X-ray Luminescence Computed Tomography Research Articles

Oxygenation imaging in deep tissue with X-Ray luminescence computed tomography (XLCT).

Oxygenation concentration of tissue is an important factor in culturing stem cells and in studying the therapy response of cancer cells. The hypoxia bone marrow is the site to harbor cancer cells. Thus, direct high-resolution measurements of molecular 𝑂2 would provide powerful means of monitoring cultured stem cells and therapied cancer cells. We proposed an imaging approach to measure oxygenation concentration in deep tissues, based on the XLCT, with combined strengths of high chemical sensitivity and high spatial resolution. We have developed different biosensing films for oxygenation measurements and tested these films with X-ray luminescent experiments. We have also performed phantom experiments with multiple targets to validate the XLCT imaging system with measurements at two channels.

Superfast Scan of Focused X-Ray Luminescence Computed Tomography Imaging.

X-ray luminescence computed tomography (XLCT) is a hybrid molecular imaging modality having the high spatial resolution of x-ray imaging and high measurement sensitivity of optical imaging. Narrow x-ray beam based XLCT imaging has shown promise for high spatial resolution imaging of luminescent targets in deep tissues, but the slow acquisition speed limits its applications. In this work, we have introduced a superfast XLCT scan scheme based on the photon counter detector and a fly-scanning method. The new scan scheme is compared with three other scan methods. We have also designed and built a single-pixel x-ray detector to detect object boundaries automatically. With the detector, we can perform the parallel beam CT imaging with the XLCT imaging simultaneously. We have built the prototype XLCT imaging system to verify the proposed scan scheme. A phantom embedded with a set of four side-by-side cylindrical targets was scanned. With the proposed superfast scan scheme, we have achieved 43 seconds per transverse scan, which is 28.6 times faster than before with slightly better XLCT image quality. The superfast scan allows us to perform 3D pencil beam XLCT imaging in the future.

Super-Fast Three-Dimensional Focused X-ray Luminescence Computed Tomography with a Gated Photon Counter.

X-ray luminescence computed tomography (XLCT) is a hybrid molecular imaging modality combining the merits of both x-ray imaging (high spatial resolution) and optical imaging (high sensitivity to tracer nanophosphors). Narrow x-ray beam based XLCT imaging has shown promise for high spatial resolution imaging, but the slow acquisition speed limits its applications for in vivo imaging. We introduced a continuous scanning scheme to replace the selective excitation scheme to improve imaging speed in a previous study. Under the continuous scanning scheme, the main factor that limits the scanning speed is the data acquisition time at each interval position. In this work, we have used a gated photon counter (SR400, Stanford Research Systems) to replace the high-speed oscilloscope (MDO3104, Tektronix) to acquire measurement data. The gated photon counter only counts the photon peaks in each measurement interval, while the oscilloscope records the entire waveform including both background noise data and photon peak data. The photon counter records much less data without losing any relevant information, which makes it ideal for super-fast three-dimensional (3D) imaging. We have built prototype XLCT imaging systems of both types and performed both single target and multiple target phantom experiments in 3D. The results have verified the feasibility of our proposed photon counter based system and good 3D imaging capabilities of XLCT within a reasonable time, yielding a 14 times faster scanning time compared with the oscilloscope based XLCT system. Now, the total scan time is reduced to 27 seconds per transverse section.

A Finite Element Mesh Regrouping Strategy-Based Hybrid Light Transport Model for Enhancing the Efficiency and Accuracy of XLCT.

