Implementation of a Talbot-Lau interferometer in a clinical-like c-arm setup: A feasibility study

Analyzer-free hard x-ray interferometry

Objective. To enable practical interferometry-based phase contrast CT using standard incoherent x-ray sources, we propose an imaging system where the analyzer grating is replaced by a high-resolution detector. Since there is no need to perform multiple exposures (with the analyzer grating at different positions) at each scan angle, this scheme is compatible with continuous-rotation CT apparatus, and has the potential to reduce patient radiation dose and patient motion artifacts.Approach. Grating-based x-ray interferometry is a well-studied technique for imaging soft tissues and highly scattering objects embedded in such tissues. In addition to the traditional x-ray absorption-based image, this technique allows reconstruction of the object phase and small-angle scattering information. When using conventional incoherent, polychromatic, hard x-ray tubes as sources, three gratings are usually employed. To sufficiently resolve the pattern generated in these interferometers with contemporary x-ray detectors, an analyzer grating is used, and consequently multiple images need to be acquired for each view angle. This adds complexity to the imaging system, slows image acquisition and thus increases sensitivity to patient motion, and is not dose efficient. By simulating image formation based on wave propagation, and proposing a novel phase retrieval algorithm based on a virtual grating, we assess the potential of a analyzer-grating-free system to overcome these limitations.Main results. We demonstrate that the removal of the analyzer-grating can produce equal image contrast-to-noise ratio at reduced dose (by a factor of 5), without prolonging scan duration.Significance.By demonstrating that an analyzer-free CT system, in conjuction with an efficient phase retrieval algorithm, can overcome the prohibitive dose and workflow penalties associated grating-stepping, an alternative path towards realizing clinical inteferometric CT appears possible.

Deep-learning-based denoising of X-ray differential phase and dark-field images

PURPOSE

Statistical photon noise has always been a common problem in X-ray multi-contrast imaging and significantly influenced the quality of retrieved differential phase and dark-field images. We intend to develop a deep learning-based denoising algorithm to reduce the noise of retrieved X-ray differential phase and dark-field images.

METHODS

A novel deep learning based image noise suppression algorithm (named DnCNN-P) is presented. We proposed two different denoising modes: Retrieval-Denoising mode (R-D mode) and Denoising-Retrieval mode (D-R mode). While the R-D mode denoises the retrieved images, the D-R mode denoises the raw phase stepping data. The two denoising modes are evaluated under different photon counts and visibilities.

RESULTS

Experimental results show that with the algorithm DnCNN-P used, the D-R mode always exhibits a better noise reduction under diverse experimental conditions, even in the case of a low photon count and/or a low visibility. With a detected photon count of 1800 and a visibility of 0.3, compared to the differential phase images without denoising, the standard deviation is reduced by 89.1% and 16.4% in the D-R and R-D modes. Compared to the dark-field images without denoising, the standard deviation is reduced by 83.7% and 12.6% in the D-R and R-D modes, respectively.

CONCLUSIONS

The novel supervised DnCNN-P algorithm can significantly reduce the noise in retrieved X-ray differential phase and dark-field images. We believe this novel algorithm can be a promising approach to improve the quality of X-ray differential phase and dark-field images, and therefore dose efficiency in future biomedical applications.

Initial Characterization of Dark-Field CT on a Clinical Gantry

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.

Modeling Vibrations of a Tiled Talbot-Lau Interferometer on a Clinical CT

X-ray computed tomography (CT) is an invaluable imaging technique for non-invasive medical diagnosis. However, for soft tissue in the human body the difference in attenuation is inherently small. Grating-based X-ray phase-contrast is a relatively novel imaging method which detects additional interaction mechanisms between photons and matter, namely refraction and small-angle scattering, to generate additional images with different contrast. The experimental setup involves a Talbot-Lau interferometer whose susceptibility to mechanical vibrations hindered acquisition schemes suitable for clinical routine in the past. We present a processing pipeline to identify spatially and temporally variable fluctuations occurring in an interferometer installed on a continuously rotating clinical CT gantry. The correlations of the vibrations in the modular grating setup are exploited to identify a small number of relevant fluctuation modes, allowing for a sample reconstruction free of vibration artifacts.

