Meso-cortical pathway damage in cognition, apathy and gait in cerebral small vessel disease

Cerebral small vessel disease (SVD) is known to contribute to cognitive impairment, apathy, and gait dysfunction. Although associations between cognitive impairment and either apathy or gait dysfunction have been shown in SVD, the inter-relations among these three clinical features and their potential common neural basis remains unexplored. The dopaminergic meso-cortical and meso-limbic pathways have been known as the important brain circuits for both cognitive control, emotion regulation and motor function. Here, we investigated the potential inter-relations between cognitive impairment, apathy, and gait dysfunction, with a specific focus on determining whether these clinical features are associated with damage to the meso-cortical and meso-limbic pathways in SVD. In this cross-sectional study, we included 213 participants with SVD in whom MRI scans and comprehensive neurobehavioral assessments were administered. These assessments comprised of six clinical measures: processing speed, executive function, memory, apathy (based on the Apathy Evaluation Scale), and gait function (based on the time and steps in Timed Up and Go test). We reconstructed five tracts connecting ventral tegmental area (VTA) and the dorsolateral prefrontal cortex (dlPFC), ventral lateral PFC (vlPFC), medial orbitofrontal cortex (mOFC), anterior cingulate cortex (ACC) and nucleus accumbens (NAc) within meso-cortical and meso-limbic pathways using diffusion weighted imaging. The damage along the five tracts was quantified using the free water (FW) and FW-corrected mean diffusivity (MD-t) indices. Furthermore, we explored the inter-correlations among the six clinical measures and identified their common components using principal component analysis (PCA). Linear regression analyses showed that higher FW values of tracts within meso-cortical pathways were related to these clinical measures in cognition, apathy, and gait (all P-corrected values < 0.05). PCA showed strong inter-associations among these clinical measures and identified a common component wherein all six clinical measures loaded on. Higher FW values of tracts within meso-cortical pathways were related to the PCA-derived common component (all P-corrected values < 0.05). Moreover, FW values of VTA-ACC tract showed the strongest contribution to the PCA-derived common component over all other neuroimaging features. In conclusion, our study showed that the three clinical features (cognitive impairment, apathy, and gait dysfunction) of SVD are strongly inter-related and that the damage in meso-cortical pathway could be the common neural basis underlying the three features in SVD. These findings advance our understanding of the mechanisms behind these clinical features of SVD and have the potential to inform novel management and intervention strategies for SVD.

Perivascular Spaces, Diffusivity Along Perivascular Spaces, and Free Water in Cerebral Small Vessel Disease

BACKGROUND AND OBJECTIVES

Previous studies have linked the MRI measures of perivascular spaces (PVSs), diffusivity along the perivascular spaces (DTI-ALPS), and free water (FW) to cerebral small vessel disease (SVD) and SVD-related cognitive impairments. However, studies on the longitudinal associations between the three MRI measures, SVD progression, and cognitive decline are lacking. This study aimed to explore how PVS, DTI-ALPS, and FW contribute to SVD progression and cognitive decline.

METHODS

This is a cohort study that included participants with SVD who underwent neuroimaging and cognitive assessment, specifically measuring Mini-Mental State Examination (MMSE), cognitive index, and processing speed, at 2 time points. Three MRI measures were quantified: PVS in basal ganglia (BG-PVS) volumes, FW fraction, and DTI-ALPS. We performed a latent change score model to test inter-relations between the 3 MRI measures and linear regression mixed models to test their longitudinal associations with the changes of other SVD MRI markers and cognitive performances.

RESULTS

In baseline assessment, we included 289 participants with SVD, characterized by a median age of 67.0 years and 42.9% women. Of which, 220 participants underwent the follow-up assessment, with a median follow-up time of 3.4 years. Baseline DTI-ALPS was associated with changes in BG-PVS volumes (β = -0.09, p = 0.030), but not vice versa (β = -0.08, p = 0.110). Baseline BG-PVS volumes were associated with changes in white matter hyperintensity (WMH) volumes (β = 0.33, p-corrected < 0.001) and lacune numbers (β = 0.28, p-corrected < 0.001); FW fraction was associated with changes in WMH volumes (β = 0.30, p-corrected < 0.001), lacune numbers (β = 0.28, p-corrected < 0.001), and brain volumes (β = -0.45, p-corrected < 0.001); DTI-ALPS was associated with changes in WMH volumes (β = -0.20, p-corrected = 0.002) and brain volumes (β = 0.23, p-corrected < 0.001). Furthermore, baseline FW fraction was associated with decline in MMSE score (β = -0.17, p-corrected = 0.006); baseline FW fraction and DTI-ALPS were associated with changes in cognitive index (FW fraction: β = -0.25, p-corrected < 0.001; DTI-ALPS: β = 0.20, p-corrected = 0.001) and processing speed over time (FW fraction: β = -0.29, p-corrected < 0.001; DTI-ALPS: β = 0.21, p-corrected < 0.001).

DISCUSSION

Our results showed that increased BG-PVS volumes, increased FW fraction, and decreased DTI-ALPS are related to progression of MRI markers of SVD, along with SVD-related cognitive decline over time. These findings may suggest that the glymphatic dysfunction is related to SVD progression, but further studies are needed.

Single-shot frequency offset measurement with HASTE using the selective parity approach

Measurements of frequency offset are commonly required in MRI. The standard method measures the signal phase as a function of evolution time. Here we use a single shot turbo-spin-echo acquisition method to measure frequency offset at a single evolution time. After excitation the transverse magnetisation evolves during the evolution time, and is then repeatedly refocused. The phase is conjugated between alternate echoes. Using partial parallel acquisition techniques we obtain separate odd- and even- echo images. An iterative procedure ensures self-consistency between them. The difference in phase between the two images yields frequency offset maps. The technique was implemented at 3 Tesla and tested on a healthy human volunteer for a range of evolution times between 6 and 42 ms. A standard method using a similar readout train and multiple evolution times was used as a gold-standard measure. In a statistical comparison with the gold standard no evidence for bias or offset was found. There was no systematic variation in precision or accuracy as a function of evolution time. We conclude that the presented approach represents a viable method for the rapid generation of frequency offset maps with a high image quality and minimal distortion.

Adiabatic null passage for on-resonance magnetization transfer preparation

PURPOSE

We propose a novel RF pulse providing an adiabatic null passage (ANP) for magnetization transfer preparation with improved insensitivity toB 1 + $$ {\mathrm{B}}_1^{+} $$ and B0 inhomogeneities and mitigated direct saturation and T2 effects.

METHOD

The phase modulation function of a 6-ms time-resampled frequency offset-corrected pulse was modified to achieve zero flip angle at the end of the pulse. The spectral response was simulated, and its insensitivity to B0 andB 1 + $$ {\mathrm{B}}_1^{+} $$ was investigated and compared with a phase-inverted (12 ¯ $$ \overline{2} $$ 1-1 ¯ $$ \overline{1} $$ 21 ¯ $$ \overline{1} $$ ) binomial pulse. The proposed pulse was implemented in a 2D-EPI pulse sequence to generate magnetization transfer (MT) contrast and MT ratio (MTR) maps. In vivo experiments were performed on 3 healthy participants with power-matched settings for ANP and the binomial pulse with the following parameters: 6-ms binomial pulse with a flip angle of 107° (shortest element) and pulse repetition period (PRP) of TRslice  = 59 ms, three experiments with 6-ms ANP and constant MT used overdrive factor (OF)/PRP values of 1/TRslice ,2 $$ \sqrt{2} $$ /2TRslice , and3 $$ \sqrt{3} $$ /3TRslice .

RESULTS

At gray matter (white matter) in vivo, the MTR decreased from 61% (64%) at OF = 1 to 38% (42%) applying ANP with an OF =3 $$ \sqrt{\mathsf{3}} $$ and PRP = 3 TRslice , demonstrating the mitigation of T2 /direct effect by 22% (22%). Bloch-McConnell simulations gave similar values. In vivo experiments showed significant improvement in the MTR values for areas with high B0 inhomogeneity.

CONCLUSION

ANP pulse was shown to be advantageous over its binomial counterpart in providing MT contrast by mitigating the T2 effect and direct saturation of the liquid pool as well as reduced sensitivity toB 1 + $$ {\mathrm{B}}_1^{+} $$ and B0 inhomogeneity.

Changes in postictal cerebral perfusion are related to the duration of electroconvulsive therapy-induced seizures

OBJECTIVE

Postictal symptoms may result from cerebral hypoperfusion, which is possibly a consequence of seizure-induced vasoconstriction. Longer seizures have previously been shown to cause more severe postictal hypoperfusion in rats and epilepsy patients. We studied cerebral perfusion after generalized seizures elicited by electroconvulsive therapy (ECT) and its relation to seizure duration.

