Objective:To assess the quality of low-keV monoenergetic images using deep learning image reconstruction (DLIR) algorithm combined with dual energy CT (DECT) in gastric cancer and to compare them with images from the conventional adaptive statistical iterative reconstruction (ASiR-V) algorithm.Methods:In this cross-sectional study, DECT images of 31 gastric cancer patients in the First Affiliated Hospital of Zhengzhou University were prospectively collected from September 2022 to March 2023. The 55 keV monoenergy images were reconstructed using the DLIR algorithm at low-, medium-, and high-intensity levels (DLIR-L, DLIR-M, and DLIR-H) based on arterial phase and venous phase images, respectively. The 70 keV 40% mixing coefficient (ASiR-V40%) images were reconstructed using the ASiR-V algorithm. In the objective evaluation of images, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for both lesions and muscle were calculated across four sets of reconstructed images. In the subjective evaluation of images, scores were assigned to the overall image quality, lesion visibility, and diagnostic confidence for each set of reconstructed images. Comparisons of SNR and CNR between the 4 groups were made by One-way repeated-measures ANOVA or Friedman′s test. Comparisons of scores were made by Friedman′s test. The P value of pairwise comparison was adjusted using Bonferroni correction methods. Results:In the objective evaluations, CNR lesion, SNR lesion and SNR muscle were highest on the 55 keV DLIR-H images in the arterial and venous phases, and showed a gradually increasing trend on the 70 keV ASiR-V40%, 55 keV DLIR-L, DLIR-M, DLIR-H images ( P<0.05). In subjective evaluations, compared to the 70 keV ASiR-V40% images, overall image quality scores were numerically higher for the 55 keV DLIR-H ( P>0.05), similar or slightly worse for the 55 keV DLIR-M, and significantly lower for the 55 keV DLIR-L ( P<0.05). The lesion visibility and diagnostic confidence on the 55 keV DLIR reconstruction images were higher in both arterial and venous phases than 70 keV ASiR-V40% images ( P<0.05). Conclusions:Compared to the conventional 70 keV ASiR-V40% images, the 55 keV DLIR-H images had higher lesion contrast and diagnostic confidence with lower image noise. The 55 keV DLIR-M images had comparable overall image quality to 70 keV ASiR-V40% images, but the former had higher lesion contrast and diagnostic confidence. The 55 keV DLIR-L was unable to improve image quality to the level of 70 keV ASiR-V40%.

Objective To form the expert consensus on the limb management of patients with transvenous temporary cardiac pacing,standardize the limb management of patients with transvenous temporary cardiac pacing,and reduce complications related to the limb.Methods Using evidence-based methods,the evidence in this field was searched,evaluated and summarized,and relevant recommendations and research conclusions were extracted and classified by the level of evidence quality,and then the first draft of the consensus was formed.From December 2023 to January 2024,through 2 rounds of expert consultation and 4 rounds of expert meetings,the content was adjusted and the consensus was reached.Results Totally 16 experts participated in the consultation.The positive coefficient is 100%;the authoritative coefficient is 0.847 and 0.836;the average value of each index is more than＞3.8;the coefficient of variation is less than 0.21.The Kendall's harmony coefficient of the 2 rounds of expert consultation is 0.372 and 0.314,respectively,which were statistically significant.The consensus covers the preoperative,intraoperative and postoperative on limb management of patients with transvenous temporary cardiac pacing.Totally 11 themes were involved,including the preoperative preparation,position and catheter fixation in operation,position and catheter fixation in postoperative,activity,turn and transfer,duty shift on limb,nursing care after withdrawal of the catheter,prevention of deep vein thrombosis of the operative limb and prevent infection.Conclusion The consensus is highly scientific,and it is helpful to standardize the limb management of patients with transvenous temporary cardiac pacing.