Biology subjects

Dadar, M.

Publications and source records attributed to Dadar, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

The Douglas Bell Canada Brain Bank Post-mortem Brain Imaging Protocol

Magnetic resonance imaging (MRI) is a valuable non-invasive tool that has been widely used for in vivo investigations of brain morphometry and microstructural characteristics. Postmortem MRIs can provide complementary anatomical and microstructural information to in vivo imaging and ex vivo neuropathological assessments without compromising the sample for future investigations. We have developed a postmortem MRI protocol for the brain specimens of the Douglas-Bell Canada Brain Bank (DBCBB), the largest brain bank in Canada housing over 3000 neurotypical and diseased brain specimens, that allows for acquisition of high-resolution 3T and 7T MRIs. Our protocol can be used to scan DBCBB specimens with minimal tissue manipulation, allowing for feasibly scanning large numbers of postmortem specimens while retaining the quality of the tissue for downstream histology and immunohistochemistry assessments. We demonstrate the robustness of this protocol in spite of the dependency of image quality on fixation by acquiring data on the first day of extraction and fixation, to over twenty years post fixation. The acquired images can be used to perform volumetric segmentations, cortical thickness measurements, and quantitative analyses which can be potentially used to link MRI-derived and ex vivo histological measures, assaying both the normative organization of the brain and ex vivo measures of pathology.

neuroscience↗

bioRxiv2024

Comparison of histological procedures and antigenicity of human post-mortem brains fixed with solutions used in gross anatomy laboratories

BackgroundBrain banks provide small tissue samples to researchers, while gross anatomy laboratories could provide larger samples, including complete brains to neuroscientists. However, they are preserved with solutions appropriate for gross-dissection, different from the classic neutral-buffered formalin (NBF) used in brain banks. Our previous work in mice showed that two gross-anatomy laboratory solutions, a saturated-salt-solution (SSS) and an alcohol-formaldehyde-solution (AFS), preserve antigenicity of the main cellular markers. Our goal is now to compare the quality of histology and antigenicity preservation of human brains fixed with NBF by immersion (practice of brain banks) vs. those fixed with a SSS and an AFS by whole body perfusion, practice of gross-anatomy laboratories. MethodsWe used a convenience sample of 42 brains (31 males, 11 females; 25-90 years old) fixed with NBF (N=12), SSS (N=13), and AFS (N=17). One cm3 tissue blocks were cut, cryoprotected, frozen and sliced into 40 m sections. The four cell populations were labeled using immunohistochemistry (neuronal-nuclei (NeuN), glial-fibrillary-acidic-protein (GFAP), ionized-calcium-binding-adaptor-molecule1 (Iba1) and myelin-proteolipid-protein (PLP)). We qualitatively assessed antigenicity and cell distribution, and compared the ease of manipulation of the sections, the microscopic tissue quality, and the quality of common histochemical stains (e.g., Cresyl violet, Luxol fast blue, etc.) across solutions. ResultsSections of SSS-fixed brains were more difficult to manipulate and showed poorer tissue quality than those from brains fixed with the other solutions. The four antigens were preserved, and cell labeling was more often homogenous in AFS-fixed specimens. NeuN and GFAP were not always present in the NBF and SSS samples. Some antigens were heterogeneously distributed in some specimens, independently of the fixative, but an antigen retrieval protocol successfully recovered them. Finally, the histochemical stains were of sufficient quality regardless of the fixative, although neurons were more often paler in SSS-fixed specimens. ConclusionAntigenicity was preserved in human brains fixed with solutions used in human gross-anatomy (albeit the poorer quality of SSS-fixed specimens). For some specific variables, histology quality was superior in AFS-fixed brains. Furthermore, we show the feasibility of frequently used histochemical stains. These results are promising for neuroscientists interested in using brain specimens from anatomy laboratories.

neuroscience↗

bioRxiv2023

Serum levels of adipokines and insulin are associated with markers of brain atrophy and cognitive decline in the spectrum of Alzheimer's Disease

