Publications by authors named "Richard Frayne"

135 Publications

Functional alterations in large-scale resting-state networks of amyotrophic lateral sclerosis: A multi-site study across Canada and the United States.

PLoS One 2022 16;17(6):e0269154. Epub 2022 Jun 16.

University of Alberta, Edmonton, Alberta, Canada.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0269154PLOS
June 2022

Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads.

NMR Biomed 2022 Jun 15:e4788. Epub 2022 Jun 15.

Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada.

Iron concentration in the human brain plays a crucial role in several neurodegenerative diseases and can be monitored noninvasively using quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R *) mapping from multiecho T *-weighted images. Large population studies enable better understanding of pathologies and can benefit from pooling multisite data. However, reproducibility may be compromised between sites and studies using different hardware and sequence protocols. This work investigates QSM and R * reproducibility at 3 T using locally optimized sequences from three centers and two vendors, and investigates possible reduction of cross-site variability through postprocessing approaches. Twenty-four healthy subjects traveled between three sites and were scanned twice at each site. Scan-rescan measurements from seven deep gray matter regions were used for assessing within-site and cross-site reproducibility using intraclass correlation coefficient (ICC) and within-subject standard deviation (SDw) measures. In addition, multiple QSM and R * postprocessing options were investigated with the aim to minimize cross-site sequence-related variations, including: mask generation approach, echo-timing selection, harmonizing spatial resolution, field map estimation, susceptibility inversion method, and linear field correction for magnitude images. The same-subject cross-site region of interest measurements for QSM and R * were highly correlated (R  ≥ 0.94) and reproducible (mean ICC of 0.89 and 0.82 for QSM and R *, respectively). The mean cross-site SDw was 4.16 parts per billion (ppb) for QSM and 1.27 s for R *. For within-site measurements of QSM and R *, the mean ICC was 0.97 and 0.87 and mean SDw was 2.36 ppb and 0.97 s , respectively. The precision level is regionally dependent and is reduced in the frontal lobe, near brain edges, and in white matter regions. Cross-site QSM variability (mean SDw) was reduced up to 46% through postprocessing approaches, such as masking out less reliable regions, matching available echo timings and spatial resolution, avoiding the use of the nonconsistent magnitude contrast between scans in field estimation, and minimizing streaking artifacts.
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http://dx.doi.org/10.1002/nbm.4788DOI Listing
June 2022

Lifespan Volume Trajectories From Non-harmonized T1-Weighted MRI Do Not Differ After Site Correction Based on Traveling Human Phantoms.

Front Neurol 2022 9;13:826564. Epub 2022 May 9.

Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada.

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.
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http://dx.doi.org/10.3389/fneur.2022.826564DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9124864PMC
May 2022

Cerebrovascular Reactivity Across the Entire Brain in Cerebral Amyloid Angiopathy.

Neurology 2022 04 24;98(17):e1716-e1728. Epub 2022 Feb 24.

From the Department of Clinical Neurosciences (A.E.B., C.R.M., B.S., A.S., A.M.Z., E.C., A.C., R.F., Z.I., G.B.P., E.E.S.), Hotchkiss Brain Institute (A.E.B., C.R.M., E.L.M., B.S., A.S., A.M.Z., E.C., A.C., R.F., Z.I., G.B.P., E.E.S.), Department of Radiology (C.R.M., E.L.M., R.F., G.B.P., E.E.S.), Department of Psychiatry (Z.I.), and Mathison Centre for Mental Health Research & Education (Z.I.), University of Calgary; Seaman Family MR Research Centre, Foothills Medical Centre (C.R.M., R.F., G.B.P., E.E.S.), Alberta Health Services, Calgary; Department of Psychology (E.L.M.), St. Francis Xavier University, Antigonish; and Division of Neurology and Department of Medicine (M.G., K.N., G.C.J., R.C.), Department of Biomedical Engineering (C.B.), and Neuroscience and Mental Health Institute (R.C.), University of Alberta, Edmonton, Canada.

Background And Objectives: Reduced cerebrovascular reactivity is proposed to be a feature of cerebral amyloid angiopathy (CAA) but has not been measured directly. Employing a global vasodilatory stimulus (hypercapnia), this study assessed the relationships between cerebrovascular reactivity and MRI markers of CAA and cognitive function.

Methods: In a cross-sectional study, individuals with probable CAA, mild cognitive impairment, or dementia due to Alzheimer disease and healthy controls underwent neuropsychological testing and an MRI that included a 5% carbon dioxide challenge. Cerebrovascular reactivity was compared across groups controlling for age, sex, and the presence of hypertension, and its associations with MRI markers of CAA in participants with CAA and with cognition across all participants were determined using multivariable linear regression adjusting for group, age, sex, education, and the presence of hypertension.

Results: Cerebrovascular reactivity data (mean ± SD) were available for 26 participants with CAA (9 female; 74.4 ± 7.7 years), 19 participants with mild cognitive impairment (5 female; 72.1 ± 8.5 years), 12 participants with dementia due to Alzheimer disease (4 female; 69.4 ± 6.6 years), and 39 healthy controls (30 female; 68.8 ± 5.4 years). Gray and whiter matter reactivity averaged across the entire brain was lower in participants with CAA and Alzheimer disease dementia compared to healthy controls, with a predominantly posterior distribution of lower reactivity in both groups. Higher white matter hyperintensity volume was associated with lower white matter reactivity (standardized coefficient [β], 95% CI -0.48, -0.90 to -0.01). Higher gray matter reactivity was associated with better global cognitive function (β 0.19, 0.03-0.36), memory (β 0.21, 0.07-0.36), executive function (β 0.20, 0.02-0.39), and processing speed (β 0.27, 0.10-0.45) and higher white matter reactivity was associated with higher memory (β 0.22, 0.08-0.36) and processing speed (β 0.23, 0.06-0.40).

