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 formulate the standardized nursing process for ultrasound guided joint cavity puncture based on evidence-based medicine, and explore its effect.Methods:In January 2021, the standardized nursing process for ultrasound guided joint cavity puncture in orthopedic based on evidence-based medicine was established. From July 2020 to August 2021, 200 outpatients with ultrasonic guided joint cavity puncture in orthopedic were selected from the Shanghai Sixth People's Hospital Affiliated to Shanghai JiaoTong University by convenience sampling. The patients before the implementation of the standardized process were taken as the control group, and the patients after the implementation of the standardized process were taken as the observation group, with 100 cases each. We compared the operation score difference of ultrasonic guided joint cavity puncture and the operation time of joint cavity puncture among nurses, as well as the pain, swelling and puncture-associated adverse events of the two groups among patients before and after the implementation of the standardized process.Results:After the implementation of the standardized process, the scores of nurses in the 5 aspects of pre operation preparation, operation process, proficiency score, theoretical total score and total score of the joint cavity puncture operation were higher than those before the implementation, and the differences were statistically significant ( P<0.05) . The operation time of joint cavity puncture in the observation group was shorter than that in the control group, with a statistically significant difference ( P<0.05) . The swelling score, pain degree and incidence of puncture-associated adverse events in the observation group 24 hours after operation were lower than those in the control group, with statistically significant differences ( P<0.05) . Conclusions:The standardized nursing process for ultrasound guided joint cavity puncture in orthopedic based on evidence-based medicine can help nurses improve the operation theory and proficiency, shorten the operation time during the operation, reduce the swelling and pain of patients after the operation, and avoid the occurrence of puncture-associated adverse events.

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.

Objective:To compare image quality and diagnostic parameters of whole-brain CT perfusion scans under different scanning conditions and assess the utility of deep learning image reconstruction algorithm (DLIR) in reducing tube current during low-dose scans.Methods:Method A total of 105 patients with suspected acute ischemic stroke (AIS) were prospectively enrolled in the First Affiliated Hospital of Zhengzhou University from March, 2022 to March, 203 and their baseline information was recorded. All patients underwent head non-contrast CT and CT perfusion (CTP) examinations. CTP scanning was performed at 80 kV in two groups with the tube current of 150 mA (regular dose) and 100 mA (low dose), respectively. The CTP images of 150 mA group were reconstructed using filtered back-projection algorithm as well as adaptive statistical iterative reconstruction-V (ASIR-V) at 40% and 80% strength levels, which were denoted as groups A-C. The CTP images of 100 mA group were reconstructed using ASIR-V80%, DLIR-M, and DLIR-H, which were denoted as groups D-F. Clinical baseline characteristics and radiation doses were compared between the two groups under different scanning conditions. Furthermore, we assessed the subjective and objective image quality, conventional perfusion parameters, and abnormal perfusion parameters of AIS patients across the six groups of reconstructed CTP images.Results:Under the scanning conditions of 150 mA and 100 mA, 47 and 48 patients were diagnosed with AIS, respectively. There were no significant differences in the baseline characteristics between the two groups. However, there was a significant difference in the mean effective radiation dose (5.71 mSv vs. 3.80 mSv, t = 2 768.30, P < 0.001). The standard deviation (SD) of noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of gray matter (GM) and white matter (WM) were significantly different among the six groups of reconstructed images ( F = 40.58-212.13, P < 0.001). In GM, the SD values in groups C, D, and F were lower than those in other groups ( P < 0.05), and the SNR values in groups C and F were higher than those in other groups ( P < 0.05). In WM, the SD and SNR values in groups C and F were significantly different from those in other groups ( P < 0.05). Additionally, CNR values in groups C and F were higher than those in other groups ( P < 0.05). There was no significant difference in subjective scores among groups B, C, and F ( P > 0.05). Regarding perfusion parameters in the brain GM, groups D and E had lower cerebral blood volume (CBV) values compared to groups A to C ( P < 0.05), and group F had lower CBV values than group B ( P < 0.05). In the brain WM, group D had consistently lower mean transit time (MTT) values compared to the other groups ( P < 0.05). Notably, there were no significant differences in AIS lesion detection rates and relevant diagnostic parameters across the six image groups. Conclusions:Low-tube current CTP scan combined with the DLIR-H algorithm can enhance image quality without affecting perfusion parameters such as CBV and MTT, while reducing radiation dose by 30%. This algorithm can be routinely applied in brain CTP examinations.