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IntroductionWhite matter hyperintensities (WMHs) are frequently observed on magnetic resonance (MR) images in older adults, commonly appearing as areas of high signal intensity on fluid-attenuated inversion recovery (FLAIR) MR scans. Elevated WMH volumes are associated with a greater risk of dementia and stroke, even after accounting for vascular risk factors. Manual segmentation, while considered the ground truth, is both labor-intensive and time-consuming, limiting the generation of annotated WMH datasets. Un-annotated data are relatively available; however, the requirement of annotated data poses a challenge for developing supervised machine learning models.MethodsTo address this challenge, we implemented a multi-stage semi-supervised learning (M3SL) approach that first uses un-annotated data segmented by traditional processing methods (“bronze” and “silver” quality data) and then uses a smaller number of “gold”-standard annotations for model refinement. The M3SL approach enabled fine-tuning of the model weights with the gold-standard annotations. This approach was integrated into the training of a U-Net model for WMH segmentation. We used data from three scanner vendors (over more than five scanners) and from both cognitively normal (CN) adult and patients cohorts [with mild cognitive impairment and Alzheimer's disease (AD)].ResultsAn analysis of WMH segmentation performance across both scanner and clinical stage (CN, MCI, AD) factors was conducted. We compared our results to both conventional and transfer-learning deep learning methods and observed better generalization with M3SL across different datasets. We evaluated several metrics (F-measure, IoU, and Hausdorff distance) and found significant improvements with our method compared to conventional (p < 0.001) and transfer-learning (p < 0.001).DiscussionThese findings suggest that automated, non-machine learning, tools have a role in a multi-stage learning framework and can reduce the impact of limited annotated data and, thus, enhance model performance.

Objective: The corticospinal tract (CST) reveals progressive microstructural alterations in ALS measurable by DTI. The aim of this study was to evaluate fractional anisotropy (FA) along the CST as a longitudinal marker of disease progression in ALS. Methods: The study cohort consisted of 114 patients with ALS and 110 healthy controls from the second prospective, longitudinal, multicentre study of the Canadian ALS Neuroimaging Consortium (CALSNIC-2). DTI and clinical data from a harmonized protocol across 7 centres were collected. Thirty-nine ALS patients and 61 controls completed baseline and two follow-up visits and were included for longitudinal analyses. Whole brain-based spatial statistics and hypothesis-guided tract-of-interest analyses were performed for cross-sectional and longitudinal analyses. Results: FA was reduced at baseline and longitudinally in the CST, mid-corpus callosum (CC), frontal lobe, and other ALS-related tracts, with alterations most evident in the CST and mid-CC. CST and pontine FA correlated with functional impairment (ALSFRS-R), upper motor neuron function, and clinical disease progression rate. Reduction in FA was largely located in the upper CST; however, the longitudinal decline was greatest in the lower CST. Effect sizes were dependent on region, resulting in study group sizes between 17 and 31 per group over a 9-month interval. Cross-sectional effect sizes were maximal in the upper CST; whereas, longitudinal effect sizes were maximal in mid-callosal tracts. Conclusions: Progressive microstructural alterations in ALS are most prominent in the CST and CC. DTI can provide a biomarker of cerebral degeneration in ALS, with longitudinal changes in white matter demonstrable over a reasonable observation period, with a feasible number of participants, and within a multicentre framework.

BackgroundStroke, even when minor, increases the risk of dementia. We aimed to determine whether patients with transient ischaemic attack (TIA) exhibit higher rates of cerebral and regional atrophy 1-year after first stroke symptoms and evaluate the relationship with small vessel disease and cognitive performance.MethodsTIA patients and controls without cognitive symptoms underwent high-resolution T1-weighted MRI and cognitive testing at baseline and 1-year. Percent brain volume change (PBVC) was measured, and the location of regional atrophy and small vessel disease (CSVD) burden was evaluated. Neuropsychological testing assessed memory, processing speed, and executive function.ResultsA total of 76 TIA patients and 53 controls of mean age 67 (SD = 8) and 68 years (SD = 8) were recruited. TIA patients demonstrated greater improvement of visual memory and executive function at 1-year. TIA patients had greater median PBVC/year compared to controls (−0.79% [(−1.22)-(−0.38)] vs. -0.41% [(−0.62)-0.19]; p

