How Does the Accuracy of Intracranial Volume Measurements Affect Normalized Brain Volumes? Sample Size Estimates Based on 966 Subjects from the HUNT MRI Cohort

Determination of Species-Specific Differences in Intracranial Volume of Tuj Sheep and Hair Goats Using Stereology and Computed Tomography Methods

The intracranial cavity contains vitally important organs. The brain, cerebellum, meninges and the vessels that supply these organs are located in the intracranial cavity. Therefore, it is important to learn about the intracranial cavity and to study it. However, there is limited information about the intracranial cavity in the veterinary field. The aim of this study was to determine the differences between the intracranial cavities of different species of animals by using stereology and tomography methods, volume calculations and morphometric measurements. In addition, the compatibility of the methods used with each other was investigated. In the study, six male adult goats and six male adult sheep were used. In this study, the intracranial cavities of sheep and goats were calculated by using Cavalieri's principle and 3D modelling using tomography sections. Morphometric measurements were taken over the intracranial space, and index calculations were made. In 3D models using computed tomography, the intracranial volume was 153.31 ± 24.06 cm3 in goats and 128.07 ± 7.93 cm3 in sheep. In the calculation using Cavalieri's principle, it was determined to be 152.73 ± 22.73 cm3 in goats and 126.15 ± 8.38 cm3 in sheep. As a result of the study, the MWCC (maximum width of the cranial cavity) parameter was found to be statistically significant between species (p < 0.05). The two methods used in Bland-Altman analysis were found to be within the limits of agreement, and the methods can be alternative to each other.

Blood-brain barrier integrity is linked to cognitive function, but not to cerebral arterial pulsatility, among elderly

Blood-brain barrier (BBB) disruption may contribute to cognitive decline, but questions remain whether this association is more pronounced for certain brain regions, such as the hippocampus, or represents a whole-brain mechanism. Further, whether human BBB leakage is triggered by excessive vascular pulsatility, as suggested by animal studies, remains unknown. In a prospective cohort (N = 50; 68-84 years), we used contrast-enhanced MRI to estimate the permeability-surface area product (PS) and fractional plasma volume ( v p ), and 4D flow MRI to assess cerebral arterial pulsatility. Cognition was assessed by the Montreal Cognitive Assessment (MoCA) score. We hypothesized that high PS would be associated with high arterial pulsatility, and that links to cognition would be specific to hippocampal PS. For 15 brain regions, PS ranged from 0.38 to 0.85 (·10-3 min-1) and v p from 0.79 to 1.78%. Cognition was related to PS (·10-3 min-1) in hippocampus (β = - 2.9; p = 0.006), basal ganglia (β = - 2.3; p = 0.04), white matter (β = - 2.6; p = 0.04), whole-brain (β = - 2.7; p = 0.04) and borderline-related for cortex (β = - 2.7; p = 0.076). Pulsatility was unrelated to PS for all regions (p > 0.19). Our findings suggest PS-cognition links mainly reflect a whole-brain phenomenon with only slightly more pronounced links for the hippocampus, and provide no evidence of excessive pulsatility as a trigger of BBB disruption.

Mapping brain volume change across time in primary-progressive multiple sclerosis

PURPOSE

Detection and prediction of the rate of brain volume loss with age is a significant unmet need in patients with primary progressive multiple sclerosis (PPMS). In this study we construct detailed brain volume maps for PPMS patients. These maps compare age-related changes in both cortical and sub-cortical regions with those in healthy individuals.

METHODS

We conducted retrospective analyses of brain volume using T1-weighted Magnetic Resonance Imaging (MRI) scans of a large cohort of PPMS patients and healthy subjects. The volume of brain parenchyma (BP), cortex, white matter (WM), deep gray matter, thalamus, and cerebellum were measured using the robust SynthSeg segmentation tool. Age- and gender-related regression curves were constructed based on data from healthy subjects, with the 95% prediction interval adopted as the normality threshold for each brain region.

RESULTS

We analyzed 495 MRI scans from 169 PPMS patients, aged 20-79 years, alongside 563 exams from healthy subjects aged 20-86. Compared to healthy subjects, a higher proportion of PPMS patients showed lower than expected brain volumes in all regions except the cerebellum. The most affected areas were BP, WM, and thalamus. Lower brain volumes correlated with longer disease duration for BP and WM, and higher disability for BP, WM, cortex, and thalamus.

CONCLUSIONS

Constructing age- and gender-related brain volume maps enabled identifying PPMS patients at a higher risk of brain volume loss. Monitoring these high-risk patients may lead to better treatment decisions and improve patient outcomes.

Localization of stuttering based on causal brain lesions

Stuttering affects approximately 1 in 100 adults and can result in significant communication problems and social anxiety. It most often occurs as a developmental disorder but can also be caused by focal brain damage. These latter cases may lend unique insight into the brain regions causing stuttering. Here, we investigated the neuroanatomical substrate of stuttering using three independent datasets: (i) case reports from the published literature of acquired neurogenic stuttering following stroke (n = 20, 14 males/six females, 16-77 years); (ii) a clinical single study cohort with acquired neurogenic stuttering following stroke (n = 20, 13 males/seven females, 45-87 years); and (iii) adults with persistent developmental stuttering (n = 20, 14 males/six females, 18-43 years). We used the first two datasets and lesion network mapping to test whether lesions causing acquired stuttering map to a common brain network. We then used the third dataset to test whether this lesion-based network was relevant to developmental stuttering. In our literature dataset, we found that lesions causing stuttering occurred in multiple heterogeneous brain regions, but these lesion locations were all functionally connected to a common network centred around the left putamen, including the claustrum, amygdalostriatal transition area and other adjacent areas. This finding was shown to be specific for stuttering (PFWE < 0.05) and reproducible in our independent clinical cohort of patients with stroke-induced stuttering (PFWE < 0.05), resulting in a common acquired stuttering network across both stroke datasets. Within the common acquired stuttering network, we found a significant association between grey matter volume and stuttering impact for adults with persistent developmental stuttering in the left posteroventral putamen, extending into the adjacent claustrum and amygdalostriatal transition area (PFWE < 0.05). We conclude that lesions causing acquired neurogenic stuttering map to a common brain network, centred to the left putamen, claustrum and amygdalostriatal transition area. The association of this lesion-based network with symptom severity in developmental stuttering suggests a shared neuroanatomy across aetiologies.

Detecting conversion from mild cognitive impairment to Alzheimer's disease using FLAIR MRI biomarkers

Mild cognitive impairment (MCI) is the prodromal phase of Alzheimer's disease (AD) and while it presents as an imperative intervention window, it is difficult to detect which subjects convert to AD (cMCI) and which ones remain stable (sMCI). The objective of this work was to investigate fluid-attenuated inversion recovery (FLAIR) MRI biomarkers and their ability to differentiate between sMCI and cMCI subjects in cross-sectional and longitudinal data. Three types of biomarkers were investigated: volume, intensity and texture. Volume biomarkers included total brain volume, cerebrospinal fluid volume (CSF), lateral ventricular volume, white matter lesion volume, subarachnoid CSF, and grey matter (GM) and white matter (WM), all normalized to intracranial volume. The mean intensity, kurtosis, and skewness of the GM and WM made up the intensity features. Texture features quantified homogeneity and microstructural tissue changes of GM and WM regions. Composite indices were also considered, which are biomarkers that represent an aggregate sum (z-score normalization and summation) of all biomarkers. The FLAIR MRI biomarkers successfully identified high-risk subjects as significant differences (p < 0.05) were found between the means of the sMCI and cMCI groups and the rate of change over time for several individual biomarkers as well as the composite indices for both cross-sectional and longitudinal analyses. Classification accuracy and feature importance analysis showed volume biomarkers to be most predictive, however, best performance was obtained when complimenting the volume biomarkers with the intensity and texture features. Using all the biomarkers, accuracy of 86.2 % and 69.2 % was achieved for normal control-AD and sMCI-cMCI classification respectively. Survival analysis demonstrated that the majority of the biomarkers showed a noticeable impact on the AD conversion probability 4 years prior to conversion. Composite indices were the top performers for all analyses including feature importance, classification, and survival analysis. This demonstrated their ability to summarize various dimensions of disease into single-valued metrics. Significant correlation (p < 0.05) with phosphorylated-tau and amyloid-beta CSF biomarkers was found with all the FLAIR biomarkers. The proposed biomarker system is easily attained as FLAIR is routinely acquired, models are not computationally intensive and the results are explainable, thus making this pipeline easily integrated into clinical workflow.

Development and validation of a deep learning-based automatic segmentation model for assessing intracranial volume: comparison with NeuroQuant, FreeSurfer, and SynthSeg

Background and purpose

To develop and validate a deep learning-based automatic segmentation model for assessing intracranial volume (ICV) and to compare the accuracy determined by NeuroQuant (NQ), FreeSurfer (FS), and SynthSeg.

Materials and methods

This retrospective study included 60 subjects [30 Alzheimer's disease (AD), 21 mild cognitive impairment (MCI), 9 cognitively normal (CN)] from a single tertiary hospital for the training and validation group (50:10). The test group included 40 subjects (20 AD, 10 MCI, 10 CN) from the ADNI dataset. We propose a robust ICV segmentation model based on the foundational 2D UNet architecture trained with four types of input images (both single and multimodality using scaled or unscaled T1-weighted and T2-FLAIR MR images). To compare with our model, NQ, FS, and SynthSeg were also utilized in the test group. We evaluated the model performance by measuring the Dice similarity coefficient (DSC) and average volume difference.

