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Updated: Jan 30, 2026

Contrast Enhanced Vessel Imaging using MicroCT
Published on: January 27, 2011
Enhancing the X-ray contrast of polymeric biochromatography particles for three-dimensional imaging
A Martinez1, M Kuhn2, H Briesen2
1Technical University of Munich, Institute of Biochemical Engineering, Boltzmannstr. 15, 85748 Garching, Germany.
Abstract:
A major limitation of the three-dimensional imaging of polymeric biochromatography particle packings using X-ray computed tomography is that the particles have a low density and a high porosity, making them almost undistinguishable from the surrounding liquid phase. Additionally, the employed media are typically composed of materials with low atomic numbers, which exhibit low X-ray absorption. We report an improvement of packed column reconstruction using micro X-ray computed tomography. A simple, inexpensive, and fast method to increase the contrast factor of highly porous polymer-based chromatographic particles was developed by applying a modified pore-blocking method. This approach relies on the selective filling of the porous chromatographic particles with a hydrophilic phase while a hydrophobic phase occupies the void spaces between the particles. The hydrophilic phase contains a dissolved X-ray absorbing radiocontrast agent. No chemical modifications of the chromatographic beads or columns were necessary. The developed method can be applied in-situ in a previously packed column and can be used for media with different organic backbones. We show the applicability of this method by carrying out the first 3D-reconstruction of packed micro columns with an inner diameter of 760 μm. The micro column contained agarose- and methacrylate-based particles commonly used in preparative biochromatography with mean diameters of 40 and 65 μm, respectively. Based on the obtained high-resolution 3D-reconstructions, we exemplarily computed packing properties such as global extraparticle porosity and radial porosity profiles, and visualized the presence of void spaces using 3D image analysis.
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