The discovery that metabolic alterations often coexist with neurodegenerative conditions has sparked interest in the examination of gastrointestinal factors as potential modulators of brain health. Here, we examined the role of adipokines (leptin, adiponectin, resistin, and IL6) and insulin on different markers of brain atrophy in participants on the spectrum of Alzheimers Disease. We included 566 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset with 1063 follow-up time points (average follow-up: one year); and examined the association between gastrointestinal factors and volumetric MRI values, white matter hyperintensities, and measures of cognitive impairment. Higher leptin, resistin, IL6, and insulin were associated with markers of cerebral atrophy, such as lower total brain volume, or higher ventricular volume. Higher leptin and resistin were also associated with greater impairment in daily life activities. Higher adiponectin was associated with lower ventricle volume. There was no association between adipokines or insulin with white matter hyperintensities. Our findings indicate a co-occurrence between alterations in gastrointestinal factors and in brain volume along the preclinical to clinical spectrum of Alzheimers Disease. These results suggest that strategies aimed at promoting metabolic health may positively impact brain health.

neuroscience↗

bioRxiv2023

Investigating the impact of motion in the scanner on brain age predictions

IntroductionBrain Age Gap (BAG) is defined as the difference between the brains predicted age and the chronological age of an individual. Magnetic resonance imaging (MRI)-based BAG can quantify acceleration of brain aging, and is used to infer brain health as aging and disease interact. Motion in the scanner is a common occurrence that can affect the acquired MRI data and act as a major confound in the derived models. As such, age-related changes in head motion may impact the observed age-related differences. However, the relationship between head motion and BAG as estimated by structural MRI has not been systematically examined. The aim of this study is to assess the impact of motion on voxel-based morphometry (VBM) based BAG. MethodsData were obtained from two sources: i) T1-weighted (T1w) MRIs from the Cambridge Centre for Ageing and Neuroscience (CamCAN) were used to train the brain age prediction model, and ii) T1w MRIs from the Movement-related artifacts (MR-ART) dataset were used to assess the impact of motion on BAG. MR-ART includes one motion-free and two motion-affected (one low and one high) 3D T1w MRIs. We also visually rated the motion levels of the MR-ART MRIs from 0 to 5, with 0 meaning no motion and 5 high motion levels. All images were pre-processed through a standard VBM pipeline. GM density across cortical and subcortical regions were then used to train the brain age prediction model and assess the relationship between BAG and MRI motion. Principal component analysis was used to perform dimension reduction and extract the VBM-based features. BAG was estimated by regressing out the portion of delta age explained by chronological age. Linear mixed effects models were used to investigate the relationship between BAG and motion session as well as motion severity, including participant IDs as random effects. We repeated the same analysis using cortical thickness based on FreeSurfer 7.4.1 and to compare the results for volumetric versus surface-based measures of brain morphometry. ResultsIn contrast with the session with no induced motion, predicted delta age was significantly higher for high motion sessions 2.35 years (t = 5.17, p < 0.0001), with marginal effect for low motion sessions 0.95 years (t = 2.11, p=0.035) for VBM analysis as well as 3.46 years (t = 11.45, p < 0.0001) for high motion and 2.28 years (t = 7.54, p<0.0001) for low motion based on cortical thickness. In addition, delta age was significantly associated with motion severity as evaluated by visual rating 0.45 years per rating level (t = 4.59, p < 0.0001) for VBM analysis and 0.83 years per motion level (t = 12.89, p<0.0001) for cortical thickness analysis. ConclusionMotion in the scanner can significantly impact brain age estimates, and needs to be accounted for as a confound, particularly when studying populations that are known to have higher levels of motion in the scanner. These results have significant implications for brain age studies in aging and neurodegeneration. Based on these findings, we recommend assessment and inclusion of visual motion ratings in such studies. In cases that the visual rating proves prohibitive, we recommend the inclusion of normalized Euler number from FreeSurfer as defined in the manuscript as a covariate in the models.

neuroscience↗

bioRxiv2023

Nucleus basalis of Meynert degeneration signals earliest stage of Alzheimer's disease progression

