Abstract

Objective

To investigate the feasibility and to optimize the parameters of nonlinear blending technique in dual-energy CT on solitary pulmonary nodules (SPN).

Methods

The simulated enhanced SPN were used the mixture of nonionic iodinated contrast agent (Iopromide 370mgI/100 ml) and normal saline and then randomly placed inside an anthropomorphic chest phantom. The phantom was examined on SOMATOM definition flash with dual mode (80/140 kV) and single energy mode (120 kV) (the same CTDIvol). Nonlinear blending images and linear blending images with a weighting factor of 0.3 were generated and the image qualities were analyzed.

Results

For different simulated density SPN, when 0 HU was chosen as the Blending Center (BC) and 0 to 30 HU were chosen as the Blending width (BW), the nonlinear blending images yielded a higher contrast-to-noise (CNR). There were significant differences in the image noise and signal-to-noise (SNR) of different simulated density SPN at non-linear blending images, linear blending images and 120 kV images (p < .05); But the differences of CNR between the three groups were not statistically significant (p > .05). The SNR of different simulated density SPN at non-linear blending images was significantly increased compared with it at linear blending images and 120 kV images (p < .05); And the image noise at non-linear blending was lower than it at linear blending images (p < .05).

Conclusion

Nonlinear blending technique in dual-energy CT can increase the SNR of enhanced SPN, and it is helpful in diagnosis of SPN.

中文翻译：

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双能CT非线性图像融合技术中孤立性肺结节的分子特征

摘要

客观的

探讨孤立性肺结节（SPN）双能CT非线性融合技术的可行性及参数优化。

方法

使用非离子碘造影剂（碘普罗胺370mgI/100ml）和生理盐水的混合物模拟增强SPN，然后随机放置在拟人化的胸部模型中。在 SOMATOM 定义闪光灯上使用双模式 (80/140 kV) 和单能量模式 (120 kV)（相同的 CTDIvol）检查了体模。生成加权因子为0.3的非线性混合图像和线性混合图像，并分析图像质量。

结果

For different simulated density SPN, when 0 HU was chosen as the Blending Center (BC) and 0 to 30 HU were chosen as the Blending width (BW), the nonlinear blending images yielded a higher contrast-to-noise (CNR). 不同模拟密度SPN在非线性混合图像、线性混合图像和120 kV图像上的图像噪声和信噪比（SNR）存在显着差异（p  < .05）；但三组CNR差异无统计学意义（p  >.05）。与线性混合图像和 120 kV 图像相比，不同模拟密度 SPN 在非线性混合图像上的信噪比显着提高（p < .05); 并且非线性混合时的图像噪声低于线性混合图像（p  < .05）。

结论

双能CT中的非线性融合技术可以提高增强SPN的信噪比，有助于SPN的诊断。