating characteristics curve (AUROC) with their 95% confidence intervals (95%CI). An ensemble of the best models was also explored. 5188 cubes were non-DME and 126 were DME. Three models achieved an AUROC of 0.94. Among these, sensitivity, and specificity (95%CI) ranged from 84.1-90.5 and 89.7-93.3, respectively, at threshold 1, from 89.7-92.1 and 80-83.1 at threshold 2, and from 80.2-81 and 93.8-97, at threshold 3. The ensemble model improved these results, and lower specificity was observed among subjects with sight-threatening DR. Analysis by age, gender, or grade of DME did not vary the performance of the models. CNN-RNN models showed high diagnostic accuracy for detecting DME in a real-world setting. This engine allowed us to detect extra-foveal DMEs commonly overlooked in other studies, and showed potential for application as the first filter of non-referable patients in an outpatient center within a population-based DR screening program, otherwise ended up in specialized care.

IL-10-induced modulation of macrophage polarization suppresses outer-blood-retinal barrier disruption in the streptozotocin-induced early diabetic retinopathy mouse model

Diabetic retinopathy (DR) is associated with ocular inflammation leading to retinal barrier breakdown, vascular leakage, macular edema, and vision loss. DR is not only a microvascular disease but also involves retinal neurodegeneration, demonstrating that pathological changes associated with neuroinflammation precede microvascular injury in early DR. Macrophage activation plays a central role in neuroinflammation. During DR, the inflammatory response depends on the polarization of retinal macrophages, triggering pro-inflammatory (M1) or anti-inflammatory (M2) activity. This study aimed to determine the role of macrophages in vascular leakage through the tight junction complexes of retinal pigment epithelium, which is the outer blood-retinal barrier (BRB). Furthermore, we aimed to assess whether interleukin-10 (IL-10), a representative M2-inducer, can decrease inflammatory macrophages and alleviate outer-BRB disruption. We found that modulation of macrophage polarization affects the structural and functional integrity of ARPE-19 cells in a co-culture system under high-glucose conditions. Furthermore, we demonstrated that intravitreal IL-10 injection induces an increase in the ratio of anti-inflammatory macrophages and effectively suppresses outer-BRB disruption and vascular leakage in a mouse model of early-stage streptozotocin-induced diabetes. Our results suggest that modulation of macrophage polarization by IL-10 administration during early-stage DR has a promising protective effect against outer-BRB disruption and vascular leakage. This finding provides valuable insights for early intervention in DR.

Difference of central foveal thickness measurement in patients with macular edema using optical coherence tomography in different display modes

Purpose

To assess the differences in the measurement of central foveal thickness (CFT) in patients with macular edema (ME) between two display modes (1:1 pixel and 1:1 micron) on optical coherence tomography (OCT).

Design

This is a retrospective, cross-sectional study.

Methods

Group A consisted of participants with well-horizontal OCT B-scan images and group B consisted of participants with tilted OCT B-scan. We manually measured the CFT under the two display modes, and the values were compared statistically using the paired t-test. Spearman's test was used to assess the correlations between the OCT image tilting angle (OCT ITA) and the differences in CFT measurement. The area under the curve (AUC) was calculated to define the OCT ITA cutoff for a defined CFT difference.

Results

In group A, the mean CFT in the 1:1 pixel display mode was 420.21 ± 130.61 µm, similar to the mean CFT of 415.27 ± 129.85 µm in the 1:1 micron display mode. In group B, the median CFT in the 1:1 pixel display mode is 409.00 μm (IQR: 171.75 μm) and 368.00 μm (IQR: 149.00 μm) in the 1:1 micron display mode. There were significant differences between the two display modes with the median (IQR) absolute difference and median (IQR) relative difference of 38.00 μm (75.00 μm) and 10.19% (21.91%) (all p = 0.01). The differences in CFT measurement between the two display modes were correlated with the OCT ITA (absolute differences, r = 0.88, p < 0.01; relative differences, r = 0.87, p < 0.01). The AUC for a predefined CFT difference was 0.878 (10 μm), 0.933 (20 μm), 0.938 (30 μm), 0.961 (40 μm), 0.962 (50 μm), and 0.970 (60 μm).

