Morphometry of the trabecular meshwork in vivo in a healthy population using fourier-domain optical coherence tomography

PURPOSE. We measured the length, thickness, and area of the trabecular meshwork (TM) in vivo using Fourier domain optical coherence tomography (FD-OCT) in a Caucasian population of healthy subjects. METHODS. A cross-sectional study was done of 1006 healthy subjects. Left eyes were randomly selected. Age, sex, IOP, and spherical refractive error were noted. The depth and volume of the anterior chamber and the central corneal thickness were measured with Pentacam, while IOL Master was used to measure the axial length. The length, thickness, and area of the TM were measured through FD-OCT RTVue. A study was done to determine the correlation between TM size, and other demographic and ocular parameters. Finally, the reproducibility of the measurements was assessed for a subgroup of 50 eyes from 50 patients. RESULTS. We were able to measure the TM in 91.1% of the total eyes studied. The mean TM length was 496.99 6 92.77 lm (range, 275–800), TM thickness was 174.16 6 28.14 lm (range, 100–276), and TM area was 0.069 6 0.031 mm2 (range, 0.023–0.133). No differences were found in terms of length and area for sex, although the TM was slightly thicker in men (P ¼ 0.046). No correlation was observed between the TM measurements and any of the studied demographic or ocular parameters (R 0.750, P < 0.001). CONCLUSIONS. The FD-OCT is an effective and reproducible examination technique to measure the length, thickness, and area of the TM in vivo

Ciliochoroidal detachment following pure sulfur hexafluoride injection in Descemet stripping automated endothelial keratoplasty

Received 29 October 2016, Accepted 6 March 2017, Available online 20 April 2017Unidad Docente de Inmunología, Oftalmología y ORLFac. de Óptica y OptometríaTRUEinpres

Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning

[Abstract]: Background and Objectives: Age-related macular degeneration (AMD) is a degenerative disorder affecting the macula, a key area of the retina for visual acuity. Nowadays, AMD is the most frequent cause of blindness in developed countries. Although some promising treatments have been proposed that effectively slow down its development, their effectiveness significantly diminishes in the advanced stages. This emphasizes the importance of large-scale screening programs for early detection. Nevertheless, implementing such programs for a disease like AMD is usually unfeasible, since the population at risk is large and the diagnosis is challenging. For the characterization of the disease, clinicians have to identify and localize certain retinal lesions. All this motivates the development of automatic diagnostic methods. In this sense, several works have achieved highly positive results for AMD detection using convolutional neural networks (CNNs). However, none of them incorporates explainability mechanisms linking the diagnosis to its related lesions to help clinicians to better understand the decisions of the models. This is specially relevant, since the absence of such mechanisms limits the application of automatic methods in the clinical practice. In that regard, we propose an explainable deep learning approach for the diagnosis of AMD via the joint identification of its associated retinal lesions. Methods: In our proposal, a CNN with a custom architectural setting is trained end-to-end for the joint identification of AMD and its associated retinal lesions. With the proposed setting, the lesion identification is directly derived from independent lesion activation maps; then, the diagnosis is obtained from the identified lesions. The training is performed end-to-end using image-level labels. Thus, lesion-specific activation maps are learned in a weakly-supervised manner. The provided lesion information is of high clinical interest, as it allows clinicians to assess the developmental stage of the disease. Additionally, the proposed approach allows to explain the diagnosis obtained by the models directly from the identified lesions and their corresponding activation maps. The training data necessary for the approach can be obtained without much extra work on the part of clinicians, since the lesion information is habitually present in medical records. This is an important advantage over other methods, including fully-supervised lesion segmentation methods, which require pixel-level labels whose acquisition is arduous. Results: The experiments conducted in 4 different datasets demonstrate that the proposed approach is able to identify AMD and its associated lesions with satisfactory performance. Moreover, the evaluation of the lesion activation maps shows that the models trained using the proposed approach are able to identify the pathological areas within the image and, in most cases, to correctly determine to which lesion they correspond. Conclusions: The proposed approach provides meaningful information—lesion identification and lesion activation maps—that conveniently explains and complements the diagnosis, and is of particular interest to clinicians for the diagnostic process. Moreover, the data needed to train the networks using the proposed approach is commonly easy to obtain, what represents an important advantage in fields with particularly scarce data, such as medical imaging.Xunta de Galicia; ED481B-2022-025Xunta de Galicia; ED431C 2020/24Xunta de Galicia; IN845D 2020/38Xunta de Galicia; ED481A 2021/140Xunta de Galicia; ED431G 2019/01This work was funded by Instituto de Salud Carlos III, Government of Spain, and the European Regional Development Fund (ERDF) of the European Union (EU) through the DTS18/00136 research project; Ministerio de Ciencia e Innovación, Government of Spain, through RTI2018-095894-B-I00 and PID2019-108435RB-I00 research projects; Axencia Galega de Innovación (GAIN), Xunta de Galicia, ref. IN845D 2020/38; Conselleria de Cultura, Educación e Universidade, Xunta de Galicia, through Grupos de Referencia Competitiva, ref. ED431C 2020/24, the predoctoral grant ref. ED481A 2021/140, and the postdoctoral grant ref. ED481B-2022-025; CITIC, Centro de Investigación de Galicia ref. ED431G 2019/01, is funded by Conselleria de Educación, Universidade e Formación Profesional, Xunta de Galicia, through the ERDF (80%) and Secretaria Xeral de Universidades (20%)

