MY CONTENT

Ten patients with clinically suspected facetogenic low back pain were prospectively recruited with a designation of specific facet joints implicated clinically. Subsequently, patients underwent an FDG-PET/MR imaging examination with gadolinium. Each facet joint was graded for perifacet signal change on MR imaging and FDG activity. The frequency and correlation of MR imaging, FDG-PET, and clinical findings were determined. There was low concordance of perifacet signal change and FDG activity with clinically implicated facet joints. This could indicate either the potential to change patient management or a lack of biomarker accuracy.

The authors assessed the reproducibility and accuracy of cervical spinal cord gray matter and white matter cross-sectional area measurements using magnetization inversion recovery acquisition images and a fully automatic postprocessing segmentation algorithm. The cervical spinal cord of 24 healthy subjects was scanned in a test-retest fashion on a 3T MR imaging system. Twelve axial averaged magnetization inversion recovery acquisition slices were acquired over a 48-mm cord segment. GM and WM were both manually segmented by 2 experienced readers and compared with an automatic variational segmentation algorithm with a shape prior modified for 3D data with a slice similarity prior. Reproducibility was high for both methods, while being better for the automatic approach. The accuracy of the automatic method compared with the manual reference standard was excellent. They conclude that the fully automated postprocessing segmentation algorithm demonstrated an accurate and reproducible spinal cord GM and WM segmentation.