Macular, papillary and peripapillary perfusion densities measured with optical coherence tomography angiography in primary open angle glaucoma and pseudoexfoliation glaucoma

Purpose: To compare the blood flow situation in primary open-angle glaucoma (POAG) and pseudoexfoliation glaucoma (PXG) using optical coherence tomography angiography (OCTA). Methods: In this prospective study a total of 26 POAG and 23 PXG eyes were included. All patients underwent a complete ophthalmological examination including standard automated perimetry, stereoscopic photographs of the optic disc, peripapillary retinal nerve fibre layer analysis and examination of vascular parameters of the optic nerve head (ONH), the peripapillary region and macula using OCTA. In addition to the vascular parameters recorded by the device, the vascular images were graphically evaluated using Image J. All recorded vascular parameters were compared between both groups and correlated to structural and functional parameters. Results: The mean superficial perifoveal plexus perfusion density (PD) was significantly lower in PXG eyes than compared to POAG eyes using OCTA (32.57% +/- 3.57% vs. 34.92% +/- 2.11%, p = 0.007). The mean PD parameters for the superficial peripapillary plexus (40.98% +/- 3.04% vs. 42.09% +/- 2.29%, p = 0.152) as well as the size of the foveal avascular zone (FAZ) (0.23 mm(2) +/- 0.1 mm(2) vs. 0.23 mm(2) +/- 0.09 mm(2)) did not differ between both groups. Additional graphic evaluation using Image J showed no significant difference for superficial perifoveal plexus PD (32.97% +/- 1.11% vs. 33.35% +/- 0.95%, p = 0.194) and peripapillary plexus PD (46.65% +/- 0.83% vs. 46.95% +/- 0.5%, p = 0.127) between the groups. Retinal nerve fibre layer (RNFL) thickness correlated significantly with peripapillary plexus PD for both OCTA data and Image J data (p < 0.001, p = 0.032). Conclusion: The severity of the glaucoma seems to be crucial for peripapillary and macular perfusion densities, and not the form of glaucoma. An additional graphic evaluation is a possible step that could be implemented to improve the comparability of OCTA scans and to optimize the possibility of quantitative perfusion analysis in the case of deviating quality criteria

Predicting wet age-related macular degeneration (AMD) using DARC (detecting apoptosing retinal cells) AI (artificial intelligence) technology

Objectives: To assess a recently described CNN (convolutional neural network) DARC (Detection of Apoptosing Retinal Cells) algorithm in predicting new Subretinal Fluid (SRF) formation in Age-related-Macular-Degeneration (AMD). Methods: Anonymized DARC, baseline and serial OCT images (n = 427) from 29 AMD eyes of Phase 2 clinical trial (ISRCTN10751859) were assessed with CNN algorithms, enabling the location of each DARC spot on corresponding OCT slices (n = 20,629). Assessment of DARC in a rabbit model of angiogenesis was performed in parallel. Results: A CNN DARC count >5 at baseline was significantly (p = 0.0156) related to development of new SRF throughout 36 months. Prediction rate of eyes using unique DARC spots overlying new SRF had positive predictive values, sensitivities and specificities >70%, with DARC count significantly (p < 0.005) related to the magnitude of SRF accumulation at all time points. DARC identified earliest stages of angiogenesis in-vivo. Conclusions: DARC was able to predict new wet-AMD activity. Using only an OCT-CNN definition of new SRF, we demonstrate that DARC can identify early endothelial neovascular activity, as confirmed by rabbit studies. Although larger validation studies are required, this shows the potential of DARC as a biomarker of wet AMD, and potentially saving vision-loss

Optic nerve head perfusion changes in eyes with proliferative diabetic retinopathy treated with intravitreal ranibizumab or photocoagulation: a randomized controlled trial

Background:&nbsp;Proliferative diabetic retinopathy (PDR) is a serious sight-threatening disease, and half of the patients with high-risk PDR can develop legal blindness within 5 years, if left untreated.&nbsp;This study was aimed at comparing panretinal photocoagulation (PRP) and intravitreal ranibizumab injections in terms of radial peripapillary capillary (RPC) density on optical coherence tomography angiography (OCTA) in patients with treatment-naive PDR.&nbsp; Methods:&nbsp;This open-label, prospective, randomized clinical trial&nbsp;included 50 patients with treatment-naive PDR with optic disc neovascularization and randomized them into two groups: group 1, with patients undergoing two sessions of PRP 2 weeks apart, and group 2, with patients received three intravitreal ranibizumab injections (0.5 mg) 1 month apart for 3 consecutive months. Patients underwent a full ophthalmological examination, including best-corrected distance visual acuity (BCDVA) measurement in the logarithm of minimal angle of resolution (logMAR) notation and OCTA before intervention and monthly after the last laser session or the first intravitreal ranibizumab injection for 3 months of follow-up. Visual field (VF) was tested at the beginning and end of 3 months. &nbsp; Results: Forty-two (84%) eyes completed the 3-month follow-up, including 22 eyes in the PRP group (88%) and 20 (80%) eyes in the ranibizumab group. The two groups were comparable in terms of demographic characteristics, diabetes duration, baseline BCDVA, glycated hemoglobin level, OCTA parameters, VF indices, and intraocular pressure (all P &gt; 0.05). The RPC density change from baseline to the 3-month follow-up was significantly lower in the PRP group than in the ranibizumab group (mean difference in RPC density change: - 3.61%; 95% confidence interval: - 5.57% to - 1.60%; P = 0.001). The median (interquartile range) logMAR change from baseline to the 3-month follow-up (0.0 [0.2]) was significantly higher in the PRP group than in the ranibizumab group (- 0.15 [0.3]; P &lt; 0.05). The median changes in central foveal thickness from baseline to the 3-month follow-up differed significantly between the two groups (P = 0.001). Conclusions: In eyes with PDR and neovascularization of the disc RPC density on OCTA increased in the ranibizumab group and decreased in the PRP group. Visual acuity gain was higher in the ranibizumab group than in the PRP group. Future multicenter trials addressing our limitations are required to verify the findings of this study