X-ray Dark-Field Imaging for Improved Contrast in Historical Handwritten Literature

If ancient documents are too fragile to be opened, X-ray imaging can be used to recover the content non-destructively. As an extension to conventional attenuation imaging, dark-field imaging provides access to microscopic structural object information, which can be especially advantageous for materials with weak attenuation contrast, such as certain metal-free inks in paper. With cotton paper and different self-made inks based on authentic recipes, we produced test samples for attenuation and dark-field imaging at a metal-jet X-ray source. The resulting images show letters written in metal-free ink that were recovered via grating-based dark-field imaging. Without the need for synchrotron-like beam quality, these results set the ground for a mobile dark-field imaging setup that could be brought to a library for document scanning, avoiding long transport routes for valuable historic documents.

Dark-field computed tomography reaches the human scale

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.

X-ray computed tomography (CT) is one of the most commonly used three-dimensional medical imaging modalities today. It has been refined over several decades, with the most recent innovations including dual-energy and spectral photon-counting technologies. Nevertheless, it has been discovered that wave-optical contrast mechanisms—beyond the presently used X-ray attenuation—offer the potential of complementary information, particularly on otherwise unresolved tissue microstructure. One such approach is dark-field imaging, which has recently been introduced and already demonstrated significantly improved radiological benefit in small-animal models, especially for lung diseases. Until now, however, dark-field CT could not yet be translated to the human scale and has been restricted to benchtop and small-animal systems, with scan durations of several minutes or more. This is mainly because the adaption and upscaling to the mechanical complexity, speed, and size of a human CT scanner so far remained an unsolved challenge. Here, we now report the successful integration of a Talbot–Lau interferometer into a clinical CT gantry and present dark-field CT results of a human-sized anthropomorphic body phantom, reconstructed from a single rotation scan performed in 1 s. Moreover, we present our key hardware and software solutions to the previously unsolved roadblocks, which so far have kept dark-field CT from being translated from the optical bench into a rapidly rotating CT gantry, with all its associated challenges like vibrations, continuous rotation, and large field of view. This development enables clinical dark-field CT studies with human patients in the near future.

Empirical beam hardening and ring artifact correction for x-ray grating interferometry (EBHC-GI)

PURPOSE

Talbot-Lau grating interferometry enables the use of polychromatic x-ray sources, extending the range of potential applications amenable to phase contrast imaging. However, these sources introduce beam hardening effects not only from the samples but also from the gratings. As a result, grating inhomogeneities due to manufacturing imperfections can cause spectral nonuniformity artifacts when used with polychromatic sources. Consequently, the different energy dependencies of absorption, phase, and visibility contrasts impose challenges that so far have limited the achievable image quality. The purpose of this work was to develop and validate a correction strategy for grating-based x-ray imaging that accounts for beam hardening generated from both the imaged object and the gratings.

METHODS

The proposed two-variable polynomial expansion strategy was inspired by work performed to address beam hardening from a primary modulator. To account for the multicontrast nature of grating interferometry, this approach was extended to each contrast to obtain three sets of correction coefficients, which were determined empirically from a calibration scan. The method's feasibility was demonstrated using a tabletop Talbot-Lau grating interferometer micro-computed tomography (CT) system using CT acquisitions of a water sample and a silicon sample, representing low and high atomic number materials. Spectral artifacts such as cupping and ring artifacts were quantified using mean squared error (MSE) from the beam-hardening-free target image and standard deviation within a reconstructed image of the sample. Finally, the model developed using the water sample was applied to a fixated murine lung sample to demonstrate robustness for similar materials.

RESULTS

The water sample's absorption CT image was most impacted by spectral artifacts, but following correction to decrease ring artifacts, an 80% reduction in MSE and 57% reduction in standard deviation was observed. The silicon sample created severe artifacts in all contrasts, but following correction, MSE was reduced by 94% in absorption, 96% in phase, and 90% in visibility images. These improvements were due to the removal of ring artifacts for all contrasts and reduced cupping in absorption and phase images and reduced capping in visibility images. When the water calibration coefficients were applied to the lung sample, ring artifacts most prominent in the absorption contrast were eliminated.

