In vivo human cardiac fibre architecture estimation using shape-based diffusion tensor processing.

In vivo imaging of cardiac 3D fibre architecture is still a practical and methodological challenge. However it potentially provides important clinical insights, for example leading to a better understanding of the pathophysiology and the follow up of ventricular remodelling after therapy. Recently, the acquisition of 2D multi-slice Diffusion Tensor Images (DTI) of the in vivo human heart has become feasible, yielding a limited number of slices with relatively poor signal-to-noise ratios.

Motion corrected compressed sensing for free-breathing dynamic cardiac MRI.

Compressed sensing (CS) has been demonstrated to accelerate MRI acquisitions by reconstructing sparse images of good quality from highly undersampled data. Motion during MR scans can cause inconsistencies in k-space data, resulting in strong motion artifacts in the reconstructed images. For CS to be useful in these applications, motion correction techniques need to be combined with the undersampled reconstruction.

Perfusion phantom: An efficient and reproducible method to simulate myocardial first-pass perfusion measurements with cardiovascular magnetic resonance.

The aim of this article is to describe a novel hardware perfusion phantom that simulates myocardial first-pass perfusion allowing comparisons between different MR techniques and validation of the results against a true gold standard. MR perfusion images were acquired at different myocardial perfusion rates and variable doses of gadolinium and cardiac output. The system proved to be sensitive to controlled variations of myocardial perfusion rate, contrast agent dose, and cardiac output.

Voxel-wise quantification of myocardial perfusion by cardiac magnetic resonance. Feasibility and methods comparison.

The purpose of this study is to enable high spatial resolution voxel-wise quantitative analysis of myocardial perfusion in dynamic contrast-enhanced cardiovascular MR, in particular by finding the most favorable quantification algorithm in this context. Four deconvolution algorithms--Fermi function modeling, deconvolution using B-spline basis, deconvolution using exponential basis, and autoregressive moving average modeling--were tested to calculate voxel-wise perfusion estimates. The algorithms were developed on synthetic data and validated against a true gold-standard using a hardware perfusion phantom.

TRIO a technique for reconstruction using intensity order: application to undersampled MRI.

Long acquisition times are still a limitation for many applications of magnetic resonance imaging (MRI), specially in 3-D and dynamic imaging. Several undersampling reconstruction techniques have been proposed to overcome this problem. These techniques are based on acquiring less samples than specified by the Nyquist criterion and estimating the nonacquired data by using some sort of prior information.

In vivo human 3D cardiac fibre architecture: reconstruction using curvilinear interpolation of diffusion tensor images.

In vivo imaging of the cardiac 3D fibre architecture is still a challenge, but it would have many clinical applications, for instance to better understand pathologies and to follow up remodelling after therapy. Recently, cardiac MRI enabled the acquisition of Diffusion Tensor images (DTI) of 2D slices. We propose a method for the complete 3D reconstruction of cardiac fibre architecture in the left ventricular myocardium from sparse in vivo DTI slices.

Model-based reconstruction for cardiac cine MRI without ECG or breath holding.

This paper describes an acquisition and reconstruction strategy for cardiac cine MRI that does not require the use of electrocardiogram or breath holding. The method has similarities with self-gated techniques as information about cardiac and respiratory motion is derived from the imaging sequence itself; here, by acquiring the center k-space line at the beginning of each segment of a balanced steady-state free precession sequence. However, the reconstruction step is fundamentally different: a generalized reconstruction by inversion of coupled systems is used instead of conventional gating.

Distribution and fibre field similarity mapping of the human anterior commissure fibres by diffusion tensor imaging.

Object: The anterior commissure is a critical interhemispheric pathway in animals, yet its connections in humans are not clearly understood. Its distribution has shown to vary greatly between species, and it is thought that in humans it may convey axons from a larger territory than previously thought. The aim was to use an anatomical mapping tool to look at the anterior commissure fibres and to compare the distribution findings with published anatomical understanding.

Pharmacokinetic modeling of delayed gadolinium enhancement in the myocardium.

Delayed contrast-enhanced magnetic resonance imaging (DCE-MRI) provides prognostic information by delineating regions of myocardial scar. The mechanism of this delayed enhancement in myocardial infarctions (MIs) is hypothesized to result from altered kinetics and changes in the volumes of distribution in the myocardium. Pharmacokinetic models with two and three compartments were fitted to the concentration-time curves of dynamic contrast-enhanced MRI data obtained from five patients with known MI.

Reconstruction of undersampled dynamic images by modeling the motion of object elements.

Dynamic MRI is restricted due to the time required to obtain enough data to reconstruct the image sequence. Several undersampled reconstruction techniques have been proposed to reduce the acquisition time. In most of these techniques the nonacquired data are recovered by modeling the temporal information as varying pixel intensities represented in time or in temporal frequencies.

Nonlinear phase correction of navigated multi-coil diffusion images.

Cardiac pulsatility causes a nonrigid motion of the brain. In multi-shot diffusion imaging this leads to spatially varying phase changes that must be corrected. A conjugate gradient based reconstruction is presented that includes phase changes measured using two-dimensional navigator echoes, coil sensitivity information, navigator-determined weightings, and data from multiple coils and averages.

Beyond the g-factor limit in sensitivity encoding using joint histogram entropy.

The maximum practical speed-up that can be achieved using parallel imaging methods is widely accepted to be limited by g-factor noise. An approximate expression for the g-factor noise as a function of the principal eigenvector of the inverse sensitivity matrix is derived. This formulation allows g-factor enhanced noise to be reduced by a constrained optimization procedure with joint image histogram entropy between a reference image and a SENSE image as an image quality metric.