  Purpose: Whole-heart MRA techniques typically target pre-determined motion
states and address cardiac and respiratory dynamics independently. We propose a
novel fast reconstruction algorithm, applicable to ungated free-running
sequences, that leverages inherent similarities in the acquired data to avoid
such physiological constraints.
  Theory and Methods: The proposed SIMilarity-Based Angiography (SIMBA) method
clusters the continuously acquired k-space data in order to find a
motion-consistent subset that can be reconstructed into a motion-suppressed
whole-heart MRA. Free-running 3D radial datasets from six ferumoxytol-enhanced
scans of pediatric cardiac patients and twelve non-contrast scans of healthy
volunteers were reconstructed with a non-motion-suppressed regridding of all
the acquired data (All Data), our proposed SIMBA method, and a previously
published free-running framework (FRF) that uses cardiac and respiratory
self-gating and compressed sensing. Images were compared for blood-myocardium
interface sharpness, contrast ratio, and visibility of coronary artery ostia.
  Results: Both the fast SIMBA reconstruction (~20s) and the FRF provided
significantly higher blood-myocardium sharpness than All Data (P<0.001). No
significant difference was observed among the former two. Significantly higher
blood-myocardium contrast ratio was obtained with SIMBA compared to All Data
and FRF (P<0.01). More coronary ostia could be visualized with both SIMBA and
FRF than with All Data (All Data: 4/36, SIMBA: 30/36, FRF: 33/36, both P<0.001)
but no significant difference was found between the first two.
  Conclusion: The combination of free-running sequences and the fast SIMBA
reconstruction, which operates without a priori assumptions related to
physiological motion, forms a simple workflow for obtaining whole-heart MRA
with sharp anatomical structures.
