Ontario Neurodegenerative Disease Research Initiative (ONDRI): Structural MRI Methods and Outcome Measures

Perivascular spaces, plasma GFAP, and speeded executive function in neurodegenerative diseases

INTRODUCTION

We investigated the effect of perivascular spaces (PVS) volume on speeded executive function (sEF), as mediated by white matter hyperintensities (WMH) volume and plasma glial fibrillary acidic protein (GFAP) in neurodegenerative diseases.

METHODS

A mediation analysis was performed to assess the relationship between neuroimaging markers and plasma biomarkers on sEF in 333 participants clinically diagnosed with Alzheimer's disease/mild cognitive impairment, frontotemporal dementia, or cerebrovascular disease from the Ontario Neurodegenerative Disease Research Initiative.

RESULTS

PVS was significantly associated with sEF (c = -0.125 ± 0.054, 95% bootstrap confidence interval [CI] [-0.2309, -0.0189], p = 0.021). This effect was mediated by both GFAP and WMH.

DISCUSSION

In this unique clinical cohort of neurodegenerative diseases, we demonstrated that the effect of PVS on sEF was mediated by the presence of elevated plasma GFAP and white matter disease. These findings highlight the potential utility of imaging and plasma biomarkers in the current landscape of therapeutics targeting dementia.

HIGHLIGHTS

Perivascular spaces (PVS) and white matter hyperintensities (WMH) are imaging markers of small vessel disease. Plasma glial fibrillary protein acidic protein (GFAP) is a biomarker of astroglial injury. PVS, WMH, and GFAP are relevant in executive dysfunction from neurodegeneration. PVS's effect on executive function was mediated by GFAP and white matter disease.

History of traumatic brain injury is associated with increased grey-matter loss in patients with mild cognitive impairment

OBJECTIVES

To investigate whether a history of traumatic brain injury (TBI) is associated with greater long-term grey-matter loss in patients with mild cognitive impairment (MCI).

METHODS

85 patients with MCI were identified, including 26 with a previous history of traumatic brain injury (MCI[TBI-]) and 59 without (MCI[TBI+]). Cortical thickness was evaluated by segmenting T1-weighted MRI scans acquired longitudinally over a 2-year period. Bayesian multilevel modelling was used to evaluate group differences in baseline cortical thickness and longitudinal change, as well as group differences in neuropsychological measures of executive function.

RESULTS

At baseline, the MCI[TBI+] group had less grey matter within right entorhinal, left medial orbitofrontal and inferior temporal cortex areas bilaterally. Longitudinally, the MCI[TBI+] group also exhibited greater longitudinal declines in left rostral middle frontal, the left caudal middle frontal and left lateral orbitofrontal areas sover the span of 2 years (median = 1-2%, 90%HDI [-0.01%: -0.001%], probability of direction (PD) = 90-99%). The MCI[TBI+] group also displayed greater longitudinal declines in Trail-Making-Test (TMT)-derived ratio (median: 0.737%, 90%HDI: [0.229%: 1.31%], PD = 98.8%) and differences scores (median: 20.6%, 90%HDI: [-5.17%: 43.2%], PD = 91.7%).

CONCLUSIONS

Our findings support the notion that patients with MCI and a history of TBI are at risk of accelerated neurodegeneration, displaying greatest evidence for cortical atrophy within the left middle frontal and lateral orbitofrontal frontal cortex. Importantly, these results suggest that long-term TBI-mediated atrophy is more pronounced in areas vulnerable to TBI-related mechanical injury, highlighting their potential relevance for diagnostic forms of intervention in TBI.

Vascular Burden Moderates the Relationship Between ADHD and Cognition in Older Adults

OBJECTIVES

Recent evidence suggests attention-deficit/hyperactivity disorder (ADHD) is a risk factor for cognitive impairment in later life. Here, we investigated cerebrovascular burden, quantified using white matter hyperintensity (WMH) volumes, as a potential mediator of this relationship.

DESIGN

This was a cross-sectional observational study.

