Signal attenuation-compensated projection-resolved OCT angiography

Nonperfused Retinal Capillaries-A New Method Developed on OCT and OCTA

Purpose

This study aims to develop a new method to quantify nonperfused retinal capillaries (NPCs) and evaluate NPCs in eyes with AMD and diabetic retinopathy (DR).

Methods

We averaged multiple registered optical coherence tomography (OCT)/OCT angiography (OCTA) scans to create high-definition volumes. The deep capillary plexus slab was defined and segmented. A developed deep learning denoising algorithm removed tissue background noise from capillaries in en face OCT/OCTA. The algorithm segmented NPCs by identifying capillaries from OCT without corresponding flow signals in OCTA. We then investigated the relationships between NPCs and known features in AMD and DR.

Results

The segmented NPC achieved an accuracy of 88.2% compared to manual grading of NPCs in DR. Compared to healthy controls, both the mean number and total length (mm) of NPCs was significantly increased in AMD and DR eyes (P < 0.001, P < 0.001). Compared to early and intermediate AMD, the number and total length of NPCs were significantly higher in advanced AMD (number: P < 0.001, P < 0.001; total length: P = 0.002, P = 0.003). Geography atrophy, macular neovascularization, drusen volume, and extrafoveal avascular area (EAA) significantly correlated with increased NPCs (P < 0.05). In DR eyes, NPCs correlated with the number of microaneurysms and EAA (P < 0.05). The presence of fluid did not significantly correlate with NPCs in AMD and DR.

Conclusions

A deep learning-based algorithm can segment and quantify retinal capillaries that lack flow using colocalized OCT/OCTA. This new biomarker may be useful in AMD and DR in predicting progression of these diseases.

Detection of Macular Neovascularization in Eyes Presenting with Macular Edema using OCT Angiography and a Deep Learning Model

PURPOSE

To test the diagnostic performance of an artificial intelligence algorithm for detecting and segmenting macular neovascularization (MNV) with OCT and OCT angiography (OCTA) in eyes with macular edema from various diagnoses.

DESIGN

Prospective cross-sectional study.

PARTICIPANTS

Study participants with macular edema due to either treatment-naïve exudative age-related macular degeneration (AMD), diabetic macular edema (DME), or retinal vein occlusion (RVO).

METHODS

Study participants were imaged with macular 3 × 3-mm and 6 × 6-mm spectral-domain OCTA. Eyes with exudative AMD were required to have MNV in the central 3 × 3-mm area. A previously developed hybrid multitask convolutional neural network for MNV detection (aiMNV), and segmentation was applied to all images, regardless of image quality.

MAIN OUTCOME MEASURES

Sensitivity, specificity, positive predictive value, and negative predictive value of detecting MNV and intersection over union (IoU) score and F1 score for segmentation.

RESULTS

Of 114 eyes from 112 study participants, 56 eyes had MNV due to exudative AMD and 58 eyes with macular edema due to either DME or RVO. The 3 × 3-mm OCTA scans with aiMNV detected MNV with 96.4% sensitivity, 98.3% specificity, 98.2% positive predictive value, and 96.6% negative predictive value. For segmentation, the average IoU score was 0.947, and the F1 score was 0.973. The 6 × 6-mm scans performed well; however, sensitivity for MNV detection was lower than 3 × 3-mm scans due to lower scan sampling density.

CONCLUSIONS

This novel aiMNV algorithm can accurately detect and segment MNV in eyes with exudative AMD from a control group of eyes that present with macular edema from either DME or RVO. Higher scan sampling density improved the aiMNV sensitivity for MNV detection.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Artificial Intelligence Versus Rules-Based Approach for Segmenting NonPerfusion Area in a DRCR Retina Network Optical Coherence Tomography Angiography Dataset

Purpose

Loss of retinal perfusion is associated with both onset and worsening of diabetic retinopathy (DR). Optical coherence tomography angiography is a noninvasive method for measuring the nonperfusion area (NPA) and has promise as a scalable screening tool. This study compares two optical coherence tomography angiography algorithms for quantifying NPA.

Methods

Adults with (N = 101) and without (N = 274) DR were recruited from 20 U.S. sites. We collected 3 × 3-mm macular scans using an Optovue RTVue-XR. Rules-based (RB) and deep-learning-based artificial intelligence (AI) algorithms were used to segment the NPA into four anatomical slabs. For comparison, a subset of scans (n = 50) NPA was graded manually.

