Fast 3-D Velocity Estimation in 4-D using a 62 + 62 Row-Column Addressed Array

This paper presents an imaging scheme capable of estimating the full 3-D velocity vector field in a volume using rowcolumn addressed (RCA) arrays at a high volume rate. A 62+62 RCA array is employed with an interleaved synthetic aperture sequence. It contains repeated emissions with rows and columns interleaved with B-mode emissions. The sequence contains 80 emissions in total and can provide continuous volumetric data at a volume rate above 125 Hz. A transverse oscillation crosscorrelation estimator determines all three velocity components. The approach is investigated using Field II simulations and measurements using a specially built 3 MHz 62+62 RCA array connected to the SARUS experimental scanner. Both the B-mode and flow sequences have a penetration depth of 14 cm when measured on a tissue mimicking phantom (0.5 dB/[MHz·cm] attenuation). Simulations of a parabolic flow in a 12 mm diameter vessel at a depth of 30 mm, beam-to-flow angle of 90°, and xyrotation of 45° gave a standard deviation (SD) of (3.3, 3.4, 0.4)% and bias of (-3.3, -3.9, -0.1)%, for (vx, vy, vz). Decreasing the beam-to-flow angle to 60° gave a SD of (8.9, 9.1, 0.8)% and bias of (-7.6, -9.5, -7.2)%, showing a slight increase. Measurements were carried out using a similar setup, and pulsing at 2 kHz yielded comparable results at 90° with a SD of (5.8, 5.5, 1.1)% and bias of (1.4, -6.4, 2.4)%. At 60° the SD was (5.2, 4.7 1.2)% and bias (-4.6, 6.9, -7.4)%. Results from measurements across all tested settings showed a maximum SD of 6.8% and a maximum bias of 15.8%, for a peak velocity of 10 cm/s. A tissue mimicking phantom with a straight vessel was used to introduce clutter, tissue motion, and a pulsating flow. The pulsating velocity magnitude was estimated across 10 pulse periods and yielded an SD of 10.9%. The method was capable of estimating transverse flow components precisely, but underestimated the flow with small beam-to-flow angles. The sequence provided continuous data in both time and s