Artikel ; Online: High-throughput 3D whole-brain quantitative histopathology in rodents.
2016 Band 6, Seite(n) 20958
Abstract: Histology is the gold standard to unveil microscopic brain structures and pathological alterations in humans and animal models of disease. However, due to tedious manual interventions, quantification of histopathological markers is classically performed ... ...
| Abstract | Histology is the gold standard to unveil microscopic brain structures and pathological alterations in humans and animal models of disease. However, due to tedious manual interventions, quantification of histopathological markers is classically performed on a few tissue sections, thus restricting measurements to limited portions of the brain. Recently developed 3D microscopic imaging techniques have allowed in-depth study of neuroanatomy. However, quantitative methods are still lacking for whole-brain analysis of cellular and pathological markers. Here, we propose a ready-to-use, automated, and scalable method to thoroughly quantify histopathological markers in 3D in rodent whole brains. It relies on block-face photography, serial histology and 3D-HAPi (Three Dimensional Histology Analysis Pipeline), an open source image analysis software. We illustrate our method in studies involving mouse models of Alzheimer's disease and show that it can be broadly applied to characterize animal models of brain diseases, to evaluate therapeutic interventions, to anatomically correlate cellular and pathological markers throughout the entire brain and to validate in vivo imaging techniques. |
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| Mesh-Begriff(e) | Alzheimer Disease/diagnostic imaging ; Alzheimer Disease/pathology ; Animals ; Brain/diagnostic imaging ; Brain/pathology ; Brain/ultrastructure ; Brain Mapping ; Disease Models, Animal ; Humans ; Image Processing, Computer-Assisted ; Imaging, Three-Dimensional ; Mice ; Software |
| Sprache | Englisch |
| Erscheinungsdatum | 2016-02-15 |
| Erscheinungsland | England |
| Dokumenttyp | Journal Article ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 2615211-3 |
| ISSN | 2045-2322 ; 2045-2322 |
| ISSN (online) | 2045-2322 |
| ISSN | 2045-2322 |
| DOI | 10.1038/srep20958 |
| Datenquelle | MEDical Literature Analysis and Retrieval System OnLINE |
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