Neuropsychiatric symptoms: Risk factor or disease marker? A study of structural imaging biomarkers of Alzheimer's disease and incident cognitive decline.

Neuropsychiatric symptoms (NPS) are risk factors for Alzheimer's disease (AD) but can also manifest secondary to AD pathology. Mild behavioral impairment (MBI) refers to later-life emergent and persistent NPS that may mark early-stage AD. To distinguish MBI from NPS that are transient or which represent psychiatric conditions (non-MBI NPS), we investigated the effect of applying MBI criteria on NPS associations with AD structural imaging biomarkers and incident cognitive decline. Data for participants (n = 1273) with normal cognition (NC) or mild cognitive impairment (MCI) in the National Alzheimer's Coordinating Center Uniform Data Set were analyzed. NPS status (MBI, non-MBI NPS) was derived from the Neuropsychiatric Inventory Questionnaire and psychiatric history. Normalized measures of bilateral hippocampal (HPC) and entorhinal cortex (EC) volume, and AD meta-region of interest (ROI) mean cortical thickness were acquired from T1-weighted magnetic resonance imaging scans. Multivariable linear and Cox regressions examined NPS associations with imaging biomarkers and incident cognitive decline, respectively. MBI was associated with lower volume and cortical thickness in all ROIs in both NC and MCI, except for EC volume in NC. Non-MBI NPS were only associated with lower HPC volume in NC. Although both of the NPS groups showed higher hazards for MCI/dementia than No NPS, MBI participants showed more rapid decline. Although both types of NPS were linked to HPC atrophy, only NPS that emerged and persisted in later-life, consistent with MBI criteria, were related to AD neurodegenerative patterns beyond the HPC. Moreover, MBI predicted faster progression to dementia than non-MBI NPS.

Myths and Methodologies: Understanding the health impact of head down bedrest for the benefit of older adults and astronauts. Study protocol of the Canadian Bedrest Study.

Weightlessness during spaceflight can harm various bodily systems, including bone density, muscle mass, strength and cognitive functions. Exercise appears to somewhat counteract these effects. A terrestrial model for this is head-down bedrest (HDBR), simulating gravity loss. This mirrors challenges faced by older adults in extended bedrest and space environments. The first Canadian study, backed by the Canadian Space Agency, Canadian Institutes of Health Research, and Canadian Frailty Network, aims to explore these issues. The study seeks to: (1) scrutinize the impact of 14-day HDBR on physiological, psychological and neurocognitive systems, and (2) assess the benefits of exercise during HDBR. Eight teams developed distinct protocols, harmonized in three videoconferences, at the McGill University Health Center. Over 26 days, 23 participants aged 55-65 underwent baseline measurements, 14 days of -6° HDBR, and 7 days of recovery. Half did prescribed exercise thrice daily combining resistance and endurance exercise for a total duration of 1 h. Assessments included demographics, cardiorespiratory fitness, bone health, body composition, quality of life, mental health, cognition, muscle health and biomarkers. This study has yielded some published outcomes, with more forthcoming. Findings will enrich our comprehension of HDBR effects, guiding future strategies for astronaut well-being and aiding bedrest-bound older adults. By outlining evidence-based interventions, this research supports both space travellers and those enduring prolonged bedrest.

An imaging-based method of mapping multi-echo BOLD intracranial pulsatility.

PURPOSE: Cardiac-related intracranial pulsatility may relate to cerebrovascular health, and this information is contained in BOLD MRI data. There is broad interest in methods to isolate BOLD pulsatility, and the current study examines a deep learning approach. METHODS: Multi-echo BOLD images, respiratory, and cardiac recordings were measured in 55 adults. Ground truth BOLD pulsatility maps were calculated with an established method. BOLD fast Fourier transform magnitude images were used as temporal-frequency image inputs to a U-Net deep learning model. Model performance was evaluated by mean squared error (MSE), mean absolute error (MAE), structural similarity index (SSIM), and mutual information (MI). Experiments evaluated the influence of input channel size, an age group effect during training, dependence on TE, performance without the U-Net architecture, and importance of respiratory preprocessing. RESULTS: The U-Net model generated BOLD pulsatility maps with lower MSE as additional fast Fourier transform input images were used. There was no age group effect for MSE (P > 0.14). MAE and SSIM metrics did not vary across TE (P > 0.36), whereas MI showed a significant TE dependence (P < 0.05). The U-Net versus no U-Net comparison showed no significant difference for MAE (P = 0.059); however, SSIM and MI were significantly different between models (P < 0.001). Within the insula, the cross-correlation values were high (r > 0.90) when comparing the U-Net model trained with/without respiratory preprocessing. CONCLUSION: Multi-echo BOLD pulsatility maps were synthesized from a U-net model that was trained to use temporal-frequency BOLD image inputs. This work adds to the deep learning methods that characterize BOLD physiological signals.

