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

Immunohistochemical field parcellation of the human hippocampus along its antero-posterior axis

The primate hippocampus includes the dentate gyrus, cornu ammonis (CA), and subiculum. CA is subdivided into four fields (CA1-CA3, plus CA3h/hilus of the dentate gyrus) with specific pyramidal cell morphology and connections. Work in non-human mammals has shown that hippocampal connectivity is precisely patterned both in the laminar and longitudinal axes. One of the main handicaps in the study of neuropathological semiology in the human hippocampus is the lack of clear laminar and longitudinal borders. The aim of this study was to explore a histochemical segmentation of the adult human hippocampus, integrating field (medio-lateral), laminar, and anteroposterior longitudinal patterning. We provide criteria for head-body-tail field and subfield parcellation of the human hippocampus based on immunodetection of Rabphilin3a (Rph3a), Purkinje-cell protein 4 (PCP4), Chromogranin A and Regulation of G protein signaling-14 (RGS-14). Notably, Rph3a and PCP4 allow to identify the border between CA3 and CA2, while Chromogranin A and RGS-14 give specific staining of CA2. We also provide novel histological data about the composition of human-specific regions of the anterior and posterior hippocampus. The data are given with stereotaxic coordinates along the longitudinal axis. This study provides novel insights for a detailed region-specific parcellation of the human hippocampus useful for human brain imaging and neuropathology.

Craniofacial Soft-Tissue Anthropomorphic Database with Magnetic Resonance Imaging and Unbiased Diffeomorphic Registration

BACKGROUND

Objective assessment of craniofacial surgery outcomes in a pediatric population is challenging because of the complexity of patient presentations, diversity of procedures performed, and rapid craniofacial growth. There is a paucity of robust methods to quantify anatomical measurements by age and objectively compare craniofacial dysmorphology and postoperative outcomes. Here, the authors present data in developing a racially and ethnically sensitive anthropomorphic database, providing plastic and craniofacial surgeons with "normal" three-dimensional anatomical parameters with which to appraise and optimize aesthetic and reconstructive outcomes.

METHODS

Patients with normal craniofacial anatomy undergoing head magnetic resonance imaging (MRI) scans from 2008 to 2021 were included in this retrospective study. Images were used to construct composite (template) images with diffeomorphic image registration method using the Advanced Normalization Tools package. Composites were thresholded to generate binary three-dimensional segmentations used for anatomical measurements in Materalise Mimics.

RESULTS

High-resolution MRI scans from 130 patients generated 12 composites from an average of 10 MRI sequences each: four 3-year-olds, four 4-year-olds, and four 5-year-olds (two male, two female, two Black, and two White). The average head circumference of 3-, 4-, and 5-year-old composites was 50.3, 51.5, and 51.7 cm, respectively, comparable to normative data published by the World Health Organization.

CONCLUSIONS

Application of diffeomorphic registration-based image template algorithm to MRI is effective in creating composite templates to represent "normal" three-dimensional craniofacial and soft-tissue anatomy. Future research will focus on development of automated computational tools to characterize anatomical normality, generation of indices to grade preoperative severity, and quantification of postoperative results to reduce subjectivity bias.

Effects of healthy aging and mnemonic strategies on verbal memory performance across the adult lifespan: Mediating role of posterior hippocampus

In this study, we aimed to understand the contributions of hippocampal anteroposterior subregions (head, body, tail) and subfields (cornu ammonis 1-3 [CA1-3], dentate gyrus [DG], and subiculum [Sub]) and encoding strategies to the age-related verbal memory decline. Healthy participants were administered the California Verbal Learning Test-II to evaluate verbal memory performance and encoding strategies and underwent 4.7 T magnetic resonance imaging brain scan with subsequent hippocampal subregions and subfields manual segmentation. While total hippocampal volume was not associated with verbal memory performance, we found the volumes of the posterior hippocampus (body) and Sub showed significant effects on verbal memory performance. Additionally, the age-related volume decline in hippocampal body volume contributed to lower use of semantic clustering, resulting in lower verbal memory performance. The effect of Sub on verbal memory was statistically independent of encoding strategies. While total CA1-3 and DG volumes did not show direct or indirect effects on verbal memory, exploratory analyses with DG and CA1-3 volumes within the hippocampal body subregion suggested an indirect effect of age-related volumetric reduction on verbal memory performance through semantic clustering. As semantic clustering is sensitive to age-related hippocampal volumetric decline but not to the direct effect of age, further investigation of mechanisms supporting semantic clustering can have implications for early detection of cognitive impairments and decline.

Contributions of hippocampal subfields and subregions to episodic memory performance in healthy cognitive aging

In the present study we investigated whether hippocampal subfield (cornu ammonis 1-3, dentate gyrus, and subiculum) and anteroposterior hippocampal subregion (head,body, and tail) volumes can predict episodic memory function using high-field high resolution structural magnetic resonance imaging (MRI). We recruited 126 healthy participants (18-85 years). MRI datasets were collected on a 4.7 T system. Participants were administered the Wechsler Memory Scale (WMS-IV) to evaluate episodic memory function. Structural equation modeling was used to test the relationship between studied variables. We found that the volume of the dentate gyrus subfield and posterior hippocampus (body) showed a significant direct effect on visuospatial memory performance; additionally, an indirect effect of age on visuospatial memory mediated through these hippocampal subfield/subregion was significant. Logical and verbal memory were not significantly associated with hippocampal subfield or subregion volumes.

High resolution 0.5mm isotropic T1-weighted and diffusion tensor templates of the brain of non-demented older adults in a common space for the MIITRA atlas

High quality, high resolution T1-weighted (T1w) and diffusion tensor imaging (DTI) brain templates located in a common space can enhance the sensitivity and precision of template-based neuroimaging studies. However, such multimodal templates have not been constructed for the older adult brain. The purpose of this work which is part of the MIITRA atlas project was twofold: (A) to develop 0.5 mm isotropic resolution T1w and DTI templates that are representative of the brain of non-demented older adults and are located in the same space, using advanced multimodal template construction techniques and principles of super resolution on data from a large, diverse, community cohort of 400 non-demented older adults, and (B) to systematically compare the new templates to other standardized templates. It was demonstrated that the new MIITRA-0.5mm T1w and DTI templates are well-matched in space, exhibit good definition of brain structures, including fine structures, exhibit higher image sharpness than other standardized templates, and are free of artifacts. The MIITRA-0.5mm T1w and DTI templates allowed higher intra-modality inter-subject spatial normalization precision as well as higher inter-modality intra-subject spatial matching of older adult T1w and DTI data compared to other available templates. Consequently, MIITRA-0.5mm templates allowed detection of smaller inter-group differences for older adult data compared to other templates. The MIITRA-0.5mm templates were also shown to be most representative of the brain of non-demented older adults compared to other templates with submillimeter resolution. The new templates constructed in this work constitute two of the final products of the MIITRA atlas project and are anticipated to have important implications for the sensitivity and precision of studies on older adults.

The Brainbox-a tool to facilitate correlation of brain magnetic resonance imaging features to histopathology

Magnetic resonance imaging (MRI) has limitations in identifying underlying tissue pathology, which is relevant for neurological diseases such as multiple sclerosis, stroke or brain tumours. However, there are no standardized methods for correlating MRI features with histopathology. Thus, here we aimed to develop and validate a tool that can facilitate the correlation of brain MRI features to corresponding histopathology. For this, we designed the Brainbox, a waterproof and MRI-compatible 3D printed container with an integrated 3D coordinate system. We used the Brainbox to acquire post-mortem ex vivo MRI of eight human brains, fresh and formalin-fixed, and correlated focal imaging features to histopathology using the built-in 3D coordinate system. With its built-in 3D coordinate system, the Brainbox allowed correlation of MRI features to corresponding tissue substrates. The Brainbox was used to correlate different MR image features of interest to the respective tissue substrate, including normal anatomical structures such as the hippocampus or perivascular spaces, as well as a lacunar stroke. Brain volume decreased upon fixation by 7% (P = 0.01). The Brainbox enabled degassing of specimens before scanning, reducing susceptibility artefacts and minimizing bulk motion during scanning. In conclusion, our proof-of-principle experiments demonstrate the usability of the Brainbox, which can contribute to improving the specificity of MRI and the standardization of the correlation between post-mortem ex vivo human brain MRI and histopathology. Brainboxes are available upon request from our institution.