Conclusions: Reduced cerebrovascular reactivity is a core feature of CAA and its assessment may provide an additional biomarker for disease severity and cognitive impairment.
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http://dx.doi.org/10.1212/WNL.0000000000200136DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9071369PMC
April 2022

Deep Learning in Large and Multi-Site Structural Brain MR Imaging Datasets.

Front Neuroinform 2021 20;15:805669. Epub 2022 Jan 20.

Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.

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 (., 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 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: that uses data standardization, quality control protocols or other similar algorithms and procedures to understand and minimize unwanted batch effects; and that develops DL tools that 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.
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http://dx.doi.org/10.3389/fninf.2021.805669DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8811356PMC
January 2022

Distinct patterns of progressive gray and white matter degeneration in amyotrophic lateral sclerosis.

Hum Brain Mapp 2022 04 15;43(5):1519-1534. Epub 2021 Dec 15.

Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.

Progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) remains poorly understood. Here, three-dimensional (3D) texture analysis was used to study longitudinal gray and white matter cerebral degeneration in ALS from routine T1-weighted magnetic resonance imaging (MRI). Participants were included from the Canadian ALS Neuroimaging Consortium (CALSNIC) who underwent up to three clinical assessments and MRI at four-month intervals, up to 8 months after baseline (T ). Three-dimensional maps of the texture feature autocorrelation were computed from T1-weighted images. One hundred and nineteen controls and 137 ALS patients were included, with 81 controls and 84 ALS patients returning for at least one follow-up. At baseline, texture changes in ALS patients were detected in the motor cortex, corticospinal tract, insular cortex, and bilateral frontal and temporal white matter compared to controls. Longitudinal comparison of texture maps between T and T (last follow-up visit) within ALS patients showed progressive texture alterations in the temporal white matter, insula, and internal capsule. Additionally, when compared to controls, ALS patients had greater texture changes in the frontal and temporal structures at T than at T . In subgroup analysis, slow progressing ALS patients had greater progressive texture change in the internal capsule than the fast progressing patients. Contrastingly, fast progressing patients had greater progressive texture changes in the precentral gyrus. These findings suggest that the characteristic longitudinal gray matter pathology in ALS is the progressive involvement of frontotemporal regions rather than a worsening pathology within the motor cortex, and that phenotypic variability is associated with distinct progressive spatial pathology.
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http://dx.doi.org/10.1002/hbm.25738DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8886653PMC
April 2022

Cerebral Amyloid Angiopathy Is Associated With Emotional Dysregulation, Impulse Dyscontrol, and Apathy.

J Am Heart Assoc 2021 11 10;10(22):e022089. Epub 2021 Nov 10.

Department of Clinical Neurosciences University of Calgary Alberta Canada.

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.
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http://dx.doi.org/10.1161/JAHA.121.022089DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751932PMC
November 2021

Extraction of a vascular function for a fully automated dynamic contrast-enhanced magnetic resonance brain image processing pipeline.

Magn Reson Med 2022 03 27;87(3):1561-1573. Epub 2021 Oct 27.

Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.

Purpose: To develop a deep-learning model that leverages the spatial and temporal information from dynamic contrast-enhanced magnetic resonance (DCE MR) brain imaging in order to automatically estimate a vascular function (VF) for quantitative pharmacokinetic (PK) modeling.

Methods: Patients with glioblastoma multiforme were scanned post-resection approximately every 2 months using a high spatial and temporal resolution DCE MR imaging sequence ( s and cm ). A region over the transverse sinus was manually drawn in the dynamic T1-weighted images to provide a ground truth VF. The manual regions and their resulting VF curves were used to train a deep-learning model based on a 3D U-net architecture. The model concurrently utilized the spatial and temporal information in DCE MR images to predict the VF. In order to analyze the contribution of the spatial and temporal terms, different weighted combinations were examined. The manual and deep-learning predicted regions and VF curves were compared.

Results: Forty-three patients were enrolled in this study and 155 DCE MR scans were processed. The 3D U-net was trained using a loss function that combined the spatial and temporal information with different weightings. The best VF curves were obtained when both spatial and temporal information were considered. The predicted VF curve was similar to the manual ground truth VF curves.

Conclusion: The use of spatial and temporal information improved VF curve prediction relative to when only the spatial information is used. The method generalized well for unseen data and can be used to automatically estimate a VF curve suitable for quantitative PK modeling. This method allows for a more efficient clinical pipeline and may improve automation of permeability mapping.
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http://dx.doi.org/10.1002/mrm.29054DOI Listing
March 2022

Progressive Neurochemical Abnormalities in Cognitive and Motor Subgroups of Amyotrophic Lateral Sclerosis: A Prospective Multicenter Study.

Neurology 2021 08 14;97(8):e803-e813. Epub 2021 Jun 14.

From the Neuroscience and Mental Health Institute (D.T., A.I., O.S., S.K.), Department of Biomedical Engineering (C.H., P.S.), School of Public Health (D.T.E.), and Division of Neurology (C.L., S.K.), University of Alberta, Edmonton; Division of Neurology (H.B.), University of British Columbia, Vancouver; Seaman Family MR Centre (R.F.) and Hotchkiss Brain Institute (R.F., L.K.), University of Calgary, Alberta; Montreal Neurological Institute (A.L.G.), McGill University, Quebec; and Sunnybrook Health Sciences Centre (S.J.G., L.Z.), University of Toronto, Ontario, Canada.

Objective: To evaluate progressive cerebral degeneration in amyotrophic lateral sclerosis (ALS) by assessing alterations in -acetylaspartate (NAA) ratios in the motor and prefrontal cortex within clinical subgroups of ALS.

Methods: Seventy-six patients with ALS and 59 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium. Participants underwent serial clinical evaluations and magnetic resonance spectroscopy at baseline and 4 and 8 months using a harmonized protocol across 5 centers. NAA ratios were quantified in the motor cortex and prefrontal cortex. Patients were stratified into subgroups based on disease progression rate, upper motor neuron (UMN) signs, and cognitive status. Linear mixed models were used for baseline and longitudinal comparisons of NAA metabolite ratios.

