Respiratory X-ray imaging enhanced by phase contrast has shown improved airway visualization in animal models. Limitations in current X-ray technology have nevertheless hindered clinical translation, leaving the potential clinical impact an open question. Here, we explore phase-contrast chest radiography in a realistic in silico framework. Specifically, we use preprocessed virtual patients to generate in silico chest radiographs by Fresnel-diffraction simulations of X-ray wave propagation. Following a reader study conducted with clinical radiologists, we predict that phase-contrast edge enhancement will have a negligible impact on improving solitary pulmonary nodule detection (6 to 20 mm). However, edge enhancement of bronchial walls visualizes small airways (<2 mm), which are invisible in conventional radiography. Our results show that phase-contrast chest radiography could play a future role in observing small-airway obstruction (e.g., relevant for asthma or early-stage chronic obstructive pulmonary disease), which cannot be directly visualized using current clinical methods, thereby motivating the experimental development needed for clinical translation. Finally, we discuss quantitative requirements on distances and X-ray source/detector specifications for clinical implementation of phase-contrast chest radiography.

Propagation-based phase-contrast X-ray imaging is an emerging technique that can improve dose efficiency in clinical imaging. In silico tools are key to understanding the fundamental imaging mechanisms and develop new applications. Here, due to the coherent nature of the phase-contrast effects, tools based on wave propagation (WP) are preferred over Monte Carlo (MC) based methods. WP simulations require very high wave-front sampling which typically limits simulations to small idealized objects. Virtual anthropomorphic voxel-based phantoms are typically provided with a resolution lower than imposed sampling requirements and, thus, cannot be directly translated for use in WP simulations. In the present paper we propose a general strategy to enable the use ofthese phantoms for WP simulations. The strategy is basedon upsampling in the 3D domain followed by projection resulting in high-resolution maps of the projected thickness for each phantom material. These maps can then be efficiently used for simulations of Fresnel diffraction to generate in silico phase-contrast X-ray images. We demonstrate the strategy on an anthropomorphic breast phantom to simulate propagation-based phase-contrast mammography using a laboratory micro-focus X-ray source.

X-ray imaging is a group of techniques using electromagnetic radiation of high energy. The ability to quickly visualize internal structures in thick opaque objects has made it an indispensable tool in research, medicine, and industry. Contrast is generally achieved by differential absorption, however, this mechanism has a strong dependence on atomic number. This results in low contrast within materials consisting of mainly elements of low atomic number, such as hydrogen, carbon and oxygen, e.g., soft organic matter. The problem with low contrast is further complicated by limitations in radiation dose. To improve contrast the phase shift of the X-rays can be measured without increasing the dose.

This Thesis concerns one method to harness this phase signal – propagation-based phase-contrast X-ray imaging (PBI). Three aspects on how to image complex objects are addressed: multi-material phase retrieval, simulations of clinical imaging, and small-animal imaging on compact systems. First, the derivation of a previously published method for multi-material phase retrieval is shown. A comparison between this method and another further reveals important differences. Secondly, a strategy to use large digital voxel-based phantoms for clinical imaging is developed. The method is demonstrated on a mammography phantom and in a reader study on clinical lung imaging. Finally, a compact X-ray system is used to demonstrate imaging of vascular canals in rat bone and high-resolution lung imaging on free-breathing mice, i.e., without mechanical ventilation.

Röntgenavbildning är en samling tekniker som använder elektromagnetisk strålning av hög energi. Förmågan att snabbt åskådliggöra inre strukturer i tjocka ogenomskinliga objekt har gjort den till ett oumbärligt redskap inom forskning, medicin och industri. Kontrast åstadkoms generellt genom skillnader i absorption av röntgenstrålningen, men denna mekanism är starkt beroende av atomnummer. Detta resulterar i låg kontrast för material som huvudsakligen består av grundämnen med lågt atomnummer som väte, kol, och syre – typiskt mjuk biologisk vävnad. Begränsningar i stråldos försvårar ytterligare problemet med låg kontrast. För att förbättra kontrasten kan röntgenstrålningens fasskift mätas utan att dosen ökas. 

Denna avhandling behandlar en metod som nyttjar denna fassignal – propagationsbaserad faskontrast (PBI). Tre aspekter av hur komplexa objekt kan avbildas behandlas: fasåterhämtning av objekt med flera material, simuleringar av klinisk avbildning och smådjursavbildning med kompakta röntgensystem. Först görs en härledning av en tidigare publicerad metod för fasåterhämtning av objekt med flera material. Viktiga skillnader visas i en jämförelse mellan denna metod och en annan. Sedan utvecklas en strategi för hur stora digitala voxelbaserade fantomer kan användas för klinisk avbildning. Den förevisas på en mammografifantom och tillämpas i en studie med radiologer om klinisk lungavbildning. Slutligen demonstreras hur kompakta röntgensystem kan användas för att avbilda nätverket av vaskulära kanaler i råttben och hur lungavbildning kan utföras med hög upplösning på möss som andas naturligt, d.v.s. utan mekanisk ventilering.