METHODS

Patients with a major depressive episode who underwent ECT were included. During treatment, 21-channel continuous electroencephalogram (EEG) was recorded. Arterial spin labeling magnetic resonance imaging scans were acquired before the ECT course (baseline) and approximately 1 h after an ECT-induced seizure (postictal) to quantify global and regional gray matter cerebral blood flow (CBF). Seizure duration was assessed from the period of epileptiform discharges on the EEG. Healthy controls were scanned twice to assess test-retest variability. We performed hypothesis-driven Bayesian analyses to study the relation between global and regional perfusion changes and seizure duration.

RESULTS

Twenty-four patients and 27 healthy controls were included. Changes in postictal global and regional CBF were correlated with seizure duration. In patients with longer seizure durations, global decrease in CBF reached values up to 28 mL/100 g/min. Regional reductions in CBF were most prominent in the inferior frontal gyrus, cingulate gyrus, and insula (up to 35 mL/100 g/min). In patients with shorter seizures, global and regional perfusion increased (up to 20 mL/100 g/min). These perfusion changes were larger than changes observed in healthy controls, with a maximum median global CBF increase of 12 mL/100 g/min and a maximum median global CBF decrease of 20 mL/100 g/min.

SIGNIFICANCE

Seizure duration is a key factor determining postictal perfusion changes. In future studies, seizure duration needs to be considered as a confounding factor due to its opposite effect on postictal perfusion.

Structural Network Efficiency Predicts Conversion to Incident Parkinsonism in Patients With Cerebral Small Vessel Disease

BACKGROUND

To investigate whether structural network disconnectivity is associated with parkinsonian signs and their progression, as well as with an increased risk of incident parkinsonism.

METHODS

In a prospective cohort (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort study) consisting of 293 participants with small vessel disease (SVD), we assessed parkinsonian signs and incident parkinsonism over an 8-year follow-up. In addition, we reconstructed the white matter network followed by graph-theoretical analyses to compute the network metrics. Conventional magnetic resonance imaging markers for SVD were assessed.

RESULTS

We included 293 patients free of parkinsonism at baseline (2011), with a mean age 68.8 (standard deviation [SD] 8.4) years, and 130 (44.4%) were men. Nineteen participants (6.5%) developed parkinsonism during a median (SD) follow-up time of 8.3 years. Compared with participants without parkinsonism, those with all-cause parkinsonism had higher Unified Parkinson's Disease Rating scale (UPDRS) scores and lower global efficiency at baseline. Baseline global efficiency was associated with UPDRS motor scores in 2011 (β = -0.047, p < .001) and 2015 (β = -0.84, p < .001), as well as with the changes in UPDRS scores during the 4-year follow-up (β = -0.63, p = .004). In addition, at the regional level, we identified an inter-hemispheric disconnected network associated with an increased UPDRS motor score. Besides, lower global efficiency was associated with an increased risk of all-cause and vascular parkinsonism independent of SVD markers.

CONCLUSIONS

Our findings suggest that global network efficiency is associated with a gradual decline in motor performance, ultimately leading to incident parkinsonism in the elderly with SVD. Global network efficiency may have the added value to serve as a useful marker to capture changes in motor signs.

Regional cortical thinning, demyelination and iron loss in cerebral small vessel disease

The link between white matter hyperintensities (WMH) and cortical thinning is thought to be an important pathway by which WMH contributes to cognitive deficits in cerebral small vessel disease (SVD). However, the mechanism behind this association and the underlying tissue composition abnormalities are unclear. The objective of this study is to determine the association between WMH and cortical thickness, and the in vivo tissue composition abnormalities in the WMH-connected cortical regions. In this cross-sectional study, we included 213 participants with SVD who underwent standardized protocol including multimodal neuroimaging scans and cognitive assessment (i.e. processing speed, executive function and memory). We identified the cortex connected to WMH using probabilistic tractography starting from the WMH and defined the WMH-connected regions at three connectivity levels (low, medium and high connectivity level). We calculated the cortical thickness, myelin and iron of the cortex based on T1-weighted, quantitative R1, R2* and susceptibility maps. We used diffusion-weighted imaging to estimate the mean diffusivity of the connecting white matter tracts. We found that cortical thickness, R1, R2* and susceptibility values in the WMH-connected regions were significantly lower than in the WMH-unconnected regions (all Pcorrected < 0.001). Linear regression analyses showed that higher mean diffusivity of the connecting white matter tracts were related to lower thickness (β = -0.30, Pcorrected < 0.001), lower R1 (β = -0.26, Pcorrected = 0.001), lower R2* (β = -0.32, Pcorrected < 0.001) and lower susceptibility values (β = -0.39, Pcorrected < 0.001) of WMH-connected cortical regions at high connectivity level. In addition, lower scores on processing speed were significantly related to lower cortical thickness (β = 0.20, Pcorrected = 0.030), lower R1 values (β = 0.20, Pcorrected = 0.006), lower R2* values (β = 0.29, Pcorrected = 0.006) and lower susceptibility values (β = 0.19, Pcorrected = 0.024) of the WMH-connected regions at high connectivity level, independent of WMH volumes and the cortical measures of WMH-unconnected regions. Together, our study demonstrated that the microstructural integrity of white matter tracts passing through WMH is related to the regional cortical abnormalities as measured by thickness, R1, R2* and susceptibility values in the connected cortical regions. These findings are indicative of cortical thinning, demyelination and iron loss in the cortex, which is most likely through the disruption of the connecting white matter tracts and may contribute to processing speed impairment in SVD, a key clinical feature of SVD. These findings may have implications for finding intervention targets for the treatment of cognitive impairment in SVD by preventing secondary degeneration.

Network structure-function coupling and neurocognition in cerebral small vessel disease

BACKGROUND

Cerebral small vessel disease is a leading cause of cognitive decline and vascular dementia. Small vessel disease pathology changes structural brain networks, but its impact on functional networks remains poorly understood. Structural and functional networks are closely coupled in healthy individuals, and decoupling is associated with clinical symptoms in other neurological conditions. We tested the hypothesis that structural-functional network coupling is related to neurocognitive outcomes in 262 small vessel disease patients.

METHODS

Participants underwent multimodal magnetic resonance imaging and cognitive assessment in 2011 and 2015. Structural connectivity networks were reconstructed using probabilistic diffusion tractography, while functional connectivity networks were estimated from resting-state functional magnetic resonance imaging. Structural and functional networks were then correlated to calculate a measure of structural-functional network coupling for each participant.

RESULTS

Lower whole-brain coupling was associated with reduced processing speed and greater apathy both cross-sectionally and longitudinally. In addition, coupling within the cognitive control network was associated with all cognitive outcomes, suggesting that neurocognitive outcomes in small vessel disease may be related to the functioning of this intrinsic connectivity network.

CONCLUSIONS

Our work demonstrates the influence of structural-functional connectivity network decoupling in small vessel disease symptomatology. Cognitive control network function may be investigated in future studies.

Cerebral Small Vessel Disease Progression and the Risk of Dementia: A 14-Year Follow-Up Study

OBJECTIVE

Cerebral small vessel disease (SVD) is considered the most important vascular contributor to cognitive decline and dementia, although a causal relation between its MRI markers and dementia still needs to be established. The authors investigated the relation between baseline SVD severity as well as SVD progression on MRI markers and incident dementia, by subtype, in individuals with sporadic SVD over a follow-up period of 14 years.

METHODS

The study included 503 participants with sporadic SVD, and without dementia, from the prospective Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) study, with screening for baseline inclusion conducted in 2006. Follow-ups in 2011, 2015, and 2020 included cognitive assessments and MRI scans. Dementia was diagnosed according to DSM-5 criteria and stratified into Alzheimer's dementia and vascular dementia.

RESULTS

Dementia as an endpoint was available for 498 participants (99.0%) and occurred in 108 participants (21.5%) (Alzheimer's dementia, N=38; vascular dementia, N=34; mixed-etiology Alzheimer's dementia/vascular dementia, N=26), with a median follow-up time of 13.2 years (interquartile range, 8.8-13.8). Higher baseline white matter hyperintensity (WMH) volume (hazard ratio=1.31 per 1-SD increase, 95% CI=1.02-1.67), presence of diffusion-weighted-imaging-positive lesions (hazard ratio=2.03, 95% CI=1.01-4.04), and higher peak width of skeletonized mean diffusivity (hazard ratio=1.24 per 1-SD increase, 95% CI=1.02-1.51) were independently associated with all-cause dementia and vascular dementia. WMH progression predicted incident all-cause dementia (hazard ratio=1.76 per 1-SD increase, 95% CI=1.18-2.63).