A Survey on Automated Diagnosis of Alzheimer's Disease Using Optical Coherence Tomography and Angiography

Retinal optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) are promising tools for the (early) diagnosis of Alzheimer's disease (AD). These non-invasive imaging techniques are cost-effective and more accessible than alternative neuroimaging tools. However, interpreting and classifying multi-slice scans produced by OCT devices is time-consuming and challenging even for trained practitioners. There are surveys on machine learning and deep learning approaches concerning the automated analysis of OCT scans for various diseases such as glaucoma. However, the current literature lacks an extensive survey on the diagnosis of Alzheimer's disease or cognitive impairment using OCT or OCTA. This has motivated us to do a comprehensive survey aimed at machine/deep learning scientists or practitioners who require an introduction to the problem. The paper contains 1) an introduction to the medical background of Alzheimer's Disease and Cognitive Impairment and their diagnosis using OCT and OCTA imaging modalities, 2) a review of various technical proposals for the problem and the sub-problems from an automated analysis perspective, 3) a systematic review of the recent deep learning studies and available OCT/OCTA datasets directly aimed at the diagnosis of Alzheimer's Disease and Cognitive Impairment. For the latter, we used Publish or Perish Software to search for the relevant studies from various sources such as Scopus, PubMed, and Web of Science. We followed the PRISMA approach to screen an initial pool of 3073 references and determined ten relevant studies (N=10, out of 3073) that directly targeted AD diagnosis. We identified the lack of open OCT/OCTA datasets (about Alzheimer's disease) as the main issue that is impeding the progress in the field.Comment: Submitted to Computerized Medical Imaging and Graphics. Concept, methodology, invest, data curation, and writing org.draft by Yasemin Turkan. Concept, method, writing review editing, and supervision by F. Boray Te

A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography

The assessment of vascular biomarkers and their correlation with visual acuity is one of the most important issues in the diagnosis and follow-up of retinal vein occlusions (RVOs). The high workloads of clinical practice make it necessary to have a fast, objective, and automatic method to analyze image features and correlate them with visual function. The aim of this study is to propose a fully automatic system which is capable of estimating visual acuity (VA) in RVO eyes, based only on information obtained from macular optical coherence tomography angiography (OCTA) images. We also propose an automatic methodology to rapidly measure the foveal avascular zone (FAZ) area and the vascular density (VD) in the superficial and deep capillary plexuses in swept-source OCTA images centered on the fovea. The proposed methodology is validated using a representative sample of 133 visits of 50 RVO patients. Our methodology estimates VA with very high precision and is even more accurate when we integrate depth information, providing a high correlation index of 0.869 with the real VA, which outperforms the correlation index of 0.855 obtained when estimating VA from the data obtained by the semiautomatic existing method. In conclusion, the proposed method is the first computational system able to estimate VA in RVO, with the additional benefits of being automatic, less time-consuming, objective and more accurate. Furthermore, the proposed method is able to integrate depth information, a feature which is lacking in the existing methodThis work has received partial financial support from the Mutua Madrileña project, Ref. 2017/365S

Digital ocular fundus imaging: a review

Ocular fundus imaging plays a key role in monitoring the health status of the human eye. Currently, a large number of imaging modalities allow the assessment and/or quantification of ocular changes from a healthy status. This review focuses on the main digital fundus imaging modality, color fundus photography, with a brief overview of complementary techniques, such as fluorescein angiography. While focusing on two-dimensional color fundus photography, the authors address the evolution from nondigital to digital imaging and its impact on diagnosis. They also compare several studies performed along the transitional path of this technology. Retinal image processing and analysis, automated disease detection and identification of the stage of diabetic retinopathy (DR) are addressed as well. The authors emphasize the problems of image segmentation, focusing on the major landmark structures of the ocular fundus: the vascular network, optic disk and the fovea. Several proposed approaches for the automatic detection of signs of disease onset and progression, such as microaneurysms, are surveyed. A thorough comparison is conducted among different studies with regard to the number of eyes/subjects, imaging modality, fundus camera used, field of view and image resolution to identify the large variation in characteristics from one study to another. Similarly, the main features of the proposed classifications and algorithms for the automatic detection of DR are compared, thereby addressing computer-aided diagnosis and computer-aided detection for use in screening programs.Fundação para a Ciência e TecnologiaFEDErPrograma COMPET

