Does Loss of Integrity of the Cingulum Bundle Link Amyloid-ß Accumulation and Neurodegeneration in Alzheimer's Disease?

BACKGROUND: Alzheimer's disease is characterized by the accumulation of amyloid-ß (Aß) into plaques, aggregation of tau into neurofibrillary tangles, and neurodegenerative processes including atrophy. However, there is a poorly understood spatial discordance between initial Aß deposition and local neurodegeneration. OBJECTIVE: Here, we test the hypothesis that the cingulum bundle links Aß deposition in the cingulate cortex to medial temporal lobe (MTL) atrophy. METHODS: 21 participants with mild cognitive impairment (MCI) from the UMC Utrecht memory clinic (UMCU, discovery sample) and 37 participants with MCI from Alzheimer's Disease Neuroimaging Initiative (ADNI, replication sample) with available Aß-PET scan, T1-weighted and diffusion-weighted MRI were included. Aß load of the cingulate cortex was measured by the standardized uptake value ratio (SUVR), white matter integrity of the cingulum bundle was assessed by mean diffusivity and atrophy of the MTL by normalized MTL volume. Relationships were tested with linear mixed models, to accommodate multiple measures for each participant. RESULTS: We found at most a weak association between cingulate Aß and MTL volume (added R2 <0.06), primarily for the posterior hippocampus. In neither sample, white matter integrity of the cingulum bundle was associated with cingulate Aß or MTL volume (added R2 <0.01). Various sensitivity analyses (Aß-positive individuals only, posterior cingulate SUVR, MTL sub region volume) provided similar results. CONCLUSION: These findings, consistent in two independent cohorts, do not support our hypothesis that loss of white matter integrity of the cingulum is a connecting factor between cingulate gyrus Aß deposition and MTL atrophy.

Corpus callosum lesions are associated with worse cognitive performance in cerebral amyloid angiopathy.

The impact of vascular lesions on cognition is location dependent. Here, we assessed the contribution of small vessel disease lesions in the corpus callosum to vascular cognitive impairment in cerebral amyloid angiopathy, as a model for cerebral small vessel disease. Sixty-five patients with probable cerebral amyloid angiopathy underwent 3T magnetic resonance imaging, including a diffusion tensor imaging scan, and neuropsychological testing. Microstructural white-matter integrity was quantified by fractional anisotropy and mean diffusivity. Z-scores on individual neuropsychological tests were averaged into five cognitive domains: information processing speed, executive functioning, memory, language and visuospatial ability. Corpus callosum lesions were defined as haemorrhagic (microbleeds or larger bleeds) or ischaemic (microinfarcts, larger infarcts and diffuse fluid-attenuated inversion recovery hyperintensities). Associations between corpus callosum lesion presence, microstructural white-matter integrity and cognitive performance were examined with multiple regression models. The prevalence of corpus callosum lesions was confirmed in an independent cohort of memory clinic patients with and without cerebral amyloid angiopathy (n = 82). In parallel, we assessed corpus callosum lesions on ex vivo magnetic resonance imaging in cerebral amyloid angiopathy patients (n = 19) and controls (n = 5) and determined associated tissue abnormalities with histopathology. A total number of 21 corpus callosum lesions was found in 19/65 (29%) cerebral amyloid angiopathy patients. Corpus callosum lesion presence was associated with reduced microstructural white-matter integrity within the corpus callosum and in the whole-brain white matter. Patients with corpus callosum lesions performed significantly worse on all cognitive domains except language, compared with those without corpus callosum lesions after correcting for age, sex, education and time between magnetic resonance imaging and neuropsychological assessment. This association was independent of the presence of intracerebral haemorrhage, whole-brain fractional anisotropy and mean diffusivity, and white-matter hyperintensity volume and brain volume for the domains of information processing speed and executive functioning. In the memory clinic patient cohort, corpus callosum lesions were present in 14/54 (26%) patients with probable and 2/8 (25%) patients with possible cerebral amyloid angiopathy, and in 3/20 (15%) patients without cerebral amyloid angiopathy. In the ex vivo cohort, corpus callosum lesions were present in 10/19 (53%) patients and 2/5 (40%) controls. On histopathology, ischaemic corpus callosum lesions were associated with tissue loss and demyelination, which extended beyond the lesion core. Together, these data suggest that corpus callosum lesions are a frequent finding in cerebral amyloid angiopathy, and that they independently contribute to cognitive impairment through strategic microstructural disruption of white-matter tracts.