IntroductionCerebral amyloid angiopathy (CAA) is a small vessel disease that causes covert and symptomatic brain hemorrhaging. We hypothesized that persons with CAA would have increased brain iron content detectable by quantitative susceptibility mapping (QSM) on magnetic resonance imaging (MRI), and that higher iron content would be associated with worse cognition.MethodsParticipants with CAA (n = 21), mild Alzheimer’s disease with dementia (AD-dementia; n = 14), and normal controls (NC; n = 83) underwent 3T MRI. Post-processing QSM techniques were applied to obtain susceptibility values for regions of the frontal and occipital lobe, thalamus, caudate, putamen, pallidum, and hippocampus. Linear regression was used to examine differences between groups, and associations with global cognition, controlling for multiple comparisons using the false discovery rate method.ResultsNo differences were found between regions of interest in CAA compared to NC. In AD, the calcarine sulcus had greater iron than NC (β = 0.99 [95% CI: 0.44, 1.53], q < 0.01). However, calcarine sulcus iron content was not associated with global cognition, measured by the Montreal Cognitive Assessment (p > 0.05 for all participants, NC, CAA, and AD).DiscussionAfter correcting for multiple comparisons, brain iron content, measured via QSM, was not elevated in CAA compared to NC in this exploratory study.

BackgroundPrevious reports have suggested that patients with cerebral amyloid angiopathy (CAA) may harbor smaller white matter, basal ganglia, and cerebellar volumes compared to age-matched healthy controls (HC) or patients with Alzheimer’s disease (AD). We investigated whether CAA is associated with subcortical atrophy.MethodsThe study was based on the multi-site Functional Assessment of Vascular Reactivity cohort and included 78 probable CAA (diagnosed according to the Boston criteria v2.0), 33 AD, and 70 HC. Cerebral and cerebellar volumes were extracted from brain 3D T1-weighted MRI using FreeSurfer (v6.0). Subcortical volumes, including total white matter, thalamus, basal ganglia, and cerebellum were reported as proportion (%) of estimated total intracranial volume. White matter integrity was quantified by the peak width of skeletonized mean diffusivity.ResultsParticipants in the CAA group were older (74.0 ± 7.0, female 44%) than the AD (69.7 ± 7.5, female 42%) and HC (68.8 ± 7.8, female 69%) groups. CAA participants had the highest white matter hyperintensity volume and worse white matter integrity of the three groups. After adjusting for age, sex, and study site, CAA participants had smaller putamen volumes (mean differences, −0.024% of intracranial volume; 95% confidence intervals, −0.041% to −0.006%; p = 0.005) than the HCs but not AD participants (−0.003%; −0.024 to 0.018%; p = 0.94). Other subcortical volumes including subcortical white matter, thalamus, caudate, globus pallidus, cerebellar cortex or cerebellar white matter were comparable between all three groups.ConclusionIn contrast to prior studies, we did not find substantial atrophy of subcortical volumes in CAA compared to AD or HCs, except for the putamen. Differences between studies may reflect heterogeneity in CAA presenting syndromes or severity.

Background and Aims: Patients with transient ischemic attack (TIA) have a substantially increased risk of early dementia. In this exploratory study, we aim to determine whether patients with TIA have 1) measurable regional cerebral hypoperfusion unrelated to the location of ischemia, and 2) determine the relationship of regional cerebral blood flow (rCBF) with their cognitive profiles. Methods: Patients with TIA (N = 49) and seventy-nine (N = 79) age and sex matched controls underwent formal neuropsychological testing and MRI. Quantitative arterial spin labelling rCBF maps (mL/min/100 g) were registered to the corresponding high resolution T1-weighted image. Linear regression was used to determine the association between demographic, clinical and cognitive variables and rCBF. Results: Patients with TIA had significantly (p

Quantitative imaging biomarkers (QIBs) can be defined as objective measures that are sensitive and specific to changes in tissue physiology. Provided the acquired QIBs are not affected by scanner changes, they could play an important role in disease diagnosis, prognosis, management, and treatment monitoring. The precision of selected QIBs was assessed from data collected on a 3-T scanner in four healthy participants over a 5-year period. Inevitable scanner changes and acquisition protocol revisions occurred during this time. Standard and custom processing pipelines were used to calculate regional brain volume, cortical thickness, T2, T2*, quantitative susceptibility, cerebral blood flow, axial, radial and mean diffusivity, peak width of skeletonized mean diffusivity, and fractional anisotropy from the acquired images. Coefficient of variation (CoV) and intra-class correlation (ICC) indices were determined in the short-term (i.e., repeatable over three acquisitions within 4 weeks) and in the long-term (i.e., reproducible over four acquisition sessions in 5 years). Precision indices varied based on acquisition technique, processing pipeline, and anatomical region. Good repeatability (average CoV=2.40% and ICC=0.78) and reproducibility (average CoV=8.86 % and ICC=0.72) were found over all QIBs. The best performance indices were obtained for diffusion derived biomarkers (CoV∼0.96% and ICCs=0.87); conversely, the poorest indices were found for the cerebral blood flow biomarker (CoV>10% and ICC

