Toward Contact-Free Motion Sensing Technique in Low-Field MRI Using Beat Pilot Tone
Low-field magnetic resonance imaging (MRI) suffers from fundamentally low signal-to-noise ratio (SNR), which is typically mitigated by acquiring multiple sets of imaging data and averaging them. However, this approach lengthens the scan time and can make images highly susceptible to motion artifacts. In this article, a novel contact-free radio frequency (RF) motion sensor beat pilot tone (BPT), which has high temporal resolution and is easy to be integrated into both MR system and imaging workflow, was first introduced in a 0.25 T permanent C-shaped MRI system. We improved the portability of BPT by integrating it into a 10 cm × 5 cm × 2 cm device and retained its adjustability in power and frequency. We compared BPT with another contact-free motion sensing technology, pilot tone (PT), for detecting the same motion. The results indicate that the motion modulation achieved by BPT is over six times that of PT, demonstrating that BPT has higher detection sensitivity. A phantom experiment was performed to suggest BPT has no adverse impact on imaging. We conducted series of in vivo experiments and demonstrated that BPT has the ability to detect different motion patterns, such as shaking and nodding head motion, respiratory motion, and cardiac motion. With BPT signal guidance, we successfully reconstructed motion-resolved images of a head scan under in-plane motion and abdominal imaging under free-breathing. SNR of images is higher than previous low-field images, and the motion artifacts are reduced, which shows the potential for wide application of BPT in low-field MRI.
Authors
- Suen Chen (ORCID: https://orcid.org/0009-0005-6308-2626)
- Sijie Zhong (ORCID: https://orcid.org/0009-0007-5668-5298)
- Yueqi Qiu (ORCID: https://orcid.org/0009-0005-7499-2983)
- Suma Anand (ORCID: https://orcid.org/0000-0003-0311-3978)
- Michael Lustig (ORCID: https://orcid.org/0000-0002-4794-221X)
- Zhiyong Zhang (ORCID: https://orcid.org/0000-0001-8809-9639)
- Hao Chen (ORCID: https://orcid.org/0000-0002-2924-4661)
- Haoyu Sun (ORCID: https://orcid.org/0009-0006-8138-5951)
Institutions
- Shanghai Jiao Tong University (CN)
- University of California, Berkeley (US)
Publication Details
- Journal
- IEEE Transactions on Instrumentation and Measurement
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tim.2025.3529065
- Citations
- 1
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Shanghai Science and Technology Development Foundation
- National Natural Science Foundation of China