Impact of thresholding on the consistency and sensitivity of diffusion MRI-based brain networks in patients with cerebral small vessel disease.

INTRODUCTION: Thresholding of low-weight connections of diffusion MRI-based brain networks has been proposed to remove false-positive connections. It has been previously established that this yields more reproducible scan-rescan network architecture in healthy subjects. In patients with brain disease, network measures are applied to assess inter-individual variation and changes over time. Our aim was to investigate whether thresholding also achieves improved consistency in network architecture in patients, while maintaining sensitivity to disease effects for these applications. METHODS: We applied fixed-density and absolute thresholding on brain networks in patients with cerebral small vessel disease (SVD, n = 86; ≈24 months follow-up), as a clinically relevant exemplar condition. In parallel, we applied the same methods in healthy young subjects (n = 44; scan-rescan interval ≈4 months) as a frame of reference. Consistency of network architecture was assessed with dice similarity of edges and intraclass correlation coefficient (ICC) of edge-weights and hub-scores. Sensitivity to disease effects in patients was assessed by evaluating interindividual variation, changes over time, and differences between those with high and low white matter hyperintensity burden, using correlation analyses and mixed ANOVA. RESULTS: Compared to unthresholded networks, both thresholding methods generated more consistent architecture over time in patients (unthresholded: dice = .70; ICC: .70-.78; thresholded: dice = .77; ICC: .73-.83). However, absolute thresholding created fragmented nodes. Similar observations were made in the reference group. Regarding sensitivity to disease effects in patients, fixed-density thresholds that were optimal in terms of consistency (densities: .10-.30) preserved interindividual variation in global efficiency and node strength as well as the sensitivity to detect effects of time and group. Absolute thresholding produced larger fluctuations of interindividual variation. CONCLUSIONS: Our results indicate that thresholding of low-weight connections, particularly when using fixed-density thresholding, results in more consistent network architecture in patients with longer rescan intervals, while preserving sensitivity to disease effects.

Prediction of Cognitive Recovery After Stroke: The Value of Diffusion-Weighted Imaging-Based Measures of Brain Connectivity.

BACKGROUND AND PURPOSE: Prediction of long-term recovery of a poststroke cognitive disorder (PSCD) is currently inaccurate. We assessed whether diffusion-weighted imaging (DWI)-based measures of brain connectivity predict cognitive recovery 1 year after stroke in patients with PSCD in addition to conventional clinical, neuropsychological, and imaging variables. METHODS: This prospective monocenter cohort study included 217 consecutive patients with a clinical diagnosis of ischemic stroke, aged ≥50 years, and Montreal Cognitive Assessment score below 26 during hospitalization. Five weeks after stroke, patients underwent DWI magnetic resonance imaging. Neuropsychological assessment was performed 5 weeks and 1 year after stroke and was used to classify PSCD as absent, modest, or marked. Cognitive recovery was operationalized as a shift to a better PSCD category over time. We evaluated 4 DWI-based measures of brain connectivity: global network efficiency and mean connectivity strength, both weighted for mean diffusivity and fractional anisotropy. Conventional predictors were age, sex, level of education, clinical stroke characteristics, neuropsychological variables, and magnetic resonance imaging findings (eg, infarct size). DWI-based measures of brain connectivity were added to a multivariable model to assess additive predictive value. RESULTS: Of 135 patients (mean age, 71 years; 95 men [70%]) with PSCD 5 weeks after ischemic stroke, 41 (30%) showed cognitive recovery. Three of 4 brain connectivity measures met the predefined threshold of P<0.1 in univariable regression analysis. There was no added value of these measures to a multivariable model that included level of education and infarct size as significant predictors of cognitive recovery. CONCLUSIONS: Current DWI-based measures of brain connectivity appear to predict recovery of PSCD but at present have no added value over conventional predictors.

White matter atrophy in cerebral amyloid angiopathy.