Impact of 14 Days of Bed Rest in Older Adults and an Exercise Countermeasure on Body Composition, Muscle Strength, and Cardiovascular Function: Canadian Space Agency Standard Measures.

INTRODUCTION: Head-down bed rest (HDBR) has long been used as an analog to microgravity, and it also enables studying the changes occurring with aging. Exercise is the most effective countermeasure for the deleterious effects of inactivity. The aim of this study was to investigate the efficacy of an exercise countermeasure in healthy older participants on attenuating musculoskeletal deconditioning, cardiovascular fitness level, and muscle strength during 14 days of HDBR as part of the standard measures of the Canadian Space Agency. METHODS: Twenty-three participants (12 males and 11 females), aged 55-65 years, were admitted for a 26-day inpatient stay at the McGill University Health Centre. After 5 days of baseline assessment tests, they underwent 14 days of continuous HDBR followed by 7 days of recovery with repeated tests. Participants were randomized to passive physiotherapy or an exercise countermeasure during the HDBR period consisting of 3 sessions per day of either high-intensity interval training (HIIT) or low-intensity cycling or strength exercises for the lower and upper body. Peak aerobic power (V̇O2peak) was determined using indirect calorimetry. Body composition was assessed by dual-energy X-ray absorptiometry, and several muscle group strengths were evaluated using an adjustable chair dynamometer. A vertical jump was used to assess whole-body power output, and a tilt test was used to measure cardiovascular and orthostatic challenges. Additionally, changes in various blood parameters were measured as well as the effects of exercise countermeasure on these measurements. RESULTS: There were no differences at baseline in main characteristics between the control and exercise groups. The exercise group maintained V̇O2peak levels similar to baseline, whereas it decreased in the control group following 14 days of HDBR. Body weight significantly decreased in both groups. Total and leg lean masses decreased in both groups. However, total body fat mass decreased only in the exercise group. Isometric and isokinetic knee extension muscle strength were significantly reduced in both groups. Peak velocity, flight height, and flight time were significantly reduced in both groups with HDBR. CONCLUSION: In this first Canadian HDBR study in older adults, an exercise countermeasure helped maintain aerobic fitness and lean body mass without affecting the reduction of knee extension strength. However, it was ineffective in protecting against orthostatic intolerance. These results support HIIT as a promising approach to preserve astronaut health and functioning during space missions, and to prevent deconditioning as a result of hospitalization in older adults.

Beware of white matter hyperintensities causing systematic errors in FreeSurfer gray matter segmentations!

Volumetric estimates of subcortical and cortical structures, extracted from T1-weighted MRIs, are widely used in many clinical and research applications. Here, we investigate the impact of the presence of white matter hyperintensities (WMHs) on FreeSurfer gray matter (GM) structure volumes and its possible bias on functional relationships. T1-weighted images from 1,077 participants (4,321 timepoints) from the Alzheimer's Disease Neuroimaging Initiative were processed with FreeSurfer version 6.0.0. WMHs were segmented using a previously validated algorithm on either T2-weighted or Fluid-attenuated inversion recovery images. Mixed-effects models were used to assess the relationships between overlapping WMHs and GM structure volumes and overall WMH burden, as well as to investigate whether such overlaps impact associations with age, diagnosis, and cognitive performance. Participants with higher WMH volumes had higher overlaps with GM volumes of bilateral caudate, cerebral cortex, putamen, thalamus, pallidum, and accumbens areas (p < .0001). When not corrected for WMHs, caudate volumes increased with age (p < .0001) and were not different between cognitively healthy individuals and age-matched probable Alzheimer's disease patients. After correcting for WMHs, caudate volumes decreased with age (p < .0001), and Alzheimer's disease patients had lower caudate volumes than cognitively healthy individuals (p < .01). Uncorrected caudate volume was not associated with ADAS13 scores, whereas corrected lower caudate volumes were significantly associated with poorer cognitive performance (p < .0001). Presence of WMHs leads to systematic inaccuracies in GM segmentations, particularly for the caudate, which can also change clinical associations. While specifically measured for the Freesurfer toolkit, this problem likely affects other algorithms.

