Feasibility of longitudinal in vivo monitoring of pulmonary disease progression in mouse models using laboratory-based x-ray dark-field CT.
Authors
Affiliations (6)
Affiliations (6)
- Department of Engineering Physics, Tsinghua University, Beijing, China.
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University) of Ministry of Education, Beijing, China.
- Department of General Surgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
- Department of Engineering Physics, Tsinghua University, Beijing, China. [email protected].
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University) of Ministry of Education, Beijing, China. [email protected].
Abstract
Early 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. We 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. The dark-field coefficient (µ<sub>d</sub>) showed distinct, model-specific temporal trajectories and appeared to reflect microstructural changes when attenuation (μ) remained stable. It exhibited pronounced left-right heterogeneity in the inflammatory-injury model and markedly different trajectories between two COPD mice under an identical protocol, underscoring inter-subject variability that the within-subject design captured. Overall, µ<sub>d</sub> changed earlier than μ, and findings were consistent with terminal histology. Our 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. 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.