Dose length product and outcome of CT fluoroscopy-guided interventions using a new 320-detector row CT scanner with deep-learning reconstruction and new bow-tie filter

使用配备深度学习重建技术和新型蝶形滤波器的320排探测器CT扫描仪,评估CT透视引导介入治疗的剂量长度乘积和疗效。

阅读:1

Abstract

OBJECTIVES: To investigate the dose length product (DLP) and outcomes of CT fluoroscopy (CTF)-guided interventions using a novel 320-detector row CT scanner with deep-learning reconstruction (DLR) and a new bow-tie filter (i.e., Aquilion ONE Prism Edition) and compare with a 320-detector row CT system without DLR and the new bow-tie filter (i.e., Aquilion ONE Vision Edition) (Vision). METHODS: CTF-guided interventions performed using Prism and Vision were retrospectively investigated in terms of the technical success rates, clinical success rates of biopsies, complications, DLPs of total CT scans (total DLPs) from February 2019 to January 2021. The total CT scans included pre-interventional CT scans, CTF scans during the CTF-guided procedure, additional CT scans for additional treatment, CTF scans for additional treatment, and post-interventional CT scans. RESULTS: In this study, 87 and 85 CTF-guided interventions were performed using Vision (Vision group) and Prism (Prism group), respectively. There was no significant difference in the technical success rate (96.6% vs 98.8%, p = 0.621), clinical success rate of biopsies (92.9% vs 93.4%, p = 1.000), and minor (8.0% vs 7.1%, p = 0.807) and major (0% vs 3.5%, p = 0.119) complications between the Prism and Vision groups. The total DLPs for the Prism group were significantly lower than those for the Vision group regardless of the procedure (278 vs 548 mGy*cm, p < 0.001, in the biopsy and 246 vs 667 mGy*cm, p < 0.001, in the drainage and aspiration). CONCLUSIONS: CTF-guided interventions on Prism reduce the total DLP without performance degradation of the intervention. ADVANCES IN KNOWLEDGE: The total DLPs of biopsies and drainages/aspirations in the Prism group decreased by 49 and 63%, respectively.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。