Journal of Neuroimaging / Cortical Thickness Estimations of FreeSurfer and the CAT12 Toolbox in Patients with Alzheimers Disease and Healthy Controls

BACKGROUND AND PURPOSE Automated cortical thickness (CT) measurements are often used to assess gray matter changes in the healthy and diseased human brain. The FreeSurfer software is frequently applied for this type of analysis. The computational anatomy toolbox (CAT12) for SPM, which offers a fast and easytouse alternative approach, was recently made available. METHODS In this study, we compared region of interest (ROI)wise CT estimations of the surfacebased FreeSurfer 6 (FS6) software and the volumebased CAT12 toolbox for SPM using 44 elderly healthy female control subjects (HC). In addition, these 44 HCs from the crosssectional analysis and 34 age and sexmatched patients with Alzheimer's disease (AD) were used to assess the potential of detecting group differences for each method. Finally, a testretest analysis was conducted using 19 HC subjects. All data were taken from the OASIS database and MRI scans were recorded at 1.5 Tesla. RESULTS A strong correlation was observed between both methods in terms of ROI mean CT estimates (R2 = .83). However, CAT12 delivered significantly higher CT estimations in 32 of the 34 ROIs, indicating a systematic difference between both approaches. Furthermore, both methods were able to reliably detect atrophic brain areas in AD subjects, with the highest decreases in temporal areas. Finally, FS6 as well as CAT12 showed excellent testretest variability scores. CONCLUSION Although CT estimations were systematically higher for CAT12, this study provides evidence that this new toolbox delivers accurate and robust CT estimates and can be considered a fast and reliable alternative to FreeSurfer.(VLID)342385

Human Brain Mapping / Comparison of continuously acquired resting state and extracted analogues from active tasks

Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on restingstate data, the application to taskspecific fMRI has received growing attention. Three major methods for extraction of restingstate data from taskrelated signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located inbetween task blocks. Despite widespread application in current research, consensus on which method best resembles restingstate seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous restingstate, two different task paradigms were assessed (emotion discrimination and right fingertapping) and five welldescribed networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous restingstate (Dice, Intraclass correlation coefficient (ICC), R2) showed that regression against task effects yields functional connectivity networks most alike to restingstate. However, all methods exhibited significant differences when compared to continuous restingstate and similarity metrics were lower than testretest of two restingstate scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to restingstate when extracting signals from task designs, although functional connectivity computed from taskspecific data may indeed yield interesting information.(VLID)484322

White matter microstructure in transsexuals and controls investigated by diffusion tensor imaging

Biological causes underpinning the well known gender dimorphisms in human behavior, cognition, and emotion have received increased attention in recent years. The advent of diffusion-weighted magnetic resonance imaging has permitted the investigation of the white matter microstructure in unprecedented detail. Here, we aimed to study the potential influences of biological sex, gender identity, sex hormones, and sexual orientation on white matter microstructure by investigating transsexuals and healthy controls using diffusion tensor imaging (DTI). Twenty-three female-to-male (FtM) and 21 male-to-female (MtF) transsexuals, as well as 23 female (FC) and 22 male (MC) controls underwent DTI at 3 tesla. Fractional anisotropy, axial, radial, and mean diffusivity were calculated using tract-based spatial statistics (TBSS) and fiber tractography. Results showed widespread significant differences in mean diffusivity between groups in almost all white matter tracts. FCs had highest mean diffusivities, followed by FtM transsexuals with lower values, MtF transsexuals with further reduced values, and MCs with lowest values. Investigating axial and radial diffusivities showed that a transition in axial diffusivity accounted for mean diffusivity results. No significant differences in fractional anisotropy maps were found between groups. Plasma testosterone levels were strongly correlated with mean, axial, and radial diffusivities. However, controlling for individual estradiol, testosterone, or progesterone plasma levels or for subjects' sexual orientation did not change group differences. Our data harmonize with the hypothesis that fiber tract development is influenced by the hormonal environment during late prenatal and early postnatal brain development

Structural Connectivity Networks of Transgender People

Although previous investigations of transsexual people have focused on regional brain alterations, evaluations on a network level, especially those structural in nature, are largely missing. Therefore, we investigated the structural connectome of 23 female-to-male (FtM) and 21 male-to-female (MtF) transgender patients before hormone therapy as compared with 25 female and 25 male healthy controls. Graph theoretical analysis of whole-brain probabilistic tractography networks (adjusted for differences in intracranial volume) showed decreased hemispheric connectivity ratios of subcortical/limbic areas for both transgender groups. Subsequent analysis revealed that this finding was driven by increased interhemispheric lobar connectivity weights (LCWs) in MtF transsexuals and decreased intrahemispheric LCWs in FtM patients. This was further reflected on a regional level, where the MtF group showed mostly increased local efficiencies and FtM patients decreased values. Importantly, these parameters separated each patient group from the remaining subjects for the majority of significant findings. This work complements previously established regional alterations with important findings of structural connectivity. Specifically, our data suggest that network parameters may reflect unique characteristics of transgender patients, whereas local physiological aspects have been shown to represent the transition from the biological sex to the actual gender identity

Testosterone affects language areas of the adult human brain

Although the sex steroid hormone testosterone is integrally involved in the development of language processing, ethical considerations mostly limit investigations to single hormone administrations. To circumvent this issue we assessed the influence of continuous high-dose hormone application in adult female-to-male transsexuals. Subjects underwent magnetic resonance imaging before and after 4 weeks of testosterone treatment, with each scan including structural, diffusion weighted and functional imaging. Voxel-based morphometry analysis showed decreased gray matter volume with increasing levels of bioavailable testosterone exclusively in Broca's and Wernicke's areas. Particularly, this may link known sex differences in language performance to the influence of testosterone on relevant brain regions. Using probabilistic tractography, we further observed that longitudinal changes in testosterone negatively predicted changes in mean diffusivity of the corresponding structural connection passing through the extreme capsule. Considering a related increase in myelin staining in rodents, this potentially reflects a strengthening of the fiber tract particularly involved in language comprehension. Finally, functional images at resting-state were evaluated, showing increased functional connectivity between the two brain regions with increasing testosterone levels. These findings suggest testosterone-dependent neuroplastic adaptations in adulthood within language-specific brain regions and connections. Importantly, deteriorations in gray matter volume seem to be compensated by enhancement of corresponding structural and functional connectivity. Hum Brain Mapp 37:1738-1748, 2016. © 2016 Wiley Periodicals, Inc

Task-relevant brain networks identified with simultaneous PET/MR imaging of metabolism and connectivity

Except for task-specific functional MRI, the vast majority of imaging studies assessed human brain function at resting conditions. However, tracking task-specific neuronal activity yields important insight how the brain responds to stimulation. We specifically investigated changes in glucose metabolism, functional connectivity and white matter microstructure during task performance using several recent methodological advancements. Opening the eyes and right finger tapping had elicited an increased glucose metabolism in primary visual and motor cortices, respectively. Furthermore, a decreased metabolism was observed in the regions of the default mode network, which allowed absolute quantification of commonly described deactivations during cognitive tasks. These brain regions showed widespread task-specific changes in functional connectivity, which stretched beyond their primary resting-state networks and presumably reflected the level of recruitment of certain brain regions for each task. Finally, the corresponding white matter fiber pathways exhibited changes in axial and radial diffusivity during the tasks, which were regionally distinctive for certain tract groups. These results highlight that even simple task performance leads to substantial changes of entire brain networks. Exploiting the complementary nature of the different imaging modalities may reveal novel insights how the brain processes external stimuli and which networks are involved in certain tasks.(VLID)473577