Comparison of histological delineations of medial temporal lobe cortices by four independent neuroanatomy laboratories.

The medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and prone to the accumulation of certain neuropathologies such as Alzheimer's disease neurofibrillary tau tangles. The MTL cortex is composed of several subregions which differ in their functional and cytoarchitectonic features. As neuroanatomical schools rely on different cytoarchitectonic definitions of these subregions, it is unclear to what extent their delineations of MTL cortex subregions overlap. Here, we provide an overview of cytoarchitectonic definitions of the entorhinal and parahippocampal cortices as well as Brodmann areas (BA) 35 and 36, as provided by four neuroanatomists from different laboratories, aiming to identify the rationale for overlapping and diverging delineations. Nissl-stained series were acquired from the temporal lobes of three human specimens (two right and one left hemisphere). Slices (50 µm thick) were prepared perpendicular to the long axis of the hippocampus spanning the entire longitudinal extent of the MTL cortex. Four neuroanatomists annotated MTL cortex subregions on digitized slices spaced 5 mm apart (pixel size 0.4 µm at 20× magnification). Parcellations, terminology, and border placement were compared among neuroanatomists. Cytoarchitectonic features of each subregion are described in detail. Qualitative analysis of the annotations showed higher agreement in the definitions of the entorhinal cortex and BA35, while the definitions of BA36 and the parahippocampal cortex exhibited less overlap among neuroanatomists. The degree of overlap of cytoarchitectonic definitions was partially reflected in the neuroanatomists' agreement on the respective delineations. Lower agreement in annotations was observed in transitional zones between structures where seminal cytoarchitectonic features are expressed less saliently. The results highlight that definitions and parcellations of the MTL cortex differ among neuroanatomical schools and thereby increase understanding of why these differences may arise. This work sets a crucial foundation to further advance anatomically-informed neuroimaging research on the human MTL cortex.

Medial temporal lobe gray matter microstructure in preclinical Alzheimer's disease.

INTRODUCTION: Typical MRI measures of neurodegeneration have limited sensitivity in early disease stages. Diffusion MRI (dMRI) microstructural measures may allow for detection in preclinical stages. METHODS: Participants had dMRI and either beta-amyloid PET or plasma biomarkers of Alzheimer's pathology within 18 months of MRI. Microstructure was measured in portions of the medial temporal lobe (MTL) with high neurofibrillary tangle (NFT) burden based on a previously developed post mortem 3D-map. Regressions examined relationships between microstructure and markers of Alzheimer's pathology in preclinical disease and then across disease stages. RESULTS: There was higher isometric volume fraction in amyloid-positive compared to amyloid-negative cognitively unimpaired individuals in high tangle MTL regions. Similarly, plasma biomarkers and 18F-flortaucipir were associated with microstructural changes in preclinical disease. Additional microstructural effects were seen across disease stages. DISCUSSION: Combining a post mortem atlas of NFT pathology with microstructural measures allows for detection of neurodegeneration in preclinical Alzheimer's disease. Highlights Typical markers of neurodegeneration are not sensitive in preclinical Alzheimer's. dMRI measured microstructure in regions with high NFT. Microstructural changes occur in medial temporal regions in preclinical disease. Microstructural changes occur in other typical Alzheimer's regions in later stages. Combining post mortem pathology atlases with in vivo MRI is a powerful framework.

Tau-neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer's continuum.

INTRODUCTION: Variability in relationship of tau-based neurofibrillary tangles (T) and neurodegeneration (N) in Alzheimer's disease (AD) arises from non-specific nature of N, modulated by non-AD co-pathologies, age-related changes, and resilience factors. METHODS: We used regional T-N residual patterns to partition 184 patients within the Alzheimer's continuum into data-driven groups. These were compared with groups from 159 non-AD (amyloid "negative") patients partitioned using cortical thickness, and groups in 98 patients with ante mortem MRI and post mortem tissue for measuring N and T, respectively. We applied the initial T-N residual model to classify 71 patients in an independent cohort into predefined groups. RESULTS: AD groups displayed spatial T-N mismatch patterns resembling neurodegeneration patterns in non-AD groups, similarly associated with non-AD factors and diverging cognitive outcomes. In the autopsy cohort, limbic T-N mismatch correlated with TDP-43 co-pathology. DISCUSSION: T-N mismatch may provide a personalized approach for determining non-AD factors associated with resilience/vulnerability in AD.

