A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T

Seven-Tesla MRI and neuroimaging biomarkers for Alzheimer's disease

The goal of this paper was to review the effectiveness of using 7-T MRI to study neuroimaging biomarkers for Alzheimer's disease (AD). The authors reviewed the literature for articles published to date on the use of 7-T MRI to study AD. Thus far, there are 3 neuroimaging biomarkers for AD that have been studied using 7-T MRI in AD tissue: 1) neuroanatomical atrophy; 2) molecular characterization of hypointensities; and 3) microinfarcts. Seven-Tesla MRI has had mixed results when used to study the 3 aforementioned neuroimaging biomarkers for AD. First, in the detection of neuroanatomical atrophy, 7-T MRI has exciting potential. Historically, noninvasive imaging of neuroanatomical atrophy during AD has been limited by suboptimal resolution. However, now there is compelling evidence that the high resolution of 7-T MRI may help overcome this hurdle. Second, in detecting the characterization of hypointensities, 7-T MRI has had varied success. PET scans will most likely continue to lead in the noninvasive imaging of amyloid plaques; however, there is emerging evidence that 7-T MRI can accurately detect iron deposits within activated microglia, which may help shed light on the role of the immune system in AD pathogenesis. Finally, in the detection of microinfarcts, 7-T MRI may also play a promising role, which may help further elucidate the relationship between cerebrovascular health and AD progression.

Brain atrophy in Alzheimer's Disease and aging

Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used in clinical routine and research field, largely contributing to our understanding of the pathophysiology of neurodegenerative disorders such as Alzheimer's disease (AD). This review aims to provide a comprehensive overview of the main findings in AD and normal aging over the past twenty years, focusing on the patterns of gray and white matter changes assessed in vivo using MRI. Major progresses in the field concern the segmentation of the hippocampus with novel manual and automatic segmentation approaches, which might soon enable to assess also hippocampal subfields. Advancements in quantification of hippocampal volumetry might pave the way to its broader use as outcome marker in AD clinical trials. Patterns of cortical atrophy have been shown to accurately track disease progression and seem promising in distinguishing among AD subtypes. Disease progression has also been associated with changes in white matter tracts. Recent studies have investigated two areas often overlooked in AD, such as the striatum and basal forebrain, reporting significant atrophy, although the impact of these changes on cognition is still unclear. Future integration of different MRI modalities may further advance the field by providing more powerful biomarkers of disease onset and progression.

Novel human intervertebral disc strain template to quantify regional three-dimensional strains in a population and compare to internal strains predicted by a finite element model

Tissue strain is an important indicator of mechanical function, but is difficult to noninvasively measure in the intervertebral disc. The objective of this study was to generate a disc strain template, a 3D average of disc strain, of a group of human L4-L5 discs loaded in axial compression. To do so, magnetic resonance images of uncompressed discs were used to create an average disc shape. Next, the strain tensors were calculated pixel-wise by using a previously developed registration algorithm. Individual disc strain tensor components were then transformed to the template space and averaged to create the disc strain template. The strain template reduced individual variability while highlighting group trends. For example, higher axial and circumferential strains were present in the lateral and posterolateral regions of the disc, which may lead to annular tears. This quantification of group-level trends in local 3D strain is a significant step forward in the study of disc biomechanics. These trends were compared to a finite element model that had been previously validated against the disc-level mechanical response. Depending on the strain component, 81-99% of the regions within the finite element model had calculated strains within one standard deviation of the template strain results. The template creation technique provides a new measurement technique useful for a wide range of studies, including more complex loading conditions, the effect of disc pathologies and degeneration, damage mechanisms, and design and evaluation of treatments. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:1264-1273, 2016.

Temporal context processing within hippocampal subfields

The episodic memory system can differentiate similar events based on the temporal information associated with the events. Temporal context, which is at least partially determined by the events that precede or follow the critical event, may be a cue to differentiate events. The purpose of the present study is to investigate whether the hippocampal dentate gyrus (DG)/CA3 and CA1 subfields are sensitive to changes in temporal context and, if so, whether the subregions show a linear or threshold-like response to similar temporal contexts. Participants incidentally encoded a series of object picture triplets and 20 of them were included in final analyses. The third picture in each triplet was operationally defined as the target and the first two pictures served as temporal context for the target picture. Each target picture was presented twice with temporal context manipulated to be either repeated, high similarity, low similarity, or new on the second presentation. We extracted beta parameters for the repeated target as a function of the type of temporal context. We expected to see repetition suppression, a reduction in the beta values, in response to repetition of the target. If temporal context information is included in the representation of the target within a given region, this repetition suppression should be greater for target images that were preceded by their original context than for target images preceded by a new context. Neuroimaging results showed that CA1, but not DG/CA3, modifies the target's representation based on its temporal context. Right CA1 did not distinguish high similarity temporal context from repeated context but did distinguish low similarity temporal context from repeated context. These results indicate that CA1 is sensitive to temporal context and suggest that it does not differentiate between a substantially similar temporal context and an identical temporal context. In contrast, DG/CA3 does not appear to process temporal context as defined in the current experiment.

Heritability and reliability of automatically segmented human hippocampal formation subregions

The human hippocampal formation can be divided into a set of cytoarchitecturally and functionally distinct subregions, involved in different aspects of memory formation. Neuroanatomical disruptions within these subregions are associated with several debilitating brain disorders including Alzheimer's disease, major depression, schizophrenia, and bipolar disorder. Multi-center brain imaging consortia, such as the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) consortium, are interested in studying disease effects on these subregions, and in the genetic factors that affect them. For large-scale studies, automated extraction and subsequent genomic association studies of these hippocampal subregion measures may provide additional insight. Here, we evaluated the test-retest reliability and transplatform reliability (1.5T versus 3T) of the subregion segmentation module in the FreeSurfer software package using three independent cohorts of healthy adults, one young (Queensland Twins Imaging Study, N=39), another elderly (Alzheimer's Disease Neuroimaging Initiative, ADNI-2, N=163) and another mixed cohort of healthy and depressed participants (Max Planck Institute, MPIP, N=598). We also investigated agreement between the most recent version of this algorithm (v6.0) and an older version (v5.3), again using the ADNI-2 and MPIP cohorts in addition to a sample from the Netherlands Study for Depression and Anxiety (NESDA) (N=221). Finally, we estimated the heritability (h(2)) of the segmented subregion volumes using the full sample of young, healthy QTIM twins (N=728). Test-retest reliability was high for all twelve subregions in the 3T ADNI-2 sample (intraclass correlation coefficient (ICC)=0.70-0.97) and moderate-to-high in the 4T QTIM sample (ICC=0.5-0.89). Transplatform reliability was strong for eleven of the twelve subregions (ICC=0.66-0.96); however, the hippocampal fissure was not consistently reconstructed across 1.5T and 3T field strengths (ICC=0.47-0.57). Between-version agreement was moderate for the hippocampal tail, subiculum and presubiculum (ICC=0.78-0.84; Dice Similarity Coefficient (DSC)=0.55-0.70), and poor for all other subregions (ICC=0.34-0.81; DSC=0.28-0.51). All hippocampal subregion volumes were highly heritable (h(2)=0.67-0.91). Our findings indicate that eleven of the twelve human hippocampal subregions segmented using FreeSurfer version 6.0 may serve as reliable and informative quantitative phenotypes for future multi-site imaging genetics initiatives such as those of the ENIGMA consortium.

