•Gait variability in aging is associated with altered brain structure and function.•Sensorimotor integration and coordination areas are most often altered.•In cognitive impairment and dementia, ...general and regional findings are limited.•Longitudinal studies of multiple brain areas are warranted to understand mechanisms.
While gait variability may reflect subtle changes due to aging or cognitive impairment (CI), associated brain characteristics remain unclear. We summarize structural and functional neuroimaging findings associated with gait variability in older adults with and without CI and dementia.
We identified 17 eligible studies; all were cross-sectional; few examined multiple brain areas. In older adults, temporal gait variability was associated with structural differences in medial areas important for lower limb coordination and balance. Both temporal and spatial gait variability were associated with structural and functional differences in hippocampus and primary sensorimotor cortex and structural differences in anterior cingulate cortex, basal ganglia, association tracts, and posterior thalamic radiation. In CI or dementia, some associations were found in primary motor cortex, hippocampus, prefrontal cortex and basal ganglia.
In older adults, gait variability may be associated with areas important for sensorimotor integration and coordination. To comprehend the neural basis of gait variability with aging and CI, longitudinal studies of multiple brain areas are needed.
Detailed whole brain segmentation is an essential quantitative technique in medical image analysis, which provides a non-invasive way of measuring brain regions from a clinical acquired structural ...magnetic resonance imaging (MRI). Recently, deep convolution neural network (CNN) has been applied to whole brain segmentation. However, restricted by current GPU memory, 2D based methods, downsampling based 3D CNN methods, and patch-based high-resolution 3D CNN methods have been the de facto standard solutions. 3D patch-based high resolution methods typically yield superior performance among CNN approaches on detailed whole brain segmentation (>100 labels), however, whose performance are still commonly inferior compared with state-of-the-art multi-atlas segmentation methods (MAS) due to the following challenges: (1) a single network is typically used to learn both spatial and contextual information for the patches, (2) limited manually traced whole brain volumes are available (typically less than 50) for training a network. In this work, we propose the spatially localized atlas network tiles (SLANT) method to distribute multiple independent 3D fully convolutional networks (FCN) for high-resolution whole brain segmentation. To address the first challenge, multiple spatially distributed networks were used in the SLANT method, in which each network learned contextual information for a fixed spatial location. To address the second challenge, auxiliary labels on 5111 initially unlabeled scans were created by multi-atlas segmentation for training. Since the method integrated multiple traditional medical image processing methods with deep learning, we developed a containerized pipeline to deploy the end-to-end solution. From the results, the proposed method achieved superior performance compared with multi-atlas segmentation methods, while reducing the computational time from >30 h to 15 min. The method has been made available in open source (https://github.com/MASILab/SLANTbrainSeg).
Display omitted
•SLANT method distributes multiple independent 3D deep networks.•SLANT was proposed for high-resolution whole brain segmentation.•Better than multi-atlas segmentation, while reducing time to 15 minutes.•Auxiliary labels on 5111 initially unlabeled scans were used for training.•The method has been made in Docker and available in open source.
In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across ...individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA.
•Non-Negative Matrix Factorization for the analysis of structural neuroimaging data•NNMF identifies regions that co-vary across individuals in a consistent way.•NNMF components align well with anatomical structures and follow functional units.•Comprehensive comparison between PCA, ICA and NNMF.•NNMF enjoys increased specificity and generalizability compared to PCA and ICA.
