Spatio-temporal bandwidth-based acquisition for dynamic contrast-enhanced magnetic resonance imaging.
OBJECTIVE
To develop a k-space formalism that provides a rationale for the design of variable-rate acquisition schemes for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).


METHODS
The formalism, termed spatio-temporal bandwidth-based (STBB) analysis, is demonstrated using a priori modeling of object and enhancement characteristics typically observed in DCE-MRI of breast tumors. A temporally enhancing lesion is considered as a two-dimensional (2D) space-time object that possesses a corresponding spatio-temporal (k(y)-k(t)) energy spectrum. The k(y)-k(t) space is segmented based on a threshold such that the total spectral energy in a finite number of k-space samples, constrained by the imaging experiment, is maximized. This thresholded map contains a set of spatial and corresponding temporal sampling prescriptions. These prescriptions are used in designing an acquisition scheme that is adequate for a range of contrast-enhancing breast lesions. The STBB scheme is compared to an equivalent "keyhole" acquisition, in terms of quantification of enhancement rate, K(trans), extracellular volume fraction, nu(e), and spatial fidelity. We chose object sizes Npix = 2, 5, 10, 15, 20, and 30 pixels and enhancement rates K(trans) = 1.5, 1, 0.6, 0.4, 0.3, and 0.2 minute(-1), and nu(e) was held at 0.3.


RESULTS
The STBB scheme results in more accurate estimation of the rate and extracellular volume fraction parameters when the object size is small (two and five pixels) and the enhancement rates are rapid (1.5 and 1 minute(-1)), compared to the keyhole acquisition. The STBB scheme provides higher spatial fidelity for very small objects. For large object and slow enhancements, the keyhole and STBB scheme perform comparably.


CONCLUSIONS
We have demonstrated an intuitive formalism applicable to DCE-MRI for a set of targeted/anticipated dynamic events as well as spatial features. This formalism can be extended to any dynamic imaging condition, and a corresponding variable-rate acquisition scheme can be designed.
Krishnan
Sumati
S
Department of Radiology-MRI, University of Michigan Health System, Ann Arbor, Michigan 48109-0030, USA.
Chenevert
Thomas L
TL
D003198:Computer Simulation; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008962:Models, Theoretical; D019047:Phantoms, Imaging