Comparison of dual-energy computed tomography (DECT) polychromatic and monochromatic images with and without iterative metal artifact reduction algorithm in patients with dental implants.

Background: Dual-energy computed tomography (DECT) and iterative metal artifact reduction (iMAR) algorithms are valuable tools for reducing metal artifacts. Different parameters of these technologies and their combination can achieve different performance. This study compared various polychromatic and monochromatic images obtained via DECT with and without using iMAR algorithm to reduce artifacts in patients with dental implants. Methods: This study included 30 patients with dental implants who underwent DECT for head and neck imaging. The computed tomography (CT) image sets comprised DECT polychromatic image sets [dual-energy (DE) polychromatic] that linearly blended 100 kV and tin-filtered 140 kV images using composition ratios of -1, -0.6, -0.3, 0, and 0.6, and virtual monochromatic images (DE monochromatic) at 90, 110, 130, 150, and 170 keV. These image sets were obtained with and without using iMAR, resulting in a total of 20 image sets. For subjective analysis, metal artifacts and image quality were assessed using a 5-point Likert scale. For objective analysis, CT attenuation, standard deviation (SD), contrast-to-noise ratio (CNR) and artifact index (AI) were evaluated. In addition, subgroup analysis was performed based on implant size. Results: In the subjective evaluation, iMAR + DE polychromatic (-0.3) images exhibited the lowest metal artifact scores [median (interquartile range): 2 (2-3)]. iMAR + DE monochromatic (110 keV) images demonstrated optimal image quality scores [median (interquartile range): 2 (2-3)]. In the objective evaluation, none of the images demonstrated a significant difference in the CNR, except polychromatic images with a composition of -1 and 0.6. iMAR + DE polychromatic (0) exhibited the lowest AI [median (interquartile range): 8.7 (5.9-14.5)]. There was no significant difference between the two groups with different implant sizes for the techniques combined with iMAR (all P>0.05). Conclusion: iMAR + DE polychromatic (-0.3 and 0) and iMAR + DE monochromatic (110 keV) images exhibited better image quality and substantial metal artifact reduction (MAR) compared with the other image sets. The performance of the techniques combined with iMAR was not affected by the size of the implant.

[Boundary threshold value method used in crystalline material internal defect detection by short wavelength X-ray diffraction].

There are few references about crystalline material internal defect detected by X-ray diffraction tomography using common X-ray source. Short wavelength X-ray diffractometer (SWXRD), invented by Institute of Southwest Technology Engineering, is a relatively small and inexpensive instrument compared to synchrotron radiation or neutron reactor. Boundary determination of defect affects the imaging quality and the distinguishing of defect in X-ray diffraction tomography using SWXRD. In the present paper, threshold value method of diffracted intensity is put forward to process the test data, so the boundary of defect is legible. In order to study how the factors influence the threshold value, Gauss function is used in fitting the test data. The influence of varisized image quality indicator pressed in powdered aluminum on threshold value has been studied. The result shows that 91% of the diffraction intensity of substrate can be regarded as the threshold value. The experiment of slit in aluminum alloy sheet further verified the threshold value method. It's useful in detecting the defect boundary.