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Aging is ubiquitous to the human condition. The MRI correlates of healthy aging have been extensively investigated using a range of modalities, including volumetric MRI, quantitative MRI (qMRI), and diffusion tensor imaging. Despite this, the reported brainstem related changes remain sparse. This is, in part, due to the technical and methodological limitations in quantitatively assessing and statistically analyzing this region. By utilizing a new method of brainstem segmentation, a large cohort of 100 healthy adults were assessed in this study for the effects of aging within the human brainstem in vivo. Using qMRI, tensor-based morphometry (TBM), and voxel-based quantification (VBQ), the volumetric and quantitative changes across healthy adults between 19 and 75 years were characterized. In addition to the increased R2* in substantia nigra corresponding to increasing iron deposition with age, several novel findings were reported in the current study. These include selective volumetric loss of the brachium conjunctivum, with a corresponding decrease in magnetization transfer and increase in proton density (PD), accounting for the previously described \"midbrain shrinkage.\" Additionally, we found increases in R1 and PD in several pontine and medullary structures. We consider these changes in the context of well-characterized, functional age-related changes, and propose potential biophysical mechanisms. This study provides detailed quantitative analysis of the internal architecture of the brainstem and provides a baseline for further studies of neurodegenerative diseases that are characterized by early, pre-clinical involvement of the brainstem, such as Parkinson's and Alzheimer's diseases.

Introduction Prediction of Alzheimer's disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end, we combine a predictive multi‐task machine learning method (cFSGL) with a novel MR‐based multivariate morphometric surface map of the hippocampus (mTBM) to predict future cognitive scores of patients. Methods Previous work has shown that a multi‐task learning framework that performs prediction of all future time points simultaneously (cFSGL) can be used to encode both sparsity as well as temporal smoothness. The authors showed that this method is able to predict cognitive outcomes of ADNI subjects using FreeSurfer‐based baseline MRI features, MMSE score demographic information and ApoE status. Whilst volumetric information may hold generalized information on brain status, we hypothesized that hippocampus specific information may be more useful in predictive modeling of AD. To this end, we applied a multivariate tensor‐based parametric surface analysis method (mTBM) to extract features from the hippocampal surfaces. Results We combined mTBM features with traditional surface features such as middle axis distance, the Jacobian determinant as well as 2 of the Jacobian principal eigenvalues to yield 7 normalized hippocampal surface maps of 300 points each. By combining these 7 × 300 = 2100 features together with the previous ~350 features, we illustrate how this type of sparsifying method can be applied to an entire surface map of the hippocampus that yields a feature space that is 2 orders of magnitude larger than what was previously attempted. Conclusions By combining the power of the cFSGL multi‐task machine learning framework with the addition of AD sensitive mTBM feature maps of the hippocampus surface, we are able to improve the predictive performance of ADAS cognitive scores 6, 12, 24, 36 and 48 months from baseline. In this work, we present our results of using machine learning to predict temporal behavior changes in Alzheimers Disease using entire topological feature maps of the hippocampus surface (2100 feature points). Our paper demonstrates that it is possible to use an entire topological map instead of just imaging derived volumetric measurements for predicting behavioral changes. We compare these results with previous results using only volumetric MR imaging features (309 features points) and show through repeated cross‐validation rounds that we are able to get better predictive power.