Medial Temporal Lobe Networks in Alzheimer's Disease: Structural and Molecular Vulnerabilities.

The medial temporal lobe (MTL) is connected to the rest of the brain through two main networks: the anterior-temporal (AT) and the posterior-medial (PM) systems. Given the crucial role of the MTL and networks in the physiopathology of Alzheimer's disease (AD), the present study aimed at (1) investigating whether MTL atrophy propagates specifically within the AT and PM networks, and (2) evaluating the vulnerability of these networks to AD proteinopathies. To do that, we used neuroimaging data acquired in human male and female in three distinct cohorts: (1) resting-state functional MRI (rs-fMRI) from the aging brain cohort (ABC) to define the AT and PM networks (n = 68); (2) longitudinal structural MRI from Alzheimer's disease neuroimaging initiative (ADNI)GO/2 to highlight structural covariance patterns (n = 349); and (3) positron emission tomography (PET) data from ADNI3 to evaluate the networks' vulnerability to amyloid and tau (n = 186). Our results suggest that the atrophy of distinct MTL subregions propagates within the AT and PM networks in a dissociable manner. Brodmann area (BA)35 structurally covaried within the AT network while the parahippocampal cortex (PHC) covaried within the PM network. In addition, these networks are differentially associated with relative tau and amyloid burden, with higher tau levels in AT than in PM and higher amyloid levels in PM than in AT. Our results also suggest differences in the relative burden of tau species. The current results provide further support for the notion that two distinct MTL networks display differential alterations in the context of AD. These findings have important implications for disease spread and the cognitive manifestations of AD.SIGNIFICANCE STATEMENT The current study provides further support for the notion that two distinct medial temporal lobe (MTL) networks, i.e., anterior-temporal (AT) and the posterior-medial (PM), display differential alterations in the context of Alzheimer's disease (AD). Importantly, neurodegeneration appears to occur within these networks in a dissociable manner marked by their covariance patterns. In addition, the AT and PM networks are also differentially associated with relative tau and amyloid burden, and perhaps differences in the relative burden of tau species [e.g., neurofibriliary tangles (NFTs) vs tau in neuritic plaques]. These findings, in the context of a growing literature consistent with the present results, have important implications for disease spread and the cognitive manifestations of AD in light of the differential cognitive processes ascribed to them.

Young versus older subject diffusion magnetic resonance imaging data for virtual white matter lesion tractography.

White matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal-appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP-Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age-matched normative data.

Automated analysis of low-field brain MRI in cerebral malaria.

A central challenge of medical imaging studies is to extract biomarkers that characterize disease pathology or outcomes. Modern automated approaches have found tremendous success in high-resolution, high-quality magnetic resonance images. These methods, however, may not translate to low-resolution images acquired on magnetic resonance imaging (MRI) scanners with lower magnetic field strength. In low-resource settings where low-field scanners are more common and there is a shortage of radiologists to manually interpret MRI scans, it is critical to develop automated methods that can augment or replace manual interpretation, while accommodating reduced image quality. We present a fully automated framework for translating radiological diagnostic criteria into image-based biomarkers, inspired by a project in which children with cerebral malaria (CM) were imaged using low-field 0.35 Tesla MRI. We integrate multiatlas label fusion, which leverages high-resolution images from another sample as prior spatial information, with parametric Gaussian hidden Markov models based on image intensities, to create a robust method for determining ventricular cerebrospinal fluid volume. We also propose normalized image intensity and texture measurements to determine the loss of gray-to-white matter tissue differentiation and sulcal effacement. These integrated biomarkers have excellent classification performance for determining severe brain swelling due to CM.

Associations of phosphorylated tau pathology with whole-hemisphere ex vivo morphometry in 7 tesla MRI.