Results

The single-modality model trained with scaled T1-weighted images showed excellent performance with a DSC of 0.989 ± 0.002 and an average volume difference of 0.46% ± 0.38%. Our multimodality model trained with both unscaled T1-weighted and T2-FLAIR images showed similar performance with a DSC of 0.988 ± 0.002 and an average volume difference of 0.47% ± 0.35%. The overall average volume difference with our model showed relatively higher accuracy than NQ (2.15% ± 1.72%), FS (3.69% ± 2.93%), and SynthSeg (1.88% ± 1.18%). Furthermore, our model outperformed the three others in each subgroup of patients with AD, MCI, and CN subjects.

Conclusion

Our deep learning-based automatic ICV segmentation model showed excellent performance for the automatic evaluation of ICV.

Cerebral electrometabolic coupling in disordered and normal states of consciousness

We assess cerebral integrity with cortical and subcortical FDG-PET and cortical electroencephalography (EEG) within the mesocircuit model framework in patients with disorders of consciousness (DoCs). The mesocircuit hypothesis proposes that subcortical activation facilitates cortical function. We find that the metabolic balance of subcortical mesocircuit areas is informative for diagnosis and is associated with four EEG-based power spectral density patterns, cortical metabolism, and α power in healthy controls and patients with a DoC. Last, regional electrometabolic coupling at the cortical level can be identified in the θ and α ranges, showing positive and negative relations with glucose uptake, respectively. This relation is inverted in patients with a DoC, potentially related to altered orchestration of neural activity, and may underlie suboptimal excitability states in patients with a DoC. By understanding the neurobiological basis of the pathophysiology underlying DoCs, we foresee translational value for diagnosis and treatment of patients with a DoC.

Normal human craniofacial growth and development from 0 to 4 years

Knowledge of human craniofacial growth (increase in size) and development (change in shape) is important in the clinical treatment of a range of conditions that affects it. This study uses an extensive collection of clinical CT scans to investigate craniofacial growth and development over the first 48 months of life, detail how the cranium changes in form (size and shape) in each sex and how these changes are associated with the growth and development of various soft tissues such as the brain, eyes and tongue and the expansion of the nasal cavity. This is achieved through multivariate analyses of cranial form based on 3D landmarks and semi-landmarks and by analyses of linear dimensions, and cranial volumes. The results highlight accelerations and decelerations in cranial form changes throughout early childhood. They show that from 0 to 12 months, the cranium undergoes greater changes in form than from 12 to 48 months. However, in terms of the development of overall cranial shape, there is no significant sexual dimorphism in the age range considered in this study. In consequence a single model of human craniofacial growth and development is presented for future studies to examine the physio-mechanical interactions of the craniofacial growth.

APOEε4 associates with microglial activation independently of Aβ plaques and tau tangles

Animal studies suggest that the apolipoprotein E ε4 (APOEε4) allele is a culprit of early microglial activation in Alzheimer's disease (AD). Here, we tested the association between APOEε4 status and microglial activation in living individuals across the aging and AD spectrum. We studied 118 individuals with positron emission tomography for amyloid-β (Aβ; [18F]AZD4694), tau ([18F]MK6240), and microglial activation ([11C]PBR28). We found that APOEε4 carriers presented increased microglial activation relative to noncarriers in early Braak stage regions within the medial temporal cortex accounting for Aβ and tau deposition. Furthermore, microglial activation mediated the Aβ-independent effects of APOEε4 on tau accumulation, which was further associated with neurodegeneration and clinical impairment. The physiological distribution of APOE mRNA expression predicted the patterns of APOEε4-related microglial activation in our population, suggesting that APOE gene expression may regulate the local vulnerability to neuroinflammation. Our results support that the APOEε4 genotype exerts Aβ-independent effects on AD pathogenesis by activating microglia in brain regions associated with early tau deposition.

Brain Anatomical Alterations in Young Cannabis Users: Is it All Hype? A Meta-Analysis of Structural Neuroimaging Studies

Introduction: Cannabis use has a high prevalence in young youth and is associated with poor psychosocial outcomes. Such outcomes have been ascribed to the impact of cannabis exposure on the developing brain. However, findings from individual studies of volumetry in youth cannabis users are equivocal. Objectives: Our primary objective was to systematically review the evidence on brain volume differences between young cannabis users and nonusers aged 12-26 where profound neuromaturation occurs, accounting for the role of global brain volumes (GBVs). Our secondary objective was to systematically integrate the findings on the association between youth age and volumetry in youth cannabis users. Finally, we aimed to evaluate the quality of the evidence. Materials and Methods: A systematic search was run in three databases (PubMed, Scopus, and PsycINFO) and was reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We run meta-analyses (with and without controlling for GBV) of brain volume differences between young cannabis users and nonusers. We conducted metaregressions to explore the role of age on volumetric differences. Results: Sixteen studies were included. The reviewed samples included 830 people with mean age 22.5 years (range 14-26 years). Of these, 386 were cannabis users (with cannabis use onset at 15-19 years) and 444 were controls. We found no detectable group differences in any of the GBVs (intracranium, total brain, total white matter, and total gray matter) and regional brain volumes (i.e., hippocampus, amygdala, orbitofrontal cortex, and total cerebellum). Age and cannabis use level did not predict (standardized mean) volume group differences in metaregression. We found little evidence of publication bias (Egger's test p>0.1). Conclusions: Contrary to evidence in adult samples (or in samples mixing adults and youth), previous single studies in young cannabis users, and meta-analyses of brain function in young cannabis users, this early evidence suggests nonsignificant volume differences between young cannabis users and nonusers. While prolonged and long-term exposure to heavy cannabis use may be required to detect gross volume alterations, more studies in young cannabis users are needed to map in detail cannabis-related neuroanatomical changes.

Association of CSF GAP-43 With the Rate of Cognitive Decline and Progression to Dementia in Amyloid-Positive Individuals

BACKGROUND AND OBJECTIVES

To test the associations between the presynaptic growth-associated protein 43 (GAP-43), quantified in CSF, and biomarkers of Alzheimer disease (AD) pathophysiology, cross-sectionally and longitudinally.

METHODS

In this retrospective study, GAP-43 was measured in participants from the AD Neuroimaging Initiative (ADNI) cohort using an in-house ELISA method, and levels were compared between groups, both cross-sectionally and longitudinally. Linear regression models tested the associations between biomarkers of AD (amyloid beta [Aβ] and tau pathologies, neurodegeneration, and cognition) adjusted by age, sex, and diagnosis. Linear mixed-effect models evaluated how baseline GAP-43 predicts brain hypometabolism, atrophy, and cognitive decline over time. Cox proportional hazard regression models tested how GAP-43 levels and Aβ status, at baseline, increased the risk of progression to AD dementia over time.

RESULTS

This study included 786 participants from the ADNI cohort, which were further classified in cognitively unimpaired (CU) Aβ-negative (nCU- = 197); CU Aβ-positive (nCU+ = 55), mild cognitively impaired (MCI) Aβ-negative (nMCI- = 228), MCI Aβ-positive (nMCI+ = 193), and AD dementia Aβ-positive (nAD = 113). CSF GAP-43 levels were increased in Aβ-positive compared with Aβ-negative participants, independent of the cognitive status. In Aβ-positive participants, high baseline GAP-43 levels led to worse brain metabolic decline (p = 0.01), worse brain atrophy (p = 8.8 × 10-27), and worse MMSE scores (p = 0.03) over time, as compared with those with low GAP-43 levels. Similarly, Aβ-positive participants with high baseline GAP-43 had the highest risk to convert to AD dementia (hazard ratio [HR = 8.56, 95% CI 4.94-14.80, p = 1.5 × 10-14]). Despite the significant association with Aβ pathology (η2 Aβ PET = 0.09, P Aβ PET < 0.001), CSF total tau (tTau) and phosphorylated tau (pTau) had a larger effect size on GAP43 than Aβ PET (η2 pTau-181 = 0.53, P pTau-181 < 0.001; η2 tTau = 0.59, P tTau < 0.001).

DISCUSSION

High baseline levels of CSF GAP-43 are associated with progression in Aβ-positive individuals, with a more aggressive neurodegenerative process, faster rate of cognitive decline, and increased risk of converting to dementia.

Coupling Between Hippocampal Parenchymal Fraction and Cortical Grey Matter Atrophy at Different Stages of Cognitive Decline

BACKGROUND

Hippocampal atrophy is a significant brain marker of pathology in Alzheimer's disease (AD). The hippocampal parenchymal fraction (HPF) was recently developed to better assess the hippocampal volumetric integrity, and it has been shown to be a sensitive measure of hippocampal atrophy in AD.

OBJECTIVE

To investigate the clinical relevance of hippocampal volumetric integrity as measured by the HPF and the coupling between the HPF and brain atrophy during AD progression.

METHODS

We included data from 143 cognitively normal (CN), 101 mild cognitive impairment (MCI), and 125 AD participants. We examined group differences in the HPF, associations between HPF and cognitive ability, and coupling between the HPF and cortical grey matter volume in the CN, MCI, and AD groups.