•First to measure MRI-based GM volume in the control and perinatally-deafened cat.•ROI analysis reveals whole-brain GM preservation following deafness.•ROI and TBM results generally aligned, but each approach provided distinct insights.•Specific auditory loci decreased in volume while visual and somatosensory increased.•GM volume changes suggest functional optimization and cortical reorganization. In response to sensory deprivation, the brain adapts according to contemporary demands to efficiently navigate a modified perceptual environment. This reorganization may result in improved processing of the remaining senses–a phenomenon referred to as compensatory crossmodal plasticity. One approach to explore this neuroplasticity is to consider the macrostructural changes in neural tissue that mirror this functional optimization. The current study is the first of its kind to measure MRI-derived gray matter (GM) volumes of control felines (n=30), while additionally identifying volumetric differences in response to perinatal deafness (30 ototoxically-deafened cats). To accomplish this purpose, regional and morphometric methods were performed in parallel. The regional analysis evaluated volumetric alterations of global GM, as well as the volumes of 146 regions of interest (ROIs) and 12 functional subgroupings of these ROIs. Results revealed whole-brain GM preservation; however, somatosensory and visual cortices exhibited an overall increase in volume. On a smaller scale, this analysis uncovered two auditory ROIs (second auditory cortex, A2, and ventral auditory field, VAF) that decreased in volume alongside two visual regions (anteromedial lateral suprasylvian area, AMLS and splenial visual area, SVA) that increased–all localized within the right hemisphere. Comparatively, the findings of tensor-based morphometry (TBM) generally aligned with those of the ROI-based method, as this voxel-wise approach demonstrated clusters of expansion coincident with visual- and somatosensory-related loci; although, it failed to detect any GM reductions following deafness. As distinct differences were identified in each analysis, the current study highlights the importance of employing multiple methods when exploring MRI volumetry. Overall, this study proposes that volumetric alterations within sensory loci allude to a redistribution of cortical space arising from modified perceptual demands following auditory deprivation.

BackgroundFriedreich ataxia is an inherited neurodegenerative disease, with cerebral and cerebellar pathology evident. Despite an increased understanding of its neuropathology, disease progression in this disease remains poorly understood. This study aimed to characterise longitudinal change in brain structure using a multi-modal approach across cerebral and cerebellar grey and white matter.MethodsT1-weighted, diffusion-tensor, and magnetisation transfer magnetic resonance images were obtained from 28 individuals with Friedreich ataxia and 29 age- and gender-matched controls at two time-points, 2 years apart. Region-of-interest and exploratory between-group comparisons assessed changes in brain macrostructure (cerebellar lobule volume, cerebral cortical thickness/gyrification, brain white matter volume) and microstructure (white matter fractional anisotropy, mean/axial/radial diffusivity, magnetisation transfer ratio). Rates of change were correlated against change in neurological severity, Time 1 severity, and onset age.ResultsIndividuals with Friedreich ataxia had a greater rate of white matter volume loss than controls in the superior cerebellar peduncles and right peri-thalamic/posterior cerebral regions, and greater reduction in left primary motor cortex gyrification. Greater cerebellar/brainstem white matter volume loss and right dorsal premotor gyrification loss was observed amongst individuals with less severe neurological symptoms at Time 1. Conversely, cerebral atrophy and changes in axial diffusivity were observed in individuals with more severe Time 1 symptoms. Progression in radial diffusivity was more pronounced amongst individuals with earlier disease onset. Greater right ventral premotor gyrification loss correlated with greater neurological progression.ConclusionHeterogeneity in Friedreich ataxia progression is observed at the neurobiological level, with evidence of earlier cerebellar and later cerebral degeneration.

Even though age-related white matter hyperintensities (WMH) begin to emerge in middle age, their effect on brain micro- and macrostructure in this age group is not fully elucidated. We have examined how presence of WMH and load of WMH affect regional brain volumes and microstructure in a validated, representative general population sample of 873 individuals between 50 and 66 years. Presence of WMH was determined as Fazakas grade ≥1. WMH load was WMH volume from manual tracing of WMHs divided on intracranial volume. The impact of age appropriate WMH (Fazakas grade 1) on the brain was also investigated. Major novel findings were that even the age appropriate WMH group had widespread macro- and microstructural changes in gray and white matter, showing that the mere presence of WMH, not just WMH load is an important clinical indicator of brain health. With increasing WMH load, structural changes spread centrifugally. Further, we found three major patterns of FA and MD changes related to increasing WMH load, demonstrating a heterogeneous effect on white matter microstructure, where distinct patterns were found in the proximity of the lesions, in deep white matter and in white matter near the cortex. This study also raises several questions about the onset of WMH related pathology, in particular, whether some of the aberrant brain structural and microstructural findings are present before the emergence of WMH. We also found, similar to other studies, that WMH risk factors had low explanatory power for WMH, making it unclear which factors lead to WMH. [Display omitted]

