Phase contrast x-ray velocimetry of small animal lungs: optimising imaging rates

Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry

In recent years, pulmonary imaging has seen enormous progress, with the introduction, validation and implementation of new hardware and software. There is a general trend from mere visual evaluation of radiological images to quantification of abnormalities and biomarkers, and assessment of ‘non visual’ markers that contribute to establishing diagnosis or prognosis. Important catalysts to these developments in thoracic imaging include new indications (like computed tomography [CT] lung cancer screening) and the COVID‐19 pandemic. This review focuses on developments in CT, radiomics, artificial intelligence (AI) and x‐ray velocimetry for imaging of the lungs. Recent developments in CT include the potential for ultra‐low‐dose CT imaging for lung nodules, and the advent of a new generation of CT systems based on photon‐counting detector technology. Radiomics has demonstrated potential towards predictive and prognostic tasks particularly in lung cancer, previously not achievable by visual inspection by radiologists, exploiting high dimensional patterns (mostly texture related) on medical imaging data. Deep learning technology has revolutionized the field of AI and as a result, performance of AI algorithms is approaching human performance for an increasing number of specific tasks. X‐ray velocimetry integrates x‐ray (fluoroscopic) imaging with unique image processing to produce quantitative four dimensional measurement of lung tissue motion, and accurate calculations of lung ventilation.

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Quantification of muco-obstructive lung disease variability in mice via laboratory X-ray velocimetry

To effectively diagnose, monitor and treat respiratory disease clinicians should be able to accurately assess the spatial distribution of airflow across the fine structure of lung. This capability would enable any decline or improvement in health to be located and measured, allowing improved treatment options to be designed. Current lung function assessment methods have many limitations, including the inability to accurately localise the origin of global changes within the lung. However, X-ray velocimetry (XV) has recently been demonstrated to be a sophisticated and non-invasive lung function measurement tool that is able to display the full dynamics of airflow throughout the lung over the natural breathing cycle. In this study we present two developments in XV analysis. Firstly, we show the ability of laboratory-based XV to detect the patchy nature of cystic fibrosis (CF)-like disease in β-ENaC mice. Secondly, we present a technique for numerical quantification of CF-like disease in mice that can delineate between two major modes of disease symptoms. We propose this analytical model as a simple, easy-to-interpret approach, and one capable of being readily applied to large quantities of data generated in XV imaging. Together these advances show the power of XV for assessing local airflow changes. We propose that XV should be considered as a novel lung function measurement tool for lung therapeutics development in small animal models, for CF and for other muco-obstructive diseases.

Dynamic K-edge Subtraction Fluoroscopy at a Compact Inverse-Compton Synchrotron X-ray Source

X-ray fluoroscopy is a commonly applied diagnostic tool for morphological and functional evaluation of the intestine in clinical routine. Acquisition of repetitive X-ray images following oral or rectal application of iodine contrast agent visualizes the time dependent distribution of the contrast medium, and helps to detect for example leakages, tumors or functional disorders. However, movements of the intestine and air trapped inside usually prevent temporal subtraction imaging to be applied to fluoroscopy of the gastrointestinal tract. K-edge subtraction (KES) imaging would enable subtraction fluoroscopy because it allows for imaging of moving organs with little artefacts. Although KES imaging is a well established technique at synchrotron sources, this imaging method is not applied in clinical routine as it relies on brilliant synchrotron radiation. Recently emerging compact synchrotron X-ray sources could provide a quasi-monochromatic, high-flux X-ray beam and allow for the application of KES in a laboratory environment. Here, we present a filter-based dynamic KES approach at the Munich Compact Light Source (MuCLS), the first user-dedicated installation of a compact synchrotron X-ray source worldwide. Compared to conventional temporal subtraction X-ray radiography, our approach increases the contrast while reducing the generated image artefacts.

In vivo Dynamic Phase-Contrast X-ray Imaging using a Compact Light Source

We describe the first dynamic and the first in vivo X-ray imaging studies successfully performed at a laser-undulator-based compact synchrotron light source. The X-ray properties of this source enable time-sequence propagation-based X-ray phase-contrast imaging. We focus here on non-invasive imaging for respiratory treatment development and physiological understanding. In small animals, we capture the regional delivery of respiratory treatment, and two measures of respiratory health that can reveal the effectiveness of a treatment; lung motion and mucociliary clearance. The results demonstrate the ability of this set-up to perform laboratory-based dynamic imaging, specifically in small animal models, and with the possibility of longitudinal studies.

Array-source X-ray velocimetry

X-ray velocimetry (XV) has shown promise for investigations into various dynamic biological systems, including the motion of lungs and the flow of blood. Prior research in the field of XV has highlighted the need for both high spatial resolution to resolve features for tracking, and temporal resolution for accurate velocity measurement. In X-ray imaging systems, enhancement of spatial and temporal resolution requires a small focal spot size and high power output respectively, increasing anode power density requirements. In this paper, we present a multi-source XV regime whereby simultaneously illuminating a sample with multiple sources of small focal spot size, overall illumination can be increased whilst maintaining minimal source blurring without increasing power density requirements. Through a series of simulations, we demonstrate the capability for multi-source systems under various practical constraints, such as focal spot size and power density, to provide increased accuracy compared to single source systems.