Mechanical ventilation of living animals is routinely used to achieve high-resolution pulmonary imaging, but this can damage the subject. Here, an alternative, free-breathing method enables X-ray tomography with 30 mu m resolution. Phase-contrast X-ray lung imaging has broken new ground in preclinical respiratory research by improving contrast at air/tissue interfaces. To minimize blur from respiratory motion, intubation and mechanical ventilation is commonly employed for end-inspiration gated imaging at synchrotrons and in the laboratory. Inevitably, the prospect of ventilation induced lung injury (VILI) renders mechanical ventilation a confounding factor in respiratory studies of animal models. Here we demonstrate proof-of-principle 3D imaging of the tracheobronchial tree in free-breathing mice without mechanical ventilation at radiation levels compatible with longitudinal studies. We use a prospective gating approach for end-expiration propagation-based phase-contrast X-ray imaging where the natural breathing of the mouse dictates the acquisition flow. We achieve intrapulmonary spatial resolution in the 30-mu m-range, sufficient for resolving terminal bronchioles in the 60-mu m-range distinguished from the surrounding lung parenchyma. These results should enable non-invasive longitudinal studies of native state murine airways for translational lung disease research in the laboratory.

Ancient remains from humans, animals and plants hold valuable information about our history. X-ray imaging methods are often, because of their non-destructive nature, used in the analysis of such samples. The classical x-ray imaging methods, radiography and computed tomography (CT), are based on absorption, which works well for radiodense structures like bone, but gives limited contrast for textiles and soft tissues, which exhibit high x-ray transmission. Destructive methods, such as classical histology, have historically been used for analysing ancient soft tissue but the extent to which it is used today is limited because of the fragility and value of many ancient samples. For detailed, non-destructive analysis of ancient biological samples, we instead propose x-ray phase-contrast CT, which like conventional CT gives volume data but with the possibility of better resolution through the detection of phase shift. Using laboratory x-ray sources, we here demonstrate the capabilities of phase-contrast tomography of dried biological samples. Virtual histological analysis of a mummified human hand from ancient Egypt is performed, revealing remains of adipose cells in situ, which would not be possible with classical histology. For higher resolution, a lab-based nano-CT arrangement based on a nanofocus transmission x-ray source is presented. With an x-ray emission spot of 300 nm the system shows potential for sub-micronresolution 3D imaging. For characterisation of the performance of phase-contrast imaging of dried samples a piece of wood is imaged. Finally, we present the first phase-contrast CT data from our nano-CT system, acquired of the dried head of a bee.

Propagation-based phase-contrast X-ray imaging provides high-resolution, dose-efficient images of biological materials. A crucial challenge is quantitative reconstruction, referred to as phase retrieval, of multi-material samples from single-distance, and hence incomplete, data. In this work, the two most promising methods for multi-material samples, the parallel method, and the linear method, are analytically, numerically, and experimentally compared. Both methods are designed for computed tomography, as they rely on segmentation in the tomographic reconstruction. The methods are found to result in comparable image quality, but the linear method provides faster reconstruction. In addition, as already done for the parallel method, we show that the linear method provides quantitative reconstruction for monochromatic radiation.

Respiratory X-ray imaging with phase contrast leads to improved sensitivity, as demonstrated in animal models to date. The translation to humans is limited by currently available technology, leaving the future clinical impact of the technique an open question. Here we demonstrate phase-contrast chest radiography using a proof-of-principle in silico framework. Specifically, we apply our previously developed preprocessing strategy to state-of-the-art realistic virtual human torso phantoms, then generate virtual chest radiographs through wave-propagation simulations. From a blind reader study conducted with clinical radiologists, we predict that phase contrast edge-enhancement has negligible impact for pulmonary nodule detection (6-20 mm). However, edge-enhancement of bronchial walls can visualize small airways (< 2 mm) invisible in conventional radiography. Our results predict that phase-contrast chest radiography could play a future role in diagnosis of small-airway obstruction (e.g., in asthma or chronic obstructive pulmonary disease) thereby motivating the experimental development needed for clinical translation.

Background: Phase-contrast X-ray techniques are known to improve contrast for soft-tissueimaging but has yet to reach the clinical setting due to limitations of available technology. Virtual clinical studies serve as important tools for exploring the potential impact of new imaging technologies. Recent progress in X-ray imaging simulations has enabled virtual studies of propagation-based phase-contrast in clinical imaging. Purpose: To explore if propagation-based phase-contrast chest X-ray providing edge-enhancement of features can improve radiological diagnosis, specifically studying ifdetection sensitivity of pulmonary nodules can be increased. Materials and Methods: A virtual extended cardiac-torso (XCAT) phantom was used to simulate anteroposterior chest X-ray (CXR) images from virtual patients (n = 5) each withthree different settings: 1) Conventional (120 kV tungsten spectrum, patient next to detector), 2) Control (60 keV monochromatic, patient next to detector) and 3) Phase-contrast (60 keV monochromatic, patient 12 m before detector). Simulated images were post-processed using Siemens software for clinical CXR. The images were used to conduct a blind reader study with two radiologists, where 80 image sections (8×8 cm2) containing 0, 1, 2 or 3 pulmonary nodules (n = 20 each) were extracted for each setting (n = 240 sections in total). The sections were presented randomly to the radiologists, who reviewed the sections and potential findings with a degree of malignant suspicion (1-5 scale). The perceived image quality of each section was also reviewed ( 1-5 scale).Result: The radiologists perceived the simulated CXR as realistic enough to be used in a virtual clinical study. P hase-contrast CXR showed the same sensitivity in pulmonary nodule detection as conventional CXR (0.84 and 0.83, respectively). The number of false positives were also similar. The image quality of phase-contrast CXR was perceived worse on average compared to conventional CXR. Conclusion: Virtual clinical studies can be used to explore potential future impact of clinical phase-contrast X-ray imaging. For the task of pulmonary nodule detection, radiologists had similar benefit of propagation-based phase-contrast CXR as conventional CXR. The strong enhancement of airways and pulmonary vasculature did not increase false positives