Improved receiver arrays and optimized parallel imaging accelerations applied to time-resolved 3D fluoroscopically tracked peripheral runoff CE-MRA

Abstract Objectives Three-station stepping-table time-resolved 3D contrast-enhanced magnetic resonance angiography has conflicting demands in the need to limit acquisition time in proximal stations to match the speed of the advancing contrast bolus and in the distal-most station to avoid venous contamination while still providing clinically useful spatial resolution. This work describes improved receiver coil arrays which address this issue by allowing increased acceleration factors, providing increased spatial resolution per unit time. Materials and methods Receiver coil arrays were constructed for each station (pelvis, thigh, calf) and then integrated into a 48-element array for three-station peripheral CE-MRA. Coil element sizes and array configurations for these three stations were designed to improve SENSE-type parallel imaging taking advantage of an increase in coil count for all stations versus the previous 32 channel capability. At each station either acceleration apportionment or optimal CAIPIRINHA selection was used to choose the optimum acceleration parameters for each subject. Results were evaluated in both single- and multi-station studies. Results Single-station studies showed that SENSE acceleration in the thigh station could be readily increased from R = 8 to R = 10, allowing reduction of the frame time from 2.5 to 2.1 s to better image the typically rapidly advancing bolus at this station. Similarly, the improved coil array for the calf station permitted acceleration increase from R = 8 to R = 12, providing a 4.0 vs. 5.2 s frame time. Results in three-station studies suggest an improved ability to track the contrast bolus in peripheral CE-MRA. Conclusions Modified receiver coil arrays and individualized parameter optimization have been used to provide improved acceleration at all stations in multi-station peripheral CE-MRA and provide high spatial resolution with frame times as short as 2.1 s.