Fine scale hippocampus morphology variation cross 552 healthy subjects from age 20 to 80

The cerebral cortex varies over the course of a person's life span: at birth, the surface is smooth, before becoming more bumpy (deeper sulci and thicker gyri) in middle age, and thinner in senior years. In this work, a similar phenomenon was observed on the hippocampus. It was previously believed the fine-scale morphology of the hippocampus could only be extracted only with high field scanners (7T, 9.4T); however, recent studies show that regular 3T MR scanners can be sufficient for this purpose. This finding opens the door for the study of fine hippocampal morphometry for a large amount of clinical data. In particular, a characteristic bumpy and subtle feature on the inferior aspect of the hippocampus, which we refer to as hippocampal dentation, presents a dramatic degree of variability between individuals from very smooth to highly dentated. In this report, we propose a combined method joining deep learning and sub-pixel level set evolution to efficiently obtain fine-scale hippocampal segmentation on 552 healthy subjects. Through non-linear dentation extraction and fitting, we reveal that the bumpiness of the inferior surface of the human hippocampus has a clear temporal trend. It is bumpiest between 40 and 50 years old. This observation should be aligned with neurodevelopmental and aging stages.

An automated, geometry-based method for hippocampal shape and thickness analysis

The hippocampus is one of the most studied neuroanatomical structures due to its involvement in attention, learning, and memory as well as its atrophy in ageing, neurological, and psychiatric diseases. Hippocampal shape changes, however, are complex and cannot be fully characterized by a single summary metric such as hippocampal volume as determined from MR images. In this work, we propose an automated, geometry-based approach for the unfolding, point-wise correspondence, and local analysis of hippocampal shape features such as thickness and curvature. Starting from an automated segmentation of hippocampal subfields, we create a 3D tetrahedral mesh model as well as a 3D intrinsic coordinate system of the hippocampal body. From this coordinate system, we derive local curvature and thickness estimates as well as a 2D sheet for hippocampal unfolding. We evaluate the performance of our algorithm with a series of experiments to quantify neurodegenerative changes in Mild Cognitive Impairment and Alzheimer's disease dementia. We find that hippocampal thickness estimates detect known differences between clinical groups and can determine the location of these effects on the hippocampal sheet. Further, thickness estimates improve classification of clinical groups and cognitively unimpaired controls when added as an additional predictor. Comparable results are obtained with different datasets and segmentation algorithms. Taken together, we replicate canonical findings on hippocampal volume/shape changes in dementia, extend them by gaining insight into their spatial localization on the hippocampal sheet, and provide additional, complementary information beyond traditional measures. We provide a new set of sensitive processing and analysis tools for the analysis of hippocampal geometry that allows comparisons across studies without relying on image registration or requiring manual intervention.

Early amygdala and ERC atrophy linked to 3D reconstruction of rostral neurofibrillary tau tangle pathology in Alzheimer's disease

Previous research has emphasized the unique impact of Alzheimer's Disease (AD) pathology on the medial temporal lobe (MTL), a reflection that tau pathology is particularly striking in the entorhinal and transentorhinal cortex (ERC, TEC) early in the course of disease. However, other brain regions are affected by AD pathology during its early phases. Here, we use longitudinal diffeomorphometry to measure the atrophy rate from MRI of the amygdala compared with that in the ERC and TEC in cognitively unimpaired (CU) controls, CU individuals who progressed to mild cognitive impairment (MCI), and individuals with MCI who progressed to dementia of the AD type (DAT), using a dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Our results show significantly higher atrophy rates of the amygdala in both groups of 'converters' (CU→MCI, MCI→DAT) compared to controls, with rates of volume loss comparable to rates of thickness loss in the ERC and TEC. We localize atrophy within the amygdala within each of these groups using fixed effects modeling. Controlling for the familywise error rate highlights the medial regions of the amygdala as those with significantly higher atrophy in both groups of converters than in controls. Using our recently developed method, referred to as Projective LDDMM, we map measures of neurofibrillary tau tangles (NFTs) from digital pathology to MRI atlases and reconstruct dense 3D spatial distributions of NFT density within regions of the MTL. The distribution of NFTs is consistent with the spatial distribution of MR measured atrophy rates, revealing high densities (and atrophy) in the amygdala (particularly medial), ERC, and rostral third of the MTL. The similarity of the location of NFTs in AD and shape changes in a well-defined clinical population suggests that amygdalar atrophy rate, as measured through MRI may be a viable biomarker for AD.

A multimodal neuroimaging study of brain abnormalities and clinical correlates in post treatment Lyme disease

Lyme disease is the most common vector-borne infectious disease in the United States. Post-treatment Lyme disease (PTLD) is a condition affecting 10-20% of patients in which symptoms persist despite antibiotic treatment. Cognitive complaints are common among those with PTLD, suggesting that brain changes are associated with the course of the illness. However, there has been a paucity of evidence to explain the cognitive difficulties expressed by patients with PTLD. This study administered a working memory task to a carefully screened group of 12 patients with well-characterized PTLD and 18 healthy controls while undergoing functional MRI (fMRI). A subset of 12 controls and all 12 PTLD participants also received diffusion tensor imaging (DTI) to measure white matter integrity. Clinical variables were also assessed and correlated with these multimodal MRI findings. On the working memory task, the patients with PTLD responded more slowly, but no less accurately, than did controls. FMRI activations were observed in expected regions by the controls, and to a lesser extent, by the PTLD participants. The PTLD group also hypoactivated several regions relevant to the task. Conversely, novel regions were activated by the PTLD group that were not observed in controls, suggesting a compensatory mechanism. Notably, three activations were located in white matter of the frontal lobe. DTI measures applied to these three regions of interest revealed that higher axial diffusivity correlated with fewer cognitive and neurological symptoms. Whole-brain DTI analyses revealed several frontal lobe regions in which higher axial diffusivity in the patients with PTLD correlated with longer duration of illness. Together, these results show that the brain is altered by PTLD, involving changes to white matter within the frontal lobe. Higher axial diffusivity may reflect white matter repair and healing over time, rather than pathology, and cognition appears to be dynamically affected throughout this repair process.

High-resolution atlasing and segmentation of the subcortex: Review and perspective on challenges and opportunities created by machine learning

This paper reviews almost three decades of work on atlasing and segmentation methods for subcortical structures in human brain MRI. In writing this survey, we have three distinct aims. First, to document the evolution of digital subcortical atlases of the human brain, from the early MRI templates published in the nineties, to the complex multi-modal atlases at the subregion level that are available today. Second, to provide a detailed record of related efforts in the automated segmentation front, from earlier atlas-based methods to modern machine learning approaches. And third, to present a perspective on the future of high-resolution atlasing and segmentation of subcortical structures in in vivo human brain MRI, including open challenges and opportunities created by recent developments in machine learning.

