Wenjing Luo1, Ling Fang2, Zhanhang Wang3, Zifeng Liu4, Jinchi Liao1, Zhanao Meng2, Shishi Shen1, Baozhu Liu3, Rui Li1, Allan G Kermode5,6, Wei Qiu7. 1. Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, China. 2. Departments of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China. 3. Department of Neurology, GuangDong 999 Brain Hospital, Guangzhou, China. 4. Department of Clinical Data Center, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China. 5. Centre for Neuromuscular and Neurological Disorders, University of Western Australia, Perth, WA, Australia. 6. Department of Neurology, Sir Charles Gairdner Hospital, Queen Elizabeth II Medical Centre, Perth, WA, Australia. 7. Department of Neurology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, Guangdong Province, China. qiuwei120@vip.163.com.
Abstract
PURPOSE: We propose a scoring system for early diagnosis of sleep abnormalities in neuromyelitis optica spectrum disorders (NMOSD) with hypothalamic lesions based on magnetic resonance imaging (MRI). MATERIALS AND METHODS: We evaluated MRI features of 45 patients with hypothalamic lesions identified from two cohorts. Univariate logistic regression analysis identified factors associated with sleepiness, which were subsequently used to develop a scoring system. Interrater reliability was determined using intraclass correlation coefficient (ICC). Correlations between scores and clinical features were analyzed. RESULTS: In total, 48.9% of 45 patients with hypothalamic lesions exhibited sleepiness. The number of involved slices, maximum width/length of hypothalamic lesions, and boundaries extending beyond the hypothalamus were associated with sleepiness (all p < 0.05). The sensitivity and specificity of the scoring system were 68.2% and 87.0%, respectively. The ICC values for the maximum width and length measurement of hypothalamic lesions were 0.82 and 0.81, respectively. Daily sleep time and Epworth sleepiness scale scores were positively correlated with MRI-based scores (p < 0.05, 95% confidence interval (CI) 0.69-0.93 and p < 0.05, 95% CI 0.55-0.88, respectively). CONCLUSION: A scoring system based on MRI features was developed to provide diagnosis of sleepiness in NMOSD with hypothalamic lesions earlier than other measures.
PURPOSE: We propose a scoring system for early diagnosis of sleep abnormalities in neuromyelitis optica spectrum disorders (NMOSD) with hypothalamic lesions based on magnetic resonance imaging (MRI). MATERIALS AND METHODS: We evaluated MRI features of 45 patients with hypothalamic lesions identified from two cohorts. Univariate logistic regression analysis identified factors associated with sleepiness, which were subsequently used to develop a scoring system. Interrater reliability was determined using intraclass correlation coefficient (ICC). Correlations between scores and clinical features were analyzed. RESULTS: In total, 48.9% of 45 patients with hypothalamic lesions exhibited sleepiness. The number of involved slices, maximum width/length of hypothalamic lesions, and boundaries extending beyond the hypothalamus were associated with sleepiness (all p < 0.05). The sensitivity and specificity of the scoring system were 68.2% and 87.0%, respectively. The ICC values for the maximum width and length measurement of hypothalamic lesions were 0.82 and 0.81, respectively. Daily sleep time and Epworth sleepiness scale scores were positively correlated with MRI-based scores (p < 0.05, 95% confidence interval (CI) 0.69-0.93 and p < 0.05, 95% CI 0.55-0.88, respectively). CONCLUSION: A scoring system based on MRI features was developed to provide diagnosis of sleepiness in NMOSD with hypothalamic lesions earlier than other measures.