Test-retest reliability of FreeSurfer automated hippocampal subfield segmentation within and across scanners

The human hippocampus is vulnerable to a range of degenerative conditions and as such, accurate in vivo measurement of the hippocampus and hippocampal substructures via neuroimaging is of great interest for understanding mechanisms of disease as well as for use as a biomarker in clinical trials of novel therapeutics. Although total hippocampal volume can be measured relatively reliably, it is critical to understand how this reliability is affected by acquisition on different scanners, as multiple scanning platforms would likely be utilized in large-scale clinical trials. This is particularly true for hippocampal subregional measurements, which have only relatively recently been measurable through common image processing platforms such as FreeSurfer. Accurate segmentation of these subregions is challenging due to their small size, magnetic resonance imaging (MRI) signal loss in medial temporal regions of the brain, and lack of contrast for delineation from standard neuroimaging procedures. Here, we assess the test-retest reliability of the FreeSurfer automated hippocampal subfield segmentation procedure using two Siemens model scanners (a Siemens Trio and Prismafit Trio upgrade). T1-weighted images were acquired for 11 generally healthy younger participants (two scans on the Trio and one scan on the Prismafit). Each scan was processed through the standard cross-sectional stream and the recently released longitudinal pipeline in FreeSurfer v6.0 for hippocampal segmentation. Test-retest reliability of the volumetric measures was examined for individual subfields as well as percent volume difference and Dice overlap among scans and intra-class correlation coefficients (ICC). Reliability was high in the molecular layer, dentate gyrus, and whole hippocampus with the inclusion of three time points with mean volume differences among scans less than 3%, overlap greater than 80%, and ICC >0.95. The parasubiculum and hippocampal fissure showed the least improvement in reliability with mean volume difference greater than 5%, overlap less than 70%, and ICC scores ranging from 0.78 to 0.89. Other subregions, including the CA regions, were stable in their mean volume difference and overlap (75% respectively) and showed improvement in reliability with the inclusion of three scans (ICC ​> ​0.9). Reliability was generally higher within scanner (Trio-Trio), however, Trio-Prismafit reliability was also high and did not exhibit an obvious bias. These results suggest that the FreeSurfer automated segmentation procedure is a reliable method to measure total as well as hippocampal subregional volumes and may be useful in clinical applications including as an endpoint for future clinical trials of conditions affecting the hippocampus

Reduced Gray to White Matter Tissue Intensity Contrast in Schizophrenia

BACKGROUND: While numerous structural magnetic resonance imaging (MRI) studies revealed changes of brain volume or density, cortical thickness and fibre integrity in schizophrenia, the effect of tissue alterations on the contrast properties of neural structures has so far remained mostly unexplored. METHODS: Whole brain high-resolution MRI at 3 Tesla was used to investigate tissue contrast and cortical thickness in patients with schizophrenia and healthy controls. RESULTS: Patients showed significantly decreased gray to white matter contrast in large portions throughout the cortical mantle with preponderance in inferior, middle, superior and medial temporal areas as well as in lateral and medial frontal regions. The extent of these intensity contrast changes exceeded the extent of cortical thinning. Further, contrast changes remained significant after controlling for cortical thickness measurements. CONCLUSIONS: Our findings clearly emphasize the presence of schizophrenia related brain tissue changes that alter the imaging properties of brain structures. Intensity contrast measurements might not only serve as a highly sensitive metric but also as a potential indicator of a distinct pathological process that might be independent from volume or thickness alterations

Adolescent brain maturation and cortical folding: evidence for reductions in gyrification

Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development

Differential Development of Human Brain White Matter Tracts

Neuroscience is increasingly focusing on developmental factors related to human structural and functional connectivity. Unfortunately, to date, diffusion-based imaging approaches have only contributed modestly to these broad objectives, despite the promise of diffusion-based tractography. Here, we report a novel data-driven approach to detect similarities and differences among white matter tracts with respect to their developmental trajectories, using 64-direction diffusion tensor imaging. Specifically, using a cross-sectional sample comprising 144 healthy individuals (7 to 48 years old), we applied k-means cluster analysis to separate white matter voxels based on their age-related trajectories of fractional anisotropy. Optimal solutions included 5-, 9- and 14-clusters. Our results recapitulate well-established tracts (e.g., internal and external capsule, optic radiations, corpus callosum, cingulum bundle, cerebral peduncles) and subdivisions within tracts (e.g., corpus callosum, internal capsule). For all but one tract identified, age-related trajectories were curvilinear (i.e., inverted ‘U-shape’), with age-related increases during childhood and adolescence followed by decreases in middle adulthood. Identification of peaks in the trajectories suggests that age-related losses in fractional anisotropy occur as early as 23 years of age, with mean onset at 30 years of age. Our findings demonstrate that data-driven analytic techniques may be fruitfully applied to extant diffusion tensor imaging datasets in normative and neuropsychiatric samples

Distinct Transcriptome Expression of the Temporal Cortex of the Primate Microcebus murinus during Brain Aging versus Alzheimer's Disease-Like Pathology