In vivo MRI signatures of hippocampal subfield pathology in intractable epilepsy

OBJECTIVES

Our aim is to assess the subfield-specific histopathological correlates of hippocampal volume and intensity changes (T1, T2) as well as diff!usion MRI markers in TLE, and investigate the efficacy of quantitative MRI measures in predicting histopathology in vivo.

EXPERIMENTAL DESIGN

We correlated in vivo volumetry, T2 signal, quantitative T1 mapping, as well as diffusion MRI parameters with histological features of hippocampal sclerosis in a subfield-specific manner. We made use of on an advanced co-registration pipeline that provided a seamless integration of preoperative 3 T MRI with postoperative histopathological data, on which metrics of cell loss and gliosis were quantitatively assessed in CA1, CA2/3, and CA4/DG.

PRINCIPAL OBSERVATIONS

MRI volumes across all subfields were positively correlated with neuronal density and size. Higher T2 intensity related to increased GFAP fraction in CA1, while quantitative T1 and diffusion MRI parameters showed negative correlations with neuronal density in CA4 and DG. Multiple linear regression analysis revealed that in vivo multiparametric MRI can predict neuronal loss in all the analyzed subfields with up to 90% accuracy.

CONCLUSION

Our results, based on an accurate co-registration pipeline and a subfield-specific analysis of MRI and histology, demonstrate the potential of MRI volumetry, diffusion, and quantitative T1 as accurate in vivo biomarkers of hippocampal pathology.

Morphological Changes of Amygdala in Turner Syndrome Patients

AIMS

Turner's syndrome (TS) losts one of the X chromosomes and exhibits social cognition deficits. Previous studies have reported that women with TS demonstrated structural and functional abnormalities in brain, including increased volume in amygdala. However, most studies regarded the amygdala as a whole, and the abnormalities in the specific subregions of amygdala in TS have not been studied. Here, we aimed to investigate the local morphological changes of amygdala in TS using the surface morphology analysis method.

METHODS

A total of 19 adolescents with 45XO TS and 20 matched adolescents with typical development were evaluated using magnetic resonance imaging. The amygdalae of all participants were manually delineated. 3D surface remodeling and parameterization were performed based on the outlined boundaries of amygdalae. We extracted two surface metrics, namely direct Euclidean displacement and normal projection that were used to represent the morphology of amygdala.

RESULTS

Statistical analysis showed significant outward deformation in the laterobasal subregion of left amygdala in patients with TS, compared with the controls using either direct Euclidean displacement or normal displacement.

CONCLUSIONS

Our findings provide novel insight into the pathological changes in the amygdala of patients with TS.

Postmortem imaging and neuropathologic correlations

Postmortem imaging refers to scanning autopsy specimens using magnetic resonance imaging (MRI) or optical imaging. This chapter summarizes postmortem imaging and its usefulness in brain mapping. Standard in vivo MRI has limited resolution due to time constraints and does not deliver cortical boundaries (e.g., Brodmann areas). Postmortem imaging offers a means to obtain ultra-high-resolution images with appropriate contrast for delineating cortical regions. Postmortem imaging provides the ability to validate MRI properties against histologic stained sections. This approach has enabled probabilistic mapping that is based on ex vivo MRI contrast, validated to histology, and subsequently mapped on to an in vivo model. This chapter emphasizes structural imaging, which can be validated with histologic assessment. Postmortem imaging has been applied to neuropathologic studies as well. This chapter includes many ex vivo studies, but focuses on studies of the medial temporal lobe, often involved in neurologic disease. New research using optical imaging is also highlighted.

Detection of aberrant hippocampal mossy fiber connections: Ex vivo mesoscale diffusion MRI and microtractography with histological validation in a patient with uncontrolled temporal lobe epilepsy

Understanding the neurobiology and functional connectivity of hippocampal structures is essential for improving the treatment of mesial temporal lobe epilepsy. At the macroscale, in vivo MRI often reveals hippocampal atrophy and decreased fractional anisotropy, whereas at the microscopic scale, there frequently is evidence of neuronal loss and gliosis. Mossy fiber sprouting in the dentate gyrus (DG), with evidence of glutamatergic synapses in the stratum moleculare (SM) putatively originating from granule cell neurons, may also be observed. This aberrant connection between the DG and SM could produce a reverberant excitatory circuit. However, this hypothesis cannot easily be evaluated using macroscopic or microscopic techniques. We here demonstrate that the ex vivo mesoscopic MRI of surgically excised hippocampi can bridge the explanatory and analytical gap between the macro‐ and microscopic scale. Specifically, diffusion‐ and T₂‐weighted MRI can be integrated to visualize a cytoarchitecture that is akin to immunohistochemistry. An appropriate spatial resolution to discern individual cell layers can then be established. Processing of diffusion tensor images using tractography detects extra‐ and intrahippocampal connections, hence providing a unique systems view of the hippocampus and its connected regions. Here, this approach suggests that there is indeed an aberrant connection between the DG and SM, supporting the sprouting hypothesis of a reverberant excitatory network. Mesoscopic ex vivo MR imaging hence provides an exciting new avenue to study hippocampi from treatment‐resistant patients and allows exploration of existing hypotheses, as well as the development of new treatment strategies based on these novel insights. Hum Brain Mapp 37:780–795, 2016. © 2015 Wiley Periodicals, Inc.

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

The human hippocampus has been broadly studied in the context of memory and normal brain function and its role in different neuropsychiatric disorders has been heavily studied. While many imaging studies treat the hippocampus as a single unitary neuroanatomical structure, it is, in fact, composed of several subfields that have a complex three-dimensional geometry. As such, it is known that these subfields perform specialized functions and are differentially affected through the course of different disease states. Magnetic resonance (MR) imaging can be used as a powerful tool to interrogate the morphology of the hippocampus and its subfields. Many groups use advanced imaging software and hardware (>3T) to image the subfields; however this type of technology may not be readily available in most research and clinical imaging centers. To address this need, this manuscript provides a detailed step-by-step protocol for segmenting the full anterior-posterior length of the hippocampus and its subfields: cornu ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus (DG), strata radiatum/lacunosum/moleculare (SR/SL/SM), and subiculum. This protocol has been applied to five subjects (3F, 2M; age 29-57, avg. 37). Protocol reliability is assessed by resegmenting either the right or left hippocampus of each subject and computing the overlap using the Dice's kappa metric. Mean Dice's kappa (range) across the five subjects are: whole hippocampus, 0.91 (0.90-0.92); CA1, 0.78 (0.77-0.79); CA2/CA3, 0.64 (0.56-0.73); CA4/dentate gyrus, 0.83 (0.81-0.85); strata radiatum/lacunosum/moleculare, 0.71 (0.68-0.73); and subiculum 0.75 (0.72-0.78). The segmentation protocol presented here provides other laboratories with a reliable method to study the hippocampus and hippocampal subfields in vivo using commonly available MR tools.

Regional hippocampal involvement and cognitive impairment in pediatric multiple sclerosis

Objectives:

We assessed global and regional hippocampal volume abnormalities in pediatric multiple sclerosis (MS) patients and their correlations with clinical, neuropsychological and magnetic resonance imaging metrics.

Methods:

From 53 pediatric MS patients and 18 healthy controls, global hippocampal volume was computed using a manual tracing procedure. Regional hippocampal volume modifications were assessed using a radial mapping analysis. MS patients with abnormal performance in three or more tests of a neuropsychological battery for children were classified as cognitively impaired.