A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography

[Abstract] The assessment of vascular biomarkers and their correlation with visual acuity is one of the most important issues in the diagnosis and follow-up of retinal vein occlusions (RVOs). The high workloads of clinical practice make it necessary to have a fast, objective, and automatic method to analyze image features and correlate them with visual function. The aim of this study is to propose a fully automatic system which is capable of estimating visual acuity (VA) in RVO eyes, based only on information obtained from macular optical coherence tomography angiography (OCTA) images. We also propose an automatic methodology to rapidly measure the foveal avascular zone (FAZ) area and the vascular density (VD) in the superficial and deep capillary plexuses in swept-source OCTA images centered on the fovea. The proposed methodology is validated using a representative sample of 133 visits of 50 RVO patients. Our methodology estimates VA with very high precision and is even more accurate when we integrate depth information, providing a high correlation index of 0.869 with the real VA, which outperforms the correlation index of 0.855 obtained when estimating VA from the data obtained by the semiautomatic existing method. In conclusion, the proposed method is the first computational system able to estimate VA in RVO, with the additional benefits of being automatic, less time-consuming, objective and more accurate. Furthermore, the proposed method is able to integrate depth information, a feature which is lacking in the existing method.Mutua Madrileña; 2017/365

Optical coherence tomography angiography

Optical coherence tomography (OCT) was one of the biggest advances in ophthalmic imaging. Building on that platform, OCT angiography (OCTA) provides depth resolved images of blood flow in the retina and choroid with levels of detailed far exceeding that obtained with older forms of imaging. This new modality is challenging because of the need for new equipment and processing techniques, current limitations of imaging capability, and rapid advancements in both imaging and in our understanding of the imaging and applicable pathophysiology of the retina and choroid, and the requirement for understanding the origins of image artifacts. These factors lead to a steep learning curve, even for those with a working understanding dye-based ocular angiography. All for a method of imaging that is a little more than 10 years old. This review begins with a historical account of the development of OCTA, and the methods used in OCTA, including signal processing, image generation, and display techniques. This forms the basis to understand what OCTA images show as well as how image artifacts arise. The anatomy and imaging of specific vascular layers of the eye are reviewed. The integration of OCTA in multimodal imaging in the evaluation of retinal vascular occlusive diseases, diabetic retinopathy, uveitis, inherited diseases, age-related macular degeneration, and disorders of the optic nerve is presented. OCTA is an exciting, disruptive technology. Its use is rapidly expanding in clinical practice as well as for research into the pathophysiology of diseases of the posterior pole

OCTA multilayer and multisector peripapillary microvascular modeling for diagnosing and staging of glaucoma

Purpose: To develop and assess an automatic procedure for classifying and staging glaucomatous vascular damage based on optical coherence tomography angiography (OCTA) imaging. Methods: OCTA scans (Zeiss Cirrus 5000 HD-OCT) from a random eye of 39 healthy subjects and 82 glaucoma patients were used to develop a new classification algorithm based on multilayer and multisector information. The averaged circumpapillary retinal nerve fiber layer (RNFL) thickness was also collected. Three models, support vector machine (SVM), random forest (RF), and gradient boosting (xGB), were developed and optimized for classifying between healthy and glaucoma patients, primary open-angle glaucoma (POAG) and normal-tension glaucoma (NTG), and glaucoma severity groups. Results: All the models, the SVM (area under the receiver operating characteristic [AUROC] 0.89 ± 0.06), the RF (AUROC 0.86 ± 0.06), and the xGB (AUROC 0.85 ± 0.07), with 26, 22, and 29 vascular features obtained after feature selection, respectively, presented a similar performance to the RNFL thickness (AUROC 0.85± 0.06) in classifying healthy and glaucoma patients. The superficial vascular plexus was the most informative layer with the infero temporal sector as the most discriminative region of interest. No significant differentiation was obtained in discriminating the POAG from the NTG group. The xGB model, after feature selection, presented the best performance in classifying the severity groups (AUROC 0.76± 0.06), outperforming the RNFL (AUROC 0.67± 0.06). Conclusions: OCTA multilayer and multisector information has similar performance to RNFL for glaucoma diagnosis, but it has an added value for glaucoma severity classification, showing promising results for staging glaucoma progression. Translational Relevance: OCTA, in its current stage, has the potential to be used in clinical practice as a complementary imaging technique in glaucoma management