Different network functional connectivity characteristics of responders and non-responders to attention training in MS
ECTRIMS Online Library. Prouskas S. 09/11/19; 279067; P707
Stefanos Enricos Prouskas
Stefanos Enricos Prouskas
Contributions
Abstract

Abstract: P707

Type: Poster Sessions

Abstract Category: RIMS - Symptoms Management (including cognition, fatigue, imbalance)

S.E. Prouskas1, M.D. Steenwijk1, K. Gehring2,3, M. Huiskamp1, B.A. de Jong4, J.J.G. Geurts1, M.M. Sitskoorn2, M.M. Schoonheim1, H.E. Hulst1

1Department of Anatomy and Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, 2Department of Cognitive Neuropsychology, Tilburg University, 3Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, 4Department of Neurology, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands

Background: Cognitive rehabilitation has been suggested as a means to improve cognitive function. However, cognitive rehabilitation is only effective in a subset of MS patients. It is therefore imperative to identify characteristics that might influence the ability to respond to rehabilitation of cognitive impairment. While cognitive impairment in MS is related to changes in functional connectivity (FC) of cognitive brain networks such as the default mode network (DMN), it is unknown how functional network characteristics affect the brain's ability to respond to cognitive training.
Aim: To investigate whether baseline resting-state FC within and between the DMN, dorsal attention network (DAN) and ventral attention network (VAN), can distinguish responders from non-responders to an attention training in MS.
Methods: Patients were randomized into an attention training (home-based computerized C-Car: 7-week, 45 min/week, N=58, age=48.4±10.2 years, 34 women, RRMS=42, median EDSS=4.0) or a waiting-list control group (CG, N=24, age=48.5±9.4 years, 19 women, RRMS=16, median EDSS=4.0). Neuropsychological assessment at baseline and follow-up included tests of attention, memory, information processing speed, and executive functioning. Based on the CG, a reliable change index (RCI) was calculated, adjusted for practice effects. Responders were defined as patients scoring RCI>1.64 (90% CI) on at least two tests. 3D T1 MRI and resting-state fMRI was obtained at baseline. After preprocessing and denoising using ICA-AROMA, a subject-wise fMRI correlation matrix was computed. Within- and between-network measures of FC of the DMN, DAN, and VAN were calculated using relative correlations and the Brainnetome atlas and compared between responders and non-responders.
Results: Responders (N=22) and non-responders (N=36) did not differ significantly in age, sex, education, MS subtype, EDSS, disease duration, or baseline cognition. Responders, compared to non-responders, had lower average FC between DMN and DAN (0.85 vs 0.92 respectively; p=0.04) and DMN and VAN (0.90 vs 0.98 respectively; p=0.04). There were no significant group differences in within-network FC.
Conclusion: Lower FC between DMN and attention networks seems an indicator of response to attention training in MS, which might reflect a more intact network functioning at baseline.
Disclosure: S.E. Prouskas has nothing to disclose.
M.D. Steenwijk has nothing to disclose.
K. Gehring has nothing to disclose.
M. Huiskamp has nothing to disclose.
B.A. de Jong received speaker and consulting fees from Merck-Serono, Biogen, TEVA, Genzyme, and Novartis.
J.J.G. Geurts is an editor of MS journal and serves on the editorial boards of Neurology and Frontiers of Neurology and is president of the Netherlands organization for health research and innovation and has served as a consultant for Merck-Serono, Biogen, Novartis, Genzyme and Teva Pharmaceuticals.
M.M. Sitskoorn has nothing to disclose.
M.M. Schoonheim serves on the editorial board of Frontiers of Neurology, receives research support from the Dutch MS Research Foundation, grant number 13-820, and has received compensation for consulting services or speaker honoraria from ExceMed, Genzyme and Biogen.
H.E. Hulst serves on the editorial board of MSJ and has received compensation for consulting services or speaker honoraria from Sanofi Genzyme, Merck Serono and Biogen Idec.

