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1.
  • Beck, Dani, et al. (författare)
  • Dissecting unique and common variance across body and brain health indicators using age prediction
  • 2024
  • Ingår i: Human Brain Mapping. - : WILEY. - 1065-9471 .- 1097-0193. ; 45:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals. A 'body age' model trained on health traits demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. Health traits may differentially influence age predictions beyond what is captured by the brain imaging data, revealing a degree of unique variance in brain and bodily ageing processes. image
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2.
  • Johnson, Jessica T.E., et al. (författare)
  • In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI
  • 2024
  • Ingår i: Human Brain Mapping. - 1065-9471. ; 45:7
  • Tidskriftsartikel (refereegranskat)abstract
    • Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, (Formula presented.), in addition to the diffusion tensor, (Formula presented.), and relaxation, (Formula presented.), (Formula presented.), correlations. A (Formula presented.) clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their (Formula presented.) distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.
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  • Bonkhoff, Anna K, et al. (författare)
  • The relevance of rich club regions for functional outcome post-stroke is enhanced in women.
  • 2023
  • Ingår i: Human brain mapping. - : Wiley. - 1097-0193 .- 1065-9471. ; 44:4, s. 1579-1592
  • Tidskriftsartikel (refereegranskat)abstract
    • This study aimed to investigate the influence of stroke lesions in predefined highly interconnected (rich-club) brain regions on functional outcome post-stroke, determine their spatial specificity and explore the effects of biological sex on their relevance. We analyzed MRI data recorded at index stroke and ~3-months modified Rankin Scale (mRS) data from patients with acute ischemic stroke enrolled in the multisite MRI-GENIE study. Spatially normalized structural stroke lesions were parcellated into 108 atlas-defined bilateral (sub)cortical brain regions. Unfavorable outcome (mRS>2) was modeled in a Bayesian logistic regression framework. Effects of individual brain regions were captured as two compound effects for (i) six bilateral rich club and (ii) all further non-rich club regions. In spatial specificity analyses, we randomized the split into "rich club" and "non-rich club" regions and compared the effect of the actual rich club regions to the distribution of effects from 1000 combinations of six random regions. In sex-specific analyses, we introduced an additional hierarchical level in our model structure to compare male and female-specific rich club effects. A total of 822 patients (age: 64.7[15.0], 39% women) were analyzed. Rich club regions had substantial relevance in explaining unfavorable functional outcome (mean of posterior distribution: 0.08, area under the curve: 0.8). In particular, the rich club-combination had a higher relevance than 98.4% of random constellations. Rich club regions were substantially more important in explaining long-term outcome in women than in men. All in all, lesions in rich club regions were associated with increased odds of unfavorable outcome. These effects were spatially specific and more pronounced in women.
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5.
  • Bussy, Aurélie, et al. (författare)
  • Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia
  • 2023
  • Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 44:7, s. 2684-2700
  • Tidskriftsartikel (refereegranskat)abstract
    • Recent studies have reported early cerebellar and subcortical impact in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the cerebello-subcortical circuitry in FTD has been understudied despite its essential role in cognition and behaviors related to FTD symptomatology. The present study aims to investigate the association between cerebellar and subcortical atrophy, and neuropsychiatric symptoms across genetic mutations. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative including mutation carriers and noncarrier first-degree relatives of known symptomatic carriers. Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed, and partial least squares analyses (PLS) were used to link morphometry and behavior. In presymptomatic C9orf72 expansion carriers, thalamic atrophy was found compared to noncarriers, suggesting the importance of this structure in FTD prodromes. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to neuropsychiatric symptoms, with significant overlap in brain/behavior patterns, but also specificity for each genetic mutation group. The largest differences were in the cerebellar atrophy (larger extent in C9orf72 expansion group) and more prominent amygdalar volume reduction in the MAPT group. Brain scores in the C9orf72 expansion carriers and MAPT carriers demonstrated covariation patterns concordant with atrophy patterns detectable up to 20 years before expected symptom onset. Overall, these results demonstrated the important role of the subcortical structures in genetic FTD symptom expression, particularly the cerebellum in C9orf72 and the amygdala in MAPT carriers.
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6.
