Correcting vs resolving respiratory motion in accelerated free-running whole-heart radial flow MRI using focused navigation (fNAV)
Mariana Baginha da Lança Falcão1, Giulia M. C. Rossi1, Liliana Ma2,3, John Heerfordt1,4, Davide Piccini1,4, Jérôme Yerly1,5, Milan Prša6, Tobias Rutz7, Estelle Tenisch1, Michael Markl2,3, Matthias Stuber1,5, and Christopher W. Roy1
1Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 2Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States, 3Department of Biomedical Engineering, Northwestern University, Chicago, IL, United States, 4Advanced clinical imaging technology, Siemens Healthcare AG, Lausanne, Switzerland, 5Center for Biomedical Imaging (CIBM), Lausanne, Switzerland, 6Woman-Mother-Child Department, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 7Service of Cardiology, Centre de resonance magnétique cardiaque (CRMC), Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
Accelerating the already undersampled free-running radial flow sequence and reconstructing it using fNAV 4D flow showed relatively less degradation in overall reconstruction and flow errors across the different acceleration factors, when compared to 5D flow.
Figure 2. Velocity differences for increasing acceleration factors in one representative subject. A. MIP of the velocity encoded in the z direction (cm/s) for each acceleration factor (a=[1,1.25,1.67,2.5,5]) and reconstruction method (5D flow at end-expiration and 4D flow fNAV). B. Voxel-wise velocity bias (in cm/s) in Bland-Altman plot between 4D flow fNAV and 5D flow at (a=1). C. Bland-Altman plots of the voxel-wise velocity differences between datasets with (a=1) and (a=[1.25,1.67,2.5,5]) for both 5D flow and 4D flow fNAV.
Figure 1. Study outline for reconstructing a free-running flow dataset. A. Reconstruction of motion-resolved 5D flow data uses the motion information to reconstruct images at different respiratory and cardiac phases. B1. Cardiac motion-resolved and respiratory motion-corrected fNAV 4D flow reconstructions take advantage of the respiratory motion and of data derived PCMRA images to iteratively estimate the rigid displacement of the heart due to respiration for every readout (B2) and use auto-focusing to correct this displacement to the end-expiratory position(fNAV)10.