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Published on: September 5, 2019
Imaging of articular cartilage--data matching using X-ray tomography, SEM, FIB slicing and conventional histology
Rolf Zehbe1, Heinrich Riesemeier, C James Kirkpatrick
1Technische Universität Berlin, Institute of Materials Science & Technologies, Strasse des 17. Juni 135, 10623 Berlin, Germany. rolf.zehbe@gmx.de
Abstract:
The study was aimed at demonstrating a true cellular resolution for articular cartilage using synchrotron radiation-based X-ray microcomputed tomography (SR-μCT) with a sample-specific optimization of the phase contrast. The generated tomographic data were later used to prepare a matching histological sample from the full volume specimen. We used highly coherent and monochromatic X-rays from a synchrotron source to image a tissue sample of bovine articular cartilage after deparaffinization. Phase contrast enhancement was achieved by using five different sample to detector distances for the same X-ray energy. After tomography, the sample was re-embedded into resin while retaining a dedicated sample orientation for subsequent sectioning and polishing, which was conducted until a previously defined spatial position was achieved. The protocol for resin embedding was developed to inhibit morphological changes during embedding. Giemsa staining was applied for better structural and morphological discrimination. Data from tomography and lightmicroscopy were exactly matched and finally compared to results from FIB/SEM imaging. Image detail was achieved at a single cell resolution. Image detail was achieved at a single cell resolution, which has been estimated to be 0.833μm/voxel in the tomographic data. SR-μCT with optimized phase contrast properties represents a method to investigate biological tissues in certain areas of interest, where true cellular resolution or enhanced volumetric imaging is needed. In this study, we demonstrate that this method can compete with conventional histology using light microscopy but even surpasses it due to the possibility of retrieving volumetric data.
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