X-ray luminescence computed tomography (XLCT) is an emerging hybrid imaging modality in optical molecular imaging, which has attracted more attention and has been widely studied. In XLCT, the accuracy and operational efficiency of an optical transmission model play a decisive role in the rapid and accurate reconstruction of light sources. For simulation of optical transmission characteristics in XLCT, considering the limitations of the diffusion equation (DE) and the time and memory costs of simplified spherical harmonic approximation equation (SPN ), a hybrid light transport model needs to be built. DE and SPN models are first-order and higher-order approximations of RTE, respectively. Due to the discontinuity of the regions using the DE and SPN models and the inconsistencies of the system matrix dimensions constructed by the two models in the solving process, the system matrix construction of a hybrid light transmission model is a problem to be solved. We provided a new finite element mesh regrouping strategy-based hybrid light transport model for XLCT. Firstly, based on the finite element mesh regrouping strategy, two separate meshes can be obtained. Thus, for DE and SP N models, the system matrixes and source weight matrixes can be calculated separately in two respective mesh systems. Meanwhile, some parallel computation strategy can be combined with finite element mesh regrouping strategy to further save the system matrix calculation time. Then, the two system matrixes with different dimensions were coupled though repeated nodes were processed according to the hybrid boundary conditions, the two meshes were combined into a regrouping mesh, and the hybrid optical transmission model was established. In addition, the proposed method can reduce the computational memory consumption than the previously proposed hybrid light transport model achieving good balance between computational accuracy and efficiency. The forward numerical simulation results showed that the proposed method had better transmission accuracy and achieved a balance between efficiency and accuracy. The reverse simulation results showed that the proposed method had superior location accuracy, morphological recovery capability, and image contrast capability in source reconstruction. In-vivo experiments verified the practicability and effectiveness of the proposed method.

Inside Front Cover

AbstractThis study adopted a hybrid diffusion equation with third order simplified spherical harmonics model and proposed a novel Least Square QR factorization based on the Lasso algorithm to overcome the limitation of the single proton propagation model and enable fast iteration and accurate sparse reconstruction for X‐ray Luminescence Computed Tomography (XLCT). It achieves superior reconstruction performance in terms of location accuracy, spatial resolution and materializes a balance between accuracy and efficiency.Further details can be found in the article by Hongbo Guo, Hengna Zhao, Jingjing Yu, Xiaowei He, Xuelei He, and Xiaolei Song (e202100089). image

Permissible Region Extraction Strategies for XLCT: A Comparative Study

Permissible region (PR) strategy has been used successfully to alleviate the ill-posedness of the X-ray luminescence computed tomography (XLCT) reconstruction problem. In the previous researches on the permissible region strategy, it is obvious that permissible region strategy can solve the reconstruction problem efficiently. This paper aims to research the performances of four types of permissible region extraction strategies, including a permissible region manually extraction strategy, a permissible region extraction strategy with a priori information of the surface nanophosphors distribution, a permissible region extraction strategy based on the first-time reconstruction result and a precise permissible region extraction strategy. In addition, some heuristic conclusions are provided for the future study in this paper. Fast iterative shrinkage-thresholding algorithm (FISTA) is used to reconstruct in this paper. The numerical simulation experiments and physical phantom experiments are setup to evaluate and illustrate the performances of the four different types of permissible region strategies.

Radiation dose estimation for pencil beam X-ray luminescence computed tomography imaging.

Pencil beam X-ray luminescence computed tomography (XLCT) imaging provides superior spatial resolution than other imaging geometries like sheet beam and cone beam geometries. However, the pencil beam geometry suffers from long scan times, resulting in concerns overdose which discourages the use of pencil beam XLCT. The dose deposited in pencil beam XLCT imaging was investigated to estimate the dose from one angular projection scan with three different X-ray sources. The dose deposited in a typical small animal XLCT imaging was investigated. A Monte Carlo simulation platform, GATE (Geant4 Application for Tomographic Emission) was used to estimate the dose from one angular projection scan of a mouse leg model with three different X-ray sources. Dose estimations from a six angular projection scan by three different X-ray source energies were performed in GATE on a mouse trunk model composed of muscle, spine bone, and a tumor. With the Sigray source, the bone marrow of mouse leg was estimated to have a radiation dose of 44 mGy for a typical XLCT imaging with six angular projections, a scan step size of 100 micrometers, and 106 X-ray photons per linear scan. With the Sigray X-ray source and the typical XLCT scanning parameters, we estimated the dose of spine bone, muscle tissues, and tumor structures of the mouse trunk were 38.49 mGy, 15.07 mGy, and 16.87 mGy, respectively. Our results indicate that an X-ray benchtop source (like the X-ray source from Sigray Inc.) with high brilliance and quasi-monochromatic properties can reduce dose concerns with the pencil beam geometry. Findings of this work can be applicable to other imaging modalities like X-ray fluorescence computed tomography if the imaging protocol consists of the pencil beam geometry.

