Exploration of clinical applications of Talbot-Lau interferometry

Talbot-Lau interferometry (TLI) is a recent innovation, that enables x-ray phase-contrast measurements using conventional x-ray tubes and detectors. This development allows clinical implementation of phase-contrast imaging. This had been anticipated for years, given the increased sensitivity of x-ray phase to variation in soft tissue density. Carestream Health engineered a prototype system, the CH-TLI setup, and this PhD work studied the clinical potential of the system. TLI systems generate three image types: a standard x-ray transmission image (Tr), and then two new types, the differential-phase (dP) image and the dark field (DF) image. The dP and DF images are very different in terms of physical origin and possible applications. Given these differences, their clinical potential might differ strongly and therefore the potential of each of the image types is discussed separately below. First the results obtained for dP imaging are presented, followed by those for DF imaging. In the initial stages of this work, a wide ranging, experimental examination of potential applications using dP imaging revealed no advantage for dP over conventional Tr imaging. However, this conclusion was based on subjective evaluations since the different appearance of Tr and dP images prohibits direct comparisons made using quantitative measures such as contrast-to-noise ratios. Therefore, a method to benchmark dP imaging to Tr imaging was developed. Using detectability as a performance metric, virtual studies were conducted to find the threshold radiation dose at which a given object became detectable. Detectability was quantified using a four alternative forced choice paradigm. The relative dose needed for Tr and dP images to reach a given detectability level was used to quantify the relative performance. This type of observer study requires many accurately simulated images. Classical simulation frameworks for TLI in the literature based on numerical wave propagation methods are computationally expensive and are therefore rather impractical for these virtual simulation studies. This stimulated the development of a hybrid simulation platform, combining analytical equations with measured quality metrics to produce realistic Tr and dP images with levels of sharpness and noise characteristic of the CH-TLI system. General tasks, including the detection of a 4 mm spherical lesion in a uniform background were studied alongside mammography tasks, where the detectability of 5.3 mm non-spherical lesion embedded in a structured mammographic background was evaluated. These virtual studies confirmed our initial experimental findings that for the current CH-TLI system set up/dimensions, Tr imaging outperforms dP imaging for almost all of the evaluated tasks. The mammography detectability study demonstrated that while overlaying tissues complicate the detection of lesions in Tr images, their influence on the detectability in dP images is somewhat reduced. As well as giving a direct means of comparing Tr and dP imaging, the detectability method can also be used to estimate the system quality required for dP to outperform Tr imaging for a given task. By increasing the system visibility, G1-to-G2 distance or G2 frequency, the dP signal-to-noise values can be improved without affecting the Tr image. Their product, `the sensitivity-visibility product', scales with the relative performance of dP. Therefore, from the relative performance, the required senstivity-visiblity product to outperform the Tr image can be estimated in first approximation. It is only a rough estimation as the same magnification, detector and focal spot properties as the CH-TLI setup were assumed. While, in general, dP did not improve detectability in our setup, the most promising dP imaging application was found to be mammography or more specifically the detection of small lesions in structured backgrounds. The sensitivity-visibility product required to outperform Tr is estimated to be around 9.6 higher than the CH-TLI system quality. Such system quality has been published in the literature [Birnbacher2016] and is thus realistic to achieve. In contrast to the dP imaging investigation, we found that dark field imaging yielded some successful results. In accordance with the literature [Hellbach2016, Schleede2012, Yaroshenko2014], improved visualization of lung tissue was seen using DF imaging. Therefore, dark field imaging was added to two preclinical studies running at the small animal department of the KULeuven, one of which investigated pulmonary aspergillus fungi in mice. It was hypothesised that the presence of the fungi lowers the DF signal produced by the lungs. DF measurements were combined with µCT and bioluminance scans to locate and identify the infected regions. Correlation between the µCT and DF scans was found, where at the suspicious regions the dark field signal indeed showed discontinuities. However, drawing conclusions solely based on the dark field images proved difficult. The second study investigated the effect of hyperoxia and prematurity on the alveolar development of pup rabbits. Preterm rabbits and humans can suffer from arrested development of alveoli, which can lead to bronchopulmonary dysplasia. Exposure to an excess of oxygen (hyperoxia) can increase this chance. In the earlier stages of alveolar development, the alveoli are larger and it was hypothesised that this would affect the DF signal measured. Preliminary results suggest that the DF signal in the lungs of full-term animals can be clearly distinguished from the preterm animals, however differentiation of the hyperoxia cases was more difficult. We can conclude that DF imaging visualizes the aerated lung with high contrast, but differentiating different stages in the alveolar development appears difficult, thus far. It therefore appears that DF imaging shows much promise as tool for lung imaging. However, the applicability for human lung imaging is not a-priori guaranteed. Human alveoli are a factor five larger than murine alveoli and a corresponding drop in DF sensitivity is expected. On the other hand, the human thorax is thicker than those of mice and the aggregated DF contrast could well saturate, destroying the image. Before designing a setup for large animals, an estimate of the overall sensitivity of DF lung imaging in humans would prove extremely valuable. To this end, a second simulation framework was developed, this time using numerical full-wave propagation methods with the aim of generating realistic DF images rather than to predict system metrics, as is commonly done with these simulations in the literature. Software models of murine and human lung were built and the resulting DF signal simulated. The lungs were modelled as a volume of spheres with diameters matching those of the alveoli. For the murine lung, the settings of the CH-TLI system were applied, while for the human lung the design energy and pixel sizes were adapted to those of PA chest radiography. The estimated linear diffusion coefficient (and thus the corresponding DF signal) of human lung tissue was found to be 120 times smaller than that of murine lung tissue. However, due to the larger thorax thickness in humans, similar total DF contrast is achieved in projection imaging. Dark field imaging has thus great potential in human lung imaging applications and the simulation method developed here could be used to optimize TLI system dimensions for these applications. To conclude, this thesis investigated the clinical potential of the CH-TLI system and TLI imaging in general. While using the CH-TLI system the dP contrast was not sufficient to outperform Tr imaging, the DF image showed promising results for lung imaging. However, with improved system dimensions, TLI could be a powerful tool for mammography as well. In this thesis we have proposed approaches to investigate the feasibility of applications for a given system setup. In the future they can be used to help estimate the required imaging performance to outperform current clinical modalities for specific applications and support the development of new system designs on a quantitative basis.status: publishe

