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.

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

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

Occupational dermatitis in health care workers evaluated for suspected allergic contact dermatitis.

BACKGROUND: Contact dermatitides occur commonly among health care workers (HCWs). OBJECTIVE: To contrast the atopic status and incidence, location, and final diagnosis of skin diseases afflicting HCWs versus non-HCWs (NHCWs) evaluated for suspicion of allergic contact dermatitis (ACD); and among the population diagnosed with ACD, to compare the incidence and occupational relatedness of allergens found in HCWs with the rates observed in NHCWs. METHODS: Between July 1, 1994, and May 30, 2014, 2611 patients underwent patch testing by the senior author. Of these, 165 were classified as HCWs based on their primary occupation. Statistical analysis was done using a χ test. RESULTS: Health care workers were more likely than NHCWs to be women and to have hand dermatitis. Women, but not men, HCWs suffered more irritant contact dermatitis. Health care workers had significantly more work-related ACD, especially to formaldehyde, quaternium-15, 2-bromo-2-nitropropane-1,3-diol, cocamide diethanolamine (DEA), thiuram mix, carba mix, thimerosal, benzalkonium chloride, glutaraldehyde, and bacitracin. LIMITATIONS: Only patients suspected of having ACD were tested. Our population was geographically limited to metropolitan Kansas City, MO and metropolitan New York, NY. CONCLUSIONS: Health care workers suffer more from occupational ACD, especially of the hands, than do NHCWs, including to allergens not present on available standard allergen series.

RECONSTRUCTION OF THE HUMAN HIPPOCAMPUS IN 3D FROM HISTOLOGY AND HIGH-RESOLUTION EX-VIVO MRI.

In this paper, we present methods for the reconstruction of 3D histological volumes of the human hippocampal formation from histology slices. Inter-slice alignment is guided by a graph-theoretic approach that minimizes the impact of badly distorted slices. The reconstruction is refined by iterative affine and deformable co-registration with a high-resolution MRI of the postmortem tissue sample. We present an evaluation of reconstruction accuracy that is based on measures of similarity between boundaries drawn on both histology and MRI. Our methodology is currently being applied to an MRI atlas of the human hippocampal formation, in which atlas anatomical labels are derived from segmentation of reconstructed histology.