SETTING

Participants were recruited from a cognitive neurology clinic where they had been referred for cognitive assessment, or from the community.

PARTICIPANTS

Thirty-nine older adults with clinical ADHD and 50 age- and gender-matched older adults without ADHD.

MEASUREMENTS

A semiautomated structural MRI pipeline was used to quantify periventricular (pWMH) and deep WMH (dWMH) volumes. Cognition was measured using standardized tests of memory, processing speed, visuo-construction, language, and executive functioning. Mediation models, adjusted for sex, were built to test the hypothesis that ADHD status exerts a deleterious impact on cognitive performance via WMH burden.

RESULTS

Results did not support a mediated effect of ADHD on cognition. Post hoc inspection of the data rather suggested a moderated effect, which was investigated as an a posteriori hypothesis. These results revealed a significant moderating effect of WMH on the relationship between ADHD memory, speed, and executive functioning, wherein ADHD was negatively associated with cognition at high and medium levels of WMH, but not when WMH volumes were low.

CONCLUSIONS

ADHD increases older adults' susceptibility to the deleterious cognitive effects of WMH in the brain. Older adults with ADHD may be at risk for cognitive impairment if they have deep WMH volumes above 61 mm3 and periventricular WMH above 260 mm3.

Link among apolipoprotein E E4, gait, and cognition in neurodegenerative diseases: ONDRI study

INTRODUCTION

Apolipoprotein E E4 allele (APOE E4) and slow gait are independently associated with cognitive impairment and dementia. However, it is unknown whether their coexistence is associated with poorer cognitive performance and its underlying mechanism in neurodegenerative diseases.

METHODS

Gait speed, APOE E4, cognition, and neuroimaging were assessed in 480 older adults with neurodegeneration. Participants were grouped by APOE E4 presence and slow gait. Mediation analyses were conducted to determine if brain structures could explain the link between these factors and cognitive performance.

RESULTS

APOE E4 carriers with slow gait had the lowest global cognitive performance and smaller gray matter volumes compared to non-APOE E4 carriers with normal gait. Coexistence of APOE E4 and slow gait best predicted global and domain-specific poorer cognitive performances, mediated by smaller gray matter volume.

DISCUSSION

Gait slowness in APOE E4 carriers with neurodegenerative diseases may indicate extensive gray matter changes associated with poor cognition.

HIGHLIGHTS

APOE E4 and slow gait are risk factors for cognitive decline in neurodegenerative diseases. Slow gait and smaller gray matter volumes are associated, independently of APOE E4. Worse cognition in APOE E4 carriers with slow gait is explained by smaller GM volume. Gait slowness in APOE E4 carriers indicates poorer cognition-related brain changes.

Neuropsychiatric symptoms and brain morphology in patients with mild cognitive impairment, cerebrovascular disease and Parkinson disease: A cross sectional and longitudinal study

OBJECTIVES

Neuropsychiatric symptoms (NPS) increase risk of developing dementia and are linked to various neurodegenerative conditions, including mild cognitive impairment (MCI due to Alzheimer's disease [AD]), cerebrovascular disease (CVD), and Parkinson's disease (PD). We explored the structural neural correlates of NPS cross-sectionally and longitudinally across various neurodegenerative diagnoses.

METHODS

The study included individuals with MCI due to AD, (n = 74), CVD (n = 143), and PD (n = 137) at baseline, and at 2-years follow-up (MCI due to AD, n = 37, CVD n = 103, and PD n = 84). We assessed the severity of NPS using the Neuropsychiatric Inventory Questionnaire. For brain structure we included cortical thickness and subcortical volume of predefined regions of interest associated with corticolimbic and frontal-executive circuits.

RESULTS

Cross-sectional analysis revealed significant negative correlations between appetite with both circuits in the MCI and CVD groups, while apathy was associated with these circuits in both the MCI and PD groups. Longitudinally, changes in apathy scores in the MCI group were negatively linked to the changes of the frontal-executive circuit. In the CVD group, changes in agitation and nighttime behavior were negatively associated with the corticolimbic and frontal-executive circuits, respectively. In the PD group, changes in disinhibition and apathy were positively associated with the corticolimbic and frontal-executive circuits, respectively.

