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  • Title: Frequency Selective Non-Linear Blending to Improve Image Quality in Liver CT.
    Author: Bongers MN, Bier G, Kloth C, Schabel C, Fritz J, Nikolaou K, Horger M.
    Journal: Rofo; 2016 Dec; 188(12):1163-1168. PubMed ID: 27907941.
    Abstract:
    Purpose: 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. Materials and Methods: 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. Results: 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 (CNRStandard 1.62 ± 1.10, CNRNLB 3.6 ± 2.94, p = 0.0002) and portal veins (CNRStandard 1.31 ± 0.85, CNRNLB 2.42 ± 3.03, p = 0.046). The SNR of liver parenchyma was significantly higher on post-processed images (SNRNLB 11.26 ± 3.16, SNRStandard 8.85 ± 2.27, p = 0.008). The overall image quality and depiction of HV were significantly higher on post-processed images (NLBDHV: 4 [3 - 4.75], StandardDHV: 2 [1.3 - 2.5], p = < 0.0001; NLBIQ: 4 [4 - 4], StandardIQ: 2 [2 - 3], p = < 0.0001). Conclusion: 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. Key Points: • 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. Citation Format: • 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.
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