Velocity Spectrum Imaging using velocity encoding preparation pulses

TL;DR

This paper introduces Velocity Spectrum Imaging, a non-invasive MRI technique that measures water velocity distributions within tissues, enabling detailed analysis of fluid movement without contrast agents, with potential applications in neurodegenerative disease research.

Contribution

The paper presents a novel velocity encoding method using RF pulses and Fourier decoding to measure voxel-wise water velocity spectra in vivo.

Findings

Velocity distributions in phantoms matched theoretical expectations.

Human brain velocity spectra revealed anatomical features and CSF flow.

Most spins were in low-velocity ranges, indicating slow fluid movement.

Abstract

Purpose: The goal of this article is to introduce a technique to measure the velocity distribution of water inside each voxel of an MR image. The method is based on the use of motion sensitizing gradients with changing first moment to encode velocity. As such, it is completely non-invasive and requires no contrast injections. Methods: The technique consists of acquiring a series of images preceded by preparatory RF pulses that encode velocity information, analogously to k-space encoding. The velocity distribution can be decoded via the Fourier transform. We demonstrate its use on a simple flow phantom with known flow characteristics. We demonstrate the technique on the brains of five human participants from whom we collected the velocity distribution along each of the three laboratory axes. Results: Velocity distribution measurements on simple phantoms yielded velocity distributions consistent with theory. Human velocity spectra identified specific anatomical features at different velocity bins. The largest fraction of spins was in the lowest velocity bands. Movement in the CSF spaces could be clearly identified at different velocity bands. Conclusion: Velocity Spectrum Imaging has great potential as a tool to study the movement of fluids in the human body without contrast agents. In addition to a useful tool for validating computational fluid dynamic models in vivo, it can be used to study the complex movement of water in the glymphatic system and its involvement in neurodegenerative disorders. However, further development is needed to probe the velocity spectrum in the ultra-low velocity regime of the perivascular spaces.