scholarly journals 3d virtual histology of the Cerebral Cortexbased on Phase-Contrast X-ray tomography

2021 ◽  
Author(s):  
Marina Eckermann ◽  
Franziska van der Meer ◽  
Peter Cloetens ◽  
Torben Ruhwedel ◽  
Wiebke Moebius ◽  
...  
2021 ◽  
Author(s):  
Matthieu Chourrout ◽  
Margaux Roux ◽  
Carlie Boisvert ◽  
Coralie Gislard ◽  
David Legland ◽  
...  

While numerous transgenic mouse strains have been produced to model the formation of amyloid-β (Aβ) plaques in the brain, efficient methods for whole-brain 3D analysis of Aβ deposits are lacking. Moreover, standard immunohistochemistry performed on brain slices precludes any shape analysis of Aβ plaques. The present study shows how in-line (propagation-based) X-ray phase-contrast tomography (XPCT) combined with ethanol-induced brain sample dehydration enables hippocampus-wide detection and morphometric analysis of Aβ plaques. Performed in three distinct Alzheimer mouse strains, the proposed workflow identified differences in signal intensity and 3D shape parameters: 3xTg displayed a different type of Aβ plaques, with a larger volume and area, greater elongation, flatness and mean breadth, and more intense average signal than J20 and APP/PS1. As a label-free non-destructive technique, XPCT can be combined with standard immunohistochemistry. XPCT virtual histology could thus become instrumental in quantifying the 3D spreading and the morphological impact of seeding when studying prion-like properties of Aβ aggregates in animal models of Alzheimer's disease. This is Part II of a series of two articles reporting the value of in-line XPCT for virtual histology of the brain; Part I shows how in-line XPCT enables 3D myelin mapping in the whole rodent brain and in human autopsy brain tissue.


Author(s):  
Mariele Romano ◽  
Dr. Alberto Bravin ◽  
Dr. Michael D. Wright ◽  
Laurent Jacques ◽  
Dr. Arttu Miettinen ◽  
...  

2016 ◽  
Author(s):  
Mareike Töpperwien ◽  
Martin Krenkel ◽  
Felix Quade ◽  
Tim Salditt

Author(s):  
Lorenzo Massimi ◽  
Tamara Suaris ◽  
Charlotte K. Hagen ◽  
Marco Endrizzi ◽  
Peter R. T. Munro ◽  
...  

2018 ◽  
Vol 24 (S2) ◽  
pp. 24-25
Author(s):  
Mareike Töpperwien ◽  
Marina Eckermann ◽  
Anna-Lena Robisch ◽  
Christine Stadelmann ◽  
Tim Salditt

2020 ◽  
Vol 27 (6) ◽  
pp. 1707-1719 ◽  
Author(s):  
Jasper Frohn ◽  
Diana Pinkert-Leetsch ◽  
Jeannine Missbach-Güntner ◽  
Marius Reichardt ◽  
Markus Osterhoff ◽  
...  

A multiscale three-dimensional (3D) virtual histology approach is presented, based on two configurations of propagation phase-contrast X-ray tomography, which have been implemented in close proximity at the GINIX endstation at the beamline P10/PETRA III (DESY, Hamburg, Germany). This enables the 3D reconstruction of characteristic morphological features of human pancreatic normal and tumor tissue, as obtained from cancer surgery, first in the form of a large-scale overview by parallel-beam illumination, followed by a zoom into a region-of-interest based on zoom tomography using a Kirkpatrick–Baez mirror with additional waveguide optics. To this end 1 mm punch biopsies of the tissue were taken. In the parallel tomography, a volumetric throughput on the order of 0.01 mm3 s−1 was achieved, while maintaining the ability to segment isolated cells. With a continuous rotation during the scan, a total acquisition time of less than 2 min was required for a full tomographic scan. Using the combination of both setups, islets of Langerhans, a three-dimensional cluster of cells in the endocrine part of the pancreas, could be located. Cells in such an islet were segmented and visualized in 3D. Further, morphological alterations of tumorous tissue of the pancreas were characterized. To this end, the anisotropy parameter Ω, based on intensity gradients, was used in order to quantify the presence of collagen fibers within the entire biopsy specimen. This proof-of-concept experiment of the multiscale approach on human pancreatic tissue paves the way for future 3D virtual pathology.


2021 ◽  
Author(s):  
Matthieu Chourrout ◽  
Hugo Rositi ◽  
Elodie Ong ◽  
Violaine Hubert ◽  
Alexandre Paccalet ◽  
...  

AbstractWhite-matter injury leads to severe functional loss in many neurological diseases. Myelin staining on histological samples is the most common technique to investigate white-matter fibers. However, tissue processing and sectioning may affect the reliability of 3D volumetric assessments. The purpose of this study was to propose an approach that enables myelin fibers to be mapped in the whole rodent brain with microscopic resolution and without the need for strenuous staining. With this aim, we coupled in-line (propagation-based) X-ray phase-contrast tomography (XPCT) to ethanol-induced brain sample dehydration. We here provide the proof-of-concept that this approach enhances myelinated axons in rodent and human brain tissue. In addition, we demonstrated that white-matter injuries could be detected and quantified with this approach, using three animal models: ischemic stroke, premature birth and multiple sclerosis. Furthermore, in analogy to diffusion tensor imaging (DTI), we retrieved fiber directions and DTI-like diffusion metrics from our XPCT data to quantitatively characterize white-matter microstructure. Finally, we showed that this non-destructive approach was compatible with subsequent complementary brain sample analysis by conventional histology. In-line XPCT might thus become a novel gold-standard for investigating white-matter injury in the intact brain. This is Part I of a series of two articles reporting the value of in-line XPCT for virtual histology of the brain; Part II shows how in-line XPCT enables the whole-brain 3D morphometric analysis of amyloid-β (Aβ) plaques.HighlightsX-ray phase-contrast tomography (XPCT) enables myelin mapping of the whole brainXPCT detects and quantifies white-matter injuries in a range of diseasesFiber directions and anisotropy metrics can be retrieved from XPCT dataXPCT is compatible with subsequent conventional histology of brain samplesXPCT is a powerful virtual histology tool that requires minimal sample preparationGraphical Abstract


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