INTRODUCTION: Neurodegenerative disorders are associated with different pathologies that often co-occur but cannot be measured specifically with in vivo methods. METHODS: Thirty-three brain hemispheres from donors with an Alzheimer's disease (AD) spectrum diagnosis underwent T2-weighted magnetic resonance imaging (MRI). Gray matter thickness was paired with histopathology from the closest anatomic region in the contralateral hemisphere. RESULTS: Partial Spearman correlation of phosphorylated tau and cortical thickness with TAR DNA-binding protein 43 (TDP-43) and α-synuclein scores, age, sex, and postmortem interval as covariates showed significant relationships in entorhinal and primary visual cortices, temporal pole, and insular and posterior cingulate gyri. Linear models including Braak stages, TDP-43 and α-synuclein scores, age, sex, and postmortem interval showed significant correlation between Braak stage and thickness in the parahippocampal gyrus, entorhinal cortex, and Broadman area 35. CONCLUSION: We demonstrated an association of measures of AD pathology with tissue loss in several AD regions despite a limited range of pathology in these cases. HIGHLIGHTS: Neurodegenerative disorders are associated with co-occurring pathologies that cannot be measured specifically with in vivo methods. Identification of the topographic patterns of these pathologies in structural magnetic resonance imaging (MRI) may provide probabilistic biomarkers. We demonstrated the correlation of the specific patterns of tissue loss from ex vivo brain MRI with underlying pathologies detected in postmortem brain hemispheres in patients with Alzheimer's disease (AD) spectrum disorders. The results provide insight into the interpretation of in vivo structural MRI studies in patients with AD spectrum disorders.

Tau-Atrophy Variability Reveals Phenotypic Heterogeneity in Alzheimer's Disease.

OBJECTIVE: Tau neurofibrillary tangles (T) are the primary driver of downstream neurodegeneration (N) and subsequent cognitive impairment in Alzheimer's disease (AD). However, there is substantial variability in the T-N relationship - manifested in higher or lower atrophy than expected for level of tau in a given brain region. The goal of this study was to determine if region-based quantitation of this variability allows for identification of underlying modulatory factors, including polypathology. METHODS: Cortical thickness (N) and 18 F-Flortaucipir SUVR (T) were computed in 104 gray matter regions from a cohort of cognitively-impaired, amyloid-positive (A+) individuals. Region-specific residuals from a robust linear fit between SUVR and cortical thickness were computed as a surrogate for T-N mismatch. A summary T-N mismatch metric defined using residuals were correlated with demographic and imaging-based modulatory factors, and to partition the cohort into data-driven subgroups. RESULTS: The summary T-N mismatch metric correlated with underlying factors such as age and burden of white matter hyperintensity lesions. Data-driven subgroups based on clustering of residuals appear to represent different biologically relevant phenotypes, with groups showing distinct spatial patterns of higher or lower atrophy than expected. INTERPRETATION: These data support the notion that a measure of deviation from a normative relationship between tau burden and neurodegeneration across brain regions in individuals on the AD continuum captures variability due to multiple underlying factors, and can reveal phenotypes, which if validated, may help identify possible contributors to neurodegeneration in addition to tau, which may ultimately be useful for cohort selection in clinical trials. ANN NEUROL 2021;90:751-762.

Regional distribution and maturation of tau pathology among phenotypic variants of Alzheimer's disease.

Alzheimer's disease neuropathologic change (ADNC) is clinically heterogenous and can present with a classic multidomain amnestic syndrome or focal non-amnestic syndromes. Here, we investigated the distribution and burden of phosphorylated and C-terminally cleaved tau pathologies across hippocampal subfields and cortical regions among phenotypic variants of Alzheimer's disease (AD). In this study, autopsy-confirmed patients with ADNC, were classified into amnestic (aAD, N = 40) and non-amnestic (naAD, N = 39) groups based on clinical criteria. We performed digital assessment of tissue sections immunostained for phosphorylated-tau (AT8 detects pretangles and mature tangles), D421-truncated tau (TauC3, a marker for mature tangles and ghost tangles), and E391-truncated tau (MN423, a marker that primarily detects ghost tangles), in hippocampal subfields and three cortical regions. Linear mixed-effect models were used to test regional and group differences while adjusting for demographics. Both groups showed AT8-reactivity across hippocampal subfields that mirrored traditional Braak staging with higher burden of phosphorylated-tau in subregions implicated as affected early in Braak staging. The burden of phosphorylated-tau and TauC3-immunoreactive tau in the hippocampus was largely similar between the aAD and naAD groups. In contrast, the naAD group had lower relative distribution of MN423-reactive tangles in CA1 (ß = - 0.2, SE = 0.09, p = 0.001) and CA2 (ß = - 0.25, SE = 0.09, p = 0.005) compared to the aAD. While the two groups had similar levels of phosphorylated-tau pathology in cortical regions, there was higher burden of TauC3 reactivity in sup/mid temporal cortex (ß = 0.16, SE = 0.07, p = 0.02) and MN423 reactivity in all cortical regions (ß = 0.4-0.43, SE = 0.09, p < 0.001) in the naAD compared to aAD. In conclusion, AD clinical variants may have a signature distribution of overall phosphorylated-tau pathology within the hippocampus reflecting traditional Braak staging; however, non-amnestic AD has greater relative mature tangle pathology in the neocortex compared to patients with clinical amnestic AD, where the hippocampus had greatest relative burden of C-terminally cleaved tau reactivity. Thus, varying neuronal susceptibility to tau-mediated neurodegeneration may influence the clinical expression of ADNC.