Results

The AI method outperformed the RB method in intersection over union, recall, and F1 score, but the RB method has better precision relative to manual grading in all anatomical slabs (all P ≤ 0.001). The AI method had a stronger rank correlation with Early Treatment of Diabetic Retinopathy Study DR severity than the RB method in all slabs (all P < 0.001). NPAs graded using the AI method had a greater area under the receiver operating characteristic curve for diagnosing referable DR than the RB method in the superficial vascular complex, intermediate capillary plexus, and combined inner retina (all P ≤ 0.001), but not in the deep capillary plexus (P = 0.92).

Conclusions

Our results indicate that output from the AI-based method agrees better with manual grading and can better distinguish between clinically relevant DR severity levels than a RB approach using most plexuses.

Advances in OCT Angiography

Optical coherence tomography angiography (OCTA) is a signal processing and scan acquisition approach that enables OCT devices to clearly identify vascular tissue down to the capillary scale. As originally proposed, OCTA included several important limitations, including small fields of view relative to allied imaging modalities and the presence of confounding artifacts. New approaches, including both hardware and software, are solving these problems and can now produce high-quality angiograms from tissue throughout the retina and choroid. Image analysis tools have also improved, enabling OCTA data to be quantified at high precision and used to diagnose disease using deep learning models. This review highlights these advances and trends in OCTA technology, focusing on work produced since 2020.

Slab-Specific Projection-Resolved Optical Coherence Tomography Angiography for Enhancing En Face Polyp Detection in Polypoidal Choroidal Vasculopathy

Purpose

A projection-resolved optical coherence tomography angiography (PR-OCTA) algorithm with slab-specific strategy was applied in polypoidal choroidal vasculopathy (PCV) to differentiate between polyp and branching vascular network (BVN) and improve polyp detection by en face OCTA.

Methods

Twenty-nine participants diagnosed with PCV by indocyanine green angiography (ICGA) and 30 participants diagnosed with typical neovascular age-related macular degeneration (nAMD) were enrolled. Polyps were classified into three categories after using the slab-specific PR algorithm. Type 1 polyps were considered in high-elevated pigment epithelial detachment (PED) and displayed in green. Type 2 polyps were considered in low-elevated PED and encoded in yellow, similar to BVN structures. Type 3 polyps were not able to be detected on OCTA. The algorithms were tested in the nAMD group to differentiate PCV and typical nAMD.

Results

With the algorithm, type 1 polyps were readily differentiated from BVN on en face OCTA. Polyp detection rate on en face OCTA only (type 1) was 68%, which was significantly improved from 30% when the algorithm was not used (P = 0.0001). To identify type 2 polyps, a combination of en face and cross-sectional OCTA images was needed and this resulted in a 91% polyp detection rate (types 1 and 2). The absence of luminal structure on OCT at the polyp site, small polyp size, and absence of halo on ICGA appeared to influence the polyp detection rate. When applying the algorithm to the nAMD group, 83% were correctly classified as typical nAMD (absence of type 1 polyps), whereas 17% showed false detection of polyps due to flow signals at the apices of large PEDs.

Conclusions

The slab-specific PR-OCTA with different color coding provides significant improvement in detecting polyp structures on en face OCTA, leading to rapid coronal visualization and diagnosis of PCV without the risk of dye injection.

Optical attenuation coefficient decorrelation-based optical coherence tomography angiography for microvascular evaluation of Alzheimer's disease on mice

Significance

The deep cortical microvasculature is closely linked to the pathogenesis of Alzheimer's disease (AD). However, tail artifacts from superficial cortical vessels often interfere with detecting deep vessels in optical coherence tomography angiography (OCTA) imaging. A more accurate method to assess deep cortical vasculature is crucial for understanding its relationship with AD onset.

Aim

We aim to reduce superficial vessel artifacts in OCTA imaging and improve the visualization and analysis of deep cortical microvasculature in an AD mouse model.

Approach

We introduced the optical attenuation coefficient decorrelation (OACD) method for OCTA, effectively reducing tail artifacts from superficial cortex vessels. This method was used to visualize and quantitatively analyze deep cortical microvasculature in vivo in a mouse model of AD.