Diffusion magnetic resonance images may suffer from geometric distortions due to susceptibility induced off resonance fields, which cause geometric mismatch with anatomical images and ultimately ...affect subsequent quantification of microstructural or connectivity indices. State-of-the art diffusion distortion correction methods typically require data acquired with reverse phase encoding directions, resulting in varying magnitudes and orientations of distortion, which allow estimation of an undistorted volume. Alternatively, additional field maps acquisitions can be used along with sequence information to determine warping fields. However, not all imaging protocols include these additional scans and cannot take advantage of state-of-the art distortion correction. To avoid additional acquisitions, structural MRI (undistorted scans) can be used as registration targets for intensity driven correction. In this study, we aim to (1) enable susceptibility distortion correction with historical and/or limited diffusion datasets that do not include specific sequences for distortion correction and (2) avoid the computationally intensive registration procedure typically required for distortion correction using structural scans. To achieve these aims, we use deep learning (3D U-nets) to synthesize an undistorted b0 image that matches geometry of structural T1w images and intensity contrasts from diffusion images. Importantly, the training dataset is heterogenous, consisting of varying acquisitions of both structural and diffusion. We apply our approach to a withheld test set and show that distortions are successfully corrected after processing. We quantitatively evaluate the proposed distortion correction and intensity-based registration against state-of-the-art distortion correction (FSL topup). The results illustrate that the proposed pipeline results in b0 images that are geometrically similar to non-distorted structural images, and more closely match state-of-the-art correction with additional acquisitions. In addition, we show generalizability of the proposed approach to datasets that were not in the original training / validation / testing datasets. These datasets included varying populations, contrasts, resolutions, and magnitudes and orientations of distortion and show efficacious distortion correction. The method is available as a Singularity container, source code, and an executable trained model to facilitate evaluation.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying ...acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,477 structural brain MRI scans from participants without a known neurological or psychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive age trends of brain structure through the lifespan (3–96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this reference of brain development and aging, and to examine deviations from ranges, potentially related to disease.
•Multi-site harmonization method that pools volumetric data from 18 studies, controlling for nonlinear age effects.•Resulting dataset covers ages 3 to 96 and used to derive age trends of brain structure through the lifespan.•Interactive visualization tool provided for exploring age trends and comparing new data.
•Unsupervised MR harmonization without traveling subjects.•Unified latent space for MR contrast synthesis.•A novel framework for disentangling contrast and anatomy in MR images.•Downstream ...segmentation consistency shows significant improvements after harmonization.
In magnetic resonance (MR) imaging, a lack of standardization in acquisition often causes pulse sequence-based contrast variations in MR images from site to site, which impedes consistent measurements in automatic analyses. In this paper, we propose an unsupervised MR image harmonization approach, CALAMITI (Contrast Anatomy Learning and Analysis for MR Intensity Translation and Integration), which aims to alleviate contrast variations in multi-site MR imaging. Designed using information bottleneck theory, CALAMITI learns a globally disentangled latent space containing both anatomical and contrast information, which permits harmonization. In contrast to supervised harmonization methods, our approach does not need a sample population to be imaged across sites. Unlike traditional unsupervised harmonization approaches which often suffer from geometry shifts, CALAMITI better preserves anatomy by design. The proposed method is also able to adapt to a new testing site with a straightforward fine-tuning process. Experiments on MR images acquired from ten sites show that CALAMITI achieves superior performance compared with other harmonization approaches.
Myelin loss and iron accumulation are cardinal features of aging and various neurodegenerative diseases. Oligodendrocytes incorporate iron as a metabolic substrate for myelin synthesis and ...maintenance. An emerging hypothesis in Alzheimer's disease research suggests that myelin breakdown releases substantial stores of iron that may accumulate, leading to further myelin breakdown and neurodegeneration. We assessed associations between iron content and myelin content in critical brain regions using quantitative magnetic resonance imaging (MRI) on a cohort of cognitively unimpaired adults ranging in age from 21 to 94 years. We measured whole-brain myelin water fraction (MWF), a surrogate of myelin content, using multicomponent relaxometry, and whole-brain iron content using susceptibility weighted imaging in all individuals. MWF was negatively associated with iron content in most brain regions evaluated indicating that lower myelin content corresponds to higher iron content. Moreover, iron content was significantly higher with advanced age in most structures, with men exhibiting a trend towards higher iron content as compared to women. Finally, relationship between MWF and age, in all brain regions investigated, suggests that brain myelination continues until middle age, followed by degeneration at older ages. This work establishes a foundation for further investigations of the etiology and sequelae of myelin breakdown and iron accumulation in neurodegeneration and may lead to new imaging markers for disease progression and treatment.