Conclusion

In patients with DM, when the OCT B-scan images were well-horizontal, manual CFT measurements under the two display modes were similar, but when the B-scan images were tilted, the CFT measurements were different under the two display modes, and the differences were correlated to the OCT ITA.

Investigating the associations of macular edema in retinitis pigmentosa

Macular edema (ME), the accumulation of intraretinal fluid in the macula, is a common sight affecting sequelae of retinitis pigmentosa (RP). However, it is unclear why some patients develop ME, and others do not. This study aims to identify associations between clinical-genetic factors in RP with ME. Patients with clinically confirmed RP cases were identified from the inherited retinal disease database at a large tertiary referral academic center. Demographic and genetic testing findings were noted. Additionally, optical coherence tomography volume scans were graded using a validated grading system. One hundred and six patients (73.1%) were found to have ME in at least one eye (OD = 88, mean = 37.9%, OS = 98, mean = 31.7%). Structurally, the presence of epiretinal membrane (ERM) (p < 0.007) and vitreo-macular traction (VMT) (p < 0.003) were significantly associated with ME. Additionally, X-linked (p < 0.032) and autosomal dominant inheritance (p < 0.039) demonstrated a significant association with ME, with RP1 (p < 0.045) and EYS (p < 0.017) pathogenic variants also significantly associated with ME. This study, in a large cohort of RP patients, confirms previous retinal structural associations for ME in RP and identifies potential new genetic associations.

A Diabetic Retinopathy Classification Framework Based on Deep-Learning Analysis of OCT Angiography

Purpose

Reliable classification of referable and vision threatening diabetic retinopathy (DR) is essential for patients with diabetes to prevent blindness. Optical coherence tomography (OCT) and its angiography (OCTA) have several advantages over fundus photographs. We evaluated a deep-learning-aided DR classification framework using volumetric OCT and OCTA.

Methods

Four hundred fifty-six OCT and OCTA volumes were scanned from eyes of 50 healthy participants and 305 patients with diabetes. Retina specialists labeled the eyes as non-referable (nrDR), referable (rDR), or vision threatening DR (vtDR). Each eye underwent a 3 × 3-mm scan using a commercial 70 kHz spectral-domain OCT system. We developed a DR classification framework and trained it using volumetric OCT and OCTA to classify eyes into rDR and vtDR. For the scans identified as rDR or vtDR, 3D class activation maps were generated to highlight the subregions which were considered important by the framework for DR classification.

Results

For rDR classification, the framework achieved a 0.96 ± 0.01 area under the receiver operating characteristic curve (AUC) and 0.83 ± 0.04 quadratic-weighted kappa. For vtDR classification, the framework achieved a 0.92 ± 0.02 AUC and 0.73 ± 0.04 quadratic-weighted kappa. In addition, the multiple DR classification (non-rDR, rDR but non-vtDR, or vtDR) achieved a 0.83 ± 0.03 quadratic-weighted kappa.

Conclusions

A deep learning framework only based on OCT and OCTA can provide specialist-level DR classification using only a single imaging modality.

Translational Relevance

The proposed framework can be used to develop clinically valuable automated DR diagnosis system because of the specialist-level performance showed in this study.

Optical Coherence Tomography Classification Systems for Diabetic Macular Edema and Their Associations With Visual Outcome and Treatment Responses - An Updated Review

ABSTRACT

Optical coherence tomography (OCT) is an invaluable imaging tool in detecting and assessing diabetic macular edema (DME). Over the past decade, there have been different proposed OCT-based classification systems for DME. In this review, we present an update of spectral-domain OCT (SDOCT)-based DME classifications over the past 5 years. In addition, we attempt to summarize the proposed OCT qualitative and quantitative parameters from different classification systems in relation to disease severity, risk of progression, and treatment outcome. Although some OCT-based measurements were found to have prognostic value on visual outcome, there has been a lack of consensus or guidelines on which parameters can be reliably used to predict treatment outcomes. We also summarize recent literatures on the prognostic value of these parameters including quantitative measures such as macular thickness or volume, central subfield thickness or foveal thickness, and qualitative features such as the morphology of the vitreoretinal interface, disorganization of retinal inner layers, ellipsoid zone disruption integrity, and hyperreflec-tive foci. In addition, we discuss that a framework to assess the validity of biomarkers for treatment outcome is essentially important in assessing the prognosis before deciding on treatment in DME. Finally, we echo with other experts on the demand for updating the current diabetic retinal disease classification.