Results

The OACD method significantly reduced superficial vessel artifacts, leading to clearer imaging of the deep cortical vasculature. Quantitative analysis revealed that changes in the deep cortical microvasculature were more pronounced than in the superficial vasculature, suggesting a more direct involvement of the deep vessels in AD progression.

Conclusions

The proposed OACD method enhances OCTA imaging by reducing tail artifacts from superficial vessels, facilitating improved assessment of deep cortical microvasculature. These findings suggest that deep cortical vascular changes may play a key role in the pathogenesis of AD, offering potential insights for early detection and monitoring of AD progression.

Visualizing features with wide-field volumetric OCT angiography

Optical coherence tomography (OCT) and its extension OCT angiography (OCTA) have become essential clinical imaging modalities due to their ability to provide depth-resolved angiographic and tissue structural information non-invasively and at high resolution. Within a field of view, the anatomic detail available is sufficient to identify several structural and vascular pathologies that are clinically relevant for multiple prevalent blinding diseases, including age-related macular degeneration (AMD), diabetic retinopathy (DR), and vein occlusions. The main limitation in contemporary OCT devices is that this field of view is limited due to a fundamental trade-off between system resolution/sensitivity, sampling density, and imaging window dimensions. Here, we describe a swept-source OCT device that can capture up to a 12 × 23-mm field of view in a single shot and show that it can identify conventional pathologic features such as non-perfusion areas outside of conventional fields of view. We also show that our approach maintains sensitivity sufficient to visualize novel features, including choriocapillaris morphology beneath the macula and macrophage-like cells at the inner limiting membrane, both of which may have implications for disease.

Optical coherence tomography angiography of choroidal neovascularization in long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHADD)

Purpose

To report the clinical utility of optical coherence tomography angiography (OCTA) for demonstrating choroidal neovascularization (CNV) associated with Long-Chain 3-Hydroxyacyl-CoA Dehydrogenase Deficiency (LCHADD) retinopathy.

Methods

Thirty-three participants with LCHADD (age 7-36 years; median 17) were imaged with OCTA and the Center for Ophthalmic Optics & Lasers Angiography Reading Toolkit (COOL-ART) software was implemented to process OCTA scans.

Results

Seven participants (21 %; age 17-36 years; median 25) with LCHADD retinopathy demonstrated evidence of CNV by retinal examination or presence of CNV within outer retinal tissue on OCTA scans covering 3 × 3 and/or 6 × 6-mm. These sub-clinical CNVs are adjacent to hyperpigmented areas in the posterior pole. CNV presented at stage 2 or later of LCHADD retinopathy prior to the disappearance of RPE pigment in the macula.

Conclusion

OCTA can be applied as a non-invasive method to evaluate the retinal and choroidal microvasculature. OCTA can reveal CNV in LCHADD even when the clinical exam is inconclusive. These data suggest that the incidence of CNV is greater than expected and can occur even in the early stages of LCHADD retinopathy.

30 Years of Optical Coherence Tomography: introduction to the feature issue

The guest editors introduce a feature issue commemorating the 30th anniversary of Optical Coherence Tomography.

OCT angiography and its retinal biomarkers [Invited]

Optical coherence tomography angiography (OCTA) is a high-resolution, depth-resolved imaging modality with important applications in ophthalmic practice. An extension of structural OCT, OCTA enables non-invasive, high-contrast imaging of retinal and choroidal vasculature that are amenable to quantification. As such, OCTA offers the capability to identify and characterize biomarkers important for clinical practice and therapeutic research. Here, we review new methods for analyzing biomarkers and discuss new insights provided by OCTA.

Introduction to Visual and Physiological Optics feature issue of Biomedical Optics Express and JOSA A

This feature issue collects articles presented at the tenth Visual and Physiological Optics meeting (VPO2022), held August 29-31, 2022, in Cambridge, UK. This joint feature issue between Biomedical Optics Express and Journal of the Optical Society of America A includes articles that cover the broad range of topics addressed at the meeting and examples of the current state of research in the field.

Visual and Physiological Optics: introduction to the joint feature issue in Biomedical Optics Express and Journal of the Optical Society of America A

This feature issue collects articles presented at the tenth Visual and Physiological Optics meeting (VPO2022), held August 29-31, 2022, in Cambridge, UK. This joint feature issue between Biomedical Optics Express and Journal of the Optical Society of America A includes articles that cover the broad range of topics addressed at the meeting and examples of the current state of research in the field.