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The effect of small vessel disease lesions on structural brain network1Department of Diagnostic Radiology, The University of Hong Kong, HKSAR, China, 2Department of Medicine, The University of Hong Kong, HKSAR, China, 3The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, HKSAR, China, 4Philips Healthcare, HKSAR, China
Synopsis
We aim to explore the influences of cerebral small vessel disease (SVD) lesion on the structural brain network of patients with transient ischemic attack or acute stroke. Our results demonstrated that the efficiency of both global and regional network of patients with SVD were lower compared to those without, and that higher total SVD burden was significantly associated with decreased network efficiency. These results suggested that both presence and severity of SVD related lesion load is associated with disrupted network organization, and brain network analysis is a sensitive method to monitor and assess SVD.
Purpose
Non-demented elderly with cerebral small vessel disease (SVD) were found to have impaired structural brain connectivity, and subtle cognitive deficits were associated with the thereof 1,2. Considering the significant role of small vessel disease (SVD) in Alzheimer disease and vascular dementia 3, that in the patients with stroke and transient ischemic attack (TIA) should also be investigated. We therefore aim to investigate the effect of SVD lesions on the structural brain network of these patients, and the association between SVD lesion burden and the thereof.Materials and Methods
Participants Patients with TIA or acute stroke (n = 95) were recruited, with n = 59 having SVD lesions, and n = 36 without, whom are considered as controls. Both groups were matched by age, gender, and stroke diagnosis.
Experiments and Brain Network Construction DWIs were acquired using single-shot EPI with b values of 1000 and 2000 s/mm2 along 32 gradient directions using a 3.0T MRI scanner (Achieva TX scanner, Philips Healthcare). 3D-MPRAGE images were segmented into 90 brain regions according to AAL atlas. Whole-brain tractography was obtained using Diffusion Toolkit (trackvis.org/dtk/). Fiber tracts traversing two regions were counted, resulting in a connectivity matrix. Global and regional network measures were obtained using the Brain Connectivity Toolbox4.
Image analysis SWI, T2-weighted images and FLAIR images were used to detect the presence of cerebral microbleeds, lacunar infarcts, high-grade white matter hyperintensities, and high-grade perivascular spaces. The SVD burden was assessed for each subject by using the total SVD score that is on an ordinal scale from 0 to 4 5.
Statistical analysis Independent-samples t-test was used to test the difference in network measures between patients with and without SVD lesions. The associations between network measures and total SVD score were investigated using Pearson correlation. Correction for multiple comparison was performed using Bonferroni-correction.
Results
Significantly longer characteristic path length (p = 0.003) and lower global efficiency (p = 0.005) were observed in patients with SVD compared to those without. Lower local clustering coefficient in hippocampus (p = 0.005), lower betweenness centrality in insular (p = 0.039) and precuneus (p = 0.036), as well as decreased nodal efficiency in supplementary motor area (p = 0.021), paracentral lobule (p = 0.045), putamen (p = 0.048) and hippocampus (p = 0.021) were also found in patients with SVD (Figure 1). Characteristic path length (r = 0.337, p = 0.003), global efficiency (r = -0.391, p = 0.002) and local efficiency (r = -0.363, p = 0.005) were correlated with total SVD score (Figure 2). The local clustering coefficient of hippocampus (r = -0.429, p = 0.001), and the nodal efficiency of hippocampus (r = -0.316, p = 0.015) and paracentral lobule (r = -0.325, p = 0.012) were associated with the total SVD score (Figure 3).
Discussions
Functional integration is one of the most essential goals a brain network needs to maintain for supporting cognition and behavior 6. In the current study, the network of stroke or TIA patients with SVD had significantly larger characteristic path length and lower global efficiency, indicating that the ability of rapid information exchange between globally distributed brain regions was compromised 7, potentially related to the impaired general cognitive function of these patients 8. Our results are in line with a previous study, which demonstrated reduced network efficiency in symptomatic SVD 1. In addition to global network changes, disrupted nodal characteristics were also found in multiple brain regions that reside in the limbic system, default mode network and motor system. These local network changes may explain the motor 9 and cognitive disturbance 10 in these patients, and further supported the idea that disrupted structural brain connections might be the most important underlying mechanism behind SVD 11. On the other hand, we found that lower global and regional network efficiency were associated with greater SVD lesion burden or disease severity. Considering that total SVD score is significantly associated with cognitive ability 12 and is predictive of cognitive decline 13, the association between network measures and total SVD score that we observe may serve as corroborative evidence for the notion that structural brain network disruption would lead to cognitive impairment 1,2.Conclusion
Our findings showed that SVD related lesions could lead to widespread disruption in both global and regional network. More importantly, higher SVD burden was associated with greater network disruption, suggesting that network analysis is a potential method to monitor and assess patients with SVD.Acknowledgements
This work was fully supported by the Research Grants Council of the Hong Kong Special Administrative Region, China, HKU 17108514References
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