Propagation-based Phase-contrast Imaging Research Articles

A hybrid simulation method towards the gamma ray phase contrast imaging for metallic material

A high efficiency simulation method for propagation-based phase-contrast imaging, called directional macro-wavefront (DMWF), is developed with the aim of simulating high-energy phase-contrast imaging. This method takes both Monte Carlo and wave optical propagation into consideration. Traditional wave-optics-based simulation methods for phase-contrast imaging encounter unacceptable computational complexity when high-energy radiation is used. In contrast, this method effectively addresses this issue by using macro-wavefront integration. Several simulation examples using typical parameters of inverse Compton scattering sources are presented to illustrate the excellent energy adaptability and efficiency of the DMWF method. This method provides a more efficient approach for phase-contrast imaging simulations, which will drive the advancement of high-energy phase-contrast imaging.

Clinical boundary conditions for propagation-based X-ray phase contrast imaging: from bio-sample models targeting to clinical applications.

Typical propagation-based X-ray phase contrast imaging (PB-PCI) experiments using polyenergetic sources are tested in very ideal conditions: low-energy spectrum (mainly characteristic X-rays), small thickness and homogeneous materials considered weakly absorbing objects, large object-to-detector distance, long exposure times and non-clinical detector. Explore PB-PCI features using boundary conditions imposed by a low power polychromatic X-ray source (X-ray spectrum without characteristic X-rays), thick and heterogenous materials and a small area imaging detector with high low-detection radiation threshold, elements commonly found in a clinical scenario. A PB-PCI setup implemented using a microfocus X-ray source and a dental imaging detector was characterized in terms of different spectra and geometric parameters on the acquired images. Test phantoms containing fibers and homogeneous materials with close attenuation characteristics and animal bone and mixed soft tissues (bio-sample models) were analyzed. Contrast to Noise Ratio (CNR), system spatial resolution and Kerma values were obtained for all images. Phase contrast images showed CNR up to 15% higher than conventional contact images. Moreover, it is better seen when large magnifications (>3) and object-to-detector distances (>13 cm) were used. The influence of the spectrum was not appreciable due to the low efficiency of the detector (thin scintillator screen) at high energies. Despite the clinical boundary condition used in this work, regarding the X-ray spectrum, thick samples, and detection system, it was possible to acquire phase contrast images of biological samples.

Framework to optimize fixed-length micro-CT systems for propagation-based phase-contrast imaging.

A laboratory X-ray imaging system with a setup that closely resembles commercial micro-CT systems with a fixed source-to-detector distance of ∼90 cm is investigated for single distance propagation-based phase-contrast imaging and computed tomography (CT). The system had a constant source-to-detector distance, and the sample positions were optimized. Initially, a PTFE wire was imaged, both in 2D and 3D, to characterize fringe contrast and spatial resolution for different X-ray source settings and source-to-sample distances. The results were compared to calculated values based on theoretical models and to simulated (wave-optics based) results, with good agreement being found. The optimization of the imaging system is discussed. CT scans of two biological samples, a tissue-engineered esophageal scaffold and a rat heart, were then acquired at the optimum parameters, demonstrating that significant image quality improvements can be obtained with widely available components placed inside fixed-length cabinets through proper optimization of propagation-based phase-contrast.

Propagation-based phase-contrast imaging of the breast: image quality and the effect of X-ray energy and radiation dose.

Propagation-based phase-contrast computed tomography (PB-CT) is a new imaging technique that exploits refractive and absorption properties of X-rays to enhance soft tissue contrast and improve image quality. This study compares image quality of PB-CT and absorption-based CT (AB-CT) for breast imaging while exploring X-ray energy and radiation dose. Thirty-nine mastectomy samples were scanned at energy levels of 28-34keV using a flat panel detector at radiation dose levels of 4mGy and 2mGy. Image quality was assessed using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), spatial resolution (res) and visibility (vis). Statistical analysis was performed to compare PB-CT images against their corresponding AB-CT images scanned at 32keV and 4mGy. The PB-CT images at 4mGy, across nearly all energy levels, demonstrated superior image quality than AB-CT images at the same dose. At some energy levels, the 2mGy PB-CT images also showed better image quality in terms of CNR/Res and vis compared to the 4mGy AB-CT images. At both investigated doses, SNR and SNR/res were found to have a statistically significant difference across all energy levels. The difference in vis was statistically significant at some energy levels. This study demonstrates superior image quality of PB-CT over AB-CT, with X-ray energy playing a crucial role in determining image quality parameters. Our findings reveal that standard dose PB-CT outperforms standard dose AB-CT across all image quality metrics. Additionally, we demonstrate that low dose PB-CT can produce superior images compared to standard dose AB-CT in terms of CNR/Res and vis.