CONCLUSIONS

Both baseline SVD severity and SVD progression were independently associated with an increase in risk of all-cause dementia over a follow-up of 14 years. The results suggest that SVD progression precedes dementia and may causally contribute to its development. Slowing SVD progression may delay dementia onset.

Combining arterial blood contrast with BOLD increases fMRI intracortical contrast

BOLD fMRI is widely applied in human neuroscience but is limited in its spatial specificity due to a cortical-depth-dependent venous bias. This reduces its localization specificity with respect to neuronal responses, a disadvantage for neuroscientific research. Here, we modified a submillimeter BOLD protocol to selectively reduce venous and tissue signal and increase cerebral blood volume weighting through a pulsed saturation scheme (dubbed Arterial Blood Contrast) at 7 T. Adding Arterial Blood Contrast on top of the existing BOLD contrast modulated the intracortical contrast. Isolating the Arterial Blood Contrast showed a response free of pial-surface bias. The results suggest that Arterial Blood Contrast can modulate the typical fMRI spatial specificity, with important applications in in-vivo neuroscience.

A vision of 14 T MR for fundamental and clinical science

OBJECTIVE

We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set.

RESEARCH FIELDS

The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes.

CONCLUSIONS

The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.

Dissociable Contributions of Thalamic-Subregions to Cognitive Impairment in Small Vessel Disease

BACKGROUND

Structural network damage is a potentially important mechanism by which cerebral small vessel disease (SVD) can cause cognitive impairment. As a central hub of the structural network, the role of thalamus in SVD-related cognitive impairments remains unclear. We aimed to determine the associations between the structural alterations of thalamic subregions and cognitive impairments in SVD.

METHODS

In this cross-sectional study, 205 SVD participants without thalamic lacunes from the third follow-up (2020) of the prospective RUN DMC study (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort), which was initiated in 2006, Nijmegen, were included. Cognitive functions included processing speed, executive function, and memory. Probabilistic tractography was performed from thalamus to 6 cortical regions, followed by connectivity-based thalamic segmentation to assess each thalamic subregion volume and connectivity (measured by mean diffusivity [MD] of the connecting white matter tracts) with the cortex. Least absolute shrinkage and selection operator regression analysis was conducted to identify the volumes or connectivity of the total thalamus and 6 thalamic subregions that have the strongest association with cognitive performance. Linear regression and mediation analyses were performed to test the association of least absolute shrinkage and selection operator-selected thalamic subregion volume or MD with cognitive performance, while adjusting for age and education.

RESULTS

We found that higher MD of the thalamic-motor tract was associated with worse processing speed (β=-0.27; P<0.001), higher MD of the thalamic-frontal tract was associated with worse executive function (β=-0.24; P=0.001), and memory (β=-0.28; P<0.001), respectively. The mediation analysis showed that MD of thalamocortical tracts mediated the association between corresponding thalamic subregion volumes and the cognitive performances in 3 domains.

CONCLUSIONS

Our results suggest that the structural alterations of thalamus are linked to cognitive impairment in SVD, largely depending on the damage pattern of the white matter tracts connecting specific thalamic subregions and cortical regions.

Relating neural oscillations to laminar fMRI connectivity in visual cortex

Laminar functional magnetic resonance imaging (fMRI) holds the potential to study connectivity at the laminar level in humans. Here we analyze simultaneously recorded electroencephalography (EEG) and high-resolution fMRI data to investigate how EEG power modulations, induced by a task with an attentional component, relate to changes in fMRI laminar connectivity between and within brain regions in visual cortex. Our results indicate that our task-induced decrease in beta power relates to an increase in deep-to-deep layer coupling between regions and to an increase in deep/middle-to-superficial layer connectivity within brain regions. The attention-related alpha power decrease predominantly relates to reduced connectivity between deep and superficial layers within brain regions, since, unlike beta power, alpha power was found to be positively correlated to connectivity. We observed no strong relation between laminar connectivity and gamma band oscillations. These results indicate that especially beta band, and to a lesser extent, alpha band oscillations relate to laminar-specific fMRI connectivity. The differential effects for alpha and beta bands indicate that they relate to different feedback-related neural processes that are differentially expressed in intra-region laminar fMRI-based connectivity.

Cerebral Small Vessel Disease Progression Increases Risk of Incident Parkinsonism

OBJECTIVE

Cerebral small vessel disease (SVD) is associated with motor impairments and parkinsonian signs cross-sectionally, however, there are little longitudinal data on whether SVD increases risk of incident parkinsonism itself. We investigated the relation between baseline SVD severity as well as SVD progression, and incident parkinsonism over a follow-up of 14 years.

METHODS

This study included 503 participants with SVD, and without parkinsonism at baseline, from the RUN DMC prospective cohort study. Baseline inclusion was performed in 2006 and follow-up took place in 2011, 2015, and 2020, including magnetic resonance imaging (MRI) and motor assessments. Parkinsonism was diagnosed according to the UK Brain Bank criteria, and stratified into vascular parkinsonism (VaP) and idiopathic Parkinson's disease (IPD). Linear mixed-effect models were constructed to estimate individual rate changes of MRI-characteristics.

RESULTS

Follow-up for incident parkinsonism was near-complete (99%). In total, 51 (10.2%) participants developed parkinsonism (33 VaP, 17 IPD, and 1 progressive supranuclear palsy). Patients with incident VaP had higher SVD burden compared with patients with IPD. Higher baseline white matter hyperintensities (hazard ratio [HR] = 1.46 per 1-SD increase, 95% confidence interval [CI] = 1.21-1.78), peak width of skeletonized mean diffusivity (HR = 1.66 per 1-SD increase, 95% CI = 1.34-2.05), and presence of lacunes (HR = 1.84, 95% CI = 0.99-3.42) were associated with increased risk of all-cause parkinsonism. Incident lacunes were associated with incident VaP (HR = 4.64, 95% CI = 1.32-16.32).

INTERPRETATION

Both baseline SVD severity and SVD progression are independently associated with long-term parkinsonism. Our findings indicate a causal role of SVD in parkinsonism. Future studies are needed to examine the underlying pathophysiology of this relation. ANN NEUROL 2023.

Role of small acute hyperintense lesions in long-term progression of cerebral small vessel disease and clinical outcome: a 14-year follow-up study

BACKGROUND

Small hyperintense lesions are found on diffusion-weighted imaging (DWI) in patients with sporadic small vessel disease (SVD). Their exact role in SVD progression remains unclear due to their asymptomatic and transient nature. The main objective is to investigate the role of DWI+lesions in the radiological progression of SVD and their relationship with clinical outcomes.

METHODS

Participants with SVD were included from the Radboud University Nijmegen Diffusion tensor MRI Cohort. DWI+lesions were assessed on four time points over 14 years. Outcome measures included neuroimaging markers of SVD, cognitive performance and clinical outcomes, including stroke, all-cause dementia and all-cause mortality. Linear mixed-effect models and Cox regression models were used to examine the outcome measures in participants with a DWI+lesion (DWI+) and those without a DWI+lesion (DWI-).

RESULTS

DWI+lesions were present in 45 out of 503 (8.9%) participants (mean age: 66.7 years (SD=8.3)). Participants with DWI+lesions and at least one follow-up (n=33) had higher white matter hyperintensity progression rates (β=0.36, 95% CI=0.05 to 0.68, p=0.023), more incident lacunes (incidence rate ratio=2.88, 95% CI=1.80 to 4.67, p<0.001) and greater cognitive decline (β=-0.03, 95% CI=-0.05 to -0.01, p=0.006) during a median follow-up of 13.2 (IQR: 8.8-13.8) years compared with DWI- participants. No differences were found in risk of all-cause mortality, stroke or dementia.

CONCLUSION

Presence of a DWI+lesion in patients with SVD is associated with greater radiological progression of SVD and cognitive decline compared with patients without DWI+lesions.

