Objective To investigate the accuracy and reproducibility of deep learning algorithms combined with asynchronous calibration quantitative computed tomography(QCT)for measuring bone mineral density(BMD),and to explore the feasibility of using low-dose scanning BMD measurement.Methods European spine phantom(ESP)was scanned with asynchronous calibration QCT and conventional synchronous calibration QCT,respectively,the accuracy and short-term reproducibility was compared.ESP were scanned with asynchronous calibration QCT,matching 120 kVp with five sets of tube currents:20,60,100,140,and 180 mA.Three levels of deep learning image reconstruction(DLIR)and hybrid model-based adaptive statistical iterative reconstruction V(40％ASIR-V)were used for reconstruction.The BMD values of three vertebrae in the ESP were measured.Furthermore,the image noise and contrast-to-noise ratio(CNR)were compared.Results The relative errors(RE)of the three vertebrae of the asynchronous calibration QCT and synchronous calibration QCT were all less than 7％.There was no statistical difference in the BMD values of the two scans at one week interval of the asynchronous calibration QCT(P＞0.05).There were no significant differences in RE among different tube currents or different reconstruction methods(P＞0.05).The image quality of deep learning-based image reconstruction of high strength(DLIR-H)at 20 mA tube current was better than that of 40％ASIR-V at 180 mA,and the radiation dose was reduced by 89％.Conclusion Asynchronous calibration QCT has high accuracy in BMD measurement,and has good repeatability.Asynchronous calibration QCT which combined with DLIR does not affect the accuracy of BMD measurement,and can significantly improve the CNR of images and reduce image noise.

Objective:To investigate the value of the virtual monoenergetic image (VMI) obtained by a new dual-layer detector spectral CT combined with metal artifact reduction algorithms(O-MAR) in reduction of different types of artifacts caused by 125I seeds implantation and in improvement of the post-operative CT image quality. Methods:This was a cross-sectional study. Thirty-five patients who underwent dual-layer detector spectral CT scanning of the chest and abdomen after 125I seeds implantation were retrospectively included at the First Affiliated Hospital of Zhengzhou University from March to September 2022. The spectral data were collected and reconstructed into conventional CT image (CI), VMI image (50-150 keV, 20 keV/level), CI+O-MAR image, and VMI+O-MAR image (50-150 keV, 20 keV/level). The artifacts′ removal effects and image quality improvement in each group were evaluated. Two slices with the strongest artifacts were selected for analysis for each patient, resulting in a total of 70 slices. Objective indicators including artifact index (AI), signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of soft tissue regions affected by artifacts were measured and calculated. Subjective indicators including the overcorrected artifacts and new artifacts, the different forms of artifacts, the diagnosis of artifacts, and the image quality were assessed. One-way analysis of variance was used for comparisons among multiple groups. Paired t test was used to compare the quantitative indicators between the combined O-MAR group and the non-O-MAR group. Kappa statistics was used to evaluate the consistency between observers. Results:In high/low-density artifacts (ROI H/L), the AI values in all groups showed decrease with increasing VMI keV. In artifact-affected tissue (ROI T), SNR of the CI/VMI (70-150 keV)+O-MAR group were significantly higher than those of the CI/VMI group ( P<0.05), CNR of the CI/VMI(50-150 keV)+O-MAR group were significantly higher than those of the CI/VMI group ( P<0.05). Both overcorrection and new artifacts mainly presented in VMI 50 keV and VMI 70 keV groups; Compared with VMI (50-70 keV) group, significantly less numbers of overcorrection and new artifacts were found in VMI (50-70 keV)+O-MAR group ( P<0.05); regarding the comparison of artifact types, with the VMI keV increasing, the number of a-type banded artifacts gradually decreased on images with high-density artifacts, reaching a minimum of 3 in the VMI 150 keV+O-MAR group; while the number of e-type artifacts with little or no artifacts increased, with the highest number of 23 in the VMI 150 keV+O-MAR group. The total number of high-density artifacts in each type decreased with increasing VMI keV. As VMI keV increased, the diagnostic and image quality scores of high-density artifacts in each group were significantly higher than those of low-density artifacts in the VMI+O-MAR group ( P<0.05). Conclusions:VMI combined with O-MAR can significantly improve the objective and subjective image quality of follow-up CT imaging after 125I seed implantation, enhancing lesion visibility and diagnostic confidence. Additionally, VMI+O-MAR showed more pronounced correction effect on high-density artifacts.