The optimal template effect in hippocampus studies of diseased populations

Individual estimates of age at detectable amyloid onset for risk factor assessment

INTRODUCTION

Individualized estimates of age at detectable amyloid-beta (Aβ) accumulation, distinct from amyloid positivity, allow for analysis of onset age of Aβ accumulation as an outcome measure to understand risk factors.

METHODS

Using longitudinal Pittsburgh compound B (PiB) positron emission tomography data from Baltimore Longitudinal Study of Aging, we estimated the age at which each PiB+ individual began accumulating Aβ. We used survival analysis methods to quantify risk of accumulating Aβ and differences in onset age of Aβ accumulation in relation to APOE ε4 status and sex among 36 APOE ε4 carriers and 83 noncarriers.

RESULTS

Age at onset of Aβ accumulation for the APOE ε4- and ε4+ groups was 73.1 and 60.7, respectively. APOE ε4 positivity conferred a threefold risk of accumulating Aβ after adjusting for sex and education.

DISCUSSION

Estimation of onset age of amyloid accumulation may help gauge treatment efficacy in interventions to delay symptom onset in Alzheimer's disease.

Statistical image analysis of longitudinal RAVENS images

Regional analysis of volumes examined in normalized space (RAVENS) are transformation images used in the study of brain morphometry. In this paper, RAVENS images are analyzed using a longitudinal variant of voxel-based morphometry (VBM) and longitudinal functional principal component analysis (LFPCA) for high-dimensional images. We demonstrate that the latter overcomes the limitations of standard longitudinal VBM analyses, which does not separate registration errors from other longitudinal changes and baseline patterns. This is especially important in contexts where longitudinal changes are only a small fraction of the overall observed variability, which is typical in normal aging and many chronic diseases. Our simulation study shows that LFPCA effectively separates registration error from baseline and longitudinal signals of interest by decomposing RAVENS images measured at multiple visits into three components: a subject-specific imaging random intercept that quantifies the cross-sectional variability, a subject-specific imaging slope that quantifies the irreversible changes over multiple visits, and a subject-visit specific imaging deviation. We describe strategies to identify baseline/longitudinal variation and registration errors combined with covariates of interest. Our analysis suggests that specific regional brain atrophy and ventricular enlargement are associated with multiple sclerosis (MS) disease progression.

Prefrontal cortex white matter tracts in prodromal Huntington disease

Huntington disease (HD) is most widely known for its selective degeneration of striatal neurons but there is also growing evidence for white matter (WM) deterioration. The primary objective of this research was to conduct a large-scale analysis using multisite diffusion-weighted imaging (DWI) tractography data to quantify diffusivity properties along major prefrontal cortex WM tracts in prodromal HD. Fifteen international sites participating in the PREDICT-HD study collected imaging and neuropsychological data on gene-positive HD participants without a clinical diagnosis (i.e., prodromal) and gene-negative control participants. The anatomical prefrontal WM tracts of the corpus callosum (PFCC), anterior thalamic radiations (ATRs), inferior fronto-occipital fasciculi (IFO), and uncinate fasciculi (UNC) were identified using streamline tractography of DWI. Within each of these tracts, tensor scalars for fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity coefficients were calculated. We divided prodromal HD subjects into three CAG-age product (CAP) groups having Low, Medium, or High probabilities of onset indexed by genetic exposure. We observed significant differences in WM properties for each of the four anatomical tracts for the High CAP group in comparison to controls. Additionally, the Medium CAP group presented differences in the ATR and IFO in comparison to controls. Furthermore, WM alterations in the PFCC, ATR, and IFO showed robust associations with neuropsychological measures of executive functioning. These results suggest long-range tracts essential for cross-region information transfer show early vulnerability in HD and may explain cognitive problems often present in the prodromal stage. Hum Brain Mapp 36:3717-3732, 2015. © 2015 Wiley Periodicals, Inc.

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients-manually annotated by up to four raters-and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%-85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously. Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.

Construction of An Unbiased Spatio-Temporal Atlas of the Tongue During Speech

Quantitative characterization and comparison of tongue motion during speech and swallowing present fundamental challenges because of striking variations in tongue structure and motion across subjects. A reliable and objective description of the dynamics tongue motion requires the consistent integration of inter-subject variability to detect the subtle changes in populations. To this end, in this work, we present an approach to constructing an unbiased spatio-temporal atlas of the tongue during speech for the first time, based on cine-MRI from twenty two normal subjects. First, we create a common spatial space using images from the reference time frame, a neutral position, in which the unbiased spatio-temporal atlas can be created. Second, we transport images from all time frames of all subjects into this common space via the single transformation. Third, we construct atlases for each time frame via groupwise diffeomorphic registration, which serves as the initial spatio-temporal atlas. Fourth, we update the spatio-temporal atlas by realigning each time sequence based on the Lipschitz norm on diffeomorphisms between each subject and the initial atlas. We evaluate and compare different configurations such as similarity measures to build the atlas. Our proposed method permits to accurately and objectively explain the main pattern of tongue surface motion.

Basal Forebrain Atrophy Contributes to Allocentric Navigation Impairment in Alzheimer's Disease Patients

The basal forebrain degenerates in Alzheimer’s disease (AD) and this process is believed to contribute to the cognitive decline observed in AD patients. Impairment in spatial navigation is an early feature of the disease but whether basal forebrain dysfunction in AD is responsible for the impaired navigation skills of AD patients is not known. Our objective was to investigate the relationship between basal forebrain volume and performance in real space as well as computer-based navigation paradigms in an elderly cohort comprising cognitively normal controls, subjects with amnestic mild cognitive impairment and those with AD. We also tested whether basal forebrain volume could predict the participants’ ability to perform allocentric- vs. egocentric-based navigation tasks. The basal forebrain volume was calculated from 1.5 T magnetic resonance imaging (MRI) scans, and navigation skills were assessed using the human analog of the Morris water maze employing allocentric, egocentric, and mixed allo/egocentric real space as well as computerized tests. When considering the entire sample, we found that basal forebrain volume correlated with spatial accuracy in allocentric (cued) and mixed allo/egocentric navigation tasks but not the egocentric (uncued) task, demonstrating an important role of the basal forebrain in mediating cue-based spatial navigation capacity. Regression analysis revealed that, although hippocampal volume reflected navigation performance across the entire sample, basal forebrain volume contributed to mixed allo/egocentric navigation performance in the AD group, whereas hippocampal volume did not. This suggests that atrophy of the basal forebrain contributes to aspects of navigation impairment in AD that are independent of hippocampal atrophy.

Altered resting perfusion and functional connectivity of default mode network in youth with autism spectrum disorder

BACKGROUND

Neuroimaging studies can shed light on the neurobiological underpinnings of autism spectrum disorders (ASD). Studies of the resting brain have shown both altered baseline metabolism from PET/SPECT and altered functional connectivity (FC) of intrinsic brain networks based on resting-state fMRI. To date, however, no study has investigated these two physiological parameters of resting brain function jointly, or explored the relationship between these measures and ASD symptom severity.

METHODS

Here, we used pseudo-continuous arterial spin labeling with 3D background-suppressed GRASE to assess resting cerebral blood flow (CBF) and FC in 17 youth with ASD and 22 matched typically developing (TD) children.

RESULTS

A pattern of altered resting perfusion was found in ASD versus TD children including frontotemporal hyperperfusion and hypoperfusion in the dorsal anterior cingulate cortex. We found increased local FC in the anterior module of the default mode network (DMN) accompanied by decreased CBF in the same area. In our cohort, both alterations were associated with greater social impairments as assessed with the Social Responsiveness Scale (SRS-total T scores). While FC was correlated with CBF in TD children, this association between FC and baseline perfusion was disrupted in children with ASD. Furthermore, there was reduced long-range FC between anterior and posterior modules of the DMN in children with ASD.