Results: Patients with ALS had reduced NAA ratios in the motor cortex at baseline ( < 0.001). Ratios were lower in those with more rapid disease progression and greater UMN signs ( < 0.05). A longitudinal decline in NAA ratios was observed in the motor cortex in the rapidly progressing ( < 0.01) and high UMN burden ( < 0.01) cohorts. The severity of UMN signs did not change significantly over time. NAA ratios were reduced in the prefrontal cortex only in cognitively impaired patients ( < 0.05; prefrontal cortex metabolites did not change over time.

Conclusions: Progressive degeneration of the motor cortex in ALS is associated with more aggressive clinical presentations. These findings provide biological evidence of variable spatial and temporal cerebral degeneration linked to the disease heterogeneity of ALS. The use of standardized imaging protocols may have a role in clinical trials for patient selection or subgrouping.

Classification Of Evidence: This study provides Class II evidence that MRS NAA metabolite ratios of the motor cortex are associated with more rapid disease progression and greater UMN signs in patients with ALS.

Trial Registration Information: ClinicalTrials.gov Identifier: NCT02405182.
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http://dx.doi.org/10.1212/WNL.0000000000012367DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397589PMC
August 2021

Pseudo Test-Retest Evaluation of Millimeter-Resolution Whole-Brain Dynamic Contrast-enhanced MRI in Patients with High-Grade Glioma.

Radiology 2021 08 8;300(2):410-420. Epub 2021 Jun 8.

From the Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, 3740 McClintock Ave, EEB 400, Los Angeles, CA 90089-2564 (Y.B., K.S.N.); GE Healthcare, Calgary, Canada (R.M.L.); Department of Radiology, University of Calgary, Calgary, Canada (R.M.L.); Seaman Family MR Research Centre, Foothills Hospital, Calgary, Canada (R.M.L., R.F.); Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, Calif (J.A., K.S.N.); and Departments of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada (R.F.).

Background Advances in sub-Nyquist-sampled dynamic contrast-enhanced (DCE) MRI enable monitoring of brain tumors with millimeter resolution and whole-brain coverage. Such undersampled quantitative methods need careful characterization regarding achievable test-retest reproducibility. Purpose To demonstrate a fully automated high-resolution whole-brain DCE MRI pipeline with 30-fold sparse undersampling and estimate its reproducibility on the basis of reference regions of stable tissue types during multiple posttreatment time points by using longitudinal clinical images of high-grade glioma. Materials and Methods Two methods for sub-Nyquist-sampled DCE MRI were extended with automatic estimation of vascular input functions. Continuously acquired three-dimensional k-space data with ramped-up flip angles were partitioned to yield high-resolution, whole-brain tracer kinetic parameter maps with matched precontrast-agent T1 and M maps. Reproducibility was estimated in a retrospective study in participants with high-grade glioma, who underwent three consecutive standard-of-care examinations between December 2016 and April 2019. Coefficients of variation and reproducibility coefficients were reported for histogram statistics of the tracer kinetic parameters plasma volume fraction and volume transfer constant (K) on five healthy tissue types. Results The images from 13 participants (mean age ± standard deviation, 61 years ± 10; nine women) with high-grade glioma were evaluated. In healthy tissues, the protocol achieved a coefficient of variation less than 57% for median K, if K was estimated consecutively. The maximum reproducibility coefficient for median K was estimated to be at 0.06 min for large or low-enhancing tissues and to be as high as 0.48 min in smaller or strongly enhancing tissues. Conclusion A fully automated, sparsely sampled DCE MRI reconstruction with patient-specific vascular input function offered high spatial and temporal resolution and whole-brain coverage; in healthy tissues, the protocol estimated median volume transfer constant with maximum reproducibility coefficient of 0.06 min in large, low-enhancing tissue regions and maximum reproducibility coefficient of less than 0.48 min in smaller or more strongly enhancing tissue regions. Published under a CC BY 4.0 license. See also the editorial by Lenkinski in this issue.
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http://dx.doi.org/10.1148/radiol.2021203628DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328086PMC
August 2021

Sparse precontrast T mapping for high-resolution whole-brain DCE-MRI.

Magn Reson Med 2021 10 25;86(4):2234-2249. Epub 2021 May 25.

Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA.

Purpose: To develop and evaluate an efficient precontrast T mapping technique suitable for quantitative high-resolution whole-brain dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI).

Methods: Variable flip angle (VFA) T mapping was considered that provides 1 × 1 × 2 mm resolution to match a recent high-resolution whole-brain DCE-MRI protocol. Seven FAs were logarithmically spaced from 1.5° to 15°. T and M maps were estimated using model-based reconstruction. This approach was evaluated using an anatomically realistic brain tumor digital reference object (DRO) with noise-mimicking 3T neuroimaging and fully sampled data acquired from one healthy volunteer. Methods were also applied on fourfold prospectively undersampled VFA data from 13 patients with high-grade gliomas.

Results: T -mapping precision decreased with undersampling factor R, althoughwhereas bias remained small before a critical R. In the noiseless DRO, T bias was <25 ms in white matter (WM) and <11 ms in brain tumor (BT). T standard deviation (SD) was <119.5 ms in WM (coefficient of variation [COV] ~11.0%) and <253.2 ms in BT (COV ~12.7%). In the noisy DRO, T bias was <50 ms in WM and <30 ms in BT. For R ≤ 10, T SD was <107.1 ms in WM (COV ~9.9%) and <240.9 ms in BT (COV ~12.1%). In the healthy subject, T bias was <30 ms for R ≤ 16. At R = 4, T SD was 171.4 ms (COV ~13.0%). In the prospective brain tumor study, T values were consistent with literature values in WM and BT.

Conclusion: High-resolution whole-brain VFA T mapping is feasible with sparse sampling, supporting its use for quantitative DCE-MRI.
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http://dx.doi.org/10.1002/mrm.28849DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8362109PMC
October 2021

Cerebral atrophy in amyotrophic lateral sclerosis parallels the pathological distribution of TDP43.

Brain Commun 2020 15;2(2):fcaa061. Epub 2020 May 15.

Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta T6G 2E1, Canada.

Amyotrophic lateral sclerosis is a neurodegenerative disease characterized by a preferential involvement of both upper and lower motor neurons. Evidence from neuroimaging and post-mortem studies confirms additional involvement of brain regions extending beyond the motor cortex. The aim of this study was to assess the extent of cerebral disease in amyotrophic lateral sclerosis cross-sectionally and longitudinally and to compare the findings with a recently proposed disease-staging model of amyotrophic lateral sclerosis pathology. Deformation-based morphometry was used to identify the patterns of brain atrophy associated with amyotrophic lateral sclerosis and to assess their relationship with clinical symptoms. Longitudinal T-weighted MRI data and clinical measures were acquired at baseline, 4 months and 8 months, from 66 patients and 43 age-matched controls who participated in the Canadian Amyotrophic Lateral Sclerosis Neuroimaging Consortium study. Whole brain voxel-wise mixed-effects modelling analysis showed extensive atrophy patterns differentiating patients from the normal controls. Cerebral atrophy was present in the motor cortex and corticospinal tract, involving both grey matter and white matter, and to a lesser extent in non-motor regions. More specifically, the results showed significant bilateral atrophy in the motor cortex and corticospinal tract (including the internal capsule and brainstem) and ventricular enlargement, along with significant longitudinal atrophy in precentral gyrus, frontal and parietal white matter, accompanied by ventricular and sulcal enlargement. Atrophy in the precentral gyrus was significantly associated with greater disability as quantified with the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised ( < 0.0001). The pattern of atrophy observed using deformation-based morphometry was consistent with the Brettschneider's four-stage pathological model of the disease. Deformation-based morphometry provides a sensitive indicator of atrophy in Amyotrophic lateral sclerosis and has potential as a biomarker of disease burden, in both grey matter and white matter.
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http://dx.doi.org/10.1093/braincomms/fcaa061DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846188PMC
May 2020

Vascular Contributions to Neurodegeneration: Protocol of the COMPASS-ND Study.

Can J Neurol Sci 2021 11 28;48(6):799-806. Epub 2021 Jan 28.

Department of Medicine (Neurology), Hurvitz Brain Sciences Research Program, LC Campbell Cognitive Neurology Unit, Canadian Partnership for Stroke Recovery, University of Toronto, London, Ontario, Canada.

Objective: To describe the neuroimaging and other methods for assessing vascular contributions to neurodegeneration in the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) study, a Canadian multi-center, prospective longitudinal cohort study, including reliability and feasibility in the first 200 participants.

Methods: COMPASS-ND includes persons with Alzheimer's disease (AD; n = 150), Parkinson's disease (PD) and Lewy body dementias (LBDs) (200), mixed dementia (200), mild cognitive impairment (MCI; 400), subcortical ischemic vascular MCI (V-MCI; 200), subjective cognitive impairment (SCI; 300), and cognitively intact elderly controls (660). Magnetic resonance imaging (MRI) was acquired according to the validated Canadian Dementia Imaging Protocol and visually reviewed by either of two experienced readers blinded to clinical characteristics. Other relevant assessments include history of vascular disease and risk factors, blood pressure, height and weight, cholesterol, glucose, and hemoglobin A1c.

Results: Analyzable data were obtained in 197/200 of whom 18 of whom were clinically diagnosed with V-MCI or mixed dementia. The overall prevalence of infarcts was 24.9%, microbleeds was 24.6%, and high white matter hyperintensity (WMH) was 31.0%. MRI evidence of a potential vascular contribution to neurodegeneration was seen in 12.9%-40.0% of participants clinically diagnosed with another condition such as AD. Inter-rater reliability was good to excellent.

Conclusion: COMPASS-ND will be a useful platform to study vascular brain injury and its association with risk factors, biomarkers, and cognitive and functional decline across multiple age-related neurodegenerative diseases. Initial findings show that MRI-defined vascular brain injury is common in all cognitive syndromes and is under-recognized clinically.
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http://dx.doi.org/10.1017/cjn.2021.19DOI Listing
November 2021

Neuroanatomical associations of the Edinburgh cognitive and Behavioural ALS screen (ECAS).

Brain Imaging Behav 2021 Jun;15(3):1641-1654

Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada.

Cognitive impairment is now recognized in a subset of patients with amyotrophic lateral sclerosis (ALS). The objective of the study was to identify group differences and neuroanatomical correlates of the Edinburgh Cognitive and Behavioural ALS Screen (ECAS) in participants ALS. Fifty-three ALS patients and 43 healthy controls recruited as a part of our multicentre study (CALSNIC) were administered the ECAS and underwent an MRI scan. Voxel-based morphometry and tract based spatial statistics (TBSS) was performed to identify structural changes and associations with impaired ECAS scores. Lower performance in the ECAS verbal fluency and executive domains were noted in ALS patients as compared to controls (p < 0.01). Extensive white matter degeneration was noted in the corticospinal tract in all ALS patients, while ALS patients with impaired verbal fluency or executive domains (ALS-exi, n = 22), displayed additional degeneration in the corpus callosum, cingulum and superior longitudinal fasciculus as compared to controls (p < 0.05, TFCE corrected). Mild grey matter changes and associations with ECAS verbal fluency or executive performance were noted at lenient statistical thresholds (p < 0.001, uncorrected). Executive impairment was detected using the ECAS in our multicentre sample of Canadian ALS patients. White matter degeneration in motor regions was revealed in ALS patients with extensive spread to frontal regions in the ALS-exi sub-group. Mild associations between ECAS verbal fluency, executive function scores and MRI metrics suggest that reduced performance may be associated with widespread structural integrity.
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http://dx.doi.org/10.1007/s11682-020-00359-7DOI Listing
June 2021

White matter tract microstructure and cognitive performance after transient ischemic attack.

PLoS One 2020 23;15(10):e0239116. Epub 2020 Oct 23.

Seaman Family MR Center, Foothills Medical Centre, Calgary, AB, Canada.