Fully automatic segmentation and monitoring of choriocapillaris flow voids in OCTA images

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG.[Abstract]: Optical coherence tomography angiography (OCTA) is a non-invasive ophthalmic imaging modality that is widely used in clinical practice. Recent technological advances in OCTA allow imaging of blood flow deeper than the retinal layers, at the level of the choriocapillaris (CC), where a granular image is obtained showing a pattern of bright areas, representing blood flow, and a pattern of small dark regions, called flow voids (FVs). Several clinical studies have reported a close correlation between abnormal FVs distribution and multiple diseases, so quantifying changes in FVs distribution in CC has become an area of interest for many clinicians. However, CC OCTA images present very complex features that make it difficult to correctly compare FVs during the monitoring of a patient. In this work, we propose fully automatic approaches for the segmentation and monitoring of FVs in CC OCTA images. First, a baseline approach, in which a fully automatic segmentation methodology based on local contrast enhancement and global thresholding is proposed to segment FVs and measure changes in their distribution in a straightforward manner. Second, a robust approach in which, prior to the use of our segmentation methodology, an unsupervised trained neural network is used to perform a deformable registration that aligns inconsistencies between images acquired at different time instants. The proposed approaches were tested with CC OCTA images collected during a clinical study on the response to photodynamic therapy in patients affected by chronic central serous chorioretinopathy (CSC), demonstrating their clinical utility. The results showed that both approaches are accurate and robust, surpassing the state of the art, therefore improving the efficacy of FVs as a biomarker to monitor the patient treatments. This gives great potential for the clinical use of our methods, with the possibility of extending their use to other pathologies or treatments associated with this type of imaging.Xunta de Galicia; ED481B-2021-059Xunta de Galicia; ED431C 2020/24Xunta de Galicia; IN845D 2020/38Xunta de Galicia; ED431G 2019/01This research was funded by Instituto de Salud Carlos III, Government of Spain, DTS18/00136 research project; Ministerio de Ciencia e Innovación y Universidades, Government of Spain, RTI2018-095894-B-I00 research project; Ministerio de Ciencia e Innovación, Government of Spain through the research projects with references PID2019-108435RB-I00; TED2021-131201B-I00 and PDC2022-133132-I00; Consellería de Cultura, Educación e Universidade, Xunta de Galicia through the postdoctoral, grant ref. ED481B-2021-059; and Grupos de Referencia Competitiva, grant ref. ED431C 2020/24; Axencia Galega de Innovación (GAIN), Xunta de Galicia, grant ref. IN845D 2020/38; CITIC, as Research Center accredited by Galician University System, is funded by “Consellería de Cultura, Educación e Universidade from Xunta de Galicia”, supported in an 80 % through ERDF Funds, ERDF Operational Programme Galicia 2014–2020, and the remaining 20 % by “Secretaría Xeral de Universidades”, grant ref. ED431G 2019/01. Emilio López Varela acknowledges its support under FPI Grant Program through PID2019-108435RB-I00 project. Funding for open access charge: Universidade da Coruña/CISUG

Update on the usefulness of optical coherence tomography in assessing the iridocorneal angle

The iridocorneal angle, due to its implications in the physiopathology of aqueous humour drainage, is a fundamental structure of the anterior chamber. Anterior segment optical coherence tomography (AS−OCT) is a rapid and non-invasive technique that obtains images in vivo. The high resolution allows it to analyse the normal anatomy of the angle, any alterations, and the changes that occur after different therapeutic interventions. AS−OCT technology has evolved to provide images that allow the identification and quantification of the angular structures in healthy subjects and in glaucoma patients, and especially the trabecular meshwork and the Schlemm's canal. It also enables the angle width to be quantified, with some objective parameters that have been standardised in recent years, such as the trabecular-iris angle (TIA), the angle opening distance (AOD), and the trabecular-iris area (TISA). This technique has multiple uses in the study of the different mechanisms of angle closure, the evaluation of changes after a laser peripheral iridotomy or iridoplasty after cataract surgery, as well as after the implantation of phakic lenses

Letter in response to article in journal of infection: “High SARS-CoV-2 antibody prevalence among healthcare workers exposed to COVID-19 patients”

Letter to editorUnidad Docente de Inmunología, Oftalmología y ORLFac. de Óptica y OptometríaTRUEpu

Effect of COVID-19 lockdown in Spain on structural and functional outcomes of Neovascular AMD patients