Deep-learning-based brain magnetic resonance imaging (MRI) reconstruction methods have the potential to accelerate the MRI acquisition process. Nevertheless, the scientific community lacks appropriate benchmarks to assess the MRI reconstruction quality of high-resolution brain images, and evaluate how these proposed algorithms will behave in the presence of small, but expected data distribution shifts. The multi-coil MRI (MC-MRI) reconstruction challenge provides a benchmark that aims at addressing these issues, using a large dataset of high-resolution, three-dimensional, T1-weighted MRI scans. The challenge has two primary goals: (1) to compare different MRI reconstruction models on this dataset and (2) to assess the generalizability of these models to data acquired with a different number of receiver coils. In this paper, we describe the challenge experimental design and summarize the results of a set of baseline and state-of-the-art brain MRI reconstruction models. We provide relevant comparative information on the current MRI reconstruction state-of-the-art and highlight the challenges of obtaining generalizable models that are required prior to broader clinical adoption. The MC-MRI benchmark data, evaluation code, and current challenge leaderboard are publicly available. They provide an objective performance assessment for future developments in the field of brain MRI reconstruction.

Multi–site imaging consortiums strive to increase participant numbers by pooling data across sites, but scanner related differences can bias results. This study combines data from three research MRI centers, including three different scanner models from two vendors, to examine non–harmonized T1–weighted brain imaging protocols in two cohorts. First, 23 human traveling phantoms were scanned twice each at all three sites (six scans per person; 138 scans total) to quantify within–participant variability of brain volumes (total brain, white matter, gray matter, lateral ventricles, thalamus, caudate, putamen and globus pallidus), and to calculate site–specific correction factors for each structure. Sample size calculations were used to determine the number of traveling phantoms needed to achieve effect sizes for observed differences to help guide future studies. Next, cross–sectional lifespan volume trajectories were examined in 856 healthy participants (5—91 years of age) scanned at these sites. Cross–sectional trajectories of volume versus age for each structure were then compared before and after application of traveling phantom based site–specific correction factors, as well as correction using the open–source method ComBat. Although small systematic differences between sites were observed in the traveling phantom analysis, correction for site using either method had little impact on the lifespan trajectories. Only white matter had small but significant differences in the intercept parameter after ComBat correction (but not traveling phantom based correction), while no other fits differed. This suggests that age–related changes over the lifespan outweigh systematic differences between scanners for volumetric analysis. This work will help guide pooling of multisite datasets as well as meta–analyses of data from non–harmonized protocols.

Large, multi-site, heterogeneous brain imaging datasets are increasingly required for the training, validation, and testing of advanced deep learning (DL)-based automated tools, including structural magnetic resonance (MR) image-based diagnostic and treatment monitoring approaches. When assembling a number of smaller datasets to form a larger dataset, understanding the underlying variability between different acquisition and processing protocols across the aggregated dataset (termed “batch effects”) is critical. The presence of variation in the training dataset is important as it more closely reflects the true underlying data distribution and, thus, may enhance the overall generalizability of the tool. However, the impact of batch effects must be carefully evaluated in order to avoid undesirable effects that, for example, may reduce performance measures. Batch effects can result from many sources, including differences in acquisition equipment, imaging technique and parameters, as well as applied processing methodologies. Their impact, both beneficial and adversarial, must be considered when developing tools to ensure that their outputs are related to the proposed clinical or research question (i.e., actual disease-related or pathological changes) and are not simply due to the peculiarities of underlying batch effects in the aggregated dataset. We reviewed applications of DL in structural brain MR imaging that aggregated images from neuroimaging datasets, typically acquired at multiple sites. We examined datasets containing both healthy control participants and patients that were acquired using varying acquisition protocols. First, we discussed issues around Data Access and enumerated the key characteristics of some commonly used publicly available brain datasets. Then we reviewed methods for correcting batch effects by exploring the two main classes of approaches: Data Harmonization that uses data standardization, quality control protocols or other similar algorithms and procedures to explicitly understand and minimize unwanted batch effects; and Domain Adaptation that develops DL tools that implicitly handle the batch effects by using approaches to achieve reliable and robust results. In this narrative review, we highlighted the advantages and disadvantages of both classes of DL approaches, and described key challenges to be addressed in future studies.