The effect of beta-amyloid and tau protein aggregations on magnetic susceptibility of anterior hippocampal laminae in Alzheimer's diseases

Previous studies have reported the changes of magnetic susceptibility induced by iron deposition in hippocampus of Alzheimer's disease (AD) brains. It is well-known that hippocampus is divided into well-defined laminar architecture, which, however, is difficult to be resolved with in-vivo MRI due to the limited imaging resolution. The present study aims to investigate layer-specific magnetic susceptibility in the hippocampus of AD patients using high-resolution ex-vivo MRI, and elucidate its relationship with beta amyloid (Aβ) and tau protein histology. We performed quantitative susceptibility mapping (QSM) and T2* mapping on postmortem anterior hippocampus samples from four AD, four Primary Age-Related Tauopathy (PART), and three control brains. We manually segmented each sample into seven layers, including four layers in the cornu ammonis1 (CA1) and three layers in the dentate gyrus (DG), and then evaluated AD-related alterations of susceptibility and T2* values and their correlations with Aβ and tau in each hippocampal layer. Specifically, we found (1) layer-specific variations of susceptibility and T2* measurements in all samples; (2) the heterogeneity of susceptibility were higher in all layers of AD patients compared with the age- and gender-matched PART cases while the heterogeneity of T2* values were lower in four layers of CA1; and (3) voxel-wise MRI-histological correlation revealed both susceptibility and T2* values in the stratum molecular (SM) and stratum lacunosum (SL) layers were correlated with the Aβ content in AD, while the T2* values in the stratum radiatum (SR) layer were correlated with the tau content in the PART but not AD. These findings suggest a selective effect of the Aβ- and tau-pathology on the susceptibility and T2* values in the different layers of anterior hippocampus. Particularly, the alterations of magnetic susceptibility in the SM and SL layers may be associated with Aβ aggregation, while those in the SR layermay reflect the age-related tau protein aggregation.

Adherence to a MIND-Like Dietary Pattern, Long-Term Exposure to Fine Particulate Matter Air Pollution, and MRI-Based Measures of Brain Volume: The Women's Health Initiative Memory Study-MRI

BACKGROUND

Previous studies suggest that certain dietary patterns and constituents may be beneficial to brain health. Airborne exposures to fine particulate matter [particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 )] are neurotoxic, but the combined effects of dietary patterns and PM 2.5 have not been investigated.

OBJECTIVES

We examined whether previously reported association between PM 2.5 exposure and lower white matter volume (WMV) differed between women whose usual diet during the last 3 months before baseline was more or less consistent with a Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND)-like diet, a dietary pattern that may slow neurodegenerative changes.

METHODS

This study included 1,302 U.S. women who were 65-79 y old and free of dementia in the period 1996-1998 (baseline). In the period 2005-2006, structural brain magnetic resonance imaging (MRI) scans were performed to estimate normal-appearing brain volumes (excluding areas with evidence of small vessel ischemic disease). Baseline MIND diet scores were derived from a food frequency questionnaire. Three-year average PM 2.5 exposure prior to MRI was estimated using geocoded participant addresses and a spatiotemporal model.

RESULTS

Average total and temporal lobe WMVs were 0.74   cm 3 [95% confidence interval (CI): 0.001, 1.48) and 0.19   cm 3 (95% CI: 0.002, 0.37) higher, respectively, with each 0.5-point increase in the MIND score and were 4.16   cm 3 (95% CI: - 6.99 , - 1.33 ) and 1.46   cm 3 (95% CI: - 2.16 , - 0.76 ) lower, respectively, with each interquartile range (IQR) (IQR = 3.22   μ g / m 3 ) increase in PM 2.5 . The inverse association between PM 2.5 per IQR and WMV was stronger (p -interaction < 0.001 ) among women with MIND scores below the median (for total WMV, - 12.47   cm 3 ; 95% CI: - 17.17 , - 7.78 ), but absent in women with scores above the median (0.16   cm 3 ; 95% CI: - 3.41 , 3.72), with similar patterns for WMV in the frontal, parietal, and temporal lobes. For total cerebral and hippocampus brain volumes or WMV in the corpus callosum, the associations with PM 2.5 were not significantly different for women with high MIND scores and women with low MIND scores.

DISCUSSION

In this cohort of U.S. women, PM 2.5 exposure was associated with lower MRI-based WMV, an indication of brain aging, only among women whose usual diet was less consistent with the MIND-like dietary pattern at baseline. https://doi.org/10.1289/EHP8036.

Stability of hippocampal subfield volumes after trauma and relationship to development of PTSD symptoms

BACKGROUND

The hippocampus plays a central role in post-traumatic stress disorder (PTSD) pathogenesis, and the majority of neuroimaging research on PTSD has studied the hippocampus in its entirety. Although extensive literature demonstrates changes in hippocampal volume are associated with PTSD, fewer studies have probed the relationship between symptoms and the hippocampus' functionally and structurally distinct subfields. We utilized data from a longitudinal study examining post-trauma outcomes to determine whether hippocampal subfield volumes change post-trauma and whether specific subfields are significantly associated with, or prospectively related to, PTSD symptom severity. As a secondary aim, we leveraged our unique study design sample to also investigate reliability of hippocampal subfield volumes using both cross-sectional and longitudinal pipelines available in FreeSurfer v6.0.

METHODS

Two-hundred and fifteen traumatically injured individuals were recruited from an urban Emergency Department. Two-weeks post-injury, participants underwent two consecutive days of neuroimaging (time 1: T1, and time 2: T2) with magnetic resonance imaging (MRI) and completed self-report assessments. Six-months later (time 3: T3), participants underwent an additional scan and were administered a structured interview assessing PTSD symptoms. First, we calculated reliability of hippocampal measurements at T1 and T2 (automatically segmented with FreeSurfer v6.0). We then examined the prospective (T1 subfields) and cross-sectional (T3 subfields) relationship between volumes and PTSD. Finally, we tested whether change in subfield volumes between T1 and T3 explained PTSD symptom variability.

RESULTS

After controlling for sex, age, and total brain volume, none of the subfield volumes (T1) were prospectively related to T3 PTSD symptoms nor were subfield volumes (T3) associated with current PTSD symptoms (T3). Tl - T2 reliability of all hippocampal subfields ranged from good to excellent (intraclass correlation coefficient (ICC) values > 0.83), with poorer reliability in the hippocampal fissure.

CONCLUSION

Our study was a novel examination of the prospective relationship between hippocampal subfield volumes in relation to PTSD in a large trauma-exposed urban sample. There was no significant relationship between subfield volumes and PTSD symptoms, however, we confirmed FreeSurfer v6.0 hippocampal subfield segmentation is reliable when applied to a traumatically-injured sample, using both cross-sectional and longitudinal analysis pipelines. Although hippocampal subfield volumes may be an important marker of individual variability in PTSD, findings are likely conditional on the timing of the measurements (e.g. acute or chronic post-trauma periods) and analysis strategy (e.g. cross-sectional or prospective).

Epilepsy under the scope of ultra-high field MRI

Ultra-high field magnetic resonance imaging (UHF-MRI) is capable of unraveling anatomical structures in a submillimeter range. In addition, its high resonance regime allows the quantification of constitutive molecules in a spatially sensitive manner, a crucial capability for determining the extent and localization of a probable epileptogenic region or the severity of the epilepsy. The main technical challenges for data acquisition under UHF are to produce a strong, homogeneous transverse field, while keeping the tissue power deposition within the safe regulatory guidelines. The nonuniformities caused by destructive and constructive interferences at UHFs required new technologies to accelerate and increase yield regarding time spent and quality achieved. Image quality is the paramount contribution of UHF high-resolution imaging, which is capable to disclose fine details of the hippocampal formation and its surroundings and their changes in the course of epilepsy. Other sequences like diffusion tensor imaging (DTI) and multiecho susceptibility imaging at 7 T in vivo can assist the creation of normative atlases of the hippocampal subfields or the reconstruction of the highly arborized cerebral blood vessels. In our review, we specify the impact of these advanced relevant techniques onto the study of epilepsy. In this context, we focused onto high field high-resolution scanners and clinically-enriched decision-making. Studies on focal dysplasias correlating ex vivo high-resolution imaging with specific histological and ultrastructural patterns showed that white matter hyperintensities were related to a demyelination process and other alterations. Preliminary results correlating thick serial sections through bioptic epileptogenic tissue could extend the strategy to localize degenerated tissue sectors, correlate nature and extent of tissue loss with preoperative diagnosis and postoperative outcome. Finally, this protocol will provide the neurosurgeon with a detailed depiction of the removed pathologic tissue and possible adverse effects by the pathologic tissue left in situ. This article is part of the special issue "NEWroscience 2018".