CONCLUSIONS

The observed correlations suggest that underlying pathological changes in the brain may contribute to alterations in neural activity associated with MBI. Notably, the difference between cross-sectional and longitudinal results indicates the necessity of conducting longitudinal studies for reproducible findings and drawing robust inferences.

Rare neurovascular genetic and imaging markers across neurodegenerative diseases

INTRODUCTION

Cerebral small vessel disease (SVD) is common in patients with cognitive impairment and neurodegenerative diseases such as Alzheimer's and Parkinson's. This study investigated the burden of magnetic resonance imaging (MRI)-based markers of SVD in patients with neurodegenerative diseases as a function of rare genetic variant carrier status.

METHODS

The Ontario Neurodegenerative Disease Research Initiative study included 520 participants, recruited from 14 tertiary care centers, diagnosed with various neurodegenerative diseases and determined the carrier status of rare non-synonymous variants in five genes (ABCC6, COL4A1/COL4A2, NOTCH3/HTRA1).

RESULTS

NOTCH3/HTRA1 were found to significantly influence SVD neuroimaging outcomes; however, the mechanisms by which these variants contribute to disease progression or worsen clinical correlates are not yet understood.

DISCUSSION

Further studies are needed to develop genetic and imaging neurovascular markers to enhance our understanding of their potential contribution to neurodegenerative diseases.

Advanced brain imaging for the diagnosis of Alzheimer disease

PURPOSE OF REVIEW

The purpose is to review the latest advances of brain imaging for the diagnosis of Alzheimer disease (AD).

RECENT FINDINGS

Brain imaging techniques provide valuable and complementary information to support the diagnosis of Alzheimer disease in clinical and research settings. The recent FDA accelerated approvals of aducanumab, lecanemab and donanemab made amyloid-PET critical in helping determine the optimal window for anti-amyloid therapeutic interventions. Tau-PET, on the other hand, is considered of key importance for the tracking of disease progression and for monitoring therapeutic interventions in clinical trials. PET imaging for microglial activation, astrocyte reactivity and synaptic degeneration are still new techniques only used in the research field, and more studies are needed to validate their use in the clinical diagnosis of AD. Finally, artificial intelligence has opened new prospective in the early detection of AD using MRI modalities.

SUMMARY

Brain imaging techniques using PET improve our understanding of the different AD-related pathologies and their relationship with each other along the course of disease. With more robust validation, machine learning and deep learning algorithms could be integrated with neuroimaging modalities to serve as valuable tools for clinicians to make early diagnosis and prognosis of AD.

Perivascular spaces mediate a relationship between diabetes and other cerebral small vessel disease markers in cerebrovascular and neurodegenerative diseases

Type 2 diabetes mellitus (T2DM) and hypertension are risk factors for cerebral small vessel disease (SVD); however, few studies have characterised their relationships with MRI-visible perivascular spaces (PVS). MRI was used to quantify deep (d) and periventricular (p) white matter hyperintensities (WMH), lacunes, PVS in the white matter (wmPVS) or basal ganglia (bgPVS), and diffusion metrics in white matter. Patients with T2DM had greater wmPVS volume and there were greater wmPVS volumes in patients with T2DM and hypertension together. Counterfactual moderated mediation models found indirect effects of T2DM on volumes of other SVD and diffusion markers that were mediated by wmPVS: pWMH, dWMH, periventricular lacunes, and deep lacunes, and progression of deep lacunes over 1 year, in patients with hypertension, but not in patients without hypertension. Studying the regulation of cortical perivascular fluid dynamics may reveal mechanisms that mediate the impact of T2DM on cerebral small vessels.

ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI

Deep artificial neural networks (DNNs) have moved to the forefront of medical image analysis due to their success in classification, segmentation, and detection challenges. A principal challenge in large-scale deployment of DNNs in neuroimage analysis is the potential for shifts in signal-to-noise ratio, contrast, resolution, and presence of artifacts from site to site due to variances in scanners and acquisition protocols. DNNs are famously susceptible to these distribution shifts in computer vision. Currently, there are no benchmarking platforms or frameworks to assess the robustness of new and existing models to specific distribution shifts in MRI, and accessible multi-site benchmarking datasets are still scarce or task-specific. To address these limitations, we propose ROOD-MRI: a novel platform for benchmarking the Robustness of DNNs to Out-Of-Distribution (OOD) data, corruptions, and artifacts in MRI. This flexible platform provides modules for generating benchmarking datasets using transforms that model distribution shifts in MRI, implementations of newly derived benchmarking metrics for image segmentation, and examples for using the methodology with new models and tasks. We apply our methodology to hippocampus, ventricle, and white matter hyperintensity segmentation in several large studies, providing the hippocampus dataset as a publicly available benchmark. By evaluating modern DNNs on these datasets, we demonstrate that they are highly susceptible to distribution shifts and corruptions in MRI. We show that while data augmentation strategies can substantially improve robustness to OOD data for anatomical segmentation tasks, modern DNNs using augmentation still lack robustness in more challenging lesion-based segmentation tasks. We finally benchmark U-Nets and vision transformers, finding robustness susceptibility to particular classes of transforms across architectures. The presented open-source platform enables generating new benchmarking datasets and comparing across models to study model design that results in improved robustness to OOD data and corruptions in MRI.

White matter hyperintensities and smaller cortical thickness are associated with neuropsychiatric symptoms in neurodegenerative and cerebrovascular diseases

BACKGROUND

Neuropsychiatric symptoms (NPS) are a core feature of most neurodegenerative and cerebrovascular diseases. White matter hyperintensities and brain atrophy have been implicated in NPS. We aimed to investigate the relative contribution of white matter hyperintensities and cortical thickness to NPS in participants across neurodegenerative and cerebrovascular diseases.

METHODS

Five hundred thirteen participants with one of these conditions, i.e. Alzheimer's Disease/Mild Cognitive Impairment, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, Parkinson's Disease, or Cerebrovascular Disease, were included in the study. NPS were assessed using the Neuropsychiatric Inventory - Questionnaire and grouped into hyperactivity, psychotic, affective, and apathy subsyndromes. White matter hyperintensities were quantified using a semi-automatic segmentation technique and FreeSurfer cortical thickness was used to measure regional grey matter loss.

RESULTS

Although NPS were frequent across the five disease groups, participants with frontotemporal dementia had the highest frequency of hyperactivity, apathy, and affective subsyndromes compared to other groups, whilst psychotic subsyndrome was high in both frontotemporal dementia and Parkinson's disease. Results from univariate and multivariate results showed that various predictors were associated with neuropsychiatric subsyndromes, especially cortical thickness in the inferior frontal, cingulate, and insula regions, sex(female), global cognition, and basal ganglia-thalamus white matter hyperintensities.

CONCLUSIONS

In participants with neurodegenerative and cerebrovascular diseases, our results suggest that smaller cortical thickness and white matter hyperintensity burden in several cortical-subcortical structures may contribute to the development of NPS. Further studies investigating the mechanisms that determine the progression of NPS in various neurodegenerative and cerebrovascular diseases are needed.

White matter hyperintensity burden predicts cognitive but not motor decline in Parkinson's disease: results from the Ontario Neurodegenerative Diseases Research Initiative

BACKGROUND AND PURPOSE

The pathophysiology of Parkinson's disease (PD) negatively affects brain network connectivity, and in the presence of brain white matter hyperintensities (WMHs) cognitive and motor impairments seem to be aggravated. However, the role of WMHs in predicting accelerating symptom worsening remains controversial. The objective was to investigate whether location and segmental brain WMH burden at baseline predict cognitive and motor declines in PD after 2 years.