A robust elastic net-ℓ 1 ℓ 2 reconstruction method for x-ray luminescence computed tomography

Objective. X-ray luminescence computed tomography (XLCT) has played a crucial role in pre-clinical research and effective diagnosis of disease. However, due to the ill-posed of the XLCT inverse problem, the generalization of reconstruction methods and the selection of appropriate regularization parameters are still challenging in practical applications. In this research, an robust Elastic net-ℓ1ℓ2 reconstruction method is proposed aiming to the challenge. Approach. Firstly, our approach consists of ℓ1 and ℓ2 regularization to enhance the sparsity and suppress the smoothness. Secondly, through optimal approximation of the optimization problem, double modification of Landweber algorithm is adopted to solve the Elastic net-ℓ1ℓ2 regulazation. Thirdly, drawing on the ideal of supervised learning, multi-parameter K-fold cross validation strategy is proposed to determin the optimal parameters adaptively. Main results. To evaluate the performance of the Elastic net-ℓ1ℓ2 method, numerical simulations, phantom and in vivo experiments were conducted. In these experiments, the Elastic net-ℓ1ℓ2 method achieved the minimum reconstruction error (with smallest location error, fluorescent yield relative error, normalized root-mean-square error) and the best image reconstruction quality (with largest contrast-to-noise ratio and Dice similarity) among all methods. The results demonstrated that Elastic net-ℓ1ℓ2 can obtain superior reconstruction performance in terms of location accuracy, dual source resolution, robustness and in vivo practicability. Significance. It is believed that this study will further benefit preclinical applications with a view to provide a more reliable reference for the later researches on XLCT.

X-ray luminescence computed tomography using a hybrid proton propagation model and Lasso-LSQR algorithm.

X-ray luminescence computed tomography (XLCT) uses external X-rays for luminescence excitation, which is becoming a promising molecular imaging technique with superb penetration depth and spatial resolution. To achieve the tomographic mapping of luminescence distribution, accurate optical propagation model and suitable reconstruction method are two keys for XLCT, but not satisfied. To overcome the limitation of the single proton propagation model (e.g., DE, SP3 ), we adopted a hybrid diffusion equation with third order simplified spherical harmonics (DE-SP3 ) model for XLCT. To enable fast iteration and accurate sparse reconstruction, we also integrated in the inversion optimization, with a novel Least Square QR-factorization based on the Lasso (Lasso-LSQR) algorithm. We first simulated the light propagation in various kinds of organs under DE model and SP3 model, respectively. By comparison with the Monte Carlo, these tissues can be categorized into two types, namely DE-fitted tissues that include muscle and lung, and SP3 -fitted tissues including heart, kidney, liver, and stomach. According to the above classification results, we built a hybrid DE-SP3 model to more accurately describing light transport. Numerical simulations and in vivo experiments illustrated that hybrid DE-SP3 model achieves superior reconstruction performance in terms of location accuracy, and spatial resolution than DE, and less computational cost than SP3 . The hybrid DE-SP3 model materializes a balance between accuracy and efficiency for XLCT.

Contrast agents for x-ray luminescence computed tomography.

Imaging probes are an important consideration for any type of contrast agent-based imaging method. X-ray luminescence imaging (XLI) and x-ray luminescence computed tomography (XLCT) are both contrast agent-based imaging methods that employ x-ray excitable scintillating imaging probes that emit light to be measured for optical imaging. In this work, we compared the performance of several select imaging probes, both commercial and self-synthesized, for application in XLI/XLCT imaging. Commercially available cadmium telluride quantum dots (CdTe QDs) and europium-doped gadolinium oxysulfide (GOS:Eu) microphosphor as well as synthesized NaGdF4 nanophosphors doped with either europium or terbium were compared through their x-ray luminescence emission spectra, luminescence intensity, and also by performing XLCT scans using phantoms embedded with each of the imaging probes. Each imaging probe displayed a unique emission spectrum that was ideal for deep-tissue optical imaging. In terms of luminescence intensity, due to the large particle size, GOS:Eu had the brightest emission, followed by NaGdF4:Tb, NaGdF4:Eu, and finally the CdTe QDs. Lastly, XLCT scans showed that each imaging probe could be reconstructed with good shape and location accuracy.