Comparison of Central Macular Fluid Volume With Central Subfield Thickness in Patients With Diabetic Macular Edema Using Optical Coherence Tomography Angiography

IMPORTANCE

Diabetic macular edema (DME) is the predominant cause of visual impairment in patients with type 1 or 2 diabetes. Automated fluid volume measurements using optical coherence tomography (OCT) may improve the diagnostic accuracy of DME screening.

OBJECTIVE

To assess the diagnostic accuracy of an automated central macular fluid volume (CMFV) quantification using OCT for DME.

DESIGN, SETTING, AND PARTICIPANTS

A cross-sectional observational study was conducted at a tertiary academic center among 215 patients with diabetes (1 eye each) enrolled from January 26, 2015, to December 23, 2019. All participants underwent comprehensive examinations, 6 × 6-mm macular structural OCT horizontal raster scans, and 6 × 6-mm macular OCT angiography volumetric scans. From January 1 to March 30, 2020, 2 retinal specialists reviewed the structural OCT scans independently and diagnosed DME if intraretinal or subretinal fluid was present. Diabetic macular edema was considered center involved if fluid was present within the central fovea (central 1-mm circle). A third retinal specialist arbitrated any discrepancy. The mean central subfield thickness (CST) within the central fovea was measured on structural OCT horizontal raster scans. A deep learning algorithm automatically quantified fluid volumes on 6 × 6-mm OCT angiography volumetric scans and within the central foveas (CMFV).

MAIN OUTCOMES AND MEASURES

The area under the receiver operating characteristic curve (AUROC) and the sensitivity and specificity of CST and CMFV for DME diagnosis.

RESULTS

We enrolled 1 eye each of 215 patients with diabetes (117 women [54.4%]; mean [SD] age, 59.6 [12.4] years). Diabetic macular edema was present in 136 eyes; 93 cases of DME were center involved. The AUROC of CMFV for diagnosis of center-involved DME (0.907 [95% CI, 0.861-0.954]) was greater than the AUROC of CST (0.832 [95% CI, 0.775-0.889]; P = .02). With the specificity set at 95%, the sensitivity of CMFV for detection of center-involved DME (78.5% [95% CI, 68.8%-86.3%]) was higher than that of CST (53.8% [95% CI, 43.1%-64.2%]; P = .002). Center-involved DME cases not detected by CST but detected by CMFV were associated with a thinner CST (290.8 μm [95% CI, 282.3-299.3 μm] vs 369.4 μm [95% CI, 347.1-391.7 μm]; P < .001), higher proportion of previous macular laser treatment (11 of 28 [39.3%; 95% CI, 21.5%-59.4%] vs 12 of 65 [18.5%; 95% CI, 9.9%-30.0%]; P = .03), and female sex (20 of 28 [71.4%; 95% CI, 51.3%-86.8%] vs 31 of 65 [47.7%; 95% CI, 35.1%-60.5%]; P = .04).

CONCLUSIONS AND RELEVANCE

These findings suggest that an automated CMFV is a more accurate diagnostic biomarker than CST for DME and may improve screening for DME.

Assessment of Inflammation Biomarkers in Diabetic Macular Edema Treated with Intravitreal Dexamethasone Implant

Purpose: To evaluate inflammation biomarkers in diabetic macular edema (DME) treated with intravitreal dexamethasone implant (Ozurdex^®). Methods: This retrospective single-center study investigated 64 eyes of 64 patients with DME who were nonresponsive to prior antivascular endothelial growth factor and treated with intravitreal Ozurdex. The neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), and platelet/lymphocyte ratio were calculated. Visual acuity and optical coherence tomography markers, including hyper-reflective dots and subretinal fluid (SRF), were determined, and central retinal thickness was also evaluated monthly for 3 months. Results: The average age was 64.06 ± 7.81 (48-84) years. The baseline NLR and MLR were significantly higher in patients with better visual outcomes (P = 0.029 and P = 0.048, respectively). Better anatomical outcomes were observed in the presence of SRF (P = 0.027). No significant differences were observed in the rates of the presence of SRF and hyper-reflective points about the better functional outcome (P > 0.05). Conclusions: SRF as an imaging biomarker, and NLR and MLR as blood biomarkers, stand out as markers of inflammation and were found to be associated with better response to Ozurdex implantation in DME.

