AIM: To determine whether corpus callosum atrophy predicts future clinical deterioration in multiple sclerosis. METHODS: In 39 multiple sclerosis patients the area of corpus callosum in the sagittal plane, T2 and T1 lesion volumes, brain parenchymal fraction and brain atrophy were determined at baseline and 1 year after treatment initiation. Non-parametric and multiple regression models were built to identify the most reliable predictors of disability and of its changes over 9 years. RESULTS: Corpus callosum atrophy during the first year of treatment was the best predictor of disability (r = -0.56) and of its increase at 9 years (r = 0.65). Corpus callosum atrophy of at least 2% predicted increase in disability with 93% sensitivity and 73% specificity (odds ratio = 35). CONCLUSION: Corpus callosum atrophy is a simple and accurate predictor of future disability accumulation and is feasible for routine clinical practice.
AIM: To determine whether corpus callosum atrophy predicts future clinical deterioration in multiple sclerosis. METHODS: In 39 multiple sclerosispatients the area of corpus callosum in the sagittal plane, T2 and T1 lesion volumes, brain parenchymal fraction and brain atrophy were determined at baseline and 1 year after treatment initiation. Non-parametric and multiple regression models were built to identify the most reliable predictors of disability and of its changes over 9 years. RESULTS:Corpus callosum atrophy during the first year of treatment was the best predictor of disability (r = -0.56) and of its increase at 9 years (r = 0.65). Corpus callosum atrophy of at least 2% predicted increase in disability with 93% sensitivity and 73% specificity (odds ratio = 35). CONCLUSION:Corpus callosum atrophy is a simple and accurate predictor of future disability accumulation and is feasible for routine clinical practice.
Authors: Eva Hynčicová; Martin Vyhnálek; Adam Kalina; Lukáš Martinkovič; Tomáš Nikolai; Jiří Lisý; Jakub Hort; Eva Meluzínová; Jan Laczó Journal: J Neurol Date: 2016-12-27 Impact factor: 4.849
Authors: A Burgetova; P Dusek; M Vaneckova; D Horakova; C Langkammer; J Krasensky; L Sobisek; P Matras; M Masek; Z Seidl Journal: AJNR Am J Neuroradiol Date: 2017-04-27 Impact factor: 3.825
Authors: Sean M Tobyne; Daria Boratyn; Jessica A Johnson; Douglas N Greve; Caterina Mainero; Eric C Klawiter Journal: Hum Brain Mapp Date: 2016-05-24 Impact factor: 5.038
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Authors: Marja Niiranen; Juha Koikkalainen; Jyrki Lötjönen; Tuomas Selander; Antti Cajanus; Päivi Hartikainen; Sakari Simula; Ritva Vanninen; Anne M Remes Journal: Brain Behav Date: 2022-06-28 Impact factor: 3.405