METHODS

Ninety-eight older adults followed longitudinally from Ontario Neurodegenerative Diseases Research Initiative with PD of 3-8 years in duration were included. Percentages of WMH volumes at baseline were calculated by location (deep and periventricular) and by brain region (frontal, temporal, parietal, occipital lobes and basal ganglia + thalamus). Cognitive and motor changes were assessed from baseline to 2-year follow-up. Specifically, global cognition, attention, executive function, memory, visuospatial abilities and language were assessed as were motor symptoms evaluated using the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III, spatial-temporal gait variables, Freezing of Gait Questionnaire and Activities Specific Balance Confidence Scale.

RESULTS

Regression analysis adjusted for potential confounders showed that total and periventricular WMHs at baseline predicted decline in global cognition (p < 0.05). Also, total WMH burden predicted the decline of executive function (p < 0.05). Occipital WMH volumes also predicted decline in global cognition, visuomotor attention and visuospatial memory declines (p < 0.05). WMH volumes at baseline did not predict motor decline.

CONCLUSION

White matter hyperintensity burden at baseline predicted cognitive but not motor decline in early to mid-stage PD. The motor decline observed after 2 years in these older adults with PD is probably related to the primary neurodegenerative process than comorbid white matter pathology.

Optimizing automated white matter hyperintensity segmentation in individuals with stroke

White matter hyperintensities (WMHs) are a risk factor for stroke. Consequently, many individuals who suffer a stroke have comorbid WMHs. The impact of WMHs on stroke recovery is an active area of research. Automated WMH segmentation methods are often employed as they require minimal user input and reduce risk of rater bias; however, these automated methods have not been specifically validated for use in individuals with stroke. Here, we present methodological validation of automated WMH segmentation methods in individuals with stroke. We first optimized parameters for FSL's publicly available WMH segmentation software BIANCA in two independent (multi-site) datasets. Our optimized BIANCA protocol achieved good performance within each independent dataset, when the BIANCA model was trained and tested in the same dataset or trained on mixed-sample data. BIANCA segmentation failed when generalizing a trained model to a new testing dataset. We therefore contrasted BIANCA's performance with SAMSEG, an unsupervised WMH segmentation tool available through FreeSurfer. SAMSEG does not require prior WMH masks for model training and was more robust to handling multi-site data. However, SAMSEG performance was slightly lower than BIANCA when data from a single site were tested. This manuscript will serve as a guide for the development and utilization of WMH analysis pipelines for individuals with stroke.

Characteristics of the Ontario Neurodegenerative Disease Research Initiative cohort

INTRODUCTION

Understanding synergies between neurodegenerative and cerebrovascular pathologies that modify dementia presentation represents an important knowledge gap.

METHODS

This multi-site, longitudinal, observational cohort study recruited participants across prevalent neurodegenerative diseases and cerebrovascular disease and assessed participants comprehensively across modalities. We describe univariate and multivariate baseline features of the cohort and summarize recruitment, data collection, and curation processes.

RESULTS

We enrolled 520 participants across five neurodegenerative and cerebrovascular diseases. Median age was 69 years, median Montreal Cognitive Assessment score was 25, median independence in activities of daily living was 100% for basic and 93% for instrumental activities. Spousal study partners predominated; participants were often male, White, and more educated. Milder disease stages predominated, yet cohorts reflect clinical presentation.

DISCUSSION

Data will be shared with the global scientific community. Within-disease and disease-agnostic approaches are expected to identify markers of severity, progression, and therapy targets. Sampling characteristics also provide guidance for future study design.