Propagation-based phase-contrast imaging method for full-field X-ray microscopy using advanced Kirkpatrick-Baez mirrors.

We demonstrate a propagation-based phase-contrast imaging method for full-field X-ray microscopy based on advanced Kirkpatrick-Baez (AKB) mirrors to achieve high-contrast observations of weak phase objects and correct field curvature aberrations. Through a demonstration performed at SPring-8, the phase contrast of weak phase objects such as polystyrene spheres and chemically fixed cells was successfully observed with high sensitivity (∼0.03 rad). Furthermore, the field of view of the AKB mirrors was expanded to the full area of the obtained images (25 × 30 µm) by correcting the field curvature aberration using reconstructed complex wavefields.

Optimization of phase contrast imaging with a nano-focus x-ray tube.

Propagation-based phase contrast imaging with a laboratory x-ray source is a valuable tool for studying samples that show only low absorption contrast, either because of low density, elemental composition, or small feature size. If a propagation distance between sample and detector is introduced and the illumination is sufficiently coherent, the phase shift in the sample will cause additional contrast around interfaces, known as edge enhancement fringes. The strength of this effect depends not only on sample parameters and energy but also on the experimental geometry, which can be optimized accordingly. Recently, x-ray lab sources using transmission targets have become available, which provide very small source sizes in the few hundred nanometer range. This allows the use of a high-magnification geometry with a very short source-sample distance, while still achieving sufficient spatial coherence at the sample position. Moreover, the high geometrical magnification makes it possible to use detectors with a larger pixel size without reducing the image resolution. Here, we explore the influence of magnification on the edge enhancement fringes in such a geometry. We find experimentally and theoretically that the fringes become maximal at a magnification that is independent of the total source-detector distance. This optimal magnification only depends on the source size, the steepness of the sample feature, and the detector resolution. A stronger influence of the sample feature on the optimal magnification compared to low-magnification geometries is observed.

Three-dimensional contrast-transfer-function approach in phase-contrast tomography.

A new method is developed for 3D reconstruction of multimaterial objects using propagation-based x-ray phase-contrast tomography (PB-CT) with phaseretrieval via contrast-transfer-function (CTF) formalism. The approach differs from conventional PB-CT algorithms, which apply phaseretrieval to individual 2D projections. Instead, this method involves performing phaseretrieval to the CT-reconstructed volume in 3D. The CTF formalism is further extended to the cases of partially coherent illumination and strongly absorbing samples. Simulated results demonstrate that the proposed post-reconstruction CTF method provides fast and stable phaseretrieval, producing results equivalent to conventional pre-reconstruction 2D CTF phaseretrieval. Moreover, it is shown that application can be highly localized to isolated objects of interest, without a significant loss of quality, thus leading to increased computational efficiency. Combined with the extended validity of the CTF to greater propagation distances, this method provides additional advantages over approaches based on the transport-of-intensity equation.

X-Ray Dark-Field and Phase Retrieval Without Optics, via the Fokker-Planck Equation.

Emerging methods of x-ray imaging that capture phase and dark-field effects are equipping medicine with complementary sensitivity to conventional radiography. These methods are being applied over a wide range of scales, from virtual histology to clinical chest imaging, and typically require the introduction of optics such as gratings. Here, we consider extracting x-ray phase and dark-field signals from bright-field images collected using nothing more than a coherent x-ray source and a detector. Our approach is based on the Fokker-Planck equation for paraxial imaging, which is the diffusive generalization of the transport-of-intensity equation. Specifically, we utilize the Fokker-Planck equation in the context of propagation-based phase-contrast imaging, where we show that two intensity images are sufficient for successful retrieval of both the projected thickness and the dark-field signal associated with the sample. We show the results of our algorithm using both a simulated dataset and an experimental dataset. These demonstrate that the x-ray dark-field signal can be extracted from propagation-based images, and that sample thickness can be retrieved with better spatial resolution when dark-field effects are taken into account. We anticipate the proposed algorithm will be of benefit in biomedical imaging, industrial settings, and other non-invasive imaging applications.

Polychromatic neutron phase-contrast imaging of weakly absorbing samples enabled by phase retrieval.