OBJECTIVE: We postulated that cerebral amyloid angiopathy (CAA) is associated with white matter atrophy (WMA) and that WMA can be related to cognitive changes in CAA. METHODS: White matter volume expressed as percent of intracranial volume (pWMV) of prospectively enrolled patients without dementia diagnosed with probable CAA was compared to age-matched healthy controls (HC) and patients with Alzheimer disease (AD). Cognitive scores were also sought to understand the potential effects of WMA on cognitive function. RESULTS: Patients with CAA (n = 72) had significantly lower pWMV (27.97% ± 2.63) when compared to age-matched HC (n = 72; mean difference [MD], 2.38%; p < 0.0001) and patients with AD (n = 72; MD, 1.57%; p < 0.0001). Differences were most pronounced in the posterior occipital regions in both comparisons. When comparisons were restricted to groups of patients with CAA but no intracerebral hemorrhage (n = 32) or hypertension (n = 32), and age-matched HC and AD, the significant differences were unaltered. Within the CAA cohort, higher age, lobar microbleed counts, and presence of hypertension were associated with lower pWMV (p = 0.0007, p = 0.031, and p = 0.003, respectively). All associations remained independent in multivariable analyses. Within the CAA cohort, higher pWMV independently correlated with better scores of executive function. CONCLUSIONS: Patients with CAA show WMA when compared to age-matched HC and patients with AD. WMA independently correlates with the number of lobar microbleeds, a marker of CAA severity. Consistent spatial patterns of WMA especially in posterior regions might be related to CAA. The association between WMA and measures of executive function suggests that WMA might represent an important mediator of CAA-related neurologic dysfunction.

Effect of Fixed-Density Thresholding on Structural Brain Networks: A Demonstration in Cerebral Small Vessel Disease.

A popular solution to control for edge density variability in structural brain network analysis is to threshold the networks to a fixed density across all subjects. However, it remains unclear how this type of thresholding affects the basic network architecture in terms of edge weights, hub location, and hub connectivity and, especially, how it affects the sensitivity to detect disease-related abnormalities. We investigated these two questions in a cohort of patients with cerebral small vessel disease and age-matched controls. Brain networks were reconstructed from diffusion magnetic resonance imaging data using deterministic fiber tractography. Networks were thresholded to a fixed density by removing edges with the lowest number of streamlines. We compared edge length (mm), fractional anisotropy (FA), proportion of hub connections, and hub location between the unthresholded and the thresholded networks of each subject. Moreover, we compared weighted graph measures of global and local connectivity obtained from the (un)thresholded networks between patients and controls. We performed these analyses over a range of densities (2-20%). Results indicate that fixed-density thresholding disproportionally removes edges composed of long streamlines, but is independent of FA. The edges removed were not preferentially connected to hub or nonhub nodes. Over half of the original hubs were reproducible when networks were thresholded to a density ≥10%. Furthermore, the between-group differences in graph measures observed in the unthresholded network remained present after thresholding, irrespective of the chosen density. We therefore conclude that moderate fixed-density thresholds can successfully be applied to control for the effects of density in structural brain network analysis.

Histopathology of diffusion-weighted imaging-positive lesions in cerebral amyloid angiopathy.

Small subclinical hyperintense lesions are frequently encountered on brain diffusion-weighted imaging (DWI) scans of patients with cerebral amyloid angiopathy (CAA). Interpretation of these DWI+ lesions, however, has been limited by absence of histopathological examination. We aimed to determine whether DWI+ lesions represent acute microinfarcts on histopathology in brains with advanced CAA, using a combined in vivo MRI-ex vivo MRI-histopathology approach. We first investigated the histopathology of a punctate cortical DWI+ lesion observed on clinical in vivo MRI 7 days prior to death in a CAA case. Subsequently, we assessed the use of ex vivo DWI to identify similar punctate cortical lesions post-mortem. Intact formalin-fixed hemispheres of 12 consecutive cases with CAA and three non-CAA controls were subjected to high-resolution 3 T ex vivo DWI and T2 imaging. Small cortical lesions were classified as either DWI+/T2+ or DWI-/T2+. A representative subset of lesions from three CAA cases was selected for detailed histopathological examination. The DWI+ lesion observed on in vivo MRI could be matched to an area with evidence of recent ischemia on histopathology. Ex vivo MRI of the intact hemispheres revealed a total of 130 DWI+/T2+ lesions in 10/12 CAA cases, but none in controls (p = 0.022). DWI+/T2+ lesions examined histopathologically proved to be acute microinfarcts (classification accuracy 100%), characterized by presence of eosinophilic neurons on hematoxylin and eosin and absence of reactive astrocytes on glial fibrillary acidic protein-stained sections. In conclusion, we suggest that small DWI+ lesions in CAA represent acute microinfarcts. Furthermore, our findings support the use of ex vivo DWI as a method to detect acute microinfarcts post-mortem, which may benefit future histopathological investigations on the etiology of microinfarcts.

