Purpose: Previous work has suggested that Descemet membrane (DM) folds arise in response to corneal swelling. However, their origin has not been closely explored. In this study, we used optical coherence tomography to evaluate whether DM folds arise secondary to folds in the middle stroma.
Methods: Serial optical coherence tomography images of donor cornea pairs in deionized water were taken for each of the following corneal manipulations: 1) untreated, 2) DM and the endothelium removed, 3) excised in the region of the deep middle/posterior stroma, and 4) excised in the middle stroma.
Results: For intact corneas, increasing duration in deionized water was marked by a progressive increase in corneal thickness and number of folds along the posterior surface. With DM and the endothelium removed, a similar phenomenon was observed. In the third set of corneas, the plane of resection created a structural separation in the region of the deep middle/posterior stroma. Folds were seen originating anterior to the resection plane. For corneas with the posterior and part of the middle stroma removed, the typical folds on the posterior surface as seen in the previous conditions were not observed. Instead, less numerous and smaller irregularities of the posterior surface of the resection plane were present.
Conclusions: Folds in DM associated with corneal edema originate in the middle and posterior stroma and are secondarily transmitted into DM. On the basis of the stromal origin of these anatomic changes, "stromal folds" should be considered a more accurate term to replace "Descemet membrane folds."
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http://dx.doi.org/10.1097/ICO.0000000000001908 | DOI Listing |
Transl Vis Sci Technol
January 2025
Department of Ophthalmology, University Hospital Bonn, Bonn, Germany.
Purpose: To compare a novel high-resolution optical coherence tomography (OCT) with improved axial resolution (High-Res OCT) with conventional spectral-domain OCT (SD-OCT) with regard to their capacity to characterize the disorganization of the retinal inner layers (DRIL) in diabetic maculopathy.
Methods: Diabetic patients underwent multimodal retinal imaging (SD-OCT, High-Res OCT, and color fundus photography). Best-corrected visual acuity and diabetes characteristics were recorded.
Invest Ophthalmol Vis Sci
January 2025
Department of Surgical Sciences, Eye Clinic Section, University of Turin, Turin, Italy.
Purpose: This study aimed to comprehensively assess visual performance in eyes with idiopathic epiretinal membrane (iERM). Additionally, it sought to explore the associations between optical coherence tomography (OCT) imaging biomarkers and visual performance in patients with iERM.
Methods: In this prospective, non-interventional study, 57 participants with treatment-naïve iERM from the University of Turin, between September 2023 and March 2024 were enrolled.
Nano Lett
January 2025
NanoPhotonics Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge CB3 0HE, United Kingdom.
Metal nanocrystals synthesized in achiral environments usually exhibit no chiroptical effects. However, by placing nominally achiral nanocrystals 1.3 nm above gold films, we find giant chiroptical effects, reaching anisotropy factors as high as ≈ 0.
View Article and Find Full Text PDFAm J Ophthalmol Case Rep
March 2025
Department of Ophthalmology, Stanley M. Truhlsen Eye Institute, University of Nebraska Medical Center, Omaha, NE, USA.
Purpose: To describe a rare case of presumed bilateral acute idiopathic maculopathy (AIM) in a pediatric patient.
Observation: An 11-year-old male was evaluated for a "fuzzy Dorito-shaped" spot in the central vision of his right eye (OD) that started 3 days before presenting to our clinic. On examination, best-corrected visual acuity (BCVA) was counting fingers at 5 feet OD, and 20/25 in the left eye (OS).
Taiwan J Ophthalmol
November 2024
Sirindhorn International Institute of Technology, Thammasat University, Bangkok, Thailand.
Recent advances of artificial intelligence (AI) in retinal imaging found its application in two major categories: discriminative and generative AI. For discriminative tasks, conventional convolutional neural networks (CNNs) are still major AI techniques. Vision transformers (ViT), inspired by the transformer architecture in natural language processing, has emerged as useful techniques for discriminating retinal images.
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