Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current.

IF 3.3 3区 医学 Q2 MEDICAL INFORMATICS
Shumeng Zhu, Baoping Zhang, Qian Tian, Ao Li, Zhe Liu, Wei Hou, Wenzhe Zhao, Xin Huang, Yao Xiao, Yiming Wang, Rui Wang, Yuhang Li, Jian Yang, Chao Jin
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引用次数: 0

Abstract

Background: The low tube-voltage technique (e.g., 80 kV) can efficiently reduce the radiation dose and increase the contrast enhancement of vascular and parenchymal structures in abdominal CT. However, a high tube current is always required in this setting and limits the dose reduction potential. This study investigated the feasibility of a deep learning iterative reconstruction algorithm (Deep IR) in reducing the radiation dose while improving the image quality for abdominal computed tomography (CT) with low tube voltage and current.

Methods: Sixty patients (male/female, 36/24; Age, 57.72 ± 10.19 years) undergoing the abdominal portal venous phase CT were randomly divided into groups A (100 kV, automatic exposure control [AEC] with reference tube-current of 213 mAs) and B (80 kV, AEC with reference of 130 mAs). Images were reconstructed via hybrid iterative reconstruction (HIR) and Deep IR (levels 1-5). The mean CT and standard deviation (SD) values of four regions of interest (ROI), i.e. liver, spleen, main portal vein and erector spinae at the porta hepatis level in each image serial were measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The image quality was subjectively scored by two radiologists using a 5-point criterion.

Results: A significant reduction in the radiation dose of 69.94% (5.09 ± 0.91 mSv vs. 1.53 ± 0.37 mSv) was detected in Group B compared with Group A. After application of the Deep IR, there was no significant change in the CT value, but the SD gradually increased. Group B had higher CT values than group A, and the portal vein CT values significantly differed between the groups (P < 0.003). The SNR and CNR in Group B with Deep IR at levels 1-5 were greater than those in Group A and significantly differed when HIR and Deep IR were applied at levels 1-3 of HIR and Deep IR (P < 0.003). The subjective scores (distortion, clarity of the portal vein, visibility of small structures and overall image quality) with Deep IR at levels 4-5 in Group B were significantly higher than those in group A with HIR (P < 0.003).

Conclusion: Deep IR algorithm can meet the clinical requirements and reduce the radiation dose by 69.94% in portal venous phase abdominal CT with a low tube voltage of 80 kV and a low tube current. Deep IR at levels 4-5 can significantly improve the image quality of the abdominal parenchymal organs and the clarity of the portal vein.

低管电压、低管电流下腹部计算机断层扫描的小剂量深度学习迭代重建。
背景:低管电压技术(如80kv)可有效降低辐射剂量,增强腹部CT血管和实质结构的对比增强。然而,在这种情况下,总是需要高的管电流,这限制了剂量减少的潜力。本研究探讨了一种深度学习迭代重建算法(deep IR)在降低辐射剂量的同时提高低管电压和电流下腹部计算机断层扫描(CT)图像质量的可行性。方法:60例患者(男/女,36/24;年龄(57.72±10.19岁),随机分为A组(100 kV,自动暴露控制[AEC],参考管电流213 mAs)和B组(80 kV, AEC,参考管电流130 mAs)。通过混合迭代重建(HIR)和Deep IR(1-5级)重建图像。测量每个图像序列中肝、脾、门静脉主静脉和竖脊四个感兴趣区域(ROI)的CT均值和标准差(SD)值,并计算信噪比(SNR)和噪声对比比(CNR)。图像质量由两名放射科医生使用5分标准主观评分。结果:与A组相比,B组放射剂量明显降低69.94%(5.09±0.91 mSv vs. 1.53±0.37 mSv)。应用深度红外后,CT值无明显变化,但SD逐渐升高。B组CT值高于A组,门静脉CT值组间差异有统计学意义(P)结论:在低管电压80 kV、低管电流条件下,深红外算法门静脉期腹部CT可满足临床要求,降低辐射剂量69.94%。4 ~ 5级深红外可显著提高腹部实质器官的图像质量和门静脉的清晰度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
5.70%
发文量
297
审稿时长
1 months
期刊介绍: BMC Medical Informatics and Decision Making is an open access journal publishing original peer-reviewed research articles in relation to the design, development, implementation, use, and evaluation of health information technologies and decision-making for human health.
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