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Diffusion Tensor Imaging of White Matter Tracts in the Dog Brain

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Abstract

Diffusion weighted imaging sequences are now widely available on Magnetic Resonance Imaging (MRI) scanners. Diffusion Tensor Imaging (DTI) of the brain is able to show white matter tracts and is now commonly used in human medicine to study brain anatomy, tumors, structural pathways,… The purpose of this study was to show the interest of DTI to reveal the white matter fibers in the dogs' brain. DTI MR Images for this study were obtained with a 3 T system of 4 dogs euthanized for other reasons than neurological disorders. Combined fractional anisotropic (FA) and directional maps were obtained in the first 2 hours after death. The heads were amputated immediately after scanning and stored in 10% formalin until preparation for dissection. An experienced anatomist tracked white matter tracts with clinical relevance using the scanner software. The selected tracts were REFVIDume rendered and correlated with gross dissection. Using DTI we were able to track relevant neurological connections, such as the corticospinal tract, the optic and the cerebellar tract. The three dimensional anatomy is better presented using modern visualization techniques. DTI seems to be a valuable tool in order to present clinically relevant white matter tracts to neurological clinicians and researchers. Anat Rec, 296:340–349, 2013. © 2013 Wiley Periodicals, Inc.
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Document Type: Research Article

Affiliations: 1: Department of Radiology, University Hospital Brussels, Morpho – Veterinary – Imaging (MOVE – IM BRUSSELS A.S.B.L.), UZ Brussel, Brussels, Belgium 2: Department of Radiology University Hospital Brussels (UZ Brussel), Vrije Universiteit Brussel (VUB) Laarbeeklaan 101 1090, Brussels, Belgium 3: Department of Basic Veterinary Sciences, Service of Anatomy, Royal Veterinary College, London, United Kingdom 4: Department of Anatomy, Faculty of Medicine, Vrije Universiteit Brussel (VUB), Brussels Laarbeeklaan 103, 1090, Brussels, Belgium

Publication date: February 1, 2013

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