Results:

Global hippocampal volume was reduced in MS patients compared with controls, but did not correlate with clinical, neuropsychological and magnetic resonance imaging measures. Compared to controls, MS patients experienced bilateral radial atrophy of the cornu ammonis, subiculum and dentate gyrus subfields as well as radial hypertrophy of the dentate gyrus subfield. Regional hippocampal volume modifications correlated with brain T2 lesion volume as well as attention and language abilities. Global hippocampal volume did not differ between cognitively impaired ( n=12) and cognitively preserved MS patients. Compared to cognitively preserved, cognitively impaired MS patients had atrophy of the subiculum and dentate gyrus subfields of the right hippocampus.

Conclusions:

Hippocampal subregions have different vulnerability to damage in pediatric MS. Regional rather than global hippocampal involvement contributes to global cognitive impairment as well as to deficits of selected cognitive tests.

Hippocampal (subfield) volume and shape in relation to cognitive performance across the adult lifespan

Newer approaches to characterizing hippocampal morphology can provide novel insights regarding cognitive function across the lifespan. We comprehensively assessed the relationships among age, hippocampal morphology, and hippocampal-dependent cognitive function in 137 healthy individuals across the adult lifespan (18-86 years of age). They underwent MRI, cognitive assessments and genotyping for Apolipoprotein E status. We measured hippocampal subfield volumes using a new multiatlas segmentation tool (MAGeT-Brain) and assessed vertex-wise (inward and outward displacements) and global surface-based descriptions of hippocampus morphology. We examined the effects of age on hippocampal morphology, as well as the relationship among age, hippocampal morphology, and episodic and working memory performance. Age and volume were modestly correlated across hippocampal subfields. Significant patterns of inward and outward displacement in hippocampal head and tail were associated with age. The first principal shape component of the left hippocampus, characterized by a lengthening of the antero-posterior axis was prominently associated with working memory performance across the adult lifespan. In contrast, no significant relationships were found among subfield volumes and cognitive performance. Our findings demonstrate that hippocampal shape plays a unique and important role in hippocampal-dependent cognitive aging across the adult lifespan, meriting consideration as a biomarker in strategies targeting the delay of cognitive aging.

Organization and Detailed Parcellation of Human Hippocampal Head and Body Regions Based on a Combined Analysis of Cyto- and Chemoarchitecture

The hippocampal formation (HF) is one of the hottest regions in neuroscience because it is critical to learning, memory, and cognition, while being vulnerable to many neurological and mental disorders. With increasing high-resolution imaging techniques, many scientists have started to use distinct landmarks along the anterior-posterior axis of HF to allow segmentation into individual subfields in order to identify specific functions in both normal and diseased conditions. These studies urgently call for more reliable and accurate segmentation of the HF subfields DG, CA3, CA2, CA1, prosubiculum, subiculum, presubiculum, and parasubiculum. Unfortunately, very limited data are available on detailed parcellation of the HF subfields, especially in the complex, curved hippocampal head region. In this study we revealed detailed organization and parcellation of all subfields of the hippocampal head and body regions on the base of a combined analysis of multiple cyto- and chemoarchitectural stains and dense sequential section sampling. We also correlated these subfields to macro-anatomical landmarks, which are visible on magnetic resonance imaging (MRI) scans. Furthermore, we created three versions of the detailed anatomic atlas for the hippocampal head region to account for brains with four, three, or two hippocampal digitations. These results will provide a fundamental basis for understanding the organization, parcellation, and anterior-posterior difference of human HF, facilitating accurate segmentation and measurement of HF subfields in the human brain on MRI scans.

Magnetic resonance spectroscopy and imaging on fresh human brain tumor biopsies at microscopic resolution

The metabolic composition and concentration knowledge provided by magnetic resonance spectroscopy (MRS) liquid and high-resolution magic angle spinning spectroscopy (HR-MAS) has a relevant impact in clinical practice during magnetic resonance imaging (MRI) monitoring of human tumors. In addition, the combination of morphological and chemical information by MRI and MRS has been particularly useful for diagnosis and prognosis of tumor evolution. MRI spatial resolution reachable in human beings is limited for safety reasons and the demanding necessary conditions are only applicable on experimental model animals. Nevertheless, MRS and MRI can be performed on human biopsies at high spatial resolution, enough to allow a direct correlation between the chemical information and the histological features observed in such biopsies. Although HR-MAS is nowadays a well-established technique for spectroscopic analysis of tumor biopsies, with this approach just a mean metabolic profile of the whole sample can be obtained and thus the high histological heterogeneity of some important tumors is mostly neglected. The value of metabolic HR-MAS data strongly depends on a wide statistical analysis and usually the microanatomical rationale for the correlation between histology and spectroscopy is lost. We present here a different approach for the combined use of MRI and MRS on fresh human brain tumor biopsies with native contrast. This approach has been designed to achieve high spatial (18 × 18 × 50 μm) and spectral (0.031 μL) resolution in order to obtain as much spatially detailed morphological and metabolical information as possible without any previous treatment that can alter the sample. The preservation of native tissue conditions can provide information that can be translated to in vivo studies and additionally opens the possibility of performing other techniques to obtain complementary information from the same sample.

Development of the human fetal hippocampal formation during early second trimester

Development of the fetal hippocampal formation has been difficult to fully describe because of rapid changes in its shape during the fetal period. The aims of this study were to: (1) segment the fetal hippocampal formation using 7.0 T MR images from 41 specimens with gestational ages ranging from 14 to 22 weeks and (2) reveal the developmental course of the fetal hippocampal formation using volume and shape analyses. Differences in hemispheric volume were observed, with the right hippocampi being larger than the left. Absolute volume changes showed a linear increase, while relative volume changes demonstrated an inverted-U shape trend during this period. Together these exhibited a variable developmental rate among different regions of the fetal brain. Different sub-regional growth of the fetal hippocampal formation was specifically observed using shape analysis. The fetal hippocampal formation possessed a prominent medial-lateral bidirectional shape growth pattern during its rotation process. Our results provide additional insight into 3D hippocampal morphology in the assessment of fetal brain development and can be used as a reference for future hippocampal studies.

A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI

Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we are releasing as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and classification based on whole hippocampal volume (82% accuracy).

Response of the medial temporal lobe network in amnestic mild cognitive impairment to therapeutic intervention assessed by fMRI and memory task performance

Studies of individuals with amnestic mild cognitive impairment (aMCI) have detected hyperactivity in the hippocampus during task-related functional magnetic resonance imaging (fMRI). Such elevated activation has been localized to the hippocampal dentate gyrus/CA3 (DG/CA3) during performance of a task designed to detect the computational contributions of those hippocampal circuits to episodic memory. The current investigation was conducted to test the hypothesis that greater hippocampal activation in aMCI represents a dysfunctional shift in the normal computational balance of the DG/CA3 regions, augmenting CA3-driven pattern completion at the expense of pattern separation mediated by the dentate gyrus. We tested this hypothesis using an intervention based on animal research demonstrating a beneficial effect on cognition by reducing excess hippocampal neural activity with low doses of the atypical anti-epileptic levetiracetam. In a within-subject design we assessed the effects of levetiracetam in three cohorts of aMCI participants, each receiving a different dose of levetiracetam. Elevated activation in the DG/CA3 region, together with impaired task performance, was detected in each aMCI cohort relative to an aged control group. We observed significant improvement in memory task performance under drug treatment relative to placebo in the aMCI cohorts at the 62.5 and 125 mg BID doses of levetiracetam. Drug treatment in those cohorts increased accuracy dependent on pattern separation processes and reduced errors attributable to an over-riding effect of pattern completion while normalizing fMRI activation in the DG/CA3 and entorhinal cortex. Similar to findings in animal studies, higher dosing at 250 mg BID had no significant benefit on either task performance or fMRI activation. Consistent with predictions based on the computational functions of the DG/CA3 elucidated in basic animal research, these data support a dysfunctional encoding mechanism detected by fMRI in individuals with aMCI and therapeutic intervention using fMRI to detect target engagement in response to treatment.