Patch-wise brain age longitudinal reliability.

We recently introduced a patch-wise technique to estimate brain age from anatomical T1-weighted magnetic resonance imaging (T1w MRI) data. Here, we sought to assess its longitudinal reliability by leveraging a unique dataset of 99 longitudinal MRI scans from a single, cognitively healthy volunteer acquired over a period of 17 years (aged 29-46 years) at multiple sites. We built a robust patch-wise brain age estimation framework on the basis of 100 cognitively healthy individuals from the MindBoggle dataset (aged 19-61 years) using the Desikan-Killiany-Tourville atlas, then applied the model to the volunteer dataset. The results show a high prediction accuracy on the independent test set (R2 = .94, mean absolute error of 0.63 years) and no statistically significant difference between manufacturers, suggesting that the patch-wise technique has high reliability and can be used for longitudinal multi-centric studies.

A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap.

Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput 'omics' are unbiased data-driven techniques that probe the complex aetiology of Alzheimer's disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer's disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer's disease.

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

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.

Reliability assessment of tissue classification algorithms for multi-center and multi-scanner data.

BACKGROUND: Gray and white matter volume difference and change are important imaging markers of pathology and disease progression in neurology and psychiatry. Such measures are usually estimated from tissue segmentation maps produced by publicly available image processing pipelines. However, the reliability of the produced segmentations when using multi-center and multi-scanner data remains understudied. Here, we assess the robustness of six publicly available tissue classification pipelines across images acquired from different MR scanners and sites. METHODS: We used 90 T1-weighted images of a single individual, scanned in 73 sessions across 27 different sites to assess the robustness of the tissue classification tools. Variability in Dice similarity index values and tissue volumes was assessed for Atropos, BISON, Classify_Clean, FAST, FreeSurfer, and SPM12. RESULTS: BISON had the highest overall Dice coefficient for GM, followed by SPM12 and Atropos; while Atropos had the highest overall Dice coefficient for WM, followed by BISON and SPM12. BISON had the lowest overall variability in its volumetric estimates, followed by FreeSurfer, and SPM12. All methods also had significant differences between some of their estimates across different scanner manufacturers (e.g. BISON had significantly higher GM estimates and correspondingly lower WM estimates for GE scans compared to Philips and Siemens), and different signal-to-noise ratio (SNR) levels (e.g. FAST and FreeSurfer had significantly higher WM volume estimates for high versus medium and low SNR tertiles as well as correspondingly lower GM volume estimates). CONCLUSIONS: Our comparisons provide a benchmark on the reliability of the publicly used tissue classification techniques and the amount of variability that can be expected when using large multi-center and multi-scanner databases.

Multivariate consistency of resting-state fMRI connectivity maps acquired on a single individual over 2.5 years, 13 sites and 3 vendors.

Studies using resting-state functional magnetic resonance imaging (rsfMRI) are increasingly collecting data at multiple sites in order to speed up recruitment or increase sample size. The main objective of this study was to assess the long-term consistency of rsfMRI connectivity maps derived at multiple sites and vendors using the Canadian Dementia Imaging Protocol (CDIP, www.cdip-pcid.ca). Nine to 10 min of functional BOLD images were acquired from an adult cognitively healthy volunteer scanned repeatedly at 13 Canadian sites on three scanner makes (General Electric, Philips and Siemens) over the course of 2.5 years. The consistency (spatial Pearson's correlation) of rsfMRI connectivity maps for seven canonical networks ranged from 0.3 to 0.8, with a negligible effect of time, but significant site and vendor effects. We noted systematic differences in data quality (i.e. head motion, number of useable time frames, temporal signal-to-noise ratio) across vendors, which may also confound some of these results, and could not be disentangled in this sample. We also pooled the long-term longitudinal data with a single-site, short-term (1 month) data sample acquired on 26 subjects (10 scans per subject), called HNU1. Using randomly selected pairs of scans from each subject, we quantified the ability of a data-driven unsupervised cluster analysis to match two scans of the same subjects. In this "fingerprinting" experiment, we found that scans from the Canadian subject (Csub) could be matched with high accuracy intra-site (>95% for some networks), but that the accuracy decreased substantially for scans drawn from different sites and vendors, even falling outside of the range of accuracies observed in HNU1. Overall, our results demonstrate good multivariate stability of rsfMRI measures over several years, but substantial impact of scanning site and vendors. How detrimental these effects are will depend on the application, yet our results demonstrate that new methods for harmonizing multisite analysis represent an important area for future work.

