Adaptive Clutter Rejection for 3D Color Doppler Imaging: Preliminary Clinical Study
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- 作者：Yang Mo Yoo ; Siddhartha Sikdar ; Kerem Karadayi ; Orpheus Kolokythas ; Yongmin Kim
- 关键词：3D ultrasound color Doppler imaging ; Adaptive clutter rejection ; Kidney transplant ; Flow signal-to-clutter ratio ; Fractional residual clutter area
- 刊名：Ultrasound in Medicine and Biology
- 出版年：2008
- 出版时间：August 2008
- 年：2008
- 卷：34
- 期：8
- 页码：1221-1231
- 全文大小：2005 K
文摘
In three-dimensional (3D) ultrasound color Doppler imaging (CDI), effective rejection of flash artifacts caused by tissue motion (clutter) is important for improving sensitivity in visualizing blood flow in vessels. Since clutter characteristics can vary significantly during volume acquisition, a clutter rejection technique that can adapt to the underlying clutter conditions is desirable for 3D CDI. We have previously developed an adaptive clutter rejection (ACR) method, in which an optimum filter is dynamically selected from a set of predesigned clutter filters based on the measured clutter characteristics. In this article, we evaluated the ACR method with 3D in vivo data acquired from 37 kidney transplant patients clinically indicated for a duplex ultrasound examination. We compared ACR against a conventional clutter rejection method, down-mixing (DM), using a commonly-used flow signal-to-clutter ratio (SCR) and a new metric called fractional residual clutter area (FRCA). The ACR method was more effective in removing the flash artifacts while providing higher sensitivity in detecting blood flow in the arcuate arteries and veins in the parenchyma of transplanted kidneys. ACR provided 3.4 dB improvement in SCR over the DM method (11.4 ± 1.6 dB versus 8.0 ± 2.0 dB, p < 0.001) and had lower average FRCA values compared with the DM method (0.006 ± 0.003 versus 0.036 ± 0.022, p < 0.001) for all study subjects. These results indicate that the new ACR method is useful for removing nonstationary tissue motion while improving the image quality for visualizing 3D vascular structure in 3D CDI. (E-mail: ykim@u.washington.edu)