Nanoparticles (NPs) are currently under intensive research for their application in tumor diagnosis and therapy. X-ray fluorescence computed tomography (XFCT) is considered a promising non-invasive imaging technique to obtain the bio-distribution of nanoparticles which include high-Z elements (e.g., gadolinium (Gd) or gold (Au)). In the present work, a set of experiments with quantitative imaging of GdNPs in mice were performed using our benchtop XFCT device. GdNPs solution which consists of 20 mg/mL NaGdF4 was injected into a nude mouse and two tumor-bearing mice. Each mouse was then irradiated by a cone-beam X-ray source produced by a conventional X-ray tube and a linear-array photon counting detector with a single pinhole collimator was placed on one side of the beamline to record the intensity and spatial information of the X-ray fluorescent photons. The maximum likelihood iterative algorithm with scatter correction and attenuation correction method was applied for quantitative reconstruction of the XFCT images. The results show that the distribution of GdNPs in each target slice (containing liver, kidney or tumor) was well reconstructed and the concentration of GdNPs deposited in each organ was quantitatively estimated, which indicates that this benchtop XFCT system provides convenient tools for obtaining accurate concentration distribution of NPs injected into animals and has potential for imaging of nanoparticles in vivo.

Current benchtop x-ray fluorescence computed tomography (XFCT) devices, which use x-ray tubes to stimulate x-ray fluorescence (XRF) photons, suffer from the contamination of Compton scatter background produced by the polychromatic incident beam. The conventional maximum-likelihood expectation-maximization (ML-EM) algorithm only considers the noise model of the XRF signal, which results in high statistical noise in reconstructed images caused by scattered photons. In this study, we proposed a scattering noise model enhanced EM-TV algorithm for benchtop XFCT image reconstruction in order to reduce the noise of scatter background and improve the sensitivity of XFCT images. The statistical noise of scattered photons was considered in the likelihood function and the EM iteration step was modified correspondingly to suppress the statistical noise caused by Compton scattered photons. The robustness of the EM iteration was improved by applying the reweighted total variation (TV) norm as the penalty function. Numerical simulations and imaging experiments of a PMMA phantom consisting of gadolinium (Gd) solutions were performed to validate the proposed algorithm. The phantom was irradiated by a cone-beam polychromatic source and the projection was recorded by a linear-array photon counting detector. For comparison, the XFCT images of Gd were reconstructed using different algorithms. Results indicate that compared with the conventional ML-EM algorithm, the proposed algorithm can obtain XFCT images with lower background noise and higher contrast, which may further improve the sensitivity and image performance of current benchtop XFCT systems.

In this paper, we propose a novel static CT system: triple planes CT (TPCT) system. Three source-detector planes in different horizontal directions are placed in the system. Line-array carbon nanotube sources with different voltages and sandwich detectors are used. Compared to conventional cone-beam CT and common inverse-geometry CT, the TPCT enables fast scanning and six-energy imaging. 1-D U-Net is applied to correct the severe scatter caused by the special geometry. The limited-view problem is solved by the hybrid reconstruction algorithm. A Monte-Carlo simulation is performed on a thorax phantom. Both the reconstruction results and decomposition results have good image quality and show the feasibility of our proposed TPCT imaging system.

Chest X-ray fluoroscopy is a commonly used medical imaging method, which has a wide range of applications in the diagnosis of lung diseases and other fields. However, due to low contrast and relatively close linear attenuation coefficients, some early small lesions are difficult to detect in time. Using the X-ray fluorescent effect of high atomic number metal elements and metal atom-containing agents that can be enriched in the lesion, the fluoroscopy signal and the fluorescent signal emitted by the metal atoms can be detected at the same time during the fluoroscopy, and the images of the two can be integrated, which can theoretically enhance the contrast between the lesion and the surrounding tissue. Based on GEANT4, this paper conducts Monte Carlo simulations to explore the feasibility and enhancement effects of three enhancement schemes: the pencil beam spot scanning method, cone-beam collimation method, and slit scanning method, and discusses the specific geometric structure and material selection.