A novel patch-based procedure for estimating brain age across adulthood.

Aging is associated with structural alterations in many regions of the brain. Monitoring these changes contributes to increasing our understanding of the brain's morphological alterations across its lifespan, and could allow the identification of departures from canonical trajectories. Here, we introduce a novel and unique patch-based grading procedure for estimating a synthetic estimate of cortical aging in cognitively intact individuals. The cortical age metric is computed based on image similarity between an unknown (test) cortical label and known (training) cortical labels using machine learning algorithms. The proposed method was trained on a dataset of 100 cognitively intact individuals aged 19-61 years, within the 31 bilateral cortical labels of the Desikan-Killiany-Tourville parcellation, then tested on an independent test set of 78 cognitively intact individuals spanning a similar age range. The proposed patch-based framework yielded a R2 = 0.94, as well as a mean absolute error of 1.66 years, which compared favorably to the literature. These experimental results demonstrate that the proposed patch-based grading framework is a reliable and robust method to estimate brain age from image data, even with a limited training size.

The Canadian Dementia Imaging Protocol: Harmonizing National Cohorts.

BACKGROUND: Harmonized protocols to collect imaging data must be devised, employed, and maintained in multicentric studies to reduce interscanner variability in subsequent analyses. PURPOSE: To present a standardized protocol for multicentric research on dementia linked to neurodegeneration in aging, harmonized on all three major vendor platforms. The protocol includes a common procedure for qualification, quality control, and quality assurance and feasibility in large-scale studies. STUDY TYPE: Prospective. SUBJECTS: The study involved a geometric phantom, a single individual volunteer, and 143 cognitively healthy, mild cognitively impaired, and Alzheimer's disease participants in a large-scale, multicentric study. FIELD STRENGTH/SEQUENCES: MRI was perform with 3T scanners (GE, Philips, Siemens) and included 3D T1 w, PD/T2 w, T2* , T2 w-FLAIR, diffusion, and BOLD resting state acquisitions. ASSESSMENT: Measures included signal- and contrast-to-noise ratios (SNR and CNR, respectively), total brain volumes, and total scan time. STATISTICAL TESTS: SNR, CNR, and scan time were compared between scanner vendors using analysis of variance (ANOVA) and Tukey tests, while brain volumes were tested using linear mixed models. RESULTS: Geometric phantom T1 w SNR was significantly (P < 0.001) higher in Philips (mean: 71.4) than Siemens (29.5), while no significant difference was observed between vendors for T2 w (32.0 and 37.2, respectively, P = 0.243). Single individual volunteer T1 w CNR was higher in subcortical regions for Siemens (P < 0.001), while Philips had higher cortical CNR (P = 0.044). No significant difference in brain volumes was observed between vendors (P = 0.310/0.582/0.055). The average scan time was 41.0 minutes (SD: 2.8) and was not significantly different between sites (P = 0.071) and cognitive groups (P = 0.853). DATA CONCLUSION: The harmonized Canadian Dementia Imaging Protocol suits the needs of studies that need to ensure quality MRI data acquisition for the measurement of brain changes across adulthood, due to aging, neurodegeneration, and other etiologies. A detailed description, exam cards, and operators' manual are freely available at the following site: www.cdip-pcid.ca. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:456-465.

White Matter Damage in the Semantic Variant of Primary Progressive Aphasia.