A comparison of multiband and multiband multiecho gradient-echo EPI for task fMRI at 3 T

A multiband (MB) echo-planar imaging (EPI) sequence is compared to a multiband multiecho (MBME) EPI protocol to investigate differences in sensitivity for task functional magnetic resonance imaging (fMRI) at 3 T. Multiecho sampling improves sensitivity in areas where single-echo-EPI suffers from dropouts. However, It requires in-plane acceleration to reduce the echo train length, limiting the slice acceleration factor and the temporal and spatial resolution Data were acquired for both protocols in two sessions 24 h apart using an adapted color-word interference Stroop task. Besides protocol comparison statistically, we performed test-retest reliability across sessions for different protocols and denoising methods. We evaluated the sensitivity of two different echo-combination strategies for MBME-EPI. We examined the performance of three different data denoising approaches: "Standard," "AROMA," and "FIX" for MB and MBME, and assessed whether a specific method is preferable. We consider using an appropriate autoregressive model order within the general linear model framework to correct TR differences between the protocols. The comparison between protocols and denoising methods showed at group level significantly higher mean z-scores and the number of active voxels for MBME in the motor, subcortical and medial frontal cortices. When comparing different echo combinations, our results suggest that a contrast-to-noise ratio weighted echo combination improves sensitivity in MBME compared to simple echo-summation. This study indicates that MBME can be a preferred protocol in task fMRI at spatial resolution (≥2 mm), primarily in medial prefrontal and subcortical areas.

Spatial Relation Between White Matter Hyperintensities and Incident Lacunes of Presumed Vascular Origin: A 14-Year Follow-Up Study

BACKGROUND

The underlying mechanisms of incident lacunes regarding their spatial distribution remain largely unknown. We investigated the spatial distribution pattern and MRI predictors of incident lacunes in relation to white matter hyperintensity (WMH) over 14 years follow-up in sporadic small vessel disease.

METHODS

Five hundred three participants from the ongoing prospective single-center Radboud University Nijmegen Diffusion Tensor and Magnetic resonance Cohort (RUN DMC) were recruited with baseline assessment in 2006 and follow ups in 2011, 2015, and 2020. Three hundred eighty-two participants who underwent at least 2 available brain MRI scans were included. Incident lacunes were systematically identified, and the spatial relationship between incident lacunes located in subcortical white matter and WMH were determined using a visual rating scale. Adjusted multiple logistic regression and linear mixed-effect regression models were used to assess the association between baseline small vessel disease markers, WMH progression, and incident lacunes. Participants with atrial fibrillation were excluded in multivariable analysis.

RESULTS

Eighty incident lacunes were identified in 43 patients (mean age 66.5±8.2 years, 37.2% women) during a mean follow-up time of 11.2±3.3 years (incidence rate 10.0/1000 person-year). Sixty percent of incident lacunes were in the white matter, of which 48.9% showed no contact with preexisting WMH. Baseline WMH volume (odds ratio=2.5 [95% CI, 1.6-4.2]) predicted incident lacunes after adjustment for age, sex, and vascular risk factors. WMH progression was associated with incident lacunes independent of age, sex, baseline WMH volume, and vascular risk factors (odds ratio, 3.2 [95% CI, 1.5-6.9]). Baseline WMH volume and progression rate were higher in participants with incident lacunes in contact with preexisting WMH. No difference in vascular risk factors was observed regarding location or relation with preexisting WMH.

CONCLUSIONS

The 2 different distribution patterns of lacunes regarding their relation to WMH may suggest distinct underlying mechanisms, one of which may be more closely linked to a similar pathophysiology as that of WMH. The longitudinal relation between WMH and lacunes further supports plausible shared mechanisms between the 2 key markers.

Systematic validation of structural brain networks in cerebral small vessel disease

Cerebral small vessel disease (SVD) is considered a disconnection syndrome, which can be quantified using structural brain network analysis obtained from diffusion MRI. Network analysis is a demanding analysis approach and the added benefit over simpler diffusion MRI analysis is largely unexplored in SVD. In this pre-registered study, we assessed the clinical and technical validity of network analysis in two non-overlapping samples of SVD patients from the RUN DMC study (n = 52 for exploration and longitudinal analysis and n = 105 for validation). We compared two connectome pipelines utilizing single-shell or multi-shell diffusion MRI, while also systematically comparing different node and edge definitions. For clinical validation, we assessed the added benefit of network analysis in explaining processing speed and in detecting short-term disease progression. For technical validation, we determined test-retest repeatability.Our findings in clinical validation show that structural brain networks provide only a small added benefit over simpler global white matter diffusion metrics and do not capture short-term disease progression. Test-retest reliability was excellent for most brain networks. Our findings question the added value of brain network analysis in clinical applications in SVD and highlight the utility of simpler diffusion MRI based markers.

Determinants and Temporal Dynamics of Cerebral Small Vessel Disease: 14-Year Follow-Up

BACKGROUND

The aim of this study is to investigate the temporal dynamics of small vessel disease (SVD) and the effect of vascular risk factors and baseline SVD burden on progression of SVD with 4 neuroimaging assessments over 14 years in patients with SVD.

METHODS

Five hundred three patients with sporadic SVD (50-85 years) from the ongoing prospective cohort study (RUN DMC [Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort]) underwent baseline assessment in 2006 and follow-up in 2011, 2015, and 2020. Vascular risk factors and magnetic resonance imaging markers of SVD were evaluated. Linear mixed-effects model and negative binomial regression model were used to examine the determinants of temporal dynamics of SVD markers.

RESULTS

A total of 382 SVD patients (mean [SD] 64.1 [8.4]; 219 men and 163 women) who underwent at least 2 serial brain magnetic resonance imaging scans were included, with mean (SD) follow-up of 11.15 (3.32) years. We found a highly variable temporal course of SVD. Mean (SD) WMH progression rate was 0.6 (0.74) mL/y (range, 0.02-4.73 mL/y) and 13.6% of patients had incident lacunes (1.03%/y) over the 14-year follow-up. About 4% showed net WMH regression over 14 years, whereas 38 out of 361 (10.5%), 5 out of 296 (2%), and 61 out of 231 (26%) patients showed WMH regression for the intervals 2006 to 2011, 2011 to 2015, and 2015 to 2020, respectively. Of these, 29 (76%), 5 (100%), and 57 (93%) showed overall progression across the 14-year follow-up, and the net overall WMH change between first and last scan considering all participants was a net average WMH progression over the 14-year period. Older age was a strong predictor for faster WMH progression and incident lacunes. Patients with mild baseline WMH rarely progressed to severe WMH. In addition, both baseline burden of SVD lesions and vascular risk factors independently and synergistically predicted WMH progression, whereas only baseline SVD burden predicted incident lacunes over the 14-year follow-up.

CONCLUSIONS

SVD shows pronounced progression over time, but mild WMH rarely progresses to clinically severe WMH. WMH regression is noteworthy during some magnetic resonance imaging intervals, although it could be overall compensated by progression over the long follow-up.

Assessing cortical cerebral microinfarcts on iron-sensitive MRI in cerebral small vessel disease

Recent studies suggest that a subset of cortical microinfarcts may be identifiable on T2* but invisible on T1 and T2 follow-up images. We aimed to investigate whether cortical microinfarcts are associated with iron accumulation after the acute stage. The RUN DMC - InTENse study is a serial MRI study including individuals with cerebral small vessel disease (SVD). 54 Participants underwent 10 monthly 3 T MRIs, including diffusion-weighted imaging, quantitative R1 (=1/T1), R2 (=1/T2), and R2* (=1/T2*) mapping, from which MRI parameters within areas corresponding to microinfarcts and control region of interests (ROIs) were retrieved within 16 participants. Finally, we compared pre- and post-lesional values with repeated measures ANOVA and post-hoc paired t-tests using the mean difference between lesion and control ROI values. We observed 21 acute cortical microinfarcts in 7 of the 54 participants (median age 69 years [IQR 66-74], 63% male). R2* maps demonstrated an increase in R2* values at the moment of the last available follow-up MRI (median [IQR], 5 [5-14] weeks after infarction) relative to prelesional values (p = .08), indicative of iron accumulation. Our data suggest that cortical microinfarcts are associated with increased R2* values, indicative of iron accumulation, possibly due to microhemorrhages, neuroinflammation or neurodegeneration, awaiting histopathological verification.

Longitudinal relation between structural network efficiency, cognition, and gait in cerebral small vessel disease

Background

To investigate changes in gait performance over time and how these changes are associated with the decline in structural network efficiency and cognition in older patients with cerebral small vessel disease (SVD).

Methods

In a prospective, single-center cohort with 217 older participants with SVD, we performed 1.5T MRI scans, cognitive tests, and gait assessments evaluated by Timed UP and Go (TUG) test twice over 4 years. We reconstructed the white matter network for each subject based on diffusion tensor imaging tractography, followed by graph-theoretical analyses to compute the global efficiency. Conventional MRI markers for SVD, that is, white matter hyperintensity (WMH) volume, number of lacunes, and microbleeds, were assessed.

Results

Baseline global efficiency was not related to changes in gait performance, while decline in global efficiency over time was significantly associated with gait decline (ie, increase in TUG time), independent of conventional MRI markers for SVD. Neither baseline cognitive performance nor cognitive decline was associated with gait decline.

