Abstract

ABSTRACTIn vivo lung micro-computed tomography (micro-CT) is being increasingly embraced in pulmonary research because it provides longitudinal information on dynamic disease processes in a field in which ex vivo assessment of experimental disease models is still the gold standard. To optimize the quantitative monitoring of progression and therapy of lung diseases, we evaluated longitudinal changes in four different micro-CT-derived biomarkers [aerated lung volume, lung tissue (including lesions) volume, total lung volume and mean lung density], describing normal development, lung infections, inflammation, fibrosis and therapy. Free-breathing mice underwent micro-CT before and repeatedly after induction of lung disease (bleomycin-induced fibrosis, invasive pulmonary aspergillosis, pulmonary cryptococcosis) and therapy (imatinib). The four lung biomarkers were quantified. After the last time point, we performed pulmonary function tests and isolated the lungs for histology. None of the biomarkers remained stable during longitudinal follow-up of adult healthy mouse lungs, implying that biomarkers should be compared with age-matched controls upon intervention. Early inflammation and progressive fibrosis led to a substantial increase in total lung volume, which affects the interpretation of aerated lung volume, tissue volume and mean lung density measures. Upon treatment of fibrotic lung disease, the improvement in aerated lung volume and function was not accompanied by a normalization of the increased total lung volume. Significantly enlarged lungs were also present in models of rapidly and slowly progressing lung infections. The data suggest that total lung volume changes could partly reflect a compensatory mechanism that occurs during disease progression in mice. Our findings underscore the importance of quantifying total lung volume in addition to aerated lung or lesion volumes to accurately document growth and potential compensatory mechanisms in mouse models of lung disease, in order to fully describe and understand dynamic processes during lung disease onset, progression and therapy. This is highly relevant for the translation of therapy evaluation results from preclinical studies to human patients.

Highlights

  • Obstructive, interstitial, infectious and malignant lung diseases remain among the most important health challenges, and novel or improved therapeutic strategies are essential for their treatment (WHO, 2014)

  • We evaluate four different established and newly proposed quantitative lung parameters [aerated lung volume, lung tissue volume, total lung volume and mean lung density], quantified from repetitive in vivo micro-CT scans of freely breathing, anesthetized mice, to evaluate how these biomarkers are affected by the normal growth of the rodent and how these changes affect the definition of control conditions during the course of a longitudinal experiment

  • To answer the question of which parameter(s) should best be used to describe meaningful changes in the lung, we investigated how total lung volume, aerated lung volume, lung tissue volume and mean lung density change over time for healthy mice, different types of lung disease models and upon their treatment

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Summary

Introduction

Obstructive, interstitial, infectious and malignant lung diseases remain among the most important health challenges, and novel or improved therapeutic strategies are essential for their treatment (WHO, 2014). Histopathological analysis of lung tissues remains the gold standard for the assessment of preclinical models. Providing excellent air-tissue contrast, micro-CT can be used to longitudinally evaluate disease progression and therapy effects in numerous models of lung diseases, including those of cancer, fibrosis, emphysema and transplantation (De Langhe et al, 2012; Li et al, 2013; Plathow et al, 2004; Wielputz et al, 2011; Wurnig et al, 2014). Lung micro-CT delivers visual and quantitative threedimensional information about the whole lung – including regional differences – with high resolution and sensitivity, yielding translational data that align well with imaging assessments routinely performed in lung disease patients. The different quantitative measures derived from a single lung scan can provide insight into lung anatomy, function and pathology

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