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| Format: | Preprint |
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2025
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| Online-Zugang: | https://arxiv.org/abs/2509.14768 |
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| author | John, Dominik Paganin, David M. Zdora, Marie-Christine Petzold, Lisa Marie Ilg, Patrick Chen, Junan Baggio, Sara Thalhammer, Johannes B. Wirtensohn, Sami Moosmann, Julian Hammel, Jörg U. Beckmann, Felix Alloo, Samantha J. Ahlers, Jannis Busse, Madleen Herzen, Julia Morgan, Kaye S. |
| author_facet | John, Dominik Paganin, David M. Zdora, Marie-Christine Petzold, Lisa Marie Ilg, Patrick Chen, Junan Baggio, Sara Thalhammer, Johannes B. Wirtensohn, Sami Moosmann, Julian Hammel, Jörg U. Beckmann, Felix Alloo, Samantha J. Ahlers, Jannis Busse, Madleen Herzen, Julia Morgan, Kaye S. |
| contents | Virtual histology is an emerging field in biomedicine that enables three-dimensional tissue visualization using X-ray micro-computed tomography. However, the method still lacks the specificity of conventional histology, in which parts of the tissue are selectively highlighted using targeted stains. Though some first X-ray stains have been developed to address this issue, their precise location and quantity inside the tissue volume remain largely unknown. In this work, we present a novel approach to virtual histology that simultaneously captures electron number density and X-ray attenuation values through modulation-based X-ray imaging with a structured phase modulator. These complementary measurements enable decomposition of tissue volumes into basis materials, which allows the extraction of three-dimensional maps of molar contrast agent distribution alongside morphological details on the micrometer scale -- here demonstrated on murine kidneys. The concentration values are validated against the established method of K-edge subtraction imaging. We also create a direct bridge from X-ray to visible light imaging by detecting the same stain both using classical histology and our proposed X-ray approach. Our methodology opens new possibilities for biomedical research into disease progression by providing quantitative three-dimensional stain mapping across entire tissue volumes alongside high-contrast morphology, enabling deeper insights into disease mechanisms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_14768 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Quantitative Stain Mapping in X-ray Virtual Histology John, Dominik Paganin, David M. Zdora, Marie-Christine Petzold, Lisa Marie Ilg, Patrick Chen, Junan Baggio, Sara Thalhammer, Johannes B. Wirtensohn, Sami Moosmann, Julian Hammel, Jörg U. Beckmann, Felix Alloo, Samantha J. Ahlers, Jannis Busse, Madleen Herzen, Julia Morgan, Kaye S. Medical Physics Optics Virtual histology is an emerging field in biomedicine that enables three-dimensional tissue visualization using X-ray micro-computed tomography. However, the method still lacks the specificity of conventional histology, in which parts of the tissue are selectively highlighted using targeted stains. Though some first X-ray stains have been developed to address this issue, their precise location and quantity inside the tissue volume remain largely unknown. In this work, we present a novel approach to virtual histology that simultaneously captures electron number density and X-ray attenuation values through modulation-based X-ray imaging with a structured phase modulator. These complementary measurements enable decomposition of tissue volumes into basis materials, which allows the extraction of three-dimensional maps of molar contrast agent distribution alongside morphological details on the micrometer scale -- here demonstrated on murine kidneys. The concentration values are validated against the established method of K-edge subtraction imaging. We also create a direct bridge from X-ray to visible light imaging by detecting the same stain both using classical histology and our proposed X-ray approach. Our methodology opens new possibilities for biomedical research into disease progression by providing quantitative three-dimensional stain mapping across entire tissue volumes alongside high-contrast morphology, enabling deeper insights into disease mechanisms. |
| title | Quantitative Stain Mapping in X-ray Virtual Histology |
| topic | Medical Physics Optics |
| url | https://arxiv.org/abs/2509.14768 |