BACKGROUND: The semantic variant of primary progressive aphasia (svPPA) is a form of dementia, mainly featuring language impairment, for which the extent of white matter (WM) damage is less described than its associated grey matter (GM) atrophy. Our study aimed to characterise the extent of this damage using a sensitive and unbiased approach. METHODS: We conducted a between-group study comparing 10 patients with a clinical diagnosis of svPPA, recruited between 2011 and 2014 at a tertiary reference centre, with 9 cognitively healthy, age-matched controls. From diffusion tensor imaging (DTI) data, we extracted fractional anisotropy (FA) values using a tract-based spatial statistics approach. We further obtained GM volumetric data using the Freesurfer automated segmentation tool. We compared both groups using non-parametric Wilcoxon rank-sum tests, correcting for multiple comparisons. RESULTS: Demographic data showed that patients and controls were comparable. As expected, clinical data showed lower results in svPPA than controls on cognitive screening tests. Tractography showed impaired diffusion in svPPA patients, with FA mostly decreased in the longitudinal, uncinate, cingulum and external capsule fasciculi. Volumetric data show significant atrophy in svPPA patients, mostly in the left entorhinal, amygdala, inferior temporal, middle temporal, superior temporal and temporal pole cortices, and bilateral fusiform gyri. CONCLUSIONS: This syndrome appears to be associated not only with GM but also significant WM degeneration. Thus, DTI could play a role in the differential diagnosis of atypical dementia by specifying WM damage specific to svPPA.

Des atteintes à la substance blanche du cerveau dans le cas de la variante sémantique de l'aphasie primaire progressive. Contexte: La variante dite « sémantique ¼ de l'aphasie primaire progressive (vsAPP) constitue une forme de démence de laquelle découlent principalement des troubles du langage. À l'inverse de l'atrophie de la substance grise associée à cette démence, on a été moins portés à décrire les atteintes à la substance blanche. Notre étude entend donc cerner l'étendue de ces atteintes au moyen d'une approche à la fois sensible et neutre. Méthodes: Nous avons effectué une étude intergroupe en comparant 10 patients ayant reçu un diagnostic clinique de vsAPP à 9 témoins en santé sur le plan cognitif. À noter que ces 10 patients ont été recrutés entre 2011 et 2014 dans un centre de soins médicaux tertiaires. C'est à partir de données obtenues grâce à l'imagerie par tenseur de diffusion (diffusion tensor imaging) que nous avons extrait, au moyen d'une approche privilégiant les statistiques spatiales basées sur les voies neuronales, des valeurs d'anisotropie fractionnelle (FA). Nous avons en outre obtenu des données volumétriques concernant la substance grise en utilisant l'outil de segmentation automatisée Freesurfer. Nous avons ensuite comparé ces deux groupes à l'aide de tests des rangs signés de Wilcoxon non-paramétriques, et ce, en veillant à appliquer une correction en vue de nombreuses comparaisons. Résultats: D'entrée de jeu, précisons que nos données démographiques ont révélé que les patients et les témoins étaient comparables. Comme il fallait s'y attendre, nos données cliniques ont montré, dans le cadre de tests de dépistage cognitif, que les résultats des patients atteints de vsAPP se sont révélés inférieurs à ceux des témoins. Des examens de tractographie ont par ailleurs montré une diffusion déficiente chez ces 10 patients, les valeurs de FA ayant surtout diminué dans les faisceaux longitudinaux et uncinés, dans le cingulum et la capsule externe. Quant à nos données volumétriques, elles ont révélé une atrophie notable chez les patients atteints de vsAPP, surtout dans les régions suivantes : cortex entorhinal gauche, amygdale, temporale inférieure, mésiotemporale, temporale supérieure, cortex temporo-polaires et lobules fusiformes bilatéraux. Conclusions: Le syndrome évoqué ci-dessus semble être associé non seulement à une dégénérescence de la substance grise mais aussi à une dégénérescence importante de la substance blanche. En précisant de manière spécifique l'atteinte à la substance blanche que sous-tend la vsAPP, l'imagerie par tenseur de diffusion pourrait donc être appelée à jouer un rôle dans l'établissement de diagnostics différentiels pour des démences atypiques.

The Comprehensive Assessment of Neurodegeneration and Dementia: Canadian Cohort Study.