Ultra-high field magnetic resonance imaging in human epilepsy: A systematic review

RATIONALE

Resective epilepsy surgery is an evidence-based curative treatment option for patients with drug-resistant focal epilepsy. The major preoperative predictor of a good surgical outcome is detection of an epileptogenic lesion by magnetic resonance imaging (MRI). Application of ultra-high field (UHF) MRI, i.e. field strengths ≥ 7 Tesla (T), may increase the sensitivity to detect such a lesion.

METHODS

A keyword search strategy was submitted to Pubmed, EMBASE, Cochrane Database and clinicaltrials.gov to select studies on UHF MRI in patients with epilepsy. Follow-up study selection and data extraction were performed following PRISMA guidelines. We focused on I) diagnostic gain of UHF- over conventional MRI, II) concordance of MRI-detected lesion, seizure onset zone and surgical decision-making, and III) postoperative histopathological diagnosis and seizure outcome.

RESULTS

Sixteen observational cohort studies, all using 7T MRI were included. Diagnostic gain of 7T over conventional MRI ranged from 8% to 67%, with a pooled gain of 31%. Novel techniques to visualize pathological processes in epilepsy and lesion detection are discussed. Seizure freedom was achieved in 73% of operated patients; no seizure outcome comparison was made between 7T MRI positive, 7T negative and 3T positive patients. 7T could influence surgical decision-making, with high concordance of lesion and seizure onset zone. Focal cortical dysplasia (54%), hippocampal sclerosis (12%) and gliosis (8.1%) were the most frequently diagnosed histopathological entities.

SIGNIFICANCE

UHF MRI increases, yet variably, the sensitivity to detect an epileptogenic lesion, showing potential for use in clinical practice. It remains to be established whether this results in improved seizure outcome after surgical treatment. Prospective studies with larger cohorts of epilepsy patients, uniform scan and sequence protocols, and innovative post-processing technology are equally important as further increasing field strengths. Besides technical ameliorations, improved correlation of imaging features with clinical semiology, histopathology and clinical outcome has to be established.

Diagnostic Performance of MRI Volumetry in Epilepsy Patients With Hippocampal Sclerosis Supported Through a Random Forest Automatic Classification Algorithm

Introduction: Several methods offer free volumetry services for MR data that adequately quantify volume differences in the hippocampus and its subregions. These methods are frequently used to assist in clinical diagnosis of suspected hippocampal sclerosis in temporal lobe epilepsy. A strong association between severity of histopathological anomalies and hippocampal volumes was reported using MR volumetry with a higher diagnostic yield than visual examination alone. Interpretation of volumetry results is challenging due to inherent methodological differences and to the reported variability of hippocampal volume. Furthermore, normal morphometric differences are recognized in diverse populations that may need consideration. To address this concern, we highlighted procedural discrepancies including atlas definition and computation of total intracranial volume that may impact volumetry results. We aimed to quantify diagnostic performance and to propose reference values for hippocampal volume from two well-established techniques: FreeSurfer v.06 and volBrain-HIPS.

Methods: Volumetry measures were calculated using clinical T1 MRI from a local population of 61 healthy controls and 57 epilepsy patients with confirmed unilateral hippocampal sclerosis. We further validated the results by a state-of-the-art machine learning classification algorithm (Random Forest) computing accuracy and feature relevance to distinguish between patients and controls. This validation process was performed using the FreeSurfer dataset alone, considering morphometric values not only from the hippocampus but also from additional non-hippocampal brain regions that could be potentially relevant for group classification. Mean reference values and 95% confidence intervals were calculated for left and right hippocampi along with hippocampal asymmetry degree to test diagnostic accuracy.

Results: Both methods showed excellent classification performance (AUC:> 0.914) with noticeable differences in absolute (cm³) and normalized volumes. Hippocampal asymmetry was the most accurate discriminator from all estimates (AUC:1~0.97). Similar results were achieved in the validation test with an automatic classifier (AUC:>0.960), disclosing hippocampal structures as the most relevant features for group differentiation among other brain regions.

Conclusion: We calculated reference volumetry values from two commonly used methods to accurately identify patients with temporal epilepsy and hippocampal sclerosis. Validation with an automatic classifier confirmed the principal role of the hippocampus and its subregions for diagnosis.

A Diffeomorphic Vector Field Approach to Analyze the Thickness of the Hippocampus From 7 T MRI

OBJECTIVE

7-Tesla MRI of the hippocampus enhances the visualization of its internal substructures. Among these substructures, the cornu Ammonis and subiculum form a contiguous folded ribbon of gray matter. Here, we propose a method to analyze local thickness measurements of this ribbon.

METHODS

We introduce an original approach based upon the estimation of a diffeomorphic vector field that traverses the ribbon. The method is designed to handle specificities of the hippocampus and corresponding 7-Tesla acquisitions: highly convoluted surface, non-closed ribbon, incompletely defined inner/outer boundaries, anisotropic acquisitions. We furthermore propose to conduct group comparisons using a population template built from the central surfaces of individual subjects.

RESULTS

We first assessed the robustness of our approach to anisotropy, as well as to inter-rater variability, on a post-mortem scan and on in vivo acquisitions respectively. We then conducted a group study on a dataset of in vivo MRI from temporal lobe epilepsy (TLE) patients and healthy controls. The method detected local thinning patterns in patients, predominantly ipsilaterally to the seizure focus, which is consistent with medical knowledge.

CONCLUSION

This new technique allows measuring the thickness of the hippocampus from 7-Tesla MRI. It shows good robustness with respect to anisotropy and inter-rater variability and has the potential to detect local atrophy in patients.

SIGNIFICANCE

As 7-Tesla MRI is increasingly available, this new method may become a useful tool to study local alterations of the hippocampus in brain disorders. It is made freely available to the community (code: https://github.com/aramis-lab/hiplay7-thickness, postmortem segmentation: https://doi.org/10.5281/zenodo.3533264).

Evolution of Human Brain Atlases in Terms of Content, Applications, Functionality, and Availability

Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and advanced brain atlas platforms, and 5 avenues in electronic atlases spanning the last two generations. Content-wise, new electronic atlases are categorized into eight groups considering their scope, parcellation, modality, plurality, scale, ethnicity, abnormality, and a mixture of them. Atlas content developments in these groups are heading in 23 various directions. Application-wise, we overview atlases in neuroeducation, research, and clinics, including stereotactic and functional neurosurgery, neuroradiology, neurology, and stroke. Functionality-wise, tools and functionalities are addressed for atlas creation, navigation, individualization, enabling operations, and application-specific. Availability is discussed in media and platforms, ranging from mobile solutions to leading-edge supercomputers, with three accessibility levels. The major application-wise shift has been from research to clinical practice, particularly in stereotactic and functional neurosurgery, although clinical applications are still lagging behind the atlas content progress. Atlas functionality also has been relatively neglected until recently, as the management of brain data explosion requires powerful tools. We suggest that the future human brain atlas-related research and development activities shall be founded on and benefit from a standard framework containing the core virtual brain model cum the brain atlas platform general architecture.

Age-related alterations in functional connectivity along the longitudinal axis of the hippocampus and its subfields

Hippocampal circuit alterations that differentially affect hippocampal subfields are associated with age-related memory decline. Additionally, functional organization along the longitudinal axis of the hippocampus has revealed distinctions between anterior and posterior (A-P) connectivity. Here, we examined the functional connectivity (FC) differences between young and older adults at high-resolution within the medial temporal lobe network (entorhinal, perirhinal, and parahippocampal cortices), allowing us to explore how hippocampal subfield connectivity across the longitudinal axis of the hippocampus changes with age. Overall, we found reliably greater connectivity for younger adults than older adults between the hippocampus and parahippocampal cortex (PHC) and perirhinal cortex (PRC). This drop in functional connectivity was more pronounced in the anterior regions of the hippocampus than the posterior ones, consistent for each of the hippocampal subfields. Further, intra-hippocampal connectivity also reflected an age-related decrease in functional connectivity within the anterior hippocampus in older adults that was offset by an increase in posterior hippocampal functional connectivity. Interestingly, the anterior-posterior dysfunction in older adults between hippocampus and PHC was predictive of lure discrimination performance on the Mnemonic similarity task (MST), suggesting a role in memory performance. While age-related dysfunction within the hippocampal subfields has been well-documented, these results suggest that the age-related dysfunction in hippocampal connectivity across the longitudinal axis may also contribute significantly to memory decline in older adults.