  • Demnitz, Naiara, et al. (författare)
  • Is it all in the baseline? Trajectories of chair stand performance over 4 years and their association with grey matter structure in older adults
  • 2023
  • Ingår i: Human Brain Mapping. - : John Wiley & Sons. - 1065-9471 .- 1097-0193. ; 44:11, s. 4299-4309
  • Tidskriftsartikel (refereegranskat)abstract
    • Understanding individual variability in response to physical activity is key to developing more effective and personalised interventions for healthy ageing. Here, we aimed to unpack individual differences by using longitudinal data from a randomised-controlled trial of a 12-month muscle strengthening intervention in older adults. Physical function of the lower extremities was collected from 247 participants (66.3 ± 2.5 years) at four time-points. At baseline and at year 4, participants underwent 3 T MRI brain scans. K-means longitudinal clustering was used to identify patterns of change in chair stand performance over 4 years, and voxel-based morphometry was applied to map structural grey matter volume at baseline and year 4. Results identified three groups showing trajectories of poor (33.6%), mid (40.1%), and high (26.3%) performance. Baseline physical function, sex, and depressive symptoms significantly differed between trajectory groups. High performers showed greater grey matter volume in the motor cerebellum compared to the poor performers. After accounting for baseline chair stand performance, participants were re-assigned to one of four trajectory-based groups: moderate improvers (38.9%), maintainers (38.5%), improvers (13%), and decliners (9.7%). Clusters of significant grey matter differences were observed between improvers and decliners in the right supplementary motor area. Trajectory-based group assignments were unrelated to the intervention arms of the study. In conclusion, patterns of change in chair stand performance were associated with greater grey matter volumes in cerebellar and cortical motor regions. Our findings emphasise that how you start matters, as baseline chair stand performance was associated with cerebellar volume 4 years later.
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7.
  • Fu, Jingru, et al. (författare)
  • Fast three-dimensional image generation for healthy brain aging using diffeomorphic registration
  • 2023
  • Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 44:4, s. 1289-1308
  • Tidskriftsartikel (refereegranskat)abstract
    • Predicting brain aging can help in the early detection and prognosis of neurodegenerative diseases. Longitudinal cohorts of healthy subjects scanned through magnetic resonance imaging (MRI) have been essential to understand the structural brain changes due to aging. However, these cohorts suffer from missing data due to logistic issues in the recruitment of subjects. This paper proposes a methodology for filling up missing data in longitudinal cohorts with anatomically plausible images that capture the subject-specific aging process. The proposed methodology is developed within the framework of diffeomorphic registration. First, two novel modules are introduced within Synthmorph, a fast, state-of-the-art deep learning-based diffeomorphic registration method, to simulate the aging process between the first and last available MRI scan for each subject in three-dimensional (3D). The use of image registration also makes the generated images plausible by construction. Second, we used six image similarity measurements to rearrange the generated images to the specific age range. Finally, we estimated the age of every generated image by using the assumption of linear brain decay in healthy subjects. The methodology was evaluated on 2662 T1-weighted MRI scans from 796 healthy participants from 3 different longitudinal cohorts: Alzheimer's Disease Neuroimaging Initiative, Open Access Series of Imaging Studies-3, and Group of Neuropsychological Studies of the Canary Islands (GENIC). In total, we generated 7548 images to simulate the access of a scan per subject every 6 months in these cohorts. We evaluated the quality of the synthetic images using six quantitative measurements and a qualitative assessment by an experienced neuroradiologist with state-of-the-art results. The assumption of linear brain decay was accurate in these cohorts (R2 ∈ [.924,.940]). The experimental results show that the proposed methodology can produce anatomically plausible aging predictions that can be used to enhance longitudinal datasets. Compared to deep learning-based generative methods, diffeomorphic registration is more likely to preserve the anatomy of the different structures of the brain, which makes it more appropriate for its use in clinical applications. The proposed methodology is able to efficiently simulate anatomically plausible 3D MRI scans of brain aging of healthy subjects from two images scanned at two different time points.
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9.
  • Morez, Jan, et al. (författare)
  • Optimal experimental design and estimation for q-space trajectory imaging
  • 2023
  • Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 44:4, s. 1793-1809
  • Tidskriftsartikel (refereegranskat)abstract
    • Tensor-valued diffusion encoding facilitates data analysis by q-space trajectory imaging. By modeling the diffusion signal of heterogeneous tissues with a diffusion tensor distribution (DTD) and modulating the encoding tensor shape, this novel approach allows disentangling variations in diffusivity from microscopic anisotropy, orientation dispersion, and mixtures of multiple isotropic diffusivities. To facilitate the estimation of the DTD parameters, a parsimonious acquisition scheme coupled with an accurate and precise estimation of the DTD is needed. In this work, we create two precision-optimized acquisition schemes: one that maximizes the precision of the raw DTD parameters, and another that maximizes the precision of the scalar measures derived from the DTD. The improved precision of these schemes compared to a naïve sampling scheme is demonstrated in both simulations and real data. Furthermore, we show that the weighted linear least squares (WLLS) estimator that uses the squared reciprocal of the noisy signal as weights can be biased, whereas the iteratively WLLS estimator with the squared reciprocal of the predicted signal as weights outperforms the conventional unweighted linear LS and nonlinear LS estimators in terms of accuracy and precision. Finally, we show that the use of appropriate constraints can considerably increase the precision of the estimator with only a limited decrease in accuracy.
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