RESULTS

We observed progressive decreases in HPF from CN to MCI and from MCI to AD, and increases in the asymmetry of HPF, with the lowest asymmetry index (AI) in the CN group and the highest AI in the AD group. There was a significant association between HPF and cognitive ability across participants. The coupling between HPF and cortical regions was observed in bilateral hippocampus, parahippocampal gyrus, temporal, frontal, and occipital regions, thalamus, and amygdala in CN, MCI, and AD groups, with a greater involvement of temporal, occipital, frontal, and subcortical regions in MCI and AD patients, especially in AD patients.

CONCLUSION

This study provides novel evidence for the neuroanatomical basis of cognitive decline and brain atrophy during AD progression, which may have important clinical implications for the prognosis of AD.

Both brain size and biological sex contribute to variation in white matter microstructure in middle-aged healthy adults

Whether head size and/or biological sex influence proxies of white matter (WM) microstructure such as fractional anisotropy (FA) and mean diffusivity (MD) remains controversial. Diffusion tensor imaging (DTI) indices are also associated with age, but there are large discrepancies in the spatial distribution and timeline of age-related differences reported. The aim of this study was to evaluate the associations between intracranial volume (ICV), sex, and age and DTI indices from WM in a population-based study of healthy individuals (n = 812) aged 50-66 in the Nord-Trøndelag health survey. Semiautomated tractography and tract-based spatial statistics (TBSS) analyses were performed on the entire sample and in an ICV-matched sample of men and women. The tractography results showed a similar positive association between ICV and FA in all major WM tracts in men and women. Associations between ICV and MD, radial diffusivity and axial diffusivity were also found, but to a lesser extent than FA. The TBSS results showed that both men and women had areas of higher and lower FA when controlling for age, but after controlling for age and ICV only women had areas with higher FA. The ICV matched analysis also demonstrated that only women had areas of higher FA. Age was negatively associated with FA across the entire WM skeleton in the TBSS analysis, independent of both sex and ICV. Combined, these findings demonstrated that both ICV and sex contributed to variation in DTI indices and emphasized the importance of considering ICV as a covariate in DTI analysis.

Amygdala subnuclear volumes in temporal lobe epilepsy with hippocampal sclerosis and in non-lesional patients

Together with hippocampus, the amygdala is important in the epileptogenic network of patients with temporal lobe epilepsy. Recently, an increase in amygdala volumes (i.e. amygdala enlargement) has been proposed as morphological biomarker of a subtype of temporal lobe epilepsy patients without MRI abnormalities, although other data suggest that this finding might be unspecific and not exclusive to temporal lobe epilepsy. In these studies, the amygdala is treated as a single entity, while instead it is composed of different nuclei, each with peculiar function and connection. By adopting a recently developed methodology of amygdala's subnuclei parcellation based of high-resolution T1-weighted image, this study aims to map specific amygdalar subnuclei participation in temporal lobe epilepsy due to hippocampal sclerosis (n = 24) and non-lesional temporal lobe epilepsy (n = 24) with respect to patients with focal extratemporal lobe epilepsies (n = 20) and healthy controls (n = 30). The volumes of amygdala subnuclei were compared between groups adopting multivariate analyses of covariance and correlated with clinical variables. Additionally, a logistic regression analysis on the nuclei resulting statistically different across groups was performed. Compared with other populations, temporal lobe epilepsy with hippocampal sclerosis showed a significant atrophy of the whole amygdala (p Bonferroni = 0.040), particularly the basolateral complex (p Bonferroni = 0.033), while the non-lesional temporal lobe epilepsy group demonstrated an isolated hypertrophy of the medial nucleus (p Bonferroni = 0.012). In both scenarios, the involved amygdala was ipsilateral to the epileptic focus. The medial nucleus demonstrated a volume increase even in extratemporal lobe epilepsies although contralateral to the seizure onset hemisphere (p Bonferroni = 0.037). Non-lesional patients with psychiatric comorbidities showed a larger ipsilateral lateral nucleus compared with those without psychiatric disorders. This exploratory study corroborates the involvement of the amygdala in temporal lobe epilepsy, particularly in mesial temporal lobe epilepsy and suggests a different amygdala subnuclei engagement depending on the aetiology and lateralization of epilepsy. Furthermore, the logistic regression analysis indicated that the basolateral complex and the medial nucleus of amygdala can be helpful to differentiate temporal lobe epilepsy with hippocampal sclerosis and with MRI negative, respectively, versus controls with a consequent potential clinical yield. Finally, the present results contribute to the literature about the amygdala enlargement in temporal lobe epilepsy, suggesting that the increased volume of amygdala can be regarded as epilepsy-related structural changes common across different syndromes whose meaning should be clarified.

Is intracranial volume a risk factor for IDH-mutant low-grade glioma? A case-control study

Purpose

Risk of cancer has been associated with body or organ size in several studies. We sought to investigate the relationship between intracranial volume (ICV) (as a proxy for lifetime maximum brain size) and risk of IDH-mutant low-grade glioma.

Methods

In a multicenter case–control study based on population-based data, we included 154 patients with IDH-mutant WHO grade 2 glioma and 995 healthy controls. ICV in both groups was calculated from 3D MRI brain scans using an automated reverse brain mask method, and then compared using a binomial logistic regression model.

Results

We found a non-linear association between ICV and risk of glioma with increasing risk above and below a threshold of 1394 ml (p < 0.001). After adjusting for ICV, sex was not a risk factor for glioma.

Conclusion

Intracranial volume may be a risk factor for IDH-mutant low-grade glioma, but the relationship seems to be non-linear with increased risk both above and below a threshold in intracranial volume.

Effects of a 5-Year Exercise Intervention on White Matter Microstructural Organization in Older Adults. A Generation 100 Substudy

Aerobic fitness and exercise could preserve white matter (WM) integrity in older adults. This study investigated the effect on WM microstructural organization of 5 years of exercise intervention with either supervised moderate-intensity continuous training (MICT), high-intensity interval training (HIIT), or following the national physical activity guidelines. A total of 105 participants (70-77 years at baseline), participating in the randomized controlled trial Generation 100 Study, volunteered to take part in this longitudinal 3T magnetic resonance imaging (MRI) study. The HIIT group (n = 33) exercised for four intervals of 4 min at 90% of peak heart rate two times a week, the MICT group (n = 24) exercised continuously for 50 min at 70% peak heart rate two times a week, and the control group (n = 48) followed the national guidelines of ≥30 min of physical activity almost every day. At baseline and at 1-, 3-, and 5-year follow-ups, diffusion tensor imaging (DTI) scans were performed, cardiorespiratory fitness (CRF) was measured as peak oxygen uptake (VO2peak) with ergospirometry, and information on exercise habits was collected. There was no group*time or group effect on any of the DTI indices at any time point during the intervention. Across all groups, CRF was positively associated with fractional anisotropy (FA) and axial diffusivity (AxD) at the follow-ups, and the effect became smaller with time. Exercise intensity was associated with mean diffusivity (MD)/FA, with the greatest effect at 1-year and no effect at 5-year follow-up. There was an association between exercise duration and FA and radial diffusivity (RD) only after 1 year. Despite the lack of group*time interaction or group effect, both higher CRF and exercise intensity was associated with better WM microstructural organization throughout the intervention, but the effect became attenuated over time. Different aspects of exercising affected the WM metrics and WM tracts differently with the greatest and most overlapping effects in the corpus callosum. The current study indicates not only that high CRF and exercise intensity are associated with WM microstructural organization in aging but also that exercise's positive effects on WM may decline with increasing age.

Longitudinal study of the effect of a 5-year exercise intervention on structural brain complexity in older adults. A Generation 100 substudy

Physical inactivity has been identified as an important risk factor for dementia. High levels of cardiorespiratory fitness (CRF) have been shown to reduce the risk of dementia. However, the mechanism by which exercise affects brain health is still debated. Fractal dimension (FD) is an index that quantifies the structural complexity of the brain. The purpose of this study was to investigate the effects of a 5-year exercise intervention on the structural complexity of the brain, measured through the FD, in a subset of 105 healthy older adults participating in the randomized controlled trial Generation 100 Study. The subjects were randomized into control, moderate intensity continuous training, and high intensity interval training groups. Both brain MRI and CRF were acquired at baseline and at 1-, 3- and 5-years follow-ups. Cortical thickness and volume data were extracted with FreeSurfer, and FD of the cortical lobes, cerebral and cerebellar gray and white matter were computed. CRF was measured as peak oxygen uptake (VO_2peak) using ergospirometry during graded maximal exercise testing. Linear mixed models were used to investigate exercise group differences and possible CRF effects on the brain's structural complexity. Associations between change over time in CRF and FD were performed if there was a significant association between CRF and FD. There were no effects of group membership on the structural complexity. However, we found a positive association between CRF and the cerebral gray matter FD (p < 0.001) and the temporal lobe gray matter FD (p < 0.001). This effect was not present for cortical thickness, suggesting that FD is a more sensitive index of structural changes. The change over time in CRF was associated with the change in temporal lobe gray matter FD from baseline to 5-year follow-up (p < 0.05). No association of the change was found between CRF and cerebral gray matter FD. These results demonstrated that entering old age with high and preserved CRF levels protected against loss of structural complexity in areas sensitive to aging and age-related pathology.