Conclusions

We found that disruption of the white matter structural network was associated with gait decline over time, while the effect of cognitive decline was not. This suggests that structural network disruption has an important role in explaining the pathophysiology of gait decline in older patients with SVD, independent of cognitive decline.

Temporal Dynamics of Cortical Microinfarcts in Cerebral Small Vessel Disease

Importance

Neuropathology studies show a high prevalence of cortical microinfarcts (CMIs) in aging individuals, especially in patients with cerebrovascular disease and dementia. However, most, are invisible on T1- and T2-weighted magnetic resonance imaging (MRI), raising the question of how to explain this mismatch. Studies on small acute infarcts, detected on diffusion-weighted imaging (DWI), suggest that infarcts are largest in their acute phase and reduce in size thereafter. Therefore, we hypothesized that a subset of the CMI that are invisible on MRI can be detected on MRI in their acute phase. However, to our knowledge, a serial imaging study investigating the temporal dynamics of acute CMI (A-CMI) is lacking.

Objective

To determine the prevalence of chronic CMI (C-CMI) and the cumulative incidence and temporal dynamics of A-CMI in individuals with cerebral small vessel disease (SVD).

Design, Setting, Participants and Exposures

The RUN DMC-Intense study is a single-center hospital-based prospective cohort study on SVD performed between March 2016 and November 2017 and comprising 10 monthly 3-T MRI scans, including high-resolution DWI, 3-dimensional T1, 3-dimensional fluid-attenuated inversion recovery, and T2. One hundred six individuals from the previous longitudinal RUN DMC study were recruited based on the presence of progression of white matter hyperintensities on MRI between 2006 and 2015 and exclusion of causes of cerebral ischemia other than SVD. Fifty-four individuals (50.9%) participated. The median total follow-up duration was 39.5 weeks (interquartile range, 37.8-40.3). Statistical data analysis was performed between May and October 2019.

Main Outcomes and Measures

We determined the prevalence of C-CMI using the baseline T1, fluid-attenuated inversion recovery, and T2 scans. Monthly high-resolution DWI scans (n = 472) were screened to determine the cumulative incidence of A-CMI. The temporal dynamics of A-CMI were determined based on the MRI scans collected during the first follow-up visit after A-CMI onset and the last available follow-up visit.

Results

The median age of the cohort at baseline MRI was 69 years (interquartile range, 66-74 years) and 34 participants (63%) were men. The prevalence of C-CMI was 35% (95% CI, 0.24-0.49). Monthly DWI detected 21 A-CMI in 7 of 54 participants, resulting in a cumulative incidence of 13% (95% CI, 0.06-0.24). All A-CMI disappeared on follow-up MRI.

Conclusions and Relevance

Acute CMI never evolved into chronically MRI-detectable lesions. We suggest that these A-CMI underlie part of the submillimeter C-CMI encountered on neuropathological examination and thereby provide a source for the high CMI burden on neuropathology.

Estimation of laminar BOLD activation profiles using deconvolution with a physiological point spread function

BACKGROUND

The specificity of gradient echo (GE)-BOLD laminar fMRI activation profiles is degraded by intracortical veins that drain blood from lower to upper cortical layers, propagating activation signal in the same direction. This work describes an approach to obtain layer specific profiles by deconvolving the measured profiles with a physiological Point Spread Function (PSF).

NEW METHOD

It is shown that the PSF can be characterised by a TE-dependent peak to tail (p2t) value that is independent of cortical depth and can be estimated by simulation. An experimental estimation of individual p2t values and the sensitivity of the deconvolved profiles to variations in p2t is obtained using laminar data measured with a multi-echo 3D-FLASH sequence. These profiles are echo time dependent, but the underlying neuronal response is the same, allowing a data-based estimation of the PSF.

RESULTS

The deconvolved profiles are highly similar to the gold-standard obtained from extremely high resolution 3D-EPI data, for a range of p2t values of 5-9, which covers both the empirically determined value (6.8) and the value obtained by simulation (6.3). -Comparison with Existing Method(s) Corrected profiles show a flatter shape across the cortex and a high level of similarity with the gold-standard, defined as a subset of profiles that are unaffected by intracortical veins.

CONCLUSIONS

We conclude that deconvolution is a robust approach for removing the effect of signal propagation through intracortical veins. This makes it possible to obtain profiles with high laminar specificity while benefitting from the higher efficiency of GE-BOLD sequences.

An in-vivo study of BOLD laminar responses as a function of echo time and static magnetic field strength

Layer specific functional MRI requires high spatial resolution data. To compensate the associated poor signal to noise ratio it is common to integrate the signal from voxels at a given cortical depth. If the region is sufficiently large then physiological noise will be the dominant noise source. In this work, activation profiles in response to the same visual stimulus are compared at 1.5 T, 3 T and 7 T using a multi-echo, gradient echo (GE) FLASH sequence, with a 0.75 mm isotropic voxel size and the cortical integration approach. The results show that after integrating over a cortical volume of 40, 60 and 100 mm³ (at 7 T, 3 T, and 1.5 T, respectively), the signal is in the physiological noise dominated regime. The activation profiles obtained are similar for equivalent echo times. BOLD-like noise is found to be the dominant source of physiological noise. Consequently, the functional contrast to noise ratio is not strongly echo-time or field-strength dependent. We conclude that laminar GE-BOLD fMRI at lower field strengths is feasible but that larger patches of cortex will need to be examined, and that the acquisition efficiency is reduced.

Multi-shell Diffusion MRI Models for White Matter Characterization in Cerebral Small Vessel Disease

OBJECTIVE

To test the hypothesis that multi-shell diffusion models improve the characterization of microstructural alterations in cerebral small vessel disease (SVD), we assessed associations with processing speed performance, longitudinal change, and reproducibility of diffusion metrics.

METHODS

We included 50 patients with sporadic and 59 patients with genetically defined SVD (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy [CADASIL]) with cognitive testing and standardized 3T MRI, including multi-shell diffusion imaging. We applied the simple diffusion tensor imaging (DTI) model and 2 advanced models: diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI). Linear regression and multivariable random forest regression (including conventional SVD markers) were used to determine associations between diffusion metrics and processing speed performance. The detection of short-term disease progression was assessed by linear mixed models in 49 patients with sporadic SVD with longitudinal high-frequency imaging (in total 459 MRIs). Intersite reproducibility was determined in 10 patients with CADASIL scanned back-to-back on 2 different 3T MRI scanners.

RESULTS

Metrics from DKI showed the strongest associations with processing speed performance (R ² up to 21%) and the largest added benefit on top of conventional SVD imaging markers in patients with sporadic SVD and patients with CADASIL with lower SVD burden. Several metrics from DTI and DKI performed similarly in detecting disease progression. Reproducibility was excellent (intraclass correlation coefficient >0.93) for DTI and DKI metrics. NODDI metrics were less reproducible.

CONCLUSION

Multi-shell diffusion imaging and DKI improve the detection and characterization of cognitively relevant microstructural white matter alterations in SVD. Excellent reproducibility of diffusion metrics endorses their use as SVD markers in research and clinical care. Our publicly available intersite dataset facilitates future studies.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that in patients with SVD, diffusion MRI metrics are associated with processing speed performance.

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

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.

Structural network efficiency predicts cognitive decline in cerebral small vessel disease

Cerebral small vessel disease (SVD) is a common disease in older adults and a major contributor to vascular cognitive impairment and dementia. White matter network damage is a potentially important mechanism by which SVD causes cognitive impairment. Earlier studies showed that a higher degree of white matter network damage, indicated by lower global efficiency (a graph-theory measure assessing efficiency of network information transfer), was associated with lower scores on cognitive performance independent of MRI markers for SVD. However, it is unknown whether this global efficiency index is the strongest predictor for cognitive impairment, as there is a wide range of network measures. Here, we investigate which network measure is the most informative in explaining baseline cognitive performance and decline over a period of 8.7 years in SVD. We used data from the Radboud University Nijmegen Diffusion tensor and MRI Cohort (RUN DMC), which included 436 participants without dementia (65.2 ± 8.8 years) but with evidence of SVD on neuroimaging. Binarized and weighted structural brain networks were reconstructed using diffusion tensor imaging and deterministic streamlining. Using graph-theory, we calculated 21 global network measures and performed linear regression analyses, elastic net analysis and linear mixed effect models to compare these measures. All analyses were adjusted for potential confounders (age, sex, educational level, depressive symptoms and conventional SVD MRI-markers (e.g. white matter hyperintensities (WMH), lacunes of presumed vascular origin and microbleeds). The elastic net analyses showed that, at baseline, global efficiency had the strongest association with cognitive index (CI), while characteristic path length showed the strongest association with psychomotor speed (PMS) and memory. Binary local efficiency showed the strongest association with attention & executive function (A&EF). In addition, linear mixed-effect models demonstrated that baseline global efficiency predicts decline in CI (χ2(1) = 8.18, p = 0.004),PMS (χ2(1) = 7.75, p = 0.005), memory (χ2(1) = 27.28, p = 0.000) over time and that binary local efficiency predicts decline in A&EF (χ2(1) = 8.66, p = 0.003) over time. Our results suggest that among all network measures, network efficiency measures, i.e. global efficiency and local efficiency, are the strongest predictors for cognitive functions at cross-sectional level and also predict faster cognitive decline in SVD, which is in line with earlier findings. These findings suggests that in our study sample network efficiency measures are the most suitable surrogate markers for cognitive performance in patients with cerebral SVD among all network measures and MRI markers, and play a key role in the genesis of cognitive decline in SVD.