Soluble Epoxide Hydrolase Derived Linoleic Acid Oxylipins, Small Vessel Disease Markers, and Neurodegeneration in Stroke

Background Cerebral small vessel disease is associated with higher ratios of soluble-epoxide hydrolase derived linoleic acid diols (12,13-dihydroxyoctadecenoic acid [DiHOME] and 9,10-DiHOME) to their parent epoxides (12(13)-epoxyoctadecenoic acid [EpOME] and 9(10)-EpOME); however, the relationship has not yet been examined in stroke. Methods and Results Participants with mild to moderate small vessel stroke or large vessel stroke were selected based on clinical and imaging criteria. Metabolites were quantified by ultra-high-performance liquid chromatography-mass spectrometry. Volumes of stroke, lacunes, white matter hyperintensities, magnetic resonance imaging visible perivascular spaces, and free water diffusion were quantified from structural and diffusion magnetic resonance imaging (3 Tesla). Adjusted linear regression models were used for analysis. Compared with participants with large vessel stroke (n=30), participants with small vessel stroke (n=50) had a higher 12,13-DiHOME/12(13)-EpOME ratio (β=0.251, P=0.023). The 12,13-DiHOME/12(13)-EpOME ratio was associated with more lacunes (β=0.266, P=0.028) but not with large vessel stroke volumes. Ratios of 12,13-DiHOME/12(13)-EpOME and 9,10-DiHOME/9(10)-EpOME were associated with greater volumes of white matter hyperintensities (β=0.364, P<0.001; β=0.362, P<0.001) and white matter MRI-visible perivascular spaces (β=0.302, P=0.011; β=0.314, P=0.006). In small vessel stroke, the 12,13-DiHOME/12(13)-EpOME ratio was associated with higher white matter free water diffusion (β=0.439, P=0.016), which was specific to the temporal lobe in exploratory regional analyses. The 9,10-DiHOME/9(10)-EpOME ratio was associated with temporal lobe atrophy (β=-0.277, P=0.031). Conclusions Linoleic acid markers of cytochrome P450/soluble-epoxide hydrolase activity were associated with small versus large vessel stroke, with small vessel disease markers consistent with blood brain barrier and neurovascular-glial disruption, and temporal lobe atrophy. The findings may indicate a novel modifiable risk factor for small vessel disease and related neurodegeneration.

Exploring biomarkers of processing speed and executive function: The role of the anterior thalamic radiations

INTRODUCTION

Processing speed and executive function are often impaired after stroke and in typical aging. However, there are no reliable neurological markers of these cognitive impairments. The trail making test (TMT) is a common index of processing speed and executive function. Here, we tested candidate MRI markers of TMT performance in a cohort of older adults and individuals with chronic stroke.

METHODS

In 61 older adults and 32 individuals with chronic stroke, we indexed white matter structure with region-specific lesion load (of white matter hyperintensities (WMHs) and stroke lesions) and diffusion tensor imaging (DTI) from four regions related to TMT performance: the anterior thalamic radiations (ATR), superior longitudinal fasciculus (SLF), forceps minor, and cholinergic pathways. Regression modelling was used to identify the marker(s) that explained the most variance in TMT performance.

RESULTS

DTI metrics of the ATR related to processing speed in both the older adult (TMT A: β = -3.431, p < 0.001) and chronic stroke (TMT A: β = 11.282, p < 0.001) groups. In the chronic stroke group executive function was best predicted by a combination of ATR and forceps minor DTI metrics (TMT B: _adjustedR² = 0.438, p < 0.001); no significant predictors of executive function (TMT B) emerged in the older adult group. No imaging metrics related to set shifting (TMT B-A). Regional DTI metrics predicted TMT performance above and beyond whole-brain stroke and WMH volumes and removing whole-brain lesion volumes improved model fits.

CONCLUSIONS

In this comprehensive assessment of candidate imaging markers, we demonstrate an association between ATR microstructure and processing speed and executive function performance. Regional DTI metrics provided better predictors of cognitive performance than whole-brain lesion volumes or regional lesion load, emphasizing the importance of lesion location in understanding cognition. We propose ATR DTI metrics as novel candidate imaging biomarker of post-stroke cognitive impairment.