Background And Purpose: Patients 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.

Methods: Ninety-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.

Results: Transient 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.

Conclusions: DTI 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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0239116PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584182PMC
November 2020

Trial of remote ischaemic preconditioning in vascular cognitive impairment (TRIC-VCI): protocol.

BMJ Open 2020 10 14;10(10):e040466. Epub 2020 Oct 14.

Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada

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.
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http://dx.doi.org/10.1136/bmjopen-2020-040466DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7559076PMC
October 2020

Involvement of the dentate nucleus in the pathophysiology of amyotrophic lateral sclerosis: A multi-center and multi-modal neuroimaging study.

Neuroimage Clin 2020 16;28:102385. Epub 2020 Aug 16.

Department of Medicine, Divison of Neurology, University of Alberta, Edmonton, Alberta, AB, Canada; Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, AB, Canada. Electronic address:

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.
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http://dx.doi.org/10.1016/j.nicl.2020.102385DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7476068PMC
June 2021

Age-related differences in cerebral blood flow and cortical thickness with an application to age prediction.

Neurobiol Aging 2020 11 3;95:131-142. Epub 2020 Jul 3.

Department of Radiology, University of Calgary, Calgary, Alberta, Canada; Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada; Healthy Brain Aging Lab, University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.

Cerebral cortex thinning and cerebral blood flow (CBF) reduction are typically observed during normal healthy aging. However, imaging-based age prediction models have primarily used morphological features of the brain. Complementary physiological CBF information might result in an improvement in age estimation. In this study, T1-weighted structural magnetic resonance imaging and arterial spin labeling CBF images were acquired in 146 healthy participants across the adult life span. Sixty-eight cerebral cortex regions were segmented, and the cortical thickness and mean CBF were computed for each region. Linear regression with age was computed for each region and data type, and laterality and correlation matrices were computed. Sixteen predictive models were trained with the cortical thickness and CBF data alone as well as a combination of both data types. The age explained more variance in the cortical thickness data (average R of 0.21) than in the CBF data (average R of 0.09). All 16 models performed significantly better when combining both measurement types and using feature selection, and thus, we conclude that the inclusion of CBF data marginally improves age estimation.
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http://dx.doi.org/10.1016/j.neurobiolaging.2020.06.019DOI Listing
November 2020

Calgary Normative Study: design of a prospective longitudinal study to characterise potential quantitative MR biomarkers of neurodegeneration over the adult lifespan.

BMJ Open 2020 08 13;10(8):e038120. Epub 2020 Aug 13.

Departments of Clinical Neurosciences and Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.

Introduction: A number of MRI methods have been proposed to be useful, quantitative biomarkers of neurodegeneration in ageing. The Calgary Normative Study (CNS) is an ongoing single-centre, prospective, longitudinal study that seeks to develop, test and assess quantitative magnetic resonance (MR) methods as potential biomarkers of neurodegeneration. The CNS has three objectives: first and foremost, to evaluate and characterise the dependence of the selected quantitative neuroimaging biomarkers on age over the adult lifespan; second, to evaluate the precision, variability and repeatability of quantitative neuroimaging biomarkers as part of biomarker validation providing proof-of-concept and proof-of-principle; and third, provide a shared repository of normative data for comparison to various disease cohorts.

Methods And Analysis: Quantitative MR mapping of the brain including longitudinal relaxation time (T1), transverse relaxation time (T2), T2*, magnetic susceptibility (QSM), diffusion and perfusion measurements, as well as morphological assessments are performed. The Montreal Cognitive Assessment (MoCA) and a brief, self-report medical history will be collected. Mixed regression models will be used to characterise changes in quantitative MR biomarker measures over the adult lifespan. In this report, we describe the study design, strategies to recruit and perform changes to the acquisition protocol from inception to 31 December 2018, planned statistical approach and data sharing procedures for the study.

Ethics And Dissemination: Participants provide signed informed consent. Changes in quantitative MR biomarkers measured over the adult lifespan as well as estimates of measurement variance and repeatability will be disseminated through peer-reviewed scientific publication.
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http://dx.doi.org/10.1136/bmjopen-2020-038120DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430487PMC
August 2020

A prospective harmonized multicenter DTI study of cerebral white matter degeneration in ALS.

Neurology 2020 08 9;95(8):e943-e952. Epub 2020 Jul 9.

From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada.

Objective: To evaluate progressive white matter (WM) degeneration in amyotrophic lateral sclerosis (ALS).

Methods: Sixty-six patients with ALS and 43 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium (CALSNIC). Participants underwent a harmonized neuroimaging protocol across 4 centers that included diffusion tensor imaging (DTI) for assessment of WM integrity. Three visits were accompanied by clinical assessments of disability (ALS Functional Rating Scale-Revised [ALSFRS-R]) and upper motor neuron (UMN) function. Voxel-wise whole-brain and quantitative tract-wise DTI assessments were done at baseline and longitudinally. Correction for site variance incorporated data from healthy controls and from healthy volunteers who underwent the DTI protocol at each center.

Results: Patients with ALS had a mean progressive decline in fractional anisotropy (FA) of the corticospinal tract (CST) and frontal lobes. Tract-wise analysis revealed reduced FA in the CST, corticopontine/corticorubral tract, and corticostriatal tract. CST FA correlated with UMN function, and frontal lobe FA correlated with the ALSFRS-R score. A progressive decline in CST FA correlated with a decline in the ALSFRS-R score and worsening UMN signs. Patients with fast vs slow progression had a greater reduction in FA of the CST and upper frontal lobe.

Conclusions: Progressive WM degeneration in ALS is most prominent in the CST and frontal lobes and, to a lesser degree, in the corticopontine/corticorubral tracts and corticostriatal pathways. With the use of a harmonized imaging protocol and incorporation of analytic methods to address site-related variances, this study is an important milestone toward developing DTI biomarkers for cerebral degeneration in ALS.