•

Patients with aMCI show increased fMRI activation in DG/CA3 relative to controls.

•

Low dose levetiracetam treatment decreases excess DG/CA3 activation in aMCI.

•

Low dose levetiracetam treatment normalizes decreased entorhinal activation in aMCI.

•

Low dose levetiracetam treatment improves task related memory performance in aMCI.

•

Targeting excess hippocampal activity has therapeutic potential in amnestic MCI.

Ultra-high resolution in-vivo 7.0T structural imaging of the human hippocampus reveals the endfolial pathway

The hippocampus is a very important structure in memory formation and retrieval, as well as in various neurological disorders such as Alzheimer's disease, epilepsy and depression. It is composed of many intricate subregions making it difficult to study the anatomical changes that take place during disease. The hippocampal hilus may have a unique neuroanatomy in humans compared to that in monkeys and rodents, with field CA3h greatly enlarged in humans compared to that in rodents, and a white-matter pathway, called the endfolial pathway, possibly only present in humans. In this study we have used newly developed 7.0T whole brain imaging sequence, balanced steady-state free precession (bSSFP) that can achieve 0.4mm isotropic images to study, in vivo, the anatomy of the hippocampal hilus. A detailed hippocampal subregional segmentation was performed according to anatomic atlases segmenting the following regions: CA4, CA3, CA2, CA1, SRLM (stratum radiatum lacunosum moleculare), alveus, fornix, and subiculum along with its molecular layer. We also segmented a hypointense structure centrally within the hilus that resembled the endfolial pathway. To validate that this hypointense signal represented the endfolial pathway, we acquired 0.1mm isotropic 8-phase cycle bSSFP on an excised specimen, and then sectioned and stained the specimen for myelin using an anti-myelin basic protein antibody (SMI 94). A structure tensor analysis was calculated on the myelin-stained section to show directionality of the underlying fibers. The endfolial pathway was consistently visualized within the hippocampal body in vivo in all subjects. It is a central pathway in the hippocampus, with unknown relevance in neurodegenerative disorders, but now that it can be visualized noninvasively, we can study its function and alterations in neurodegeneration.

Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment

We evaluate a fully automatic technique for labeling hippocampal subfields and cortical subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs segmentation on a T2-weighted MRI scan with 0.4 × 0.4 × 2.0 mm(3) resolution, partial brain coverage, and oblique orientation. Hippocampal subfields, entorhinal cortex, and perirhinal cortex are labeled using a pipeline that combines multi-atlas label fusion and learning-based error correction. In contrast to earlier work on automatic subfield segmentation in T2-weighted MRI [Yushkevich et al., 2010], our approach requires no manual initialization, labels hippocampal subfields over a greater anterior-posterior extent, and labels the perirhinal cortex, which is further subdivided into Brodmann areas 35 and 36. The accuracy of the automatic segmentation relative to manual segmentation is measured using cross-validation in 29 subjects from a study of amnestic mild cognitive impairment (aMCI) and is highest for the dentate gyrus (Dice coefficient is 0.823), CA1 (0.803), perirhinal cortex (0.797), and entorhinal cortex (0.786) labels. A larger cohort of 83 subjects is used to examine the effects of aMCI in the hippocampal region using both subfield volume and regional subfield thickness maps. Most significant differences between aMCI and healthy aging are observed bilaterally in the CA1 subfield and in the left Brodmann area 35. Thickness analysis results are consistent with volumetry, but provide additional regional specificity and suggest nonuniformity in the effects of aMCI on hippocampal subfields and MTL cortical subregions.

Ultrahigh-resolution imaging of the human brain with phase-cycled balanced steady-state free precession at 7 T

OBJECTIVES

The objectives of this study were to acquire ultra-high resolution images of the brain using balanced steady-state free precession (bSSFP) at 7 T and to identify the potential utility of this sequence.

MATERIALS AND METHODS

Eight volunteers participated in this study after providing informed consent. Each volunteer was scanned with 8 phase cycles of bSSFP at 0.4-mm isotropic resolution using 0.5 number of excitations and 2-dimensional parallel acceleration of 1.75 × 1.75. Each phase cycle required 5 minutes of scanning, with pauses between the phase cycles allowing short periods of rest. The individual phase cycles were aligned and then averaged. The same volunteers underwent scanning using 3-dimensional (3D) multiecho gradient recalled echo at 0.8-mm isotropic resolution, 3D Cube T2 at 0.7-mm isotropic resolution, and thin-section coronal oblique T2-weighted fast spin echo at 0.22 × 0.22 × 2.0-mm resolution for comparison. Two neuroradiologists assessed image quality and potential research and clinical utility.

RESULTS

The volunteers generally tolerated the scan sessions well, and composite high-resolution bSSFP images were produced for each volunteer. Rater analysis demonstrated that bSSFP had a superior 3D visualization of the microarchitecture of the hippocampus, very good contrast to delineate the borders of the subthalamic nucleus, and relatively good B1 homogeneity throughout. In addition to an excellent visualization of the cerebellum, subtle details of the brain and skull base anatomy were also easier to identify on the bSSFP images, including the line of Gennari, membrane of Liliequist, and cranial nerves. Balanced steady-state free precession had a strong iron contrast similar to or better than the comparison sequences. However, cortical gray-white contrast was significantly better with Cube T2 and T2-weighted fast spin echo.

CONCLUSIONS

Balanced steady-state free precession can facilitate ultrahigh-resolution imaging of the brain. Although total imaging times are long, the individually short phase cycles can be acquired separately, improving examination tolerability. These images may be beneficial for studies of the hippocampus, iron-containing structures such as the subthalamic nucleus and line of Gennari, and the basal cisterns and their contents.

High-resolution 7T fMRI of Human Hippocampal Subfields during Associative Learning

Examining the function of individual human hippocampal subfields remains challenging because of their small sizes and convoluted structures. Previous human fMRI studies at 3 T have successfully detected differences in activation between hippocampal cornu ammonis (CA) field CA1, combined CA2, CA3, and dentate gyrus (DG) region (CA23DG), and the subiculum during associative memory tasks. In this study, we investigated hippocampal subfield activity in healthy participants using an associative memory paradigm during high-resolution fMRI scanning at 7 T. We were able to localize fMRI activity to anterior CA2 and CA3 during learning and to the posterior CA2 field, the CA1, and the posterior subiculum during retrieval of novel associations. These results provide insight into more specific human hippocampal subfield functions underlying learning and memory and a unique opportunity for future investigations of hippocampal subfield function in healthy individuals as well as those suffering from neurodegenerative diseases.