The Nucleus Basalis of Meynert (NbM) is the main source of cholinergic projection to the entorhinal cortex (EC) and hippocampus (HC), where acetylcholine plays a key role in their function. Both cholinergic cells of NbM and their receptive targets in the EC and HC show sensitivity to neurofibrillary degeneration during the early stages of Alzheimers disease. Precise delineation of the NbM region on T1w scans is challenging due to limited spatial resolution and contrast. Using deformation-based morphometry (DBM), we sought to quantify NbM degeneration along the Alzheimers disease trajectory and confirm recent studies suggesting that NbM degeneration happens before degeneration in the EC or HC. MRI scans of 1447 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI1, 2 and GO) were up-sampled to 0.5 mm voxel-size in each direction (0.125 mm3) before non-linear registration to an ADNI-based unbiased symmetric average MRI template. A subgroup of 677 amyloid-positive participants were chosen for volume time course analysis where the resulting deformation fields were used to compute a high-resolution Jacobian determinant map for each participant as a proxy for local volume change within NbM, EC, and HC masks. Scores of volume change were corrected for age and sex and z-scored using normative data from cognitively healthy amyloid-negative (CN-) participants (n = 219). Two-sample t-tests were then used to compare the baseline differences between NbM, EC, and HC for amyloid-positive cognitively normal controls (CN+), amyloid-positive early mild cognitive impairment (eMCI), and amyloid-positive late mild cognitive impairment (lMCI). Longitudinal linear mixed-effect models were used to compare trajectories of volume change after realigning all participants into a common timeline based on their cognitive decline. Results showed a significant cross-sectional difference at baseline between CN+ and eMCI, and eMCI and lMCI for both left and right Z-scored NbM volumes. There was no difference in z-scored EC and HC volumes between CN+ and eMCI groups but results from eMCI and lMCI differed significantly in these regions. Longitudinal analysis, with a focus on the early disease stages showed the earliest deviation from the CN- trajectory in the NbM and HC in the subject-specific time realigned data. Contrary to the notion that Alzheimers disease originates in EC, we found that NbM volume changes earlier in the disease trajectory than EC or HC. Converging evidence from cross-sectional and longitudinal models suggest that the NbM may be a focal target of early AD progression, which is often obscured by normal age-related decline.

bioinformatics↗

bioRxiv2023

Distinctive Whole-brain Cell-Types Strongly Predict Tissue Damage Patterns in Eleven Neurodegenerative Disorders

For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuronal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in thirteen neurodegenerative conditions, including early-and late-onset Alzheimers disease, Parkinsons disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and three clinical variants of frontotemporal lobar degeneration (behavioural variant, semantic and non-fluent primary progressive aphasia) along with associated 3-repeat and 4-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorders pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.

neuroscience↗

bioRxiv2023

FONDUE: Robust resolution-invariant denoising of MR Images using Nested UNets

Recent human neuroimaging studies tend to have increased magnetic resonance image (MRI) acquisition resolutions, seeking finer levels of detail and more accurate brain morphometry. However, higher-resolution images inherently contain greater amounts of noise contamination, leading to poorer quality brain morphometry if not addressed adequately. This study proposes a novel, robust, resolution-invariant deep learning method to denoise structural human brain MRIs. We explore denoising of T1-weighted (T1w) brain images from varying field strengths (1.5T to 7T), voxel sizes (1.2mm to 250{micro}m), scanner vendors (Siemens, GE, and Phillips), and diseased and healthy participants from a wide age range (young adults to aging individuals). Our proposed Fast-Optimized Network for Denoising through residual Unified Ensembles (FONDUE) method demonstrated stable denoising capabilities across multiple resolutions with performance comparable to the state-of-the-art methods. FONDUE was capable of denoising 0.5mm3 isotropic T1w images in under 3 minutes on an NVIDIA RTX 3090 GPU using less than 8GB of video memory. We have also made the repository of FONDUE as well as its trained weights publicly available on: https://github.com/waadgo/FONDUE.

neuroscience↗

bioRxiv2023

Assessment of white matter hyperintensity severity using multimodal MRI in Alzheimer's Disease