Amyotrophic lateral sclerosis (ALS) is a multisystem neurodegenerative disorder characterized by progressive degeneration of upper motor neurons and lower motor neurons, and frontotemporal regions resulting in impaired bulbar, limb, and cognitive function. Magnetic resonance imaging studies have reported cortical and subcortical brain involvement in the pathophysiology of ALS. The present study investigates the functional integrity of resting-state networks (RSNs) and their importance in ALS. Intra- and inter-network resting-state functional connectivity (Rs-FC) was examined using an independent component analysis approach in a large multi-center cohort. A total of 235 subjects (120 ALS patients; 115 healthy controls (HC) were recruited across North America through the Canadian ALS Neuroimaging Consortium (CALSNIC). Intra-network and inter-network Rs-FC was evaluated by the FSL-MELODIC and FSLNets software packages. As compared to HC, ALS patients displayed higher intra-network Rs-FC in the sensorimotor, default mode, right and left fronto-parietal, and orbitofrontal RSNs, and in previously undescribed networks including auditory, dorsal attention, basal ganglia, medial temporal, ventral streams, and cerebellum which negatively correlated with disease severity. Furthermore, ALS patients displayed higher inter-network Rs-FC between the orbitofrontal and basal ganglia RSNs which negatively correlated with cognitive impairment. In summary, in ALS there is an increase in intra- and inter-network functional connectivity of RSNs underpinning both motor and cognitive impairment. Moreover, the large multi-center CALSNIC dataset permitted the exploration of RSNs in unprecedented detail, revealing previously undescribed network involvement in ALS.

Abstract 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.

Background Cerebral amyloid angiopathy (CAA) causes cognitive decline, but it is not known whether it is associated with neuropsychiatric symptoms (NPS). Methods and Results Participants with CAA, mild cognitive impairment, mild dementia due to Alzheimer's disease, and normal cognition were recruited from stroke and dementia clinics and community advertising. NPS were captured using the Neuropsychiatric Inventory Questionnaire short form. The number and total severity (number multiplied by severity of each symptom [mild, moderate, or severe]) of NPS were analyzed using generalized linear regression with a negative binomial link and multiple linear regression, adjusting for age, sex, and education. A total of 109 participants (43 with CAA, 15 with Alzheimer's disease, 28 with mild cognitive impairment, and 23 with normal cognition) (mean age 71.1 [SD=7.6]; 53.2% male) were included. The most frequent NPS in CAA were depression/dysphoria (48.8%), irritability/lability (37.2%), agitation/aggression (37.2%), apathy/indifference (34.9%), and anxiety (32.6%). In adjusted models, patients with CAA had 3.2 times (95% CI, 1.7–6.0) more NPS symptoms and 3.1 units (95% CI, 1.0–5.1) higher expected severity score. The number of NPS was similar to patients with mild cognitive impairment (3.2 times higher than controls) but less than in patients with Alzheimer's disease dementia (4.1 times higher than controls). Within patients with CAA, there were 1.20 times (95% CI, 1.01–1.32) more NPS per 1% increase in white matter hyperintensity as a percentage of intracranial volume. Conclusions NPS are common in CAA, with a similar prevalence as in mild cognitive impairment. The association of the total number of NPS with higher white matter hyperintensity volume suggests that white matter damage may underlie some of these symptoms.

Introduction: Transient ischemic attack (TIA) and minor ischemic stroke (IS) is associated with a increased risk of late life dementia. In this study we aim to study the extent to which the rates of hippocampal atrophy in TIA/IS differ from healthy controls, and how they are correlated to neuropsychological measurements. Methods: TIA or minor stroke patients were tested with a neuropsychological battery including tests of executive function, and verbal and non-verbal memory at three time points out to 3 years. Annualized rates of hippocampal atrophy in TIA/IS patients were compared to controls. A linear-mixed regression model was used to assess the difference in rates of hippocampal atrophy after adjusting for time and demographic characteristics. Results: TIA/IS patients demonstrated a higher hippocampal atrophy rate than healthy controls over a 3-year interval: the annual percentage change of the left hippocampal volume was 2.5% (78 mm3 per year (SD 60)) for TIA/IS patients compared to 0.9% (29 mm3 per year (SD 32)) for controls (p