7T MRI features in control human hippocampus and hippocampal sclerosis: an ex vivo study with histologic correlations

OBJECTIVE

Hippocampal sclerosis (HS) is the major structural brain lesion in patients with temporal lobe epilepsy (TLE). However, its internal anatomic structure remains difficult to recognize at 1.5 or 3 Tesla (T) magnetic resonance imaging (MRI), which allows neither identification of specific pathology patterns nor their proposed value to predict postsurgical outcome, cognitive impairment, or underlying etiologies. We aimed to identify specific HS subtypes in resected surgical TLE samples on 7T MRI by juxtaposition with corresponding histologic sections.

METHODS

Fifteen nonsclerotic and 18 sclerotic hippocampi were studied ex vivo using an experimental 7T MRI scanner. T2 -weighted images (T2wi) and diffusion tensor imaging (DTI) data were acquired and validated using a systematic histologic analysis of same specimens along the anterior-posterior axis of the hippocampus.

RESULTS

In nonsclerotic hippocampi, differences in MR intensity could be assigned to seven clearly recognizable layers and anatomic boundaries as confirmed by histology. All hippocampal subfields could be visualized also in the hippocampal head with three-dimensional imaging and angulated coronal planes. Only four discernible layers were identified in specimens with histopathologically confirmed HS. All sclerotic hippocampi showed a significant atrophy and increased signal intensity along the pyramidal cell layer. Changes in DTI parameters such as an increased mean diffusivity, allowed to distinguish International League Against Epilepsy (ILAE) HS type 1 from type 2. Whereas the increase in T2wi signal intensities could not be attributed to a distinct specific histopathologic substrate, that is, decreased neuronal or increased glial cell densities, intrahippocampal projections and fiber tracts were distorted in HS specimens suggesting a complex disorganization of the cellular composition, fiber networks, as well as its extracellular matrix.

SIGNIFICANCE

Our data further advocate high-resolution MRI as a helpful and promising diagnostic tool for the investigation of hippocampal pathology along the anterior-posterior extent in TLE, as well as in other neurologic and neurodegenerative disorders.

Hippocampal abnormalities and age in chronic schizophrenia: morphometric study across the adult lifespan

BACKGROUND

Hippocampal abnormalities have been demonstrated in schizophrenia. It is unclear whether these abnormalities worsen with age, and whether they affect cognition and function.

AIMS

To determine whether hippocampal abnormalities in chronic schizophrenia are associated with age, cognition and socio-occupational function.

METHOD

Using 3 T magnetic resonance imaging we scanned 100 persons aged 19-82 years: 51 were out-patients with stable schizophrenia at least 2 years after diagnosis and 49 were healthy volunteers matched for age and gender. Automated analysis was used to determine hippocampal volume and shape.

RESULTS

There were differential effects of age in the schizophrenia and control samples on total hippocampal volume (group × age interaction: F(1,95) = 6.57, P = 0.012), with steeper age-related reduction in the schizophrenia group. Three-dimensional shape analysis located the age-related deformations predominantly in the mid-body of the hippocampus. In the schizophrenia group similar patterns of morphometric abnormalities were correlated with impaired cognition and poorer socio-occupational function.

CONCLUSIONS

Hippocampal abnormalities are associated with age in people with chronic schizophrenia, with a steeper decline than in healthy individuals. These abnormalities are associated with cognitive and functional deficits, suggesting that hippocampal morphometry may be a biomarker for cognitive decline in older patients with schizophrenia.

In vivo mapping of hippocampal subfields in mesial temporal lobe epilepsy: relation to histopathology

A particularly popular automated magnetic resonance imaging (MRI) hippocampal subfield mapping technique is the one described by Van Leemput et al. (2009: Hippocampus 19:549-557) that is currently distributed with FreeSurfer software. This method assesses the probabilistic locations of subfields based on a priori knowledge of subfield topology determined from high-field MRI. Many studies have applied this technique to conventionally acquired T1-weighted MRI data. In the present study, we investigated the relationship between this technique applied to conventional T1-weighted MRI data acquired at 3 T and postsurgical hippocampal histology in patients with medically intractable mesial temporal lobe epilepsy (mTLE) and hippocampal sclerosis (HS). Patients with mTLE (n = 82) exhibited significant volume loss of ipsilateral CA1, CA2-3, CA4-dentate gyrus (DG), subiculum, and fimbria relative to controls (n = 81). Histopathological analysis indicated that the most significant neuronal loss was observed in CA1, then CA4 and CA3, and more subtle neuronal loss in CA2, consistent with classical HS. Neuronal density of CA1 significantly correlated with MRI-determined volume of CA1, and increasingly so with CA2-3 and CA4-DG. Patients with increased HS based on histopathology had greater volume loss of the ipsilateral hippocampal regions on MRI. We conclude by suggesting that whilst time efficient and fully reproducible when applied to conventional single acquisition sequences, the use of the automated subfield technique described here may necessitate the application to multiacquisition high-resolution MR sequences for accurate delineation of hippocampal subfields.

Building a Surface Atlas of Hippocampal Subfields from MRI Scans using FreeSurfer, FIRST and SPHARM

The hippocampus is widely studied with neuroimaging techniques given its importance in learning and memory and its potential as a biomarker for brain disorders such as Alzheimer's disease and epilepsy. However, its complex folding anatomy often presents analytical challenges. In particular, the critical hippocampal subfield information is usually ignored by hippocampal registration in detailed morphometric studies. Such an approach is thus inadequate to accurately characterize hippocampal morphometry and effectively identify hippocampal structural changes related to different conditions. To bridge this gap, we present our initial effort towards building a computational framework for subfield-guided hippocampal morphometry. This initial effort is focused on surface-based morphometry and aims to build a surface atlas of hippocampal subfields. Using the FreeSurfer software package, we obtain valuable hippocampal subfield information. Using the FIRST software package, we extract reliable hippocampal surface information. Using SPHARM, we develop an approach to create an atlas by mapping interpolated subfield information onto an average surface. The empirical result using ADNI data demonstrates the promise and good reproducibility of the proposed method.

Delineation of hippocampal subregions using T1-weighted magnetic resonance images at 3 Tesla

Although several novel approaches for hippocampal subregion delineation have been developed, they need to be applied prospectively and may be limited by long scan times, the use of high field (>3T) imaging systems, and limited reliability metrics. Moreover, the majority of MR imaging data collected to date has employed a T1-weighted acquisition, creating a critical need for an approach that provides reliable hippocampal subregion segmentation using such a contrast. We present a highly reliable approach for the identification of six subregions comprising the hippocampal formation from MR images including the subiculum, dentate gyrus/cornu Ammonis 4 (DG/CA4), entorhinal cortex, fimbria, and anterior and posterior segments of cornu Ammonis 1-3 (CA1-3). MR images were obtained in the coronal plane using a standard 3D spoiled gradient sequence acquired on a GE 3T scanner through the whole head in approximately 10 min. The average ICC for inter-rater reliability across right and left volumetric regions-of-interest was 0.85 (range 0.71-0.98, median 0.86) and the average ICC for intra-rater reliability was 0.92 (range 0.66-0.99, median 0.97). The mean Dice index for inter-rater reliability across right and left hemisphere subregions was 0.75 (range 0.70-0.81, median 0.75) and the mean Dice index for intra-rater reliability was 0.85 (range 0.82-0.90, median 0.85). An investigation of hippocampal asymmetry revealed significantly greater right compared to left hemisphere volumes in the anterior segment of CA1-3 and in the subiculum.

