Alterations and test–retest reliability of functional connectivity network measures in cerebral small vessel disease

Abstract

While structural network analysis consolidated the hypothesis of cerebral small vessel disease (SVD) being a disconnection syndrome, little is known about functional changes on the level of brain networks. In patients with genetically defined SVD (CADASIL, n = 41) and sporadic SVD (n = 46), we independently tested the hypothesis that functional networks change with SVD burden and mediate the effect of disease burden on cognitive performance, in particular slowing of processing speed. We further determined test–retest reliability of functional network measures in sporadic SVD patients participating in a high‐frequency (monthly) serial imaging study (RUN DMC—InTENse, median: 8 MRIs per participant). Functional networks for the whole brain and major subsystems (i.e., default mode network, DMN; fronto‐parietal task control network, FPCN; visual network, VN; hand somatosensory‐motor network, HSMN) were constructed based on resting‐state multi‐band functional MRI. In CADASIL, global efficiency (a graph metric capturing network integration) of the DMN was lower in patients with high disease burden (standardized beta = −.44; p [corrected] = .035) and mediated the negative effect of disease burden on processing speed (indirect path: std. beta = −.20, p = .047; direct path: std. beta = −.19, p = .25; total effect: std. beta = −.39, p = .02). The corresponding analyses in sporadic SVD showed no effect. Intraclass correlations in the high‐frequency serial MRI dataset of the sporadic SVD patients revealed poor test–retest reliability and analysis of individual variability suggested an influence of age, but not disease burden, on global efficiency. In conclusion, our results suggest that changes in functional connectivity networks mediate the effect of SVD‐related brain damage on cognitive deficits. However, limited reliability of functional network measures, possibly due to age‐related comorbidities, impedes the analysis in elderly SVD patients.

Functional connectivity changes in cerebral small vessel disease - a systematic review of the resting-state MRI literature

“…temporal gyrus, left middle temporal gyrus, left precentral gyrus, and left sup. parietal lobule High (2) [ 29 ] 29 CSVD WMH (clinical diagnosis) WMH volume VRF 0, 20.4 ± 19.3 VRF 1, 27.3 ± 21.5 VRF 3, 17.4 ± 19.5 MoCA VRF 0, 25.8 ± 3.5 VRF 1, 22.0 ± 6.2 VRF 3, 21.0 ± 5.4 Philips Achieva, 3 T TR 2000 ms, TE 30 ms 64 × 64 × 40 3.6 × 2.9 × 3 mm 3 184–259 volumes, [eyes] FSL v4.1 Confound regression - ICA Motion scrubbing - ‘relative motion’ > 1.5 mm ICA to define DMN, SMN, medial-visual RSN Pearson correlation FC in DMN ↗ cardiovascular reactivity Moderate (4) [ 30 ] 21 CSVD-CN 16 CSVD-MCI 13 SVaD WMH (clinical diagnosis) MMSE CN 28.9 ± 0.7 MCI 26.3 ± 1.0 SVaD 20.5 ± 2.3 MoCA CN 24.6 ± 2.9 MCI 20.6 ± 2.8 SVaD 15.1 ± 3.6 Siemens, 3 T TR 2480 ms, TE 30 ms 64 × 64 × 36, 3 × 3 × 4 mm 3 240 volumes eyes closed SPM 8 [Confound regression] Motion scrubbing - Head motion > 2 mm/2° AAL atlas Pearson correlation, (extended) maximal information coefficient SVM classification None High (3) [ 31 ] 46 CSVD 41 CADASIL WMH volume 0.3% [0.03, 3.1]% of intracranial volume Lacunes 0 (0) [0–20] MMSE median 29, IQR [ 26 , 32 ] Siemens Skyra/Prisma, 3 T, 64-/32-channel head coils, multi-band × 8 TR 700 ms, TE 39 ms [matrix] 3 × 3 × 3 mm 3 2.4 × 2.4 × 2.4 mm 3 675–700 volumes eyes closed FSL, ANTs, BRAMILA v2.0 Confound regression - ICA-AROMA non-aggressive - Linear trend, 6 motion params - GSR: CSF, WM Motion scrubbing - Volume censoring (FD > 0.5 mm, total time < 5 min) Power atlas to define DMN, FPCN, hand-SMN, VN Pearson correlation graph theory No association between WMH and FC Poor reproducibility of network measures in CSVD Moderate (6) [ 33 ] 33 MCI with confluent (C) WMH 30 MCI with non-confluent (NC) WMH Fazekas ...…”

“…Beyond the presence of white matter lesions, evidence of lacunes or recent lacunar infarcts was considered in 13/24 studies; the distinction between the two entities was often imprecise, with only three articles referring to the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE, [ 6 ]) consensus statement in this context [ 31 , 50 , 51 ]. Reflecting their conceptualisation as fluid-filled cavities, lacunes were defined as hypointense ovoid regions on T2- or FLAIR-weighted imaging with a diameter ranging from [2–3] to [15–20] mm.…”

“…Twenty-five studies employed subject-wise censoring in which participants were excluded from further analysis if the maximum or average head translation or rotation during the scan exceeded a certain threshold ranging from 0.5 to 3 mm translation and 0.5 to 3° rotation. Ten studies performed volume censoring according to a framewise displacement (FD) or framewise translation/rotation cut-off, excluding participants with too few remaining uncontaminated volumes [ 31 , 49 ]. Two studies used spike regression [ 39 , 65 ].…”

“…Many authors interpreted alterations in functional connectivity in the context of a small number of large-scale resting-state brain networks (RSNs), in particular the default mode (DMN) and frontoparietal control (FPCN) networks, but also the dorsal attention (DAN) and salience (SN) networks [ 22 ]. Eight reports used graph theoretical approaches, including global network parameters such as efficiency and clustering coefficient [ 31 , 42 , 43 , 52 , 53 ]; analysis of modularity structures [ 45 , 50 ]; and self-referential quantification of region-specific centrality [ 35 ] to summarise the patterns of connectivity between multiple regions and to thus reflect global organisational principles of the brain networks.…”

“…Risk factors and outcomes (Item 7) were mostly valid (see above); exceptions included one unvalidated method to quantify WMH load [ 87 ] and the use of global graph parameters such as efficiency and path length. Reliability of outcome measures (Item 9) was generally judged to be low given the poor reproducibility of FC estimates in the context of CSVD, except for studies who explicitly estimated reliability as part of the study design [ 31 , 42 ]. There were two main problems with the statistical methods used: firstly, confusion of exploratory and confirmatory approaches (cf.…”