Five years of exercise intervention at different intensities and development of white matter hyperintensities in community dwelling older adults, a Generation 100 sub-study

We investigated if a five-year supervised exercise intervention with moderate-intensity continuous training (MICT) or high-intensity interval training (HIIT) versus control; physical activity according to national guidelines, attenuated the growth of white matter hyperintensities (WMH). We hypothesized that supervised exercise, in particular HIIT, reduced WMH growth. Older adults from the general population participating in the RCT Generation 100 Study were scanned at 3T MRI at baseline (age 70–77), and after 1-, 3- and 5-years. At each follow-up, cardiorespiratory fitness was measured with ergospirometry, and physical activity plus clinical data collected. Manually delineated total WMH, periventricular (PWMH), deep (DWMH), and automated total white matter hypointensity volumes were obtained. No group by time interactions were present in linear mixed model analyses with the different WMH measurements as outcomes. In the combined exercise (MICT&HIIT) group, a significant group by time interaction was uncovered for PWMH volume, with a larger increase in the MICT&HIIT group. Cardiorespiratory fitness at the follow-ups or change in cardiorespiratory fitness over time were not associated with any WMH measure. Contrary to our hypothesis, taking part in MICT or HIIT over a five-year period did not attenuate WMH growth compared to being in a control group following national physical activity guidelines.

Generalizing deep learning brain segmentation for skull removal and intracranial measurements

Total intracranial volume (TICV) and posterior fossa volume (PFV) are essential covariates for brain volumetric analyses with structural magnetic resonance imaging (MRI). Detailed whole brain segmentation provides a non-invasive way to measure brain regions. Furthermore, increasing neuroimaging data are distributed in a skull-stripped manner for privacy protection. Therefore, generalizing deep learning brain segmentation for skull removal and intracranial measurements is an appealing task. However, data availability is challenging due to a limited set of manually traced atlases with whole brain and TICV/PFV labels. In this paper, we employ U-Net tiles to achieve automatic TICV estimation and whole brain segmentation simultaneously on brains w/and w/o the skull. To overcome the scarcity of manually traced whole brain volumes, a transfer learning method is introduced to estimate additional TICV and PFV labels during whole brain segmentation in T1-weighted MRI. Specifically, U-Net tiles are first pre-trained using large-scale BrainCOLOR atlases without TICV and PFV labels, which are created by multi-atlas segmentation. Then the pre-trained models are refined by training the additional TICV and PFV labels using limited BrainCOLOR atlases. We also extend our method to handle skull-stripped brain MR images. From the results, our method provides promising whole brain segmentation and volume estimation results for both brains w/and w/o skull in terms of mean Dice similarity coefficients and mean surface distance and absolute volume similarity. This method has been made available in open source (https://github.com/MASILab/SLANTbrainSeg_skullstripped).

Effect of 5 Years of Exercise Intervention at Different Intensities on Brain Structure in Older Adults from the General Population: A Generation 100 Substudy

Purpose

The aim was to examine the effect of a 5-year exercise intervention at different intensities on brain structure in older adults from the general population partaking in the randomized controlled trial Generation 100 Study.

Participants and Methods

Generation 100 Study participants were invited to a longitudinal neuroimaging study before randomization. A total of 105 participants (52 women, 70–77 years) volunteered. Participants were randomized into supervised exercise twice a week performing high intensity interval training in 4×4 intervals at ~90% peak heart rate (HIIT, n = 33) or 50 minutes of moderate intensity continuous training at ~70% of peak heart rate (MICT, n = 24). The control group (n = 48) followed the national physical activity guidelines of ≥30 min physical activity daily. Brain MRI at 3T, clinical and cardiorespiratory fitness (CRF), measured as peak oxygen uptake, were collected at baseline, and after 1, 3, and 5 years of intervention. Brain volumes and cortical thickness were derived from T1 weighted 3D MRI data using FreeSurfer. The effect of HIIT or MICT on brain volumes over time was investigated with linear mixed models, while linear regressions examined the effect of baseline CRF on brain volumes at later time points.

Results

Adherence in each group was between 79 and 94% after 5 years. CRF increased significantly in all groups during the first year. Compared to controls, the HIIT group had significantly increased hippocampal atrophy located to CA1 and hippocampal body, though within normal range, and the MICT group greater thalamic atrophy. No other effects of intervention group were found. CRF across the intervention was not associated with brain structure, but CRF at baseline was positively associated with cortical volume at all later time points.

Conclusion

Higher baseline CRF reduced 5-year cortical atrophy rate in older adults, while following physical activity guidelines was associated with the lowest hippocampal and thalamic atrophy rates.

The APOE ε4 variant and hippocampal atrophy in Alzheimer's disease and Lewy body dementia: a systematic review of magnetic resonance imaging studies and therapeutic relevance

Introduction: The apolipoprotein E ɛ4-allele (APOE-ɛ4) increases the risk not only for Alzheimer's disease (AD) but also for Parkinson's disease dementia and dementia with Lewy bodies (collectively, Lewy body dementia [LBD]). Hippocampal volume is an important neuroimaging biomarker for AD and LBD, although its association with APOE-ɛ4 is inconsistently reported. We investigated the association of APOE-ε4 with hippocampal atrophy quantified using magnetic resonance imaging in AD and LBD.Areas covered: Databases were searched for volumetric and voxel-based morphometric studies published up until December 31^st, 2020. Thirty-nine studies (25 cross-sectional, 14 longitudinal) were included. We observed that (1) APOE-ε4 was associated with greater rate of hippocampal atrophy in longitudinal studies in AD and in those who progressed from mild cognitive impairment to AD, (2) association of APOE-ε4 with hippocampal atrophy in cross-sectional studies was inconsistent, (3) APOE-ɛ4 may influence hippocampal atrophy in dementia with Lewy bodies, although longitudinal investigations are needed. We comprehensively discussed methodological aspects, APOE-based therapeutic approaches, and the association of APOE-ε4 with hippocampal sub-regions and cognitive performance.Expert opinion: The role of APOE-ɛ4 in modulating hippocampal phenotypes may be further clarified through more homogenous, well-powered, and pathology-proven, longitudinal investigations. Understanding the underlying mechanisms will facilitate the development of prevention strategies targeting APOE-ɛ4.

Clinical adaptation of synthetic MRI-based whole brain volume segmentation in children at 3 T: comparison with modified SPM segmentation methods

PURPOSE

To validate the use of synthetic magnetic resonance imaging (SyMRI) volumetry by comparing with child-optimized SPM 12 volumetry in 3 T pediatric neuroimaging.

METHODS

In total, 106 children aged 4.7-18.7 years who underwent both synthetic and 3D T1-weighted imaging and had no abnormal imaging/neurologic findings were included for the SyMRI vs. SPM T1-only segmentation (SPM T1). Forty of the 106 children who underwent an additional 3D T2-weighted imaging were included for the SyMRI vs. SPM multispectral segmentation (SPM multi). SPM segmentation using an age-appropriate atlas and inverse-transforming template-space intracranial mask was compared with SyMRI segmentation. Volume differences between SyMRI and SPM T1 were plotted against age to evaluate the influence of age on volume difference.

RESULTS

Measurements derived from SyMRI and two SPM methods showed excellent agreements and strong correlations except for the CSF volume (CSFV) (intraclass correlation coefficients = 0.87-0.98; r = 0.78-0.96; relative volume difference other than CSFV = 6.8-18.5% [SyMRI vs. SPM T1] and 11.3-22.7% [SyMRI vs. SPM multi]). Dice coefficients of all brain tissues (except CSF) were in the range 0.78-0.91. The Bland-Altman plot and age-related volume difference change suggested that the volume differences between the two methods were influenced by the volume of each brain tissue and subject's age (p < 0.05).

CONCLUSION

SyMRI and SPM segmentation results were consistent except for CSFV, which supports routine clinical use of SyMRI-based volumetry in pediatric neuroimaging. However, caution should be taken in the interpretation of the CSF segmentation results.

Trace Elements in the Large Population-Based HUNT3 Survey

The Nord-Trøndelag Health Study (The HUNT Study) is a large health survey population study in the county of Trøndelag, Norway. The survey has been repeated four times in about 10-year intervals. In the HUNT3 survey (2006-2008), we collected 28,000 samples for trace element analysis. Blood samples from 758 healthy persons without known occupational exposure were selected for multielement analysis of a small sample of blood (0.25 mL). The aim of the study was to determine the minimum blood volume that can be used for the analytical procedure and to compare our results with previously published results of similar surveys in healthy populations. Samples were digested and the concentration of selected trace elements was determined by ICP-MS. We report results on essential elements (B, Co, Cu, Mn, Se and Zn) as well as non-essential elements (As, Be, Br, Cd, Cs, In, La, Pb, Hg, Nd, Ni, Nb, Pd, Pt, Sm, Ta and Sn). Results are similar to previous studies on the HUNT3 population, and with a few exceptions, our data compares very well with results obtained in recent studies from other countries. We wanted to test a minimum volume of blood in a large-scale analytical program. For a number of nonessential elements, our results were below the limit of detection. We suggest that future studies using similar ICP-MS equipment as analytical tool should use at least 0.5 mL of blood.