A half-century of innovation in technology-preparing MRI for the 21st century

MRI developed during the last half-century from a very basic concept to an indispensable non-ionising medical imaging technique that has found broad application in diagnostics, therapy control and far beyond. Due to its excellent soft-tissue contrast and the huge variety of accessible tissue- and physiological-parameters, MRI is often preferred to other existing modalities. In the course of its development, MRI underwent many substantial transformations. From the beginning, starting as a proof of concept, much effort was expended to develop the appropriate basic scanning technology and methodology, and to establish the many clinical contrasts (e.g., T₁, T₂, flow, diffusion, water/fat, etc.) that MRI is famous for today. Beyond that, additional prominent innovations to the field have been parallel imaging and compressed sensing, leading to significant scanning time reductions, and the move towards higher static magnetic field strengths, which led to increased sensitivity and improved image quality. Improvements in workflow and the use of artificial intelligence are among many current trends seen in this field, paving the way for a broad use of MRI. The 125th anniversary of the BJR is a good point to reflect on all these changes and developments and to offer some slightly speculative ideas as to what the future may bring.

Functional connectivity of the Precuneus reflects effectiveness of visual restitution training in chronic hemianopia

Visual field defects in chronic hemianopia can improve through visual restitution training, yet not all patients benefit equally from this long and exhaustive procedure. Here, we asked if resting-state functional connectivity prior to visual restitution could predict training success. In two training sessions of eight weeks each, 20 patients with chronic hemianopia performed a visual discrimination task by directing spatial selective attention towards stimuli presented in either hemifield, while suppressing eye movements. We examined two effects: a sensitivity change in the attended (trained) minus the unattended (control) hemifield (i.e., a training-specific improvement), and an overall improvement (i.e., a total change in sensitivity after both sessions). We then identified five visual resting-state networks and evaluated their functional connectivity in relation to both training effects. We found that the functional connectivity strength between the anterior Precuneus and the Occipital Pole Network was positively related to the attention modulated (i.e., training-specific) improvement. No such relationship was found for the overall improvement or for the other visual networks of interest. Our finding suggests that the anterior Precuneus plays a role in attention-modulated visual field improvements. The resting-state functional connectivity between the anterior Precuneus and the Occipital Pole Network may thus serve as an imaging-based biomarker that quantifies a patient's potential capacity to direct spatial attention. This may help to identify hemianopia patients that are most likely to benefit from visual restitution training.

Adapted cabling of an EEG cap improves simultaneous measurement of EEG and fMRI at 7T

BACKGROUND

The combination of EEG and ultra-high-field (7 T and above) fMRI holds the promise to relate electrophysiology and hemodynamics with greater signal to noise level and at higher spatial resolutions than conventional field strengths. Technical and safety restrictions have so far resulted in compromises in terms of MRI coil selection, resulting in reduced, signal quality, spatial coverage and resolution in EEG-fMRI studies at 7 T.

NEW METHOD

We adapted a 64-channel MRI-compatible EEG cap so that it could be used with a closed 32-channel MRI head coil thus avoiding several of these compromises. We compare functional and anatomical as well as the EEG quality recorded with this adapted setup with those recorded with a setup that uses an open-ended 8-channel head-coil.

RESULTS

Our set-up with the adapted EEG cap inside the closed 32 channel coil resulted in the recording of good quality EEG and (f)MRI data. Both functional and anatomical MRI images show no major effects of the adapted EEG cap on MR signal quality. We demonstrate the ability to compute ERPs and changes in alpha and gamma oscillations from the recorded EEG data.

COMPARISON WITH EXISTING METHODS

Compared to MRI recordings with an 8-channel open-ended head-coil, the loss in signal quality of the MRI images related to the adapted EEG cap is considerably reduced.

CONCLUSIONS

The adaptation of the EEG cap permits the simultaneous recording of good quality whole brain (f)MRI data using a 32 channel receiver coil, while maintaining the quality of the EEG data.

A comparison of sLASER and MEGA-sLASER using simultaneous interleaved acquisition for measuring GABA in the human brain at 7T

γ-Aminobutyric acid (GABA), the major inhibitory neurotransmitter, is challenging to measure using proton spectroscopy due to its relatively low concentration, J-coupling and overlapping signals from other metabolites. Currently, the prevalent methods for detecting GABA at ultrahigh field strengths (≥ 7 T) are GABA-editing and model fitting of non-editing single voxel spectra. These two acquisition approaches have their own advantages: the GABA editing approach directly measures the GABA resonance at 3 ppm, whereas the fitting approach on the non-editing spectrum allows the detection of multiple metabolites, and has an SNR advantage over longer echo time (TE) acquisitions. This study aims to compare these approaches for estimating GABA at 7 T. We use an interleaved sequence of semi-LASER (sLASER: TE = 38 ms) and MEGA-sLASER (TE = 80 ms). This simultaneous interleaved acquisition minimizes the differential effect of extraneous factors, and enables an accurate comparison of the two acquisition methods. Spectra were acquired with an 8 ml isotropic voxel at six different brain regions: anterior-cingulate cortex, dorsolateral-prefrontal cortex, motor cortex, occipital cortex, posterior cingulate cortex, and precuneus. Spectral fitting with LCModel quantified the GABA to total Cr (tCr: Creatine + Phosphocreatine) concentration ratio. After correcting the T2 relaxation time variation, GABA/tCr ratios were similar between the two acquisition approaches. GABA editing showed smaller spectral fitting error according to Cramér-Rao lower bound than the sLASER approach for all regions examined. We conclude that both acquisition methods show similar accuracy but the precision of the MEGA-editing approach is higher for GABA measurement. In addition, the 2.28 ppm GABA resonance was found to be important for estimating GABA concentration without macromolecule contamination in the GABA-edited acquisition, when utilizing spectral fitting with LCModel.

Risk of Nursing Home Admission in Cerebral Small Vessel Disease

Background and Purpose- Since cerebral small vessel disease (SVD) is associated with cognitive and motor impairment and both might ultimately lead to nursing home admission, our objective was to investigate the association of SVD markers with nursing home admission. Methods- The RUN DMC study (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort) is a prospective cohort of 503 independent living individuals with SVD. Date of nursing home admission was retrieved from the Dutch municipal personal records database. Risk of nursing home admission was calculated using a competing risk analysis, with mortality as a competing risk. Results- During follow-up (median 8.7 years, interquartile range 8.5-8.9), 31 participants moved to a nursing home. Before nursing home admission, 19 participants were diagnosed with dementia, 6 with parkinsonism, and 10 with stroke. Participants with the lowest white matter volume had an 8-year risk of nursing home admission of 13.3% (95% CI, 8.6-18.9), which was significantly different from participants with middle or highest white matter volume (respectively, 4.8% [95% CI, 2.3-8.8] and 0%; P<0.001). After adjusting for baseline age and living condition, the association of white matter volume and total brain volume with nursing home admission was significant, with, respectively, hazard ratios of 0.88 [95% CI, 0.84-0.95] ( P value 0.025) and 0.92 [95% CI, 0.85-0.98] ( P<0.001) per 10 mL. The association of white matter hyperintensities and lacunes with nursing home admission was not significant. Conclusions- This study demonstrates that in SVD patients, independent from age and living condition, a lower white matter volume and a lower total brain volume is associated with an increased risk of nursing home admission. Nursing home admission is a relevant outcome in SVD research since it might be able to combine both cognitive and functional consequences of SVD in 1 outcome.

The role of small diffusion-weighted imaging lesions in cerebral small vessel disease

OBJECTIVE

To investigate the prevalence of asymptomatic diffusion-weighted imaging-positive (DWI+) lesions in individuals with cerebral small vessel disease (SVD) and identify their role in the origin of SVD markers on MRI.

