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AJNR Am J Neuroradiol ; 38(11): 2203-2209, 2017 Nov.
Article in English | MEDLINE | ID: mdl-28882864

ABSTRACT

BACKGROUND AND PURPOSE: MR imaging of peripheral nerves (MR neurography) allows improved assessment of nerve anatomy and pathology. The objective of this study was to evaluate patients with unilateral occipital neuralgia using MR neurography and to assess the differences in greater occipital nerve signal and size between the symptomatic and asymptomatic sides. MATERIALS AND METHODS: In this case-control evaluation using MR neurography, bilateral greater occipital nerve caliber, signal intensity, signal-to-noise ratios, and contrast-to-noise ratios were determined by 2 observers. RESULTS: Among 18 subjects with unilateral occipital migraines, the average greater occipital nerve diameter for the symptomatic side was significantly greater at 1.77 ± 0.4 mm than for the asymptomatic side at 1.29 ± 0.25 mm (P = .001). The difference in nerve signal intensity between the symptomatic and asymptomatic sides was statistically significant at 269.06 ± 170.93 and 222.44 ± 170.46, respectively (P = .043). The signal-to-noise ratios on the symptomatic side were higher at 15.79 ± 4.59 compared with the asymptomatic nerve at 14.02 ± 5.23 (P = .009). Contrast-to-noise ratios were significantly higher on the symptomatic side than on the asymptomatic side at 2.57 ± 4.89 and -1.26 ± 5.02, respectively (P = .004). Intraobserver performance was good to excellent (intraclass coefficient correlation, 0.68-0.93), and interobserver performance was fair to excellent (intraclass coefficient correlation, 0.54-0.81). CONCLUSIONS: MR neurography can be reliably used for the diagnosis of greater occipital nerve neuropathy in patients with unilateral occipital migraines with a good correlation of imaging findings to the clinical presentation.


Subject(s)
Magnetic Resonance Imaging/methods , Migraine Disorders/diagnostic imaging , Neuralgia/diagnostic imaging , Adult , Aged , Case-Control Studies , Female , Humans , Image Interpretation, Computer-Assisted , Male , Middle Aged
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