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| The value of the pixel shine algorithm in improving the display of small hepatocellular metastases in
low single energy image with single-source dual-energy CT |
| XU Ming-zhe1, LIU Ai-lian1, LIU Yi-jun1, LIU Jing-hong1, PAN Ju-dong2 |
| 1. Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian Liaoning 116011, China;
2. Department of Radiology, University of California San Francisso, San Francisso 173304, America |
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Abstract Objective: To explore the value of pixel shine(PS) algorithm to improve the quality of single-energy image, especially the low single-energy image by single-source dual-energy CT, and to improve the detection of small liver metastases. Methods: Fourteen patients, who underwent spectral CT imaging using spectrum imaging modality(GSI) were retrospectively enrolled with 38 lesions in this study. The PS algorithm(A7 mode) was applied to process the low single-energy images obtained from the AW4.6 workstation to obtain four groups of 40~70 KeV single energy images before and after calculation by PS. The ROIs were draw in the liver metastases and normal liver parenchyma respectively at the same location and on the same slice, showing the maximum area of the lesion, of 40~70 KeV single-energy images by a senior radiologist, then CT and SD values were measured and recorded. The SNRs of liver metastases, the CNRs of liver metastases relative to normal liver parenchyma and the ratios of SNRs and CNRs in images after calculation by PS relative to before were calculated. The Shapiro-Wilk normal distribution test was used to check the normality of data. The CT values of liver metastases and normal liver parenchyma, SNRs and CNRs of hepatic metastases were compared between four groups of 40~70 KeV single energy images before and after calculation by PS, then the SNRs and CNRs of hepatic metastases in 40 KeV, 50 KeV and 60 KeV images processed by PS algorithm were compared with those in 70 KeV images. Paired samples t-test was used to compare the data that fit the normal distribution, and the Wilcoxon signed-rank test was used to compare the data that didn’t conform to normal distribution. The nonparametric Friedman test was used to compare the differences of SNR and CNR increase ratios of 40~70 KeV single energy images processed by PS algorithm. If there was a difference, the Wilcoxon signed rank test was used for comparison. Results: There were no differences between the CT values of liver metastases and liver parenchyma in four groups of 40~70 KeV single energy images before and after calculation by PS(P＞0.05). The SNR and CNR of liver metastases in 40~70 KeV single energy images processed by PS algorithm were greater than those in images without PS calculation(all P=0.000). Compared with SNRs and CNRs of hepatic metastases in 70 KeV PS images, the SNRs of hepatic metastases in 40 KeV images processed by PS was less than that in 70 KeV images without PS calculation, while the SNRs of hepatic metastases in 50 KeV and 60 KeV images processed by PS and the CNRs of liver metastases in 40 KeV, 50 KeV and 60 KeV images processed by PS were significantly greater than that in 70 KeV images without PS calculation. Conclusion: PS algorithm can significantly improve quality of single-energy images to show the intrahepatic metastasis lesion, and the PS algorithm used in the low single energy image has better effect on the display of lesions.
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Received: 09 December 2017
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