White matter hyperintensities (WMHs) are clinically significant MRI abnormalities often detected in the elderly and early stages of Alzheimers Disease. They are indicative of vascular pathology but represent a mixture of microstructural tissue alterations that is highly variable between individuals. To better understand these alterations, we leveraged the signal of different MRI contrasts sampled within WMHs, which have differential sensitivity to microstructural properties. Subsequently, we sought to examine the asso of these WMH signal measures to clinically-relevant measures such as cortical and global brain atrophy, cognitive function, diagnostic and demographic differences, and Alzheimers Disease-relevant cardiovascular risk factors. Our sample of 118 subjects was composed of healthy controls (n=30), high-risk of Alzheimers Disease due to familial history (n=47), mild cognitive impairment (n=32), and clinical Alzheimers Disease (n=9) as a means of ascertaining a spectrum of impairment. We sampled the median signal within WMHs on weighted MRI images that are commonly acquired (T1-weighted [T1w], T2-weighted [T2w], T1w/T2w ratio, Fluid-Attenuated Inversion Recovery [FLAIR]), and the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. Main analyses were performed with a periventricular/deep/superficial white matter parcellation and were repeated with a lobar white matter parcellation. We demonstrated that the correlations between WMH signal measures were variable, suggesting that they are likely influenced by different microstructural properties. We observed that the WMH qT2* and FLAIR measures displayed different age- and disease-related trends compared to normal-appearing white matter, highlighting sensitivity to WMH-specific tissue deterioration. Further, WMH qT2* particularly in periventricular and occipital white matter regions was consistently associated with several of our clinical variables of interest using both parcellation schemes in univariate analyses, and further showed high contributions to a pattern of brain variables that was associated with age and cognitive variables in multivariate Partial Least Squares Correlation analyses. qT1 and FLAIR measures showed consistent clinical relationships in multivariate analyses only, while T1w, T2w, and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to WMHs. Combining volumetric and signal measures of WMH, particularly qT2* and to a lesser extent qT1 and FLAIR, should be considered to more precisely characterize the severity of WMHs in vivo. These findings may have implications in determining the reversibility of WMHs and potential efficacy of cardio- and cerebrovascular treatments.

neuroscience↗

bioRxiv2022

QRATER: a collaborative and centralized imaging quality control web-based application.

Quality control (QC) is an important part of all scientific analysis, including neuroscience. With manual curation considered the gold standard, there remains a lack of available tools that make manual neuroimaging QC accessible, fast, and easy. In this article we present Qrater, a containerized web-based python application that enables viewing and rating of previously generated QC images. A group of raters with varying amounts of experience in QC evaluated Qrater in three different tasks: QC of MRI raw acquisition (10,196 images), QC of non-linear registration to a standard template (10,196 images) and QC of skull segmentation (6,968 images). We measured the proportion of failed images, timing and intra- and inter-rater agreement. Raters spent vastly different amounts of time on each image depending on their experience and the task at hand. QC of MRI raw acquisition was the slowest. While an expert rater needed approximately one minute, trained raters spent 2-6 minutes evaluating an image. The fastest was the curation of a skull segmentation image, where expert raters spent on average 3 seconds per image before assigning a rating. Rating agreement also varied depending on the experience of the raters and the task at hand: trained raters inter-rater agreement with the experts gold standard ranged from fair to substantial in raw acquisition (Cohens chance corrected kappa agreement scores up to 0.72) and from fair to excellent in linear registration (kappa scores up to 0.82), while the experts inter-rater agreement of the skull segmentation task was excellent (kappa = 0.83). These results demonstrate that Qrater is a useful asset for QC tasks that rely on manual curation of images.

bioinformatics↗

bioRxiv2022

Antigenicity is preserved with fixative solutions used in human gross anatomy: A mice brain immunohistochemistry study.