Clinicaltrialsgov Identifier: NCT02405182.
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http://dx.doi.org/10.1212/WNL.0000000000010235DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668555PMC
August 2020

Cerebrovascular reactivity in cerebral amyloid angiopathy, Alzheimer disease, and mild cognitive impairment.

Neurology 2020 09 8;95(10):e1333-e1340. Epub 2020 Jul 8.

From the Department of Clinical Neurosciences (A.R.S., C.R.M., A.Z., A.C., A.A.-V., R.S., C.Z., R.B.S., R.F., B.G.G., E.E.S), Hotchkiss Brain Institute (R.F., B.G.G., E.E.S), Department of Community Health Sciences (C.Z., E.E.S), and Department of Radiology (R.F., B.G.G., E.E.S), University of Calgary, Alberta; Faculty of Medicine (I.C.), University of Toronto, Ontario; and Seaman Family MR Research Centre (C.R.M., R.F., B.G.G.), Foothills Medical Centre, Calgary, Alberta, Canada

Objective: To assess cerebrovascular reactivity in response to a visual task in participants with cerebral amyloid angiopathy (CAA), Alzheimer disease (AD), and mild cognitive impairment (MCI) using fMRI.

Methods: This prospective cohort study included 40 patients with CAA, 22 with AD, 27 with MCI, and 25 healthy controls. Each participant underwent a visual fMRI task using a contrast-reversing checkerboard stimulus. Visual evoked potentials (VEPs) were used to compare visual cortex neuronal activity in 83 participants. General linear models using least-squares means, adjusted for multiple comparisons with the Tukey test, were used to estimate mean blood oxygen level-dependent (BOLD) signal change during the task and VEP differences between groups.

Results: After adjustment for age and hypertension, estimated mean BOLD response amplitude was as follows: CAA 1.88% (95% confidence interval [CI] 1.60%-2.15%), AD 2.26% (1.91%-2.61%), MCI 2.15% (1.84%-2.46%), and control 2.65% (2.29%-3.00%). Only patients with CAA differed from controls ( = 0.01). In the subset with VEPs, group was not associated with prolonged latencies or lower amplitudes. Lower BOLD amplitude response was associated with higher white matter hyperintensity (WMH) volumes in CAA (for each 0.1% lower BOLD response amplitude, the WMH volume was 9.2% higher, 95% CI 6.0%-12.4%) but not other groups ( = 0.002 for interaction) when controlling for age and hypertension.

Conclusions: Mean visual BOLD response amplitude was lowest in participants with CAA compared to controls, without differences in VEP latencies and amplitudes. This suggests that the impaired visual BOLD response is due to reduced vascular reactivity in CAA. In contrast to participants with CAA, the visual BOLD response amplitude did not differ between those with AD or MCI and controls.
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http://dx.doi.org/10.1212/WNL.0000000000010201DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538216PMC
September 2020

Dual-domain cascade of U-nets for multi-channel magnetic resonance image reconstruction.

Magn Reson Imaging 2020 09 17;71:140-153. Epub 2020 Jun 17.

Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Seaman Family MR Research Centre, Foothills Medical Center, Calgary, AB, Canada; Calgary Image Processing and Analysis Center (CIPAC), Foothills Medical Centre, Calgary, AB, Canada.

The U-net is a deep-learning network model that has been used to solve a number of inverse problems. In this work, the concatenation of two-element U-nets, termed the W-net, operating in k-space (K) and image (I) domains, were evaluated for multi-channel magnetic resonance (MR) image reconstruction. The two-element network combinations were evaluated for the four possible image-k-space domain configurations: a) W-net II, b) W-net KK, c) W-net IK, and d) W-net KI. Selected four element (WW-nets) and six element (WWW-nets) networks were also examined. Two configurations of each network were compared: 1) each coil channel was processed independently, and 2) all channels were processed simultaneously. One hundred and eleven volumetric, T1-weighted, 12-channel coil k-space datasets were used in the experiments. Normalized root mean squared error, peak signal-to-noise ratio and visual information fidelity were used to assess the reconstructed images against the fully sampled reference images. Our results indicated that networks that operate solely in the image domain were better when independently processing individual channels of multi-channel data. Dual-domain methods were better when simultaneously reconstructing all channels of multi-channel data. In addition, the best cascade of U-nets performed better (p < 0.01) than the previously published, state-of-the-art Deep Cascade and Hybrid Cascade models in three out of four experiments.
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http://dx.doi.org/10.1016/j.mri.2020.06.002DOI Listing
September 2020

Cross-sectional and longitudinal differences in peak skeletonized white matter mean diffusivity in cerebral amyloid angiopathy.

Neuroimage Clin 2020 26;27:102280. Epub 2020 May 26.

Departments of Clinical Neurosciences and Radiology, Hotchkiss Brain Institute, University of Calgary, Seaman Family MR Research Centre, Foothills Medical Centre, Alberta Health Sciences, Calgary, Alberta, Canada.

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 mm/s) compared to NC (3.25 × 10 mm/s), MCI (3.62 × 10 mm/s) and AD (3.89 × 10 mm/s) groups (p < .01). Among CAA patients, higher PSMD was associated with slower processing speed (estimated -0.22 standard deviation (SD) change in processing speed z score per SD increase in PSMD, 95% CI -0.42 to -0.03, p = .03), higher WMH volume [β = 0.74, CI 0.48 to 1.00], and higher CAA SVD score [β = 0.68, CI 0.24 to 1.21] but was not associated with MMSE, executive function, memory, CMB count, or cortical thickness. PSMD increased over 1-year in all groups (p < .01) but without rate differences between groups (p = .66).

Conclusions: PSMD, a simple marker of diffuse global white matter heterogeneity, is increased in CAA. Our findings further support a role for white matter disruption in causing cognitive impairment in CAA.
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http://dx.doi.org/10.1016/j.nicl.2020.102280DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7284130PMC
March 2021

The Use of Random Forests to Identify Brain Regions on Amyloid and FDG PET Associated With MoCA Score.

Clin Nucl Med 2020 Jun;45(6):427-433

Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada.

