ISSN 1004-4140
CN 11-3017/P
汪琴,严伟杰,袁元,等. 深度学习重建算法在上腹部能谱CT小血管显示中的研究[J]. CT理论与应用研究(中英文),xxxx,x(x): 1-7. DOI: 10.15953/j.ctta.2024.168.
引用本文: 汪琴,严伟杰,袁元,等. 深度学习重建算法在上腹部能谱CT小血管显示中的研究[J]. CT理论与应用研究(中英文),xxxx,x(x): 1-7. DOI: 10.15953/j.ctta.2024.168.
WANG Q, YAN W J, YUAN Y, et al. Study of a Deep Learning Reconstruction Algorithm for Displaying Small- and Medium-sized Blood Vessels in Upper Abdominal Energy Spectrum CT[J]. CT Theory and Applications, xxxx, x(x): 1-7. DOI: 10.15953/j.ctta.2024.168. (in Chinese).
Citation: WANG Q, YAN W J, YUAN Y, et al. Study of a Deep Learning Reconstruction Algorithm for Displaying Small- and Medium-sized Blood Vessels in Upper Abdominal Energy Spectrum CT[J]. CT Theory and Applications, xxxx, x(x): 1-7. DOI: 10.15953/j.ctta.2024.168. (in Chinese).

深度学习重建算法在上腹部能谱CT小血管显示中的研究

Study of a Deep Learning Reconstruction Algorithm for Displaying Small- and Medium-sized Blood Vessels in Upper Abdominal Energy Spectrum CT

  • 摘要: 目的:探讨上腹部CT能谱增强扫描时,采用深度学习重建算法(DLIR)的单能量图像显示腹部小血管的效果和临床价值。方法:回顾性分析2021年2月至2022年6月在四川大学华西医院因上腹不适而行CT能谱增强检查的患者28例,采用自适应统计迭代重建(ASIR-V)、DLIR-M、DLIR-H三种重建算法进行重建,同时通过能谱后处理软件提取40 keV和70 keV单能量图像,共生成4组图像,分别标记为40 keV-AV、40 keV-DL-M、40 keV-DL-H、70 keV-AV。测量肝总动脉、胃左动脉、脾动脉、肠系膜上动脉CT值和SD值,同时测量相同层面竖脊肌CT值和SD值,计算各分支血管信噪比(SNR)、对比噪声比(CNR)。两名放射科医师对图像噪声,图像伪影,目标血管对比度,图像“蜡状感”及图像整体质量做出主观评分。采用重复测量的单因素方差分析、配对 T检验比较4组图像间SNR、CNR及背景噪声的差异性。Kappa检验用于比较主观评价的一致性差异。结果:无论客观评价还是主观评价方面,DL-H图像的SNR、CNR、整体图像质量评分及噪声均优于DL-M,两者均优于AV图像,SNR、CNR和图像质量评分随DL强度增加而增加,噪声随着DL强度增加而降低。4组图像主观评分中,DL-H评分高于DL-M,DL-M高于AV。结论:深度学习重建算法可提高上腹部能谱增强CT40 keV单能量图像中小血管显示效果,且随强度增高,改善图像质量和降低噪声能力增强。与AV相比,DL图像重建算法对上腹部能谱增强CT检查小血管的显示能力有明显的提高。

     

    Abstract: Objective: To investigate the effectiveness and clinical value of using a deep learning reconstruction algorithm (DLIR) to display small blood vessels in upper abdominal computed tomography (CT) with an enhanced energy spectrum. Methods: Using three reconstruction algorithms, a retrospective analysis was performed on 28 patients with upper abdominal discomfort who underwent enhanced CT spectrum examination at the West China Hospital of Sichuan University from February 2021 to June 2022. The three reconstruction algorithms were adaptive statistical iterative reconstruction (ASIR-V), DLIR-M, and DLIR-H. Simultaneously, 40 keV and 70 keV single-energy images were extracted using energy spectrum post-processing software, and four groups of images were generated, which were labeled as 40 keV-AV, 40 keV-DL-M, 40 keV-DL-H, and 70 keV-AV, respectively. The CT and standard deviation (SD) values of common hepatic, left gastric, splenic, and superior mesenteric arteries were measured, and the CT and SD values of the vertical spinal muscle at the same level were measured. In addition, the signal-to-noise (SNR) and contrast-to-noise (CNR) ratios of each branch vessel were calculated. Two radiologists provided subjective scores on image noise, image artifacts, target blood vessel contrast, image “waxiness.” and overall image quality. Differences in SNR, CNR, and background noise among the four groups of images were compared using one-way analysis of variance (ANOVA) and paired t-tests. The kappa test was used to compare differences in the consistency of the subjective evaluations. Results: In both objective and subjective evaluations, the SNR, CNR, overall image quality score, and noise of the DL-H images were superior to those of the DL-M images, where the latter in turn were superior to those of the AV images. The SNR, CNR, and image quality score increased and the noise decreased with an increase in DL intensity. In the subjective scores of the four groups of images, the DL-H score was higher than the DL-M score, and the DL-M score was higher than the AV score. Conclusion: The DLIR can improve the display of small- and medium-sized vessels in upper abdomen energy spectrum enhanced CT40 keV single-energy images. With an increase in intensity, the image quality is improved and noise is reduced. Compared with AV, the DLIR significantly improves the display capabilities of upper abdominal energy spectrum-enhanced CT in the examination of small blood vessels.

     

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