Time‐resolved contrast‐enhanced imaging with isotropic resolution and broad coverage using an undersampled 3D projection trajectory

Abstract

Time-resolved contrast-enhanced 3D MR angiography (MRA) methods have gained in popularity but are still limited by the tradeoff between spatial and temporal resolution. A method is presented that greatly reduces this tradeoff by employing undersampled 3D projection reconstruction trajectories. The variable density k-space sampling intrinsic to this sequence is combined with temporal k-space interpolation to provide time frames as short as 4 s. This time resolution reduces the need for exact contrast timing while also providing dynamic information. Spatial resolution is determined primarily by the projection readout resolution and is thus isotropic across the FOV, which is also isotropic. Although undersampling the outer regions of k-space introduces aliased energy into the image, which may compromise resolution, this is not a limiting factor in highcontrast applications such as MRA. Results from phantom and volunteer studies are presented demonstrating isotropic resolution, broad coverage with an isotropic field of view (FOV), minimal projection reconstruction artifacts, and temporal information. In one application, a single breath-hold exam covering the entire pulmonary vasculature generates high-resolution, isotropic imaging volumes depicting the bolus passage. Contrast-enhanced magnetic resonance angiography (MRA) of the chest or abdomen is typically accomplished by completing the scan in a single breath-hold to limit respiratory artifacts, and during the first pass of a contrast agent for maximum arterial enhancement (1,2). As the arterial-to-venous delay decreases, timing the bolus arrival and rapid scanning become more important. Time-resolved methods have become of increasing interest as they can mitigate the need for precise bolus timing, in addition to providing important dynamic information (3,4). Repetitive 3D Cartesian acquisitions of k-space acquired at high speed have recently generated dynamic MRA exams of the pulmonary vasculature (5,6), and when combined with correlation postprocessing, they can be used to calculate arterial and venous image volumes (7). Time-resolved methods generally require further compromises between temporal resolution, spatial resolution, and field of view (FOV) (8). Speed is generated by acquiring less throughplane resolution or by a partial acquisition of k-space in all three dimensions.Sparse sampling of k-space, analyzed generally in Ref. 9, has increased resolution per unit time in cases wherein the artifacts from aliased energy are acceptable due to high signal contrast. Peters et al. (10) increased in-plane resolution by a factor of 4 relative to Cartesian techniques by sampling the in-plane k-space dimensions with projections, and the slice dimension with Cartesian encoding. As is well known in computed tomography (CT), the readout resolution of the projections determines the resolution of the image, and the total number of acquired projections determines the level of artifact (11). Imaging time with these hybrid project reconstruction (PR) methods, termed PRojecti...

Highly constrained backprojection for time‐resolved MRI

“…In the case of time-resolved contrast-enhanced VIPR studies, the streak artifacts have been reduced using a spatial frequency dependent (Tornado) filter (3) in which the temporal window is increased as the radial distance from the center of k-space increases. This reduces streak artifacts but causes vessel edges to have a reduced temporal bandwidth and to appear too early in the reconstructed time sequence.…”

Efficient sample density estimation by combining gridding and an optimized kernel

“…Because each of the trajectories tested is a center-out trajectory, a rough approximation of the density is that of a 3D projection trajectory, where the weighting is proportional to the radius squared (6). This approximation, defined as W PR = |k| 2 , was used with subsequent iterations of the grid method performed with R = 2.1.…”

x‐f choice: Reconstruction of undersampled dynamic MRI by data‐driven alias rejection applied to contrast‐enhanced angiography

“…1 ϭC 1 Ϫ1 s 0 [3] where the inverse used is the standard pseudoinverse. The sensitivity matrix is continually reduced and the new solution vectors are calculated by operating the inverse of the reduced matrix on s 0 .…”