Purpose: The aim of this study was to evaluate random forests (RFs) to identify ROIs on F-florbetapir and F-FDG PET associated with Montreal Cognitive Assessment (MoCA) score.

Materials And Methods: Fifty-seven subjects with significant white matter disease presenting with either transient ischemic attack/lacunar stroke or mild cognitive impairment from early Alzheimer disease, enrolled in a multicenter prospective observational trial, had MoCA and F-florbetapir PET; 55 had F-FDG PET. Scans were processed using the MINC toolkit to generate SUV ratios, normalized to cerebellar gray matter (F-florbetapir PET), or pons (F-FDG PET). SUV ratio data and MoCA score were used for supervised training of RFs programmed in MATLAB.

Results: F-Florbetapir PETs were randomly divided into 40 training and 17 testing scans; 100 RFs of 1000 trees, constructed from a random subset of 16 training scans and 20 ROIs, identified ROIs associated with MoCA score: right posterior cingulate gyrus, right anterior cingulate gyrus, left precuneus, left posterior cingulate gyrus, and right precuneus. Amyloid increased with decreasing MoCA score. F-FDG PETs were randomly divided into 40 training and 15 testing scans; 100 RFs of 1000 trees, each tree constructed from a random subset of 16 training scans and 20 ROIs, identified ROIs associated with MoCA score: left fusiform gyrus, left precuneus, left posterior cingulate gyrus, right precuneus, and left middle orbitofrontal gyrus. F-FDG decreased with decreasing MoCA score.

Conclusions: Random forests help pinpoint clinically relevant ROIs associated with MoCA score; amyloid increased and F-FDG decreased with decreasing MoCA score, most significantly in the posterior cingulate gyrus.
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http://dx.doi.org/10.1097/RLU.0000000000003043DOI Listing
June 2020

High-resolution T2-FLAIR and non-contrast CT brain atlas of the elderly.

Sci Data 2020 02 17;7(1):56. Epub 2020 Feb 17.

Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

Normative brain atlases are a standard tool for neuroscience research and are, for example, used for spatial normalization of image datasets prior to voxel-based analyses of brain morphology and function. Although many different atlases are publicly available, they are usually biased with respect to an imaging modality and the age distribution. Both effects are well known to negatively impact the accuracy and reliability of the spatial normalization process using non-linear image registration methods. An important and very active neuroscience area that lacks appropriate atlases is lesion-related research in elderly populations (e.g. stroke, multiple sclerosis) for which FLAIR MRI and non-contrast CT are often the clinical imaging modalities of choice. To overcome the lack of atlases for these tasks and modalities, this paper presents high-resolution, age-specific FLAIR and non-contrast CT atlases of the elderly generated using clinical images.
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http://dx.doi.org/10.1038/s41597-020-0379-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026039PMC
February 2020

Cerebral degeneration in amyotrophic lateral sclerosis: A prospective multicenter magnetic resonance spectroscopy study.

Neurol Clin Pract 2019 Oct;9(5):400-407

Faculty of Science (OS); Department of Biomedical Engineering (CH, PS, SK); Neuroscience and Mental Health Institute (SC, DT, SK); Divison of Neurology (DM, CL, SK), Department of Medicine; School of Public Health (DE); University of Alberta, Edmonton, Alberta; Sunnybrook Health Sciences Centre (LZ, AA, SJG), University of Toronto, Toronto, Ontario; Montreal Neurological Institute and Hospital (AG), McGill University, Montreal, Quebec; Departments of Radiology and Clinical Neurosciences (LK, RF), Hotchkiss Brain Institute, University of Calgary; and Seaman Family MR Research Centre (LK, RF), Foothills Medical Centre, Calgary, Alberta, Canada.

Background: We investigated cerebral degeneration and neurochemistry in patients with amyotrophic lateral sclerosis (ALS) using magnetic resonance spectroscopy (MRS).

Methods: We prospectively studied 65 patients and 43 age-matched healthy controls. Participants were recruited from 4 centers as part of a study in the Canadian ALS Neuroimaging Consortium. All participants underwent single-voxel proton MRS using a protocol standardized across all sites. Metabolites reflecting neuronal integrity (total -acetyl aspartyl moieties [tNAA]) and gliosis (myo-inositol [Ino]), as well as creatine (Cr) and choline (Cho), were quantified in the midline motor cortex and midline prefrontal cortex. Comparisons were made between patients with ALS and healthy controls. Metabolites were correlated with clinical measures of upper motor neuron dysfunction, disease progression rate, and cognitive performance.

Results: In the motor cortex, tNAA/Cr, tNAA/Cho, and tNAA/Ino ratios were reduced in the ALS group compared with controls. Group differences in tNAA/Cr and tNAA/Cho in the prefrontal cortex displayed reduced ratios in ALS patients; however, these were not statistically significant. Reduced motor cortex ratios were associated with slower foot tapping rate, whereas only motor tNAA/Ino was associated with finger tapping rate. Disease progression rate was associated with motor tNAA/Cho. Verbal fluency, semantic fluency, and digit span forwards and backwards were associated with prefrontal tNAA/Cr.

Conclusions: This study demonstrates that cerebral degeneration in ALS is more pronounced in the motor than prefrontal cortex, that multicenter MRS studies are feasible, and that motor tNAA/Ino shows promise as a potential biomarker.
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http://dx.doi.org/10.1212/CPJ.0000000000000674DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6814429PMC
October 2019

Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks.

Artif Intell Med 2019 07 23;98:48-58. Epub 2019 Jul 23.

Medical Image Computing Laboratory (MICLab), Department of Computer Engineering and Industrial Automation, School of Electrical and Computer Engineering, University of Campinas, Campinas, São Paulo, Brazil.