Early stages of tau pathology and its associations with functional connectivity, atrophy and memory.

In Alzheimer's disease, post-mortem studies have shown that the first cortical site where neurofibrillary tangles appear is the transentorhinal region, a subregion within the medial temporal lobe that largely overlaps with Brodmann area 35, and the entorhinal cortex. Here we used tau-PET imaging to investigate the sequence of tau pathology progression within the human medial temporal lobe and across regions in the posterior-medial system. Our objective was to study how medial temporal tau is related to functional connectivity, regional atrophy, and memory performance. We included 215 amyloid-ß- cognitively unimpaired, 81 amyloid-ß+ cognitively unimpaired and 87 amyloid-ß+ individuals with mild cognitive impairment, who each underwent 18F-RO948 tau and 18F-flutemetamol amyloid PET imaging, structural T1-MRI and memory assessments as part of the Swedish BioFINDER-2 study. First, event-based modelling revealed that the entorhinal cortex and Brodmann area 35 show the earliest signs of tau accumulation followed by the anterior and posterior hippocampus, Brodmann area 36 and the parahippocampal cortex. In later stages, tau accumulation became abnormal in neocortical temporal and finally parietal brain regions. Second, in cognitively unimpaired individuals, increased tau load was related to local atrophy in the entorhinal cortex, Brodmann area 35 and the anterior hippocampus and tau load in several anterior medial temporal lobe subregions was associated with distant atrophy of the posterior hippocampus. Tau load, but not atrophy, in these regions was associated with lower memory performance. Further, tau-related reductions in functional connectivity in critical networks between the medial temporal lobe and regions in the posterior-medial system were associated with this early memory impairment. Finally, in patients with mild cognitive impairment, the association of tau load in the hippocampus with memory performance was partially mediated by posterior hippocampal atrophy. In summary, our findings highlight the progression of tau pathology across medial temporal lobe subregions and its disease stage-specific association with memory performance. While tau pathology might affect memory performance in cognitively unimpaired individuals via reduced functional connectivity in critical medial temporal lobe-cortical networks, memory impairment in mild cognitively impaired patients is associated with posterior hippocampal atrophy.

Three-dimensional mapping of neurofibrillary tangle burden in the human medial temporal lobe.

Tau protein neurofibrillary tangles are closely linked to neuronal/synaptic loss and cognitive decline in Alzheimer's disease and related dementias. Our knowledge of the pattern of neurofibrillary tangle progression in the human brain, critical to the development of imaging biomarkers and interpretation of in vivo imaging studies in Alzheimer's disease, is based on conventional two-dimensional histology studies that only sample the brain sparsely. To address this limitation, ex vivo MRI and dense serial histological imaging in 18 human medial temporal lobe specimens (age 75.3 ± 11.4 years, range 45 to 93) were used to construct three-dimensional quantitative maps of neurofibrillary tangle burden in the medial temporal lobe at individual and group levels. Group-level maps were obtained in the space of an in vivo brain template, and neurofibrillary tangles were measured in specific anatomical regions defined in this template. Three-dimensional maps of neurofibrillary tangle burden revealed significant variation along the anterior-posterior axis. While early neurofibrillary tangle pathology is thought to be confined to the transentorhinal region, we found similar levels of burden in this region and other medial temporal lobe subregions, including amygdala, temporopolar cortex, and subiculum/cornu ammonis 1 hippocampal subfields. Overall, the three-dimensional maps of neurofibrillary tangle burden presented here provide more complete information about the distribution of this neurodegenerative pathology in the region of the cortex where it first emerges in Alzheimer's disease, and may help inform the field about the patterns of pathology spread, as well as support development and validation of neuroimaging biomarkers.

Fully Automated Placental Volume Quantification From 3D Ultrasound for Prediction of Small-for-Gestational-Age Infants.