Large-cube 30° × 25° optical coherence tomography in diabetic macular edema

Background

To evaluate the contribution of large-cube 30° × 25° optical coherence tomography (OCT) in the characterization of diabetic macular edema (DME) by assessing its extent and the presence of additional retinal edemas and to evaluate the factors that influenced their occurrence.

Methods

This retrospective study enrolled patients with diabetes who presented with retinal edema detected by horizontal large-cube 30° × 25° (8.7 × 7.3 mm) OCT. Two individualized areas were selected from the thickness map: the area within the 6-mm Early Treatment of Diabetic Retinopathy Study (ETDRS) grid, and that outside the ETDRS grid. Retinal edemas located within the ETDRS grid were designated as “main DME” and those located outside the ETDRS grid were designated as “peripheral retinal edemas.” For each area, OCT features were assessed while the extent of the main DME and the presence of peripheral retinal oedema were analysed in the area outside the ETDRS grid. Finally, part of included eyes was followed by the same protocol, of which a part benefited from intravitreal injections.

Results

Peripheral events were detected outside the ETDRS area in 279 eyes (74.4%) of the 375 eyes of the 218 patients included in this study: an extension of the main DME outside ETDRS grid in 177 eyes (47.2%) and/or the presence of peripheral retinal edemas in 207 eyes (55.2%). The analysis of associations between main DME and peripheral retinal edemas patterns did not find an association for retinal cyst localization (P = 0.42) while a week association was found fort cyst size (Cramer’s V = 0.188, p = 0.028). Nevertheless, a moderate association was found for the presence of microaneurysms (Cramer’s V = 0.247, p < 0.001) and strong association for hard exudates (Cramer’s V = 0.386, p < 0.001), The binary logistic regression analysis retained the following influencing factors of the occurrence of peripheral events: advanced DR stage (Odds ratio OR = 2.19, p = 0.03), diffuse DME (OR = 7.76, p < 0.001) and its location in outer fields (OR = 7.09, p = 0.006). Likewise, the extension of the main DME outside the ETDRS area in was influenced by the same factors in addition to CMT (OR = 0.98, p = 0.004) while the presence of peripheral retinal edema was influenced by the same factors except the outer location of the Main DME. Finally, from the 94 eyes treated by intravitreal injections, extension of the main DME outside the ETDRS grid was detected in 54 eyes (56.44%) at baseline visit and still remained detectable in 37 eyes (39.36%) after treatment initiation.

Conclusions

Large-cube 30° × 25° OCT allowed for more precise assessment of DME extension and better detection of retinal thickening mainly in the advanced stages of diabetic retinopathy with significant DME whether at the baseline visit or during follow-up. The combination of this protocol with a wider ETDRS grid would enhance DME detection and topography.

Spectral domain optical coherence tomography classification of diabetic macular edema: a new proposal to clinical practice

PURPOSE

To classify the types of diabetic macular edema (DME) and evaluate its morphological features on spectral domain optical coherence tomography (SD-OCT) and determine correlations between visual acuity and OCT findings.

METHODS

We assessed 406 eyes of 309 patients with a diagnosis of DME retrospectively. Three types based on SD-OCT were identified: diffuse macular edema, cystoid macular edema, and cystoid degeneration. Morphological features such as serous macular detachment (SMD), vitreomacular interface abnormalities (VMAI), hard exudates, photoreceptor status, and correlations between visual acuity and those morphological features were also evaluated by SD-OCT.

RESULTS

The most common type of DME was cystoid edema (68.5%). No statistically significant difference was found between groups in sex (P = 0.40), type of diabetes (P = 0.50), or diabetic retinopathy (P = 0.78). However, the duration of symptoms and BCVA was significantly lower in the group with cystoid degeneration compared with the group with cystoid edema (P < 0.001) and the group with diffuse macular edema (P < 0.001). In the group with cystoid degeneration compared with the groups with cystoid and diffuse edema, the central fovea and central subfield were significantly thicker (both (P < 0.001), the subfoveal choroid was significantly thinner (P = 0.049), rate of serous macular detachment was significantly lower (P < 0.001), and the rate of outer retinal damage was significantly higher (P < 0.001).