The use of a phase-retrieval technique for propagation-based phase-contrast neutron imaging with a polychromatic beam is demonstrated. This enables imaging of samples with low absorption contrast and/or improving the signal-to-noise ratio to facilitate e.g. time-resolved measurements. A metal sample, designed to be close to a phase pure object, and a bone sample with canals partially filled with D2O were used for demonstrating the technique. These samples were imaged with a polychromatic neutron beam followed by phase retrieval. For both samples the signal-to-noise ratios were significantly improved and, in the case of the bone sample, the phase retrieval allowed for separation of bone and D2O, which is important for example for in situ flow experiments. The use of deuteration contrast avoids the use of chemical contrast enhancement and makes neutron imaging an interesting complementary method to X-ray imaging of bone.

Investigating the robustness of a deep learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions

Objective. Quantitative phase retrieval (QPR) in propagation-based x-ray phase contrast imaging of heterogeneous and structurally complicated objects is challenging under laboratory conditions due to partial spatial coherence and polychromaticity. A deep learning-based method (DLBM) provides a nonlinear approach to this problem while not being constrained by restrictive assumptions about object properties and beam coherence. The objective of this work is to assess a DLBM for its applicability under practical scenarios by evaluating its robustness and generalizability under typical experimental variations. Approach. Towards this end, an end-to-end DLBM was employed for QPR under laboratory conditions and its robustness was investigated across various system and object conditions. The robustness of the method was tested via varying propagation distances and its generalizability with respect to object structure and experimental data was also tested. Main results. Although the end-to-end DLBM was stable under the studied variations, its successful deployment was found to be affected by choices pertaining to data pre-processing, network training considerations and system modeling. Significance. To our knowledge, we demonstrated for the first time, the potential applicability of an end-to-end learning-based QPR method, trained on simulated data, to experimental propagation-based x-ray phase contrast measurements acquired under laboratory conditions with a commercial x-ray source and a conventional detector. We considered conditions of polychromaticity, partial spatial coherence, and high noise levels, typical to laboratory conditions. This work further explored the robustness of this method to practical variations in propagation distances and object structure with the goal of assessing its potential for experimental use. Such an exploration of any DLBM (irrespective of its network architecture) before practical deployment provides an understanding of its potential behavior under experimental settings.

Revisiting Neutron Propagation-Based Phase-Contrast Imaging and Tomography: Use of Phase Retrieval to Amplify the Effective Degree of Brilliance

Propagation-based neutron phase-contrast tomography is demonstrated using the ISIS pulsed spallation source. The proof-of-concept tomogram with a Paganin-type phase-retrieval filter applied exhibits an effective net boost of $23\ifmmode\pm\else\textpm\fi{}1$ in the signal-to-noise ratio as compared with an attenuation-based tomogram, implying a boost in the effective degree of neutron brilliance of over 2 orders of magnitude. This comparison is for phase retrieval versus conventional absorption with no additional collimation in place. We provide expressions for the optimal phase-contrast geometry as well as conditions for the validity of the method. The underpinning theory is derived under the assumption of the sample being composed of a single material. The effective boost in brilliance may be employed to give reduced acquisition time, or may instead be used to keep exposure times fixed while improving the measured contrast.

Reduced volume of diabetic pancreatic islets in rodents detected by synchrotron X-ray phase-contrast microtomography and deep learning network

The pancreatic islet is a highly structured micro-organ that produces insulin in response to rising blood glucose. Here we develop a label-free and automatic imaging approach to visualize the islets in situ in diabetic rodents by the synchrotron radiation X-ray phase-contrast microtomography (SRμCT) at the ID17 station of the European Synchrotron Radiation Facility. The large-size images (3.2mm×15.97mm) were acquired in the pancreas in STZ-treated mice and diabetic GK rats. Each pancreas was dissected by 3000 reconstructed images. The image datasets were further analysed by a self-developed deep learning method, AA-Net. All islets in the pancreas were segmented and visualized by the three-dimension (3D) reconstruction. After quantifying the volumes of the islets, we found that the number of larger islets (=>1500 μm3) was reduced by 2-fold (wt 1004±94 vs GK 419±122, P<0.001) in chronically developed diabetic GK rat, while in STZ-treated diabetic mouse the large islets were decreased by half (189±33 vs 90±29, P<0.001) compared to the untreated mice. Our study provides a label-free tool for detecting and quantifying pancreatic islets in situ. It implies the possibility of monitoring the state of pancreatic islets in vivo diabetes without labelling.