OBJECTIVES: Early placental volume (PV) has been associated with small-for-gestational-age infants born under the 10th/5th centiles (SGA10/SGA5). Manual or semiautomated PV quantification from 3D ultrasound (3DUS) is time intensive, limiting its incorporation into clinical care. We devised a novel convolutional neural network (CNN) pipeline for fully automated placenta segmentation from 3DUS images, exploring the association between the calculated PV and SGA. METHODS: Volumes of 3DUS obtained from singleton pregnancies at 11-14 weeks' gestation were automatically segmented by our CNN pipeline trained and tested on 99/25 images, combining two 2D and one 3D models with downsampling/upsampling architecture. The PVs derived from the automated segmentations (PVCNN ) were used to train multivariable logistic-regression classifiers for SGA10/SGA5. The test performance for predicting SGA was compared to PVs obtained via the semiautomated VOCAL (GE-Healthcare) method (PVVOCAL ). RESULTS: We included 442 subjects with 37 (8.4%) and 18 (4.1%) SGA10/SGA5 infants, respectively. Our segmentation pipeline achieved a mean Dice score of 0.88 on an independent test-set. Adjusted models including PVCNN or PVVOCAL were similarly predictive of SGA10 (area under curve [AUC]: PVCNN  = 0.780, PVVOCAL  = 0.768). The addition of PVCNN to a clinical model without any PV included (AUC = 0.725) yielded statistically significant improvement in AUC (P < .05); whereas PVVOCAL did not (P = .105). Moreover, when predicting SGA5, including the PVCNN (0.897) brought statistically significant improvement over both the clinical model (0.839, P = .015) and the PVVOCAL model (0.870, P = .039). CONCLUSIONS: First trimester PV measurements derived from our CNN segmentation pipeline are significantly associated with future SGA. This fully automated tool enables the incorporation of including placental volumetric biometry into the bedside clinical evaluation as part of a multivariable prediction model for risk stratification and patient counseling.

DeepAtrophy: Teaching a neural network to detect progressive changes in longitudinal MRI of the hippocampal region in Alzheimer's disease.

Measures of change in hippocampal volume derived from longitudinal MRI are a well-studied biomarker of disease progression in Alzheimer's disease (AD) and are used in clinical trials to track therapeutic efficacy of disease-modifying treatments. However, longitudinal MRI change measures based on deformable registration can be confounded by MRI artifacts, resulting in over-estimation or underestimation of hippocampal atrophy. For example, the deformation-based-morphometry method ALOHA (Das et al., 2012) finds an increase in hippocampal volume in a substantial proportion of longitudinal scan pairs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, unexpected, given that the hippocampal gray matter is lost with age and disease progression. We propose an alternative approach to quantify disease progression in the hippocampal region: to train a deep learning network (called DeepAtrophy) to infer temporal information from longitudinal scan pairs. The underlying assumption is that by learning to derive time-related information from scan pairs, the network implicitly learns to detect progressive changes that are related to aging and disease progression. Our network is trained using two categorical loss functions: one that measures the network's ability to correctly order two scans from the same subject, input in arbitrary order; and another that measures the ability to correctly infer the ratio of inter-scan intervals between two pairs of same-subject input scans. When applied to longitudinal MRI scan pairs from subjects unseen during training, DeepAtrophy achieves greater accuracy in scan temporal ordering and interscan interval inference tasks than ALOHA (88.5% vs. 75.5% and 81.1% vs. 75.0%, respectively). A scalar measure of time-related change in a subject level derived from DeepAtrophy is then examined as a biomarker of disease progression in the context of AD clinical trials. We find that this measure performs on par with ALOHA in discriminating groups of individuals at different stages of the AD continuum. Overall, our results suggest that using deep learning to infer temporal information from longitudinal MRI of the hippocampal region has good potential as a biomarker of disease progression, and hints that combining this approach with conventional deformation-based morphometry algorithms may lead to improved biomarkers in the future.

Hippocampal subfield volumetry from structural isotropic 1 mm3 MRI scans: A note of caution.