FreeSurfer ‐based segmentation of hippocampal subfields: A review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized.

Mesoscale diffusion magnetic resonance imaging of the ex vivo human hippocampus

Mesoscale diffusion magnetic resonance imaging (MRI) endeavors to bridge the gap between macroscopic white matter tractography and microscopic studies investigating the cytoarchitecture of human brain tissue. To ensure a robust measurement of diffusion at the mesoscale, acquisition parameters were arrayed to investigate their effects on scalar indices (mean, radial, axial diffusivity, and fractional anisotropy) and streamlines (i.e., graphical representation of axonal tracts) in hippocampal layers. A mesoscale resolution afforded segementation of the pyramidal cell layer (CA1-4), the dentate gyrus, as well as stratum moleculare, radiatum, and oriens. Using ex vivo samples, surgically excised from patients with intractable epilepsy (n = 3), we found that shorter diffusion times (23.7 ms) with a b-value of 4,000 s/mm2 were advantageous at the mesoscale, providing a compromise between mean diffusivity and fractional anisotropy measurements. Spatial resolution and sample orientation exerted a major effect on tractography, whereas the number of diffusion gradient encoding directions minimally affected scalar indices and streamline density. A sample temperature of 15°C provided a compromise between increasing signal-to-noise ratio and increasing the diffusion properties of the tissue. Optimization of the acquisition afforded a system's view of intra- and extra-hippocampal connections. Tractography reflected histological boundaries of hippocampal layers. Individual layer connectivity was visualized, as well as streamlines emanating from individual sub-fields. The perforant path, subiculum and angular bundle demonstrated extra-hippocampal connections. Histology of the samples confirmed individual cell layers corresponding to ROIs defined on MR images. We anticipate that this ex vivo mesoscale imaging will yield novel insights into human hippocampal connectivity.

Ex vivo mesoscopic diffusion MRI correlates with seizure frequency in patients with uncontrolled mesial temporal lobe epilepsy

The role of hippocampal connectivity in mesial temporal lobe epilepsy (mTLE) remains poorly understood. The use of ex vivo hippocampal samples excised from patients with mTLE affords mesoscale diffusion magnetic resonance imaging (MRI) to identify individual cell layers, such as the pyramidal (PCL) and granule cell layers (GCL), which are thought to be impacted by seizure activity. Diffusion tensor imaging (DTI) of control (n = 3) and mTLE (n = 7) hippocampi on an 11.7 T MRI scanner allowed us to reveal intra‐hippocampal connectivity and evaluate how epilepsy affected mean (MD), axial (AD), and radial diffusivity (RD), as well as fractional anisotropy (FA). Regional measurements indicated a volume loss in the PCL of the cornu ammonis (CA) 1 subfield in mTLE patients compared to controls, which provided anatomical context. Diffusion measurements, as well as streamline density, were generally higher in mTLE patients compared to controls, potentially reflecting differences due to tissue fixation. mTLE measurements were more variable than controls. This variability was associated with disease severity, as indicated by a strong correlation (r = 0.87) between FA in the stratum radiatum and the frequency of seizures in patients. MD and RD of the PCL in subfields CA3 and CA4 also correlated strongly with disease severity. No correlation of MR measures with disease duration was evident. These results reveal the potential of mesoscale diffusion MRI to examine layer‐specific diffusion changes and connectivity to determine how these relate to clinical measures. Improving the visualization of intra‐hippocampal connectivity will advance the development of novel hypotheses about seizure networks.

Dentate gyrus volume deficit in schizophrenia

BACKGROUND

Schizophrenia is associated with robust hippocampal volume deficits but subregion volume deficits, their associations with cognition, and contributing genes remain to be determined.

METHODS

Hippocampal formation (HF) subregion volumes were obtained using FreeSurfer 6.0 from individuals with schizophrenia (n = 176, mean age ± s.d. = 39.0 ± 11.5, 132 males) and healthy volunteers (n = 173, mean age ± s.d. = 37.6 ± 11.3, 123 males) with similar mean age, gender, handedness, and race distributions. Relationships between the HF subregion volume with the largest between group difference, neuropsychological performance, and single-nucleotide polymorphisms were assessed.

RESULTS

This study found a significant group by region interaction on hippocampal subregion volumes. Compared to healthy volunteers, individuals with schizophrenia had significantly smaller dentate gyrus (DG) (Cohen's d = -0.57), Cornu Ammonis (CA) 4, molecular layer of the hippocampus, hippocampal tail, and CA 1 volumes, when statistically controlling for intracranial volume; DG (d = -0.43) and CA 4 volumes remained significantly smaller when statistically controlling for mean hippocampal volume. DG volume showed the largest between group difference and significant positive associations with visual memory and speed of processing in the overall sample. Genome-wide association analysis with DG volume as the quantitative phenotype identified rs56055643 (β = 10.8, p < 5 × 10-8, 95% CI 7.0-14.5) on chromosome 3 in high linkage disequilibrium with MOBP. Gene-based analyses identified associations between SLC25A38 and RPSA and DG volume.

CONCLUSIONS

This study suggests that DG dysfunction is fundamentally involved in schizophrenia pathophysiology, that it may contribute to cognitive abnormalities in schizophrenia, and that underlying biological mechanisms may involve contributions from MOBP, SLC25A38, and RPSA.

Distinct Genetic Signatures of Cortical and Subcortical Regions Associated with Human Memory

Despite the discovery of gene variants linked to memory performance, understanding the genetic basis of adult human memory remains a challenge. Here, we devised an unsupervised framework that relies on spatial correlations between human transcriptome data and functional neuroimaging maps to uncover the genetic signatures of memory in functionally-defined cortical and subcortical memory regions.

Despite the discovery of gene variants linked to memory performance, understanding the genetic basis of adult human memory remains a challenge. Here, we devised an unsupervised framework that relies on spatial correlations between human transcriptome data and functional neuroimaging maps to uncover the genetic signatures of memory in functionally-defined cortical and subcortical memory regions. Results were validated with animal literature and showed that our framework is highly effective in identifying memory-related processes and genes compared to a control cognitive function. Genes preferentially expressed in cortical memory regions are linked to memory-related processes such as immune and epigenetic regulation. Genes expressed in subcortical memory regions are associated with neurogenesis and glial cell differentiation. Genes expressed in both cortical and subcortical memory areas are involved in the regulation of transcription, synaptic plasticity, and glutamate receptor signaling. Furthermore, distinct memory-associated genes such as PRKCD and CDK5 are linked to cortical and subcortical regions, respectively. Thus, cortical and subcortical memory regions exhibit distinct genetic signatures that potentially reflect functional differences in health and disease, and nominates gene candidates for future experimental investigations.

Functional parcellation of the hippocampus from resting-state dynamic functional connectivity

The hippocampus consists of functionally and structurally heterogeneous regions that are involved in multiple functions such as learning and memory. Previous studies on connectivity-based functional subdivisions of the hippocampus, however, overlooked the dynamic nature of resting-state functional connectivity (FC). In this study, we selected 50 subjects with the lowest head motion from the Human Connectome Project dataset and performed a two-stage spectral clustering technique to windowed FC correlations for identifying the potential covariant structures during the spontaneous fluctuation of hippocampal-cortical FC. The obtained covariant structures were believed to be functionally homogeneous by coupling with whole-brain regions in all transient connectivity states and consequently subdivided the left and right hippocampus into six and five functional subregions, respectively. Further, we demonstrated that this dynamic-FC-derived hippocampal parcellation exhibited significantly improved reproducibility of segmented subregions across subjects compared with static FC analysis. The findings extend our understanding to the functional organization within the hippocampus and provide a more comprehensive view of the functional flexibility of the hippocampus over time.