CONCLUSION

Taken together, the findings of this study--the first to jointly assess resting CBF and FC in ASD--highlight new avenues for identifying novel imaging markers of ASD symptomatology.

Whole-central nervous system functional imaging in larval Drosophila

Understanding how the brain works in tight concert with the rest of the central nervous system (CNS) hinges upon knowledge of coordinated activity patterns across the whole CNS. We present a method for measuring activity in an entire, non-transparent CNS with high spatiotemporal resolution. We combine a light-sheet microscope capable of simultaneous multi-view imaging at volumetric speeds 25-fold faster than the state-of-the-art, a whole-CNS imaging assay for the isolated Drosophila larval CNS and a computational framework for analysing multi-view, whole-CNS calcium imaging data. We image both brain and ventral nerve cord, covering the entire CNS at 2 or 5 Hz with two- or one-photon excitation, respectively. By mapping network activity during fictive behaviours and quantitatively comparing high-resolution whole-CNS activity maps across individuals, we predict functional connections between CNS regions and reveal neurons in the brain that identify type and temporal state of motor programs executed in the ventral nerve cord.

To understand how neuronal networks function, it is important to measure neuronal network activity at the systems level. Here Lemon et al. develop a framework that combines a high-speed multi-view light-sheet microscope, a whole-CNS imaging assay and computational tools to demonstrate simultaneous functional imaging across the entire isolated Drosophila larval CNS.

Multi-atlas segmentation of biomedical images: A survey

Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering work of Rohlfing, et al. (2004), Klein, et al. (2005), and Heckemann, et al. (2006), is becoming one of the most widely-used and successful image segmentation techniques in biomedical applications. By manipulating and utilizing the entire dataset of "atlases" (training images that have been previously labeled, e.g., manually by an expert), rather than some model-based average representation, MAS has the flexibility to better capture anatomical variation, thus offering superior segmentation accuracy. This benefit, however, typically comes at a high computational cost. Recent advancements in computer hardware and image processing software have been instrumental in addressing this challenge and facilitated the wide adoption of MAS. Today, MAS has come a long way and the approach includes a wide array of sophisticated algorithms that employ ideas from machine learning, probabilistic modeling, optimization, and computer vision, among other fields. This paper presents a survey of published MAS algorithms and studies that have applied these methods to various biomedical problems. In writing this survey, we have three distinct aims. Our primary goal is to document how MAS was originally conceived, later evolved, and now relates to alternative methods. Second, this paper is intended to be a detailed reference of past research activity in MAS, which now spans over a decade (2003-2014) and entails novel methodological developments and application-specific solutions. Finally, our goal is to also present a perspective on the future of MAS, which, we believe, will be one of the dominant approaches in biomedical image segmentation.

Semi-automated hippocampal segmentation in people with cognitive impairment using an age appropriate template for registration

BACKGROUND

To evaluate a new semi-automated segmentation method for calculating hippocampal volumes and to compare results with standard software tools in a cohort of people with subjective memory complaints (SMC) and mild cognitive impairment (MCI).

METHODS

Data from 58 participants, 39 with SMC (17 male, 22 female, mean age 72.6) and 19 with MCI (6 male, 13 female, mean age 74.3), were analyzed. For each participant, T1-weighted images were acquired using an MPRAGE sequence on a 3 Tesla MRI system. Hippocampal volumes (left, right, and total) were calculated with a new, age appropriate registration template, based on older people and using the advanced software tool ANTs (Advanced Normalization Tools). The results were compared with manual tracing (seen as the reference standard) and two widely accepted automated software tools (FSL, FreeSurfer).

RESULTS

The hippocampal volumes, calculated by using the age appropriate registration template were significantly (P < 0.05) more accurate (mean volume accuracy more than 90%) than those obtained with FreeSurfer and FSL (both less than 70%). Dice coefficients for the hippocampal segmentations with the new template method (75.3%) were slightly, but significantly (P < 0.05) higher than those from FreeSurfer (72.4%).

CONCLUSION

These results suggest that an age appropriate registration template might be a more accurate alternative to calculate hippocampal volumes when manual segmentation is not feasible.

Deformation field correction for spatial normalization of PET images

Spatial normalization of positron emission tomography (PET) images is essential for population studies, yet the current state of the art in PET-to-PET registration is limited to the application of conventional deformable registration methods that were developed for structural images. A method is presented for the spatial normalization of PET images that improves their anatomical alignment over the state of the art. The approach works by correcting the deformable registration result using a model that is learned from training data having both PET and structural images. In particular, viewing the structural registration of training data as ground truth, correction factors are learned by using a generalized ridge regression at each voxel given the PET intensities and voxel locations in a population-based PET template. The trained model can then be used to obtain more accurate registration of PET images to the PET template without the use of a structural image. A cross validation evaluation on 79 subjects shows that the proposed method yields more accurate alignment of the PET images compared to deformable PET-to-PET registration as revealed by 1) a visual examination of the deformed images, 2) a smaller error in the deformation fields, and 3) a greater overlap of the deformed anatomical labels with ground truth segmentations.

Functional subregions of the human entorhinal cortex

The entorhinal cortex (EC) is the primary site of interactions between the neocortex and hippocampus. Studies in rodents and nonhuman primates suggest that EC can be divided into subregions that connect differentially with perirhinal cortex (PRC) vs parahippocampal cortex (PHC) and with hippocampal subfields along the proximo-distal axis. Here, we used high-resolution functional magnetic resonance imaging at 7 Tesla to identify functional subdivisions of the human EC. In two independent datasets, PRC showed preferential intrinsic functional connectivity with anterior-lateral EC and PHC with posterior-medial EC. These EC subregions, in turn, exhibited differential connectivity with proximal and distal subiculum. In contrast, connectivity of PRC and PHC with subiculum followed not only a proximal-distal but also an anterior-posterior gradient. Our data provide the first evidence that the human EC can be divided into functional subdivisions whose functional connectivity closely parallels the known anatomical connectivity patterns of the rodent and nonhuman primate EC.

Hippocampal volume and functional connectivity changes during the female menstrual cycle

Hippocampal volume has been shown to be sensitive to variations in estrogen and progesterone levels across rodents' estrous cycle. However, little is known about the covariation of hormone levels and brain structure in the course of the human menstrual cycle. Here, we examine this covariation with a multi-method approach that includes several brain imaging methods and hormonal assessments. We acquired structural and functional scans from 21 naturally cycling women on four time points during their cycles (early follicular phase, late follicular phase, ovulation and luteal phase). Hormone blood concentrations and cognitive performance in different domains were assessed on each of the measurement occasions. Structural MRI images were processed by means of whole-brain voxel-based morphometry and FreeSurfer. With either method, bilateral increases in hippocampal volume were found in the late follicular phase relative to the early follicular phase. The gray matter probability in regions of hippocampal volume increase was associated with lower mean diffusivity in the same region. In addition, we observed higher functional connectivity between the hippocampi and the bilateral superior parietal lobe in the late follicular phase. We did not find any reliable cycle-related performance variations on the cognitive tasks. The present results show that hormonal fluctuations covary with hippocampal structure and function in the course of the human menstrual cycle.