BACKGROUND: The Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) cohort study of the Canadian Consortium on Neurodegeneration in Aging (CCNA) is a national initiative to catalyze research on dementia, set up to support the research agendas of CCNA teams. This cross-country longitudinal cohort of 2310 deeply phenotyped subjects with various forms of dementia and mild memory loss or concerns, along with cognitively intact elderly subjects, will test hypotheses generated by these teams. METHODS: The COMPASS-ND protocol, initial grant proposal for funding, fifth semi-annual CCNA Progress Report submitted to the Canadian Institutes of Health Research December 2017, and other documents supplemented by modifications made and lessons learned after implementation were used by the authors to create the description of the study provided here. RESULTS: The CCNA COMPASS-ND cohort includes participants from across Canada with various cognitive conditions associated with or at risk of neurodegenerative diseases. They will undergo a wide range of experimental, clinical, imaging, and genetic investigation to specifically address the causes, diagnosis, treatment, and prevention of these conditions in the aging population. Data derived from clinical and cognitive assessments, biospecimens, brain imaging, genetics, and brain donations will be used to test hypotheses generated by CCNA research teams and other Canadian researchers. The study is the most comprehensive and ambitious Canadian study of dementia. Initial data posting occurred in 2018, with the full cohort to be accrued by 2020. CONCLUSION: Availability of data from the COMPASS-ND study will provide a major stimulus for dementia research in Canada in the coming years.

Évaluation complète d'une étude de cohorte canadienne portant sur la démence et la neuro-dégénérescence. Contexte : L'évaluation globale de la neuro-dégénérescence et de la démence (COMPASS-ND), étude de cohorte du Consortium canadien en neuro-dégénérescence associée au vieillissement (CCNV), représente une initiative nationale visant à promouvoir la recherche portant sur la démence et à soutenir les programmes de recherche des équipes du CCNV. Totalisant 2310 sujets recrutés partout au pays, cette cohorte longitudinale regroupe des individus fortement « phénotypés ¼ qui présentent diverses formes de démence et de pertes de mémoire légères. En plus de sujets âgés dont les fonctions cognitives sont intactes, ces 2310 sujets ont permis de valider les hypothèses formulées par les équipes du CCNV. Méthodes : Nous avons utilisé de nombreux documents pour décrire cette étude : le protocole de la COMPASS-ND ; la demande initiale de subvention ; le cinquième rapport d'étape semi-annuel du CCNV soumis aux Instituts de recherche en santé du Canada (IRSC) en décembre 2017 ; ainsi que d'autres documents produits à la suite de modifications consécutives à la mise en œuvre de ce projet. Résultats: L'étude de cohorte COMPASS-ND du CCNV inclut des participants de partout au Canada dont les divers états cognitifs sont associés à des maladies neurodégénératives ou au risque d'en souffrir. Ils feront l'objet d'un large éventail d'examens expérimentaux, cliniques, génétiques et d'imagerie afin d'aborder de manière spécifique les causes, le diagnostic, le traitement et la prévention de ces états cognitifs chez les personnes âgées. Les données obtenues à la suite d'évaluations cliniques et cognitives, ainsi que celles issues d'échantillons biologiques, d'imagerie cérébrale, de tests génétiques et de dons de cerveaux, seront utilisées pour tester les hypothèses générées par les équipes de recherche du CCNV et d'autres chercheurs canadiens. Cette étude constitue donc à ce jour l'étude canadienne la plus complète et la plus ambitieuse au sujet de la démence. La présentation des données initiales ayant eu lieu en 2018, la cohorte devrait atteindre sa taille maximale d'ici à 2020.Conclusion : La disponibilité des données de l'étude COMPASS-ND stimulera considérablement la recherche sur la démence au Canada au cours des prochaines années.

Validation of an Magnetic Resonance Imaging Acquisition and Review Protocol for Alzheimer's Disease and Related Disorders.