Introduction Cerebral small vessel disease (cSVD) accounts for 20%–25% of strokes and is the most common cause of vascular cognitive impairment (VCI). In an animal VCI model, inducing brief periods of limb ischaemia-reperfusion reduces subsequent ischaemic brain injury with remote and local protective effects, with hindlimb remote ischaemic conditioning (RIC) improving cerebral blood flow, decreasing white-matter injury and improving cognition. Small human trials suggest RIC is safe and may prevent recurrent strokes. It remains unclear what doses of chronic daily RIC are tolerable and safe, whether effects persist after treatment cessation, and what parameters are optimal for treatment response.Methods and analysis This prospective, open-label, randomised controlled trial (RCT) with blinded end point assessment and run-in period, will recruit 24 participants, randomised to one of two RIC intensity groups: one arm treated once daily or one arm twice daily for 30 consecutive days. RIC will consistent of 4 cycles of blood pressure cuff inflation to 200 mm Hg for 5 min followed by 5 min deflation (total 35 min). Selection criteria include: age 60–85 years, evidence of cSVD on brain CT/MRI, Montreal Cognitive Assessment (MoCA) score 13–24 and preserved basic activities of living. Outcomes will be assessed at 30 days and 90 days (60 days after ceasing treatment). The primary outcome is adherence (completing ≥80% of sessions). Secondary safety/tolerability outcomes include the per cent of sessions completed and pain/discomfort scores from patient diaries. Efficacy outcomes include changes in cerebral blood flow (per arterial spin-label MRI), white-matter hyperintensity volume, diffusion tensor imaging, MoCA and Trail-Making tests.Ethics and dissemination Research Ethics Board approval has been obtained. The results will provide information on feasibility, dose, adherence, tolerability and outcome measures that will help design a phase IIb RCT of RIC, with the potential to prevent VCI. Results will be disseminated through peer-reviewed publications, organisations and meetings.Trial registration number NCT04109963.

Amyotrophic lateral sclerosis (ALS) is characterized primarily by motor neuron but also frontotemporal lobar degeneration. Although the cerebellum is involved in both motor and cognitive functions, little is known of its role in ALS. We targeted the dentate nucleus (DN) in the cerebellum and the associated white matter fibers tracts connecting the DN to the rest of the brain using multimodal imaging techniques to examine the cerebellar structural and functional connectivity patterns in ALS patients and hypothesized that the DN is implicated in the pathophysiology of ALS. A cohort of 127 participants (56 healthy subjects (HS); 71 ALS patients) were recruited across Canada through the Canadian ALS Neuroimaging Consortium (CALSNIC). Resting state functional MRI, diffusion tensor imaging (DTI), and 3D weighted T1 structural images were acquired on a 3-tesla scanner. The DN in the cerebellum was used as a seed to evaluate the whole brain cerebral resting-state functional connectivity (rsFC). The superior cerebellar peduncle (SCP), middle cerebellar peduncle (MCP) and inferior cerebellar peduncle (ICP) were used as a region of interest in DTI to evaluate the structural integrity of the DN with the cortex and brain stem. Cerebellar volumetric analysis was done to examine the lobular and DN grey matter (GM) changes in ALS patients. Lastly, an association between DN rsFC and structural alterations were explored. DN rsFC was reduced with cerebrum (supplementary motor area, precentral gyrus, frontal, posterior parietal, temporal), lobule IV, and brain stem, and increased with parieto-occipital region. DN rsFC and white matter (WM) diffusivity alterations at SCP, MCP, and ICP were accompanied by correlations with ALSFRS-R. There were no DN volumetric changes. Notably, DN rsFC correlated with WM abnormalities at superior cerebellar peduncle. The DN plays a pathophysiological role in ALS. Impaired rsFC is likely due to the observed cerebellar peduncular WM damage given the lack of GM atrophy of the DN. This study demonstrates altered cerebellar rsFC connectivity with motor and extra-motor regions in ALS, and impaired rsFC is likely due to the observed cerebellar peduncular WM damage given the lack of GM atrophy of the DN. The correlation between the altered DN connectivity, and the behavioral data support the hypothesis that the DN plays a pathophysiological role in ALS.

Background and purposePatients with transient ischemic attack (TIA) show evidence of cognitive impairment but the reason is not clear. Measurement of microstructural changes in white matter (WM) using diffusion tensor imaging (DTI) may be a useful outcome measure. We report WM changes using DTI and the relationship with neuropsychological performance in a cohort of transient ischemic attack (TIA) and non-TIA subjects.MethodsNinety-five TIA subjects and 51 non-TIA subjects were assessed using DTI and neuropsychological batteries. Fractional anisotropy (FA) and mean diffusivity (MD) maps were generated and measurements were collected from WM tracts. Adjusted mixed effects regression modelled the relationship between groups and DTI metrics.ResultsTransient ischemic attack subjects had a mean age of 67.9 ± 9.4 years, and non-TIA subjects had a mean age 64.9 ± 9.9 years. The TIA group exhibited higher MD values in the fornix (0.36 units, P < 0.001) and lower FA in the superior longitudinal fasciculus (SLF) (-0.29 units, P = 0.001), genu (-0.22 units, P = 0.016), and uncinate fasciculus (UF) (-0.26 units, P = 0.004). Compared to non-TIA subjects, subjects with TIA scored lower on the Addenbrooke's Cognitive Assessment-Revised (median score 95 vs 91, P = 0.01) but showed no differences in scores on the Montreal Cognitive Assessment (median 27 vs 26) or the Mini-Mental State Examination (median 30). TIA subjects had lower scores in memory (median 44 vs 52, P < 0.01) and processing speed (median 45 vs 62, P < 0.01) but not executive function, when compared to non-TIA subjects. Lower FA and higher MD in the fornix, SLF, and UF were associated with poorer performance on tests of visual memory and executive function but not verbal memory. Lower FA in the UF and fornix were related to higher timed scores on the TMT-B (P < 0.01), and higher SLF MD was related to higher scores on TMT-B (P < 0.01), confirming worse executive performance in the TIA group.ConclusionsDTI scans may be useful for detecting microstructural disease in TIA subjects before cognitive symptoms develop. DTI parameters, white matter hyperintensities, and vascular risk factors underly some of the altered neuropsychological measures in TIA subjects.

