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基于声辐射力脉冲(ARFI)成像的针可视化。

Acoustic Radiation Force Impulse (ARFI) imaging-based needle visualization.

机构信息

Department of Biomedical Engineering, Duke University, Box 90281, 136 Hudson Hall Durham, NC 27708, USA.

出版信息

Ultrason Imaging. 2011 Jan;33(1):1-16. doi: 10.1177/016173461103300101.

Abstract

Ultrasound-guided needle placement is widely used in the clinical setting, particularly for central venous catheter placement, tissue biopsy and regional anesthesia. Difficulties with ultrasound guidance in these areas often result from steep needle insertion angles and spatial offsets between the imaging plane and the needle. Acoustic Radiation Force Impulse (ARFI) imaging leads to improved needle visualization because it uses a standard diagnostic scanner to perform radiation force based elasticity imaging, creating a displacement map that displays tissue stiffness variations. The needle visualization in ARFI images is independent of needle-insertion angle and also extends needle visibility out of plane. Although ARFI images portray needles well, they often do not contain the usual B-mode landmarks. Therefore, a three-step segmentation algorithm has been developed to identify a needle in an ARFI image and overlay the needle prediction on a coregistered B-mode image. The steps are: (1) contrast enhancement by median filtration and Laplacian operator filtration, (2) noise suppression through displacement estimate correlation coefficient thresholding and (3) smoothing by removal of outliers and best-fit line prediction. The algorithm was applied to data sets from horizontal 18, 21 and 25 gauge needles between 0-4 mm offset in elevation from the transducer imaging plane and to 18G needles on the transducer axis (in plane) between 10 degrees and 35 degrees from the horizontal. Needle tips were visualized within 2 mm of their actual position for both horizontal needle orientations up to 1.5 mm offset in elevation from the transducer imaging plane and on-axis angled needles between 10 degrees-35 degrees above the horizontal orientation. We conclude that segmented ARFI images overlaid on matched B-mode images hold promise for improved needle visibility in many clinical applications.

摘要

超声引导下的针放置在临床环境中得到广泛应用,特别是在中心静脉导管放置、组织活检和区域麻醉中。在这些领域中,超声引导存在困难,通常是由于针插入角度陡峭以及成像平面与针之间的空间偏移。声辐射力脉冲(ARFI)成像可改善针可视化效果,因为它使用标准诊断扫描仪进行基于辐射力的弹性成像,创建显示组织硬度变化的位移图。ARFI 图像中的针可视化效果独立于针插入角度,并且还可以将针的可视性扩展到平面外。尽管 ARFI 图像可以很好地描绘针,但它们通常不包含通常的 B 模式标记。因此,开发了一种三步分割算法来识别 ARFI 图像中的针,并在配准的 B 模式图像上叠加针预测。步骤如下:(1)通过中值滤波和拉普拉斯算子滤波进行对比度增强,(2)通过位移估计相关系数阈值进行噪声抑制,(3)通过去除异常值和平滑最佳拟合线预测进行平滑处理。该算法应用于从换能器成像平面向上 0-4 毫米偏移的水平 18、21 和 25 号针以及换能器轴上 18G 针(平面内)的数据集,从水平方向的 10 度到 35 度。对于从换能器成像平面向上 1.5 毫米偏移的水平针和在水平方向以上 10 度至 35 度的轴上倾斜针,针尖端在实际位置的 2 毫米内可视化。我们得出结论,在许多临床应用中,叠加在匹配的 B 模式图像上的分割 ARFI 图像有望提高针的可视性。

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