Cerebral arterial pulsatility is linked to hippocampal microvascular function and episodic memory in healthy older adults

Microvascular damage in the hippocampus is emerging as a central cause of cognitive decline and dementia in aging. This could be a consequence of age-related decreases in vascular elasticity, exposing hippocampal capillaries to excessive cardiac-related pulsatile flow that disrupts the blood-brain barrier and the neurovascular unit. Previous studies have found altered intracranial hemodynamics in cognitive impairment and dementia, as well as negative associations between pulsatility and hippocampal volume. However, evidence linking features of the cerebral arterial flow waveform to hippocampal function is lacking. We used a high-resolution 4D flow MRI approach to estimate global representations of the time-resolved flow waveform in distal cortical arteries and in proximal arteries feeding the brain in healthy older adults. Waveform-based clustering revealed a group of individuals featuring steep systolic onset and high amplitude that had poorer hippocampus-sensitive episodic memory (p = 0.003), lower whole-brain perfusion (p = 0.001), and weaker microvascular low-frequency oscillations in the hippocampus (p = 0.035) and parahippocampal gyrus (p = 0.005), potentially indicating compromised neurovascular unit integrity. Our findings suggest that aberrant hemodynamic forces contribute to cerebral microvascular and hippocampal dysfunction in aging.

What does hand motor function tell us about our aging brain in association with WMH?

Background

White matter hyperintensities (WMH) are a common cerebral finding in older people. WMH are usually asymptomatic, but excessive WMH are associated with cognitive decline and dementia. WMH are also among the neurological findings most consistently associated with declining motor performance in healthy ageing.

Aims

To determine if WMH load is associated with simple and complex motor movements in dominant and non-dominant hands in cognitively intact older subjects.

Methods

Hand motor performance was assessed with the Purdue Pegboard and Finger-tapping tests on 44 healthy right-handed participants, mean age 70.9 years (range 59–84 years). Participants also underwent magnetic resonance (MR) imaging, which were used to quantify WMH volume. The effect of WMH on the motor parameters was assessed via mediation analyses.

Results

WMH load increased significantly with age, while the motor scores decreased significantly with age. WMH load mediated only the relationship between age and left-hand pegboard scores.

Discussion

WMH mediated only the more complex Purdue Pegboard task for the non-dominant hand. This is likely because complex movements in the non-dominant hand recruit a larger cerebral network, which is more vulnerable to WMH.

Conclusions

Complex hand movements in the non-dominant hand are mediated by WMH. Subtle loss of motor movements of non-dominant hand might predict future excessive white matter atrophy.

Alcohol Consumption, Brain Amyloid-β Deposition, and Brain Structural Integrity Among Older Adults Free of Dementia

BACKGROUND

Light to moderate alcohol consumption has been variably associated with lower or higher risk of dementia, but effects on Alzheimer's disease pathology are less clear.

OBJECTIVE

We determined whether late-life alcohol consumption was associated with Alzheimer's disease pathology among older adults.

METHODS

We assessed the associations of alcohol consumption self-reported in 2000-2002 with brain amyloid-β deposition on PET scans, and white matter lesion and hippocampal volume on MRIs measured 7-9 years later in 189 participants of the Ginkgo Evaluation of Memory Study (age 75-87 years at baseline) who were free of clinical dementia, using multivariable-adjusted and inverse probability-weighted robust linear regression models.

RESULTS

Alcohol consumption was not statistically significantly associated with amyloid-β deposition (standardized uptake value ratio difference per drink: -0.013 [95% CI: -0.027, 0.002]). Both non-drinkers and participants consuming ≥1 drink(s)/week had higher white matter lesion volume (% intracranial volume) than did the reference group of those consuming <1 drink/week (differences: 0.25 % [95% CI: 0.01, 0.50]; 0.26 % [95% CI: 0.02, 0.50]). The association of alcohol consumption and hippocampal volume was modified by age (p = 0.02). Among participants younger than 77 years, participants consuming 1-7 drinks/week had larger hippocampal volume compared with participants consuming <1 drink/week.

CONCLUSIONS

Alcohol consumption was not statistically significantly associated with amyloid-β deposition 7-9 years later. Non-drinking and greater alcohol consumption were associated with higher white matter lesion volume compared with drinking <1 drink/week. Moderate drinking was associated with higher hippocampal volume in younger individuals. Given the selective nature of this population and adverse health effects of excessive alcohol consumption, these findings warrant further investigation, but cannot be translated into clinical recommendations.

Significant Impact of Coffee Consumption on MR-Based Measures of Cardiac Function in a Population-Based Cohort Study without Manifest Cardiovascular Disease

Subclinical effects of coffee consumption (CC) with regard to metabolic, cardiac, and neurological complications were evaluated using a whole-body magnetic resonance imaging (MRI) protocol. A blended approach was used to estimate habitual CC in a population-based study cohort without a history of cardiovascular disease. Associations of CC with MRI markers of gray matter volume, white matter hyperintensities, cerebral microhemorrhages, total and visceral adipose tissue (VAT), hepatic proton density fat fraction, early/late diastolic filling rate, end-diastolic/-systolic and stroke volume, ejection fraction, peak ejection rate, and myocardial mass were evaluated by linear regression. In our analysis with 132 women and 168 men, CC was positively associated with MR-based cardiac function parameters including late diastolic filling rate, stroke volume (p < 0.01 each), and ejection fraction (p < 0.05) when adjusting for age, sex, smoking, hypertension, diabetes, Low-density lipoprotein (LDL), triglycerides, cholesterol, and alcohol consumption. CC was inversely associated with VAT independent of demographic variables and cardiovascular risk factors (p < 0.05), but this association did not remain significant after additional adjustment for alcohol consumption. CC was not significantly associated with potential neurodegeneration. We found a significant positive and independent association between CC and MRI-based systolic and diastolic cardiac function. CC was also inversely associated with VAT but not independent of alcohol consumption.

Uses of Human MR and PET Imaging in Research of Neurodegenerative Brain Diseases

In the past decades, many neuroimaging studies have aimed to improve the scientific understanding of human neurodegenerative diseases using MRI and PET. This article is designed to provide an overview of the major classes of brain imaging and how/why they are used in this line of research. It is intended as a primer for individuals who are relatively unfamiliar with the methods of neuroimaging research to gain a better understanding of the vocabulary and overall methodologies. It is not intended to describe or review any research findings for any disease or biology, but rather to broadly describe the imaging methodologies that are used in conducting this neurodegeneration research. We will also review challenges and strategies for analyzing neuroimaging data across multiple sites and studies, i.e., harmonization and standardization of imaging data for multi-site and meta-analyses.

Comparison of Multispectral Image-Processing Methods for Brain Tissue Classification in BrainWeb Synthetic Data and Real MR Images

Accurate quantification of brain tissue is a fundamental and challenging task in neuroimaging. Over the past two decades, statistical parametric mapping (SPM) and FMRIB's Automated Segmentation Tool (FAST) have been widely used to estimate gray matter (GM) and white matter (WM) volumes. However, they cannot reliably estimate cerebrospinal fluid (CSF) volumes. To address this problem, we developed the TRIO algorithm (TRIOA), a new magnetic resonance (MR) multispectral classification method. SPM8, SPM12, FAST, and the TRIOA were evaluated using the BrainWeb database and real magnetic resonance imaging (MRI) data. In this paper, the MR brain images of 140 healthy volunteers (51.5 ± 15.8 y/o) were obtained using a whole-body 1.5 T MRI system (Aera, Siemens, Erlangen, Germany). Before classification, several preprocessing steps were performed, including skull stripping and motion and inhomogeneity correction. After extensive experimentation, the TRIOA was shown to be more effective than SPM and FAST. For real data, all test methods revealed that the participants aged 20–83 years exhibited an age-associated decline in GM and WM volume fractions. However, for CSF volume estimation, SPM8-s and SPM12-m both produced different results, which were also different compared with those obtained by FAST and the TRIOA. Furthermore, the TRIOA performed consistently better than both SPM and FAST for GM, WM, and CSF volume estimation. Compared with SPM and FAST, the proposed TRIOA showed more advantages by providing more accurate MR brain tissue classification and volume measurements, specifically in CSF volume estimation.

Diagnostic performance and prediction of clinical progression of plasma phospho-tau181 in the Alzheimer's Disease Neuroimaging Initiative

Whilst cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers for amyloid-β (Aβ) and tau pathologies are accurate for the diagnosis of Alzheimer's disease (AD), their broad implementation in clinical and trial settings are restricted by high cost and limited accessibility. Plasma phosphorylated-tau181 (p-tau181) is a promising blood-based biomarker that is specific for AD, correlates with cerebral Aβ and tau pathology, and predicts future cognitive decline. In this study, we report the performance of p-tau181 in >1000 individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI), including cognitively unimpaired (CU), mild cognitive impairment (MCI) and AD dementia patients characterized by Aβ PET. We confirmed that plasma p-tau181 is increased at the preclinical stage of Alzheimer and further increases in MCI and AD dementia. Individuals clinically classified as AD dementia but having negative Aβ PET scans show little increase but plasma p-tau181 is increased if CSF Aβ has already changed prior to Aβ PET changes. Despite being a multicenter study, plasma p-tau181 demonstrated high diagnostic accuracy to identify AD dementia (AUC = 85.3%; 95% CI, 81.4-89.2%), as well as to distinguish between Aβ- and Aβ+ individuals along the Alzheimer's continuum (AUC = 76.9%; 95% CI, 74.0-79.8%). Higher baseline concentrations of plasma p-tau181 accurately predicted future dementia and performed comparably to the baseline prediction of CSF p-tau181. Longitudinal measurements of plasma p-tau181 revealed low intra-individual variability, which could be of potential benefit in disease-modifying trials seeking a measurable response to a therapeutic target. This study adds significant weight to the growing body of evidence in the use of plasma p-tau181 as a non-invasive diagnostic and prognostic tool for AD, regardless of clinical stage, which would be of great benefit in clinical practice and a large cost-saving in clinical trial recruitment.