Manual annotation is considered to be the "gold standard" in medical imaging analysis. However, medical imaging datasets that include expert manual segmentation are scarce as this step is time-consuming, and therefore expensive. Moreover, single-rater manual annotation is most often used in data-driven approaches making the network biased to only that single expert. In this work, we propose a CNN for brain extraction in magnetic resonance (MR) imaging, that is fully trained with what we refer to as "silver standard" masks. Therefore, eliminating the cost associated with manual annotation. Silver standard masks are generated by forming the consensus from a set of eight, public, non-deep-learning-based brain extraction methods using the Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm. Our method consists of (1) developing a dataset with "silver standard" masks as input, and implementing (2) a tri-planar method using parallel 2D U-Net-based convolutional neural networks (CNNs) (referred to as CONSNet). This term refers to our integrated approach, i.e., training with silver standard masks and using a 2D U-Net-based architecture. We conducted our analysis using three public datasets: the Calgary-Campinas-359 (CC-359), the LONI Probabilistic Brain Atlas (LPBA40), and the Open Access Series of Imaging Studies (OASIS). Five performance metrics were used in our experiments: Dice coefficient, sensitivity, specificity, Hausdorff distance, and symmetric surface-to-surface mean distance. Our results showed that we outperformed (i.e., larger Dice coefficients) the current state-of-the-art skull-stripping methods without using gold standard annotation for the CNNs training stage. CONSNet is the first deep learning approach that is fully trained using silver standard data and is, thus, more generalizable. Using these masks, we eliminate the cost of manual annotation, decreased inter-/intra-rater variability, and avoided CNN segmentation overfitting towards one specific manual annotation guideline that can occur when gold standard masks are used. Moreover, once trained, our method takes few seconds to process a typical brain image volume using modern a high-end GPU. In contrast, many of the other competitive methods have processing times in the order of minutes.
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http://dx.doi.org/10.1016/j.artmed.2019.06.008DOI Listing
July 2019

The Use of Random Forests to Classify Amyloid Brain PET.

Clin Nucl Med 2019 Oct;44(10):784-788

Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.

Purpose: To evaluate random forests (RFs) as a supervised machine learning algorithm to classify amyloid brain PET as positive or negative for amyloid deposition and identify key regions of interest for stratification.

Methods: The data set included 57 baseline F-florbetapir (Amyvid; Lilly, Indianapolis, IN) brain PET scans in participants with severe white matter disease, presenting with either transient ischemic attack/lacunar stroke or mild cognitive impairment from early Alzheimer disease, enrolled in a multicenter prospective observational trial. Scans were processed using the MINC toolkit to generate SUV ratios, normalized to cerebellar gray matter, and clinically read by 2 nuclear medicine physicians with interpretation based on consensus (35 negative, 22 positive). SUV ratio data and clinical reads were used for supervised training of an RF classifier programmed in MATLAB.

Results: A 10,000-tree RF, each tree using 15 randomly selected cases and 20 randomly selected features (SUV ratio per region of interest), with 37 cases for training and 20 cases for testing, had sensitivity = 86% (95% confidence interval [CI], 42%-100%), specificity = 92% (CI, 64%-100%), and classification accuracy = 90% (CI, 68%-99%). The most common features at the root node (key regions for stratification) were (1) left posterior cingulate (1039 trees), (2) left middle frontal gyrus (1038 trees), (3) left precuneus (857 trees), (4) right anterior cingulate gyrus (655 trees), and (5) right posterior cingulate (588 trees).

Conclusions: Random forests can classify brain PET as positive or negative for amyloid deposition and suggest key clinically relevant, regional features for classification.
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http://dx.doi.org/10.1097/RLU.0000000000002747DOI Listing
October 2019

Automatic identification of atherosclerosis subjects in a heterogeneous MR brain imaging data set.

Magn Reson Imaging 2019 10 19;62:18-27. Epub 2019 Jun 19.

Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Seaman Family MR Research Centre, Foothills Medical Center, Calgary, AB, Canada; Calgary Image Processing and Analysis Center (CIPAC), Foothills Medical Centre, Calgary, AB, Canada.

Carotid-artery atherosclerosis (CA) contributes significantly to overall morbidity and mortality in ischemic stroke. We propose a machine learning technique to automatically identify subjects with CA from a heterogeneous cohort of magnetic resonance brain images. The cohort includes 190 subjects with CA, white mater hyperintensites of presumed vascular origin or multiple sclerosis, as well as 211 presumed healthy subjects. We determined a set of handcrafted and convolutional discriminant features to perform this task. A support vector machine (SVM) was used to perform this four-class classification task. Our approach had an accuracy rate of 97.5% (higher than chance accuracy of 52.6% for guessing majority class), sensitivity of 96.4% and specificity of 97.9% in identifying subjects with CA, suggesting that the proposed combination of features may be used as an imaging biomarker for characterizing atherosclerotic disease on brain imaging.
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http://dx.doi.org/10.1016/j.mri.2019.06.007DOI Listing
October 2019

Quantifying blood-brain barrier leakage in small vessel disease: Review and consensus recommendations.

Alzheimers Dement 2019 06 25;15(6):840-858. Epub 2019 Apr 25.

Centre for Clinical Brain Science, University of Edinburgh, Edinburgh, UK; Dementia Research Institute, University of Edinburgh, Edinburgh, UK; Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.

Cerebral small vessel disease (cSVD) comprises pathological processes of the small vessels in the brain that may manifest clinically as stroke, cognitive impairment, dementia, or gait disturbance. It is generally accepted that endothelial dysfunction, including blood-brain barrier (BBB) failure, is pivotal in the pathophysiology. Recent years have seen increasing use of imaging, primarily dynamic contrast-enhanced magnetic resonance imaging, to assess BBB leakage, but there is considerable variability in the approaches and findings reported in the literature. Although dynamic contrast-enhanced magnetic resonance imaging is well established, challenges emerge in cSVD because of the subtle nature of BBB impairment. The purpose of this work, authored by members of the HARNESS Initiative, is to provide an in-depth review and position statement on magnetic resonance imaging measurement of subtle BBB leakage in clinical research studies, with aspects requiring further research identified. We further aim to provide information and consensus recommendations for new investigators wishing to study BBB failure in cSVD and dementia.
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http://dx.doi.org/10.1016/j.jalz.2019.01.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6565805PMC
June 2019
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