Brain network topology early after stroke relates to recovery

Abstract

Analyses of alterations of brain networks have gained an increasing interest in stroke rehabilitation research. Compared to functional networks derived from resting-state analyses, there is limited knowledge of how structural network topology might undergo changes after stroke and, more importantly, if structural network information obtained early after stroke could enhance recovery models to infer later outcome. The present work re-analysed cross-sectional structural imaging data, obtained within the first two weeks, of 45 acute stroke patients (22 females, 24 right-sided strokes, age 68±13 years). Whole-brain tractography was performed to reconstruct structural connectomes and graph-theoretical analyses were employed to quantify global network organisation with a focus on parameters of network integration and modular processing. Graph measures were compared between stroke patients and 34 healthy controls (15 females, aged 69±10 years) and they were integrated with four clinical scores of the late subacute stage, covering neurological symptom burden (National Institutes of Health Stroke Scale stroke scale), global disability (modified Rankin Scale), activity-related disability (Barthel-Index), and motor functions (Upper-Extremity Score of the Fugl-Meyer Assessment). The analyses were employed across the complete cohort and, based on clustering analysis, separately within subgroups stratified in mild to moderate (n=21) and severe (n=24) initial deficits. The main findings were (1) a significant reduction of network’s global efficiency, specifically in patients with severe deficits compared with controls (P=0.010), and (2) a significant negative correlation of network efficiency with the extent of persistent functional deficits at follow-up after three to six months (P≤0.032). Specifically, regression models revealed that this measure was capable to increase the explained variance in future deficits by 18 % for modified Rankin Scale, up to 24 % for National Institutes of Health Stroke Scale stroke scale), and 16 % for Barthel-Index when compared to models including the initial deficits and the lesion volume. Patients with mild to moderate deficits did not exhibit a similar impact of network efficiency on outcome inference. Clustering coefficient and modularity, measures of segregation and modular processing, did not exhibit comparable structure-outcome relationships, neither in severely nor in mildly affected patients. This study provides empirical evidence that structural network efficiency as a graph-theoretical marker of large-scale network topology, quantified early after stroke, relates to recovery. Notably, this contribution was only evident in severely but not mildly affected stroke patients. This suggests that the initial clinical deficit might shape the dependency of recovery on global network topology after stroke.

Retracted and Replaced: Altered microstructure of the contralesional ventral premotor cortex and motor output after stroke

“…The rational for this approach was that previous studies have found that patients with complete or almost complete recovery were found to exhibit much weaker relationships between brain structure and outcome 34 , 35 and that structure–outcome relationships might be particularly driven by more impaired patients and might not generalize to patients with minor deficits. 36 Table 1 summarizes the demographic and clinical data.…”

Frontoparietal structural network disconnections correlate with outcome after a severe stroke

“…Stroke lesions were semi-automatically delineated with SNAP-ITK 29 and available from our previous analyses [26][27][28]30 . The resulting lesion masks were registered to a 1-mm 3 Montreal Neurological Institute (MNI) template.…”

Localized network damage related to white matter hyperintensities is linked to worse outcome after severe stroke

“…7 However, from a systems neuroscience perspective, WMH may impact recovery trajectories by affecting large-scale structural and functional brain networks 9,10 as numerous studies have consistently reported that the state of structural brain networks, quantified early after acute stroke, can inform about subsequent recovery. [11][12][13] WMH-related network damage could serve as a surrogate for pre-existing disturbances in brain networks, and it could be a novel approach to better understand the underlying mechanisms of brain reserve capacity 14 and outcome variability after stroke, as recently evidenced for cortical and cerebellar brain anatomy. 15,16 The present study sought to answer the question whether the extent of WMH-related network damage, quantified early after severe ischemic stroke, can explain outcome variability.…”