Abstract: P707

Type: Poster Sessions

Abstract Category: RIMS - Symptoms Management (including cognition, fatigue, imbalance)

S.E. Prouskas1, M.D. Steenwijk1, K. Gehring2,3, M. Huiskamp1, B.A. de Jong4, J.J.G. Geurts1, M.M. Sitskoorn2, M.M. Schoonheim1, H.E. Hulst1

1Department of Anatomy and Neurosciences, Amsterdam UMC, Location VU University Medical Center, Amsterdam, 2Department of Cognitive Neuropsychology, Tilburg University, 3Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, 4Department of Neurology, Amsterdam UMC, Location VU University Medical Center, Amsterdam, The Netherlands

Background: Cognitive rehabilitation has been suggested as a means to improve cognitive function. However, cognitive rehabilitation is only effective in a subset of MS patients. It is therefore imperative to identify characteristics that might influence the ability to respond to rehabilitation of cognitive impairment. While cognitive impairment in MS is related to changes in functional connectivity (FC) of cognitive brain networks such as the default mode network (DMN), it is unknown how functional network characteristics affect the brain's ability to respond to cognitive training.
Aim: To investigate whether baseline resting-state FC within and between the DMN, dorsal attention network (DAN) and ventral attention network (VAN), can distinguish responders from non-responders to an attention training in MS.
Methods: Patients were randomized into an attention training (home-based computerized C-Car: 7-week, 45 min/week, N=58, age=48.4±10.2 years, 34 women, RRMS=42, median EDSS=4.0) or a waiting-list control group (CG, N=24, age=48.5±9.4 years, 19 women, RRMS=16, median EDSS=4.0). Neuropsychological assessment at baseline and follow-up included tests of attention, memory, information processing speed, and executive functioning. Based on the CG, a reliable change index (RCI) was calculated, adjusted for practice effects. Responders were defined as patients scoring RCI>1.64 (90% CI) on at least two tests. 3D T1 MRI and resting-state fMRI was obtained at baseline. After preprocessing and denoising using ICA-AROMA, a subject-wise fMRI correlation matrix was computed. Within- and between-network measures of FC of the DMN, DAN, and VAN were calculated using relative correlations and the Brainnetome atlas and compared between responders and non-responders.
Results: Responders (N=22) and non-responders (N=36) did not differ significantly in age, sex, education, MS subtype, EDSS, disease duration, or baseline cognition. Responders, compared to non-responders, had lower average FC between DMN and DAN (0.85 vs 0.92 respectively; p=0.04) and DMN and VAN (0.90 vs 0.98 respectively; p=0.04). There were no significant group differences in within-network FC.
Conclusion: Lower FC between DMN and attention networks seems an indicator of response to attention training in MS, which might reflect a more intact network functioning at baseline.
Disclosure: S.E. Prouskas has nothing to disclose.
M.D. Steenwijk has nothing to disclose.
K. Gehring has nothing to disclose.
M. Huiskamp has nothing to disclose.
B.A. de Jong received speaker and consulting fees from Merck-Serono, Biogen, TEVA, Genzyme, and Novartis.
J.J.G. Geurts is an editor of MS journal and serves on the editorial boards of Neurology and Frontiers of Neurology and is president of the Netherlands organization for health research and innovation and has served as a consultant for Merck-Serono, Biogen, Novartis, Genzyme and Teva Pharmaceuticals.
M.M. Sitskoorn has nothing to disclose.
M.M. Schoonheim serves on the editorial board of Frontiers of Neurology, receives research support from the Dutch MS Research Foundation, grant number 13-820, and has received compensation for consulting services or speaker honoraria from ExceMed, Genzyme and Biogen.
H.E. Hulst serves on the editorial board of MSJ and has received compensation for consulting services or speaker honoraria from Sanofi Genzyme, Merck Serono and Biogen Idec.

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