CONCLUSIONS

Cystoid macular degeneration, which is consistent with poor functional and morphological outcomes, should be differentiated from cystoid macular edema. Serous macular detachment, which is mostly seen in eyes with early stages of DME, should be evaluated as an accompanying morphological finding rather than a type of DME.

The Evolving Treatment of Diabetic Retinopathy

Purpose

To review the current therapeutic options for the management of diabetic retinopathy (DR) and diabetic macular edema (DME) and examine the evidence for integration of laser and pharmacotherapy.

Methods

A review of the PubMed database was performed using the search terms diabetic retinopathy, diabetic macular edema, neovascularization, laser photocoagulation, intravitreal injection, vascular endothelial growth factor (VEGF), vitrectomy, pars plana vitreous surgery, antiangiogenic therapy. With additional cross-referencing, this yielded 835 publications of which 301 were selected based on content and relevance.

Results

Many recent studies have evaluated the pharmacological, laser and surgical therapeutic strategies for the treatment and prevention of DR and DME. Several newer diagnostic systems such as optical coherence tomography (OCT), microperimetry, and multifocal electroretinography (mfERG) are also assisting in further refinements in the staging and classification of DR and DME. Pharmacological therapies for both DR and DME include both systemic and ocular agents. Systemic agents that promote intensive glycemic control, control of dyslipidemia and antagonists of the renin-angiotensin system demonstrate beneficial effects for both DR and DME. Ocular therapies include anti-VEGF agents, corticosteroids and nonsteroidal anti-inflammatory drugs. Laser therapy, both as panretinal and focal or grid applications continue to be employed in management of DR and DME. Refinements in laser devices have yielded more tissue-sparing (subthreshold) modes in which many of the benefits of conventional continuous wave (CW) lasers can be obtained without the adverse side effects. Recent attempts to lessen the burden of anti-VEGF injections by integrating laser therapy have met with mixed results. Increasingly, vitreoretinal surgical techniques are employed for less advanced stages of DR and DME. The development and use of smaller gauge instrumentation and advanced anesthesia agents have been associated with a trend toward earlier surgical intervention for diabetic retinopathy. Several novel drug delivery strategies are currently being examined with the goal of decreasing the therapeutic burden of monthly intravitreal injections. These fall into one of the five categories: non-biodegradable polymeric drug delivery systems, biodegradable polymeric drug delivery systems, nanoparticle-based drug delivery systems, ocular injection devices and with sustained release refillable devices. At present, there remains no one single strategy for the management of the particular stages of DR and DME as there are many options that have not been rigorously tested through large, randomized, controlled clinical trials.

Conclusion

Pharmacotherapy, both ocular and systemic, will be the primary mode of intervention in the management of DR and DME in many cases when cost and treatment burden are less constrained. Conventional laser therapy has become a secondary intervention in these instances, but remains a first-line option when cost and treatment burden are more constrained. Results with subthreshold laser appear promising but will require more rigorous study to establish its role as adjunctive therapy. Evidence to support an optimal integration of the various treatment options is lacking. Central to the widespread adoption of any therapeutic regimen for DR and DME is substantiation of safety, efficacy, and cost-effectiveness by a body of sound clinical trials.

Quantitative optical coherence tomography angiography: A review

As a new optical coherence tomography (OCT) modality, OCT angiography (OCTA) provides a noninvasive method to detect microvascular distortions correlated with eye conditions. By providing unparalleled capability to differentiate individual plexus layers in the retina, OCTA has demonstrated its excellence in clinical management of diabetic retinopathy, glaucoma, sickle cell retinopathy, diabetic macular edema, and other eye diseases. Quantitative OCTA analysis of retinal and choroidal vasculatures is essential to standardize objective interpretations of clinical outcome. Quantitative features, including blood vessel tortuosity, blood vessel caliber, blood vessel density, vessel perimeter index, fovea avascular zone area, fovea avascular zone contour irregularity, vessel branching coefficient, vessel branching angle, branching width ratio, and choroidal vascular analysis have been established for objective OCTA assessment. Moreover, differential artery–vein analysis has been recently demonstrated to improve OCTA performance for objective detection and classification of eye diseases. In this review, technical rationales and clinical applications of these quantitative OCTA features are summarized, and future prospects for using these quantitative OCTA features for artificial intelligence classification of eye conditions are discussed.

