Spectral unmixing method for multi-pixel energy dispersive x-ray diffraction systems

Method of sparse-view coded-aperture x-ray diffraction tomography

Objective.X-ray diffraction (XRD) has been considered as a valuable diagnostic technology providing material specific 'finger-print' information i.e. XRD pattern to distinguish different biological tissues. XRD tomography (XRDT) further obtains spatial-resolved XRD pattern distribution, which has become a frontier biological sample inspection method. Currently, XRD computed tomography (XRD-CT) featured by the conventional CT scan mode with rotation has the best spatial resolution among various XRDT methods, but its scan process takes hours. Meanwhile, snapshot XRDT methods such as coded-aperture XRDT (CA-XRDT) aim at direct imaging without scan movements. With compressed-sensing acquisition applied, CA-XRDT significantly shortens data acquisition time. However, the snapshot acquisition results in a significant drop in spatial resolution. Hence, we need an advanced XRDT method that significantly accelerates XRD-CT acquisition and still maintains an acceptable imaging accuracy for biological sample inspection.Approach.Inspired by the high spatial resolution of XRD-CT from rotational scan and the fast compressed-sensing acquisition in snapshot CA-XRDT (SnapshotCA-XRDT), we proposed a new XRDT imaging method: sparse-view rotational CA-XRDT (RotationCA-XRDT). It takes SnapshotCA-XRDT as a preliminary depth-resolved XRDT method, and combines rotational scan to significantly improve the spatial resolution. A model-based iterative reconstruction (MBIR) method is adopted for RotationCA-XRDT. Moreover, we suggest a refined system model calculation for the RotationCA-XRDT MBIR which is a key factor to improve reconstruction image quality.Main results.We conducted our experimental validation based on Monte-Carlo simulation for a breast sample. The results show that the proposed RotationCA-XRDT method succeeded in producing good images for detecting 2 mm square carcinoma with a 15-view scan. The spatial resolution is significantly improved from current SnapshotCA-XRDT methods. With our refined system model, MBIR can obtain high quality images with little artifacts.Significance.In this work, we proposed a new high spatial resolution XRDT method combining coded-aperture compressed-sensing acquisition and sparse-view scan. The proposed RotationCA-XRDT method obtained significantly better image resolution than current SnapshotCA-XRDT methods in the field. It is of great potential for biological sample XRDT inspection. The proposed RotationCA-XRDT is the fastest millimetre-resolution XRDT method in the field which reduces the scan time from hours to minutes.

Quantifying multiple stain distributions in bioimaging by hyperspectral X-ray tomography

Chemical staining of biological specimens is commonly utilised to boost contrast in soft tissue structures, but unambiguous identification of staining location and distribution is difficult without confirmation of the elemental signature, especially for chemicals of similar density contrast. Hyperspectral X-ray computed tomography (XCT) enables the non-destructive identification, segmentation and mapping of elemental composition within a sample. With the availability of hundreds of narrow, high resolution (~ 1 keV) energy channels, the technique allows the simultaneous detection of multiple contrast agents across different tissue structures. Here we describe a hyperspectral imaging routine for distinguishing multiple chemical agents, regardless of contrast similarity. Using a set of elemental calibration phantoms, we perform a first instance of direct stain concentration measurement using spectral absorption edge markers. Applied to a set of double- and triple-stained biological specimens, the study analyses the extent of stain overlap and uptake regions for commonly used contrast markers. An improved understanding of stain concentration as a function of position, and the interaction between multiple stains, would help inform future studies on multi-staining procedures, as well as enable future exploration of heavy metal uptake across medical, agricultural and ecological fields.

Reciprocal-FDK reconstruction for x-ray diffraction computed tomography

Objective. X-ray diffraction (XRD) technology uses x-ray small-angle scattering signal for material analysis, which is highly sensitive to material inter-molecular structure. To meet the high spatial resolution requirement in applications such as medical imaging, XRD computed tomography (XRDCT) has been proposed to provide XRD intensity with improved spatial resolution from point-wise XRD scan. In XRDCT, 2D spatial tomography corresponds to a 3D reconstruction problem with the third dimension being the XRD spectrum dimension, i.e. the momentum transfer dimension. Current works in the field have studied reconstruction methods for either angular-dispersive XRDCT or energy-dispersive XRDCT for small samples. The approximations used are only suitable for regions near the XRDCT iso-center. A new XRDCT reconstruction method is needed for more general imaging applications. Approach. We derive a new FDK-type reconstruction method (Reciprocal-FDK) for XRDCT without limitation on object size. By introducing a set of reciprocal variables, the XRDCT model is transformed into a classical cone-parallel CT model, which is an extension of a circular-trajectory cone-beam CT model, after which the FDK method is applied for XRDCT reconstruction. Main results. Both analytical simulation and Monte Carlo simulation experiments are conducted to validate the XRDCT reconstruction method. The results show that when compared to existing analytical reconstruction methods, there are improvements in the proposed Reciprocal-FDK method with regard to relative structure reconstruction and XRD pattern peak reconstruction. Since cone-parallel CT does not satisfy the data completeness condition, cone-angle effect affects the reconstruction accuracy of XRDCT. The property of cone-angle effect in XRDCT is also analyzed with ablation studies. Significance. We propose a general analytical reconstruction method for XRDCT without constraint on object size. Reciprocal-FDK provides a complete derivation and theoretical support for XRDCT reconstruction by analogy to the well-studied cone-parallel CT model. In addition, the intrinsic problem with the XRDCT data model and the corresponding reconstruction error are discussed for the first time.

Simulation based evaluation of a fan beam coded aperture x-ray diffraction imaging system for biospecimen analysis

X-ray diffraction (XRD) imaging yields spatially resolved, material-specific information, which can aid medical diagnosis and inform treatment. In this work we used simulations to analyze the utility of fan beam coded aperture XRD imaging for fast, high-resolution scatter imaging of biospecimens for tissue assessment. To evaluate the proposed system's utility in a specific task, we employed a deterministic model to produce simulated data from biologically realistic breast tissue phantoms and model-based reconstruction to recover a spatial map of the XRD signatures throughout the phantoms. We found an XRD spatial resolution of ≈1 mm with a mean reconstructed spectral accuracy of 0.98 ± 0.01 for a simulated 1 × 150 mm2 fan beam operating at 160 kVp, 10 mA, and 4.5 s exposures. A classifier for cancer detection was developed utilizing cross-correlation of XRD spectra against a spectral library, with a receiver operating characteristic curve with an area under the curve value of 0.972. Our results indicated a potential diagnostic modality that could aid in tasks ranging from analysis of ex-vivo pathology biospecimens to intraoperative cancer margin assessment, motivating future work to develop an experimental system while enabling the development of improved algorithms for imaging and tissue analysis-based classification performance.