ArticleEuropean radiology experimental2026
Feasibility of longitudinal in vivo monitoring of pulmonary disease progression in mouse models using laboratory-based x-ray dark-field CT.
Article in European radiology experimental, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveEarly alterations in pulmonary microstructure are central to the onset and progression of chronic obstructive pulmonary disease (COPD) and acute lung injury, yet these changes remain undetectable with conventional attenuation-based computed tomography (CT). Dark-field computed tomography is sensitive to small-angle x-ray scattering generated by intact alveolar structures; however, all prior in vivo studies have been cross-sectional and pseudo-longitudinal, precluding direct observation of disease evolution within the same subject. A longitudinal, microstructure-resolved imaging approach is needed to capture true disease trajectories, reduce inter-subject variability, and support preclinical therapeutic development. MATERIALS AND
methodsWe developed a dedicated dark-field CT imaging system and integrated workflow, including dose-optimized acquisition, a mouse-specific fixation device, motion compensation, pseudo-dark-field suppression, and deep learning-based three-dimensional lung segmentation, to support repeated imaging over 12 weeks in healthy, inflammatory-injury, and COPD mouse models.
resultsThe dark-field coefficient (µ
conclusionOur results suggest the feasibility of long-term in vivo dark-field CT in preclinical lung studies. The dark-field coefficient shows promise as a potential noninvasive biomarker for early pulmonary damage, quantitative disease assessment, and therapy monitoring, supporting further investigation of longitudinal dark-field imaging in lung pathology and drug development. KEY POINTS: Question First laboratory-based longitudinal in vivo dark-field CT in mouse lung disease models over 12 weeks. Findings Dark-field signal showed more pronounced temporal variation than attenuation signal, with distinct model-specific trajectories. Relevance statement These findings establish a methodological foundation for longitudinal preclinical imaging of lung microstructure, which may support future translational research and the development of time-resolved imaging strategies for pulmonary disease.
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