Background And Importance: Intracranial arterial dolichoectasia (or dilatative arteriopathy) is characterized by abnormal elongation, tortuosity, or increase in diameter of at least one of the main cerebral vessels. Dolichoectasia can be found incidentally or can present with cranial neuropathies (including vision loss) or stroke. Here, we describe the presentation and open surgical treatment of a patient with dolichoectasia of the intracranial internal carotid artery (ICA) causing monocular vision loss.
Clinical Presentation: A 73-year-old man presented with several months of progressive monocular vision loss and was found to have dolichoectasia of the supraclinoid ICA and subsequently underwent microsurgical decompression of the overlying affected optic nerve. The patient's postoperative convalescence was uncomplicated, and he had improvement in his right-sided monocular vision loss after surgery.
Conclusion: We present the case of a patient with dolichoectasia of the supraclinoid ICA causing compression of the optic nerve with resultant monocular vision loss. Timely microvascular decompression proves to be an effective technique for vision preservation in the setting of this rare pathologic entity.
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http://dx.doi.org/10.1227/ons.0000000000000520 | DOI Listing |
J Imaging Inform Med
January 2025
College of Engineering, Department of Computer Engineering, Koç University, Rumelifeneri Yolu, 34450, Sarıyer, Istanbul, Turkey.
This study explores a transfer learning approach with vision transformers (ViTs) and convolutional neural networks (CNNs) for classifying retinal diseases, specifically diabetic retinopathy, glaucoma, and cataracts, from ophthalmoscopy images. Using a balanced subset of 4217 images and ophthalmology-specific pretrained ViT backbones, this method demonstrates significant improvements in classification accuracy, offering potential for broader applications in medical imaging. Glaucoma, diabetic retinopathy, and cataracts are common eye diseases that can cause vision loss if not treated.
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January 2025
Rare Disease Translational Center, The Jackson Laboratory, Bar Harbor, ME, USA.
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Sci Rep
January 2025
Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA.
The Sharp-van der Heijde score (SvH) is crucial for assessing joint damage in rheumatoid arthritis (RA) through radiographic images. However, manual scoring is time-consuming and subject to variability. This study proposes a multistage deep learning model to predict the Overall Sharp Score (OSS) from hand X-ray images.
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January 2025
Faculty of Psychology, University of Maastricht, P.O. Box 616, 6200 MD Maastricht, The Netherlands, Maastricht, 6211 LK, NETHERLANDS.
Recent strides in neurotechnology show potential to restore vision in individuals afflicted with blindness due to early visual pathway damage. As neuroprostheses mature and become available to a larger population, manual placement and evaluation of electrode designs becomes costly and impractical. An automatic method to optimize the implantation process of electrode arrays at large-scale is currently lacking.
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