An optical coherence tomography-based grading of diabetic maculopathy proposed by an international expert panel: The European School for Advanced Studies in Ophthalmology classification

AIMS

To present an authoritative, universal, easy-to-use morphologic classification of diabetic maculopathy based on spectral domain optical coherence tomography.

METHODS

The first draft of the project was developed based on previously published classifications and a literature search regarding the spectral domain optical coherence tomography quantitative and qualitative features of diabetic maculopathy. This draft was sent to an international panel of retina experts for a first revision. The panel met at the European School for Advanced Studies in Ophthalmology headquarters in Lugano, Switzerland, and elaborated the final document.

RESULTS

Seven tomographic qualitative and quantitative features are taken into account and scored according to a grading protocol termed TCED-HFV, which includes foveal thickness (T), corresponding to either central subfoveal thickness or macular volume, intraretinal cysts (C), the ellipsoid zone (EZ) and/or external limiting membrane (ELM) status (E), presence of disorganization of the inner retinal layers (D), number of hyperreflective foci (H), subfoveal fluid (F), and vitreoretinal relationship (V). Four different stages of the disease, that is, early diabetic maculopathy, advanced diabetic maculopathy, severe diabetic maculopathy, and atrophic maculopathy, are based on the first four variables, namely the T, C, E, and D. The different stages reflect progressive severity of the disease.

CONCLUSION

A novel grading system of diabetic maculopathy is hereby proposed. The classification is aimed at providing a simple, direct, objective tool to classify diabetic maculopathy (irrespective to the treatment status) even for non-retinal experts and can be used for therapeutic and prognostic purposes, as well as for correct evaluation and reproducibility of clinical investigations.

Angiopoietin-like 4 binds neuropilins and cooperates with VEGF to induce diabetic macular edema

The majority of patients with diabetic macular edema (DME), the most common cause of vision loss in working-age Americans, do not respond adequately to current therapies targeting VEGFA. Here, we show that expression of angiopoietin-like 4 (ANGPTL4), a HIF-1-regulated gene product, is increased in the eyes of diabetic mice and patients with DME. We observed that ANGPTL4 and VEGF act synergistically to destabilize the retinal vascular barrier. Interestingly, while ANGPTL4 modestly enhanced tyrosine phosphorylation of VEGF receptor 2, promotion of vascular permeability by ANGPTL4 was independent of this receptor. Instead, we found that ANGPTL4 binds directly to neuropilin 1 (NRP1) and NRP2 on endothelial cells (ECs), leading to rapid activation of the RhoA/ROCK signaling pathway and breakdown of EC-EC junctions. Treatment with a soluble fragment of NRP1 (sNRP1) prevented ANGPTL4 from binding to NRP1 and blocked ANGPTL4-induced activation of RhoA as well as EC permeability in vitro and retinal vascular leakage in diabetic animals in vivo. In addition, sNRP1 reduced the stimulation of EC permeability by aqueous fluid from patients with DME. Collectively, these data identify the ANGPTL4/NRP/RhoA pathway as a therapeutic target for the treatment of DME.

Optical coherence tomography angiography and arterial hypertension: A role in identifying subclinical microvascular damage?

INTRODUCTION

To evaluate retinal microvasculature modifications by means of optical coherence tomography angiography in human subjects diagnosed with arterial hypertension and to assess potential clinical relevance for early diagnosis.

METHODS

A cross-sectional study of 30 subjects affected by arterial hypertension compared to a matched cohort of healthy patients was conducted. Patients were evaluated by the Outpatient Clinic for Hypertension and the Retina Center, University of Insubria, Varese, Italy. Patients were divided into three groups: Group 1-healthy subjects, Group 2-patients first diagnosed with hypertension, and Group 3-patients with treated hypertension. Optical coherence tomography angiography was performed applying different analysis protocols for macula and optic disk, using an AngioVue OCTA System on an Optovue device. Morphological data were compared to and correlated with clinical vascular parameters, to evaluate preclinical microvascular damage.

