Free‐breathing radial imaging using a pilot‐tone radiofrequency transmitter for detection of respiratory motion

• Published in: Magnetic resonance in medicine Vol. 85; no. 5; pp. 2672 - 2685
• Main Authors: Solomon, Eddy, Rigie, David S., Vahle, Thomas, Paška, Jan, Bollenbeck, Jan, Sodickson, Daniel K., Boada, Fernando E., Block, Kai Tobias, Chandarana, Hersh
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.05.2021
• Subjects: Breathing; Humans; Image Enhancement; Image processing; Image Processing, Computer-Assisted; Image quality; Image reconstruction; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Motion; Motion perception; motion‐resolved reconstruction; pilot‐tone; radial sampling; Radio frequency; Reference signals; Respiration; Respiratory-Gated Imaging Techniques; self‐navigation; XD‐GRASP; motion-resolved reconstruction; XD-GRASP; radial sampling; self-navigation; pilot-tone
• ISSN: 0740-3194; 1522-2594; 1522-2594
• DOI: 10.1002/mrm.28616

Purpose To describe an approach for detection of respiratory signals using a transmitted radiofrequency (RF) reference signal called Pilot‐Tone (PT) and to use the PT signal for creation of motion‐resolved images based on 3D stack‐of‐stars imaging under free‐breathing conditions. Methods This work explores the use of a reference RF signal generated by a small RF transmitter, placed outside the MR bore. The reference signal is received in parallel to the MR signal during each readout. Because the received PT amplitude is modulated by the subject’s breathing pattern, a respiratory signal can be obtained by detecting the strength of the received PT signal over time. The breathing‐induced PT signal modulation can then be used for reconstructing motion‐resolved images from free‐breathing scans. The PT approach was tested in volunteers using a radial stack‐of‐stars 3D gradient echo (GRE) sequence with golden‐angle acquisition. Results Respiratory signals derived from the proposed PT method were compared to signals from a respiratory cushion sensor and k‐space‐center‐based self‐navigation under different breathing conditions. Moreover, the accuracy was assessed using a modified acquisition scheme replacing the golden‐angle scheme by a zero‐angle acquisition. Incorporating the PT signal into eXtra‐Dimensional (XD) motion‐resolved reconstruction led to improved image quality and clearer anatomical depiction of the lung and liver compared to k‐space‐center signal and motion‐averaged reconstruction, when binned into 6, 8, and 10 motion states. Conclusion PT is a novel concept for tracking respiratory motion. Its small dimension (8 cm), high sampling rate, and minimal interaction with the imaging scan offers great potential for resolving respiratory motion.