METHODS

We included 503 individuals with SVD from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort (RUN DMC) study (mean age 65.6 years [SD 8.8], 56.5% male) with 1.5T MRI in 2006 and, if available, follow-up MRI in 2011 and 2015. We screened DWI scans (n = 1,152) for DWI+ lesions, assessed lesion evolution on follow-up fluid-attenuated inversion recovery, T1 and T2* images, and examined the association between DWI+ lesions and annual SVD progression (white matter hyperintensities [WMH], lacunes, microbleeds).

RESULTS

We found 50 DWI+ lesions in 39 individuals on 1,152 DWI (3.4%). Individuals with DWI+ lesions were older (p = 0.025), more frequently had a history of hypertension (p = 0.021), and had a larger burden of preexisting SVD MRI markers (WMH, lacunes, microbleeds: all p < 0.001) compared to individuals without DWI+ lesions. Of the 23 DWI+ lesions with available follow-up MRI, 14 (61%) evolved into a WMH, 8 (35%) resulted in a cavity, and 1 (4%) was no longer visible. Presence of DWI+ lesions was significantly associated with annual WMH volume increase and yearly incidence of lacunes and microbleeds (all p < 0.001).

CONCLUSION

Over 3% of individuals with SVD have DWI+ lesions. Although DWI+ lesions play a role in the progression of SVD, they may not fully explain progression of SVD markers on MRI, suggesting that other factors than acute ischemia are at play.

Contribution of acute infarcts to cerebral small vessel disease progression

Objective

To determine the contribution of acute infarcts, evidenced by diffusion‐weighted imaging positive (DWI+) lesions, to progression of white matter hyperintensities (WMH) and other cerebral small vessel disease (SVD) markers.

Methods

We performed monthly 3T magnetic resonance imaging (MRI) for 10 consecutive months in 54 elderly individuals with SVD. MRI included high‐resolution multishell DWI, and 3‐dimensional fluid‐attenuated inversion recovery, T1, and susceptibility‐weighted imaging. We determined DWI+ lesion evolution, WMH progression rate (ml/mo), and number of incident lacunes and microbleeds, and calculated for each marker the proportion of progression explained by DWI+ lesions.

Results

We identified 39 DWI+ lesions on 21 of 472 DWI scans in 9 of 54 subjects. Of the 36 DWI+ lesions with follow‐up MRI, 2 evolved into WMH, 4 evolved into a lacune (3 with cavity <3mm), 3 evolved into a microbleed, and 27 were not detectable on follow‐up. WMH volume increased at a median rate of 0.027 ml/mo (interquartile range = 0.005–0.073), but was not significantly higher in subjects with DWI+ lesions compared to those without (p = 0.195). Of the 2 DWI+ lesions evolving into WMH on follow‐up, one explained 23% of the total WMH volume increase in one subject, whereas the WMH regressed in the other subject. DWI+ lesions preceded 4 of 5 incident lacunes and 3 of 10 incident microbleeds.

Interpretation

DWI+ lesions explain only a small proportion of the total WMH progression. Hence, WMH progression seems to be mostly driven by factors other than acute infarcts. DWI+ lesions explain the majority of incident lacunes and small cavities, and almost one‐third of incident microbleeds, confirming that WMH, lacunes, and microbleeds, although heterogeneous on MRI, can have a common initial appearance on MRI. ANN NEUROL 2019;86:582–592

A comparison of in vivo MRI based cortical myelin mapping using T1w/T2w and R1 mapping at 3T

In this manuscript, we compare two commonly used methods to perform cortical mapping based on myelination of the human neocortex. T1w/T2w and R1 maps with matched total acquisition times were obtained from a young cohort in randomized order and using a test–retest design. Both methodologies showed cortical myelin maps that enhanced similar anatomical features, namely primary sensory regions known to be myelin rich. T1w/T2w maps showed increased robustness to movement artifacts in comparison to R1 maps, while the test re-test reproducibility of both methods was comparable. Based on Brodmann parcellation, both methods showed comparable variability within each region. Having parcellated cortical myelin maps into VDG11b areas of 4a, 4p, 3a, 3b, 1, 2, V2, and MT, both methods behave identically with R1 showing an increased variability between subjects. In combination with the test re-test evaluation, we concluded that this increased variability between subjects reflects relevant tissue variability. A high level of correlation was found between the R1 and T1w/T2w regions with regions of higher deviations being co-localized with those where the transmit RF field deviated most from its nominal value. We conclude that R1 mapping strategies might be preferable when studying different population cohorts where cortical properties are expected to be altered while T1w/T2w mapping will have advantages when performing cortical based segmentation.

Higher GABA concentration in the medial prefrontal cortex of Type 2 diabetes patients is associated with episodic memory dysfunction

Type 2 diabetes (T2D) is associated with an accelerated episodic memory decline, but the underlying pathophysiological mechanisms are not well understood. Hallmarks of T2D comprise impairment of insulin secretion and insulin sensitivity. Insulin signaling modulates cerebral neurotransmitter activity, including the excitatory glutamate and inhibitory gamma-aminobutyric acid (GABA) systems. Here we tested the hypothesis that the glutamate and GABA systems are altered in T2D patients and this relates to memory decline and insulin resistance. Using ¹ H-magnetic resonance spectroscopy (MRS), we examined glutamate and GABA concentrations in episodic memory relevant brain regions (medial prefrontal cortex and precuneus) of T2D patients and matched controls. Insulin sensitivity was measured by hyperinsulinemic-euglycemic clamps and memory performance was assessed using a face-profession associations test. T2D patients exhibited peripheral insulin resistance and had a decreased memory for face-profession associations as well as elevated GABA concentration in the medial prefrontal cortex but not precuneus. In addition, medial prefrontal cortex GABA concentration was negatively associated with memory performance suggesting that abnormal GABA levels in the medial prefrontal cortex are linked to the episodic memory decline that occurs in T2D patients.

Effect of linewidth on estimation of metabolic concentration when using water lineshape spectral model fitting for single voxel proton spectroscopy at 7 T

Good B₀ field homogeneity is considered an essential requirement to obtain high-quality MRS data. Many commonly used spectral fitting methods assume that all metabolite signals have Lorentzian or Gaussian shapes. However, B₀ inhomogeneity can both broaden the linewidth and modify the lineshape. In this study, it is hypothesized that a realistic metabolite fitting model, which accounts for B₀ homogeneity on the basis of the water lineshape, will improve the accuracy of estimation of metabolite concentrations. In-vivo water suppressed/unsuppressed single voxel spectroscopy signals were acquired under three different B₀ field homogeneity regimes. Individual realistic basis sets were created for each acquisition. Frequency-domain spectral fitting with LCModel was used to quantify the metabolite concentrations with fitting uncertainties given in terms of the Cramer-Rao lower bound. The quantification results obtained using the water lineshape basis set yielded similar concentrations independent of linewidth and showed a larger fitting error as the linewidth increased. The conventional approach, however quantifies metabolite concentrations with greater variations despite showing a supposedly improved fitting quality. The water lineshape basis set achieved single voxel spectroscopy accuracy that is less sensitive to the linewidth compared to the conventional spectral fitting method for the range of linewidths used in this study, but the precision deteriorated with worsening B₀ field inhomogeneity. The beneficial effect was ascribed to a reduction in the number of degrees of freedom when using the water lineshape to generate the basis set.

Dissociable laminar profiles of concurrent bottom-up and top-down modulation in the human visual cortex

Recent developments in human neuroimaging make it possible to non-invasively measure neural activity from different cortical layers. This can potentially reveal not only which brain areas are engaged by a task, but also how. Specifically, bottom-up and top-down responses are associated with distinct laminar profiles. Here, we measured lamina-resolved fMRI responses during a visual task designed to induce concurrent bottom-up and top-down modulations via orthogonal manipulations of stimulus contrast and feature-based attention. BOLD responses were modulated by both stimulus contrast (bottom-up) and by engaging feature-based attention (top-down). Crucially, these effects operated at different cortical depths: Bottom-up modulations were strongest in the middle cortical layer and weaker in deep and superficial layers, while top-down modulations were strongest in the superficial layers. As such, we demonstrate that laminar activity profiles can discriminate between concurrent top-down and bottom-up processing, and are diagnostic of how a brain region is activated.