RESULTS

A significant reduction in deep vascular layer density (Group 1: 59.2% ± 1.5% standard deviation; Group 2: 59.2% ± 2.2% standard deviation; Group 3: 57.8% ± 2.6% standard deviation; p < 0.05) as well as an enlargement of the deep foveal avascular zone area (Group 1: 0.34 ± 0.09 mm²; Group 2: 0.36 ± 0.07 mm²; Group 3: 0.39 ± 0.1 mm²; p < 0.05) was measured in patients with first diagnosed hypertension and in treated patients compared to healthy subjects. We also observed a significant decrease in mean foveal choroidal thickness in affected patients compared to controls (Group 1: 319.68 ± 61.72 µm standard deviation; Group 2: 251.04 ± 63.1 µm standard deviation; Group 3: 262.65 ± 51.08 µm standard deviation; p < 0.05). Our preliminary data did not show a significant correlation with microalbuminuria levels.

DISCUSSION

Retinal vascular density showed pathological modifications between healthy subjects and hypertensive patients. These preliminary findings suggest that optical coherence tomography angiography may identify pathological markers of an early hypertensive damage and help monitor disease progression with potential therapeutic advantages.

Future clinical applicability of optical coherence tomography angiography

Optical coherence tomography angiography (OCT-A) is an emerging technology that allows for the non-invasive imaging of the ocular microvasculature. Despite the wealth of observations and numerous research studies illustrating the potential clinical uses of OCT-A, this technique is currently rarely used in routine clinical settings. In this review, technical and clinical aspects of OCT-A imaging are discussed, and the future clinical potential of OCT-A is considered. An understanding of the basic principles and limitations of OCT-A technology will better inform clinicians of its future potential in the diagnosis and management of ocular diseases.

VALUE OF FRACTAL ANALYSIS OF OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IN VARIOUS STAGES OF DIABETIC RETINOPATHY

PURPOSE

To use fractal dimensional analysis to investigate retinal vascular disease patterns in patients with diabetic retinopathy using spectral domain optical coherence tomography angiography.

METHODS

A retrospective study was conducted which included 49 eyes from 26 control subjects and 58 eyes from 35 patients known to have diabetic retinopathy. Of the 58 eyes with known retinopathy, 31 were categorized as nonproliferative diabetic retinopathy (13 mild, 9 moderate, and 9 severe) and 27 were categorized as proliferative diabetic retinopathy. Optical coherence tomography angiography images were acquired using the RTVue XR Avanti (Optovue, Inc). Automated segmentation was obtained through both the superficial and deep capillary plexuses for each eye. Grayscale optical coherence tomography angiography images were standardized and binarized using ImageJ (National Institutes of Health). Fractal box-counting analyses were conducted using Fractalyse (ThéMA). Fractal dimensions (FDs) and correlation coefficient of the superficial and deep capillary plexuses were compared between control eyes and those in various stages of diabetic retinopathy.

RESULTS

The superficial and deep capillary plexuses from diabetic and control eyes were analyzed. The average FD for diabetic eyes was significantly lower than in control eyes in the superficial plexus (P = 2.4 × 10) and in the deep capillary plexus (P = 1.87 × 10 ) with a more statistically significant difference noted in the deep capillary plexus. When analyzing diabetic patients without edema noted on optical coherence tomography, the FD was significantly reduced in the superficial (P = 0.001) and deep (P = 1.49 × 10) plexuses. When analyzing diabetic patients with edema noted on optical coherence tomography, the FD was significantly reduced in the superficial (P = 2.0 × 10) and deep (P = 1.85 × 10) plexuses.

CONCLUSION

The optical coherence tomography angiography FD is significantly lower in both superficial and deep capillary plexuses in eyes with all stages studied of diabetic retinopathy. The results were more often significant for the deep capillary plexus. The use of fractal analysis provides an objective criterion to assess microvascular disease burden in diabetic retinopathy.

EFFECT OF OPTIC DISK-FOVEA DISTANCE ON MEASUREMENTS OF INDIVIDUAL MACULAR INTRARETINAL LAYERS IN NORMAL SUBJECTS

PURPOSE

To investigate the effect of optic disk-fovea distance (DFD) on measurements of macular intraretinal layers using spectral domain optical coherence tomography in normal subjects.