Extent to Which Network Hubs Are Affected by Ischemic Stroke Predicts Cognitive Recovery.

Background and Purpose- It is uncertain what determines the potential for cognitive recovery after ischemic stroke. The extent to which strategic areas of the brain network, so-called hubs, are affected by the infarct could be a key factor. We developed a lesion impact score, which estimates the damage to network hubs by integrating information on infarct size with healthy brain network topology. We verified whether the lesion impact score indeed reflects global network disturbances in patients and assessed if it could predict cognitive recovery. Methods- Seventy-five ischemic stroke patients without signs of a prestroke cognitive disorder were included, all with evidence of a cognitive disorder during hospitalization. A brain magnetic resonance imaging and neuropsychological assessment were performed 5 weeks (±1 week) after stroke. Neuropsychological testing was repeated after 1 year to assess cognitive recovery. Brain networks were reconstructed from diffusion-weighted data and consisted of 90 gray matter regions (ie, network nodes). A standard brain network map, indicating the hub-score of each node, was obtained from network data of 44 cognitively healthy adults. For each patient, we calculated the lesion impact score by multiplying the percentage of node volume affected by the infarct with the node's corresponding hub-score. The patients' maximum lesion impact score was used as outcome predictor. Results- A higher lesion impact score in patients, indicating an increasing infarct size in nodes with a higher hub-score, was related to lower global brain network efficiency (ß=-0.528 [-0.776 to -0.277]; P<0.001), independent of age, brain volume, infarct volume, and white matter hyperintensity severity. A lower lesion impact score, however, was an independent predictor of cognitive recovery 1 year after stroke (odds ratio=0.434 [0.193-0.978]; P=0.044). Conclusions- We introduced a lesion impact score that combines information on infarct size and network topology to predict long-term recovery after stroke. This score can potentially be used in a clinical setting, also without availability of high-resolution diffusion-weighted magnetic resonance imaging.

The road ahead in clinical network neuroscience.

Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like "How do dynamic processes alter the underlying structural network?" and "Can we use network neuroscience for disease classification?" This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others.

Physical Performance in Memory Clinic Patients: The Potential Role of the White Matter Network.

BACKGROUND/OBJECTIVES: Memory clinic patients commonly also have declined physical performance. This may be attributable to white matter injury, due to vascular damage or neurodegeneration. Quantifying white matter injury is made possible by new magnetic resonance imaging (MRI) techniques, including diffusion-weighted imaging (DWI) of network connectivity. We investigated whether physical performance in memory clinic patients is related to white matter network connectivity. DESIGN: Observational cross-sectional study. SETTING: Memory clinic. PARTICIPANTS: Patients referred to a memory clinic with vascular brain injury on MRI (n = 90; average age = 72 years; 60% male; 34% with diagnosis Alzheimer disease). MEASUREMENTS: We reconstructed structural brain networks from DWI with fiber tractography and used graph theory to calculate global efficiency, fractional anisotropy (FA), and mean diffusivity (MD) of the white matter, and nodal strength (mean FA or MD of all white matter tracts connected to a node). Assessment of physical performance included gait speed, chair stand time, and Short Physical Performance Battery (SPPB) score. RESULTS: Lower global efficiency, lower FA, and higher MD correlated with poorer gait speed, SPPB scores, and chair stand times (R range = 0.23-0.42). Global efficiency and FA explained 5% to 16% of the variance in gait speed, chair stand times, and SPPB scores, independent of age and sex. Moreover, global efficiency and FA explained an additional 4% to 5% of variance on top of lacunar infarcts and white matter hyperintensities. Regional analyses showed that, in particular, the connectivity strength of prefrontal, occipital, striatal, and thalamic nodes correlated with gait speed. CONCLUSION: Poorer physical performance is related to disrupted white matter network connectivity in memory clinic patients with vascular brain injury. The associations of these network abnormalities are partially independent of visible vascular injury. J Am Geriatr Soc 67:1880-1887, 2019.

Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration.

INTRODUCTION: Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease. METHODS: Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis. RESULTS: A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository. CONCLUSIONS: The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

Histopathology of diffusion imaging abnormalities in cerebral amyloid angiopathy.