White matter integrity in dementia with Lewy bodies: a voxel-based analysis of diffusion tensor imaging

Many patients with dementia with Lewy bodies (DLB) have overlapping Alzheimer's disease (AD)-related pathology, which may contribute to white matter (WM) diffusivity alterations on diffusion tensor imaging (DTI). Consecutive patients with DLB (n = 30), age- and sex-matched AD patients (n = 30), and cognitively normal controls (n = 60) were recruited. All subjects underwent DTI, 18F 2-fluoro-deoxy-d-glucose, and (11)C Pittsburgh compound B positron emission tomography scans. DLB patients had reduced fractional anisotropy (FA) in the parietooccipital WM but not elsewhere compared with cognitively normal controls, and elevated FA in parahippocampal WM compared with AD patients, which persisted after controlling for β-amyloid load in DLB. The pattern of WM FA alterations on DTI was consistent with the more diffuse posterior parietal and occipital glucose hypometabolism of 2-fluoro-deoxy-d-glucose positron emission tomography in the cortex. DLB is characterized by a loss of parietooccipital WM integrity, independent of concomitant AD-related β-amyloid load. Cortical glucose hypometabolism accompanies WM FA alterations with a concordant pattern of gray and WM involvement in the parietooccipital lobes in DLB.

Sodium selenate reduces hyperphosphorylated tau and improves outcomes after traumatic brain injury

Traumatic brain injury is a common and serious neurodegenerative condition that lacks a pharmaceutical intervention to improve long-term outcome. Hyperphosphorylated tau is implicated in some of the consequences of traumatic brain injury and is a potential pharmacological target. Protein phosphatase 2A is a heterotrimeric protein that regulates key signalling pathways, and protein phosphatase 2A heterotrimers consisting of the PR55 B-subunit represent the major tau phosphatase in the brain. Here we investigated whether traumatic brain injury in rats and humans would induce changes in protein phosphatase 2A and phosphorylated tau, and whether treatment with sodium selenate-a potent PR55 activator-would reduce phosphorylated tau and improve traumatic brain injury outcomes in rats. Ninety young adult male Long-Evans rats were administered either a fluid percussion injury or sham-injury. A proportion of rats were killed at 2, 24, and 72 h post-injury to assess acute changes in protein phosphatase 2A and tau. Other rats were given either sodium selenate or saline-vehicle treatment that was continuously administered via subcutaneous osmotic pump for 12 weeks. Serial magnetic resonance imaging was acquired prior to, and at 1, 4, and 12 weeks post-injury to assess evolving structural brain damage and axonal injury. Behavioural impairments were assessed at 12 weeks post-injury. The results showed that traumatic brain injury in rats acutely reduced PR55 expression and protein phosphatase 2A activity, and increased the expression of phosphorylated tau and the ratio of phosphorylated tau to total tau. Similar findings were seen in post-mortem brain samples from acute human traumatic brain injury patients, although many did not reach statistical significance. Continuous sodium selenate treatment for 12 weeks after sham or fluid percussion injury in rats increased protein phosphatase 2A activity and PR55 expression, and reduced the ratio of phosphorylated tau to total tau, attenuated brain damage, and improved behavioural outcomes in rats given a fluid percussion injury. Notably, total tau levels were decreased in rats 12 weeks after fluid percussion injury, and several other factors, including the use of anaesthetic, the length of recovery time, and that some brain injury and behavioural dysfunction still occurred in rats treated with sodium selenate must be considered in the interpretation of this study. However, taken together these data suggest protein phosphatase 2A and hyperphosphorylated tau may be involved in the neurodegenerative cascade of traumatic brain injury, and support the potential use of sodium selenate as a novel traumatic brain injury therapy.

White-matter relaxation time and myelin water fraction differences in young adults with autism

BACKGROUND

Increasing evidence suggests that autism is associated with abnormal white-matter (WM) anatomy and impaired brain 'connectivity'. While myelin plays a critical role in synchronized brain communication, its aetiological role in autistic symptoms has only been indirectly addressed by WM volumetric, relaxometry and diffusion tensor imaging studies. A potentially more specific measure of myelin content, termed myelin water fraction (MWF), could provide improved sensitivity to myelin alteration in autism.

METHOD

We performed a cross-sectional imaging study that compared 14 individuals with autism and 14 age- and IQ-matched controls. T 1 relaxation times (T 1), T 2 relaxation times (T 2) and MWF values were compared between autistic subjects, diagnosed using the Autism Diagnostic Interview - Revised (ADI-R), with current symptoms assessed using the Autism Diagnostic Observation Schedule (ADOS) and typical healthy controls. Correlations between T 1, T 2 and MWF values with clinical measures [ADI-R, ADOS, and the Autism Quotient (AQ)] were also assessed.

RESULTS

Individuals with autism showed widespread WM T 1 and MWF differences compared to typical controls. Within autistic individuals, worse current social interaction skill as measured by the ADOS was related to reduced MWF although not T 1. No significant differences or correlations with symptoms were observed with respect to T 2.

CONCLUSIONS

Autistic individuals have significantly lower global MWF and higher T 1, suggesting widespread alteration in tissue microstructure and biochemistry. Areas of difference, including thalamic projections, cerebellum and cingulum, have previously been implicated in the disorder; however, this is the first study to specifically indicate myelin alteration in these regions.

Clinical and neuroimaging biomarkers of amyloid-negative logopenic primary progressive aphasia

Logopenic primary progressive aphasia (lvPPA) is a progressive language disorder characterized by anomia, difficulty repeating complex sentences, and phonological errors. The majority, although not all, lvPPA patients have underlying Alzheimer's disease. We aimed to determine whether clinical or neuroimaging features differ according to the deposition of Aβ on Pittsburgh-compound B PET in lvPPA. Clinical features, patterns of atrophy on MRI, hypometabolism on FDG-PET, and white matter tract degeneration were compared between six PiB-negative and 20 PiB-positive lvPPA patients. PiB-negative patients showed more asymmetric left-sided patterns of atrophy, hypometabolism and white matter tract degeneration, with greater left anteromedial temporal and medial prefrontal involvement, than PiB-positive patients. PiB-positive patients showed greater involvement of right temporoparietal and frontal lobes. There was very little evidence for clinical differences between the groups. Strikingly asymmetric neuroimaging findings with relatively preserved right hemisphere may provide clues that AD pathology is absent in lvPPA.

Clustering autism: using neuroanatomical differences in 26 mouse models to gain insight into the heterogeneity

Autism is a heritable disorder, with over 250 associated genes identified to date, yet no single gene accounts for >1-2% of cases. The clinical presentation, behavioural symptoms, imaging and histopathology findings are strikingly heterogeneous. A more complete understanding of autism can be obtained by examining multiple genetic or behavioural mouse models of autism using magnetic resonance imaging (MRI)-based neuroanatomical phenotyping. Twenty-six different mouse models were examined and the consistently found abnormal brain regions across models were parieto-temporal lobe, cerebellar cortex, frontal lobe, hypothalamus and striatum. These models separated into three distinct clusters, two of which can be linked to the under and over-connectivity found in autism. These clusters also identified previously unknown connections between Nrxn1α, En2 and Fmr1; Nlgn3, BTBR and Slc6A4; and also between X monosomy and Mecp2. With no single treatment for autism found, clustering autism using neuroanatomy and identifying these strong connections may prove to be a crucial step in predicting treatment response.

