Microcomputed Tomography to Visualize and Quantify Fungal Infection Burden and Inflammation in the Mouse Lung Over Time

Pulmonary mycoses are an important threat for immunocompromised patients, and although current treatments are effective, they suffer from multiple limitations and fail to further reduce mortality. With the increasing immunocompromised population and increased antifungal resistance, fungal infection research is more relevant than ever. In preclinical respiratory fungal infection research, animal models are indispensable. However, too often researchers still rely on endpoint measurements to assess fungal burden while the dynamics of disease progression are left undiscovered. To open up this "black box", microcomputed tomography (μCT) can be implemented to longitudinally visualize lung pathology in a noninvasive way and to quantify μCT-image derived biomarkers. That way, disease onset, progression, and responsiveness to treatment can be followed up with high resolution spatially and temporally in individual mice, increasing statistical power. Here, we describe a general method for the use of low-dose high-resolution μCT to longitudinally visualize and quantify lung pathology in mouse models of respiratory fungal infections, applied to mouse models of aspergillosis and cryptococcosis.