Combined free-running four-dimensional anatomical and flow magnetic resonance imaging with native contrast using Synchronization of Neighboring Acquisitions by Physiological Signals
AUTHORS: Falcão M. B. L., Mackowiak A. L. C., Rossi G. M. C., Prša M., Tenisch E., Rumac S., Bacher M., Rutz T., Van Heeswijk R. B., Speier P., Markl M., Bastiaansen J. A. M., Stuber M., Roy C. W.
Journal of Cardiovascular Magnetic Resonance, 26(1): 101006, 15 February 2024
ABSTRACT
Background
Four-dimensional (4D) flow magnetic resonance imaging (MRI) often relies on the injection of gadolinium- or iron-oxide-based contrast agents to improve vessel delineation. In this work, a novel technique is developed to acquire and reconstruct 4D flow data with excellent dynamic visualization of blood vessels but without the need for contrast injection. Synchronization of Neighboring Acquisitions by Physiological Signals (SyNAPS) uses pilot tone (PT) navigation to retrospectively synchronize the reconstruction of two free-running three-dimensional radial acquisitions, to create co-registered anatomy and flow images.
Methods
Thirteen volunteers and two Marfan syndrome patients were scanned without contrast agent using one free-running fast interrupted steady-state (FISS) sequence and one free-running phase-contrast MRI (PC-MRI) sequence. PT signals spanning the two sequences were recorded for retrospective respiratory motion correction and cardiac binning. The magnitude and phase images reconstructed, respectively, from FISS and PC-MRI, were synchronized to create SyNAPS 4D flow datasets. Conventional two-dimensional (2D) flow data were acquired for reference in ascending (AAo) and descending aorta (DAo). The blood-to-myocardium contrast ratio, dynamic vessel area, net volume, and peak flow were used to compare SyNAPS 4D flow with Native 4D flow (without FISS information) and 2D flow. A score of 0–4 was given to each dataset by two blinded experts regarding the feasibility of performing vessel delineation.
Results
Conclusion
BibTex
https://doi.org/10.1016/j.jocmr.2024.101006
Module: MRI