Multisite Comparison of MRI Defacing Software Across Multiple Cohorts

With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3-85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3-20 years) for afni_refacer and the oldest (44-85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files.

Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study

To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning approach. Gray Matter Volume (GMV) was derived from magnetic resonance imaging (3T, FLAIR) and adjusted for intracranial volume (ICV). 93 potential determinants of GMV from the categories sociodemographics, anthropometric measurements, cardio-metabolic variables, lifestyle factors, medication, sleep, and nutrition were obtained from 293 participants from a population-based cohort from Southern Germany. Elastic net regression was used to identify the most important determinants of ICV-adjusted GMV. The four variables age (selected in each of the 1000 splits), glomerular filtration rate (794 splits), diabetes (323 splits) and diabetes duration (122 splits) were identified to be most relevant predictors of GMV adjusted for intracranial volume. The elastic net model showed better performance compared to a constant linear regression (mean squared error = 1.10 vs. 1.59, p < 0.001). These findings are relevant for preventive and therapeutic considerations and for neuroimaging studies, as they suggest to take information on metabolic status and renal function into account as potential confounders.

Association of Neighborhood-Level Disadvantage With Cerebral and Hippocampal Volume

Importance

Identifying risk factors for brain atrophy during the aging process can help direct new preventive approaches for dementia and cognitive decline. The association of neighborhood socioeconomic disadvantage with brain volume in this context is not well known.

Objective

To test whether neighborhood-level socioeconomic disadvantage is associated with decreased brain volume in a cognitively unimpaired population enriched for Alzheimer disease risk.

Design, Setting, and Participants

This study, conducted from January 6, 2010, to January 17, 2019, at an academic research neuroimaging center, used cross-sectional data on 951 participants from 2 large, ongoing cohort studies of Alzheimer disease (Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center clinical cohort). Participants were cognitively unimpaired based on National Institute on Aging-Alzheimer's Association workgroup diagnostic criteria for mild cognitive impairment and Alzheimer disease, confirmed through a consensus diagnosis panel. The cohort was enriched for Alzheimer disease risk based on family history of dementia. Statistical analysis was performed from April 3 to September 27, 2019.

Main Outcomes and Measures

The Area Deprivation Index, a geospatially determined index of neighborhood-level disadvantage, and cardiovascular disease risk indices were calculated for each participant. Linear regression models were fitted to test associations between relative neighborhood-level disadvantage (highest 20% based on state of residence) and hippocampal and total brain tissue volume, as assessed by magnetic resonance imaging.

Results

In the primary analysis of 951 participants (637 women [67.0%]; mean [SD] age, 63.9 [8.1] years), living in the 20% most disadvantaged neighborhoods was associated with 4.1% lower hippocampal volume (β = -317.44; 95% CI, -543.32 to -91.56; P = .006) and 2.0% lower total brain tissue volume (β = -20 959.67; 95% CI, -37 611.92 to -4307.43; P = .01), after controlling for intracranial volume, individual-level educational attainment, age, and sex. Robust propensity score-matched analyses determined that this association was not due to racial/ethnic or demographic characteristics. Cardiovascular risk score, examined in a subsample of 893 participants, mediated this association for total brain tissue but not for hippocampal volume.

Conclusions and Relevance

For cognitively unimpaired individuals, living in the most disadvantaged neighborhoods was associated with significantly lower cerebral volumes, after controlling for maximal premorbid (total intracranial) volume. This finding suggests an association of community socioeconomic context, distinct from individual-level socioeconomic status, with brain volume during aging. Cardiovascular risk mediated this association for total brain tissue volume but not for hippocampal volume, suggesting that neighborhood-level disadvantage may be associated with these 2 outcomes via distinct biological pathways.

Test-retest reliability and sample size estimates after MRI scanner relocation

OBJECTIVE

Many factors can contribute to the reliability and robustness of MRI-derived metrics. In this study, we assessed the reliability and reproducibility of three MRI modalities after an MRI scanner was relocated to a new hospital facility.

METHODS

Twenty healthy volunteers (12 females, mean age (standard deviation) ​= ​41 (11) years, age range [25-66]) completed three MRI sessions. The first session (S1) was one week prior to the 3T GE HDxt scanner relocation. The second (S2) occurred nine weeks after S1 and at the new location; a third session (S3) was acquired 4 weeks after S2. At each session, we acquired structural T1-weighted, pseudo-continuous arterial spin labelled, and diffusion tensor imaging sequences. We used longitudinal processing streams to create 12 summary MRI metrics, including total gray matter (GM), cortical GM, subcortical GM, white matter (WM), and lateral ventricle volume; mean cortical thickness; total surface area; average gray matter perfusion, and average diffusion tensor metrics along principal white matter pathways. We compared mean MRI values and variance at the old scanner location to multiple sessions at the new location using Bayesian multi-level regression models. K-fold cross validation allowed identification of important predictors. Whole-brain analyses were used to investigate any regional differences. Furthermore, we calculated within-subject coefficient of variation (wsCV), intraclass correlation coefficient (ICC), and dice similarity index (SI) of cortical segmentations across scanner relocation and within-site. Additionally, we estimated sample sizes required to robustly detect a 4% difference between two groups across MRI metrics.

RESULTS

All global MRI metrics exhibited little mean difference and small variability (bar cortical gray matter perfusion) both across scanner relocation and within-site repeat. T1- and DTI-derived tissue metrics showed ​< ​|0.3|% mean difference and <1.2% variance across scanner location and <|0.4|% mean difference and <0.8% variance within the new location, with between-site intraclass correlation coefficient (ICC) ​> ​0.80 and within-subject coefficient of variation (wsCV) ​< ​1.4%. Mean cortical gray matter perfusion had the highest between-session variability (6.7% [0.3, 16.7], estimate [95% uncertainty interval]), and hence the smallest ICC (0.71 [0.44,0.92]) and largest wsCV (13.4% [5.4, 18.1]). No global metric exhibited evidence of a meaningful mean difference between scanner locations. However, surface area showed evidence of a mean difference within-site repeat (between S2 and S3). Whole-brain analyses revealed no significant areas of difference between scanner relocation or within-site. For all metrics, we found no support for a systematic difference in variance across relocation sites compared to within-site test-retest reliability. Necessary sample sizes to detect a 4% difference between two independent groups varied from a maximum of n ​= ​362 per group (cortical gray matter perfusion), to total gray matter volume (n ​= ​114), average fractional anisotropy (n ​= ​23), total gray matter volume normalized by intracranial volume (n ​= ​19), and axial diffusivity (n ​= ​3 per group).

CONCLUSION

Cortical gray matter perfusion was the most variable metric investigated (necessitating large sample sizes to identify group differences), with other metrics showing substantially less variability. Scanner relocation appeared to have a negligible effect on variability of the global MRI metrics tested. This manuscript reports within-site test-retest variability to act as a tool for calculating sample size in future investigations. Our results suggest that when all other parameters are held constant (e.g., sequence parameters and MRI processing), the effect of scanner relocation is indistinguishable from within-site variability, but may need to be considered depending on the question being investigated.

Differences in Total Brain Volume between Sexes in a Cognitively Unimpaired Elderly Population

OBJECTIVES

Although a large number of studies have shown brain volumetric differences between men and women, only a few investigations have analyzed brain tissue volumes in representative samples of the general elderly population. We investigated differences in gray matter (GM) volumes, white matter (WM) volumes, and intracranial volumes (ICVs) between the sexes in individuals older than 66 years using structural magnetic resonance imaging (MRI).

METHODS

Using FreeSurfer version 5.3, we obtained the ICVs and GM and WM volumes from the MRI datasets of 84 men and 92 women. To correct for interindividual variations in ICV, GM and WM volumes were adjusted with a method using the residuals of a least-square-derived linear regression between raw volumes and ICVs. We then performed an analysis of covariance comparing men and women, including age and years of schooling as confounding factors.

RESULTS

Women had a lower socioeconomic status overall and fewer years of schooling than men. The comparison of unadjusted brain volumes showed larger GM and WM volumes in men. After the ICV correction, the adjusted volumes of GM and WM were larger in women.

CONCLUSION

After the ICV correction and taking into account differences in socioeconomic status and years of schooling, our results confirm previous findings of proportionally larger GM in women, as well as larger WM volumes. These results in an elderly population indicate that brain volumetric differences between sexes persist throughout the aging process. Additional studies combining MRI and other biomarkers to identify the hormonal and molecular bases influencing such differences are warranted.

Does risk of brain cancer increase with intracranial volume? A population-based case control study

Background

Glioma is the most common primary brain tumor and is believed to arise from glial stem cells. Despite large efforts, there are limited established risk factors. It has been suggested that tissue with more stem cell divisions may exhibit higher risk of cancer due to chance alone. Assuming a positive correlation between the number of stem cell divisions in an organ and size of the same organ, we hypothesized that variation in intracranial volume, as a proxy for brain size, may be linked to risk of high-grade glioma.