Longitudinal alignment of disease progression in fibrosing interstitial lung disease

Generating disease progression models from longitudinal medical imaging data is a challenging task due to the varying and often unknown state and speed of disease progression at the time of data acquisition, the limited number of scans and varying scanning intervals. We propose a method for temporally aligning imaging data from multiple patients driven by disease appearance. It aligns follow- up series of different patients in time, and creates a cross-sectional spatio-temporal disease pattern distribution model. Similarities in the disease distribution guide an optimization process, regularized by temporal rigidity and disease volume terms. We demonstrate the benefit of longitudinal alignment by classifying instances of different fibrosing interstitial lung diseases. Classification results (AUC) of Usual Interstitial Pneumonia (UIP) versus non-UIP improve from AUC = 0.71 to 0.78 following alignment, classification of UIP vs. Extrinsic Allergic Alveolitis (EAA) improves from 0.78 to 0.88.

Temporal Trajectory and Progression Score Estimation from Voxelwise Longitudinal Imaging Measures: Application to Amyloid Imaging

Abstract. Cortical β-amyloid deposition begins in Alzheimer's disease (AD) years before the onset of any clinical symptoms. It is therefore important to determine the temporal trajectories of amyloid deposition in these earliest stages in order to better understand their associations with progression to AD. A method for estimating the temporal trajectories of voxelwise amyloid as measured using longitudinal positron emission tomography (PET) imaging is presented. The method involves the estimation of a score for each subject visit based on the PET data that reflects their amyloid progression. This amyloid progression score allows subjects with similar progressions to be aligned and analyzed together. The estimation of the progression scores and the amyloid trajectory parameters are performed using an expectation-maximization algorithm. The correlations among the voxel measures of amyloid are modeled to reflect the spatial nature of PET images. Simulation results show that model parameters are captured well at a variety of noise and spatial correlation levels. The method is applied to longitudinal amyloid imaging data considering each cerebral hemisphere separately. The results are consistent across the hemispheres and agree with a global index of brain amyloid known as mean cortical DVR. Unlike mean cortical DVR, which depends on a priori defined regions, the progression score extracted by the method is data-driven and does not make assumptions about regional longitudinal changes. Compared to regressing on age at each voxel, the longitudinal trajectory slopes estimated using the proposed method show better localized longitudinal changes.

Basal forebrain atrophy correlates with amyloid β burden in Alzheimer's disease

The brains of patients suffering from Alzheimer's disease (AD) have three classical pathological hallmarks: amyloid-beta (Aβ) plaques, tau tangles, and neurodegeneration, including that of cholinergic neurons of the basal forebrain. However the relationship between Aβ burden and basal forebrain degeneration has not been extensively studied. To investigate this association, basal forebrain volumes were determined from magnetic resonance images of controls, subjects with amnestic mild cognitive impairment (aMCI) and AD patients enrolled in the longitudinal Alzheimer's Disease Neuroimaging Initiative (ADNI) and Australian Imaging, Biomarkers and Lifestyle (AIBL) studies. In the AIBL cohort, these volumes were correlated within groups to neocortical gray matter retention of Pittsburgh compound B (PiB) from positron emission tomography images as a measure of Aβ load. The basal forebrain volumes of AD and aMCI subjects were significantly reduced compared to those of control subjects. Anterior basal forebrain volume was significantly correlated to neocortical PiB retention in AD subjects and aMCI subjects with high Aβ burden, whereas posterior basal forebrain volume was significantly correlated to neocortical PiB retention in control subjects with high Aβ burden. Therefore this study provides new evidence for a correlation between neocortical Aβ accumulation and basal forebrain degeneration. In addition, cluster analysis showed that subjects with a whole basal forebrain volume below a determined cut-off value had a 7 times higher risk of having a worse diagnosis within ~18 months.

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The link between amyloid (Aβ) and basal forebrain degeneration in AD is unclear.

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We find that basal forebrain volumes are correlated with neocortical Aβ burden.

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Basal forebrain volume correlates with Aβ burden in at-risk control subjects.

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Basal forebrain atrophy delineates subjects at increased risk of progressing to AD.

Laminar activity in the hippocampus and entorhinal cortex related to novelty and episodic encoding

The ability to form long-term memories for novel events depends on information processing within the hippocampus (HC) and entorhinal cortex (EC). The HC-EC circuitry shows a quantitative segregation of anatomical directionality into different neuronal layers. Whereas superficial EC layers mainly project to dentate gyrus (DG), CA3 and apical CA1 layers, HC output is primarily sent from pyramidal CA1 layers and subiculum to deep EC layers. Here we utilize this directionality information by measuring encoding activity within HC/EC subregions with 7 T high resolution functional magnetic resonance imaging (fMRI). Multivariate Bayes decoding within HC/EC subregions shows that processing of novel information most strongly engages the input structures (superficial EC and DG/CA2-3), whereas subsequent memory is more dependent on activation of output regions (deep EC and pyramidal CA1). This suggests that while novelty processing is strongly related to HC-EC input pathways, the memory fate of a novel stimulus depends more on HC-EC output.

Morphometry-based measurements of the structural response to whole-brain radiation

PURPOSE

Morphometry techniques were applied to quantify the normal tissue therapy response in patients receiving whole-brain radiation for intracranial malignancies.

METHODS

Pre- and Post-irradiation magnetic resonance imaging (MRI) data sets were retrospectively analyzed in N = 15 patients. Volume changes with respect to pre-irradiation were quantitatively measured in the cerebrum and ventricles. Measurements were correlated with the time interval from irradiation. Criteria for inclusion included craniospinal irradiation, pre-irradiation MRI, at least one follow-up MRI, and no disease progression. The brain on each image was segmented to remove the skull and registered to the initial pre-treatment scan. Average volume changes were measured using morphometry analysis of the deformation Jacobian and direct template registration-based segmentation of brain structures.

RESULTS

An average cerebral volume atrophy of -0.2 and -3% 3% was measured for the deformation morphometry and direct segmentation methods, respectively. An average ventricle volume dilation of 21 and 20% was measured for the deformation morphometry and direct segmentation methods, respectively.

CONCLUSION

The presented study has developed an image processing pipeline for morphometric monitoring of brain tissue volume changes as a response to radiation therapy. Results indicate that quantitative morphometric monitoring is feasible and may provide additional information in assessing response.

Mild cognitive impairment, poor episodic memory, and late-life depression are associated with cerebral cortical thinning and increased white matter hyperintensities

In various independent studies to date, cerebral cortical thickness and white matter hyperintensity (WMH) volume have been associated with episodic memory, depression, and mild cognitive impairment (MCI). The aim of this study was to uncover variations in cortical thickness and WMH volume in association with episodic memory, depressive state, and the presence of MCI simultaneously in a single study population. The participants were 186 individuals with MCI (clinical dementia rating [CDR] of 0.5) and 136 healthy elderly controls (HCs; CDR of 0) drawn from two community-based cohort studies in northern Japan. We computed cerebral cortical thickness and WMH volume by using MR scans and statistically analyzed differences in these indices between HCs and MCI participants. We also assessed the associations of these indices with memory performance and depressive state in participants with MCI. Compared with HCs, MCI participants exhibited thinner cortices in the temporal and inferior parietal lobes and greater WMH volumes in the corona radiata and semioval center. In MCI participants, poor episodic memory was associated with thinner cortices in the left entorhinal region and increased WMH volume in the posterior periventricular regions. Compared with non-depressed MCI participants, depressed MCI participants showed reduced cortical thickness in the anterior medial temporal lobe and gyrus adjacent to the amygdala bilaterally, as well as greater WMH volume as a percentage of the total intracranial volume (WMHr). A higher WMHr was associated with cortical thinning in the frontal, temporal, and parietal regions in MCI participants. These results demonstrate that episodic memory and depression are associated with both cortical thickness and WMH volume in MCI participants. Additional longitudinal studies are needed to clarify the dynamic associations and interactions among these indices.

