Significance: X-ray computed tomography (CT) is one of the most commonly used diagnostic three-dimensional imaging modalities today. Conventionally, this noninvasive technique generates contrast by measuring the X-ray attenuation properties of different tissues. Considering the wave nature of X-rays, complementary contrast can be achieved by further measuring their small-angle scattering (dark-field) properties. This provides additional valuable diagnostic information on otherwise unresolved tissue microstructure. In our work, we have translated this wave-optical mechanism from the optical bench to a human-sized prototype CT system. This involved the integration of an interferometer into a clinical CT gantry and overcoming several associated challenges regarding vibrations, continuous gantry rotation, and large field of view. This development puts complementary X-ray contrast within reach for real-word medical applications.
Background: Currently, alternative medical imaging methods for the assessment of pulmonary involvement in patients infected with COVID-19 are sought that combine a higher sensitivity than conventional (attenuation-based) chest radiography with a lower radiation dose than CT imaging. Methods: Sixty patients with COVID-19-associated lung changes in a CT scan and 40 subjects without pathologic lung changes visible in the CT scan were included (in total, 100, 59 male, mean age 58 ± 14 years). All patients gave written informed consent. We employed a clinical setup for grating-based dark-field chest radiography, obtaining both a dark-field and a conventional attenuation image in one image acquisition. Attenuation images alone, dark-field images alone, and both displayed simultaneously were assessed for the presence of COVID-19-associated lung changes on a scale from 1 to 6 (1 = surely not, 6 = surely) by four blinded radiologists. Statistical analysis was performed by evaluation of the area under the receiver–operator-characteristics curves (AUC) using Obuchowski’s method with a 0.05 level of significance. Results: We show that dark-field imaging has a higher sensitivity for COVID-19-pneumonia than attenuation-based imaging and that the combination of both is superior to one imaging modality alone. Furthermore, a quantitative image analysis shows a significant reduction of dark-field signals for COVID-19-patients. Conclusions: Dark-field imaging complements and improves conventional radiography for the visualisation and detection of COVID-19-pneumonia.
Grating-based X-ray interferometry offers vast potential for imaging materials and tissues that are not easily visualised using conventional X-ray imaging. Tomographic reconstruction based on X-ray interferometric data provides not only access to the attenuation coefficient of an object, but also the refractive index and information about ultra-small-angle scattering. This improved functionality comes at the cost of longer measurement times because existing projection-based signal extraction algorithms require not only a single measurement per projection angle but several with precise grating movements in between. This obstacle hinders the adaptation of grating-based interferometry into a continuously rotating gantry. Several solutions to this problem have been proposed but all suffer from major drawbacks. We present results using an iterative reconstruction algorithm working directly on the interferograms. The suggested direct approach enables improved image quality, since interpolations and unnecessary assumptions about the object are circumvented. Our results demonstrate that it is possible to successfully reconstruct the linear attenuation coefficient, the refractive index and the linear diffusion coefficient, which is a measure related to ultra-small-angle scattering, using a single measurement per projection angle and without any grating movements. This is a milestone for future clinical implementation of grating-based phase-contrast and dark-field contrast X-ray computed tomography.
The conventional form of computed tomography using X-ray attenuation without any contrast agents is of limited use for the characterization of soft tissue in many fields of medical and biological studies. Grating-based phase-contrast computed tomography (gbPC-CT) is a promising alternative imaging method solving the low soft tissue contrast without the need of any contrast agent. While highly sensitive measurements are possible using conventional X-ray sources the spatial resolution does often not fulfill the requirements for specific imaging tasks, such as visualization of pathologies. The focus of this study is the increase in spatial resolution without loss of sensitivity. To overcome this limitation a super-resolution reconstruction based on sub-pixel shifts involving a deconvolution of the image data during each iteration is applied. In our study we achieve an effective pixel size of 28 μm with a conventional rotating anode tube and a photon-counting detector. We also demonstrate that the method can upgrade existing setups to measure tomographies with higher resolution. The results show the increase in resolution at high sensitivity and with the ability to make quantitative measurements. The combination of sparse sampling and statistical iterative reconstruction may be used to reduce the total measurement time. In conclusion, we present high-quality and high-resolution tomographic images of biological samples to demonstrate the experimental feasibility of super-resolution reconstruction.
17 November 2022 in IEEE Transactions on Medical Imaging
X-ray computed tomography (CT) is an important non-destructive imaging technique, particularly in clinical diagnostics. Even with the latest innovations like dual-energy and photon-counting CT, the image contrast is solely generated from attenuation in the tissue. An extension – fully compatible with these novelties – is dark-field CT, which retrieves an additional, so-called dark-field contrast. Unlike the attenuation channel, the dark-field channel is sensitive to tissue microstructure and porosity below the resolution of the imaging system, which allows additional insights into the health of the lung tissue or the structure of calcifications. The potential clinical value has been demonstrated in several preclinical studies and recently also in radiography patient studies. Just recently the first dark-field CT for the human body was established at the Technical University of Munich and in this paper, we discuss the performance of this prototype. We evaluate the interferometer components and the imposed challenges that the integration into the CT gantry brings by comparing the results to simulations and measurements at a laboratory setup. The influence of the clinical X-ray source on the Talbot-Lau interferometer and the impact of vibrations, which are immanent on the clinical CT gantry, are analyzed in detail to reveal their characteristic frequencies and origin. A beam hardening correction is introduced as an important step to adapt to the poly-chromatic spectrum and make quantitative dark-field imaging possible. We close with an analysis of the image resolution and the applied patient dose, and conclude that the performance is sufficient to suggest initial patient studies using the presented dark-field CT system.
X-ray phase-contrast computed tomography is an emerging imaging technology with powerful capabilities for three-dimensional (3D) visualization of weakly absorbing objects such as biological soft tissues. This technique is an extension of existing X-ray applications because conventional attenuation-contrast images are simultaneously acquired. The complementary information provided by both the contrast modalities suggests that enhanced material characterization is possible when performing combined data analysis. In this study, we describe how protein, lipid, and water concentrations in each 3D voxel can be quantified by vector decomposition. Experimental results of dairy products, porcine fat and rind, and different human soft tissue types are presented. The results demonstrate the potential of phase-contrast imaging as a new analysis tool. The 3D representations of protein, lipid, and water contents open up new opportunities in the fields of biology, medicine, and food science.