Spurred by availability of automatic segmentation software, in vivo MRI investigations of human hippocampal subfield volumes have proliferated in the recent years. However, a majority of these studies apply automatic segmentation to MRI scans with approximately 1 × 1 × 1 mm3 resolution, a resolution at which the internal structure of the hippocampus can rarely be visualized. Many of these studies have reported contradictory and often neurobiologically surprising results pertaining to the involvement of hippocampal subfields in normal brain function, aging, and disease. In this commentary, we first outline our concerns regarding the utility and validity of subfield segmentation on 1 × 1 × 1 mm3 MRI for volumetric studies, regardless of how images are segmented (i.e., manually or automatically). This image resolution is generally insufficient for visualizing the internal structure of the hippocampus, particularly the stratum radiatum lacunosum moleculare, which is crucial for valid and reliable subfield segmentation. Second, we discuss the fact that automatic methods that are employed most frequently to obtain hippocampal subfield volumes from 1 × 1 × 1 mm3 MRI have not been validated against manual segmentation on such images. For these reasons, we caution against using volumetric measurements of hippocampal subfields obtained from 1 × 1 × 1 mm3 images.

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.

Characterization of hippocampal subfields using ex vivo MRI and histology data: Lessons for in vivo segmentation.

Hippocampal subfield segmentation on in vivo MRI is of great interest for cognition, aging, and disease research. Extant subfield segmentation protocols have been based on neuroanatomical references, but these references often give limited information on anatomical variability. Moreover, there is generally a mismatch between the orientation of the histological sections and the often anisotropic coronal sections on in vivo MRI. To address these issues, we provide a detailed description of hippocampal anatomy using a postmortem dataset containing nine specimens of subjects with and without dementia, which underwent a 9.4 T MRI and histological processing. Postmortem MRI matched the typical orientation of in vivo images and segmentations were generated in MRI space, based on the registered annotated histological sections. We focus on the following topics: the order of appearance of subfields, the location of subfields relative to macroanatomical features, the location of subfields in the uncus and tail and the composition of the dark band, a hypointense layer visible in T2-weighted MRI. Our main findings are that: (a) there is a consistent order of appearance of subfields in the hippocampal head, (b) the composition of subfields is not consistent in the anterior uncus, but more consistent in the posterior uncus, (c) the dark band consists only of the CA-stratum lacunosum moleculare, not the strata moleculare of the dentate gyrus, (d) the subiculum/CA1 border is located at the middle of the width of the hippocampus in the body in coronal plane, but moves in a medial direction from anterior to posterior, and (e) the variable location and composition of subfields in the hippocampal tail can be brought back to a body-like appearance when reslicing the MRI scan following the curvature of the tail. Our findings and this publicly available dataset will hopefully improve anatomical accuracy of future hippocampal subfield segmentation protocols.

Longitudinal atrophy in early Braak regions in preclinical Alzheimer's disease.

A major focus of Alzheimer's disease (AD) research has been finding sensitive outcome measures to disease progression in preclinical AD, as intervention studies begin to target this population. We hypothesize that tailored measures of longitudinal change of the medial temporal lobe (MTL) subregions (the sites of earliest cortical tangle pathology) are more sensitive to disease progression in preclinical AD compared to standard cognitive and plasma NfL measures. Longitudinal T1-weighted MRI of 337 participants were included, divided into amyloid-ß negative (Aß-) controls, cerebral spinal fluid p-tau positive (T+) and negative (T-) preclinical AD (Aß+ controls), and early prodromal AD. Anterior/posterior hippocampus, entorhinal cortex, Brodmann areas (BA) 35 and 36, and parahippocampal cortex were segmented in baseline MRI using a novel pipeline. Unbiased change rates of subregions were estimated using MRI scans within a 2-year-follow-up period. Experimental results showed that longitudinal atrophy rates of all MTL subregions were significantly higher for T+ preclinical AD and early prodromal AD than controls, but not for T- preclinical AD. Posterior hippocampus and BA35 demonstrated the largest group differences among hippocampus and MTL cortex respectively. None of the cross-sectional MTL measures, longitudinal cognitive measures (PACC, ADAS-Cog) and cross-sectional or longitudinal plasma NfL reached significance in preclinical AD. In conclusion, longitudinal atrophy measurements reflect active neurodegeneration and thus are more directly linked to active disease progression than cross-sectional measurements. Moreover, accelerated atrophy in preclinical AD seems to occur only in the presence of concomitant tau pathology. The proposed longitudinal measurements may serve as efficient outcome measures in clinical trials.

Quantitative three-dimensional echocardiographic analysis of the bicuspid aortic valve and aortic root: A single modality approach.