PURPOSE: Magnetic resonance imaging (MRI) of the brain allows for the identification of structural lesions typical of Alzheimer's disease (AD), the main cause of dementia. However, to have a clinical impact, it is imperative that acquisition and reporting of this MRI-based evidence be standardized, ensuring the highest possible reliability and reproducibility. Our objective was to validate a systematic radiological MRI acquisition and review process in the context of AD. METHODS: We included 100 individuals with a suspicion of dementia due to AD for whom MRI were acquired using our proposed protocol of clinically achievable acquisitions and used a unified reading grid to gather semi-quantitative evidence guiding diagnostic. MRIs were read by 3 raters with different experience levels. Interrater reliability was measured using Cohen's kappa statistic. RESULTS: Interrater reliability average for lesions occupying space, hemorrhage, or ischemia, was respectively 0.754, 0.715, and 0.501. Average reliability of white matter hyperintensity burden (Fazekas), global cortical atrophy, and temporal lobe atrophy (Scheltens) scales was 0.687, 0.473, and 0.621 (right)/0.599 (left), respectively. The kappas for regional cortical atrophy (frontal, parietal, occipital, temporal, and posterior cingulum) varied from 0.281-0.678. The average MRI reading time varied between 1.43-5.22 minutes. CONCLUSIONS: The presence of space occupying lesions, hemorrhagic or ischemic phenomena, and radiological scales have a good interrater reproducibility in MRI. Coupled with standardized acquisitions, such a protocol should be used when evaluating possible dementias, especially those due to probable AD.

Diffusion tensor imaging correlates of early markers of depression in youth at high-familial risk for bipolar disorder.

BACKGROUND: Mood disorders are familial psychiatric diseases, in which patients show reduced white matter (WM) integrity. We sought to determine whether WM integrity was affected in young offspring at high-familial risk of mood disorder before they go on to develop major depressive disorder (MDD). METHODS: The Bipolar Family study is a prospective longitudinal study examining young individuals (age 16-25 years) at familial risk of mood disorder on three occasions 2 years apart. This study used baseline imaging data, categorizing groups according to clinical outcome at follow-up. Diffusion tensor MRI data were acquired for 61 controls and 106 high-risk individuals, the latter divided into 78 high-risk subjects who remained well throughout the study ('high-risk well') and 28 individuals who subsequently developed MDD ('high-risk MDD'). Voxel-wise between-group comparison of fractional anisotropy (FA) based on diagnostic status was performed using tract-based spatial statistics (TBSS). RESULTS: Compared to controls, both high-risk groups showed widespread decreases in FA (pcorr  < .05) at baseline. Although FA in the high-risk MDD group negatively correlated with subthreshold depressive symptoms at the time of scanning (pcorr  < .05), there were no statistically significant differences at p-corrected levels between the two high-risk groups. CONCLUSIONS: These results suggest that decreased FA is related to the presence of familial risk for mood disorder along with subdiagnostic symptoms at the time of scanning rather than predictive of subsequent diagnosis. Due to the difficulties performing such longitudinal prospective studies, we note, however, that this latter analysis may be underpowered due to sample size within the high-risk MDD group. Further clinical follow-up may clarify these findings.

Normative morphometric data for cerebral cortical areas over the lifetime of the adult human brain.

Proper normative data of anatomical measurements of cortical regions, allowing to quantify brain abnormalities, are lacking. We developed norms for regional cortical surface areas, thicknesses, and volumes based on cross-sectional MRI scans from 2713 healthy individuals aged 18 to 94 years using 23 samples provided by 21 independent research groups. The segmentation was conducted using FreeSurfer, a widely used and freely available automated segmentation software. Models predicting regional cortical estimates of each hemisphere were produced using age, sex, estimated total intracranial volume (eTIV), scanner manufacturer, magnetic field strength, and interactions as predictors. The explained variance for the left/right cortex was 76%/76% for surface area, 43%/42% for thickness, and 80%/80% for volume. The mean explained variance for all regions was 41% for surface areas, 27% for thicknesses, and 46% for volumes. Age, sex and eTIV predicted most of the explained variance for surface areas and volumes while age was the main predictors for thicknesses. Scanner characteristics generally predicted a limited amount of variance, but this effect was stronger for thicknesses than surface areas and volumes. For new individuals, estimates of their expected surface area, thickness and volume based on their characteristics and the scanner characteristics can be obtained using the derived formulas, as well as Z score effect sizes denoting the extent of the deviation from the normative sample. Models predicting normative values were validated in independent samples of healthy adults, showing satisfactory validation R2. Deviations from the normative sample were measured in individuals with mild Alzheimer's disease and schizophrenia and expected patterns of deviations were observed.

