Purpose: To report a case of a developmental anatomic finding of the ophthalmic artery (OA) in a patient with ipsilateral progressive advanced glaucomatous optic neuropathy and visual field loss.

Methods: A 59-year-old Asian man with normal tension glaucoma had progressive asymmetric visual field loss OD. Magnetic resonance imaging and angiography of the orbit were performed because of continued progression despite medical and surgical intervention.

Results: Magnetic resonance angiography revealed an anomalous OA, lateral to the carotid artery and emanating from a branch of the middle meningeal artery.

Conclusion: OA anomalies should be added to the differential diagnosis of risk factors for unilateral progressive glaucomatous optic neuropathy, and neuroradiologic imaging should be considered to detect such anatomic variants.

Download full-text PDF

Source
http://dx.doi.org/10.1097/IJG.0b013e318168f050DOI Listing

Publication Analysis

Top Keywords

glaucomatous optic
12
optic neuropathy
12
progressive glaucomatous
8
ophthalmic artery
8
visual field
8
magnetic resonance
8
asymmetric progressive
4
neuropathy patient
4
patient rare
4
rare developmental
4

Similar Publications

Pseudoexfoliation glaucoma is a severe form of secondary open angle glaucoma and is associated with activation of the TGF-β pathway by TGF-β1. MicroRNAs (miRNAs) are small non-coding RNA species that are involved in regulation of mRNA expression and translation. To investigate what glaucomatous changes occur in the trabecular meshwork and how these changes may be regulated by miRNAs, we performed a bioinformatics analysis resulting in a miRNA-mRNA interactome.

View Article and Find Full Text PDF

Precis: Current optical coherence tomography normative sample data may not represent diverse human optic nerve anatomy to accurately classify all individuals with true glaucomatous optic neuropathy.

Purpose: To compare optic nerve head (ONH) measurements between published values from an optical coherence tomography (OCT) normative database and a more diverse cohort of healthy individuals.

Patients And Methods: ONH parameters from healthy participants of the Michigan Screening and Intervention for Glaucoma and Eye Health through Telemedicine (MI-SIGHT) program and the Topcon Maestro-1 normative cohort were compared.

View Article and Find Full Text PDF

Glaucoma Detection and Feature Identification via GPT-4V Fundus Image Analysis.

Ophthalmol Sci

November 2024

Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, La Jolla, California.

Purpose: The aim is to assess GPT-4V's (OpenAI) diagnostic accuracy and its capability to identify glaucoma-related features compared to expert evaluations.

Design: Evaluation of multimodal large language models for reviewing fundus images in glaucoma.

Subjects: A total of 300 fundus images from 3 public datasets (ACRIMA, ORIGA, and RIM-One v3) that included 139 glaucomatous and 161 nonglaucomatous cases were analyzed.

View Article and Find Full Text PDF

Glaucoma poses a growing health challenge projected to escalate in the coming decades. However, current automated diagnostic approaches on Glaucoma diagnosis solely rely on black-box deep learning models, lacking explainability and trustworthiness. To address the issue, this study uses optical coherence tomography (OCT) images to develop an explainable artificial intelligence (XAI) tool for diagnosing and staging glaucoma, with a focus on its clinical applicability.

View Article and Find Full Text PDF

Purpose: In this study, it was planned to compare the macular ganglion cell analysis (GCA) and peripapillary retinal nerve fiber layer (pRNFL) of the patients with preperimetric glaucoma (PPG), early stage glaucoma (EG) and the control group.

Methods: This retrospective study included a total of 103 eyes: 38 from EG patients, 30 from PPG patients, and 35 from healthy individuals at Ankara Bilkent City Hospital Glaucoma Unit between January 2018 and September 2021. Eyes were categorized into control, PPG, and EG groups based on visual field (VF) classification.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!