Objectives: To test the hypotheses that peak skeletonized mean diffusivity (PSMD), a measure of cerebral white matter microstructural disruption, is 1) increased in patients with cerebral amyloid angiopathy (CAA) compared to normal control (NC), mild cognitive impairment (MCI), and Alzheimer’s disease (AD); 2) associated with neuropsychological test performance among CAA patients; and 3) increased more quickly over one year in CAA than in AD, MCI, and NC. Methods: Ninety-two participants provided a medical history, completed a neuropsychological assessment, and had a magnetic resonance (MR) exam including diffusion tensor imaging (DTI) from which PSMD was calculated. A 75-minute neuropsychological test battery was used to derive domain scores for memory, executive function, and processing speed. Multivariable analyses controlling for age and sex (and education, for cognitive outcomes) were used to test the study hypotheses. Results: PSMD was higher in the CAA group (mean 4.97 × 10−4 mm2/s) compared to NC (3.25 × 10−4 mm2/s), MCI (3.62 × 10−4 mm2/s) and AD (3.89 × 10−4 mm2/s) groups (p

Abstract Background Late-life cognitive decline, caused by progressive neuronal loss leading to brain atrophy years before symptoms are detected, is expected to double in Canada over the next two decades. Cognitive impairment in late life is attributed to vascular and lifestyle related risk factors in mid-life in a substantial proportion of cases (50%), thereby providing an opportunity for effective prevention of cognitive decline if incipient disease is detected earlier. Patients presenting with transient ischemic attack (TIA) commonly display some degree of cognitive impairment and are at a 4-fold increased risk of dementia. In the Predementia Neuroimaging of Transient Ischemic Attack (PREVENT) study, we will address what disease processes (i.e., Alzheimer’s vs. vascular disease) lead to neurodegeneration, brain atrophy, and cognitive decline, and whether imaging measurements of brain iron accumulation using quantitative susceptibility mapping predicts subsequent brain atrophy and cognitive decline. Methods A total of 440 subjects will be recruited for this study with 220 healthy subjects and 220 TIA patients. Early Alzheimer’s pathology will be determined by cerebrospinal fluid samples (including tau, a marker of neuronal injury, and amyloid β1–42) and by MR measurements of iron accumulation, a marker for Alzheimer’s-related neurodegeneration. Small vessel disease will be identified by changes in white matter lesion volume. Predictors of advanced rates of cerebral and hippocampal atrophy at 1 and 3 years will include in vivo Alzheimer’s disease pathology markers, and MRI measurements of brain iron accumulation and small vessel disease. Clinical and cognitive function will be assessed annually post-baseline for a period of 5-years using a clinical questionnaire and a battery of neuropsychological tests, respectively. Discussion The PREVENT study expects to demonstrate that TIA patients have increased early progressive rates of cerebral brain atrophy after TIA, before cognitive decline can be clinically detected. By developing and optimizing high-level machine learning models based on clinical data, image-based (quantitative susceptibility mapping, regional brain, and white matter lesion volumes) features, and cerebrospinal fluid biomarkers, PREVENT will provide a timely opportunity to identify individuals at greatest risk of late-life cognitive decline early in the course of disease, supporting future therapeutic strategies for the promotion of healthy aging.