CONCLUSIONS

The described method, which was developed to remove artifacts in absorption, phase, and normalized visibility micro-CT images due to beam hardening in the system gratings and imaged object, reduced the MSE by up to 96%. The method depends on calibrations that can be performed on any system and does not require detailed knowledge of the x-ray spectrum, detector energy response, grating attenuation properties and imperfections, or the geometry and composition of the imaged object.

Discrimination analysis of breast calcifications using x-ray dark-field radiography

BACKGROUND

X-ray dark-field radiography could enhance mammography by providing more information on imaged tissue and microcalcifications. The dark field signal is a measure of small angle scattering and can thus provide additional information on the imaged materials. This information can be useful for material distinction of calcifications and the diagnosis of breast cancer by classifying benign and malign association of these calcifications.

METHODS

For this study, institutional review board approval was obtained. We present the evaluation of images acquired with interferometric grating-based x-ray imaging of 323 microcalcifications (166 malign and 157 benign associated) in freshly dissected breast tissue and compare the results to the information extracted in follow-up pathological evaluation. The number of imaged calcifications is sufficiently higher than in similar previous studies. Fourteen calcification properties were extracted from the digital images and used as predictors in three different models common in discrimination analysis namely a simple threshold model, a naive Bayes model and a linear regression model, which classify the calcifications as associated with a benign or suspicious finding. Three of these fourteen predictors have been newly defined in this work and are independent from the tissue background surrounding the microcalcifications. Using these predictors no background correction is needed, as in previous works in this field. The new predictors are the length of the first and second principle component of the absorption and dark-field data, as well as the angle between the first principle component and the dark-field axis. We called these predictors data length, data width, and data orientation.

RESULTS

In fourfold cross-validation malignancy of the imaged tissue was predicted. Models that take only classical absorption predictors into account reached a sensitivity of 53.3% at a specificity of 81.1%. For a combination of predictors that also include dark field information, a sensitivity of 63.2% and specificity of 80.8% were obtained. The included dark field information consisted of the newly introduced parameters, data orientation and data width.

CONCLUSIONS

While remaining at a similar specificity, the sensitivity, with which a trained model was able to distinguish malign from benign associated calcifications, was increased by 10% on including dark-field information. This suggests grating-based x-ray imaging as a promising clinical imaging method in the field of mammography.

Contrast-to-noise ratios and thickness-normalized, ventilation-dependent signal levels in dark-field and conventional in vivo thorax radiographs of two pigs

Lung tissue causes significant small-angle X-ray scattering, which can be visualized with grating-based X-ray dark-field imaging. Structural lung diseases alter alveolar microstructure, which often causes a dark-field signal decrease. The imaging method provides benefits for diagnosis of such diseases in small-animal models, and was successfully used on porcine and human lungs in a fringe-scanning setup. Micro- and macroscopic changes occur in the lung during breathing, but their individual effects on the dark-field signal are unknown. However, this information is important for quantitative medical evaluation of dark-field thorax radiographs. To estimate the effect of these changes on the dark-field signal during a clinical examination, we acquired in vivo dark-field chest radiographs of two pigs at three ventilation pressures. Pigs were used due to the high degree of similarity between porcine and human lungs. To analyze lung expansion separately, we acquired CT scans of both pigs at comparable posture and ventilation pressures. Segmentation, masking, and forward-projection of the CT datasets yielded maps of lung thickness and logarithmic lung attenuation signal in registration with the dark-field radiographs. Upon correlating this data, we discovered approximately linear relationships between the logarithmic dark-field signal and both projected quantities for all scans. Increasing ventilation pressure strongly decreased dark-field extinction coefficients, whereas the ratio of lung dark-field and attenuation signal changed only slightly. Furthermore, we investigated ratios of dark-field and attenuation noise levels at realistic signal levels via calculations and phantom measurements. Dark-field contrast-to-noise ratio (CNR) per lung height was 5 to 10% of the same quantity in attenuation. We conclude that better CNR performance in the dark-field modality is typically due to greater anatomical noise in the conventional radiograph. Given the high physiological similarity of human and porcine lungs, the presented thickness-normalized, ventilation-dependent values allow estimation of dark-field activity of human lungs of variable size and inspiration, which facilitates the design of suitable clinical imaging setups.