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Register a new userFat to Muscle Ratio Measurements with Dual Energy X Ray Absorbtiometry
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Accurate measurement of the fat-to-muscle ratio in animal model is important for obesity research. An efficient way to measure the fat to muscle ratio in animal model using dual-energy absorptiometry is presented in this paper. A radioactive source exciting x-ray fluorescence from a target material is used to provide the two x-ray energies needed. The x-rays, after transmitting through the sample, are measured with an energy-sensitive Ge detector. Phantoms and specimens were measured. The results showed that the method was sensitive to the fat to muscle ratios with good linearity. A standard deviation of a few percent in the fat to muscle ratio could be observed with the x-ray dose of 0.001 mGy.
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Currently, dual-energy X-ray phase contrast imaging is usually conducted with an X-ray Talbot-Lau interferometer. However, in this system, the two adopted energy spectra have to be chosen carefully in order to match well with the phase grating. For example, the accelerating voltages of the X-ray tube are supposed to be respectively set as 40 kV and 70 kV, with other energy spectra being practically unusable for dual energy imaging. This system thus has low flexibility and maneuverability in practical applications. In this work, dual energy X-ray phase-contrast imaging is performed in a grating-based non-interferometric imaging system rather than in a Talbot-Lau interferometer. The advantage of this system is that, theoretically speaking, any two separated energy spectra can be utilized to perform dual energy X-ray phase-contrast imaging. The preliminary experimental results show that dual-energy X-ray phase contrast imaging is successfully performed when the accelerating voltages of the X-ray tube are successively set as 40 kV and 50 kV. Our work increases the flexibility and maneuverability when employing dual-energy X-ray phase-contrast imaging in medical diagnoses and nondestructive tests.
Dual-energy subtraction imaging (DES) is a method to improve the detectability of contrast agents over a lumpy background. Two images, acquired at x-ray energies above and below an absorption edge of the agent material, are logarithmically subtracted, resulting in suppression of the signal from the tissue background and a relative enhancement of the signal from the agent. Although promising, DES is still not widely used in clinical practice. One reason may be the need for two distinctly separated x-ray spectra that are still close to the absorption edge, realized through dual exposures which may introduce motion unsharpness. In this study, electronic spectrum-splitting with a silicon-strip detector is theoretically and experimentally investigated for a mammography model with iodinated contrast agent. Comparisons are made to absorption imaging and a near-ideal detector using a signal-to-noise ratio that includes both statistical and structural noise. Similar to previous studies, heavy absorption filtration was needed to narrow the spectra at the expense of a large reduction in x-ray flux. Therefore, potential improvements using a chromatic multi-prism x-ray lens (MPL) for filtering were evaluated theoretically. The MPL offers a narrow tunable spectrum, and we show that the image quality can be improved compared to conventional filtering methods.
Purpose: Dual-energy CT (DECT) has been shown to derive stopping power ratio (SPR) map with higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. However, DECT is not as widely implemented as SECT in proton radiation therapy simulation. This work presents a learning-based method to synthetize DECT images from SECT for proton radiation therapy. Methods: The proposed method uses a residual attention generative adversarial network. Residual blocks with attention gates were used to force the model focus on the difference between DECT maps and SECT images. To evaluate the accuracy of the method, we retrospectively investigated 20 head-and-neck cancer patients with both DECT and SECT scans available. The high and low energy CT images acquired from DECT acted as learning targets in the training process for SECT datasets and were evaluated against results from the proposed method using a leave-one-out cross-validation strategy. To evaluate our method in the context of a practical application, we generated SPR maps from sDECT using physics-based dual-energy stoichiometric method and compared the maps to those generated from DECT. Results: The synthesized DECT images showed an average mean absolute error around 30 Hounsfield Unit (HU) across the whole-body volume. The corresponding SPR maps generated from synthetic DECT showed an average normalized mean square error of about 1% with reduced noise level and artifacts than those from original DECT. Conclusions: The accuracy of the synthesized DECT image by our machine-learning-based method was evaluated on head and neck patient, and potential feasibility for proton treatment planning and dose calculation was shown by generating SPR map using the synthesized DECT.
Chromatic properties of the multi-prism and prism-array X-ray lenses (MPL and PAL) can potentially be utilized for efficient energy filtering and dose reduction in mammography. The line-shaped foci of the lenses are optimal for coupling to photon-counting silicon strip detectors in a scanning system. A theoretical model was developed and used to investigate the benefit of two lenses compared with an absorption-filtered reference system. The dose reduction of the MPL filter was ~15% compared with the reference system at matching scan time, and the spatial resolution was higher. The dose of the PAL-filtered system was found to be ~20% lower than for the reference system at equal scan time and resolution, and only ~20% higher than for a monochromatic beam. An investigation of some practical issues remains, including the feasibility of brilliant-enough X-ray sources and manufacturing of a polymer PAL.
In dual-energy computed tomography (DECT), low- and high- kVp data are collected often over a full-angular range (FAR) of $360^circ$. While there exists strong interest in DECT with low- and high-kVp data acquired over limited-angular ranges (LARs), there remains little investigation of image reconstruction in DECT with LAR data. Objective: We investigate image reconstruction with minimized LAR artifacts from low- and high-kVp data over LARs of $le 180^circ$ by using a directional-total-variation (DTV) algorithm. Methods: Image reconstruction from LAR data is formulated as a convex optimization problem in which data-$ell_2$ is minimized with constraints on images DTVs along orthogonal axes. We then achieve image reconstruction by applying the DTV algorithm to solve the optimization problem. We conduct numerical studies from data generated over arcs of LARs, ranging from $14^circ$ to $180^circ$, and perform visual inspection and quantitative analysis of images reconstructed. Results: Monochromatic images of interest obtained with the DTV algorithm from LAR data show substantially reduced artifacts that are observed often in images obtained with existing algorithms. The improved image quality also leads to accurate estimation of physical quantities of interest, such as effective atomic number and iodine-contrast concentration. Conclusion: Our study reveals that from LAR data of low- and high-kVp, monochromatic images can be obtained that are visually, and physical quantities can be estimated that are quantitatively, comparable to those obtained in FAR DECT. Significance: As LAR DECT is of high practical application interest, the results acquired in the work may engender insights into the design of DECT with LAR scanning configurations of practical application significance.
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