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.
Grating-based X-ray phase-contrast imaging (XPCi) systems offer higher sensitivity compared to other XPCi methods; however, realizing a high-resolution, compact, dose-efficient imaging system has been a significant challenge from technological and practical points of view until now. X-ray gratings quality and characteristics directly determine the final imaging quality, where a proper grating fabrication process can potentially minimize image artifacts and increase the system visibility. To achieve a high-resolution, compact, dose-efficient XPCi system, high-resolution detectors and high-resolution X-ray absorption gratings are a must. Moreover, an efficient image processing method is required to retrieve multimodal XPCi information—transmission, refraction (phase-contrast), and dark-field—efficiently and simultaneously. In this work, we report on a compact XPCi system that enables multimodal information retrieval through single-shot imaging with two-directional sensitivity. We first present an elegant cost-effective fabrication method to make high-resolution micropillar-based X-ray absorption gratings. A prototype 2D grating is fabricated with micropillars with 4 μm in diameter, periodicity of 16.3 μm, and aspect ratio of more than 40. This grating is then employed along with a prototype hybrid a-Se/CMOS direct conversion high-resolution X-ray detector with a pixel pitch of 8 μm in a compact system with a polychromatic microfocus source to perform X-ray phase-contrast imaging of various samples. We successfully demonstrate a single-shot XPCi and retrieve multimodal XPCi data with transmission and dark-field metrics. The final system is a promising candidate for XPCi applications as it facilitates single-shot imaging, which reduces the exposure dose on samples and yields multimodal XPCi images efficiently, all in a compact bench-top setup. The delivered X-ray dose at the sample, resolution of the system, and compactness of the reported imaging setup are potentially beneficial for ex vivo, in vivo, and computed tomography (CT) imaging applications.
Speckle-based phase-contrast imaging offers enhanced sensitivity towards weakly-attenuating materials and a simple and cheap setup, but requires accurate tracking of sample-induced speckle pattern modulations. We implemented a convolution neural network for speckle tracking in x-ray phase contrast imaging. The model was trained on simulated speckle patterns generated from a wave-optics simulation and then compared against conventional algorithms. Our solution showed comparable bias, substantially improved root mean squared error and spatial resolution, and the shortest computational time. Thus, our approach enhances the performance of speckle-based phase-contrast imaging.
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