Methods

Intracranial volume was calculated from pretreatment 3D T1-weighted MRI brain scans from 124 patients with high-grade glioma and 995 general population-based controls. Binomial logistic regression analyses were performed to ascertain the effect of intracranial volume and sex on the likelihood that participants had high-grade glioma.

Results

An increase in intracranial volume of 100 mL was associated with an odds ratio of high-grade glioma of 1.69 (95% CI: 1.44‒1.98; P < 0.001). After adjusting for intracranial volume, female sex emerged as a risk factor for high-grade glioma (odds ratio for male sex = 0.56, 95% CI: 0.33‒0.93; P = 0.026).

Conclusions

Intracranial volume is strongly associated with risk of high-grade glioma. After correcting for intracranial volume, risk of high-grade glioma was higher in women. The development of glioma is correlated to brain size and may to a large extent be a stochastic event related to the number of cells at risk.

The effect of white matter hyperintensities on regional brain volumes and white matter microstructure, a population-based study in HUNT

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.

Diffusion tensor imaging in middle-aged headache sufferers in the general population: a cross-sectional population-based imaging study in the Nord-Trøndelag health study (HUNT-MRI)

BACKGROUND

Several studies have investigated white matter with diffusion tensor imaging (DTI) in those suffering from headache, but so far only in clinic based samples and with conflicting results.

METHODS

In the present study, 1006 individuals (50-66 years) from the general population (Nord-Trøndelag Health Study) participated in an imaging study of the head at 1.5 T (HUNT-MRI). Hundred and ninety-six individuals were excluded because of errors in the data acquisition or brain pathology. Two hundred and forty-six of the remaining participants reported suffering from headache (69 from migraine and 76 from tension-type headache) the year prior to the scanning. DTI data were analysed with Tract-Based Spatial Statistics and automated tractography. Type of headache, frequency of attacks and evolution of headache were investigated for an association with white matter fractional anisotropy (FA), mean diffusivity (MD), axonal diffusivity (AD), radial diffusivity (RD) and tract volume. Correction for various demographical and clinical variables were performed.

RESULTS

Headache sufferers had widespread higher white matter MD, AD and RD compared to headache free individuals (n = 277). The effect sizes were mostly small with the largest seen in those with middle-age onset headache, who also had lower white matter FA. There were no associations between white matter microstructure and attack frequency or type of headache.

CONCLUSION

Middle-age onset headache may be related to a widespread process in the white matter leading to altered microstructure.

CRISPR/Cas9 mediated generation of an ovine model for infantile neuronal ceroid lipofuscinosis (CLN1 disease)

The neuronal ceroid lipofuscinoses (NCLs) are a group of devastating monogenetic lysosomal disorders that affect children and young adults with no cure or effective treatment currently available. One of the more severe infantile forms of the disease (INCL or CLN1 disease) is due to mutations in the palmitoyl-protein thioesterase 1 (PPT1) gene and severely reduces the child's lifespan to approximately 9 years of age. In order to better translate the human condition than is possible in mice, we sought to produce a large animal model employing CRISPR/Cas9 gene editing technology. Three PPT1 homozygote sheep were generated by insertion of a disease-causing PPT1 (R151X) human mutation into the orthologous sheep locus. This resulted in a morphological, anatomical and biochemical disease phenotype that closely resembles the human condition. The homozygous sheep were found to have significantly reduced PPT1 enzyme activity and accumulate autofluorescent storage material, as is observed in CLN1 patients. Clinical signs included pronounced behavioral deficits as well as motor deficits and complete loss of vision, with a reduced lifespan of 17 ± 1 months at a humanely defined terminal endpoint. Magnetic resonance imaging (MRI) confirmed a significant decrease in motor cortical volume as well as increased ventricular volume corresponding with observed brain atrophy and a profound reduction in brain mass of 30% at necropsy, similar to alterations observed in human patients. In summary, we have generated the first CRISPR/Cas9 gene edited NCL model. This novel sheep model of CLN1 disease develops biochemical, gross morphological and in vivo brain alterations confirming the efficacy of the targeted modification and potential relevance to the human condition.

Hepatic fat is superior to BMI, visceral and pancreatic fat as a potential risk biomarker for neurodegenerative disease

OBJECTIVES

Prior studies relating body mass index (BMI) to brain volumes suggest an overall inverse association. However, BMI might not be an ideal marker, as it disregards different fat compartments, which carry different metabolic risks. Therefore, we analyzed MR-based fat depots and their association with gray matter (GM) volumes of brain structures, which show volumetric changes in neurodegenerative diseases.

METHODS

Warp-based automated brain segmentation of 3D FLAIR sequences was obtained in a population-based study cohort. Associations of temporal lobe, cingulate gyrus, and hippocampus GM volume with BMI and MR-based quantification of visceral adipose tissue (VAT), as well as hepatic and pancreatic proton density fat fraction (PDFF_hepatic and PDFF_panc, respectively), were assessed by linear regression.

RESULTS

In a sample of 152 women (age 56.2 ± 9.0 years) and 199 men (age 56.1 ± 9.1 years), we observed a significant inverse association of PDFF_hepatic and cingulate gyrus volume (p < 0.05) as well as of PDFF_hepatic and hippocampus volume (p < 0.05), when adjusting for age and sex. This inverse association was further enhanced for cingulate gyrus volume after additionally adjusting for hypertension, smoking, BMI, LDL, and total cholesterol (p < 0.01) and also alcohol (p < 0.01). No significant association was observed between PDFF_hepatic and temporal lobe and between temporal lobe, cingulate gyrus, or hippocampus volume and BMI, VAT, and PDFF_panc.

CONCLUSIONS

We observed a significant inverse, independent association of cingulate gyrus and hippocampus GM volume with hepatic fat, but not with other obesity measures. Increased hepatic fat could therefore serve as a marker of high-risk fat distribution.

KEY POINTS

• Obesity is associated with neurodegenerative processes. • In a population-based study cohort, hepatic fat was superior to BMI and visceral and pancreatic fat as a risk biomarker for decreased brain volume of cingulate gyrus and hippocampus. • Increased hepatic fat could serve as a marker of high-risk fat distribution.

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen’s d = −0.24 to −0.73; P < 1.49 × 10⁻⁴), and lower thickness in the precentral gyri bilaterally (d = −0.34 to −0.52; P < 4.31 × 10⁻⁶). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = −1.73 to −1.91, P < 1.4 × 10⁻¹⁹), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = −0.36 to −0.52; P < 1.49 × 10⁻⁴). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = −0.29 to −0.54; P < 1.49 × 10⁻⁴). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = −0.27 to −0.51; P < 1.49 × 10⁻⁴). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < −0.0018; P < 1.49 × 10⁻⁴). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.

Reduced hippocampal subfield volumes and memory function in school-aged children born preterm with very low birthweight (VLBW)

BACKGROUND

The hippocampus, an essential structure for learning and memory, has a reduced volume in preterm born (gestational age < 37 weeks) individuals with very low birth weight (VLBW: birth weight < 1500 g), which may affect memory function. However, the hippocampus is a complex structure with distinct subfields related to specific memory functions. These subfields are differentially affected by a variety of neuropathological conditions, but it remains unclear how these subfields may be affected by medical complications following preterm birth which may cause aberrant brain development, and the consequences of this on learning and memory function in children with VLBW.

METHODS

Children born preterm with VLBW (n = 34) and term-born controls from the Norwegian Mother and Child Cohort Study (MoBa) (n = 104) underwent structural MRI and a neuropsychological assessment of memory function at primary school age. FreeSurfer 6.0 was used to analyze the volumes of hippocampal subfields which were compared between groups, as was memory performance. Correlations between abnormal hippocampal subfields and memory performance were explored in the VLBW group.

RESULTS

All absolute hippocampal subfield volumes were lower in the children with VLBW compared to MoBa term-born controls, and the volumes of the left and right dentate gyrus and the right subiculum remained significantly lower after correcting for total intracranial volume. The VLBW group had inferior working memory performance and the score on the subtest Spatial Span backwards was positively correlated to the volume of the right dentate gyrus.

CONCLUSIONS

Hippocampal subfield volumes seem to be differently affected by early brain development related to preterm birth. The dentate gyrus appears particularly susceptible to adverse effects of preterm birth. Reduced working memory function among children with VLBW was associated with smaller volume of right dentate gyrus. This finding demonstrates alterations in hippocampal structure-function relationships associated with early brain development related to preterm birth.

Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database

When analyzing large multicenter databases, the effects of multiple confounding covariates increase the variability in the data and may reduce the ability to detect changes due to the actual effect of interest, for example, changes due to disease. Efficient ways to evaluate the effect of covariates toward the data harmonization are therefore important. In this article, we showcase techniques to assess the "goodness of harmonization" of covariates. We analyze 7,656 MR images in the multisite, multiscanner Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We present a comparison of three methods for estimating total intracranial volume to assess their robustness and correct the brain structure volumes using the residual method and the proportional (normalization by division) method. We then evaluated the distribution of brain structure volumes over the entire ADNI database before and after accounting for multiple covariates such as total intracranial volume, scanner field strength, sex, and age using two techniques: (a) Zscapes, a panoramic visualization technique to analyze the entire database and (b) empirical cumulative distributions functions. The results from this study highlight the importance of assessing the goodness of data harmonization as a necessary preprocessing step when pooling large data set with multiple covariates, prior to further statistical data analysis.

