Reduced-field of view three-dimensional MR acoustic radiation force imaging with a low-rank reconstruction for targeting transcranial focused ultrasound

Abstract

Purpose: To rapidly image and localize the focus in MR-guided focused ultrasound (FUS) while maintaining a low ultrasound duty cycle to minimize tissue effects.

Methods: MR-acoustic radiation force imaging (ARFI) is key to targeting FUS procedures such as neuromodulation, and works by encoding ultrasound-induced displacements into the phase of MR images. However, it can require long scan times to cover a volume of tissue, especially when minimizing the FUS dose during targeting is paramount. To simultaneously minimize scan time and the FUS duty cycle, a 2-min three-dimensional (3D) reduced-FOV spin echo ARFI scan with two-dimensional undersampling was implemented at 3T with a FUS duty cycle of 0.85%. The 3D k-space sampling scheme incorporated uniform undersampling in one phase-encoded axis and partial Fourier (PF) sampling in the other. The scan interleaved FUS-on and FUS-off data collection to improve displacement map quality via a joint low-rank image reconstruction. Experiments in agarose and graphite phantoms and living macaque brains for neuromodulation and blood-brain barrier opening studied the effects of the sampling and reconstruction strategy on the acquisition, and evaluated its repeatability and accuracy.

Results: In the phantom, the distances between displacement centroids of 10 prospective reconstructions and a fully sampled reference were below 1 mm. In in vivo brain, the distances between centroids ranged from 1.3 to 2.1 mm. Results in phantom and in vivo brain both showed that the proposed method can recover the FUS focus compared to slower fully sampled scans.

Conclusion: The proposed 3D MR-ARFI reduced-FOV method enables rapid imaging of the FUS focus while maintaining a low FUS duty cycle.

Keywords: 3D; MR-ARFI; MRI; focused-ultrasound; low-rank; reduced-FOV.

Figure 1.

a: The 3D rFOV MR-ARFI sequence images a rectangular cube sized to cover the entire focus along the FUS axial dimension. b Timing diagram of the 3D reduced-FOV (rFOV) spin-echo ARFI sequence which uses multi-shot EPI with an echo train length of 3. Unipolar motion-encoding gradients (MEGs) were placed before and after the 180° pulse, the 180° pulse was applied to the in-plane EPI phase-encoded dimension (y) to reduce the FOV, and the ultrasound emission was alternated on or off between TRs. The ultrasound was started 1.5 ms before the beginning of the MEGs. c: The proposed k-space undersampling scheme. The top colored blocks illustrate the ordering of the ky segments, which yields three 3D k-space datasets with complementary undersampling patterns (y^ON+, y^ON− and y^OFF), as illustrated by the k_y-k_z phase encoding patterns at the bottom. The FUS pulses were synchronized with the first MEG (odd ky lines) or the second MEG (even ky lines) to obtain positive and negative motion-encoded phases. The partial Fourier direction was alternated between TRs. d: Perpendicular k-space dataset slices illustrate how the root-flipped refocusing pulse applied an approximately quadratic phase that spread out k-space energy in the ky direction, making that dimension amenable to uniform R = 2 undersampling, while the k_z dimension was better suited to partial Fourier sampling.

Figure 2.

Flowchart of Low-rank image reconstruction. Step a - b: At each iteration, the k-space datasets for the three images are segmented into blocks that are stretched to form a Block Hankel matrix; Step c: That matrix is singular value-thresholded and converted back to estimated images; Step d - f: One magnitude image Im was calculated by taking the first singular component of SVD of three images (FUS ON, +; FUS ON, −; FUS-OFF) and then was applied to replace the magnitudes of the current image estimates with unchanging phases; Step g: The originally acquired k-space data were reinserted into the recovered data to enforce data self-consistency.

Figure 3.

Experimental setup for phantom (left) and macaque imaging (right).

Figure 4.

Middle axial and sagittal slices of reduced-FOV images compared with full-FOV high-resolution structural scans of in vivo macaque brain (top) and a brain-tissue mimicking phantom (bottom). The axial plane was selected by the sequence’s 180° RF pulse and the sagittal plane was selected by its 90° RF pulse.

Figure 5.

Phantom displacement maps reconstructed from retrospectively undersampled data with different sampling settings (from top to bottom): Fully-sampled, R = 2 only, R = 2 and PF = 0.67, R = 2 and PF = 0.67 but without joint reconstruction of the FUS-OFF images. The subfigure on the right shows the position of the displacement maps shown on the left in the larger phantom, overlaid on a full-FOV axial image.

Figure 6.

Macaque displacement maps overlaid on reconstructed magnitude images with a midbrain focus for neuromodulation. The right figure shows the position of the zoomed-in displacement maps on the left in the axial plane (US x-y) of the whole brain.

Figure 7.

Macaque displacement maps overlaid on reconstructed magnitude images with a focus positioned in cortical grey matter for blood-brain barrier opening. The right figure shows the position of the zoomed-in displacement maps on the left in the axial plane (US x-y) of whole brain.

Figure 8.

Gadolinium-based signal changes at the region of blood-brain barrier disruption overlaid on a T₁-weighted image. The blue contour line indicates the 0.5-μm isocontour of the focus shown in Figure 7.