Precise phase retrieval for propagation-based images using discrete mathematics

The ill-posed problem of phase retrieval in optics, using one or more intensity measurements, has a multitude of applications using electromagnetic or matter waves. Many phase retrieval algorithms are computed on pixel arrays using discrete Fourier transforms due to their high computational efficiency. However, the mathematics underpinning these algorithms is typically formulated using continuous mathematics, which can result in a loss of spatial resolution in the reconstructed images. Herein we investigate how phase retrieval algorithms for propagation-based phase-contrast X-ray imaging can be rederived using discrete mathematics and result in more precise retrieval for single- and multi-material objects and for spectral image decomposition. We validate this theory through experimental measurements of spatial resolution using computed tomography (CT) reconstructions of plastic phantoms and biological tissues, using detectors with a range of imaging system point spread functions (PSFs). We demonstrate that if the PSF substantially suppresses high spatial frequencies, the potential improvement from utilising the discrete derivation is limited. However, with detectors characterised by a single pixel PSF (e.g. direct, photon-counting X-ray detectors), a significant improvement in spatial resolution can be obtained, demonstrated here at up to 17%.

Imaging Breast Microcalcifications Using Dark-Field Signal in Propagation-Based Phase-Contrast Tomography

Breast microcalcifications are an important primary radiological indicator of breast cancer. However, microcalcification classification and diagnosis may be still challenging for radiologists due to limitations of the standard 2D mammography technique, including spatial and contrast resolution. In this study, we propose an approach to improve the detection of microcalcifications in propagation-based phase-contrast X-ray computed tomography of breast tissues. Five fresh mastectomies containing microcalcifications were scanned at different X-ray energies and radiation doses using synchrotron radiation. Both bright-field (i.e. conventional phase-retrieved images) and dark-field images were extracted from the same data sets using different image processing methods. A quantitative analysis was performed in terms of visibility and contrast-to-noise ratio of microcalcifications. The results show that while the signal-to-noise and the contrast-to-noise ratios are lower, the visibility of the microcalcifications is more than two times higher in the dark-field images compared to the bright-field images. Dark-field images have also provided more accurate information about the size and shape of the microcalcifications.

Combined optical fluorescence microscopy and X-ray tomography reveals substructures in cell nuclei in 3D.

The function of a biological cell is fundamentally defined by the structural architecture of packaged DNA in the nucleus. Elucidating information about the packaged DNA is facilitated by high-resolution imaging. Here, we combine and correlate hard X-ray propagation-based phase contrast tomography and visible light confocal microscopy in three dimensions to probe DNA in whole cell nuclei of NIH-3T3 fibroblasts. In this way, unlabeled and fluorescently labeled substructures within the cell are visualized in a complementary manner. Our approach enables the quantification of the electron density, volume and optical fluorescence intensity of nuclear material. By joining all of this information, we are able to spatially localize and physically characterize both active and inactive heterochromatin, euchromatin, pericentric heterochromatin foci and nucleoli.

Direct Conversion X-ray Detector with Micron-Scale Pixel Pitch for Edge-Illumination and Propagation-Based X-ray Phase-Contrast Imaging.

In this work, we investigate the potential of employing a direct conversion integration mode X-ray detector with micron-scale pixels in two different X-ray phase-contrast imaging (XPCi) configurations, propagation-based (PB) and edge illumination (EI). Both PB-XPCi and EI-XPCi implementations are evaluated through a wave optics model—numerically simulated in MATLAB—and are compared based on their contrast, edge-enhancement, visibility, and dose efficiency characteristics. The EI-XPCi configuration, in general, demonstrates higher performance compared to PB-XPCi, considering a setup with the same X-ray source and detector. However, absorption masks quality (thickness of X-ray absorption material) and environmental vibration effect are two potential challenges for EI-XPCi employing a detector with micron-scale pixels. Simulation results confirm that the behavior of an EI-XPCi system employing a high-resolution detector is susceptible to its absorption masks thickness and misalignment. This work demonstrates the potential and feasibility of employing a high-resolution direct conversion detector for phase-contrast imaging applications where higher dose efficiency, higher contrast images, and a more compact imaging system are of interest.

Optimization of pixel size and propagation distance in X-ray phase-contrast virtual histology