Introduction: Patients with transient ischemic attack (TIA) and minor stroke demonstrate cognitive impairment, and a four-fold risk of late-life dementia.Aim: To study the extent to which the rates of brain volume loss in TIA patients differ from healthy controls and how they are correlated with cognitive impairment.Methods: TIA or minor stroke patients were tested with a neuropsychological battery and underwent T1 weighted volumetric magnetic resonance imaging scans at fixed intervals over a 3 years period. Linear mixed effects regression models were used to compare brain atrophy rates between groups, and to determine the relationship between atrophy rates and cognitive function in TIA and minor stroke patients.Results: Whole brain atrophy rates were calculated for the TIA and minor stroke patients; n = 38 between 24 h and 18 months, and n = 68 participants between 18 and 36 months, and were compared to healthy controls. TIA and minor stroke patients demonstrated a significantly higher whole brain atrophy rate than healthy controls over a 3 years interval (p = 0.043). Diabetes (p = 0.012) independently predicted higher atrophy rate across groups. There was a relationship between higher rates of brain atrophy and processing speed (composite P = 0.047 and digit symbol coding P = 0.02), but there was no relationship with brain atrophy rates and memory or executive composite scores or individual cognitive tests for language (Boston naming, memory recall, verbal fluency or Trails A or B score).Conclusion: TIA and minor stroke patients experience a significantly higher rate of whole brain atrophy. In this cohort of TIA and minor stroke patients changes in brain volume over time precede cognitive decline.

Lower blood oxygenation level dependent (BOLD) signal changes in response to a visual stimulus in functional magnetic resonance imaging (fMRI) have been observed in cross-sectional studies of cerebral amyloid angiopathy (CAA), and are presumed to reflect impaired vascular reactivity. We used fMRI to detect a longitudinal change in BOLD responses to a visual stimulus in CAA, and to determine any correlations between these changes and other established biomarkers of CAA progression. Data were acquired from 22 patients diagnosed with probable CAA (using the Boston Criteria) and 16 healthy controls at baseline and one year. BOLD data were generated from the 200 most active voxels of the primary visual cortex during the fMRI visual stimulus (passively viewing an alternating checkerboard pattern). In general, BOLD amplitudes were lower at one year compared to baseline in patients with CAA (p = 0.01) but were unchanged in controls (p = 0.18). The longitudinal difference in BOLD amplitudes was significantly lower in CAA compared to controls (p

Purpose: We aim to characterize infarct volume evolution within the first month post-ischemic stroke and to determine the effect of recanalization status on early infarct volume estimation. Methods: Ischemic stroke patients recruited for the MONITOR and VISION studies were retrospectively screened and patients who had infarcts on diffusion-weighted imaging (DWI) at baseline and had at least two follow-up MR scans (n = 56) were included. Pre-defined target imaging time points, obtained on a 3-T MR scanner, were 12 hours (h), 24 h, 7 days, and ≥30 days post-stroke. Infarct tissue was manually traced blinded to the images at the other time points. Infarct expansion index was calculated by dividing infarct volume at each follow-up time point by the baseline DWI infarct volume. Recanalization was assessed within 24 h post-stroke. Correlation and statistical comparison analysis were done using the Spearman, Mann–Whitney, and Kruskal–Wallis tests. Results: Follow-up infarct volumes were positively correlated with the baseline infarct volume (ρ > 0.81; p

Structural connectivity (SC) of white matter (WM) and functional connectivity (FC) of cortical regions undergo changes in normal aging. As WM tracts form the underlying anatomical architecture that connects regions within resting state networks (RSNs), it is intuitive to expect that SC and FC changes with age are correlated. Studies that investigated the relationship between SC and FC in normal aging are rare, and have mainly compared between groups of elderly and younger subjects. The objectives of this work were to investigate linear SC and FC changes across the healthy adult lifespan, and to define relationships between SC and FC measures within seven whole-brain large scale RSNs. Diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI) data were acquired from 177 healthy participants (male/female = 69/108; aged 18–87 years). Forty cortical regions across both hemispheres belonging to seven template-defined RSNs were considered. Mean diffusivity (MD), fractional anisotropy (FA), mean tract length, and number of streamlines derived from DTI data were used as SC measures, delineated using deterministic tractography, within each RSN. Pearson correlation coefficients of rs-fMRI-obtained BOLD signal time courses between cortical regions were used as FC measure. SC demonstrated significant age-related changes in all RSNs (decreased FA, mean tract length, number of streamlines; and increased MD), and significant FC decrease was observed in five out of seven networks. Among the networks that showed both significant age related changes in SC and FC, however, SC was not in general significantly correlated with FC, whether controlling for age or not. The lack of observed relationship between SC and FC suggests that measures derived from DTI data that are commonly used to infer the integrity of WM microstructure are not related to the corresponding changes in FC within RSNs. The possible temporal lag between SC and FC will need to be addressed in future longitudinal studies to better elucidate the links between SC and FC changes in normal aging.

