MR-ARFI and Beyond: Characterizing the Temporal Dynamics of Acoustic Radiation Force in Human Brain

Magnetic Resonance Acoustic Radiation Force Imaging (MR-ARFI) encodes focused ultrasound (FUS)-induced tissue displacements to MR phase shifts. Because these phase shifts are small, optimizing displacement sensitivity and minimizing motion artifacts requires characterization of the temporal dynamics of acoustic radiation force (ARF). Beyond sequence design, such characterization enables MR-ARFI to serve as a probe of brain viscoelastic behavior and can inform the design of therapeutic ultrasound pulsing schemes by quantifying how rapidly tissue deforms and relaxes.

We developed a dynamic model assuming a gamma-variate impulse response for ARF(t), with time constant (τ) to be estimated. A single-shot spin echo ARFI acquisition with a bipolar motion encoding gradient (MEG) was implemented, incorporating retrospective corrections for head motion and physiological noise. A 500 kHz FUS pulse was applied in on/off blocks while systematically varying the timing between the MEG and sonication. The resulting phase time series were fit to the model to estimate τ in five human participants. To assess sensitivity to tissue stiffness, τ was additionally measured in two customized gelatin phantoms of differing stiffness, characterized independently by MR elastography (MRE).

The average measured time constant in human participants was τ= 3.7 ± 0.27 ms. Comparing the two phantoms, the stiffer phantom exhibited a shorter τ (3.0-3.5 ms) than the softer phantom (4.0-4.5 ms), which tracked the MRE-derived Kelvin-Voigt viscoelastic time constants. In addition, the peak ARFI displacement was lower in the stiffer phantom (0.17 vs 0.74 μm for the less stiff phantom), and a broader displacement focal spot size (FWHM 22 mm vs 15 mm).

This time-series approach with motion and physiological noise corrections validates an MR-based technique capable of characterizing the brain's temporal response to sonication-induced mechanical forces, providing a foundation for optimizing the design of ultrasound pulsing schemes for ARFI, as well as for future studies of brain biomechanics.