Contributions
Abstract: 104
Type: Oral
Abstract Category: Pathology and pathogenesis of MS - 21 Imaging
Background: Cognitive decline in multiple sclerosis (MS) is heterogeneous and strongly affects overall quality of life. Despite recent advances in structural brain imaging methodology, such as diffusion tensor imaging (DTI) and more accurate brain atrophy measurements, the lack of longitudinal data limits knowledge on which structural measures best predict the rate of cognitive decline. The objective of this study was to identify which structural MRI measures predict cognitive decline during a 5-year follow-up period.
Methods: A total of 234 clinically definite MS patients and 60 healthy controls (HC) were seen twice, with a 5-year interval. Structural MRI measures (3T) at baseline included cortical, deep grey matter and white matter volumes (using 3DT1), lesion volumes (using FLAIR) and the severity of white matter integrity loss (using DTI). An extensive neuropsychological evaluation based on the BRB-N was performed at both time points. Cognitive scores were corrected for effects of sex, normal aging and education at both time points and then transformed into seven cognitive domain Z-scores. Changes in individual Z-scores were divided by the interval duration and averaged across domains, to obtain a global score for the yearly rate of cognitive decline for each subject. A forward selection regression model was used to determine which baseline measures significantly predicted cognitive decline with sex, age and education entered as covariates.
Results: At baseline, MS patients had a mean disease duration of 14.77 (SD=8.43) years, with an average cognitive performance of Z=-0.70 (SD=0.83). After five years, the cognitive performance decreased to Z = -0.92 (SD=0.92), resulting in an average rate of cognitive decline in patients of Z=-0.05/yr (Interquartile range: -0.09 to 0.02), which was significant compared to the HC decline rate of Z=0.00 (p< 0.01). A faster rate of cognitive decline in patients was independently predicted (adjusted R2 = 0.15, p< 0.001) by a lower level of education (β=0.17), higher average cognitive performance at baseline (β=-0.35), progressive disease types (β=0.21), lower deep grey matter volumes (β=0.18) and lower white matter integrity (β=0.25).
Conclusion: These results demonstrate that baseline MRI measures of grey and white matter damage help to predict future cognitive decline. Future studies are now needed to elucidate the mechanisms of how these structural abnormalities lead to disturbances in brain function and cognitive impairment.
Disclosure: Mr. Eijlers receives research support from the Dutch MS Research Foundation, grant number 14-358e.
Ms. Dekker receives research support from the Dutch MS Research Foundation, grant number 14-358e and has received speakers honoraria from Roche.
Ms. Meijer receives a research grant from Biogen.
Prof. Uitdehaag has received consultancy fees from Biogen Idec, Genzyme, Merck Serono, Novartis, Roche and Teva.
Prof. Barkhof serves as a consultant for Bayer-Schering Pharma, Sanofi-Aventis, Biogen, Teva, Novartis, Roche, Synthon BV, Genzyme and Jansen Research.
Prof. Geurts is an editor of Multiple Sclerosis Journal, a member of the editorial boards of BMC Neurology, Neurology and Frontiers in Neurology, and serves as a consultant for Biogen and Genzyme.
Dr. Schoonheim receives research support from the Dutch MS Research Foundation, grant number 13-820, has received compensation for consulting services or speaker honoraria from ExceMed, Genzyme and Biogen and serves on the editorial board of Frontiers in Neurology.
Abstract: 104
Type: Oral
Abstract Category: Pathology and pathogenesis of MS - 21 Imaging
Background: Cognitive decline in multiple sclerosis (MS) is heterogeneous and strongly affects overall quality of life. Despite recent advances in structural brain imaging methodology, such as diffusion tensor imaging (DTI) and more accurate brain atrophy measurements, the lack of longitudinal data limits knowledge on which structural measures best predict the rate of cognitive decline. The objective of this study was to identify which structural MRI measures predict cognitive decline during a 5-year follow-up period.
Methods: A total of 234 clinically definite MS patients and 60 healthy controls (HC) were seen twice, with a 5-year interval. Structural MRI measures (3T) at baseline included cortical, deep grey matter and white matter volumes (using 3DT1), lesion volumes (using FLAIR) and the severity of white matter integrity loss (using DTI). An extensive neuropsychological evaluation based on the BRB-N was performed at both time points. Cognitive scores were corrected for effects of sex, normal aging and education at both time points and then transformed into seven cognitive domain Z-scores. Changes in individual Z-scores were divided by the interval duration and averaged across domains, to obtain a global score for the yearly rate of cognitive decline for each subject. A forward selection regression model was used to determine which baseline measures significantly predicted cognitive decline with sex, age and education entered as covariates.
Results: At baseline, MS patients had a mean disease duration of 14.77 (SD=8.43) years, with an average cognitive performance of Z=-0.70 (SD=0.83). After five years, the cognitive performance decreased to Z = -0.92 (SD=0.92), resulting in an average rate of cognitive decline in patients of Z=-0.05/yr (Interquartile range: -0.09 to 0.02), which was significant compared to the HC decline rate of Z=0.00 (p< 0.01). A faster rate of cognitive decline in patients was independently predicted (adjusted R2 = 0.15, p< 0.001) by a lower level of education (β=0.17), higher average cognitive performance at baseline (β=-0.35), progressive disease types (β=0.21), lower deep grey matter volumes (β=0.18) and lower white matter integrity (β=0.25).
Conclusion: These results demonstrate that baseline MRI measures of grey and white matter damage help to predict future cognitive decline. Future studies are now needed to elucidate the mechanisms of how these structural abnormalities lead to disturbances in brain function and cognitive impairment.
Disclosure: Mr. Eijlers receives research support from the Dutch MS Research Foundation, grant number 14-358e.
Ms. Dekker receives research support from the Dutch MS Research Foundation, grant number 14-358e and has received speakers honoraria from Roche.
Ms. Meijer receives a research grant from Biogen.
Prof. Uitdehaag has received consultancy fees from Biogen Idec, Genzyme, Merck Serono, Novartis, Roche and Teva.
Prof. Barkhof serves as a consultant for Bayer-Schering Pharma, Sanofi-Aventis, Biogen, Teva, Novartis, Roche, Synthon BV, Genzyme and Jansen Research.
Prof. Geurts is an editor of Multiple Sclerosis Journal, a member of the editorial boards of BMC Neurology, Neurology and Frontiers in Neurology, and serves as a consultant for Biogen and Genzyme.
Dr. Schoonheim receives research support from the Dutch MS Research Foundation, grant number 13-820, has received compensation for consulting services or speaker honoraria from ExceMed, Genzyme and Biogen and serves on the editorial board of Frontiers in Neurology.