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Cross-sectional area and fat content in dachshund epaxial muscles: an MRI and CT reliability study
MRI and CT are frequently used to diagnose spinal diseases in dogs. These modalities have detected epaxial muscle degeneration in dachshunds with intervertebral disc herniation. However, research on the reliability of epaxial muscular measurements is limited in veterinary medicine. The aims of the s...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5888436/ https://www.ncbi.nlm.nih.gov/pubmed/29632671 http://dx.doi.org/10.1136/vetreco-2017-000256 |
Sumario: | MRI and CT are frequently used to diagnose spinal diseases in dogs. These modalities have detected epaxial muscle degeneration in dachshunds with intervertebral disc herniation. However, research on the reliability of epaxial muscular measurements is limited in veterinary medicine. The aims of the study were to assess the intrarater and inter-rater reliability of epaxial muscle cross-sectional area (CSA) and fat content measurements on MRI and CT images in dachshunds, and to compare the CSA measurement between the two modalities. MRI and CT images of 10 healthy dachshunds were evaluated. Two blinded observers assessed MRI CSA, MRI fat content, CT CSA and CT muscle attenuation of three thoracolumbar epaxial muscles using OsiriX. The results showed ‘substantial’ to ‘almost perfect’ intrarater reliability (intraclass correlation coefficient (ICC) 0.828–0.998) and inter-rater reliability (ICC 0.685–0.854) for all variables. When individual spinal segments were analysed, the intrarater and inter-rater reliability decreased and the confidence intervals increased. There was positive correlation (r= 0.719–0.841, P=0.001) and high agreement (0.824–0.894) for the measured CSA between MRI and CT. Epaxial muscle CSA and fat content can be reliably measured on MRI and CT, bearing in mind that measurement of certain segments requires adequate training. |
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