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Published on: February 19, 2021
[Neutral position magnetic resonance imaging for diagnosis of Hirayama disease]
Yu Fu1, Dong-sheng Fan, Xin-long Pei
1Department of Neurology, Peking University Third Hospital, Beijing 100083, China.
Objective:
To investigate the sensitivity and specificity of neutral position cervical MRI in the diagnosis of Hirayama disease.
Methods:
Neutral position cervical MRI of 18 patients and 31 young normal control subjects were evaluated for localized lower cervical cord atrophy, asymmetric cord flattening, abnormal cervical curvature, loss of attachment (LOA) and noncompressed intramedullary high signal intensity on T2-weighted MRI. The difference in frequency of these findings between the control and patient groups was examined by means of the x' test. The sensitivity and specificity of these MRI findings in the diagnosis of Hirayama disease were calculated. Multiple logistic regression was performed to explore the relationship with Hirayama disease.
Results:
(1) There was significant difference in the frequency of localized lower cervical cord atrophy, asymmetric cord flattening and LOA between the patient and control groups (P < 0.05). (2) After adjusting localized lower cervical cord atrophy, asymmetric cord flattening, abnormal cervical curvature and LOA, the analysis showed that LOA was the only significantly important predictor of the disease, with odds ratio of 49.38 (95% CI: 3.97 - 614.73). Sensitivity and specificity of LOA were 88.0% and 90.6% respectively. (3) Sensitivity and specificity of localized lower cervical cord atrophy were 84.6% and 80.6%. Sensitivity and specificity of asymmetric cord flattening were 87.5% and 73.2%, but our case-control study did not fine any significant association between localized lower cervical cord atrophy and Hirayama disease and also between asymmetric cord flattening and Hirayama disease.
Conclusions:
LOA between posterior dural sac and subjacent lamina is the most valuable finding in the diagnosis of Hirayama disease at neutral position MR imaging.
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