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Tin-filter enhanced dual-energy-ct: Image quality and accuracy of CT numbers in virtual noncontrast imaging

机译：锡过滤器增强了双能-CT：虚拟非共同影像中CT号的图像质量和准确性

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摘要

Objectives: To measure and compare the objective image quality of true noncontrast (TNC) images with virtual noncontrast (VNC) images acquired by tin-filter-enhanced, dual-source, dual-energy computed tomography (DECT) of upper abdomen. Materials and Methods: Sixty-three patients received unenhanced abdominal CT and enhanced abdominal DECT (100/140 kV with tin filter) in portal-venous phase. VNC images were calculated from the DECT datasets using commercially available software. The mean attenuation of relevant tissues and image quality were compared between the TNC and VNC images. Image quality was rated objectively by measuring image noise and the sharpness of object edges using custom-designed software. Measurements were compared using Student two-tailed t-test. Correlation coefficients for tissue attenuation measurements between TNC and VNC were calculated and the relative deviations were illustrated using Bland-Altman plots. Results: Mean attenuation differences between TNC and VNC (HUTNC - HUVNC) image sets were as follows: right liver lobe -4.94 Hounsfield units (HU), left liver lobe -3.29 HU, vena cava -2.19 HU, spleen -7.46 HU, pancreas 1.29 HU, fat -11.14 HU, aorta 1.29 HU, bone marrow 36.83 HU (all P .05); right kidney 0.46 HU, left kidney 0.56 HU, vena portae -0.48 HU and muscle -0.62 HU (nonsignificant). Good correlations between VNC and TNC series were observed for liver, vena portae, kidneys, pancreas, muscle and bone marrow (Pearson's correlation coefficient ??0.75). Mean image noise was significantly higher in TNC images (P .0001). Measurements of edge sharpness revealed no significant differences between VNC and TNC images (P = .19). Conclusion: The Hounsfield units in VNC images closely resemble TNC images in the majority of the organs of the upper abdomen (kidneys, liver, pancreas). In spleen and fat, Hounsfield numbers in VNC images are tend to be higher than in TNC images. VNC images show a low image noise and satisfactory edge sharpness. Other criteria of image quality and the depiction of certain lesions need to be evaluated additionally. ? 2013 AUR.
机译：目标：测量和比较通过上腹部的锡滤波器增强，双源，双能量计算断层扫描（DECT）的虚拟非共控制（VNC）图像的真正非共用（TNC）图像的客观图像质量。材料和方法：六十三名患者在门静脉期中接受未加入腹部CT和增强腹部DECT（100/140 kV用锡过滤器）。使用商业上可用的软件从DECT数据集计算VNC图像。在TNC和VNC图像之间比较了相关组织和图像质量的平均衰减。通过使用定制设计的软件测量图像噪声和物体边缘的锐度，图像质量客观地评估。使用学生双尾T检验进行比较测量。计算TNC和VNC之间的组织衰减测量的相关系数，并使用Bland-Altman图示出了相对偏差。结果：TNC和VNC（HUTNC - HUVNC）图像集之间的平均衰减差异如下：右肝LOBE -4.94 Hounsfield单位（HU），左肝叶-3.29胡，腔静脉-2.19胡，脾脏-7.46胡，胰腺1.29胡，脂肪-11.14胡，主动脉1.29胡，骨髓36.83胡（所有P <05）;右肾0.46胡，左肾0.56胡，静脉Portae -0.48胡和肌肉-0.62胡（不显着）。对于肝脏，腔葡萄球菌，肾脏，胰腺，肌肉和骨髓（Pearson的相关系数？0.75），观察到VNC和TNC系列之间的良好相关性。 TNC图像中的平均图像噪声显着高（P <.0001）。边缘清晰度的测量显示VNC和TNC图像之间没有显着差异（P = .19）。结论：VNC图像中的Hounsfield单元在上腹部大部分器官（肾脏，肝脏，胰腺）中非常类似于TNC图像。在脾脏和脂肪中，VNC图像中的Hounsfield号往往高于TNC图像。 VNC图像显示出低图像噪声和令人满意的边缘清晰度。另外需要评估图像质量的其他标准和某些病变的描述。还2013年AUR。

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  • 来源
    《Academic radiology》 |2013年第5期|共8页
  • 作者

    KaufmannS.; SauterA.; SpiraD.; GatidisS.; KetelsenD.; HeuschmidM.; ClaussenC.D.; ThomasC.;

  • 作者单位

    Department of Radiology Diagnostic and Interventional Radiology Hoppe-Seyler-Str. 3 72076;

    Department of Radiology Diagnostic and Interventional Radiology Hoppe-Seyler-Str. 3 72076;

    Department of Radiology Diagnostic and Interventional Radiology Hoppe-Seyler-Str. 3 72076;

    Department of Radiology Diagnostic and Interventional Radiology Hoppe-Seyler-Str. 3 72076;

    Department of Radiology Diagnostic and Interventional Radiology Hoppe-Seyler-Str. 3 72076;

    Department of Radiology Diagnostic and Interventional Radiology Hoppe-Seyler-Str. 3 72076;

    Department of Radiology Diagnostic and Interventional Radiology Hoppe-Seyler-Str. 3 72076;

    Department of Radiology Diagnostic and Interventional Radiology Hoppe-Seyler-Str. 3 72076;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 放射医学;
  • 关键词

    Computed tomography; Dual energy; Dual source; Virtual noncontrast imaging;

    机译：计算断层扫描;双能量;双来源;虚拟非共同影像;

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