Accuracy of Pulmonary Nodule Volumetry Using Noise-Optimized Virtual Monoenergetic Image and Nonlinear Blending Image Algorithms in Dual-Energy Computed Tomography: A Phantom Study

被引:4
作者
He, Changjiu [1 ]
Liu, Jieke [1 ]
Hu, Shibei [1 ]
Qing, Haomiao [1 ]
Qiao, Liang [2 ]
Luo, Hongbing [1 ]
Chen, Xiaoli [1 ]
Zhou, Peng [1 ]
机构
[1] Univ Elect Sci & Technol China, Dept Radiol, Sichuan Canc Hosp & Inst, Sichuan Canc Ctr,Sch Med, Chengdu, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Dept Canc Prevent & Treatment, Sichuan Canc Hosp & Inst, Sichuan Canc Ctr,Sch Med, Chengdu, Sichuan, Peoples R China
关键词
pulmonary nodule volumetry; noise-optimized virtual monoenergetic image; nonlinear blending image; dual energy computed tomography; phantom;
D O I
10.1097/RCT.0000000000001102
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objective The aim of the study was to assess accuracy of pulmonary nodule volumetry using noise-optimized virtual monoenergetic image (VMI+) and nonlinear blending image (NBI) algorithms in dual-energy computed tomography (DECT). Methods An anthropomorphic chest phantom with 10 simulated nodules (5 solid nodules and 5 ground-glass opacities) was scanned using DECT80/Sn140kV, DECT100/Sn140kV, and single-energy CT (SECT120kV/200mAs), respectively. The dual-energy images were reconstructed using VMI+ (70 keV) and NBI algorithms. The contrast-to-noise ratio and absolute percentage error (APE) of nodule volume were measured to assess image quality and accuracy of nodule volumetry. The radiation dose was also estimated. Results The contrast-to-noise ratio of SECT120kV/200mAs was significantly higher than that of NBI80/Sn140kV and VMI+(80/Sn140kV) (both corrected P < 0.05), whereas there were no significant differences between NBI100/sn140kV and SECT120kV/200mAs and between VMI+(100/sn140kV) and SECT120kV/200mAs (both corrected P > 0.05). The APE of SECT120kV/200mAs was significantly lower than that of NBI80/Sn140kV and VMI+(80/Sn140kV) in both types of nodules (all corrected P < 0.05), whereas there were no significant differences between VMI+(100/sn140kV) and SECT120kV/200mAs in solid nodules and between NBI100/Sn140kV and SECT120kV/200mAs in ground-glass opacities (both corrected P > 0.05). The radiation dose of DECT100/Sn140kV and DECT80/Sn140kV were significantly lower than that of SECT120kV/200mAs (both corrected P < 0.05). Conclusions The DECT100/sn140kV can ensure image quality and nodule volumetry accuracy with lower radiation dose compared with SECT120kV/200mAs. Specifically, the VMI+ algorithm could be used in solid nodules and NBI algorithm in ground-glass opacities.
引用
收藏
页码:847 / 851
页数:5
相关论文
共 35 条
  • [31] Advanced virtual monochromatic reconstruction of dual-energy unenhanced brain computed tomography in children: comparison of image quality against standard mono-energetic images and conventional polychromatic computed tomography
    Juil Park
    Young Hun Choi
    Jung-Eun Cheon
    Woo Sun Kim
    In-One Kim
    Seong Yong Pak
    Bernhard Krauss
    Pediatric Radiology, 2017, 47 : 1648 - 1658
  • [32] High-Temporal Resolution Dual-Energy Computed Tomography of the Heart Using a Novel Hybrid Image Reconstruction Algorithm: Initial Experience
    Nance, John William, Jr.
    Bastarrika, Gorka
    Kang, Doo Kyoung
    Ruzsics, Balazs
    Vogt, Sebastian
    Schmidt, Bernhard
    Raupach, Rainer
    Flohr, Thomas G.
    Schoepf, U. Joseph
    JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 2011, 35 (01) : 119 - 125
  • [33] Stopping-power ratio estimation for proton radiotherapy using dual-energy computed tomography and prior-image constrained denoising
    Zimmerman, Jens
    Thor, Daniel
    Poludniowski, Gavin
    MEDICAL PHYSICS, 2023, 50 (03) : 1481 - 1495
  • [34] Evaluation of pulmonary function using single-breath-hold dual-energy computed tomography with xenon Results of a preliminary study
    Kyoyama, Hiroyuki
    Hirata, Yusuke
    Kikuchi, Satoshi
    Sakai, Kosuke
    Saito, Yuriko
    Mikami, Shintaro
    Moriyama, Gaku
    Yanagita, Hisami
    Watanabe, Wataru
    Otani, Katharina
    Honda, Norinari
    Uematsu, Kazutsugu
    MEDICINE, 2017, 96 (03)
  • [35] Obtaining dual-energy computed tomography (CT) information from a single-energy CT image for quantitative imaging analysis of living subjects by using deep learning
    Zhao, Wei
    Lv, Tianling
    Lee, Rena
    Chen, Yang
    Xing, Lei
    PACIFIC SYMPOSIUM ON BIOCOMPUTING 2020, 2020, : 139 - 148