A High-resolution Atlas and Statistical Model of the Vocal Tract from Structural MRI

Magnetic resonance imaging (MRI) is an essential tool in the study of muscle anatomy and functional activity in the tongue. Objective assessment of similarities and differences in tongue structure and function has been performed using unnormalized data, but this is biased by the differences in size, shape, and orientation of the structures. To remedy this, we propose a methodology to build a 3D vocal tract atlas based on structural MRI volumes from twenty normal subjects. We first constructed high-resolution volumes from three orthogonal stacks. We then removed extraneous data so that all 3D volumes contained the same anatomy. We used an unbiased diffeomorphic groupwise registration using a cross-correlation similarity metric. Principal component analysis was applied to the deformation fields to create a statistical model from the atlas. Various evaluations and applications were carried out to show the behaviour and utility of the atlas.

Visualization of the amygdalo-hippocampal border and its structural variability by 7T and 3T magnetic resonance imaging

The amygdala and the hippocampus are two adjacent structures in the medial temporal lobe that have been broadly investigated in functional and structural neuroimaging due to their central importance in sensory perception, emotion, and memory. Exact demarcation of the amygdalo-hippocampal border (AHB) is, however, difficult in conventional structural imaging. Recent evidence suggests that, due to this difficulty, functional activation sites with high probability of being located in the hippocampus may erroneously be assigned to the amygdala, and vice versa. In the present study, we investigated the potential of ultra-high-field magnetic resonance imaging (MRI) in single sessions for detecting the AHB in humans. We show for the first time the detailed structure of the AHB as it can be visualized in T1-weighted 7T in vivo images at 0.5-mm(3) isotropic resolution. Compared to data acquired at 3T, 7T images revealed considerably more structural detail in the AHB region. Thus, we observed a striking inter-hemispheric and interindividual variability of the exact anatomical configuration of the AHB that points to the necessity of individual imaging of the AHB as a prerequisite for accurate anatomical assignment in this region. The findings of the present study demonstrate the usefulness of ultra-high-field structural MRI to resolve anatomical ambiguities of the human AHB. Highly accurate morphometric and functional investigations in this region at 7T may allow addressing such hitherto unexplored issues as whether the structural configuration of the AHB is related to functional differences in amygdalo-hippocampal interaction.

Reprint of "Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging"

The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application.

Intensity and sulci landmark combined brain atlas construction for Chinese pediatric population

Constructing an atlas from a population of brain images is of vital importance to medical image analysis. Especially in neuroscience study, creating a brain atlas is useful for intra- and inter-population comparison. Research on brain atlas construction has attracted great attention in recent years, but the research on pediatric population is still limited, mainly due to the limited availability and the relatively low quality of pediatric magnetic resonance brain images. This article is targeted at creating a high quality representative brain atlas for Chinese pediatric population. To achieve this goal, we have designed a set of preprocessing procedures to improve the image quality and developed an intensity and sulci landmark combined groupwise registration method to align the population of images for atlas construction. As demonstrated in experiments, the newly constructed atlas can better represent the size and shape of brains of Chinese pediatric population, and show better performance in Chinese pediatric brain image analysis compared with other standard atlases.

In vivo normative atlas of the hippocampal subfields using multi-echo susceptibility imaging at 7 Tesla

OBJECTIVES

To generate a high-resolution atlas of the hippocampal subfields using images acquired from 7 T, multi-echo, gradient-echo MRI for the evaluation of epilepsy and neurodegenerative disorders as well as investigating R2* (apparent transverse relaxation rate) and quantitative volume magnetic susceptibility (QS) of the subfields.

EXPERIMENTAL DESIGN

Healthy control subjects (n=17) were scanned at 7 T using a multi-echo gradient-echo sequence and susceptibility-weighted magnitude images, R2* and QS maps were reconstructed. We defined a hippocampal subfield labeling protocol for the magnitude image produced from the average of all echoes and assessed reproducibility through volume and shape metrics. A group-wise diffeomorphic registration procedure was used to generate an average atlas of the subfields for the whole subject cohort. The quantitative MRI maps and subfield labels were then warped to the average atlas space and used to measure mean values of R2* and QS characterizing each subfield.

PRINCIPAL OBSERVATIONS

We were able to reliably label hippocampal subfields on the multi-echo susceptibility images. The group-averaged atlas accurately aligns these structures to produce a high-resolution depiction of the subfields, allowing assessment of both quantitative susceptibility and R2* across subjects. Our analysis of variance demonstrates that there are more apparent differences between the subfields on these quantitative maps than the normalized magnitude images.

CONCLUSION

We constructed a high-resolution atlas of the hippocampal subfields for use in voxel-based studies and demonstrated in vivo quantification of susceptibility and R2* in the subfields. This work is the first in vivo quantification of susceptibility values within the hippocampal subfields at 7 T.

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.

Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging

The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application.

Structural layers of ex vivo rat hippocampus at 7T MRI

Magnetic resonance imaging (MRI) applied to the hippocampus is challenging in studies of the neurophysiology of memory and the physiopathology of numerous diseases such as epilepsy, Alzheimer’s disease, ischemia, and depression. The hippocampus is a well-delineated cerebral structure with a multi-layered organization. Imaging of hippocampus layers is limited to a few studies and requires high magnetic field and gradient strength. We performed one conventional MRI sequence on a 7T MRI in order to visualize and to delineate the multi-layered hippocampal structure ex vivo in rat brains. We optimized a volumic three-dimensional T2 Rapid Acquisition Relaxation Enhancement (RARE) sequence and quantified the volume of the hippocampus and one of its thinnest layers, the stratum granulare of the dentate gyrus. Additionally, we tested passive staining by gadolinium with the aim of decreasing the acquisition time and increasing image contrast. Using appropriated settings, six discrete layers were differentiated within the hippocampus in rats. In the hippocampus proper or Ammon’s Horn (AH): the stratum oriens, the stratum pyramidale of, the stratum radiatum, and the stratum lacunosum moleculare of the CA1 were differentiated. In the dentate gyrus: the stratum moleculare and the stratum granulare layer were seen distinctly. Passive staining of one brain with gadolinium decreased the acquisition time by four and improved the differentiation between the layers. A conventional sequence optimized on a 7T MRI with a standard receiver surface coil will allow us to study structural layers (signal and volume) of hippocampus in various rat models of neuropathology (anxiety, epilepsia, neurodegeneration).

Histology-derived volumetric annotation of the human hippocampal subfields in postmortem MRI

Recently, there has been a growing effort to analyze the morphometry of hippocampal subfields using both in vivo and postmortem magnetic resonance imaging (MRI). However, given that boundaries between subregions of the hippocampal formation (HF) are conventionally defined on the basis of microscopic features that often lack discernible signature in MRI, subfield delineation in MRI literature has largely relied on heuristic geometric rules, the validity of which with respect to the underlying anatomy is largely unknown. The development and evaluation of such rules are challenged by the limited availability of data linking MRI appearance to microscopic hippocampal anatomy, particularly in three dimensions (3D). The present paper, for the first time, demonstrates the feasibility of labeling hippocampal subfields in a high resolution volumetric MRI dataset based directly on microscopic features extracted from histology. It uses a combination of computational techniques and manual post-processing to map subfield boundaries from a stack of histology images (obtained with 200μm spacing and 5μm slice thickness; stained using the Kluver-Barrera method) onto a postmortem 9.4Tesla MRI scan of the intact, whole hippocampal formation acquired with 160μm isotropic resolution. The histology reconstruction procedure consists of sequential application of a graph-theoretic slice stacking algorithm that mitigates the effects of distorted slices, followed by iterative affine and diffeomorphic co-registration to postmortem MRI scans of approximately 1cm-thick tissue sub-blocks acquired with 200μm isotropic resolution. These 1cm blocks are subsequently co-registered to the MRI of the whole HF. Reconstruction accuracy is evaluated as the average displacement error between boundaries manually delineated in both the histology and MRI following the sequential stages of reconstruction. The methods presented and evaluated in this single-subject study can potentially be applied to multiple hippocampal tissue samples in order to construct a histologically informed MRI atlas of the hippocampal formation.