High resolution magnetic resonance imaging for characterization of the neuroligin-3 knock-in mouse model associated with autism spectrum disorder

Autism spectrum disorders (ASD) comprise an etiologically heterogeneous set of neurodevelopmental disorders. Neuroligin-3 (NL-3) is a cell adhesion protein that mediates synapse development and has been implicated in ASD. We performed ex-vivo high resolution magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and behavioral (social approach and zero maze) tests at 3 different time points (30, 50 and 70 days-of-age) on NL-3 and wild-type littermates to assess developmental brain abnormalities in NL-3 mice. MRI data were segmented in 39 different gray and white matter regions. Volumetric measurements, along with DTI indices from these segmented regions were also performed. After controlling for age and gender, the NL-3 knock-in animals demonstrated significantly reduced sociability and lower anxiety-related behavior in comparison to their wild type littermates. Significantly reduced volume of several white and gray matter regions in the NL-3 knock-in mice were also observed after considering age, gender and time point as covariates. These findings suggest that structural changes in the brain of NL-3 mice are induced by the mutation in the NL-3 gene. No significant differences in DTI indices were observed, which suggests that the NL-3 mutation may not have a profound effect on water diffusion as detected by DTI. The volumetric and DTI studies aid in understanding the biology of disrupting function on an ASD risk model and may assist in the development of imaging biomarkers for ASD.

Progression of brain atrophy in the early stages of Parkinson's disease: a longitudinal tensor-based morphometry study in de novo patients without cognitive impairment

The presence of brain atrophy and its progression in early Parkinson's disease (PD) are still a matter of debate, particularly in patients without cognitive impairment. The aim of this longitudinal study was to assess whether PD patients who remain cognitively intact develop progressive atrophic changes in the early stages of the disease. For this purpose, we employed high-resolution T1-weighted MR imaging to compare 22 drug-naïve de novo PD patients without cognitive impairment to 17 age-matched control subjects, both at baseline and at three-year follow-up. We used tensor-based morphometry to explore the presence of atrophic changes at baseline and to compute yearly atrophy rates, after which we performed voxel-wise group comparisons using threshold-free cluster enhancement. At baseline, we did not observe significant differences in regional atrophy in PD patients with respect to control subjects. In contrast, PD patients showed significantly higher yearly atrophy rates in the prefrontal cortex, anterior cingulum, caudate nucleus, and thalamus when compared to control subjects. Our results indicate that even cognitively preserved PD patients show progressive cortical and subcortical atrophic changes in regions related to cognitive functions and that these changes are already detectable in the early stages of the disease.

Complementary roles of human hippocampal subregions during retrieval of spatiotemporal context

Current evidence strongly supports the central involvement of the human medial temporal lobes (MTL) in storing and retrieving memories for recently experienced events. However, a critical remaining question regards exactly how the hippocampus and surrounding cortex represents spatiotemporal context defining an event in memory. Competing accounts suggest that this process may be accomplished by the following: (1) an overall increase in neural similarity of representations underlying spatial and temporal context, (2) a differentiation of competing spatiotemporal representations, or (3) a combination of the two processes, with different subregions performing these two functions within the MTL. To address these competing proposals, we used high-resolution functional magnetic resonance imaging targeting the MTL along with a multivariate pattern similarity approach with 19 participants. While undergoing imaging, participants performed a task in which they retrieved spatial and temporal contextual representations from a recently learned experience. Results showed that successfully retrieving spatiotemporal context defining an episode involved a decrease in pattern similarity between putative spatial and temporal contextual representations in hippocampal subfields CA2/CA3/DG, whereas the parahippocampal cortex (PHC) showed the opposite pattern. These findings could not be accounted for by differences in univariate activations for complete versus partial retrieval nor differences in correlations for correct or incorrect retrieval. Together, these data suggest that the CA2/CA3/DG serves to differentiate competing contextual representations, whereas the PHC stores a comparatively integrated trace of scene-specific context, both of which likely play important roles in successful episodic memory retrieval.

Impact of social status and antidepressant treatment on neurogenesis in the baboon hippocampus

Adult hippocampal neurogenesis is critically implicated in rodent models of stress and anxiety as well as behavioral effects of antidepressants. Whereas similar factors such as psychiatric disorder and antidepressant administration are correlated with hippocampal volume in humans, the relationship between these factors and adult neurogenesis is less well understood. To better bridge the gap between rodent and human physiology, we examined the numbers of proliferating neural precursors and immature cells in the hippocampal dentate gyrus (DG) as well as in vivo magnetic resonance imaging (MRI)-estimated whole hippocampal volume in eight socially dominant- or subordinate-like (SL) baboons administered the antidepressant fluoxetine or vehicle. SL baboons had lower numbers of proliferating cells and immature neurons than socially dominant-like baboons. Fluoxetine treatment was associated with a larger whole hippocampal volume but surprisingly resulted in lower numbers of immature neurons. These findings are the first to indicate that adult neurogenesis in the baboon hippocampal DG may be functionally relevant in the context of social stress and mechanisms of antidepressant action.

Mapping track density changes in nigrostriatal and extranigral pathways in Parkinson's disease

In Parkinson's disease (PD) the demonstration of neuropathological disturbances in nigrostriatal and extranigral brain pathways using magnetic resonance imaging remains a challenge. Here, we applied a novel diffusion-weighted imaging approach-track density imaging (TDI). Twenty-seven non-demented Parkinson's patients (mean disease duration: 5 years, mean score on the Hoehn & Yahr scale=1.5) were compared with 26 elderly controls matched for age, sex, and education level. Track density images were created by sampling each subject's spatially normalized fiber tracks in 1mm isotropic intervals and counting the fibers that passed through each voxel. Whole-brain voxel-based analysis was performed and significance was assessed with permutation testing. Statistically significant increases in track density were found in the Parkinson's patients, relative to controls. Clusters were distributed in disease-relevant areas including motor, cognitive, and limbic networks. From the lower medulla to the diencephalon and striatum, clusters encompassed the known location of the locus coeruleus and pedunculopontine nucleus in the pons, and from the substantia nigra up to medial aspects of the posterior putamen, bilaterally. The results identified in brainstem and nigrostriatal pathways show a large overlap with the known distribution of neuropathological changes in non-demented PD patients. Our results also support an early involvement of limbic and cognitive networks in Parkinson's disease.

Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements

Many studies of the human brain have explored the relationship between cortical thickness and cognition, phenotype, or disease. Due to the subjectivity and time requirements in manual measurement of cortical thickness, scientists have relied on robust software tools for automation which facilitate the testing and refinement of neuroscientific hypotheses. The most widely used tool for cortical thickness studies is the publicly available, surface-based FreeSurfer package. Critical to the adoption of such tools is a demonstration of their reproducibility, validity, and the documentation of specific implementations that are robust across large, diverse imaging datasets. To this end, we have developed the automated, volume-based Advanced Normalization Tools (ANTs) cortical thickness pipeline comprising well-vetted components such as SyGN (multivariate template construction), SyN (image registration), N4 (bias correction), Atropos (n-tissue segmentation), and DiReCT (cortical thickness estimation). In this work, we have conducted the largest evaluation of automated cortical thickness measures in publicly available data, comparing FreeSurfer and ANTs measures computed on 1205 images from four open data sets (IXI, MMRR, NKI, and OASIS), with parcellation based on the recently proposed Desikan-Killiany-Tourville (DKT) cortical labeling protocol. We found good scan-rescan repeatability with both FreeSurfer and ANTs measures. Given that such assessments of precision do not necessarily reflect accuracy or an ability to make statistical inferences, we further tested the neurobiological validity of these approaches by evaluating thickness-based prediction of age and gender. ANTs is shown to have a higher predictive performance than FreeSurfer for both of these measures. In promotion of open science, we make all of our scripts, data, and results publicly available which complements the use of open image data sets and the open source availability of the proposed ANTs cortical thickness pipeline.

