Presentation
3 April 2024 Development of an inflatable murine lung phantom for phase-contrast and darkfield imaging
Author Affiliations +
Abstract
Chronic respiratory diseases affect 10% of the adult population and account for the third leading cause of death. As diagnosis and monitoring of such diseases are typically performed based on functional metrics, x-ray Phase-Contrast Imaging (PCI) has been recently proposed as a method capable of capturing tissue microstructure, particularly in early stages of disease. In this study, we aim to design and develop an inflatable murine lung phantom that can house an ex vivo murine lung and support inflation of the tissue sample. The phantom consists of two sections – the phantom casing and vacuum system – which are respectively responsible for encasing the tissue sample and inducing inflation. Then, a lung sample with all lobes, trachea, and aorta intact is obtained from an adult mouse and placed within the phantom casing. X-ray intensity images are taken for two lung tissue samples pre- and post-inflation and measured for width and height of each left and right lobes. Results show discernable left and right lobes of each tissue sample with an average 9 μm increase in width from pre- to post-inflation. Qualitative assessment shows appreciable increase in size of both lobes in photos and intensity images from pre- to post-inflation, with additional visual color change from red to pink and loss of intensity in x-ray images. Thus, we have introduced a murine lung phantom with thorough design, construction, and assembly methods, demonstrated its effectiveness in x-ray imaging, and confirmed its capability to inflate a complete mouse lung.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Serena Qinyun Z. Shi, Austin Zhuang, Ryan Fair, and Peter B. Noël "Development of an inflatable murine lung phantom for phase-contrast and darkfield imaging", Proc. SPIE 12930, Medical Imaging 2024: Clinical and Biomedical Imaging, 129300X (3 April 2024); https://doi.org/10.1117/12.3005456
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KEYWORDS
Lung

Biological samples

Tissues

X-ray imaging

Pulmonary disorders

X-rays

Design and modelling

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