Laminar signal extraction over extended cortical areas by means of a spatial GLM

There is converging evidence that distinct neuronal processes leave distinguishable footprints in the laminar BOLD response. However, even though the achievable spatial resolution in functional MRI has much improved over the years, it is still challenging to separate signals arising from different cortical layers. In this work, we propose a new method to extract laminar signals. We use a spatial General Linear Model in combination with the equivolume principle of cortical layers to unmix laminar signals instead of interpolating through and integrating over a cortical area: thus reducing partial volume effects. Not only do we provide a mathematical framework for extracting laminar signals with a spatial GLM, we also illustrate that the best case scenarios of existing methods can be seen as special cases within the same framework. By means of simulation, we show that this approach has a sharper point spread function, providing better signal localisation. We further assess the partial volume contamination in cortical profiles from high resolution human ex vivo and in vivo structural data, and provide a full account of the benefits and potential caveats. We eschew here any attempt to validate the spatial GLM on the basis of fMRI data as a generally accepted ground-truth pattern of laminar activation does not currently exist. This approach is flexible in terms of the number of layers and their respective thickness, and naturally integrates spatial regularisation along the cortex, while preserving laminar specificity. Care must be taken, however, as this procedure of unmixing is susceptible to sources of noise in the data or inaccuracies in the laminar segmentation.

Cognitive consequences of regression of cerebral small vessel disease

Introduction

Recent studies have shown that neuroimaging markers of cerebral small vessel disease can also regress over time. We investigated the cognitive consequences of regression of small vessel disease markers.

Patients and methods

Two hundred and seventy-six participants of the RUNDMC study underwent neuroimaging and cognitive assessments at three time-points over 8.7 years. We semi-automatically assessed white matter hyperintensities volumes and manually rated lacunes and microbleeds. We analysed differences in cognitive decline and accompanying brain atrophy between participants with regression, progression and stable small vessel disease by analysis of variance.

Results

Fifty-six participants (20.3%) showed regression of small vessel disease markers: 31 (11.2%) white matter hyperintensities regression, 10 (3.6%) vanishing lacunes and 27 (9.8%) vanishing microbleeds. Participants with regression showed a decline in overall cognition, memory, psychomotor speed and executive function similar to stable small vessel disease. Participants with small vessel disease progression showed more cognitive decline compared with stable small vessel disease (p < 0.001 for cognitive index and memory; p < 0.01 for executive function), although significance disappeared after adjusting for age and sex. Loss of total brain, gray matter and white matter volume did not differ between participants with small vessel disease regression and stable small vessel disease, while participants with small vessel disease progression showed more volume loss of total brain and gray matter compared to those with stable small vessel disease (p < 0.05), although significance disappeared after adjustments.

Discussion

Regression of small vessel disease markers was associated with similar cognitive decline compared to stable small vessel disease and did not accompany brain atrophy, suggesting that small vessel disease regression follows a relatively benign clinical course. Future studies are required to validate these findings and to assess the role of vascular risk factor control on small vessel disease regression and possible recovery of clinical symptoms.

Conclusion

Our findings of comparable cognitive decline between participants with regression and stable small vessel disease might suggest that small vessel disease regression has a relative benign cognitive outcome.

Implications of the magnetic susceptibility difference between grey and white matter for single-voxel proton spectroscopy at 7 T

Magnetic susceptibility differences between grey matter (GM) and white matter (WM) can potentially affect lineshapes and chemical shifts in single-voxel spectroscopy. This study aimed to investigate the consequences and potential utility of these effects. Spectroscopy voxels were segmented into GM, WM, and cerebrospinal fluid based on T₁-weighted images. GM and WM lineshapes were computed using multi-echo gradient-echo images to measure the frequency distribution. Twenty 7 Tesla single voxel spectra with corresponding T₁-weighted images were acquired from the frontal and parietal lobes from five healthy human volunteers. Consistent frequency shifts (mean [±SD] 4.9 ± 2.0 Hz) and linewidth differences (2.4 ± 1.5 Hz) between the two tissue types were observed. Directly visible metabolites (creatine, choline, and myo-inositol) exhibited frequency shifts and linewidth differences that were consistent with a linear-weighted summation of their expected GM and WM distribution ratios. The magnetic susceptibility difference between GM and WM had a detectable effect on single-voxel proton spectra, which results in both frequency shifts and lineshape broadening. This effect can be used to estimate the relative metabolic distribution in the GM and WM for directly observable metabolites. Fractional distributions estimated with this method demonstrated good agreement with literature values for the selected metabolites.

Pros and cons of ultra-high-field MRI/MRS for human application

Magnetic resonance imaging and spectroscopic techniques are widely used in humans both for clinical diagnostic applications and in basic research areas such as cognitive neuroimaging. In recent years, new human MR systems have become available operating at static magnetic fields of 7 T or higher (≥300 MHz proton frequency). Imaging human-sized objects at such high frequencies presents several challenges including non-uniform radiofrequency fields, enhanced susceptibility artifacts, and higher radiofrequency energy deposition in the tissue. On the other side of the scale are gains in signal-to-noise or contrast-to-noise ratio that allow finer structures to be visualized and smaller physiological effects to be detected. This review presents an overview of some of the latest methodological developments in human ultra-high field MRI/MRS as well as associated clinical and scientific applications. Emphasis is given to techniques that particularly benefit from the changing physical characteristics at high magnetic fields, including susceptibility-weighted imaging and phase-contrast techniques, imaging with X-nuclei, MR spectroscopy, CEST imaging, as well as functional MRI. In addition, more general methodological developments such as parallel transmission and motion correction will be discussed that are required to leverage the full potential of higher magnetic fields, and an overview of relevant physiological considerations of human high magnetic field exposure is provided.

Memory decline in elderly with cerebral small vessel disease explained by temporal interactions between white matter hyperintensities and hippocampal atrophy

White matter hyperintensities (WMH) constitute the visible spectrum of cerebral small vessel disease (SVD) markers and are associated with cognitive decline, although they do not fully account for memory decline observed in individuals with SVD. We hypothesize that WMH might exert their effect on memory decline indirectly by affecting remote brain structures such as the hippocampus. We investigated the temporal interactions between WMH, hippocampal atrophy and memory decline in older adults with SVD. Five hundred and three participants of the RUNDMC study underwent neuroimaging and cognitive assessments up to 3 times over 8.7 years. We assessed WMH volumes semi-automatically and calculated hippocampal volumes (HV) using FreeSurfer. We used linear mixed effects models and causal mediation analyses to assess both interaction and mediation effects of hippocampal atrophy in the associations between WMH and memory decline, separately for working memory (WM) and episodic memory (EM). Linear mixed effect models revealed that the interaction between WMH and hippocampal volumes explained memory decline (WM: β = .067; 95%CI[.024-0.111]; p < .01; EM: β = .061; 95%CI[.025-.098]; p < .01), with better model fit when the WMH*HV interaction term was added to the model, for both WM (likelihood ratio test, χ² [1] = 9.3, p < .01) and for EM (likelihood ratio test, χ² [1] = 10.7, p < .01). Mediation models showed that both baseline WMH volume (β = -.170; p = .001) and hippocampal atrophy (β = 0.126; p = .009) were independently related to EM decline, but the effect of baseline WMH on EM decline was not mediated by hippocampal atrophy (p value indirect effect: 0.572). Memory decline in elderly with SVD was best explained by the interaction of WMH and hippocampal volumes. The relationship between WMH and memory was not causally mediated by hippocampal atrophy, suggesting that memory decline during aging is a heterogeneous condition in which different pathologies contribute to the memory decline observed in elderly with SVD.

Laminar Organization of Working Memory Signals in Human Visual Cortex

The human primary visual cortex (V1) is not only activated by incoming visual information but is also engaged by top-down cognitive processes, such as visual working memory, even in the absence of visual input [1-3]. This feedback may be critical to our ability to visualize specific visual features, as higher-order regions lack the selectivity to represent such information [4]. Clearly, such internally generated signals do not trigger genuine perception of the remembered stimulus, meaning they must be organized in a manner that is different to bottom-up-driven signals. Internally generated signals may be kept separate from incoming sensory data by virtue of the laminar organization of inter-area cortical connections. Namely, bottom-up driving connections target layer 4, located in the middle of the cortical column, and feedback connections target deep and superficial layers and avoid layer 4 [5-7]. Using lamina-resolved fMRI, we simultaneously measured the activity in three early visual cortical areas (V1-V3) that are recruited to represent stimulus information during visual working memory [8]. We observed item-specific working memory signals in early visual cortex. In V1, this item-specific activity was selectively present at deep and superficial cortical depths, avoiding the middle layers, and working-memory-related activity was present at all depths in V2 and V3. These results show for the first time the laminar organization of internally generated signals during visual working memory in the human visual system and provide new insights into how bottom-up and top-down signals in visual cortex are deployed.