Image quality enhancement of CT hepatic portal venography using dual energy blending with computer determined
Tao Wang1,2,3,4, Yuxin Han1,2,3,4, Liying Lin5
1Department of Radiology, Tianjin Third Central Hospital, Tianjin, China.
Background:
Previous studies have shown that using some post-processing methods, such as nonlinear-blending and linear blending techniques, has potential to improve dual-energy computed (DECT) image quality.
Objective:
To improve DECT image quality of hepatic portal venography (CTPV) using a new non-linear blending method with computer-determined parameters, and to compare the results to additional linear and non-linear blending techniques.
Methods:
DECT images of 60 patients who were clinically diagnosed with liver cirrhosis were selected and studied. Dual-energy scanning (80 kVp and Sn140 kVp) of CTPV was utilized in the portal venous phase through a dual-source CT scanner. For image processing, four protocols were utilized including linear blending with a weighing factor of 0.3 (protocol A) and 1.0 (protocol B), non-linear blending with fixed blending width of 200 HU and set blending center of 150HU (protocol C), and computer-based blending (protocol D). Several image quality indicators, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and contrast of hepatic portal vein and hepatic parenchyma, were evaluated using the paired-sample t-test. A 5-grade scale scoring system was also utilized for subjective analysis.
Results:
SNR of protocols A-D were 9.1±2.1, 12.1±3.0, 11.6±2.8 and 14.4±3.2, respectively. CNR of protocols A-D were 4.6±1.3, 8.0±2.3, 7.0±2.0 and 9.8±2.4, respectively. The contrast of protocols A-D were 37.7±11.6, 91.9±21.0, 66.2±19.0 and 107.7±21.3, respectively. The differences between protocol D and other three protocols were significant (P < 0.01). In subjective evaluation, the modes of protocols A, B, C, and D were rated poor, good, generally acceptable, and excellent, respectively.
Conclusion:
The non-linear blending technique of protocol D with computer-determined blending parameters can help improve imaging quality of CTPV and contribute to a diagnosis of liver disease.
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