BACKGROUND: Patients with bicuspid aortic valves (BAV) are heterogeneous with regard to patterns of root remodeling and valvular dysfunction. Two-dimensional echocardiography is the standard surveillance modality for patients with aortic valve dysfunction. However, ancillary computed tomography or magnetic resonance imaging is often necessary to characterize associated patterns of aortic root pathology. Conversely, the pairing of three-dimensional (3D) echocardiography with novel quantitative modeling techniques allows for a single modality description of the entire root complex. We sought to determine 3D aortic valve and root geometry with this quantitative approach. METHODS: Transesophageal real-time 3D echocardiography was performed in five patients with tricuspid aortic valves (TAV) and in five patients with BAV. No patient had evidence of valvular dysfunction or aortic root pathology. A customized image analysis protocol was used to assess 3D aortic annular, valvular, and root geometry. RESULTS: Annular, sinus and sinotubular junction diameters and areas were similar in both groups. Coaptation length and area were higher in the TAV group (7.25 ± 0.98 mm and 298 ± 118 mm2 , respectively) compared to the BAV group (5.67 ± 1.33 mm and 177 ± 43 mm2 ; P = .07 and P = .01). Cusp surface area to annular area, coaptation height, and the sub- and supravalvular tenting indices did not differ significantly between groups. CONCLUSIONS: Single modality 3D echocardiography-based modeling allows for a quantitative description of the aortic valve and root geometry. This technique together with novel indices will improve our understanding of normal and pathologic geometry in the BAV population and may help to identify geometric predictors of adverse remodeling and guide tailored surgical therapy.

Contribution of mixed pathology to medial temporal lobe atrophy in Alzheimer's disease.

INTRODUCTION: It is unclear how different proteinopathies (tau, transactive response DNA-binding protein 43 [TDP-43], amyloid ß [Aß], and α-synuclein) contribute to atrophy within medial temporal lobe (MTL) subregions in Alzheimer's disease (AD). METHODS: We utilized antemortem structural magnetic resonance imaging (MRI) data to measure MTL substructures and examined the relative contribution of tau, TDP-43, Aß, and α-synuclein measured in post-mortem tissue from 92 individuals with intermediate to high AD neuropathology. Receiver-operating characteristic (ROC) curves were analyzed for each subregion in order to discriminate TDP-43-negative and TDP-43-positive patients. RESULTS: TDP-43 was strongly associated with anterior MTL regions, whereas tau was relatively more associated with the posterior hippocampus. Among the MTL regions, the anterior hippocampus showed the highest area under the ROC curve (AUC). DISCUSSION: We found specific contributions of different pathologies on MTL substructure in this population with AD neuropathology. The anterior hippocampus may be a relevant region to detect concomitant TDP-43 pathology in the MTL of patients with AD.

Task-enhanced arterial spin labeled perfusion MRI predicts longitudinal neurodegeneration in mild cognitive impairment.

Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer's disease (AD), but is also recognized to be a heterogeneous condition. Biomarkers that predict AD progression in MCI are of clinical significance because they can be used to better identify appropriate candidates for therapeutic intervention studies. It has been hypothesized that comparing to structural measurements, functional ones may be more sensitive to early disease abnormalities and the sensitivity could be further enhanced when combined with cognitive task, a "brain stress test." In this study, we investigated the value of regional cerebral blood flow (CBF), measured by arterial spin labeled perfusion MRI (ASL MRI) during a memory-encoding task, in predicting the estimated rate of hippocampal atrophy, an established marker of AD progression. Thirty-one amnestic MCI patients (20 male and 11 female; age: 70.9 ± 6.5 years, range from 56 to 83 years; mini mental status examination: 27.8 ± 1.8) and 42 normal control subjects (13 male and 29 female; age: 70.6 ± 8.8 years, range from 55 to 88 years; mini mental status examination: 29.1 ± 1.2) were included in this study. We compared the predictive value of CBF during task to CBF during rest and structural volumetry. Both region-of-interest and voxelwise analyses showed that baseline CBF measurements during task (strongest effect in fusiform gyrus, region-of-interest analysis statistics: r = 0.56, p = .003), but not resting ASL MRI or structural volumetry, were correlated with the estimated rate of hippocampal atrophy in amnestic MCI patients. Further, stepwise linear regression demonstrated that resting ASL MRI and volumetry did not provide complementary information in prediction. These results support the notion that physiologic measures during a cognitive challenge may increase the ability to detect subtle functional changes that predict progression. As such, ASL MRI could have important utility in stratifying candidates for AD treatment trials.