BackgroundHistology remains the gold standard to assess human brain biology, so ex vivo studies using tissue from brain banks are standard practice in neuroscientific research. However, a larger number of specimens could be obtained from gross anatomy laboratories. These specimens are fixed with solutions appropriate for dissections, but whether they also preserve brain tissue antigenicity is unclear. Therefore, we perfused mice brains with solutions used for human body preservation to assess and compare the tissue quality and antigenicity of the main cell populations. Methods28 C57BL/6J mice were perfused with: 4% formaldehyde (FAS, N=9), salt-saturated solution (SSS, N=9), and alcohol-solution (AS, N=10). The brains were cut into 40m sections for antigenicity analysis and were assessed by immunohistochemistry of four antigens: neuronal nuclei (NeuN), glial fibrillary acidic protein (GFAP-astrocytes), ionized calcium binding adaptor molecule1 (Iba1-microglia), and myelin proteolipid protein (PLP). We compared the fixatives according to multiple variables: perfusion quality, ease of manipulation, tissue quality, immunohistochemistry quality, and antigenicity preservation. ResultsThe perfusion quality was better using FAS and worse using AS. The manipulation was very poor in SSS brains. FAS and AS fixed brains showed higher tissue and immunohistochemistry quality than the SSS brains. All antigens were readily observed in every specimen, regardless of the fixative solution. ConclusionSolutions designed to preserve specimens for human gross anatomy dissections also preserve tissue antigenicity in different brain cells. This offers opportunities for the use of human brains fixed in gross anatomy laboratories to assess normal or pathological conditions. SIGNIFICANCE STATEMENTNeuroscientists currently obtain tissue samples from brain banks. Alternatively, a much larger amount of tissue may be obtained from bodies donated to gross anatomy laboratories. However, they are preserved with different fixative solutions that are used for dissection purposes. We ignore if these solutions also preserve antigenicity of the main cell populations, essential in neuroscientific research. This work is the first to show that two solutions currently used in human gross anatomy laboratories preserve sufficient histological quality, in addition to preserve antigenicity of the main cell populations of the mice brain. This work opens the door to the use of human brain tissue obtained from anatomy laboratories in neuroscientific research.

neuroscience↗

bioRxiv2022

Using Transfer Learning for Automated Microbleed Segmentation

IntroductionCerebral microbleeds are small perivascular haemorrhages that can occur in both grey and white matter brain regions. Microbleeds are a marker of cerebrovascular pathology, and are associated with an increased risk of cognitive decline and dementia. Microbleeds can be identified and manually segmented by expert radiologists and neurologists, usually from susceptibility-contrast MRI. The latter is hard to harmonize across scanners, while manual segmentation is laborious, time-consuming, and subject to inter- and intra-rater variabiltiy. Automated techniques so far have shown high accuracy at a neighborhood ("patch") level at the expense of a high number of false positives voxel-wise lesions. We aimed to develop an automated, more precise microbleeds segmentation tool able to use standardizable MRI contrasts. MethodsWe first trained a ResNet50 network on another MRI segmentations task (cerberospinal fluid versus background segmentation) using T1-weighted, T2-weighted, and T2* MRI. We then used transfer learning to train the network for the detection of microbleeds with the same contrasts. As a final step, we employed a combination of morphological operators and rules at the local lesion level to remove false positives. Manual segmentations of microbleeds from 78 participants were used to train and validate the system. We assessed the impact of patch size, freezing weights of the initial layers, mini-batch size, learning rate, as well as data augmentation on the performance of the Microbleed ResNet50 network. ResultsThe proposed method achieved a high performance, with a patch-level sensitivity, specificity, and accuracy of 99.57%, 99.16%, and 99.93%, respectively. At a per lesion level, sensitivity, precision, and Dice similarity index values were 89.1%, 20.1%, and 0.28 for cortical GM; 100%, 100%, and 1.0 for deep GM; and 91.1%, 44.3%, and 0.58 for WM, respectively. DiscussionThe proposed microbleed segmentation method is more suitable for the automated detection of microbleeds with high sensitivity.

neuroscience↗

bioRxiv2021

White Matter Hyperintensity Distribution Differences in Aging and Neurodegenerative Disease Cohorts