The effect of Zika virus infection in the ferret

Although initial observations of infections with the Zika virus describe a mild illness, more recent reports show that infections by Zika result in neurotropism. In 2015, substantial congenital malformations were observed, with numerous infants born with microcephaly in Brazil. To study the underlying mechanism and effects of the disease, it is critical to find suitable animal models. Rodents lack an immune system parallel to humans and also have lissencephalic brains, which are likely to react differently to infections. As the smallest gyrencephalic mammal, ferrets may provide an important animal model to study the Zika virus, as their brains share many characteristics with humans. To evaluate the prospect of using ferrets to study Zika virus infection, we injected seven pregnant jills with the PR strain subcutaneously on gestational day 21, corresponding to the initiation of corticogenesis. These injections resulted in mixed effects. Two animals died of apparent infection, and all kits were resorbed in another animal that did not die. The other four animals remained pregnant until gestational day 40, when the kits were delivered by caesarian section. We evaluated the animals using CT, MRI, diffusion tensor imaging, and immunohistochemistry. The kits displayed a number of features compatible with an infection that impacted both the brain and skull. The outcomes, however, were variable and differed within and across litters, which ranged from the absence of observable abnormalities to prominent changes, suggesting differential vulnerability of kits to infection by the Zika virus or to subsequent mechanisms of neurodevelopmental disruption.

Normal Aging Brain Collection Amsterdam (NABCA): A comprehensive collection of postmortem high-field imaging, neuropathological and morphometric datasets of non-neurological controls

Well-characterized, high-quality brain tissue of non-neurological control subjects is a prerequisite to study the healthy aging brain, and can serve as a control for the study of neurological disorders. The Normal Aging Brain Collection Amsterdam (NABCA) provides a comprehensive collection of post-mortem (ultra-)high-field MRI (3Tesla and 7 Tesla) and neuropathological datasets of non-neurological controls. By providing MRI within the pipeline, NABCA uniquely stimulates translational neurosciences; from molecular and morphometric tissue studies to the clinical setting. We describe our pipeline, including a description of our on-call autopsy team, donor selection, in situ and ex vivo post-mortem MRI protocols, brain dissection and neuropathological diagnosis. A demographic, radiological and pathological overview of five selected cases on all these aspects is provided. Additionally, information is given on data management, data and tissue application procedures, including review by a scientific advisory board, and setting up a material transfer agreement before distribution of tissue. Finally, we focus on future prospects, which includes laying the foundation for a unique platform for neuroanatomical, histopathological and neuro-radiological education, of professionals, students and the general (lay) audience.

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NABCA provides a collection of correlative post-mortem MRI and pathological datasets.

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Non-neurological control brains for studies on aging and neurological disorders.

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Stimulating micro- to macroscale structural exploration within same patient

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Post-mortem MRI data and tissue available for integrated advanced data analytics

Cortical thickness atrophy in the transentorhinal cortex in mild cognitive impairment

This study examines the atrophy rates of subjects with mild cognitive impairment (MCI) compared to controls in four regions within the medial temporal lobe: the transentorhinal cortex (TEC), entorhinal cortex (ERC), hippocampus, and amygdala. These regions were manually segmented and then corrected for undesirable longitudinal variability via Large Deformation Diffeomorphic Metric Mapping (LDDMM) based longitudinal diffeomorphometry. Diffeomorphometry techniques were used to compare thickness measurements in the TEC with the ERC. There were more significant changes in thickness atrophy rate in the TEC than medial regions of the entorhinal cortex. Volume measures were also calculated for all four regions. Classifiers were constructed using linear discriminant analysis to demonstrate that average thickness and atrophy rate of TEC together was the most discriminating measure compared to the thickness and volume measures in the areas examined, in differentiating MCI from controls. These findings are consistent with autopsy findings demonstrating that initial neuronal changes are found in TEC before spreading more medially in the ERC and to other regions in the medial temporal lobe. These findings suggest that the TEC thickness could serve as a biomarker for Alzheimer's disease in the prodromal phase of the disease.

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The transentorhinal cortex is significantly thinner in subjects with mild cognitive impairment than controls.

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Mildly cognitively impaired subjects show a significantly greater atrophy rate in the transentorhinal cortex than controls.

Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections

Nonlinear registration of 2D histological sections with corresponding slices of MRI data is a critical step of 3D histology reconstruction algorithms. This registration is difficult due to the large differences in image contrast and resolution, as well as the complex nonrigid deformations and artefacts produced when sectioning the sample and mounting it on the glass slide. It has been shown in brain MRI registration that better spatial alignment across modalities can be obtained by synthesising one modality from the other and then using intra-modality registration metrics, rather than by using information theory based metrics to solve the problem directly. However, such an approach typically requires a database of aligned images from the two modalities, which is very difficult to obtain for histology and MRI.

Here, we overcome this limitation with a probabilistic method that simultaneously solves for deformable registration and synthesis directly on the target images, without requiring any training data. The method is based on a probabilistic model in which the MRI slice is assumed to be a contrast-warped, spatially deformed version of the histological section. We use approximate Bayesian inference to iteratively refine the probabilistic estimate of the synthesis and the registration, while accounting for each other’s uncertainty. Moreover, manually placed landmarks can be seamlessly integrated in the framework for increased performance and robustness.

Experiments on a synthetic dataset of MRI slices show that, compared with mutual information based registration, the proposed method makes it possible to use a much more flexible deformation model in the registration to improve its accuracy, without compromising robustness. Moreover, our framework also exploits information in manually placed landmarks more efficiently than mutual information: landmarks constrain the deformation field in both methods, but in our algorithm, it also has a positive effect on the synthesis – which further improves the registration. We also show results on two real, publicly available datasets: the Allen and BigBrain atlases. In both of them, the proposed method provides a clear improvement over mutual information based registration, both qualitatively (visual inspection) and quantitatively (registration error measured with pairs of manually annotated landmarks).

Physical activity and dentate gyrus volume in pediatric acquired demyelinating syndromes

Objective

To assess the association between daily moderate-to-vigorous physical activity (MVPA) and dentate gyrus volume (DGv) in pediatric patients with acquired demyelinating syndromes (ADSs) of the CNS.

Methods

Cross-sectional analysis of accelerometry (7 days) and research protocol MRI data from 12 pediatric MS and 18 children with monophasic ADS (monoADS). Total brain and DGv were quantified using standardized methods. The association of daily minutes of MVPA with normalized DGv (nDGv) was assessed using multivariable generalized linear models.

Results

Median (interquartile range) MVPA was lower in MS patients [9.5 (14)] and exhibited less variation than in monoADS patients [24.5 (47)]. nDGv did not differ significantly between groups [mean nDGv (SD) [cm³]: MS 0.34 (0.1); monoADS 0.4 (0.1); p = 0.100]. In the monoADS group, every 1-minute increase in MVPA was associated with a 2.4-mm³ increase in nDGv (p = 0.0017), an association that was independent of age at incident demyelination, time from incident demyelination, sex, and brain white matter T2 lesion volume. No significant association was found between MVPA and nDGv (−2.6 mm³/min, p = 0.16) in the MS group.

Conclusions

Higher MVPA associates with greater nDGv in children who have recovered from monophasic demyelination. Larger studies are required to determine whether MVPA can promote regional brain development, or limit tissue damage, in youth with MS.

Characterizing the human hippocampus in aging and Alzheimer's disease using a computational atlas derived from ex vivo MRI and histology

Although the hippocampus is one of the most studied structures in the human brain, limited quantitative data exist on its 3D organization, anatomical variability, and effects of disease on its subregions. Histological studies provide restricted reference information due to their 2D nature. In this paper, high-resolution (∼200 × 200 × 200 μm³) ex vivo MRI scans of 31 human hippocampal specimens are combined using a groupwise diffeomorphic registration approach into a 3D probabilistic atlas that captures average anatomy and anatomic variability of hippocampal subfields. Serial histological imaging in 9 of the 31 specimens was used to label hippocampal subfields in the atlas based on cytoarchitecture. Specimens were obtained from autopsies in patients with a clinical diagnosis of Alzheimer's disease (AD; 9 subjects, 13 hemispheres), of other dementia (nine subjects, nine hemispheres), and in subjects without dementia (seven subjects, nine hemispheres), and morphometric analysis was performed in atlas space to measure effects of age and AD on hippocampal subfields. Disproportional involvement of the cornu ammonis (CA) 1 subfield and stratum radiatum lacunosum moleculare was found in AD, with lesser involvement of the dentate gyrus and CA2/3 subfields. An association with age was found for the dentate gyrus and, to a lesser extent, for CA1. Three-dimensional patterns of variability and disease and aging effects discovered via the ex vivo hippocampus atlas provide information highly relevant to the active field of in vivo hippocampal subfield imaging.