Three-term conjugate gradient method for X-ray luminescence computed tomography.

X-ray luminescence computed tomography (XLCT) has become an emerging hybrid molecular imaging technology with high detection sensitivity and low cost. However, the inverse problem of reconstruction has severe ill-posed consequences. The original regularization algorithm needs to take much time to solve the problem. To reduce the cost of time, a three-term conjugate gradient (TTCG) algorithm is proposed for XLCT. Useful truncation information is added to the descent direction to find the optimal solution quickly in our proposed algorithm. Both numerical simulation experiments and real experiments are carried out to verify the performance of the algorithm. Experimental results show that the presented algorithm can effectively speed up the reconstruction process.

Focused x-ray luminescence imaging system for small animals based on a rotary gantry.

.Significance: The ability to detect and localize specific molecules through tissue is important for elucidating the molecular basis of disease and treatment. Unfortunately, most current molecular imaging tools in tissue either lack high spatial resolution (e.g., diffuse optical fluorescence tomography or positron emission tomography) or lack molecular sensitivity (e.g., micro-computed tomography, ). X-ray luminescence imaging emerged about 10 years ago to address this issue by combining the molecular sensitivity of optical probes with the high spatial resolution of x-ray imaging through tissue. In particular, x-ray luminescence computed tomography (XLCT) has been demonstrated as a powerful technique for the high-resolution imaging of deeply embedded contrast agents in three dimensions (3D) for small-animal imaging.Aim: To facilitate the translation of XLCT for small-animal imaging, we have designed and built a small-animal dedicated focused x-ray luminescence tomography (FXLT) scanner with a scanner, synthesized bright and biocompatible nanophosphors as contrast agents, and have developed a deep-learning-based reconstruction algorithm.Approach: The proposed FXLT imaging system was designed using computer-aided design software and built according to specifications. nanophosphors doped with europium or terbium were synthesized with a silica shell for increased biocompatibility and functionalized with biotin. A deep-learning-based XLCT image reconstruction was also developed based on the residual neural network as a data synthesis method of projection views from few-view data to enhance the reconstructed image quality.Results: We have built the FXLT scanner for small-animal imaging based on a rotational gantry. With all major imaging components mounted, the motor controlling the gantry can be used to rotate the system with a high accuracy. The synthesized nanophosphors displayed distinct x-ray luminescence emission, which enables multi-color imaging, and has successfully been bound to streptavidin-coated substrates. Lastly, numerical simulations using the proposed deep-learning-based reconstruction algorithm has demonstrated a clear enhancement in the reconstructed image quality.Conclusions: The designed FXLT scanner, synthesized nanophosphors, and deep-learning-based reconstruction algorithm show great potential for the high-resolution molecular imaging of small animals.

Investigation of a simple coded-aperture based multi-narrow beam x-ray luminescence computed tomography system.

The purpose of this paper is to introduce and study a multi-narrow beam X-ray Luminescence Computed Tomography (XLCT) system based on a simple coded aperture. The proposed XLCT system is studied through simulations of x rays and diffuse light propagation and the implementation of the multi-narrow beam XLCT reconstruction algorithm. The relationship between the reconstructed quality of the XLCT image and the pass-element distribution of the coded aperture mask is investigated. The coded aperture that produces the best image quality metrics for the numerical phantom is selected for the XLCT system. The effects of detection positions and the number of projection angles are also investigated for considering the scanning efficiency and system structural complexity. The results demonstrate that the proposed multi-narrow beam XLCT system is competent in resolving targets with high complexity when comparing with the coded aperture compressed sensing XLCT system based on a complicated mask. It can also offer an enhancement in scanning efficiency in comparison with the conventional multi-narrow beam XLCT system.

High-resolution x-ray luminescence computed tomography.