Detection of hippocampal atrophy in patients with temporal lobe epilepsy: a 3-Tesla MRI shape

In patients with mesial temporal lobe epilepsy (MTLE), brain MRI often detects hippocampal sclerosis (HS). Almost half of patients with MTLE do not show any hippocampal damage on visual or volumetric assessment. Here, we wished to prospectively assess 65 patients with MTLE (41 women, mean age: 39±10years, range: 21-69; right (12/65 patients) (MRI-negative) nMTLE; right (14/65 patients) (MRI-positive with HS) pMTLE; left (24/65 patients) nMTLE; and left (15/65 patients) pMTLE) using shape analysis (SA). There were significant differences among pMTLE versus nMTLE for age at seizure onset (20.2±12.8 vs. 31.8±16.7years; p=.0029), duration of epilepsy (14.6±12.7 vs. 21.3±9.6years; p=.0227), risk of refractoriness (p=.0067), frequency of antecedent febrile convulsions (FCs) (p<.001), as well as a history of epilepsy or FCs (p=.0104). All the subjects underwent the same 3-Tesla MRI protocol. Shape analysis of hippocampal formation was conducted comparing each group versus 44 matched controls. In all four subgroups, SA detected a significant atrophy in the corresponding hippocampus that coincided with the epileptogenic area. The damage was significantly more severe in patients with pMTLE (F value: 5.00) than in subgroups with nMTLE (F value: 3.50) and mainly corresponded to the CA1 subregion and subiculum. In the patients with MTLE, SA detects hippocampal damage that lateralizes with the epileptogenic area. Such damage is most prominent in the CA1 subregion and subiculum that are crucial in the pathogenesis of MTLE.

A longitudinal study of brain atrophy over two years in community-dwelling older individuals

Most previous neuroimaging studies of age-related brain structural changes in older individuals have been cross-sectional and/or restricted to clinical samples. The present study of 345 community-dwelling non-demented individuals aged 70-90years aimed to examine age-related brain volumetric changes over two years. T1-weighted magnetic resonance imaging scans were obtained at baseline and at 2-year follow-up and analyzed using the FMRIB Software Library and FreeSurfer to investigate cortical thickness and shape and volumetric changes of subcortical structures. The results showed significant atrophy across much of the cerebral cortex with bilateral transverse temporal regions shrinking the fastest. Atrophy was also found in a number of subcortical structures, including the CA1 and subiculum subfields of the hippocampus. In some regions, such as left and right entorhinal cortices, right hippocampus and right precentral area, the rate of atrophy increased with age. Our analysis also showed that rostral middle frontal regions were thicker bilaterally in older participants, which may indicate its ability to compensate for medial temporal lobe atrophy. Compared to men, women had thicker cortical regions but greater rates of cortical atrophy. Women also had smaller subcortical structures. A longer period of education was associated with greater thickness in a number of cortical regions. Our results suggest a pattern of brain atrophy with non-demented people that resembles a less extreme form of the changes associated with Alzheimer's disease (AD).

Evaluating Alzheimer's disease progression using rate of regional hippocampal atrophy

Alzheimer's disease (AD) is characterized by neurofibrillary tangle and neuropil thread deposition, which ultimately results in neuronal loss. A large number of magnetic resonance imaging studies have reported a smaller hippocampus in AD patients as compared to healthy elderlies. Even though this difference is often interpreted as atrophy, it is only an indirect measurement. A more direct way of measuring the atrophy is to use repeated MRIs within the same individual. Even though several groups have used this appropriate approach, the pattern of hippocampal atrophy still remains unclear and difficult to relate to underlying pathophysiology. Here, in this longitudinal study, we aimed to map hippocampal atrophy rates in patients with AD, mild cognitive impairment (MCI) and elderly controls. Data consisted of two MRI scans for each subject. The symmetric deformation field between the first and the second MRI was computed and mapped onto the three-dimensional hippocampal surface. The pattern of atrophy rate was similar in all three groups, but the rate was significantly higher in patients with AD than in control subjects. We also found higher atrophy rates in progressive MCI patients as compared to stable MCI, particularly in the antero-lateral portion of the right hippocampus. Importantly, the regions showing the highest atrophy rate correspond to those that were described to have the highest burden of tau deposition. Our results show that local hippocampal atrophy rate is a reliable biomarker of disease stage and progression and could also be considered as a method to objectively evaluate treatment effects.

Volumetric analysis of medial temporal lobe subregions in developmental amnesia using high-resolution magnetic resonance imaging

There is great interest in the cognitive consequences of hippocampal volume loss in developmental amnesia (DA). In many DA cases, volume loss occurs before the hippocampus is fully developed, and yet little is known about the locus, extent, and distribution of damage in these cases. We used high-resolution MRI to manually segment the medial temporal lobe (MTL) subregions in H.C., an adult with DA, and a group of sex-, age- and education-matched control participants (n = 10). The hippocampus was defined and divided into anterior (head) and posterior (body and tail) segments. Within the body of the hippocampus, the subregions (CA₁, DG/CA_2/3, and subiculum) were defined. Finally, the entorhinal (ERC), perirhinal (PRC), and parahippocampal (PHC) cortices were segmented. Anterior hippocampus was reduced bilaterally and posterior hippocampus was significantly reduced on the right. In the body of the hippocampus, all three subregions were reduced in the left hemisphere, whereas CA₁ and subiculum were reduced in the right hemisphere. No group differences were observed in the PRC and ERC, whereas left PHC volume was marginally increased in H.C. compared to controls. These results can be used to inform patterns of spared and impaired cognitive abilities in DA and perhaps in amnesia more generally. © The Authors. Hippocampus Published by Wiley Periodicals, Inc.

Atlas-based neuroinformatics via MRI: harnessing information from past clinical cases and quantitative image analysis for patient care

With the ever-increasing amount of anatomical information radiologists have to evaluate for routine diagnoses, computational support that facilitates more efficient education and clinical decision making is highly desired. Despite the rapid progress of image analysis technologies for magnetic resonance imaging of the human brain, these methods have not been widely adopted for clinical diagnoses. To bring computational support into the clinical arena, we need to understand the decision-making process employed by well-trained clinicians and develop tools to simulate that process. In this review, we discuss the potential of atlas-based clinical neuroinformatics, which consists of annotated databases of anatomical measurements grouped according to their morphometric phenotypes and coupled with the clinical informatics upon which their diagnostic groupings are based. As these are indexed via parametric representations, we can use image retrieval tools to search for phenotypes along with their clinical metadata. The review covers the current technology, preliminary data, and future directions of this field.

FKBP5 and attention bias for threat: associations with hippocampal function and shape

IMPORTANCE

The FKBP5 gene product regulates glucocorticoid receptor (GR) sensitivity and hypothalamic-pituitary-adrenal axis functioning and has been associated with many stress-related psychiatric disorders. The study of intermediate phenotypes, such as emotion-processing biases and their neural substrates, provides a way to clarify the mechanisms by which FKBP5 dysregulation mediates risk for psychiatric disorders.