Postnatal development of the hippocampus in the Rhesus macaque (Macaca mulatta): a longitudinal magnetic resonance imaging study

Nonhuman primates are widely used models to investigate the neural substrates of human behavior, including the development of higher cognitive and affective function. Due to their neuroanatomical and behavioral homologies with humans, the rhesus macaque monkey (Macaca mulatta) provides an excellent animal model in which to characterize the maturation of brain structures from birth through adulthood and into senescence. To evaluate hippocampal development in rhesus macaques, structural magnetic resonance imaging scans were obtained longitudinally at 9 time points between 1 week and 260 weeks (5 years) of age on 24 rhesus macaque monkeys (12 males, 12 females). In our sample, the hippocampus reaches 50% of its adult volume by 13 weeks of age and reaches an adult volume by 52 weeks in both males and females. The hippocampus appears to be slightly larger at 3 years than at 5 years of age. Male rhesus macaques have larger hippocampi than females from 8 weeks onward by approximately 5%. Interestingly, there was increased variability in hemispheric asymmetry for hippocampus volumes at younger ages than at later ages. These data provide a comprehensive evaluation of the longitudinal development of male and female rhesus macaque hippocampus across development from 1 week to 5 years of age.

COMT Genetic Reduction Produces Sexually Divergent Effects on Cortical Anatomy and Working Memory in Mice and Humans

Genetic variations in catechol-O-methyltransferase (COMT) that modulate cortical dopamine have been associated with pleiotropic behavioral effects in humans and mice. Recent data suggest that some of these effects may vary among sexes. However, the specific brain substrates underlying COMT sexual dimorphisms remain unknown. Here, we report that genetically driven reduction in COMT enzyme activity increased cortical thickness in the prefrontal cortex (PFC) and postero-parieto-temporal cortex of male, but not female adult mice and humans. Dichotomous changes in PFC cytoarchitecture were also observed: reduced COMT increased a measure of neuronal density in males, while reducing it in female mice. Consistent with the neuroanatomical findings, COMT-dependent sex-specific morphological brain changes were paralleled by divergent effects on PFC-dependent working memory in both mice and humans. These findings emphasize a specific sex-gene interaction that can modulate brain morphological substrates with influence on behavioral outcomes in healthy subjects and, potentially, in neuropsychiatric populations.

Neonatal atlas construction using sparse representation

Atlas construction generally includes first an image registration step to normalize all images into a common space and then an atlas building step to fuse the information from all the aligned images. Although numerous atlas construction studies have been performed to improve the accuracy of the image registration step, unweighted or simply weighted average is often used in the atlas building step. In this article, we propose a novel patch-based sparse representation method for atlas construction after all images have been registered into the common space. By taking advantage of local sparse representation, more anatomical details can be recovered in the built atlas. To make the anatomical structures spatially smooth in the atlas, the anatomical feature constraints on group structure of representations and also the overlapping of neighboring patches are imposed to ensure the anatomical consistency between neighboring patches. The proposed method has been applied to 73 neonatal MR images with poor spatial resolution and low tissue contrast, for constructing a neonatal brain atlas with sharp anatomical details. Experimental results demonstrate that the proposed method can significantly enhance the quality of the constructed atlas by discovering more anatomical details especially in the highly convoluted cortical regions. The resulting atlas demonstrates superior performance of our atlas when applied to spatially normalizing three different neonatal datasets, compared with other start-of-the-art neonatal brain atlases.

Thalamic connectivity in patients with essential tremor treated with MR imaging-guided focused ultrasound: in vivo fiber tracking by using diffusion-tensor MR imaging

PURPOSE

To use diffusion-tensor (DT) magnetic resonance (MR) imaging in patients with essential tremor who were treated with transcranial MR imaging-guided focused ultrasound lesion inducement to identify the structural connectivity of the ventralis intermedius nucleus of the thalamus and determine how DT imaging changes correlated with tremor changes after lesion inducement.

MATERIALS AND METHODS

With institutional review board approval, and with prospective informed consent, 15 patients with medication-refractory essential tremor were enrolled in a HIPAA-compliant pilot study and were treated with transcranial MR imaging-guided focused ultrasound surgery targeting the ventralis intermedius nucleus of the thalamus contralateral to their dominant hand. Fourteen patients were ultimately included. DT MR imaging studies at 3.0 T were performed preoperatively and 24 hours, 1 week, 1 month, and 3 months after the procedure. Fractional anisotropy (FA) maps were calculated from the DT imaging data sets for all time points in all patients. Voxels where FA consistently decreased over time were identified, and FA change in these voxels was correlated with clinical changes in tremor over the same period by using Pearson correlation.

RESULTS

Ipsilateral brain structures that showed prespecified negative correlation values of FA over time of -0.5 or less included the pre- and postcentral subcortical white matter in the hand knob area; the region of the corticospinal tract in the centrum semiovale, in the posterior limb of the internal capsule, and in the cerebral peduncle; the thalamus; the region of the red nucleus; the location of the central tegmental tract; and the region of the inferior olive. The contralateral middle cerebellar peduncle and bilateral portions of the superior vermis also showed persistent decrease in FA over time. There was strong correlation between decrease in FA and clinical improvement in hand tremor 3 months after lesion inducement (P < .001).

CONCLUSION

DT MR imaging after MR imaging-guided focused ultrasound thalamotomy depicts changes in specific brain structures. The magnitude of the DT imaging changes after thalamic lesion inducement correlates with the degree of clinical improvement in essential tremor.

The burden of microstructural damage modulates cortical activation in elderly subjects with MCI and leuko-araiosis. A DTI and fMRI study

The term leuko-araiosis (LA) describes a common chronic affection of the cerebral white matter (WM) in the elderly due to small vessel disease with variable clinical correlates. To explore whether severity of LA entails some adaptive reorganization in the cerebral cortex we evaluated with functional MRI (fMRI) the cortical activation pattern during a simple motor task in 60 subjects with mild cognitive impairment and moderate or severe (moderate-to-severe LA group, n = 46) and mild (mild LA group, n = 14) LA extension on visual rating. The microstructural damage associated with LA was measured on diffusion tensor data by computation of the mean diffusivity (MD) of the cerebral WM and by applying tract based spatial statistics (TBSS). Subjects were examined with fMRI during continuous tapping of the right dominant hand with task performance measurement. Moderate-to-severe LA group showed hyperactivation of left primary sensorimotor cortex (SM1) and right cerebellum. Regression analyses using the individual median of WM MD as explanatory variable revealed a posterior shift of activation within the left SM1 and hyperactivation of the left SMA and paracentral lobule and of the bilateral cerebellar crus. These data indicate that brain activation is modulated by increasing severity of LA with a local remapping within the SM1 and increased activity in ipsilateral nonprimary sensorimotor cortex and bilateral cerebellum. These potentially adaptive changes as well lack of contralateral cerebral hemisphere hyperactivation are in line with sparing of the U fibers and brainstem and cerebellar WM tracts and the emerging microstructual damage of the corpus callosum revealed by TBSS with increasing severity of LA.