A hybrid simulation framework for computer simulation and modelling studies of grating-based x-ray phase-contrast images

Clinical studies performed using computer simulation are inexpensive, flexible methods that can be used to study aspects of a proposed imaging technique prior to a full clinical study. Typically, lesions are simulated into (experimental) data to assess the clinical potential of new methods or algorithms. In grating-based phase-contrast imaging (GB-PCI), full wave simulations are, however, computationally expensive due to the high periodicity of the gratings and therefore not practically applicable when large data sets are required. This work describes the development of a hybrid modelling platform that combines analytical and empirical input data for a more rapid simulation of GB-PCI images with little loss of accuracy. Instead of an explicit implementation of grating details, measured summary metrics (i.e. visibility, flux, noise power spectra, presampling modulation transfer function) are applied in order to generate transmission and differential phase images with large fields of view. Realistic transmission and differential phase images were obtained with good quantitative accuracy. The different steps of the simulation framework, as well as the methods to measure the summary metrics, are discussed in detail such that the technique can be easily customized for a given system. The platform offers a fast, accurate alternative to full wave simulations when the focus switches from grating/system design and set up to the generation of GB-PCI images for an established system.status: publishe

Preterm birth impairs postnatal lung development in the neonatal rabbit model

Background Bronchopulmonary dysplasia continues to cause important respiratory morbidity throughout life, and new therapies are needed. The common denominator of all BPD cases is preterm birth, however most preclinical research in this area focusses on the effect of hyperoxia or mechanical ventilation. In this study we investigated if and how prematurity affects lung structure and function in neonatal rabbits. Methods Pups were delivered on either day 28 or day 31. For each gestational age a group of pups was harvested immediately after birth for lung morphometry and surfactant protein B and C quantification. All other pups were hand raised and harvested on day 4 for the term pups and day 7 for the preterm pups (same corrected age) for lung morphometry, lung function testing and qPCR. A subset of pups underwent microCT and dark field imaging on day 0, 2 and 4 for terms and on day 0, 3, 5 and 7 for preterms. Results Preterm pups assessed at birth depicted a more rudimentary lung structure (larger alveoli and thicker septations) and a lower expression of surfactant proteins in comparison to term pups. MicroCT and dark field imaging revealed delayed lung aeration in preterm pups, in comparison to term pups. Preterm birth led to smaller pups, with smaller lungs with a lower alveolar surface area on day 7/day 4. Furthermore, preterm birth affected lung function with increased tissue damping, tissue elastance and resistance and decreased dynamic compliance. Expression of vascular endothelial growth factor (VEGFA) was significantly decreased in preterm pups, however in the absence of structural vascular differences. Conclusions Preterm birth affects lung structure and function at birth, but also has persistent effects on the developing lung. This supports the use of a preterm animal model, such as the preterm rabbit, for preclinical research on BPD. Future research that focuses on the identification of pathways that are involved in in-utero lung development and disrupted by pre-term birth, could lead to novel therapeutic strategies for BPD

Investigation of the refractive index decrement of 3D printing materials for manufacturing breast phantoms for phase contrast imaging

3D breast modelling for 2D and 3D breast x-ray imaging would benefit from the availability of digital and physical phantoms that reproduce accurately the complexity of the breast anatomy. While a number of groups have produced digital phantoms with increasing level of complexity, physical phantoms reproducing that software approach have been scarcely developed. One possibility is offered by 3D printing technology. This implies the assessment of the energy dependent absorption index β of 3D printing materials for absorption based imaging, as well as the assessment of the refractive index decrement, δ, of the printing material, for phase contrast imaging studies, at the energies of interest for breast imaging. In this work we set-up a procedure and performed a series of measurements (at 30, 45 and 60 keV, at the European Synchrotron Radiation Facility) for assessing the relative value of δ with respect to that of breast tissues, for twelve 3D printing materials. The method included propagation based phase contrast 2D imaging and retrieval of the estimated phase shift map, using the Paganin's algorithm. Breast glandular, adipose and skin tissues were used as reference materials of known ratio δ/β. A percentage difference Δδ was introduced to assess the suitability of the printing materials as tissue substitutes. The accuracy of the method (about 4%) was assessed based on the properties of PMMA and Nylon, acting as gold standard. Results show that, for the above photon energies, ABS is a good substitute for adipose tissue, Hybrid as a substitute of the glandular tissue and PET-G for simulating the skin. We plan to realize a breast phantom manufactured by fused deposition modelling (FDM) technology using ABS, Hybrid and PET-G as substitutes of the glandular and skin tissue and a second phantom by stereolithography (SLA) technology with the resins Flex, Tough and Black.status: publishe