Accelerating cine‐MR imaging in mouse hearts using compressed sensing

Abstract

PurposeTo combine global cardiac function imaging with compressed sensing (CS) in order to reduce scan time and to validate this technique in normal mouse hearts and in a murine model of chronic myocardial infarction.Materials and MethodsTo determine the maximally achievable acceleration factor, fully acquired cine data, obtained in sham and chronically infarcted (MI) mouse hearts were 2–4-fold undersampled retrospectively, followed by CS reconstruction and blinded image segmentation. Subsequently, dedicated CS sampling schemes were implemented at a preclinical 9.4 T magnetic resonance imaging (MRI) system, and 2- and 3-fold undersampled cine data were acquired in normal mouse hearts with high temporal and spatial resolution.ResultsThe retrospective analysis demonstrated that an undersampling factor of three is feasible without impairing accuracy of cardiac functional parameters. Dedicated CS sampling schemes applied prospectively to normal mouse hearts yielded comparable left-ventricular functional parameters, and intra- and interobserver variability between fully and 3-fold undersampled data.ConclusionThis study introduces and validates an alternative means to speed up experimental cine-MRI without the need for expensive hardware. J. Magn. Reson. Imaging 2011. © 2011 Wiley Periodicals, Inc.

Accelerated self-gated UTE MRI of the murine heart

“…This allows for a reduction in scan time, or higher spatial or temporal resolution of the image series. A reconstruction algorithm that recently has received a lot of attention is Compressed Sensing (CS) [16][17][18]. The undersampled data obtained by the self-gated radial acquisition schemes used in this work, fits very well with the CS requirements.…”

Functional imaging of murine hearts using accelerated self-gated UTE cine MRI

“…Compressed sensing (CS) has proven a valuable technique for speeding up data acquisition in MRI by exploiting the compressibility of MR images [19][20][21][22]. The ability to transform the data to a sparse representation and the radial trajectory, which is used in Cine UTE imaging, fits very well with the sparsity and incoherence requirements for CS.…”

Magnetic resonance imaging of the regenerating neonatal mouse heart

“…Analysis of the navigator echo was performed as described previously 24 to yield k-space signals for 20 frames per slice, which were then subjected to CS-reconstruction as reported previously 25 , followed by isotropic zerofilling (factor of two), filtering (modified third-order Butterworth filter), and Fourier transformation. Examples for respiratory and cardiac traces obtained from the navigator signal are shown in Fig.…”