IntroductionWhite matter hyperintensities (WMHs) are common magnetic resonance imaging (MRI) findings in the aging population in general, as well as in patients with neurodegenerative diseases. They are known to exacerbate the cognitive deficits and worsen the clinical outcomes in the patients. However, it is not well-understood whether there are disease-specific differences in prevalence and distribution of WMHs in different neurodegenerative disorders. MethodsData included 976 participants with cross-sectional T1-weighted and fluid attenuated inversion recovery (FLAIR) MRIs from the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) cohort of the Canadian Consortium on Neurodegeneration in Aging (CCNA) with eleven distinct diagnostic groups: cognitively intact elderly (CIE), subjective cognitive impairment (SCI), mild cognitive impairment (MCI), vascular MCI (V-MCI), Alzheimers dementia (AD), vascular AD (V-AD), frontotemporal dementia (FTD), Lewy body dementia (LBD), cognitively intact elderly with Parkinsons disease (PD-CIE), cognitively impaired Parkinsons disease (PD-CI), and mixed dementias. WMHs were segmented using a previously validated automated technique. WMH volumes in each lobe and hemisphere were compared against matched CIE individuals, as well as each other, and between men and women. ResultsAll cognitively impaired diagnostic groups had significantly greater overall WMH volumes than the CIE group. Vascular groups (i.e. V-MCI, V-AD, and mixed dementia) had significantly greater WMH volumes than all other groups, except for FTD, which also had significantly greater WMH volumes than all non-vascular groups. Women tended to have lower WMH burden than men in most groups and regions, controlling for age. The left frontal lobe tended to have a lower WMH burden than the right in all groups. In contrast, the right occipital lobe tended to have greater WMH loads than the left. ConclusionsThere were distinct differences in WMH prevalence and distribution across diagnostic groups, sexes, and in terms of asymmetry. WMH burden was significantly greater in all neurodegenerative dementia groups, likely encompassing areas exclusively impacted by neurodegeneration as well as areas related to cerebrovascular disease pathology.

neuroscience↗

bioRxiv2021

White matter hyperintensities may be an early marker for age-related cognitive decline in the ADNI cohort

BackgroundResearch suggests that cerebral small vessel disease (CSVD), amyloid, and pTau contribute to age-related cognitive decline. It remains unknown how these factors relate to one another, nor how they jointly contribute to cognitive decline in normal aging. This project examines the association between these pathologies and their relationship to cognitive decline in cognitively normal older adults without subjective cognitive decline. MethodsA total of 230 subjects with CSF A{beta}42, CSF pTau181, white matter hyperintensities (WMHs) used as a proxy of CSVD and cognitive scores from the Alzheimers Disease Neuroimaging Initiative were included. Associations between each pathology and cognitive score were investigated using regression models. Furthermore, relationships between the three pathologies were also examined using regression models. ResultsAt baseline, there was an inverse association between WMH load and A{beta}42 (t=-4.20, p<.001). There was no association between WMH load and pTau (t=0.32, p=0.75), nor with A{beta}42 and pTau (t=0.51, p=.61). Correcting for age, sex and education, baseline WMH load was associated with baseline ADAS-13 scores (t=2.59, p=.01) and lower follow-up executive functioning (t= -2.84, p=.005). Baseline A{beta}42 was associated with executive function at baseline (t=3.58, p<.004) but not at follow-up (t=1.05, p=0.30), nor with ADAS-13 at baseline (t=-0.24, p0.81) or follow-up (t=0.09, p=0.93). Finally, baseline pTau was not associated with any cognitive measure at baseline or follow-up. ConclusionBoth baseline A{beta}42 and WMH load are associated with some baseline cognition scores, but only baseline WMH load is associated with follow-up executive functioning, indicating that it may be one of the earliest pathologies that contributes to future cognitive decline, in cognitively healthy older adults. Given that healthy older adults with WMH pathology exhibit declines in cognitive functioning, they may be less resilient to future pathology increasing their risk for cognitive impairment due to dementia than those without WMHs.

neuroscience↗

bioRxiv2021

Global network structure and local transcriptomic vulnerability shape atrophy in sporadic and genetic behavioral variant frontotemporal dementia

Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioral variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). We first identify distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbors, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicenter of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and anteromedial temporal areas. Finally, we find that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, effectively modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability.

neuroscience↗

bioRxiv2021

DARQ: Deep learning of quality control for stereotaxic registration of human brain MRI