Progression of brain atrophy in spinocerebellar ataxia type 2: a longitudinal tensor-based morphometry study

Spinocerebellar ataxia type 2 (SCA2) is the second most frequent autosomal dominant inherited ataxia worldwide. We investigated the capability of magnetic resonance imaging (MRI) to track in vivo progression of brain atrophy in SCA2 by examining twice 10 SCA2 patients (mean interval 3.6 years) and 16 age- and gender-matched healthy controls (mean interval 3.3 years) on the same 1.5 T MRI scanner. We used T1-weighted images and tensor-based morphometry (TBM) to investigate volume changes and the Inherited Ataxia Clinical Rating Scale to assess the clinical deficit. With respect to controls, SCA2 patients showed significant higher atrophy rates in the midbrain, including substantia nigra, basis pontis, middle cerebellar peduncles and posterior medulla corresponding to the gracilis and cuneatus tracts and nuclei, cerebellar white matter (WM) and cortical gray matter (GM) in the inferior portions of the cerebellar hemisphers. No differences in WM or GM volume loss were observed in the supratentorial compartment. TBM findings did not correlate with modifications of the neurological deficit. In conclusion, MRI volumetry using TBM is capable of demonstrating the progression of pontocerebellar atrophy in SCA2, supporting a possible role of MRI as biomarker in future trials.

A semi-automated pipeline for the segmentation of rhesus macaque hippocampus: validation across a wide age range

This report outlines a neuroimaging pipeline that allows a robust, high-throughput, semi-automated, template-based protocol for segmenting the hippocampus in rhesus macaque (Macaca mulatta) monkeys ranging from 1 week to 260 weeks of age. The semiautomated component of this approach minimizes user effort while concurrently maximizing the benefit of human expertise by requiring as few as 10 landmarks to be placed on images of each hippocampus to guide registration. Any systematic errors in the normalization process are corrected using a machine-learning algorithm that has been trained by comparing manual and automated segmentations to identify systematic errors. These methods result in high spatial overlap and reliability when compared with the results of manual tracing protocols. They also dramatically reduce the time to acquire data, an important consideration in large-scale neuroradiological studies involving hundreds of MRI scans. Importantly, other than the initial generation of the unbiased template, this approach requires only modest neuroanatomical training. It has been validated for high-throughput studies of rhesus macaque hippocampal anatomy across a broad age range.

Comparing manual and automatic segmentation of hippocampal volumes: reliability and validity issues in younger and older brains

We compared hippocampal volume measures obtained by manual tracing to automatic segmentation with FreeSurfer in 44 younger (20-30 years) and 47 older (60-70 years) adults, each measured with magnetic resonance imaging (MRI) over three successive time points, separated by four months. Retest correlations over time were very high for both manual and FreeSurfer segmentations. With FreeSurfer, correlations over time were significantly lower in the older than in the younger age group, which was not the case with manual segmentation. Pearson correlations between manual and FreeSurfer estimates were sufficiently high, numerically even higher in the younger group, whereas intra-class correlation coefficient (ICC) estimates were lower in the younger than in the older group. FreeSurfer yielded higher volume estimates than manual segmentation, particularly in the younger age group. Importantly, FreeSurfer consistently overestimated hippocampal volumes independently of manually assessed volume in the younger age group, but overestimated larger volumes in the older age group to a less extent, introducing a systematic age bias in the data. Age differences in hippocampal volumes were significant with FreeSurfer, but not with manual tracing. Manual tracing resulted in a significant difference between left and right hippocampus (right > left), whereas this asymmetry effect was considerably smaller with FreeSurfer estimates. We conclude that FreeSurfer constitutes a feasible method to assess differences in hippocampal volume in young adults. FreeSurfer estimates in older age groups should, however, be interpreted with care until the automatic segmentation pipeline has been further optimized to increase validity and reliability in this age group.

Diffusion tensor imaging comparison of progressive supranuclear palsy and corticobasal syndromes

BACKGROUND

Corticobasal syndrome (CBS) and progressive supranuclear palsy syndrome (PSPS) are atypical parkinsonian syndromes that are both associated with white matter tract degeneration. However, little is known about how patterns of degeneration compare across these two syndromes.

METHODS

Twenty-seven subjects, nine with CBS and eighteen with probable or definite PSPS (9 pathologically confirmed) were prospectively recruited and underwent 3.0 T diffusion tensor imaging. A whole-brain voxel-based analysis was performed on fractional anisotropy (FA) and mean diffusivity (MD) images to compare both groups to each other and to 50 healthy controls.

RESULTS

The two syndromes showed overlapping regions of reduced FA and increased MD in the body of the corpus callosum, middle cingulum bundle, and premotor and prefrontal white matter, with reduced FA also observed in the superior cerebellar peduncles in both syndromes. However, CBS showed a more supratentorial and posterior pattern of degeneration with greater involvement of the splenium of the corpus callosum, premotor, motor and parietal lobes than PSPS. Findings in CBS were also highly asymmetric. Conversely, PSPS showed a more symmetric and infratentorial pattern of degeneration, with greater involvement of the superior cerebellar peduncles and midbrain than CBS.

CONCLUSIONS

CBS and PSPS are both associated with striking white matter tract degeneration. Despite differences in the supratentorial and infratentorial distribution of degeneration, and in asymmetry, both tend to target a common structural network. Measurements of white matter tract diffusion could therefore be useful disease biomarkers in both of these syndromes.

Deformation field correction for spatial normalization of PET images using a population-derived partial least squares model

Spatial normalization of positron emission tomography (PET) images is essential for population studies, yet work on anatomically accurate PET-to-PET registration is limited. We present a method for the spatial normalization of PET images that improves their anatomical alignment based on a deformation correction model learned from structural image registration. To generate the model, we first create a population-based PET template with a corresponding structural image template. We register each PET image onto the PET template using deformable registration that consists of an affine step followed by a diffeomorphic mapping. Constraining the affine step to be the same as that obtained from the PET registration, we find the diffeomorphic mapping that will align the structural image with the structural template. We train partial least squares (PLS) regression models within small neighborhoods to relate the PET intensities and deformation fields obtained from the diffeomorphic mapping to the structural image deformation fields. The trained model can then be used to obtain more accurate registration of PET images to the PET template without the use of a structural image. A cross validation based evaluation on 79 subjects shows that our method yields more accurate alignment of the PET images compared to deformable PET-to-PET registration as revealed by 1) a visual examination of the deformed images, 2) a smaller error in the deformation fields, and 3) a greater overlap of the deformed anatomical labels with ground truth segmentations.

Effects of repeated adolescent stress and serotonin transporter gene partial knockout in mice on behaviors and brain structures relevant to major depression

In humans, exposure to stress during development is associated with structural and functional alterations of the prefrontal cortex (PFC), amygdala (AMY), and hippocampus (HC) and their circuits of connectivity, and with an increased risk for developing major depressive disorder particularly in carriers of the short (s) variant of the serotonin transporter (5-HTT) gene-linked polymorphic region (5-HTTLPR). Although changes in these regions are found in carriers of the s allele and/or in depressed patients, evidence for a specific genotype × developmental stress effect on brain structure and function is limited. Here, we investigated the effect of repeated stress exposure during adolescence in mice with partial knockout of the 5-HTT gene (HET) vs. wildtype (WT) on early-adulthood behavioral measures and brain structure [using magnetic resonance imaging (MRI)] relevant to human major depression. Behaviorally, adolescent stress (AS) increased anxiety and decreased activity and did so to a similar degree in HET and WT. In a probabilistic reversal learning task, HET-AS mice achieved fewer reversals than did HET-No-AS mice. 5-HTT genotype and AS were without effect on corticosterone stress response. In terms of structural brain differences, AS reduced the volume of two long-range white matter tracts, the optic tract (OT) and the cerebral peduncle (CP), in WT mice specifically. In a region-of-interest analysis, AS was associated with increased HC volume and HET genotype with a decreased frontal lobe volume. In conclusion, we found that 5-HTT and AS genotype exerted long-term effects on behavior and development of brain regions relevant to human depression.

