Efficient implementation of hardware-optimized gradient sequences for real-time imaging

Abstract

This work improves the performance of interactive real-time imaging with balanced steady-state free precession. The method employs hardware-optimized gradient pulses, together with a novel phase-encoding strategy that simplifies the design and implementation of the optimized gradient waveforms. In particular, the waveforms for intermediate phase-encode steps are obtained by simple linear combination, rather than separate optimized waveform calculations. Gradient waveforms are redesigned in real time as the scan plane is manipulated, and the resulting sequence operates at the specified limits of the MRI gradient subsystem for each new scan-plane orientation. The implementation provides 14-25% improvement in the sequence pulse repetition time over the vendor-supplied interactive real-time imaging sequence for similar scan parameters on our MRI scanner.

© 2010 Wiley-Liss, Inc.

Figures

FIG. 1

Conventional and HOT pulse-based bSSFP sequences. a: Pulse sequence (top left) shows a bSSFP sequence designed conventionally in logical coordinate system (Gs = slice, Gp = phase, Gr = readout) for an arbitrary oblique scan plane. The gradient specification used for the waveform design was reduced by √3 during design to avoid overranging when the sequence is rotated into the physical coordinate representation (b). The gray regions are dead time where no RF transmission or data acquisition occurs. c,d: A HOT pulse implementation of bSSFP with the same parameters, but optimized for the particular oblique scan-plane orientation and designed in the physical coordinate system (d) to match the full amplitude and slew rate specifications. This approach permits a reduction in dead time and shorter TR. Note that the shapes of the HOT pulse gradient waveforms change from one phase encode to the next on all three axes in both the physical (d) and logical (c) coordinate representations. This observation precludes the use of simple amplitude scaling to implement phase encoding. In effect, the read dephase and slice rephase gradients are modified slightly from one phase encode to the next (without changing their 0th moment) to permit a slight optimization of the phase-encoding pulse.

FIG. 2

Construction and implementation of HOT pulses as the linear combination of static and dynamic components. This example demonstrates the design process for the HOT pulse waveform on the physical X-axis gradient between the end of slice selection and the beginning of the readout. Each HOT pulse gradient, designed in physical gradient space, contains portions of the slice rewinder, read dephaser, and phase-encode gradients. The PLG waveforms for the extreme positive and negative phase encodes are decomposed into static portions, s(t), and dynamic portions, d(t). To perform phase encoding, a linear combination g(t) = s(t) + λd(t) is played where −1 ≤ λ < 1 is the phase-encoding factor.

FIG. 3

Performance of the HOT pulse sequence. The surface plot (a) shows the minimum TR of the HOT pulse sequence as a function of the scan plane normal orientation for a 2562 sampling matrix. The TR varies with both scan-plane orientation normal vector and the in-plane rotation. The surface shows the minimum TR over all the in-plane rotations. The upper graph (b) shows the performance of the vendor-supplied interactive real-time true FISP sequence (black) compared with the HOT-pulse sequence as a function of resolution. HOT pulse TRs shown are for the minimum, maximum, and mean obtained from 100,000 scan-plane orientations, with rotation matrices uniformly sampled from the space of all three-dimensional rotation matrices, SO (3). The red plot (“opt”) represents the TR obtained for the same rotation matrices, when sequence optimization by inverting the readout polarity (or, equivalently a 180° in-plane rotation) is permitted. The lower graph (c) shows the variation of the TR of the HOT pulse sequence with in-plane rotation for a cardiac short-axis slice. The preferred slice orientation for imaging (prescribed by the MR system operator) is indicated by the dashed line.

FIG. 4

Real-time, cardiac short-axis images. All images were acquired with 360mm square field of view and 6mm slice thickness. Images (a) and (b) were acquired with 192 × 192 matrix using the standard real-time imaging sequence, true FISP (TR = 3.23 ms), and bSSFP with HOT pulses (TR = 2.78 ms), respectively. Images (c–e) are 128 × 128 acquisitions using the standard FISP sequence (TR = 2.67) and the new bSSFP (TR = 2.22 ms and TR = 2.67 ms). Note that the 192-resolution HOT pulse sequence provided TRs only slightly longer than the 128-resolution conventional image. In (e), the bSSFP TR was extended to match the conventional sequence by reducing the acquisition bandwidth (sampling bandwidth).