Linear registration to stereotaxic space is a common first step in many automated image-processing tools for analysis of human brain MRI scans. This step is crucial for the success of the subsequent image-processing steps. Several well-established algorithms are commonly used in the field of neuroimaging for this task, but none have a 100% success rate. Manual assessment of the registration is commonly used as part of quality control. To reduce the burden of this time-consuming step, we propose Deep Automated Registration Qc (DARQ), a fully automatic quality control method based on deep learning that can replace the human rater and accurately perform quality control assessment for stereotaxic registration of T1w brain scans. In a recently published study from our group comparing linear registration methods, we used a database of 9325 MRI scans and 64476 registrations from several publicly available datasets and applied seven linear registration tools to them. In this study, the resulting images that were assessed and labeled by a human rater are used to train a deep neural network to detect cases when registration failed. We further validated the results on an independent dataset of patients with multiple sclerosis, with manual QC labels available (n=1200). In terms of agreement with a manual rater, our automated QC method was able to achieve 89%accuracy and 85% true negative rate (equivalently 15% false positive rate) in detecting scans that should pass quality control in a balanced cross-validation experiments, and 96.1% accuracy and 95.5% true negative rate (or 4.5% FPR) when evaluated in a balanced independent sample, similar to manual QC rater (test-retest accuracy of 93%). The results show that DARQ is robust, fast, accurate, and generalizable in detecting failure in linear stereotaxic registrations and can substantially reduce QC time (by a factor of 20 or more) when processing large datasets.

neuroscience↗

bioRxiv2021

Diffusely abnormal white matter converts to T2 lesion volume in the absence of acute inflammation

Diffusely abnormal white matter (DAWM), characterised by biochemical changes of myelin in the absence of frank demyelination, has been associated with clinical progression in secondary progressive MS (SPMS). However, little is known about changes of DAWM over time and their relation to focal white matter lesions (FWML). The objectives of this work were: 1) To characterize the longitudinal evolution of FWML, DAWM, and DAWM that transforms into FWML, and 2) To determine whether gadolinium enhancement, known to be associated with the development of new FWML, is also related to DAWM voxels that transform into FWML. Our data included 4220 MRI scans of 689 SPMS participants, followed for 156 weeks and 2677 scans of 686 RRMS participants, followed for 96 weeks. FWML and DAWM were segmented using a previously validated, automatic thresholding technique based on normalized T2 intensity values. Using longitudinally registered images, DAWM voxels at each visit that transformed into FWML on the last MRI scan as well as their overlap with gadolinium enhancing lesion masks were identified. Our results showed that the average yearly rate of conversion of DAWM-to-FWML was 1.27cc for SPMS and 0.80cc for RRMS. FWML in SPMS participants significantly increased (t=3.9; p=0.0001) while DAWM significantly decreased (t=-4.3 p<0.0001) and the ratio FWML:DAWM increased (t=12.7; p<0.00001). RRMS participants also showed an increase in the FWML:DAWM Ratio (t=6.9; p<0.00001) but without a significant change of the individual volumes. Gadolinium enhancement was associated with 7.3% and 18.7% of focal New T2 lesion formation in the infrequent scans of the RRMS and SPMS cohorts, respectively. In comparison, only 0.1% and 0.0% of DAWM-to-FWML voxels overlapped with gadolinium enhancement. We conclude that DAWM transforms into FWML over time, in both RRMS and SPMS. DAWM appears to represent a form of pre-lesional pathology that contributes to T2 lesion volume increase over time, independent of new focal inflammation and gadolinium enhancement.

neuroscience↗

bioRxiv2021

White Matter Hyperintensities, Grey Matter Atrophy, and Cognitive Decline in Neurodegenerative Diseases

