Visualization of small vibrations inside an MRI scanner using video motion amplification

Diffusion-weighted magnetic resonance imaging (DW-MRI) acquisition requires the application of strong magnetic field gradients, which can induce mechanical vibrations in tissues or phantoms, potentially leading to signal loss or degradation. A qualitative assessment of these vibrations would be valuable for quality assurance (QA). Conventional methods, such as piezoelectric accelerometers and laser interferometry, have limitations in their applicability and availability. There remains a need for a readily accessible method to detect and characterize these vibrations as part of a robust QA protocol.

The objective of this study is to investigate the feasibility of using motion amplification of high-speed video to assess vibrations during DW-MRI scanning.

A gel phantom simulating a human head was positioned supine within a head receive coil inside an MRI scanner. A 45-degree angled mirror was placed to visualize the phantom's face, while a high-speed camera, positioned outside the scanner, was used to record videos under two conditions: (1) the scanner in an idle state (still condition), and (2) during a DW-MRI scan (vibration condition). The recorded videos were processed using a motion amplification software tool to enhance subtle movements. The motion of multiple position markers affixed to the phantom was quantitatively analyzed.

No motion was visible to the naked eye under either still or scanning conditions. However, motion amplification revealed clear marker displacement during DW-MRI, with substantially smaller movement during scanner idling. Across all facial markers and directions (X (L-R), Y (A-P) and Z (I-S)), median root-mean-square displacement increased from 0.85 µm (range: 0.61-1.50 µm) at idle to 2.59 µm (2.04-4.31 µm) during DW-MRI scanning (b = 2500 s/mm²). Similarly, median peak-to-peak displacement rose from 7.71 µm (3.92-10.37 µm) to 18.47 µm (15.22-31.77 µm).

Motion amplification of high-speed video provides a viable method for detecting and analyzing vibrations during MRI scans. This approach could serve as a valuable tool for QA, offering an alternative to conventional vibration assessment techniques.