High-resolution imaging modalities play a critical role for advancing biomedical sciences. Recently, x-ray luminescence computed tomography (XLCT) imaging was introduced as a hybrid molecular imaging modality that combines the high-spatial resolution of x-ray imaging and molecular sensitivity of optical imaging. The narrow x-ray beam based XLCT imaging has been demonstrated to achieve high spatial resolution, even at depth, with great molecular sensitivity. Using a focused x-ray beam as the excitation source, orders of magnitude of increased sensitivity has been verified compared with previous methods with a collimated x-ray beam. In this work, we demonstrate the high-spatial resolution capabilities of our focused x-ray beam based XLCT imaging system by scanning two sets of targets, differing in the target size, embedded inside of two tissue-mimicking cylindrical phantoms. Gd2O2S:Eu3+ targets of 200 µm and 150 µm diameters were created and embedded with the same edge-to-edge distances as their diameters respectively. We scanned and reconstructed a single transverse section and successfully demonstrated that a focused x-ray beam with an average dual-cone size of 125 µm could separate the targets in both phantoms with good shape and location accuracy. We have also improved the current XLCT imaging system to make it feasible for fast three-dimensional XLCT scanning.

X-ray luminescence imaging for small animals.

X-ray luminescence imaging emerged for about a decade and combines both the high spatial resolution of x-ray imaging with the high measurement sensitivity of optical imaging, which could result in a great molecular imaging tool for small animals. So far, there are two types of x-ray luminescence computed tomography (XLCT) imaging. One uses a pencil beam x-ray for high spatial resolution at a cost of longer measurement time. The other uses cone beam x-ray to cover the whole mouse to obtain XLCT images at a very short time but with a compromised spatial resolution. Here we review these two methods in this paper and highlight the synthesized nanophosphors by different research groups. We are building a focused x-ray luminescence tomography (FXLT) imaging system, developing a machine-learning based FXLT reconstruction algorithm, and synthesizing nanophosphors with different emission wavelengths. In this paper, we will report our current progress from these three aspects. Briefly, we mount all main components, including the focused x-ray tube, the fiber detector, and the x-ray tube and x-ray detector for a microCT system, on a rotary which is a heavy-duty ring track. A microCT scan will be performed before FXLT scan. For a FXLT scan, we will have four PMTs to measure four fiber detectors at two different wavelengths simultaneously for each linear scan position. We expect the spatial resolution of the FXLT imaging will be around 100 micrometers and a limit of detection of approximately 2 μg/mL (for Gd2O2S:Eu).

X-ray-induced shortwave infrared luminescence computed tomography

X-ray luminescence computed tomography (XLCT) based on x-ray-excitable nanophosphors has been proposed as a new modality for molecular imaging. The technique has two main advantages compared to other modalities. First, autofluorescence, which is problematic for fluorescence imaging, can be substantially reduced. Second, deep-tissue in vivo imaging with high optical contrast and spatial resolution becomes achievable. Here, we extend the novel XLCT modality from the visible or infrared region to a shortwave infrared wavelength by developing an x-ray-induced shortwave infrared luminescence computed tomography (SWIR-XLCT). For this application, rare-earth nanophosphors (RENPs) were synthesized as core/shell structures consisting of a Ho-doped NaYbF4 core surrounded by a NaYF4 shell that emit light efficiently in the shortwave infrared spectral region under x-ray excitation. Through numerical simulations and phantom experiments, we showed the feasibility of SWIR-XLCT and demonstrated its potential for x-ray luminescence imaging with high spatial resolution and deep depth.

Method for improving the spatial resolution of narrow x-ray beam-based x-ray luminescence computed tomography imaging.

.X-ray luminescence computed tomography (XLCT) is an emerging hybrid imaging modality which has the potential for achieving both high sensitivity and spatial resolution simultaneously. For the narrow x-ray beam-based XLCT imaging, based on previous work, a spatial resolution of about double the x-ray beam size can be achieved using a translate/rotate scanning scheme, taking step sizes equal to the x-ray beam width. To break the current spatial resolution limit, we propose a scanning strategy achieved by reducing the scanning step size to be smaller than the x-ray beam size. We performed four sets of numerical simulations and a phantom experiment using cylindrical phantoms and have demonstrated that our proposed scanning method can greatly improve the XLCT-reconstructed image quality compared with the traditional scanning approach. In our simulations, by using a fixed x-ray beam size of 0.8 mm, we were able to successfully reconstruct six embedded targets as small as 0.5 mm in diameter and with the same edge-to-edge distances by using a scanning step as small as 0.2 mm which is a 1.6 times improvement in the spatial resolution compared with the traditional approach. Lastly, the phantom experiment further demonstrated the efficacy of our proposed method in improving the XLCT image quality, with all image quality metrics improving as the step size decreased.