Age effects on cognitive functioning are well-documented, but effects of sex on trajectories of cognitive aging are less clear. We examined cognitive ability across a variety of measures for 1,065 to ...2,127 participants (mean baseline age 64.1 to 69.7 years) from the Baltimore Longitudinal Study of Aging who were repeatedly tested over a mean follow-up interval of 3.0 to 9.0 years with a mean of 2.3 to 4.4 assessments. Memory and other cognitive tests were administered at each visit, assessing mental status, verbal learning and memory, figural memory, language, attention, perceptuomotor speed and integration, executive function, and visuospatial ability. Importantly, participants free from cognitive impairment at all time points were used in the analyses. Results showed that for all tests, higher age at baseline was significantly associated with lower scores, and performance declined over time. In addition, advancing age was associated with accelerated longitudinal declines in performance (trend for mental status). After adjusting for age, education, and race, sex differences were observed across most tests of specific cognitive abilities examined. At baseline, males outperformed females on the 2 tasks of visuospatial ability, and females outperformed males in most other tests of cognition. Sex differences in cognitive change over time indicated steeper rates of decline for men on measures of mental status, perceptuomotor speed and integration, and visuospatial ability, but no measures on which women showed significantly steeper declines. Our results highlight greater resilience to age-related cognitive decline in older women compared with men.
IMPORTANCE: In one-third of older men with anemia, no recognized cause can be found. OBJECTIVE: To determine if testosterone treatment of men 65 years or older with unequivocally low testosterone ...levels and unexplained anemia would increase their hemoglobin concentration. DESIGN, SETTING, AND PARTICIPANTS: A double-blinded, placebo-controlled trial with treatment allocation by minimization using 788 men 65 years or older who have average testosterone levels of less than 275 ng/dL. Of 788 participants, 126 were anemic (hemoglobin ≤12.7 g/dL), 62 of whom had no known cause. The trial was conducted in 12 academic medical centers in the United States from June 2010 to June 2014. INTERVENTIONS: Testosterone gel, the dose adjusted to maintain the testosterone levels normal for young men, or placebo gel for 12 months. MAIN OUTCOMES AND MEASURES: The percent of men with unexplained anemia whose hemoglobin levels increased by 1.0 g/dL or more in response to testosterone compared with placebo. The statistical analysis was intent-to-treat by a logistic mixed effects model adjusted for balancing factors. RESULTS: The men had a mean age of 74.8 years and body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) of 30.7; 84.9% were white. Testosterone treatment resulted in a greater percentage of men with unexplained anemia whose month 12 hemoglobin levels had increased by 1.0 g/dL or more over baseline (54%) than did placebo (15%) (adjusted OR, 31.5; 95% CI, 3.7-277.8; P = .002) and a greater percentage of men who at month 12 were no longer anemic (58.3%) compared with placebo (22.2%) (adjusted OR, 17.0; 95% CI, 2.8-104.0; P = .002). Testosterone treatment also resulted in a greater percentage of men with anemia of known cause whose month 12 hemoglobin levels had increased by 1.0 g/dL or more (52%) than did placebo (19%) (adjusted OR, 8.2; 95% CI, 2.1-31.9; P = .003). Testosterone treatment resulted in a hemoglobin concentration of more than 17.5 g/dL in 6 men who had not been anemic at baseline. CONCLUSIONS AND RELEVANCE: Among older men with low testosterone levels, testosterone treatment significantly increased the hemoglobin levels of those with unexplained anemia as well as those with anemia from known causes. These increases may be of clinical value, as suggested by the magnitude of the changes and the correction of anemia in most men, but the overall health benefits remain to be established. Measurement of testosterone levels might be considered in men 65 years or older who have unexplained anemia and symptoms of low testosterone levels. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00799617
Effects of Testosterone Treatment in Older Men Snyder, Peter J; Bhasin, Shalender; Cunningham, Glenn R ...
The New England journal of medicine,
02/2016, Letnik:
374, Številka:
7
Journal Article
Recenzirano
Odprti dostop
In this study, men 65 years of age or older with low serum testosterone and symptoms of hypoandrogenism received testosterone or placebo for a year. Testosterone had a moderate benefit in sexual ...function and some benefit in mood but no benefit in vitality or walking distance.
Testosterone concentrations in men decrease with increasing age.
1
,
2
Many symptoms and conditions similar to those that are caused by low testosterone levels in men with pituitary or testicular disease become more common with increasing age. Such symptoms include decreases in mobility, sexual function, and energy. These parallels suggest that the lower testosterone levels in older men may contribute to these conditions.
Previous trials of testosterone treatment in men 65 years of age or older, however, have yielded equivocal results. Although testosterone treatment consistently increased muscle mass and decreased fat mass,
3
,
4
effects on physical performance,
3
,
5
,
6
sexual function, . . .
PDF