In vivo myelin imaging and tissue microstructure in white matter hyperintensities and perilesional white matter

White matter hyperintensities negatively impact white matter structure and relate to cognitive decline in aging. Diffusion tensor imaging detects changes to white matter microstructure, both within the white matter hyperintensity and extending into surrounding (perilesional) normal-appearing white matter. However, diffusion tensor imaging markers are not specific to tissue components, complicating the interpretation of previous microstructural findings. Myelin water imaging is a novel imaging technique that provides specific markers of myelin content (myelin water fraction) and interstitial fluid (geometric mean T₂). Here we combined diffusion tensor imaging and myelin water imaging to examine tissue characteristics in white matter hyperintensities and perilesional white matter in 80 individuals (47 older adults and 33 individuals with chronic stroke). To measure perilesional normal-appearing white matter, white matter hyperintensity masks were dilated in 2 mm segments up to 10 mm in distance from the white matter hyperintensity. Fractional anisotropy, mean diffusivity, myelin water fraction, and geometric mean T₂ were extracted from white matter hyperintensities and perilesional white matter. We observed a spatial gradient of higher mean diffusivity and geometric mean T₂, and lower fractional anisotropy, in the white matter hyperintensity and perilesional white matter. In the chronic stroke group, myelin water fraction was reduced in the white matter hyperintensity but did not show a spatial gradient in perilesional white matter. Across the entire sample, white matter metrics within the white matter hyperintensity related to whole-brain white matter hyperintensity volume; with increasing white matter hyperintensity volume there was increased mean diffusivity and geometric mean T₂, and decreased myelin water fraction in the white matter hyperintensity. Normal-appearing white matter adjacent to white matter hyperintensities exhibits characteristics of a transitional stage between healthy white matter and white matter hyperintensities. This effect was observed in markers sensitive to interstitial fluid, but not in myelin water fraction, the specific marker of myelin concentration. Within the white matter hyperintensity, interstitial fluid was higher and myelin concentration was lower in individuals with more severe cerebrovascular disease. Our data suggests white matter hyperintensities have penumbra-like effects in perilesional white matter that specifically reflect increased interstitial fluid, with no changes to myelin concentration. In contrast, within the white matter hyperintensity there are varying levels of demyelination, which vary based on the severity of cerebrovascular disease. Diffusion tensor imaging and myelin imaging may be useful clinical markers to predict white matter hyperintensity formation, and to stage neuronal damage within white matter hyperintensities.

Investigating the contribution of white matter hyperintensities and cortical thickness to empathy in neurodegenerative and cerebrovascular diseases

Change in empathy is an increasingly recognised symptom of neurodegenerative diseases and contributes to caregiver burden and patient distress. Empathy impairment has been associated with brain atrophy but its relationship to white matter hyperintensities (WMH) is unknown. We aimed to investigate the relationships amongst WMH, brain atrophy, and empathy deficits in neurodegenerative and cerebrovascular diseases. Five hundred thirteen participants with Alzheimer's disease/mild cognitive impairment, amyotrophic lateral sclerosis, frontotemporal dementia (FTD), Parkinson's disease, or cerebrovascular disease (CVD) were included. Empathy was assessed using the Interpersonal Reactivity Index. WMH were measured using a semi-automatic segmentation and FreeSurfer was used to measure cortical thickness. A heterogeneous pattern of cortical thinning was found between groups, with FTD showing thinning in frontotemporal regions and CVD in left superior parietal, left insula, and left postcentral. Results from both univariate and multivariate analyses revealed that several variables were associated with empathy, particularly cortical thickness in the fronto-insulo-temporal and cingulate regions, sex (female), global cognition, and right parietal and occipital WMH. Our results suggest that cortical atrophy and WMH may be associated with empathy deficits in neurodegenerative and cerebrovascular diseases. Future work should consider investigating the longitudinal effects of WMH and atrophy on empathy deficits in neurodegenerative and cerebrovascular diseases.

MRI-visible perivascular space volumes, sleep duration and daytime dysfunction in adults with cerebrovascular disease

OBJECTIVES

Recent studies suggest that interindividual genetic differences in glial-dependent CSF flow through the brain parenchyma, known as glymphatic flow, may trigger compensatory changes in human sleep physiology. In animal models, brain perivascular spaces are a critical conduit for glymphatic flow. We tested the hypothesis that MRI-visible PVS volumes, a putative marker of perivascular dysfunction, are associated with compensatory differences in real-world human sleep behavior.