Associations of Changes in Cardiorespiratory Fitness and Symptoms of Anxiety and Depression With Brain Volumes: The HUNT Study

Objective: We investigated the independent and joint associations of changes in estimated cardiorespiratory fitness (eCRF) and symptoms of anxiety and depression with brain volumes in individuals from the general population. Method: 751 participants (52% women, aged 50-67 years) from the Nord-Trøndelag Health Study (HUNT) MRI cohort were included. eCRF obtained from a non-exercise algorithm and symptoms of anxiety and depression were assessed twice; at HUNT2 (1995-97) and HUNT3 (2006-08). Brain MRI was performed shortly after HUNT3. Brain parenchymal fraction (BPF), bilateral hippocampal and total cortical volume were extracted from brain MRI obtained at 1.5T, using FreeSurfer and Statistical Parametric Mapping. Results: Multiple regression revealed that participants whose eCRF increased had larger BPF (β = 0.09, 95% CI 0.02, 0.16) and larger hippocampal volume (β = 0.09, 95% CI 0.03, 0.16) compared to participants whose eCRF remained low. Participants whose eCRF remained high had larger BPF (β = 0.15, 95% CI 0.07, 0.22) and larger cortical volume (β = 0.05, 95% CI 0.01, 0.09). Participants whose anxiety symptoms worsened had smaller BPF (β = -0.09, 95% CI -0.15, -0.02) and cortical volume (β = -0.05, -0.08, -0.01) than participants whose anxiety symptoms remained low. Each ml/kg/min increase in eCRF was associated with larger cortical volume among individuals with worsening of anxiety symptoms (β = 0.13, 95% CI 0.001, 0.27), and larger BPF among individuals whose depressive symptoms improved (β = 0.28, 95% CI 0.02, 0.53). Conclusion: Promoting exercise intended to improve eCRF may be an important public health initiative aimed at maintaining brain health among middle-aged individuals with and without changing psychological symptoms.

Altered grey matter volume, perfusion and white matter integrity in very low birthweight adults

This study examined the long-term effects of being born very-low-birth-weight (VLBW, <1500 g) on adult cerebral structural development using a multi-method neuroimaging approach. The New Zealand VLBW study cohort comprised 413 individuals born VLBW in 1986. Of the 338 who survived to discharge, 229 were assessed at age 27–29 years. Of these, 150 had a 3 T MRI scan alongside 50 healthy term-born controls. The VLBW group included 53/57 participants born <28 weeks gestation. MRI analyses included: a) structural MRI to assess grey matter (GM) volume and cortical thickness; b) arterial spin labelling (ASL) to quantify GM perfusion; and c) diffusion tensor imaging (DTI) to measure white matter (WM) integrity. Compared to controls, VLBW adults had smaller GM volumes within frontal, temporal, parietal and occipital cortices, bilateral cingulate gyri and left caudate, as well as greater GM volumes in frontal, temporal and occipital areas. Thinner cortex was observed within frontal, temporal and parietal cortices. VLBW adults also had less GM perfusion within limited temporal areas, bilateral hippocampi and thalami. Finally, lower fractional anisotropy (FA) and axial diffusivity (AD) within principal WM tracts was observed in VLBW subjects. Within the VLBW group, birthweight was positively correlated with GM volume and perfusion in cortical and subcortical regions, as well as FA and AD across numerous principal WM tracts. Between group differences within temporal cortices were evident across all imaging modalities, suggesting that the temporal lobe may be particularly susceptible to disruption in development following preterm birth. Overall, findings reveal enduring and pervasive effects of preterm birth on brain structural development, with individuals born at lower birthweights having greater long-term neuropathology.

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Very-low-birth-weight adults had smaller GM volumes and thinner cortex than controls.

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VLBW adults also showed regions of larger grey matter volumes and thicker cortex.

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Several small regions showed lower cerebral perfusion in VLBW adults than in controls.

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Diffusion tensor MRI suggested poorer WM integrity in VLBW adults than in controls.

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Within VLBW adults, all MRI measures showed positive associations with birthweight.

Cortisol relates to regional limbic system structure in older but not younger adults

We investigated if the relationship between age and regional limbic system brain structure would be moderated by diurnal cortisol output and diurnal cortisol slope. Participants aged 23-83 years collected seven salivary cortisol samples each day for 10 consecutive days and underwent magnetic resonance imaging. Age, sex, cortisol, and an age x cortisol interaction were tested as predictors of hippocampal and amygdalar volume and caudal and rostral anterior cingulate cortex (ACC) thickness. We found significant interactions between age and cortisol on left and right amygdalar volumes and right caudal ACC thickness. Older adults with higher cortisol output had smaller left and right amygdalar volumes than older adults with lower cortisol output and younger adults with higher cortisol output. Older and younger adults with lower cortisol output had similar amygdalar volumes. Older adults with a steeper decline in diurnal cortisol had a thicker right caudal ACC than younger adults with a similarly shaped cortisol slope. Hippocampal volume was not related to either cortisol slope or output, nor was pallidum volume which was assessed as an extra-limbic control region. Results suggest that subtle differences in cortisol output are related to differences in limbic system structure in older but not younger adults.

Sexual Dimorphism and Hemispheric Asymmetry of Hippocampal Volumetric Integrity in Normal Aging and Alzheimer Disease

BACKGROUND AND PURPOSE

Asymmetric atrophy of the hippocampus is an important clinical finding in normal aging and Alzheimer disease. In this study, we investigate the associations between the magnitude and asymmetry of hippocampal volumetric integrity and age, sex, and dementia severity.

MATERIALS AND METHODS

We have recently developed a rapid fully automatic algorithm to measure the hippocampal parenchymal fraction, an index of hippocampal volumetric integrity on structural MR imaging of the brain. We applied this algorithm to measure the hippocampal parenchymal fraction bilaterally on 775 MR imaging volumes scanned from 198 volunteers in a publicly available data base. All subjects were right-handed and older than 60 years of age. Subjects were categorized as cognitively healthy (n = 98), with mild cognitive impairment (n = 70), or with mild/moderate Alzheimer disease (n = 30). We used linear mixed-effects models to analyze the hippocampal parenchymal fraction and its asymmetry with respect to age, sex, dementia severity, and intracranial volume.

RESULTS

After controlling for age, sex, and intracranial volume, we found that the magnitude of the hippocampal parenchymal fraction decreased and its asymmetry increased significantly with dementia severity. Also, hippocampal parenchymal fraction asymmetry was significantly higher in men after controlling for all other variables, but there was no sex effect on hippocampal parenchymal fraction magnitude. The magnitude of the hippocampal parenchymal fraction decreased and its asymmetry increased significantly with age in subjects who were cognitively healthy, but associations with age were different in nature in the mild cognitive impairment and Alzheimer disease groups.

CONCLUSIONS

Hippocampal atrophy progresses asymmetrically with age in cognitively healthy subjects. Hippocampal parenchymal fraction asymmetry is significantly higher in men than women and in mild cognitive impairment/Alzheimer disease relative to cognitively healthy individuals.

Diffusion tensor imaging and ventricle volume quantification in patients with chronic shunt-treated hydrocephalus: a matched case-control study

OBJECTIVEThe object of this study was to use diffusion tensor imaging (DTI) and tract-based spatial statistics (TBSS) to characterize the long-term effects of hydrocephalus and shunting on white matter integrity and to investigate the relationship of ventricular size and alterations in white matter integrity with headache and quality-of-life outcome measures.METHODSPatients with shunt-treated hydrocephalus and age- and sex-matched healthy controls were recruited into the study and underwent anatomical and DTI imaging on a 3-T MRI scanner. All patients were clinically stable, had undergone CSF shunt placement before 2 years of age, and had a documented history of complaints of headaches. Outcome was scored based on the Headache Disability Inventory and the Hydrocephalus Outcome Questionnaire. Fractional anisotropy (FA) and other DTI-based measures (axial, radial, and mean diffusivity; AD, RD, and MD, respectively) were extracted in the corpus callosum and internal capsule with manual region-of-interest delineation and in other regions with TBSS. Paired t-tests, corrected with a 5% false discovery rate, were used to identify regions with significant differences between patients and controls. Within the patient group, linear regression models were used to investigate the relationship between FA or ventricular volume and outcome, as well as the effect of shunt-related covariates.RESULTSTwenty-one hydrocephalus patients and 21 matched controls completed the study, and their data were used in the final analysis. The authors found significantly lower FA for patients than for controls in 20 of the 48 regions, mostly posterior white matter structures, in periventricular as well as more distal tracts. Of these 20 regions, 17 demonstrated increased RD, while only 5 showed increased MD and 3 showed decreased AD. No areas of increased FA were observed. Higher FA in specific periventricular white matter tracts, tending toward FA in controls, was associated with increased ventricular size, as well as improved clinical outcome.CONCLUSIONSThe study shows that TBSS-based DTI is a sensitive technique for elucidating changes in white matter structures due to hydrocephalus and chronic CSF shunting and provides preliminary evidence that DTI may be a valuable tool for tailoring shunt procedures to monitor ventricular size following shunting and achieve optimal outcome, as well as for guiding the development of alternate therapies for hydrocephalus.