Explicit B-spline regularization in diffeomorphic image registration

Diffeomorphic mappings are central to image registration due largely to their topological properties and success in providing biologically plausible solutions to deformation and morphological estimation problems. Popular diffeomorphic image registration algorithms include those characterized by time-varying and constant velocity fields, and symmetrical considerations. Prior information in the form of regularization is used to enforce transform plausibility taking the form of physics-based constraints or through some approximation thereof, e.g., Gaussian smoothing of the vector fields [a la Thirion's Demons (Thirion, 1998)]. In the context of the original Demons' framework, the so-called directly manipulated free-form deformation (DMFFD) (Tustison et al., 2009) can be viewed as a smoothing alternative in which explicit regularization is achieved through fast B-spline approximation. This characterization can be used to provide B-spline “flavored” diffeomorphic image registration solutions with several advantages. Implementation is open source and available through the Insight Toolkit and our Advanced Normalization Tools (ANTs) repository. A thorough comparative evaluation with the well-known SyN algorithm (Avants et al., 2008), implemented within the same framework, and its B-spline analog is performed using open labeled brain data and open source evaluation tools.

Automatic hippocampus segmentation of 7.0 Tesla MR images by combining multiple atlases and auto-context models

In many neuroscience and clinical studies, accurate measurement of hippocampus is very important to reveal the inter-subject anatomical differences or the subtle intra-subject longitudinal changes due to aging or dementia. Although many automatic segmentation methods have been developed, their performances are still challenged by the poor image contrast of hippocampus in the MR images acquired especially from 1.5 or 3.0 Tesla (T) scanners. With the recent advance of imaging technology, 7.0 T scanner provides much higher image contrast and resolution for hippocampus study. However, the previous methods developed for segmentation of hippocampus from 1.5 T or 3.0 T images do not work for the 7.0 T images, due to different levels of imaging contrast and texture information. In this paper, we present a learning-based algorithm for automatic segmentation of hippocampi from 7.0 T images, by taking advantages of the state-of-the-art multi-atlas framework and also the auto-context model (ACM). Specifically, ACM is performed in each atlas domain to iteratively construct sequences of location-adaptive classifiers by integrating both image appearance and local context features. Due to the plenty texture information in 7.0 T images, more advanced texture features are also extracted and incorporated into the ACM during the training stage. Then, under the multi-atlas segmentation framework, multiple sequences of ACM-based classifiers are trained for all atlases to incorporate the anatomical variability. In the application stage, for a new image, its hippocampus segmentation can be achieved by fusing the labeling results from all atlases, each of which is obtained by applying the atlas-specific ACM-based classifiers. Experimental results on twenty 7.0 T images with the voxel size of 0.35×0.35×0.35 mm3 show very promising hippocampus segmentations (in terms of Dice overlap ratio 89.1±0.020), indicating high applicability for the future clinical and neuroscience studies.

Quantifying the reliability of image replication studies: the image intraclass correlation coefficient (I2C2)

This article proposes the image intraclass correlation (I2C2) coefficient as a global measure of reliability for imaging studies. The I2C2 generalizes the classic intraclass correlation (ICC) coefficient to the case when the data of interest are images, thereby providing a measure that is both intuitive and convenient. Drawing a connection with classical measurement error models for replication experiments, the I2C2 can be computed quickly, even in high-dimensional imaging studies. A nonparametric bootstrap procedure is introduced to quantify the variability of the I2C2 estimator. Furthermore, a Monte Carlo permutation is utilized to test reproducibility versus a zero I2C2, representing complete lack of reproducibility. Methodologies are applied to three replication studies arising from different brain imaging modalities and settings: regional analysis of volumes in normalized space imaging for characterizing brain morphology, seed-voxel brain activation maps based on resting-state functional magnetic resonance imaging (fMRI), and fractional anisotropy in an area surrounding the corpus callosum via diffusion tensor imaging. Notably, resting-state fMRI brain activation maps are found to have low reliability, ranging from .2 to .4. Software and data are available to provide easy access to the proposed methods.

A gestational ketogenic diet alters maternal metabolic status as well as offspring physiological growth and brain structure in the neonatal mouse

BACKGROUND

The use of the ketogenic diet (KD) among women of child-bearing age has been increasing, leading to increased interest in identifying the diet's suitability during gestation. To date, no studies have thoroughly investigated the effect of a gestational KD on offspring growth. Since ketones have been reported to play a role in cerebral lipid and myelin synthesis, it is particularly important to investigate the diet's impact on brain anatomy of the offspring.

METHODS

To fill this knowledge gap we imaged CD-1 mouse neonates whose mothers were fed either a standard diet (SD) or a KD prior to and during gestation. Images were collected at postnatal (P) 11.5 and 21.5 using Magnetic Resonance Imaging (MRI). Maternal metabolic status was also tracked during lactation, by following their body weight, blood glucose, ketone, cholesterol, and triglyceride concentrations.

RESULTS

The KD dams exhibit a significant reduction in maternal fertility and litter size, as well as a high risk of developing fatal ketoacidosis by mid-lactation. To increase survival of the KD dams and offspring, fostering of P2.5 pups (from both KD and SD litters) by SD-foster dams was carried out. This resulted in stabilization of blood ketones of the KD dams, and aversion of the fatal ketoacidosis. We also note a slower and smaller weight loss for the KD compared with the SD dams. The average fostered KD pup exhibits retarded growth by P21.5 compared with the average fostered SD pup. An anatomical comparison of their brains further revealed significant structural differences at P11.5, and particularly at P21.5. The KD brain shows a relative bilateral decrease in the cortex, fimbria, hippocampus, corpus callosum and lateral ventricle, but a relative volumetric enlargement of the hypothalamus and medulla.

CONCLUSION

A gestational ketogenic diet deleteriously affects maternal fertility and increases susceptibility to fatal ketoacidosis during lactation. Prenatal and early postnatal exposure to a ketogenic diet also results in significant alterations to neonatal brain structure, and results in retarded physiological growth. These alterations could be accompanied by functional and behavioural changes in later postnatal life.

Local label learning (LLL) for subcortical structure segmentation: application to hippocampus segmentation

Automatic and reliable segmentation of subcortical structures is an important but difficult task in quantitative brain image analysis. Multi-atlas based segmentation methods have attracted great interest due to their promising performance. Under the multi-atlas based segmentation framework, using deformation fields generated for registering atlas images onto a target image to be segmented, labels of the atlases are first propagated to the target image space and then fused to get the target image segmentation based on a label fusion strategy. While many label fusion strategies have been developed, most of these methods adopt predefined weighting models that are not necessarily optimal. In this study, we propose a novel local label learning strategy to estimate the target image's segmentation label using statistical machine learning techniques. In particular, we use a L1-regularized support vector machine (SVM) with a k nearest neighbor (kNN) based training sample selection strategy to learn a classifier for each of the target image voxel from its neighboring voxels in the atlases based on both image intensity and texture features. Our method has produced segmentation results consistently better than state-of-the-art label fusion methods in validation experiments on hippocampal segmentation of over 100 MR images obtained from publicly available and in-house datasets. Volumetric analysis has also demonstrated the capability of our method in detecting hippocampal volume changes due to Alzheimer's disease.