METHODS

We analyzed data from 152 cerebrovascular disease patients from the Ontario Neurodegenerative Disease Research Initiative (ONDRI). PVS volumes were measured using 3T-MRI. Self-reported total sleep time, time in bed, and daytime dysfunction were extracted from the Pittsburgh Sleep Quality Index.

RESULTS

Individuals with greater PVS volumes reported longer time in bed (+0.85 h per log10 proportion of intracranial volume (ICV) occupied by PVS, SE = 0.30, p = 0.006) and longer total sleep times (+0.70 h per log10 proportion of ICV occupied by PVS volume, SE = 0.33, p = 0.04), independent of vascular risk factors, sleep apnea, nocturnal sleep disturbance, depression, and global cognitive status. Further analyses suggested that the positive association between PVS volumes and total sleep time was mediated by greater time in bed. Moreover, despite having on average greater total sleep times, individuals with greater basal ganglia PVS volumes were more likely to report daytime dysfunction (OR 5.63 per log10 proportion of ICV occupied by PVS, 95% CI: 1.38-22.26, p = 0.018).

CONCLUSIONS

Individuals with greater PVS volumes spend more time in bed, resulting in greater total sleep time, which may represent a behavioral compensatory response to perivascular space dysfunction.

Multisite Comparison of MRI Defacing Software Across Multiple Cohorts

With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3-85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3-20 years) for afni_refacer and the oldest (44-85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files.

Cortical Thickness Estimation in Individuals With Cerebral Small Vessel Disease, Focal Atrophy, and Chronic Stroke Lesions

BACKGROUND

Regional changes to cortical thickness in individuals with neurodegenerative and cerebrovascular diseases (CVD) can be estimated using specialized neuroimaging software. However, the presence of cerebral small vessel disease, focal atrophy, and cortico-subcortical stroke lesions, pose significant challenges that increase the likelihood of misclassification errors and segmentation failures.

PURPOSE

The main goal of this study was to examine a correction procedure developed for enhancing FreeSurfer's (FS's) cortical thickness estimation tool, particularly when applied to the most challenging MRI obtained from participants with chronic stroke and CVD, with varying degrees of neurovascular lesions and brain atrophy.

METHODS

In 155 CVD participants enrolled in the Ontario Neurodegenerative Disease Research Initiative (ONDRI), FS outputs were compared between a fully automated, unmodified procedure and a corrected procedure that accounted for potential sources of error due to atrophy and neurovascular lesions. Quality control (QC) measures were obtained from both procedures. Association between cortical thickness and global cognitive status as assessed by the Montreal Cognitive Assessment (MoCA) score was also investigated from both procedures.

RESULTS

Corrected procedures increased "Acceptable" QC ratings from 18 to 76% for the cortical ribbon and from 38 to 92% for tissue segmentation. Corrected procedures reduced "Fail" ratings from 11 to 0% for the cortical ribbon and 62 to 8% for tissue segmentation. FS-based segmentation of T1-weighted white matter hypointensities were significantly greater in the corrected procedure (5.8 mL vs. 15.9 mL, p < 0.001). The unmodified procedure yielded no significant associations with global cognitive status, whereas the corrected procedure yielded positive associations between MoCA total score and clusters of cortical thickness in the left superior parietal (p = 0.018) and left insula (p = 0.04) regions. Further analyses with the corrected cortical thickness results and MoCA subscores showed a positive association between left superior parietal cortical thickness and Attention (p < 0.001).

CONCLUSION

These findings suggest that correction procedures which account for brain atrophy and neurovascular lesions can significantly improve FS's segmentation results and reduce failure rates, thus maximizing power by preventing the loss of our important study participants. Future work will examine relationships between cortical thickness, cerebral small vessel disease, and cognitive dysfunction due to neurodegenerative disease in the ONDRI study.