Key clinical benefits of neuroimaging at 7T

The growing interest in ultra-high field MRI, with more than 35.000 MR examinations already performed at 7T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7T is to gain higher spatial resolution in the brain compared to 3T. Of specific clinical interest for neuro applications is the cerebral cortex at 7T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7T.

Post-mortem inference of the human hippocampal connectivity and microstructure using ultra-high field diffusion MRI at 11.7 T

The human hippocampus plays a key role in memory management and is one of the first structures affected by Alzheimer's disease. Ultra-high magnetic resonance imaging provides access to its inner structure in vivo. However, gradient limitations on clinical systems hinder access to its inner connectivity and microstructure. A major target of this paper is the demonstration of diffusion MRI potential, using ultra-high field (11.7 T) and strong gradients (750 mT/m), to reveal the extra- and intra-hippocampal connectivity in addition to its microstructure. To this purpose, a multiple-shell diffusion-weighted acquisition protocol was developed to reach an ultra-high spatio-angular resolution with a good signal-to-noise ratio. The MRI data set was analyzed using analytical Q-Ball Imaging, Diffusion Tensor Imaging (DTI), and Neurite Orientation Dispersion and Density Imaging models. High Angular Resolution Diffusion Imaging estimates allowed us to obtain an accurate tractography resolving more complex fiber architecture than DTI models, and subsequently provided a map of the cross-regional connectivity. The neurite density was akin to that found in the histological literature, revealing the three hippocampal layers. Moreover, a gradient of connectivity and neurite density was observed between the anterior and the posterior part of the hippocampus. These results demonstrate that ex vivo ultra-high field/ultra-high gradients diffusion-weighted MRI allows the mapping of the inner connectivity of the human hippocampus, its microstructure, and to accurately reconstruct elements of the polysynaptic intra-hippocampal pathway using fiber tractography techniques at very high spatial/angular resolutions.

Three-Dimensional Volumetric Segmentation of Pituitary Tumors: Assessment of Inter-rater Agreement and Comparison with Conventional Geometric Equations

Background  The assessment of pituitary tumor (PT) volume is important in the treatment and follow-up of patients with PT. Previously, PT volume estimation has been performed by conventional geometric equations (CGE) such as abc/2 (simplified ellipsoid volume equation) and 4πr ³ /3 (sphere), both presuming a symmetric tumor shape, which occurs uncommonly in patients with PT. In contrast, three-dimensional (3D) voxel-based software segmentation takes the irregular and asymmetric shapes that PTs often possess into account and might be a more accurate method for PT volume segmentation. The purpose of this study is twofold. (1) To compare 3D segmentation with CGE for PT volume estimation. (2) To assess inter-rater reliability in 3D segmentation of PTs. Methods  Nineteen high-resolution (1mm slice thickness) T1-weighted MRI examinations of patients with PT were independently analyzed and manually segmented, using the software ITK-SNAP, by two certified neuroradiologists. Concurrently, the volumes of the PTs were estimated with abc/2 and 4πr ³ /3 by a clinician, and the results were compared with the corresponding segmented volumes. Results  There was a significant decrease in PT volume attained from the segmentations compared with the calculations made with abc/2 ( p  < 0.001, mean volume 18% higher than segmentation) and 4πr ³ /3 ( p  < 0.001, mean volume 28% higher than segmentation). The intraclass correlation coefficient (ICC) for the two sets of segmented PTs was 0.99. Conclusion  CGE ( abc/2 and 4πr ³ /3 ) significantly overestimates PT volume compared with 3D volumetric segmentation. The inter-rater agreement on manual 3D volumetric software segmentation is excellent.

The bumps under the hippocampus

Shown in every neuroanatomy textbook, a key morphological feature is the bumpy ridges, which we refer to as hippocampal dentation, on the inferior aspect of the hippocampus. Like the folding of the cerebral cortex, hippocampal dentation allows for greater surface area in a confined space. However, examining numerous approaches to hippocampal segmentation and morphology analysis, virtually all published 3D renderings of the hippocampus show the inferior surface to be quite smooth or mildly irregular; we have rarely seen the characteristic bumpy structure on reconstructed 3D surfaces. The only exception is a 9.4T postmortem study (Yushkevich et al. [2009]: NeuroImage 44:385-398). An apparent question is, does this indicate that this specific morphological signature can only be captured using ultra high-resolution techniques? Or, is such information buried in the data we commonly acquire, awaiting a computation technique that can extract and render it clearly? In this study, we propose an automatic and robust super-resolution technique that captures the fine scale morphometric features of the hippocampus based on common 3T MR images. The method is validated on 9.4T ultra-high field images and then applied on 3T data sets. This method opens possibilities of future research on the hippocampus and other sub-cortical structural morphometry correlating the degree of dentation with a range of diseases including epilepsy, Alzheimer's disease, and schizophrenia. Hum Brain Mapp 39:472-490, 2018. © 2017 Wiley Periodicals, Inc.

Segmenting hippocampal subfields from 3T MRI with multi-modality images

Hippocampal subfields play important roles in many brain activities. However, due to the small structural size, low signal contrast, and insufficient image resolution of 3T MR, automatic hippocampal subfields segmentation is less explored. In this paper, we propose an automatic learning-based hippocampal subfields segmentation method using 3T multi-modality MR images, including structural MRI (T1, T2) and resting state fMRI (rs-fMRI). The appearance features and relationship features are both extracted to capture the appearance patterns in structural MR images and also the connectivity patterns in rs-fMRI, respectively. In the training stage, these extracted features are adopted to train a structured random forest classifier, which is further iteratively refined in an auto-context model by adopting the context features and the updated relationship features. In the testing stage, the extracted features are fed into the trained classifiers to predict the segmentation for each hippocampal subfield, and the predicted segmentation is iteratively refined by the trained auto-context model. To our best knowledge, this is the first work that addresses the challenging automatic hippocampal subfields segmentation using relationship features from rs-fMRI, which is designed to capture the connectivity patterns of different hippocampal subfields. The proposed method is validated on two datasets and the segmentation results are quantitatively compared with manual labels using the leave-one-out strategy, which shows the effectiveness of our method. From experiments, we find a) multi-modality features can significantly increase subfields segmentation performance compared to those only using one modality; b) automatic segmentation results using 3T multi-modality MR images could be partially comparable to those using 7T T1 MRI.

Development of a histologically validated segmentation protocol for the hippocampal body

BACKGROUND

Recent findings have demonstrated that hippocampal subfields can be selectively affected in different disease states, which has led to efforts to segment the human hippocampus with in vivo magnetic resonance imaging (MRI). However, no studies have examined the histological accuracy of subfield segmentation protocols. The presence of MRI-visible anatomical landmarks with known correspondence to histology represents a fundamental prerequisite for in vivo hippocampal subfield segmentation. In the present study, we aimed to: 1) develop a novel method for hippocampal body segmentation, based on two MRI-visible anatomical landmarks (stratum lacunosum moleculare [SLM] & dentate gyrus [DG]), and assess its accuracy in comparison to the gold standard direct histological measurements; 2) quantify the accuracy of two published segmentation strategies in comparison to the histological gold standard; and 3) apply the novel method to ex vivo MRI and correlate the results with histology.