OBJECTIVE: We sought to determine the underlying mechanism for altered white matter diffusion tensor imaging (DTI) measures at the histopathologic level in patients with cerebral amyloid angiopathy (CAA). METHODS: Formalin-fixed intact hemispheres from 9 CAA cases and 2 elderly controls were scanned at 3-tesla MRI, including a diffusion-weighted sequence. DTI measures (i.e., fractional anisotropy [FA] and mean diffusivity [MD]) and histopathology measures were obtained from 2 tracts: the anterior thalamic radiation and inferior longitudinal fasciculus. RESULTS: FA was reduced in both tracts and MD was increased in cases with CAA compared to controls. Regional FA was significantly correlated with tissue rarefaction, myelin density, axonal density, and white matter microinfarcts. MD correlated significantly with tissue rarefaction, myelin density, and white matter microinfarcts, but not axonal density. FA and MD did not correlate with oligodendrocytes, astrocytes, or gliosis. Multivariate analysis revealed that tissue rarefaction (ß = -0.32 ± 0.12, p = 0.009) and axonal density (ß = 0.25 ± 0.12, p = 0.04) were both independently associated with FA, whereas myelin density was independently associated with MD (ß = -0.32 ± 0.12, p = 0.013). Finally, we found an association between increased MD in the frontal white matter and CAA severity in the frontal cortex (p = 0.035). CONCLUSIONS: These results suggest that overall tissue loss, and in particular axonal and myelin loss, are major components underlying CAA-related alterations in DTI properties observed in living patients. The findings allow for a more mechanistic interpretation of DTI parameters in small vessel disease and for mechanism-based selection of candidate treatments to prevent vascular cognitive impairment.

Microstructural White Matter Abnormalities and Cognitive Impairment After Aneurysmal Subarachnoid Hemorrhage.

Background and Purpose- Aneurysmal subarachnoid hemorrhage (aSAH) may have detrimental effects on white matter microstructure, which may in turn explain the cognitive impairments that occur often after aSAH. We investigated (1) whether the white matter microstructure is altered in patients with aSAH compared with patients with an unruptured intracranial aneurysm and (2) whether these abnormalities are associated with cognitive impairment 3 months after ictus. Methods- Forty-nine patients with aSAH and 22 patients with an unruptured intracranial aneurysm underwent 3T brain magnetic resonance imaging, including a high-resolution diffusion tensor imaging sequence. Patients with aSAH were scanned 2 weeks and 6 months after ictus. Microstructural white matter alterations were quantified by the fractional anisotropy and mean diffusivity (MD). Cognition was evaluated 3 months after ictus. Results- Patients with aSAH had higher white matter MD 2 weeks after ictus than patients with an unruptured intracranial aneurysm (mean difference±SEM, 0.3±0.01×10-3 mm2/s; P≤0.01), reflecting an abnormal microstructure. After 6 months, the MD had returned to the level of the unruptured intracranial aneurysm group. No between-group differences in fractional anisotropy were found (-0.01±0.01; P=0.16). Higher MD at 2 weeks was associated with cognitive impairment after 3 months (odds ratio per SD increase in MD, 2.6; 95% CI, 1.1-6.7). The association between MD and cognitive impairment was independent of conventional imaging markers of aSAH-related brain injury (ie, cerebral infarction, hydrocephalus, total amount of subarachnoid blood, total brain volume, or white matter hyperintensity severity). Conclusions- Patients with aSAH have temporary white matter abnormalities in the subacute phase that are associated with cognitive impairment at 3 months after ictus.

Cerebral Cortical Microinfarcts on Magnetic Resonance Imaging and Their Association With Cognition in Cerebral Amyloid Angiopathy.

