2 research outputs found
Accelerated Reconstruction of Perfusion-Weighted MRI Enforcing Jointly Local and Nonlocal Spatio-temporal Constraints
Perfusion-weighted magnetic resonance imaging (MRI) is an imaging technique
that allows one to measure tissue perfusion in an organ of interest through the
injection of an intravascular paramagnetic contrast agent (CA). Due to a
preference for high temporal and spatial resolution in many applications, this
modality could significantly benefit from accelerated data acquisitions. In
this paper, we specifically address the problem of reconstructing perfusion MR
image series from a subset of k-space data. Our proposed approach is motivated
by the observation that temporal variations (dynamics) in perfusion imaging
often exhibit correlation across different spatial scales. Hence, we propose a
model that jointly penalizes the voxel-wise deviations in temporal gradient
images obtained based on a baseline, and the patch-wise dissimilarities between
the spatio-temporal neighborhoods of entire image sequence. We validate our
method on dynamic susceptibility contrast (DSC)-MRI and dynamic
contrast-enhanced (DCE)-MRI brain perfusion datasets acquired from 10 tumor
patients in total. We provide extensive analysis of reconstruction performance
and perfusion parameter estimation in comparison to state-of-the-art
reconstruction methods. Experimental results on clinical datasets demonstrate
that our reconstruction model can potentially achieve up to 8-fold acceleration
by enabling accurate estimation of perfusion parameters while preserving
spatial image details and reconstructing the complete perfusion time-intensity
curves (TICs).Comment: Submission to IEEE Transactions on Medical Imaging (August 2017
Designing contrasts for rapid, simultaneous parameter quantification and flow visualization with quantitative transient-state imaging
Magnetic resonance imaging (MRI) is a remarkably powerful diagnostic
technique: it generates wide-ranging information for the non-invasive study of
tissue anatomy and physiology. Complementary data is normally obtained in
separate measurements, either as contrast-weighted images, which are fast and
simple to acquire, or as quantitative parametric maps, which offer an absolute
quantification of underlying biophysical effects, such as relaxation times or
flow. Here, we demonstrate how to acquire and reconstruct data in a
transient-state with a dual purpose: 1 - to generate contrast-weighted images
that can be adjusted to emphasise clinically relevant image biomarkers;
exemplified with signal modulation according to flow to obtain angiography
information, and 2 - to simultaneously infer multiple quantitative parameters
with a single, highly accelerated acquisition. This is a achieved by
introducing three novel elements: a model that accounts for flowing blood, a
method for sequence design that incorporates both parameter encoding and signal
contrast, and the reconstruction of temporally resolved contrast-weighted
images. From these images we simultaneously obtain angiography projections and
multiple quantitative maps. By doing so, we increase the amount of clinically
relevant data without adding measurement time, creating new dimensions for
biomarker exploration and adding value to MR examinations for patients and
clinicians alike