AI Insight
Researchers developed a new imaging method that combines phase-contrast X-ray CT with automated nuclear segmentation to count and analyze cells in three-dimensional tissue samples without staining or destroying them. They demonstrated the technique on human liver tissue, successfully extracting quantitative measurements of cell nuclei including size, shape, and spatial distribution throughout intact tissue volumes. The method was validated by comparing results with traditional histology staining techniques, showing consistent measurements across different tissue regions.
Why it matters
This approach overcomes major limitations of current cell counting methods, which typically require tissue destruction, chemical processing, or are restricted to surface layers. The ability to quantify cells throughout intact 3D tissue samples while preserving structural context could accelerate biomedical research, improve disease diagnosis, and enable better analysis of tissue architecture in conditions like cancer or organ pathology.
⚠️ Preprint – Noch nicht peer-reviewed
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Quantifying cells within intact three-dimensional biological specimens remains a major challenge, as standard optical and histological techniques are inherently two-dimensional, destructive, or constrained by light scattering. Optical clearing can extend imaging depth but is time-consuming, disruptive to tissue integrity, and often incompatible with downstream analyses, limiting its practical use for routine three-dimensional quantification. X-ray computed tomography can overcome these limitations, yet conventional micro-CT lacks the soft-tissue contrast required for cellular-scale analysis. Here, we introduce an integrated imaging framework in which propagation-based phase-contrast X-ray CT is combined with volumetric nuclear segmentation to enable three-dimensional cell quantification in unstained volumetric tissue. We imaged ex vivo human liver tissue and segmented nuclei throughout the reconstructed volume, extracting quantitative nuclear metrics and spatial organisation metrics, including equivalent diameter, minor-to-major axis ratio and nearest-neighbour distance. We assessed measurement consistency across two non-overlapping volumes of interest and benchmark slice-resolved nuclear metrics against haematoxylin and eosin histology. The resulting high-contrast volumetric datasets preserve tissue context, allowing quantitative measurements to be interpreted alongside surrounding architecture and microstructure. Together, these results show that laboratory phase-contrast X-ray CT supports nuclei-based volumetric cell quantification in intact unstained tissue and provides a framework for context-preserving quantitative analysis in three dimensions.