Background and Purpose- We aimed to explore the association between presence of cerebral cortical microinfarcts (CMIs) on magnetic resonance imaging and other small-vessel disease neuroimaging biomarkers in cerebral amyloid angiopathy (CAA) and to analyze the role of CMIs on individual cognitive domains and dementia conversion. Methods- Participants were recruited from an ongoing longitudinal research cohort of eligible CAA patients between March 2006 and October 2016. A total of 102 cases were included in the analysis that assessed the relationship of cortical CMIs to CAA neuroimaging markers. Ninety-five subjects had neuropsychological tests conducted within 1 month of magnetic resonance imaging scanning. Seventy-five nondemented CAA patients had cognitive evaluation data available during follow-up. Results- Among 102 patients enrolled, 40 patients had CMIs (39%) on magnetic resonance imaging. CMIs were uniformly distributed throughout the cortex without regional predilection ( P=0.971). The presence of CMIs was associated with lower total brain volume (odds ratio, 0.85; 95% CI, 0.74-0.98; P=0.025) and presence of cortical superficial siderosis (odds ratio, 2.66; 95% CI, 1.10-6.39; P=0.029). In 95 subjects with neuropsychological tests, presence of CMIs was associated with impaired executive function (ß, -0.23; 95% CI, -0.44 to -0.02; P=0.036) and processing speed (ß, -0.24; 95% CI, -0.45 to -0.04; P=0.020). Patients with CMIs had a higher cumulative dementia incidence compared with patients without CMIs ( P=0.043), whereas only baseline total brain volume (hazard ratio, 0.76; 95% CI, 0.62-0.92; P=0.006) independently predicted dementia conversion. Conclusions- Magnetic resonance imaging-detected CMIs in CAA correlated with greater overall disease burden. The presence of CMIs was associated with worse cognitive performance, whereas only total brain atrophy independently predicted dementia conversion.

Parietal Involvement in Constructional Apraxia as Measured Using the Pentagon Copying Task.

Deficits in copying ("constructional apraxia") is generally defined as a multifaceted deficit. The exact neural correlates of the different types of copying errors are unknown. To assess whether the different categories of errors on the pentagon drawing relate to different neural correlates, we examined the pentagon drawings of the MMSE in persons with subjective cognitive complaints, mild cognitive impairment, or early dementia due to Alzheimer's disease. We adopted a qualitative scoring method for the pentagon copy test (QSPT) which categorizes different possible errors in copying rather than the dichotomous categories "correct" or "incorrect." We correlated (regional) gray matter volumes with performance on the different categories of the QSPT. Results showed that the total score of the QSPT was specifically associated with parietal gray matter volume and not with frontal, temporal, and occipital gray matter volume. A more fine-grained analysis of the errors reveals that the intersection score and the number of angles share their underlying neural correlates and are associated with specific subregions of the parietal cortex. These results are in line with the idea that constructional apraxia can be attributed to the failure to integrate visual information correctly from one fixation to the next, a process called spatial remapping.

The cumulative effect of small vessel disease lesions is reflected in structural brain networks of memory clinic patients.

Background and purpose: Mechanisms underlying cognitive impairment in patients with small vessel disease (SVD) are still unknown. We hypothesized that cognition is affected by the cumulative effect of multiple SVD-related lesions on brain connectivity. We therefore assessed the relationship between the total SVD burden on MRI, global brain network efficiency, and cognition in memory clinic patients with vascular brain injury. Methods: 173 patients from the memory clinic of the University Medical Center Utrecht underwent a 3 T brain MRI scan (including diffusion MRI sequences) and neuropsychological testing. MRI markers for SVD were rated and compiled in a previously developed total SVD score. Structural brain networks were reconstructed using fiber tractography followed by graph theoretical analysis. The relationship between total SVD burden score, global network efficiency and cognition was assessed using multiple linear regression analyses. Results: Each point increase on the SVD burden score was associated with 0.260 [-0.404 - -0.117] SD units decrease of global brain network efficiency (p < .001). Global network efficiency was associated with information processing speed (standardized B = -0.210, p = .004) and attention and executive functioning (B = 0.164, p = .042), and mediated the relationship between SVD burden and information processing speed (p = .027) but not with executive functioning (p = .12). Conclusion: Global network efficiency is sensitive to the cumulative effect of multiple manifestations of SVD on brain connectivity. Global network efficiency may therefore serve as a useful marker for functionally relevant SVD-related brain injury in clinical trials.

A Role for New Brain Magnetic Resonance Imaging Modalities in Daily Clinical Practice: Protocol of the Prediction of Cognitive Recovery After Stroke (PROCRAS) Study.