This is a retrospective single-center study of patients with neovascular age-related macular degeneration whose follow-up was delayed due to COVID-19 pandemic with at least three months between visits in Madrid, Spain. The purpose of the study was to evaluate best corrected visual acuity (BCVA) changes and try to identify features in optical coherence tomography (OCT) that could be related to more profound visual loss. It included 270 eyes. The two last visits before lockdown were used for comparison with the visit after lockdown. BCVA changed from 60.2 ± 18.2 to 55.9 ± 20.5 ETDRS letters. 29% of the eyes lost more than 5 letters. OCT was active in 67% of eyes before lockdown and in 80.4% after lockdown. Multiple lineal analysis showed that patients whose OCT before lockdown presented with a combination of intra and subretinal fluid were more likely to suffer a greater visual loss (p = 0.002). These patients should be encouraged to not miss any visits in case a new lockdown is imposed

Robust multi-view approaches for retinal layer segmentation in glaucoma patients via transfer learning

Background: Glaucoma is the leading global cause of irreversible blindness. Glaucoma patients experience a progressive deterioration of the retinal nervous tissues that begins with a loss of peripheral vision. An early diagnosis is essential in order to prevent blindness. Ophthalmologists measure the deterioration caused by this disease by assessing the retinal layers in different regions of the eye, using different optical coherence tomography (OCT) scanning patterns to extract images, generating different views from multiple parts of the retina. These images are used to measure the thickness of the retinal layers in different regions. Methods: We present two approaches for the multi-region segmentation of the retinal layers in OCT images of glaucoma patients. These approaches can extract the relevant anatomical structures for glaucoma assessment from three different OCT scan patterns: circumpapillary circle scans, macular cube scans and optic disc (OD) radial scans. By employing transfer learning to take advantage of the visual patterns present in a related domain, these approaches use state-of-the-art segmentation modules to achieve a robust, fully automatic segmentation of the retinal layers. The first approach exploits inter-view similarities by using a single module to segment all of the scan patterns, considering them as a single domain. The second approach uses view-specific modules for the segmentation of each scan pattern, automatically detecting the suitable module to analyse each image. Results: The proposed approaches produced satisfactory results with the first approach achieving a dice coefficient of 0.85±0.06 and the second one 0.87±0.08 for all segmented layers. The first approach produced the best results for the radial scans. Concurrently, the view-specific second approach achieved the best results for the better represented circle and cube scan patterns. Conclusions: To the extent of our knowledge, this is the first proposal in the literature for the multi-view segmentation of the retinal layers of glaucoma patients, demonstrating the applicability of machine learningbased systems for aiding in the diagnosis of this relevant pathology

Hypercytokinemia in COVID-19: Tear cytokine profile in hospitalized COVID-19 patients

The aim of this study is to analyze the concentrations of cytokines in tear of hospitalized COVID-19 patients compared to healthy controls. Tear samples were obtained from 41 healthy controls and 62 COVID-19 patients. Twenty-seven cytokines were assessed: interleukin (IL)-1b, IL-1RA, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL9, IL-10, IL-12, IL-13, IL-15, IL-17, eotaxin, fibroblast growth factor basic, granulocyte colony-stimulating factor (G-CSF), granulocyte-monocyte colony-stimulating factor (GM-CSF), interferon (IFN)-γ, interferon gamma-induced protein, monocyte chemo-attractant protein-1, macrophage inflammatory protein (MIP)-1a, MIP-1b, platelet-derived growth factor (PDGF), regulated on activation normal T cell expressed and secreted, tumor necrosis factor-α and vascular endothelial growth factor (VEGF). In tear samples of COVID-19 patients, an increase in IL-9, IL-15, G-CSF, GM-CSF, IFN-γ, PDGF and VEGF was observed, along with a decrease in eotaxin compared to the control group (p < 0.05). A poor correlation between IL-6 levels in tear and blood was found. IL-1RA and GM-CSF were significantly lower in severe patients and those who needed treatment targeting the immune system (p < 0.05). Tear cytokine levels corroborate the inflammatory nature of SARS-CoV-2

Proinflammatory cytokine profile differences between primary open angle and pseudoexfoliative glaucoma

Introduction: Few studies have investigated glaucoma biomarkers in aqueous humor and tear and have found elevations of proinflammatory cytokines in patients with primary open-angle glaucoma (POAG) and pseudoexfoliative glaucoma (PXG). In this study we investigate differences in inflammatory cytokines between POAG and PXG patients to find specific disease biomarkers. Methods: For this purpose, tear and aqueous humor samples of 14 eyes with POAG and 15 eyes with PXG undergoing cataract surgery were immunoassayed for 27 pro-inflammatory cytokines. The concentrations of cytokines in tear and aqueous humor and their association with clinical variables were analysed, correlated and compared between the groups. Results: We found that the levels of three cytokines differed significantly in the aqueous humor of POAG and PXG patients: IL-12 and IL-13 were higher in the POAG group, while MCP-1(MCAF) was higher in the PXG group. The number of topical hypotensive medications was correlated with diminished levels of two cytokines (IL-7 and basic fibroblast growth factor) in aqueous humor in the POAG group and with diminished levels of IL-12 in tear in the PXG group. Conclusion: We conclude that both POAG and PXG show elevated concentrations of proinflammatory cytokines in tear and aqueous humor that could be used as biomarkers for these types of glaucoma and that the concentrations in aqueous humor of three cytokines: IL-12, IL-13 and MCP-1(MCAF) could be used to differentiate POAG and PXG