Focused x-ray luminescence computed tomography: experimental studies.

X-ray luminescence computed tomography (XLCT) is an emerging hybrid molecular imaging modality and has shown great promises in overcoming the strong optical scattering in deep tissues. Though the narrow x-ray beam based XLCT imaging has been demonstrated to obtain high spatial resolution at depth, it suffers from a relatively long measurement time, hindering its practical applications. Recently, we have designed a focused x-ray beam based XLCT imaging system and have successfully performed imaging in about 7.5 seconds per section for a mouse sized object. However, its high spatial resolution capacity has not been fully implemented yet. In this paper, with a superfine focused x-ray beam we design a focused-x-ray luminescence tomography (FXLT) system for spatial resolution up to 94 μm. First, we have described our design in details. Then, we estimate the performance of the designed FXLT imaging system. Lastly, we have found that the spatial resolution of FXLT can be further improved by reducing the scan step size, which has been demonstrated by numerical simulations.

Energy-modulated x-ray fluorescence and luminescence emissions from therapeutic nanoparticles

In this study, we have investigated the possibility of modulating x-ray fluorescence (XF) and x-ray luminescence (XL) emissions from therapeutic nanoparticles (NPs) by fine-tuning the energy of incident x-rays from benchtop x-ray sources. We have carried out detailed experimental studies to determine the strength of XF and XL emissions from Y2O3:Eu3+ and LaF3:Tb3+ NPs being irradiated with x-rays from benchtop x-ray sources operated with different tube-voltages and coupled to various filter configurations. These studies demonstrated that low-energy x-rays with average energy at around 10–15 keV are the most efficient to stimulate XL emission from the Y2O3:Eu3+ and LaF3:Tb3+ NPs. The efficiency falls quickly when x-ray energies go above or below the optimum energy range. As one would expect, x-rays with average energy just above the corresponding absorption edge of the target metal would be the most efficient in inducing XF emission. In this study, we have also demonstrated that one could fine-tune the incident x-ray energy to modulate the XL and XF emissions, such as (a) selectively inducing either XL or XF emission from the same type of NPs, (b) inducing preferential XL activation of Y2O3:Eu3+ over LaF3:Eu3+ or controlling the ratio of XL activation of these two types of NPs, and (c) introducing preferential XF emission from one type of NPs over the other. As a potential application, one could optimize the energy-characteristics of the incident x-rays to facilitate multiplexed combinatorial delivery of photodynamic therapy (X-PDT), where different agents could be administrated and then selectively activated in user-defined spatial and temporal patterns to fulfill combinatorial therapeutic effects. The understanding gained through this study could prove critical for enhancing the therapeutic delivery in X-PDT, and for attaining high-quality x-ray fluorescence computed tomography (XFCT) and x-ray luminescence computed tomography (XLCT) images while minimizing the x-ray dose to the sample.

Background luminescence in x-ray luminescence computed tomography (XLCT) imaging.

X-ray luminescence computed tomography (XLCT) is an emerging hybrid imaging modality. It has been recently reported that materials such as water, tissue, or even air can generate optical photons upon x-ray irradiation, which can increase the noises in measurements of XLCT. In this study, we have investigated the x-ray luminescence from water, air, as well as tissue mimicking phantoms, including one embedded with a 0.01mg/mL GOS:Eu3+ microphosphor target. We have measured the optical emission spectrum from each sample, including samples of meat and fat, using a spectrograph. Our results indicate that there are plenty of optical photons emitted by x-ray irradiation, and a small nanophosphor concentration, as low as 5.28μM in a deep background, can provide enough contrast for XLCT imaging.