ABSTRACT
PURPOSE: The purpose of this case report was to provide a detailed description of the ocular manifestations, in a patient with multicentric carpotarsal osteolysis (MCTO), with particular emphasis on bilateral corneal opacities. METHODS: A 43-year-old woman with a history of MCTO was followed with visual acuity assessment and slit-lamp examination at the Department of Ophthalmology in the University Hospitals of Leuven. RESULTS: The patient was found to have bilateral subepithelial haze, along with anterior stromal corneal opacities, and small central lens opacities upon examination. There was a slight corneal thickening. A progression of the corneal opacities was observed, without a further drop in visual acuity. CONCLUSIONS: This case report shows a rare association between MCTO and corneal opacities in adulthood. Interdisciplinary care involving an ophthalmologist is beneficiary for patients with MCTO.
ABSTRACT
[This corrects the article DOI: 10.3389/fcvm.2022.1024044.].
ABSTRACT
Background: Glaucoma stands as a prominent global cause of irreversible blindness and the primary treatment approach involves reducing intraocular pressure (IOP). However, around one-third of patients exhibit disease progression despite effective IOP reduction. Microvascular endothelial function, chronic inflammation, and oxidative stress are known to affect retinal neuronal networks and have been associated with disease severity and progression. Exercise training has the potential to counteract these mechanisms as add-on treatment to usual care. Aims: The HIT-GLAUCOMA study will investigate the effects of a 6-month high-intensity interval training (HIIT) on intermediate endpoints such as local retinal microvascular and systemic large artery function, inflammation, and oxidative stress as well as clinical endpoints such as visual field indices, optic nerve rim assessment, retinal nerve fiber layer thickness, IOP, number of eye drops, vision-related quality of life and ocular surface disease symptomatology. Methods: The study is a multi-center randomized controlled clinical trial in patients with both normal tension and high-tension primary open angle glaucoma. Across two study centers, 128 patients will be enrolled and randomized on a 1:1 basis into an exercise intervention group and a usual care control group. The primary microvascular endpoints are retinal arteriolar and venular flicker light-induced dilation at 6 months. The primary endpoint in the systemic circulation is brachial artery flow-mediated dilation at 6 months. Anticipated results: We hypothesize that exercise therapy will improve retinal microvascular function and thus ocular blood flow in patients with glaucoma. As clinical outcomes, we will investigate the effect of exercise on visual field indices, optic nerve rim assessment, retinal nerve fiber layer thickness, IOP, number of eye drops, vision-related quality of life and ocular surface disease symptomatology. Discussion: HIT-GLAUCOMA is a blueprint trial design to study the effect of exercise training on neurodegenerative and cardiovascular diseases. Importantly, patients are also expected to benefit from improvements in general health and cardiovascular co-morbidities. If proven effective, exercise may offer a new add-on treatment strategy to slow glaucoma progression. Clinical Trial Registration Number: The trial is registered at Clinicaltrials.gov under the identifier NCT06058598 and is currently in the recruitment stage.
ABSTRACT
Objective.This study aims to automate the segmentation of retinal arterioles and venules (A/V) from digital fundus images (DFI), as changes in the spatial distribution of retinal microvasculature are indicative of cardiovascular diseases, positioning the eyes as windows to cardiovascular health.Approach.We utilized active learning to create a new DFI dataset with 240 crowd-sourced manual A/V segmentations performed by 15 medical students and reviewed by an ophthalmologist. We then developed LUNet, a novel deep learning architecture optimized for high-resolution A/V segmentation. The LUNet model features a double dilated convolutional block to widen the receptive field and reduce parameter count, alongside a high-resolution tail to refine segmentation details. A custom loss function was designed to prioritize the continuity of blood vessel segmentation.Main Results.LUNet significantly outperformed three benchmark A/V segmentation algorithms both on a local test set and on four external test sets that simulated variations in ethnicity, comorbidities and annotators.Significance.The release of the new datasets and the LUNet model (www.aimlab-technion.com/lirot-ai) provides a valuable resource for the advancement of retinal microvasculature analysis. The improvements in A/V segmentation accuracy highlight LUNet's potential as a robust tool for diagnosing and understanding cardiovascular diseases through retinal imaging.
Subject(s)
Deep Learning , Fundus Oculi , Image Processing, Computer-Assisted , Humans , Venules/diagnostic imaging , Venules/anatomy & histology , Image Processing, Computer-Assisted/methods , Arterioles/diagnostic imaging , Arterioles/anatomy & histology , Retinal Vessels/diagnostic imagingABSTRACT
The Leuven-Haifa dataset contains 240 disc-centered fundus images of 224 unique patients (75 patients with normal tension glaucoma, 63 patients with high tension glaucoma, 30 patients with other eye diseases and 56 healthy controls) from the University Hospitals of Leuven. The arterioles and venules of these images were both annotated by master students in medicine and corrected by a senior annotator. All senior segmentation corrections are provided as well as the junior segmentations of the test set. An open-source toolbox for the parametrization of segmentations was developed. Diagnosis, age, sex, vascular parameters as well as a quality score are provided as metadata. Potential reuse is envisioned as the development or external validation of blood vessels segmentation algorithms or study of the vasculature in glaucoma and the development of glaucoma diagnosis algorithms. The dataset is available on the KU Leuven Research Data Repository (RDR).