PURPOSE:Volume flow rate (VFR) measurements based on phase contrast (PC)-magnetic resonance (MR) imaging datasets have spatially varying bias due to eddy current induced phase errors. The purpose of this study was to assess the impact of phase errors in time averaged PC-MR imaging of the cerebral vasculature and explore the effects of three common correction schemes (local bias correction (LBC), local polynomial correction (LPC), and whole brain polynomial correction (WBPC)). METHODS:Measurements of the eddy current induced phase error from a static phantom were first obtained. In thirty healthy human subjects, the methods were then assessed in background tissue to determine if local phase offsets could be removed. Finally, the techniques were used to correct VFR measurements in cerebral vessels and compared statistically. RESULTS:In the phantom, phase error was measured to be

To determine the initial feasibility of using magnetic resonance (MR) imaging to detect early atherosclerosis, we investigated inflammatory cells labeled with a positive contrast agent in an endothelial cell–based testing system. The human monocytic cell line THP-1 was labeled by overnight incubation with a gadolinium colloid (Gado CELLTrack) prior to determination of the in vitro release profile from T1-weighted MR images. Next, MR signals arising from both a synthetic model of THP-1/human umbilical vein endothelial cell (HUVEC) accumulation and the dynamic adhesion of THP-1 cells to activated HUVECs under flow were obtained. THP-1 cells were found to be successfully—but not optimally—labeled with gadolinium colloid, and MR images demonstrated increased signal from labeled cells in both the synthetic and dynamic THP-1/HUVEC models. The observed THP-1 contrast release profile was rapid, suggesting the need for an agent that is optimized for retention in the target cells for use in further studies. Detection of labeled THP-1 cells was accomplished with no signal enhancement from unlabeled cells. These achievements demonstrate the feasibility of targeting early atherosclerosis with MR imaging, and suggest that using an in vitro system like the one described provides a rapid, efficient, and cost-effective way to support the development and evaluation of novel MR contrast agents.

Many risk factors have been proposed in the development of the cerebral aneurysms. Hemodynamics including blood velocity, volume flow rate (VFR), and intravascular pressure are thought to be prognostic indicators of aneurysm development. We hypothesize that treatment of cerebral aneurysm using a flow-diverting stent will bring these hemodynamic parameters closer to those observed on the contralateral side. In the current study, a patient with a giant cerebral aneurysm was studied pre- and postoperatively using phase contrast MRI (PC-MRI) to measure the hemodynamic changes resulting from the deployment of a flow-diverting stent. PC-MRI was used to calculate intravascular pressure, which was compared to more invasive endovascular catheter-derived measurements. After stent placement, the measured VFRs in vessels of the treated hemisphere approached those measured on the contralateral side, and flow symmetry changed from a laterality index of -0.153 to 0.116 in the middle cerebral artery. Pressure estimates derived from the PC-MRI velocity data had an average difference of 6.1% as compared to invasive catheter transducer measurements. PC-MRI can measure the hemodynamic parameters with the same accuracy as invasive methods pre- and postoperatively.

Consideration of information from multiple modalities has been shown to have increased diagnostic power in breast imaging. As a result, new techniques such as microwave imaging continue to be developed. Interpreting these novel image modalities is a challenge, requiring comparison to established techniques such as the gold standard X-ray mammography. However, due to the highly deformable nature of breast tissues, comparison of 3D and 2D modalities is a challenge. To enable this comparison, a registration technique was developed to map features from 2D mammograms to locations in the 3D image space. This technique was developed and tested using magnetic resonance (MR) images as a reference 3D modality, as MR breast imaging is an established technique in clinical practice. The algorithm was validated using a numerical phantom then successfully tested on twenty-four image pairs. Dice's coefficient was used to measure the external goodness of fit, resulting in an excellent overall average of 0.94. Internal agreement was evaluated by examining internal features in consultation with a radiologist, and subjective assessment concludes that reasonable alignment was achieved.

Current clinical breast imaging modalities include ultrasound, magnetic resonance (MR) imaging, and the ubiquitous X-ray mammography. Microwave imaging, which takes advantage of differing electromagnetic properties to obtain image contrast, shows potential as a complementary imaging technique. As an emerging modality, interpretation of 3D microwave images poses a significant challenge. MR images are often used to assist in this task, and X-ray mammograms are readily available. However, X-ray mammograms provide 2D images of a breast under compression, resulting in significant geometric distortion. This paper presents a method to estimate the 3D shape of the breast and locations of regions of interest from standard clinical mammograms. The technique was developed using MR images as the reference 3D shape with the future intention of using microwave images. Twelve breast shapes were estimated and compared to ground truth MR images, resulting in a skin surface estimation accurate to within an average Euclidean distance of 10 mm. The 3D locations of regions of interest were estimated to be within the same clinical area of the breast as corresponding regions seen on MR imaging. These results encourage investigation into the use of mammography as a source of information to assist with microwave image interpretation as well as validation of microwave imaging techniques.