Acoustic Radiation Force Impulse (ARFI) Imaging-Based Needle Visualization

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° and 35° 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°–35° 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.