BACKGROUND: Cognitive impairment is common after acute ischemic stroke, affecting up to 75% of the patients. About half of the patients will show recovery, whereas the others will remain cognitively impaired or deteriorate. It is difficult to predict these different cognitive outcomes. OBJECTIVE: The objective of this study is to investigate whether diffusion tensor imaging-based measures of brain connectivity predict cognitive recovery after 1 year, in addition to patient characteristics and stroke severity. A specific premise of the Prediction of Cognitive Recovery After Stroke (PROCRAS) study is that it is conducted in a daily practice setting. METHODS: The PROCRAS study is a prospective, mono-center cohort study conducted in a large teaching hospital in the Netherlands. A total of 350 patients suffering from an ischemic stroke who screen positive for cognitive impairment on the Montreal Cognitive Assessment (MoCA<26) in the acute stage will undergo a 3Tesla-Magnetic Resonance Imaging (3T-MRI) with a diffusion-weighted sequence and a neuropsychological assessment. Patients will be classified as being unimpaired, as having a mild vascular cognitive disorder, or as having a major vascular cognitive disorder. One year after stroke, patients will undergo follow-up neuropsychological assessment. The primary endpoint is recovery of cognitive function 1 year after stroke in patients with a confirmed poststroke cognitive disorder. The secondary endpoint is deterioration of cognitive function in the first year after stroke. RESULTS: The study is already ongoing for 1.5 years, and thus far, 252 patients have provided written informed consent. Final results are expected in June 2019. CONCLUSIONS: The PROCRAS study will show the additional predictive value of diffusion tensor imaging-based measures of brain connectivity for cognitive outcome at 1 year in patients with a poststroke cognitive disorder in a daily clinical practice setting. REGISTERED REPORT IDENTIFIER: RR1-10.2196/9431.

Automated Multi-Atlas Segmentation of Hippocampal and Extrahippocampal Subregions in Alzheimer's Disease at 3T and 7T: What Atlas Composition Works Best?

BACKGROUND: Multi-atlas segmentation, a popular technique implemented in the Automated Segmentation of Hippocampal Subfields (ASHS) software, utilizes multiple expert-labelled images ("atlases") to delineate medial temporal lobe substructures. This multi-atlas method is increasingly being employed in early Alzheimer's disease (AD) research, it is therefore becoming important to know how the construction of the atlas set in terms of proportions of controls and patients with mild cognitive impairment (MCI) and/or AD affects segmentation accuracy. OBJECTIVE: To evaluate whether the proportion of controls in the training sets affects the segmentation accuracy of both controls and patients with MCI and/or early AD at 3T and 7T. METHODS: We performed cross-validation experiments varying the proportion of control subjects in the training set, ranging from a patient-only to a control-only set. Segmentation accuracy of the test set was evaluated by the Dice similarity coeffiecient (DSC). A two-stage statistical analysis was applied to determine whether atlas composition is linked to segmentation accuracy in control subjects and patients, for 3T and 7T. RESULTS: The different atlas compositions did not significantly affect segmentation accuracy at 3T and for patients at 7T. For controls at 7T, including more control subjects in the training set significantly improves the segmentation accuracy, but only marginally, with the maximum of 0.0003 DSC improvement per percent increment of control subject in the training set. CONCLUSION: ASHS is robust in this study, and the results indicate that future studies investigating hippocampal subfields in early AD populations can be flexible in the selection of their atlas compositions.

Dementia incidence and predictors in cerebral amyloid angiopathy patients without intracerebral hemorrhage.

Cerebral amyloid angiopathy (CAA) is a common cause of cognitive impairment in older individuals. This study aimed to investigate predictors of dementia in CAA patients without intracerebral hemorrhage (ICH). A total of 158 non-demented patients from the Stroke Service or the Memory Clinic who met the modified Boston Criteria for probable CAA were included. At baseline, neuroimaging markers, including lobar microbleeds (cerebral microbleeds (CMBs)), white matter hyperintensities (WMH), cortical superficial siderosis (cSS), magnetic resonance imaging (MRI)-visible centrum semiovale perivascular spaces (CSO-PVS), lacunes, and medial temporal atrophy (MTA) were assessed. The overall burden of small vessel disease (SVD) for CAA was calculated by a cumulative score based on CMB number, WMH severity, cSS presence and extent and CSO-PVS severity. The estimated cumulative dementia incidence at 1 year was 14% (95% confidence interval (CI): 5%-23%), and 5 years 73% (95% CI: 55%, 84%). Age (hazard ratio (HR) 1.05 per year, 95% CI: 1.01-1.08, p = 0.007), presence of MCI status (HR 3.40, 95% CI: 1.97-6.92, p < 0.001), MTA (HR 1.71 per point, 95% CI: 1.26-2.32, p = 0.001), and SVD score (HR 1.23 per point, 95% CI: 1.20-1.48, p = 0.030) at baseline were independent predictors for dementia conversion in these patients. Cognitive deterioration of CAA patients appears attributable to cumulative changes, from both vasculopathic and neurodegenerative lesions.