OBJECTIVE

To examine whether allelic variations for a putatively functional single-nucleotide polymorphism associated with FKBP5 gene regulation (rs1360780) would relate differentially to attention bias for threat. this was measured through behavioral response on a dot probe task and hippocampal activation during task performance. Morphologic substrates of differential hippocampal response were also measured.

DESIGN

Cross-sectional study conducted from 2010 to 2012 examining associations between genotype, behavioral response, and neural response (using functional magnetic resonance imaging [fMRI]) on the dot probe; voxel-based morphometry and global and local shape analyses were used to measure structural differences in hippocampi between genotype groups.

SETTING

Participants were recruited from primary care clinics of a publicly funded hospital in Atlanta, Georgia.

PARTICIPANTS

An African American cohort of adults (N = 103) was separated into 2 groups by genotype: one genotype group included carriers of the rs1360780 T allele, which has been associated with increased risk for posttraumatic stress disorder and affective disorders; the other group did not carry this allele. Behavioral data included both sexes (N = 103); the MRI cohort (n = 36) included only women.

MAIN OUTCOME MEASURES

Behavioral and fMRI (blood oxygen level-dependent) response, voxel-based morphometry, and shape analyses.

RESULTS

Carriers of the rs1360780 T allele showed an attention bias toward threat compared with individuals without this allele (F1,90 = 5.19, P = .02). Carriers of this allele demonstrated corresponding increases in hippocampal activation and differences in morphology; global and local shape analyses revealed alterations in hippocampal shape for TT/TC compared with CC genotype groups.

CONCLUSION

Genetic variants of FKBP5 may be associated with risk for stress-related psychiatric disorders via differential effects on hippocampal structure and function, resulting in altered attention response to perceived threat.

Assessment of subcortical source localization using deep brain activity imaging model with minimum norm operators: a MEG study

Subcortical structures are involved in many healthy and pathological brain processes. It is crucial for many studies to use magnetoencephalography (MEG) to assess the ability to detect subcortical generators. This study aims to assess the source localization accuracy and to compare the characteristics of three inverse operators in the specific case of subcortical generators. MEG has a low sensitivity to subcortical sources mainly because of their distance from sensors and their complex cyto-architecture. However, we show that using a realistic anatomical and electrophysiological model of deep brain activity (DBA), the sources make measurable contributions to MEG sensors signals. Furthermore, we study the point-spread and cross-talk functions of the wMNE, sLORETA and dSPM inverse operators to characterize distortions in cortical and subcortical regions and to study how noise-normalization methods can improve or bias accuracy. We then run Monte Carlo simulations with neocortical and subcortical activations. In the case of single hippocampus patch activations, the results indicate that MEG can indeed localize the generators in the head and the body of the hippocampus with good accuracy. We then tackle the question of simultaneous cortical and subcortical activations. wMNE can detect hippocampal activations that are embedded in cortical activations that have less than double their amplitude, but it does not completely correct the bias to more superficial sources. dSPM and sLORETA can still detect hippocampal activity above this threshold, but such detection might include the creation of ghost deeper sources. Finally, using the DBA model, we showed that the detection of weak thalamic modulations of ongoing brain activity is possible.

A statistical framework for inter-group image registration

Groupwise image registration plays an important role in medical image analysis. The principle of groupwise image registration is to align a given set of images to a hidden template space in an iteratively manner without explicitly selecting any individual image as the template. Although many approaches have been proposed to address the groupwise image registration problem for registering a single group of images, few attentions and efforts have been paid to the registration problem between two or more different groups of images. In this paper, we propose a statistical framework to address the registration problems between two different image groups. The main contributions of this paper lie in the following aspects: (1) In this paper, we demonstrate that directly registering the group mean images estimated from two different image groups is not sufficient to establish the reliable transformation from one image group to the other image group. (2) A novel statistical framework is proposed to extract anatomical features from the white matter, gray matter and cerebrospinal fluid tissue maps of all aligned images as morphological signatures for each voxel. The extracted features provide much richer anatomical information than the voxel intensity of the group mean image, and can be integrated with the multi-channel Demons registration algorithm to perform the registration process. (3) The proposed method has been extensively evaluated on two publicly available brain MRI databases: the LONI LPBA40 and the IXI databases, and it is also compared with a conventional inter-group image registration approach which directly performs deformable registration between the group mean images of two image groups. Experimental results show that the proposed method consistently achieves higher registration accuracy than the method under comparison.

In vivo analysis of hippocampal subfield atrophy in mild cognitive impairment via semi-automatic segmentation of T2-weighted MRI

The measurement of hippocampal volumes using MRI is a useful in-vivo biomarker for detection and monitoring of early Alzheimer's disease (AD), including during the amnestic mild cognitive impairment (a-MCI) stage. The pathology underlying AD has regionally selective effects within the hippocampus. As such, we predict that hippocampal subfields are more sensitive in discriminating prodromal AD (i.e., a-MCI) from cognitively normal controls than whole hippocampal volumes, and attempt to demonstrate this using a semi-automatic method that can accurately segment hippocampal subfields. High-resolution coronal-oblique T2-weighted images of the hippocampal formation were acquired in 45 subjects (28 controls and 17 a-MCI (mean age: 69.5 ± 9.2; 70.2 ± 7.6)). CA1, CA2, CA3, and CA4/DG subfields, along with head and tail regions, were segmented using an automatic algorithm. CA1 and CA4/DG segmentations were manually edited. Whole hippocampal volumes were obtained from the subjects' T1-weighted anatomical images. Automatic segmentation produced significant group differences in the following subfields: CA1 (left: p = 0.001, right: p = 0.038), CA4/DG (left: p = 0.002, right: p = 0.043), head (left: p = 0.018, right: p = 0.002), and tail (left: p = 0.019). After manual correction, differences were increased in CA1 (left: p < 0.001, right: p = 0.002), and reduced in CA4/DG (left: p = 0.029, right: p = 0.221). Whole hippocampal volumes significantly differed bilaterally (left: p = 0.028, right: p = 0.009). This pattern of atrophy in a-MCI is consistent with the topography of AD pathology observed in postmortem studies, and corrected left CA1 provided stronger discrimination than whole hippocampal volume (p = 0.03). These results suggest that semi-automatic segmentation of hippocampal subfields is efficient and may provide additional sensitivity beyond whole hippocampal volumes.

Surface morphology of amygdala is associated with trait anxiety

Previous neuroimaging studies have suggested a role of amygdala in trait anxiety level, in which amygdala was typically treated as a whole. To date, it remains unknown whether the morphology of specific subregions of amygdala are associated with trait anxiety. Here, we employed a shape analysis approach to locate the association between its morphology and trait anxiety on the surface of amygdala. 24 healthy young participants were included. The boundary of amygdala for each subject was first manually outlined using high-resolution magnetic resonance (MR) image, followed by 3D surface reconstruction and parameterization using spherical harmonic description. Two point-wise metrics, direct displacement between the individual surface and atlas surface and its normal projection, were used to quantify the surface morphology of amygdala. Statistical analysis revealed significant correlations between the two surface metrics and trait anxiety levels, which were located around the lateral and central nucleus of right amygdala. Our results provided localized information for the association between amygdala and trait anxiety, and suggested a central role of the lateral and central nucleus of right amygdala on trait anxiety.