X-ray phase-contrast coupled to high-spatial resolution imaging systems provides a high sensitivity for distinguishing soft tissue structures in small samples, thus being suited for X-ray virtual histology. Propagation-based phase-contrast tomography can deliver a considerable gain in signal-to-noise ratio (SNR) at small pixel sizes when it is combined to a suitable phase retrieval filter. We optimized acquisition parameters, namely the propagation distance and the pixel size, with the aim of providing adequate spatial resolution and sensitivity for virtual histology of breast surgery specimens, scanned with a phase-contrast microtomography (μCT) system employing a commercial sCMOS detector at the SYRMEP beamline of the Italian synchrotron facility Elettra (Trieste, Italy). A pathological breast tissue sample was embedded in paraffin and imaged using a polychromatic synchrotron beam at an average energy of 24 keV. The high numerical optical aperture of the imaging system enabled to adjust the pixel size to 1, 2.5 and 4 μm. The scans were acquired at five sample-to-detector distances: 4.5, 150, 250, 500 and 1000 mm. SNR was measured in an homogeneous region portion of the μCT image for each combination of pixel size and propagation distance. Experimental results were compared to a theoretical model taking into account the actual point spread function of the employed imaging system. The measured gain of SNR associated with the application of the phase-retrieval matched the predictions for large Fresnel numbers (N F > 2). For each pixel size, an optimal range of propagation distances was found. Optimal μCT reconstructions were then compared with their respective histopatological images, showing an excellent visibility of relevant structures. The optimization performed in this study will allow to select the most appropriate geometrical configurations for future acquisitions of virtual histology images of different specimens via phase-contrast microtomography.

Tomographic phase and attenuation extraction for a sample composed of unknown materials using x-ray propagation-based phase-contrast imaging.

Propagation-based phase-contrast x-ray imaging (PB-PCXI) generates image contrast by utilizing sample-imposed phase-shifts. This has proven useful when imaging weakly attenuating samples, as conventional attenuation-based imaging does not always provide adequate contrast. We present a PB-PCXI algorithm capable of extracting the x-ray attenuation β and refraction δ, components of the complex refractive index of distinct materials within an unknown sample. The method involves curve fitting an error-function-based model to a phase-retrieved interface in a PB-PCXI tomographic reconstruction, which is obtained when Paganin-type phase retrieval is applied with incorrect values of δ and β. The fit parameters can then be used to calculate true δ and β values for composite materials. This approach requires no a priori sample information, making it broadly applicable. Our PB-PCXI reconstruction is single-distance, requiring only one exposure per tomographic angle, which is important for radiosensitive samples. We apply this approach to a breast-tissue sample, recovering the refraction component δ, with 0.6-2.4% accuracy compared with theoretical values.

Single-exposure X-ray phase imaging microscopy with a grating interferometer.

The advent of hard X-ray free-electron lasers enables nanoscopic X-ray imaging with sub-picosecond temporal resolution. X-ray grating interferometry offers a phase-sensitive full-field imaging technique where the phase retrieval can be carried out from a single exposure alone. Thus, the method is attractive for imaging applications at X-ray free-electron lasers where intrinsic pulse-to-pulse fluctuations pose a major challenge. In this work, the single-exposure phase imaging capabilities of grating interferometry are characterized by an implementation at the I13-1 beamline of Diamond Light Source (Oxfordshire, UK). For comparison purposes, propagation-based phase contrast imaging was also performed at the same instrument. The characterization is carried out in terms of the quantitativeness and the contrast-to-noise ratio of the phase reconstructions as well as via the achievable spatial resolution. By using a statistical image reconstruction scheme, previous limitations of grating interferometry regarding the spatial resolution can be mitigated as well as the experimental applicability of the technique.

Performance evaluation of segmentation methods for assessing the lens of the frog Thoropa miliaris from synchrotron-based phase-contrast micro-CT images.

In the context of synchrotron microtomography using propagation-based phase-contrast imaging (XSPCT), we evaluated the performance of semiautomatic and automatic image segmentation of soft biological structures by means of Dice Similarity Coefficient (DSC) and volume quantification. We took advantage of the phase-contrast effects of XSPCT to provide enhanced object boundaries and improved visualization of the lenses of the frog Thoropa miliaris. Then, we applied semiautomatic segmentation methods 1 and 2 (Interpolation and Watershed, respectively) and method 3, an automatic segmentation algorithm using the U-Net architecture, to the reconstructed images. DSC and volume quantification of the lenses were used to quantify the performance of image segmentation methods. Comparing the lenses segmented by the three methods, the most pronounced difference in volume quantification was between methods 1 and 3: a reduction of 4.24%. Method 1, 2 and 3 obtained the global average DSC of 97.02%, 95.41% and 89.29%, respectively. Although it obtained the lowest DSC, method 3 performed the segmentation in a matter of seconds, while the semiautomatic methods had the average time to segment the lenses around 1h and 30min. Our results suggest that the performance of U-Net was impaired due to the irregularities of the ROI edges mainly in its lower and upper regions, but it still showed high accuracy (DSC=89.29%) with significantly reduced segmentation time compared to the semiautomatic methods. Besides, with the present work we have established a baseline for future assessments of Deep Neural Networks applied to XSPCT volumes.