METHODS

Ultra-high resolution ex vivo MRI was performed on six whole cadaveric hippocampal specimens, which were then divided into 22 blocks and histologically processed. The hippocampal bodies were segmented into subfields based on histological criteria and subfield boundaries and areas were directly measured. A novel method was developed using mean percentage of the total SLM distance to define subfield boundaries. Boundary distances and subfield areas on histology were then determined using the novel method and compared to the gold standard histological measurements. The novel method was then used to determine ex vivo MRI measures of subfield boundaries and areas, which were compared to histological measurements.

RESULTS

For direct histological measurements, the mean percentages of total SLM distance were: Subiculum/CA1 = 9.7%, CA1/CA2 = 78.4%, CA2/CA3 = 97.5%. When applied to histology, the novel method provided accurate measures for CA1/CA2 (ICC = 0.93) and CA2/CA3 (ICC = 0.97) boundaries, but not for the Subiculum/CA1 (ICC = -0.04) boundary. Accuracy was poorer using previous techniques for CA1/CA2 (maximum ICC = 0.85) and CA2/CA3 (maximum ICC = 0.88), with the previously reported techniques also performing poorly in defining the Subiculum/CA1 boundary (maximum ICC = 0.00). Ex vivo MRI measurements using the novel method were linearly related to direct measurements of SLM length (r² = 0.58), CA1/CA2 boundary (r² = 0.39) and CA2/CA3 boundary (r² = 0.47), but not for Subiculum/CA1 boundary (r² = 0.01). Subfield areas measured with the novel method on histology and ex vivo MRI were linearly related to gold standard histological measures for CA1, CA2, and CA3/CA4/DG.

CONCLUSIONS

In this initial proof of concept study, we used ex vivo MRI and histology of cadaveric hippocampi to develop a novel segmentation protocol for the hippocampal body. The novel method utilized two anatomical landmarks, SLM & DG, and provided accurate measurements of CA1, CA2, and CA3/CA4/DG subfields in comparison to the gold standard histological measurements. The relationships demonstrated between histology and ex vivo MRI supports the potential feasibility of applying this method to in vivo MRI studies.

Segmenting subregions of the human hippocampus on structural magnetic resonance image scans: An illustrated tutorial

BACKGROUND

The hippocampus plays a central role in cognition, and understanding the specific contributions of its subregions will likely be key to explaining its wide-ranging functions. However, delineating substructures within the human hippocampus in vivo from magnetic resonance image scans is fraught with difficulties. To our knowledge, the extant literature contains only brief descriptions of segmentation procedures used to delineate hippocampal subregions in magnetic resonance imaging/functional magnetic resonance imaging studies.

METHODS

Consequently, here we provide a clear, step-by-step and fully illustrated guide to segmenting hippocampal subregions along the entire length of the human hippocampus on 3T magnetic resonance images.

RESULTS

We give a detailed description of how to segment the hippocampus into the following six subregions: dentate gyrus/Cornu Ammonis 4, CA3/2, CA1, subiculum, pre/parasubiculum and the uncus. Importantly, this in-depth protocol incorporates the most recent cyto- and chemo-architectural evidence and includes a series of comprehensive figures which compare slices of histologically stained tissue with equivalent 3T images.

CONCLUSION

As hippocampal subregion segmentation is an evolving field of research, we do not suggest this protocol is definitive or final. Rather, we present a fully explained and expedient method of manual segmentation which remains faithful to our current understanding of human hippocampal neuroanatomy. We hope that this 'tutorial'-style guide, which can be followed by experts and non-experts alike, will be a practical resource for clinical and research scientists with an interest in the human hippocampus.

In vivo quantification of amygdala subnuclei using 4.7 T fast spin echo imaging

The amygdala (AG) is an almond-shaped heterogeneous structure located in the medial temporal lobe. The majority of previous structural Magnetic Resonance Imaging (MRI) volumetric methods for AG measurement have so far only been able to examine this region as a whole. In order to understand the role of the AG in different neuropsychiatric disorders, it is necessary to understand the functional role of its subnuclei. The main goal of the present study was to develop a reliable volumetric method to delineate major AG subnuclei groups using ultra-high resolution high field MRI. 38 healthy volunteers (15 males and 23 females, 21-60 years of age) without any history of medical or neuropsychiatric disorders were recruited for this study. Structural MRI datasets were acquired at 4.7 T Varian Inova MRI system using a fast spin echo (FSE) sequence. The AG was manually segmented into its five major anatomical subdivisions: lateral (La), basal (B), accessory basal (AB) nuclei, and cortical (Co) and centromedial (CeM) groups. Inter-(intra-) rater reliability of our novel volumetric method was assessed using intra-class correlation coefficient (ICC) and Dice's Kappa. Our results suggest that reliable measurements of the AG subnuclei can be obtained by image analysts with experience in AG anatomy. We provided a step-by-step segmentation protocol and reported absolute and relative volumes for the AG subnuclei. Our results showed that the basolateral (BLA) complex occupies seventy-eight percent of the total AG volume, while CeM and Co groups occupy twenty-two percent of the total AG volume. Finally, we observed no hemispheric effects and no gender differences in the total AG volume and the volumes of its subnuclei. Future applications of this method will help to understand the selective vulnerability of the AG subnuclei in neurological and psychiatric disorders.

Subcortical Shape Changes, Hippocampal Atrophy and Cortical Thinning in Future Alzheimer's Disease Patients

Efficacy of future treatments depends on biomarkers identifying patients with mild cognitive impairment at highest risk for transitioning to Alzheimer's disease. Here, we applied recently developed analysis techniques to investigate cross-sectional differences in subcortical shape and volume alterations in patients with stable mild cognitive impairment (MCI) (n = 23, age range 59–82, 47.8% female), future converters at baseline (n = 10, age range 66–84, 90% female) and at time of conversion (age range 68–87) compared to group-wise age and gender matched healthy control subjects (n = 23, age range 61–81, 47.8% female; n = 10, age range 66–82, 80% female; n = 10, age range 68–82, 70% female). Additionally, we studied cortical thinning and global and local measures of hippocampal atrophy as known key imaging markers for Alzheimer's disease. Apart from bilateral striatal volume reductions, no morphometric alterations were found in cognitively stable patients. In contrast, we identified shape alterations in striatal and thalamic regions in future converters at baseline and at time of conversion. These shape alterations were paralleled by Alzheimer's disease like patterns of left hemispheric morphometric changes (cortical thinning in medial temporal regions, hippocampal total and subfield atrophy) in future converters at baseline with progression to similar right hemispheric alterations at time of conversion. Additionally, receiver operating characteristic curve analysis indicated that subcortical shape alterations may outperform hippocampal volume in identifying future converters at baseline. These results further confirm the key role of early cortical thinning and hippocampal atrophy in the early detection of Alzheimer's disease. But first and foremost, and by distinguishing future converters but not patients with stable cognitive abilities from cognitively normal subjects, our results support the value of early subcortical shape alterations and reduced hippocampal subfield volumes as potential markers for the early detection of Alzheimer's disease.

Hippocampal subfields at ultra high field MRI: An overview of segmentation and measurement methods

The hippocampus is one of the most interesting and studied brain regions because of its involvement in memory functions and its vulnerability in pathological conditions, such as neurodegenerative processes. In the recent years, the increasing availability of Magnetic Resonance Imaging (MRI) scanners that operate at ultra‐high field (UHF), that is, with static magnetic field strength ≥7T, has opened new research perspectives. Compared to conventional high‐field scanners, these systems can provide new contrasts, increased signal‐to‐noise ratio and higher spatial resolution, thus they may improve the visualization of very small structures of the brain, such as the hippocampal subfields. Studying the morphometry of the hippocampus is crucial in neuroimaging research because changes in volume and thickness of hippocampal subregions may be relevant in the early assessment of pathological cognitive decline and Alzheimer's Disease (AD). The present review provides an overview of the manual, semi‐automated and fully automated methods that allow the assessment of hippocampal subfield morphometry at UHF MRI, focusing on the different hippocampal segmentation produced. © 2017 The Authors Hippocampus Published by Wiley Periodicals, Inc.