METHODS

One hundred and eighty-two eyes from 182 normal subjects were imaged using spectral domain optical coherence tomography. The average thicknesses of eight macular intraretinal layers were measured using an automatic segmentation algorithm. Partial correlation test and multiple regression analysis were used to determine the effect of DFD on thicknesses of intraretinal layers.

RESULTS

Disk-fovea distance correlated negatively with the overall average thickness in all the intraretinal layers (r ≤ -0.17, all P ≤ 0.025) except the ganglion cell layer and photoreceptor. In multiple regression analysis, greater DFD was associated with thinner nerve fiber layer (6.78 μm decrease per each millimeter increase in DFD, P < 0.001), thinner ganglion cell-inner plexiform layer (2.16 μm decrease per each millimeter increase in DFD, P = 0.039), thinner ganglion cell complex (8.94 μm decrease per each millimeter increase in DFD, P < 0.001), thinner central macular thickness (18.16 μm decrease per each millimeter increase in DFD, P < 0.001), and thinner total macular thickness (15.94 μm decrease per each millimeter increase in DFD, P < 0.001).

CONCLUSION

Thinner measurements of macular intraretinal layers were significantly associated with greater DFD. A clinical assessment of macular intraretinal layers in the evaluation of various macular diseases should always be interpreted in the context of DFD.

Qualitative and quantitative assessment of posterior segment optical coherence tomography images using standard photos: the Liwan Eye Study

BACKGROUND/AIMS

To develop a standardised grading scheme, using standard photos, for spectral-domain ocular coherence tomography (SD-OCT) images of the posterior eye and evaluate the interobserver agreement among trained ophthalmologists in identifying pathological changes.

METHODS

Subjects were recruited from Liwan District, Guangzhou, with SD-OCT data collection from June 2013 to November 2013 as part of 10-year follow-up visits from the Liwan Eye Study. All subjects underwent SD-OCT imaging of the macula with scanning lines analysed by two ophthalmologists to assess for the presence of 12 different posterior segment lesions. Per cent agreement for each lesion between the graders and quantitative measures of dome-shaped macula (DSM) height and choroidal thickness were calculated.

RESULTS

A total of 679 SD-OCT images from 679 subjects were independently evaluated by the two graders. Each of the 12 lesions was successfully graded as present or absent in over 96% of images. For all lesions, per cent agreement between observers was over 90%, ranging from 90.7% for epiretinal membranes and retinal pigment epithelium thickenings to 99.7% for full thickness macular holes and retinal detachments. Quantitative measurements of DSM height and choroidal thickness at three locations of the eye all exhibited intraclass correlation scores between the two graders of greater than 0.9.

CONCLUSION

Our study demonstrates high concordance between graders in characterising posterior segment lesions using SD-OCT images, validating the continued use of this imaging modality in the diagnosis of posterior eye disease.

Macular Choroidal Thickness May Be the Earliest Determiner to Detect the Onset of Diabetic Retinopathy in Patients with Prediabetes: A Prospective and Comparative Study

PURPOSE

To evaluate the macular and peripapillary choroidal thickness and retinal volume in prediabetes.

MATERIAL AND METHODS

This prospective comparative study included 53 patients with prediabetes and 53 age- and sex-matched healthy subjects. Only right eyes were selected. Choroidal thicknesses (CT) and retinal volume were measured by optical coherence tomography. Macular CT was measured at the seven points including macular center, 1, 2, and 3 mm distances along the temporal and nasal scans. Peripapillary CT was measured at the eight points of the optic disk area. Systemic and laboratory findings of the subjects were also recorded.

RESULTS

There were no significant differences in blood pressures, ocular findings including intraocular pressure, visual acuity, and refractive powers, and macular volumes between the two groups (p > 0.005). Macular and peripapillary CT at all measuring points, body mass index (BMI), fasting blood glucose (FBG), hemoglobinA1C, and lipid profile were significantly higher in prediabetic patients (p < 0.05). There was a significant positive correlation between all points of macular choroidal thicknesses with BMI, FBG, and hemoglobin A1C (p < 0.05).

CONCLUSION

Prediabetic factors including impaired FBG, increased hemoglobinA1C, and BMI are independent risk factors for increase in choroidal thickness. Increased macular choroidal thickness may be the earliest determiner to detect the onset of diabetic retinopathy in prediabetes.