BACKGROUND: Although grey matter damage in multiple sclerosis is currently recognized, determinants of grey matter volume and its relationship with disability are not yet clear. OBJECTIVES: The objectives of the study were to measure grey and white matter volumes across different disease phenotypes; identify MRI parameters associated with grey matter volume; and study grey and white matter volume as explanatory variables for clinical impairment. METHODS: This is a cross-sectional study in which MRI data of 95 clinically isolated syndrome, 657 relapsing-remitting, 125 secondary-progressive and 50 primary-progressive multiple sclerosis patients from three centres were acquired. Grey and white matter volumes were determined, together with T2 and T1 lesion volumes. Physical disability was assessed with the Expanded Disability Status Scale, cognitive impairment with the Paced Auditory Serial Addition Task. Data were analysed using multiple regression. RESULTS: Grey matter volume was lower in relapsing-remitting patients (mean [SD]: 0.80 [0.05] L) than in clinically isolated syndrome patients (0.82 [0.05] L), and even greater relative atrophy was found in secondary-progressive patients (0.77 [0.05] L). In contrast, white matter volume in secondary-progressive patients was comparable to that in relapsing-remitting patients. Grey matter volume was the strongest independent predictor of physical disability and cognitive impairment, and was associated with both T2 and T1 lesion volume. CONCLUSIONS: Our findings show that grey matter volume is lower in secondary-progressive than in relapsing-remitting disease. Grey matter volume explained physical and cognitive impairment better than white matter volume, and is itself associated with T2 and T1 lesion volume.
BACKGROUND: Although grey matter damage in multiple sclerosis is currently recognized, determinants of grey matter volume and its relationship with disability are not yet clear. OBJECTIVES: The objectives of the study were to measure grey and white matter volumes across different disease phenotypes; identify MRI parameters associated with grey matter volume; and study grey and white matter volume as explanatory variables for clinical impairment. METHODS: This is a cross-sectional study in which MRI data of 95 clinically isolated syndrome, 657 relapsing-remitting, 125 secondary-progressive and 50 primary-progressive multiple sclerosispatients from three centres were acquired. Grey and white matter volumes were determined, together with T2 and T1 lesion volumes. Physical disability was assessed with the Expanded Disability Status Scale, cognitive impairment with the Paced Auditory Serial Addition Task. Data were analysed using multiple regression. RESULTS: Grey matter volume was lower in relapsing-remitting patients (mean [SD]: 0.80 [0.05] L) than in clinically isolated syndromepatients (0.82 [0.05] L), and even greater relative atrophy was found in secondary-progressive patients (0.77 [0.05] L). In contrast, white matter volume in secondary-progressive patients was comparable to that in relapsing-remitting patients. Grey matter volume was the strongest independent predictor of physical disability and cognitive impairment, and was associated with both T2 and T1 lesion volume. CONCLUSIONS: Our findings show that grey matter volume is lower in secondary-progressive than in relapsing-remitting disease. Grey matter volume explained physical and cognitive impairment better than white matter volume, and is itself associated with T2 and T1 lesion volume.
Authors: Bruce D Trapp; Megan Vignos; Jessica Dudman; Ansi Chang; Elizabeth Fisher; Susan M Staugaitis; Harsha Battapady; Sverre Mork; Daniel Ontaneda; Stephen E Jones; Robert J Fox; Jacqueline Chen; Kunio Nakamura; Richard A Rudick Journal: Lancet Neurol Date: 2018-08-22 Impact factor: 44.182
Authors: Martijn D Steenwijk; Marita Daams; Petra J W Pouwels; Lisanne J Balk; Prejaas K Tewarie; Jeroen J G Geurts; Frederik Barkhof; Hugo Vrenken Journal: Hum Brain Mapp Date: 2015-01-27 Impact factor: 5.038
Authors: Maria A Rocca; Marco Battaglini; Ralph H B Benedict; Nicola De Stefano; Jeroen J G Geurts; Roland G Henry; Mark A Horsfield; Mark Jenkinson; Elisabetta Pagani; Massimo Filippi Journal: Neurology Date: 2016-12-16 Impact factor: 9.910
Authors: Regina Schlaeger; Nico Papinutto; Valentina Panara; Carolyn Bevan; Iryna V Lobach; Monica Bucci; Eduardo Caverzasi; Jeffrey M Gelfand; Ari J Green; Kesshi M Jordan; William A Stern; H-Christian von Büdingen; Emmanuelle Waubant; Alyssa H Zhu; Douglas S Goodin; Bruce A C Cree; Stephen L Hauser; Roland G Henry Journal: Ann Neurol Date: 2014-08-21 Impact factor: 10.422