ArticleMagnetic resonance in medicine2016
Disambiguating the optic nerve from the surrounding cerebrospinal fluid: Application to MS-related atrophy.
Article in Magnetic resonance in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Towards a Deeper Understanding of Cerebrospinal Fluid Transport in the Optic Nerve Subarachnoid Space: A Computational Approach.Annals of biomedical engineering · 2026Article
- Research progress of optic nerve imaging during 1991-2023: a bibliometric analysis.Quantitative imaging in medicine and surgery · 2024Article
- Automatic segmentation and quantification of the optic nerve on MRI using a 3D U-Net.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- Ultra-High Field Magnetic Resonance Imaging of the Retrobulbar Optic Nerve, Subarachnoid Space, and Optic Nerve Sheath in Emmetropic and Myopic Eyes.Translational vision science & technology · 2021Article
- Incorporating non-linear alignment and multi-compartmental modeling for improved human optic nerve diffusion imaging.NeuroImage · 2019Article
- Improved Automatic Optic Nerve Radius Estimation from High Resolution MRI.Proceedings of SPIE--the International Society for Optical Engineering · 2017Article
- Short Term Reproducibility of a High Contrast 3-D Isotropic Optic Nerve Imaging Sequence in Healthy Controls.Proceedings of SPIE--the International Society for Optical Engineering · 2016Article
- Constructing a statistical atlas of the radii of the optic nerve and cerebrospinal fluid sheath in young healthy adults.Proceedings of SPIE--the International Society for Optical Engineering · 2015Article
- Quantitative characterization of optic nerve atrophy in patients with multiple sclerosis.Multiple sclerosis journal - experimental, translational and clinicalArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
purposeOur goal is to develop an accurate, automated tool to characterize the optic nerve (ON) and cerebrospinal fluid (CSF) to better understand ON changes in disease.
methodsMulti-atlas segmentation is used to localize the ON and sheath on T2-weighted MRI (0.6 mm(3) resolution). A sum of Gaussian distributions is fit to coronal slice-wise intensities to extract six descriptive parameters, and a regression forest is used to map the model space to radii. The model is validated for consistency using tenfold cross-validation and for accuracy using a high resolution (0.4 mm(2) reconstructed to 0.15 mm(2)) in vivo sequence. We evaluated this model on 6 controls and 6 patients with multiple sclerosis (MS) and a history of optic neuritis.
resultsIn simulation, the model was found to have an explanatory R-squared for both ON and sheath radii greater than 0.95. The accuracy of the method was within the measurement error on the highest possible in vivo resolution. Comparing healthy controls and patients with MS, significant structural differences were found near the ON head and the chiasm, and structural trends agreed with the literature.
conclusionThis is a first demonstration that the ON can be exclusively, quantitatively measured and separated from the surrounding CSF using MRI.
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Registered trials
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