•First to examine MRI-based subcortical volumes in the perinatally deafened cat.•Reveals large-scale disuse-driven atrophy in the deafened feline subcortex.•Magnitude of reductions in lower-level auditory nuclei are influenced by hierarchy.•Visual nuclei also exhibit reductions based on modified perceptual importance.•Deafened feline subcortex remains structurally symmetrical. In response to sensory deprivation, the brain adapts to efficiently navigate a modified perceptual environment through a process referred to as compensatory crossmodal plasticity, allowing the remaining senses to repurpose deprived regions and networks. A mechanism that has been proposed to contribute to this plasticity involves adaptations within subcortical nuclei that trigger cascading effects throughout the brain. The current study uses 7T MRI to investigate the effect of perinatal deafness on the volumes of subcortical structures in felines, focusing on key sensory nuclei within the brainstem and thalamus. Using both ROI-based and morphometric approaches, the regional macrostructure of four auditory and two visual nuclei were studied, as well as the corresponding volumetric asymmetries within and across groups. In the auditory pathway, significant bilateral volumetric reductions were revealed within the lower-level structures (cochlear nucleus, superior olivary complex, and inferior colliculus), alongside a shrinkage of solely the left medial geniculate body. Within the visual pathway, a significant bilateral volumetric reduction was found in the lateral geniculate nucleus, with the superior colliculus largely unaffected. These regional alterations, along with an extensive loss of volume throughout the brainstem of deprived cats, were attributed to disuse-driven atrophy corresponding to evolved functional demands reflective of a modified perceptual environment. Furthermore, the left-right volumetric symmetries of the control subcortex were preserved following deafness. Overall, the current study reinforces the notion that subcortical structures likely contribute to compensatory crossmodal plasticity prior to cortical processing, and that these deafness-induced adaptations appear to be influenced by both the level of the affected structure within its respective sensory processing hierarchy and the specifics of its afferent profile.

A recently identified variant within the fat mass and obesity-associated (FTO) gene is carried by 46% of Western Europeans and is associated with an ∼1.2 kg higher weight, on average, in adults and an ∼1 cm greater waist circumference. With >1 billion overweight and 300 million obese persons worldwide, it is crucial to understand the implications of carrying this very common allele for the health of our aging population. FTO is highly expressed in the brain and elevated body mass index (BMI) is associated with brain atrophy, but it is unknown how the obesity-associated risk allele affects human brain structure. We therefore generated 3D maps of regional brain volume differences in 206 healthy elderly subjects scanned with MRI and genotyped as part of the Alzheimer's Disease Neuroimaging Initiative. We found a pattern of systematic brain volume deficits in carriers of the obesity-associated risk allele versus noncarriers. Relative to structure volumes in the mean template, FTO risk allele carriers versus noncarriers had an average brain volume difference of ∼8% in the frontal lobes and 12% in the occipital lobes—these regions also showed significant volume deficits in subjects with higher BMI. These brain differences were not attributable to differences in cholesterol levels, hypertension, or the volume of white matter hyperintensities; which were not detectably higher in FTO risk allele carriers versus noncarriers. These brain maps reveal that a commonly carried susceptibility allele for obesity is associated with structural brain atrophy, with implications for the health of the elderly.

