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MRI cross sectional atlas of normal canine cervical musculoskeletal structure

Authors :
Claudia Zindl
Mina Alizadeh
Gregory G. Knapik
William S. Marras
Noel Fitzpatrick
Matthew J. Allen
Allen, Matthew [0000-0001-8535-3937]
Apollo - University of Cambridge Repository
Publication Year :
2016
Publisher :
Elsevier, 2016.

Abstract

Although magnetic resonance imaging (MRI) has been increasingly used as a diagnostic tool for cervical spine injuries in canines, a comprehensive normal MRI anatomy of the canine cervical spine muscles is lacking. Therefore, the purpose of this study was to build a magnetic resonance imaging atlas of the normal cross sectional anatomy of the muscles of the canine cervical spine. MRI scans were performed on a canine cadaver using a combination of T1 and T2-weighted images in the transverse, sagittal and dorsal planes acquired at a slice thickness of 1 mm. Muscle contours were traced manually in each slice, using local osseous structures as reference points for muscle identification. Twenty-two muscles were traced in 401 slices in the cervical region. A three dimensional surface model of all the contoured muscles was created to illustrate the complex geometrical arrangement of canine neck muscles. The cross-sectional area of the muscles was measured at the mid-level of each vertebra. The accuracy of the location of the mapped muscles was verified by comparing the sagittal view of the 3D model of muscles with still photographs obtained from anatomic canine cadaver dissection. We believe that this information will provide a unique and valuable resource for veterinary researchers, clinicians and surgeons who wish to evaluate MRI images of the cervical spine. It will also serve as the foundation for ongoing work to develop a computational model of the canine cervical spine in which anatomical information is combined with electromyographic, kinematic and kinetic data.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....c6f7d23f3991a1736ad8751d1e28ddc0
Full Text :
https://doi.org/10.17863/cam.6704