IntroductionWhite matter hyperintensities (WMHs) as seen on T2w and FLAIR scans represent small-vessel disease related changes in the brain. WMHs are associated with cognitive decline in the normal aging population in general and more specifically in patients with neurodegenerative diseases. In this study, we assessed the different spatial patterns and relationships between WMHs and grey matter (GM) atrophy in normal aging, individuals with mild cognitive impairment (MCI), Alzheimers dementia (AD), fronto-temporal dementia (FTD), and de novo Parkinsons disease (PD). MethodsImaging and clinical data were obtained from 3 large multi-center databases: The Alzheimers Disease Neuroimaging Initiative (ADNI), the frontotemporal lobar degeneration neuroimaging initiative (NIFD), and the Parkinsons Progression Markers Initiative (PPMI). WMHs and GM atrophy maps were measured in normal controls (N= 571), MCI (N= 577), AD (N= 222), FTD (N= 144), and PD (N= 363). WMHs were segmented using T1w and T2w/PD or FLAIR images and mapped onto 45 white matter tracts using the Yeh WM atlas. GM volume was estimated from the Jacobian determinant of the nonlinear deformation field required to map the subjects MRI to a standard template. The CerebrA atlas was used to obtain volume estimates in 84 GM regions. Mixed effects models were used to compare WMH in different WM tracts and volume of multiple GM structures between patients and controls, assess the relationship between regional WMHs and GM loss for each disease, and investigate their impact on cognition. ResultsMCI, AD, and FTD patients had significantly higher WMH loads than the matched controls. There was no significant difference in WMHs between PD and controls. For each cohort, significant interactions between WMH load and GM atrophy were found for several regions and tracts, reflecting additional contribution of WMH burden to GM atrophy. While these associations were more relevant for insular and parieto-occipital regions in MCI and AD cohorts, WMH burden in FTD subjects had greater impact on frontal and basal ganglia atrophy. Finally, we found additional contribution of WMH burden to cognitive deficits in AD and FTD subjects compared with matched controls, whereas their impact on cognitive performance in MCI and PD were not significantly different from controls. ConclusionsWMHs occur more extensively in MCI, AD, and FTD patients than age-matched normal controls. WMH burden on WM tracts also correlates with regional GM atrophy in regions anatomically and functionally related to those tracts, suggesting a potential involvement of WMHs in the neurodegenerative process.

neuroscience↗

bioRxiv2021

Spontaneous Neural Activity Changes after Bariatric Surgery: a resting-state fMRI study

1.BackgroundMetabolic disorders associated with obesity could lead to alterations in brain structure and function. Whether these changes can be reversed after weight loss is unclear. Bariatric surgery provides a unique opportunity to address these questions because it induces marked weight loss and metabolic improvements which in turn may impact the brain in a longitudinal fashion. Previous studies found widespread changes in grey matter (GM) and white matter (WM) after bariatric surgery. However, findings regarding changes in spontaneous neural activity following surgery, as assessed with the fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity of neural activity (ReHo), are scarce and heterogenous. In this study, we used a longitudinal design to examine the changes in spontaneous neural activity after bariatric surgery (comparing pre- to post-surgery), and to determine whether these changes are related to cardiometabolic variables. MethodsThe study included 57 participants with severe obesity (mean BMI=43.1{+/-}4.3kg/m2) who underwent sleeve gastrectomy (SG), biliopancreatic diversion with duodenal switch (BPD), or Roux-en-Y gastric bypass (RYGB), scanned prior to bariatric surgery and at follow-up visits of 4 months (N=36), 12 months (N=29), and 24 months (N=14) after surgery. We examined fALFF and ReHo measures across 1022 cortical and subcortical regions (based on combined Schaeffer-Xiao parcellations) using a linear mixed effect model. Voxel-based morphometry (VBM) based on T1-weighted images was also used to measure GM density in the same regions. We also used an independent sample from the Human Connectome Project (HCP) to assess regional differences between individuals who had normal-weight (N=46) or severe obesity (N=46). ResultsWe found a global increase in the fALFF signal with greater increase within dorsolateral prefrontal cortex, precuneus, inferior temporal gyrus, and visual cortex. This effect was more significant 4 months after surgery. The increase within dorsolateral prefrontal cortex, temporal gyrus, and visual cortex was more limited after 12 months and only present in the visual cortex after 24 months. These increases in neural activity measured by fALFF were also significantly associated with the increase in GM density following surgery. Furthermore, the increase in neural activity was significantly related to post-surgery weight loss and improvement in cardiometabolic variables, such as insulin resistance index and blood pressure. In the independent HCP sample, normal-weight participants had higher global and regional fALFF signals, mainly in dorsolateral/medial frontal cortex, precuneus and middle/inferior temporal gyrus compared to the obese participants. These BMI-related differences in fALFF were associated with the increase in fALFF 4 months post-surgery especially in regions involved in control, default mode and dorsal attention networks. ConclusionsBariatric surgery-induced weight loss and improvement in metabolic factors are associated with widespread global and regional increases in neural activity, as measured by fALFF signal. These findings alongside the higher fALFF signal in normal-weight participants compared to participants with severe obesity in an independent dataset suggest an early recovery in the neural activity signal level after the surgery.

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