INTRODUCTION Diffusion magnetic resonance imaging studies investigating Down syndrome (DS) and Alzheimer's disease (AD) have mainly relied on white matter (WM) skeleton‐based techniques, potentially overlooking broader WM architecture. METHOD We applied diffusion tensor–based morphometry (D‐TBM), a novel whole‐volume WM registration technique, to characterize WM properties in DS. Between‐ and within‐group analyses were conducted in 51 adults with DS and 35 controls, divided into two age groups, using diffusion tensor imaging (DTI)–derived metrics and local volumetric changes. RESULTS DS participants exhibited extensive volumetric and DTI‐based differences affecting association fibers and commissures. Within‐group comparisons revealed further changes in older DS participants in these fibers. Reduced axial diffusivity (AxD) in temporal and commissural WM was reported for the first time in DS. DISCUSSION DTI changes in the older DS cohort affect WM structures supporting language, memory, and executive functions and may be due to AD‐related atrophy. Reduced AxD may reflect neuroinflammation or atypical WM development. Highlights Diffusion tensor–based morphometry (D‐TBM) was applied for the first time in Down syndrome (DS) adults. Diffusion tensor imaging alterations in DS affect structures for language, memory, and executive functions. Increased radial diffusivity and mean diffusivity in older DS adults highlight Alzheimer's disease (AD)‐related neurodegeneration in key tracts. AD in DS affects commissural structures, including the genu of the corpus callosum. Axial diffusivity reductions in DS may indicate neuroinflammation.

Structural brain abnormalities likely underlie impaired balance control in cerebral palsy (CP). This study investigated whether balance measures were associated with measures derived from conventional MRI and diffusion tensor imaging (DTI), and whether an X-Box One Kinect balance training (6 weeks, 5 days/week, 30 min/session) could induce neuroplastic changes in CP. Twelve children with spastic CP (age:11.3 ± 2.3y) underwent balance evaluation and MRI examination, at baseline and after training. Nine age-matched typically developing (TD) children underwent baseline measurements. Balance control was evaluated testing advanced motor skills (Challenge score) and during gait (medio-lateral Margin of Stability, MoS). With conventional MRI, but especially with DTBM (DTI-based VBM), we found smaller volumes of several deep grey matter structures and within the right inferior parietal cortex, right supramarginal cortex, and left postcentral cortex, and lower fractional anisotropy (FA) and smaller volumes of various white matter regions in CP compared to TD. Within the CP group alone, no correlations within brain tissue were found. After training, Challenge scores of children with CP improved. In an exploratory analysis DTBM showed a trend for volume increase within the right inferior parietal cortex, volume decrease within the right retrolenticular limb of the internal capsule, and an increase of FA within the right corticospinal tract. This indicates that a 6-week balance intervention may induce neuroplastic changes in children with CP. CP-RehOP (trial registration number: NTR6034/NL5854, date of registration: August 26th 2016).

Rehabilitative training has shown to improve significantly motor outcomes and functional walking capacity in patients with incomplete spinal cord injury (iSCI). However, whether performance improvements during rehabilitation relate to brain plasticity or whether it is based on functional adaptation of movement strategies remain uncertain. This study assessed training improvement-induced structural brain plasticity in chronic iSCI patients using longitudinal MRI. We used tensor-based morphometry (TBM) to analyze longitudinal brain volume changes associated with intensive virtual reality (VR)-augmented lower limb training in nine traumatic iSCI patients. The MRI data was acquired before and after a 4-week training period (16-20 training sessions). Before training, voxel-based morphometry (VBM) and voxel-based cortical thickness (VBCT) assessed baseline morphometric differences in nine iSCI patients compared to 14 healthy controls. The intense VR-augmented training of limb control improved significantly balance, walking speed, ambulation, and muscle strength in patients. Retention of clinical improvements was confirmed by the 3-4 months follow-up. In patients relative to controls, VBM revealed reductions of white matter volume within the brainstem and cerebellum and VBCT showed cortical thinning in the primary motor cortex. Over time, TBM revealed significant improvement-induced volume increases in the left middle temporal and occipital gyrus, left temporal pole and fusiform gyrus, both hippocampi, cerebellum, corpus callosum, and brainstem in iSCI patients. This study demonstrates structural plasticity at the cortical and brainstem level as a consequence of VR-augmented training in iSCI patients. These structural changes may serve as neuroimaging biomarkers of VR-augmented lower limb neurorehabilitation in addition to performance measures to detect improvements in rehabilitative training.