Freesurfer cortical normative data for adults using Desikan-Killiany-Tourville and ex vivo protocols.

We recently built normative data for FreeSurfer morphometric estimates of cortical regions using its default atlas parcellation (Desikan-Killiany or DK) according to individual and scanner characteristics. We aimed to produced similar normative values for Desikan-Killianny-Tourville (DKT) and ex vivo-based labeling protocols, as well as examine the differences between these three atlases. Surfaces, thicknesses, and volumes of cortical regions were produced using cross-sectional magnetic resonance scans from the same 2713 healthy individuals aged 18-94 years as used in the reported DK norms. Models predicting regional cortical estimates of each hemisphere were produced using age, sex, estimated intracranial volume (eTIV), scanner manufacturer and magnetic field strength (MFS) as predictors. The DKT and DK models generally included the same predictors and produced similar R2. Comparison between DK, DKT, ex vivo atlases normative cortical measures showed that the three protocols generally produced similar normative values.

Voxel-based morphometry meta-analysis of gray and white matter finds significant areas of differences in bipolar patients from healthy controls.

OBJECTIVE: We present a retrospective meta-analysis of voxel-based morphometry (VBM) of gray (GM) and white matter (WM) differences between patients with bipolar disorder (BD) and behaviorally healthy controls. METHODS: We used the activation likelihood estimation and Sleuth software for our meta-analysis, considering P-value maps at the cluster level inference of .05 with uncorrected P<.001. Results were visualized with the software MANGO. RESULTS: We included twenty-five articles in the analysis, and separated the comparisons where BD patients had lower GM or WM concentrations than controls (573 subjects, 21 experiments, and 117 locations/180 subjects, five experiments, and 15 locations, respectively) and the comparisons where BD patients had greater GM concentrations than controls (217 subjects, nine experiments, and 49 locations). Higher WM concentrations in BD patients were not detected. We observed for BD reduced GM concentrations in the left medial frontal gyrus and right inferior/precentral gyri encompassing the insular cortex, and greater GM concentrations in the left putamen. Further, lower WM concentrations were detected in the left inferior longitudinal fasciculus, left superior corona radiata, and left posterior cingulum. CONCLUSIONS: This meta-analysis confirms deterioration of frontal and insular regions as already found in previous meta-analysis. GM reductions in these regions could be related to emotional processing and decision making, which are typically impaired in BD. Moreover, we found abnormalities in precentral frontal areas and putamen that have been linked to more basic functions, which could point to sensory and specific cognitive deficits. Finally, WM reductions involved circuitry that may contribute to emotional dysregulation in BD.

Longitudinal differences in white matter integrity in youth at high familial risk for bipolar disorder.

OBJECTIVES: Previous neuroimaging studies have reported abnormalities in white matter (WM) pathways in subjects at high familial risk of mood disorders. In the current study, we examined the trajectory of these abnormalities during the early stages of illness development using longitudinal diffusion tensor imaging (DTI) data. METHODS: Subjects (16-28 years old) were recruited in the Scottish Bipolar Family Study, a prospective longitudinal study that has examined individuals at familial risk of mood disorder on three occasions, 2 years apart. The current study concerns imaging data from the first and second assessments. We analysed DTI data for 43 controls and 69 high-risk individuals who were further subdivided into a group of 53 high-risk subjects who remained well (high-risk well) and 16 who met diagnostic criteria for major depressive disorder (high-risk MDD) at follow-up. Longitudinal differences in fractional anisotropy (FA) between groups based on diagnostic status were investigated using the tract-based spatial statistics technique (TBSS). RESULTS: We found a significant reduction in FA (Pcorr <.05) across widespread brain regions over 2 years in all three groups. The trajectory of FA reduction did not differ significantly between groups. CONCLUSIONS: These results suggest that there are similar trajectories of FA reductions for controls and high-risk young adults, despite high-risk individuals being at a disadvantaged starting point considering their reduced WM integrity detected at baseline in previous studies. Difference in WM integrity between high-risk individuals and controls could therefore occur in earlier childhood and be a necessary but not sufficient condition to develop future mood disorders.