Aging is the primary risk factor of neurodegenerative disorders such as Alzheimer's disease (AD). However, the molecular events occurring during brain aging are extremely complex and still largely unknown. For a better understanding of these age-associated modifications, animal models as close as possible to humans are needed. We thus analyzed the transcriptome of the temporal cortex of the primate Microcebus murinus using human oligonucleotide microarrays (Affymetrix). Gene expression profiles were assessed in the temporal cortex of 6 young adults, 10 healthy old animals and 2 old, “AD-like” animals that presented ß-amyloid plaques and cortical atrophy, which are pathognomonic signs of AD in humans. Gene expression data of the 14,911 genes that were detected in at least 3 samples were analyzed. By SAM (significance analysis of microarrays), we identified 47 genes that discriminated young from healthy old and “AD-like” animals. These findings were confirmed by principal component analysis (PCA). ANOVA of the expression data from the three groups identified 695 genes (including the 47 genes previously identified by SAM and PCA) with significant changes of expression in old and “AD-like” in comparison to young animals. About one third of these genes showed similar changes of expression in healthy aging and in “AD-like” animals, whereas more than two thirds showed opposite changes in these two groups in comparison to young animals. Hierarchical clustering analysis of the 695 markers indicated that each group had distinct expression profiles which characterized each group, especially the “AD-like” group. Functional categorization showed that most of the genes that were up-regulated in healthy old animals and down-regulated in “AD-like” animals belonged to metabolic pathways, particularly protein synthesis. These data suggest the existence of compensatory mechanisms during physiological brain aging that disappear in “AD-like” animals. These results open the way to new exploration of physiological and “AD-like” aging in primates

Sparse Representation of Brain Aging: Extracting Covariance Patterns from Structural MRI

An enhanced understanding of how normal aging alters brain structure is urgently needed for the early diagnosis and treatment of age-related mental diseases. Structural magnetic resonance imaging (MRI) is a reliable technique used to detect age-related changes in the human brain. Currently, multivariate pattern analysis (MVPA) enables the exploration of subtle and distributed changes of data obtained from structural MRI images. In this study, a new MVPA approach based on sparse representation has been employed to investigate the anatomical covariance patterns of normal aging. Two groups of participants (group 1∶290 participants; group 2∶56 participants) were evaluated in this study. These two groups were scanned with two 1.5 T MRI machines. In the first group, we obtained the discriminative patterns using a t-test filter and sparse representation step. We were able to distinguish the young from old cohort with a very high accuracy using only a few voxels of the discriminative patterns (group 1∶98.4%; group 2∶96.4%). The experimental results showed that the selected voxels may be categorized into two components according to the two steps in the proposed method. The first component focuses on the precentral and postcentral gyri, and the caudate nucleus, which play an important role in sensorimotor tasks. The strongest volume reduction with age was observed in these clusters. The second component is mainly distributed over the cerebellum, thalamus, and right inferior frontal gyrus. These regions are not only critical nodes of the sensorimotor circuitry but also the cognitive circuitry although their volume shows a relative resilience against aging. Considering the voxels selection procedure, we suggest that the aging of the sensorimotor and cognitive brain regions identified in this study has a covarying relationship with each other

Asymmetry, sex differences and age-related changes in the white matter in the healthy elderly: a tract-based study

<p>Abstract</p> <p>Background</p> <p>Hemispherical asymmetry, sex differences and age-related changes have been reported for the human brain. Meanwhile it was still unclear the presence of the asymmetry or sex differences in the human brain occurred whether as a normal development or as consequences of any pathological changes. The aim of this study was to investigate hemispherical asymmetry, sex differences and age-related changes by using a tract-based analysis in the nerve bundles.</p> <p>Methods</p> <p>40 healthy elderly subjects underwent magnetic resonance diffusion tensor imaging, and we calculated fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values along the major white matter bundles.</p> <p>Results</p> <p>We identified hemispherical asymmetry in the ADC values for the cingulate fasciculus in the total subject set and in males, and a sex difference in the FA values for the right uncinate fasciculus. For age-related changes, we demonstrated a significant increase in ADC values with advancing age in the right cingulum, left temporal white matter, and a significant decrease in FA values in the right superior longitudinal fasciculus.</p> <p>Conclusion</p> <p>In this study, we found hemispherical asymmetry, sex differences and age-related changes in particular regions of the white matter in the healthy elderly. Our results suggest considering these differences can be important in imaging studies.</p

Quantification of myelin loss in frontal lobe white matter in vascular dementia, Alzheimer's disease, and dementia with Lewy bodies

The aim of this study was to characterize myelin loss as one of the features of white matter abnormalities across three common dementing disorders. We evaluated post-mortem brain tissue from frontal and temporal lobes from 20 vascular dementia (VaD), 19 Alzheimer’s disease (AD) and 31 dementia with Lewy bodies (DLB) cases and 12 comparable age controls. Images of sections stained with conventional luxol fast blue were analysed to estimate myelin attenuation by optical density. Serial adjacent sections were then immunostained for degraded myelin basic protein (dMBP) and the mean percentage area containing dMBP (%dMBP) was determined as an indicator of myelin degeneration. We further assessed the relationship between dMBP and glutathione S-transferase (a marker of mature oligodendrocytes) immunoreactivities. Pathological diagnosis significantly affected the frontal but not temporal lobe myelin attenuation: myelin density was most reduced in VaD compared to AD and DLB, which still significantly exhibited lower myelin density compared to ageing controls. Consistent with this, the degree of myelin loss was correlated with greater %dMBP, with the highest %dMBP in VaD compared to the other groups. The %dMBP was inversely correlated with the mean size of oligodendrocytes in VaD, whereas it was positively correlated with their density in AD. A two-tier regression model analysis confirmed that the type of disorder (VaD or AD) determines the relationship between %dMBP and the size or density of oligodendrocytes across the cases. Our findings, attested by the use of three markers, suggest that myelin loss may evolve in parallel with shrunken oligodendrocytes in VaD but their increased density in AD, highlighting partially different mechanisms are associated with myelin degeneration, which could originate from hypoxic–ischaemic damage to oligodendrocytes in VaD whereas secondary to axonal degeneration in AD