Bongers M N, Bier G, Kloth C, Schabel C, Fritz J, Nikolaou K, Horger M
Department of Diagnostic and Interventional Radiology, University Hospital of Tübingen, Germany.
Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, United States.
Rofo. 2016 Dec;188(12):1163-1168. doi: 10.1055/s-0042-116440. Epub 2016 Dec 1.
To evaluate the effects of a new frequency selective non-linear blending (NLB) algorithm on the contrast resolution of liver CT with low intravascular concentration of iodine contrast. Our local ethics committee approved this retrospective study. The informed consent requirement was waived. CT exams of 25 patients (60 % female, mean age: 65 ± 16 years of age) with late phase CT scans of the liver were included as a model for poor intrahepatic vascular contrast enhancement. Optimal post-processing settings to enhance the contrast of hepatic vessels were determined. Outcome variables included signal-to-noise (SNR) and contrast-to-noise ratios (CNR) of hepatic vessels and SNR of liver parenchyma of standard and post-processed images. Image quality was quantified by two independent readers using Likert scales. The post-processing settings for the visualization of hepatic vasculature were optimal at a center of 115HU, delta of 25HU, and slope of 5. Image noise was statistically indifferent between standard and post-processed images. The CNR between the hepatic vasculature (HV) and liver parenchyma could be significantly increased for liver veins (CNR 1.62 ± 1.10, CNR 3.6 ± 2.94, p = 0.0002) and portal veins (CNR 1.31 ± 0.85, CNR 2.42 ± 3.03, p = 0.046). The SNR of liver parenchyma was significantly higher on post-processed images (SNR 11.26 ± 3.16, SNR 8.85 ± 2.27, p = 0.008). The overall image quality and depiction of HV were significantly higher on post-processed images (NLB: 4 [3 - 4.75], S: 2 [1.3 - 2.5], p = < 0.0001; : 4 [4 - 4], : 2 [2 - 3], p = < 0.0001). The use of a frequency selective non-linear blending algorithm increases the contrast resolution of liver CT and can improve the visibility of the hepatic vasculature in the setting of a low contrast ratio between vessels and the parenchyma. • Using the new frequency selective non-linear blending algorithm is feasible in contrast-enhanced liver CT.• Optimal post-processing settings make it possible to significantly increase the contrast resolution of liver CT without affecting image noise.• Especially in low contrast CT images, the novel algorithm is capable of significantly increasing image quality. • Bongers MN, Bier G, Kloth C et al. Frequency Selective Non-Linear Blending to Improve Image Quality in Liver CT. Fortschr Röntgenstr 2016; 188: 1163 - 1168.
为评估一种新的频率选择性非线性融合（NLB）算法对碘对比剂血管内浓度较低时肝脏CT对比分辨率的影响。我们当地的伦理委员会批准了这项回顾性研究。免除了知情同意要求。纳入25例患者（60%为女性，平均年龄：65±16岁）的肝脏晚期CT扫描作为肝内血管对比增强不佳的模型。确定了增强肝血管对比度的最佳后处理设置。结果变量包括标准图像和后处理图像的肝血管信噪比（SNR）、对比噪声比（CNR）以及肝实质的SNR。由两名独立阅片者使用李克特量表对图像质量进行量化。肝血管可视化的后处理设置在中心值115HU、差值25HU和斜率5时最佳。标准图像和后处理图像之间的图像噪声在统计学上无差异。肝静脉（CNR 1.62±1.10，CNR 3.6±2.94，p = 0.0002）和门静脉（CNR 1.31±0.85，CNR 2.42±3.03，p = 0.046）的肝血管与肝实质之间的CNR可显著提高。后处理图像上肝实质的SNR显著更高（SNR 11.26±3.16，SNR 8.85±2.27，p = 0.008）。后处理图像上的整体图像质量和肝血管的显示显著更高（NLB：评分4[3 - 4.75]，标准图像：评分2[1.3 - 2.5]，p = <0.0001；肝血管：评分4[4 - 4]，标准图像：评分2[2 - 3]，p = <0.0001）。使用频率选择性非线性融合算法可提高肝脏CT的对比分辨率，并能在血管与实质之间对比度较低的情况下改善肝血管的可视性。• 在对比增强肝脏CT中使用新的频率选择性非线性融合算法是可行的。• 最佳后处理设置能够在不影响图像噪声的情况下显著提高肝脏CT的对比分辨率。• 特别是在低对比度CT图像中，该新算法能够显著提高图像质量。• 邦格斯·MN、比尔·G、克洛思·C等。频率选择性非线性融合改善肝脏CT图像质量。《德国放射学杂志》2016年；188: 1163 - 1168。
