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Reliability of standing weight-bearing (0.25T) MR imaging findings and positional changes in the lumbar spine

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OBJECTIVE: To test the reliability and absolute agreement of common degenerative findings in standing positional magnetic resonance imaging (pMRI).

METHODS AND MATERIALS: Low back pain patients with and without sciatica were consecutively enrolled to undergo a supine and standing pMRI. Three readers independently evaluated the standing pMRI for herniation, spinal stenosis, spondylolisthesis, HIZ lesions and facet joint effusion. The evaluation included a semi-quantitative grading of spinal stenosis, foraminal stenosis and spinal nerve root compression. The standing pMRI images were evaluated with full access to supine MRI. In case lower grades or the degenerative findings were not present in the supine images, this was reported separately as position-dependent changes. A subsample of 20 pMRI examinations was reevaluated after two months. The reproducibility was assessed by inter- and intra-reader reliability (kappa statistic) and absolute agreement between readers.

RESULTS: Fifty-six patients were included in this study. There was fair-to-substantial inter-reader reliability (κ 0.47 to 0.82) and high absolute agreement (72.3% to 99.1%) for the pMRI findings. The intra-reader assessment showed similar reliability and agreement (κ 0.36 to 0.85; absolute agreement: 62.5% to 98.8%). Positional changes between the supine and standing position showed a fair-to-moderate inter- and intra-reader reliability (κ 0.25 to 0.52; absolute agreement: 97.0% to 99.1).

CONCLUSION: Evaluation of the lumbar spine for degenerative findings by standing pMRI has acceptable reproducibility; however, positional changes from the supine to the standing position as an independent outcome should be interpreted with caution because of lower reliability, which calls for further standardisation.

OriginalsprogEngelsk
TidsskriftSkeletal Radiology
Vol/bind47
Udgave nummer1
Sider (fra-til)25-35
Antal sider11
ISSN0364-2348
DOI
StatusUdgivet - jan. 2018

ID: 53652854