High-resolution cardiac MRI using partially separable functions and weighted spatial smoothness regularization.

Imaging of cardiac morphology and functions in high spatiotemporal resolution using MRI is a challenging problem due to limited imaging speed and the inherent tradeoff between spatial resolution, temporal resolution, and signal-to-noise ratio (SNR). The partially separable function (PSF) model has been shown to achieve high spatiotemporal resolution but can lead to noisy reconstructions. This paper proposes a method to improve the SNR and reduce artifacts in PSF-based reconstructions through the use of anatomical constraints. These anatomical constraints are obtained from a high-SNR image of composite (k, t)-space data (summed along the time axis) and used to regularize the PSF reconstruction. The method has been evaluated on experimental data of rat hearts to achieve 390 εm in-plane resolution and 15 ms temporal resolution.

First-pass perfusion cardiac MRI using the Partially Separable Functions model with generalized support.

Dynamic imaging methods based on the Partially Separable Functions (PSF) model have been used to perform ungated cardiac MRI, and the critical parameter determining the quality of the reconstructed images is the order, L, of the PSF model. This work extends previous methods by increasing L in the cardiac region to improve the ability of the PSF model to represent complex spatiotemporal signals. The resulting higher order PSF model is fit to sparse (k, t)-space data using spatial-spectral support, spatial-eigenbasis support, and spectral sparsity constraints. This new method is demonstrated in the context of 2D first-pass perfusion MRI in a healthy rat heart.

Real-time cardiac MRI using prior spatial-spectral information.

Cardiac MRI performed while the patient is breathing is typically achieved using non-real-time techniques such as ECG triggering with respiratory gating; however, modern dynamic imaging techniques are beginning to enable this type of imaging in real-time. One of these dynamic imaging techniques is based on forming a Partially Separable Function (PSF) model of the data, but the model fitting process is known to be sensitive even when truncated SVD regularization is used. As a result, physiologically meaningless artifacts can appear in the dynamic images when the total number of measurements is limited. To address this issue, the dynamic imaging problem is formulated as a generalized Tikhonov regularization problem with the PSF model as a component of the forward data model, and a penalty function is used to introduce spatial-spectral prior information. This new method both reduces data acquisition requirements and improves stability relative to the original PSF based method when applied to cardiac MRI.

Sensitive and automated detection of iron-oxide-labeled cells using phase image cross-correlation analysis.

Superparamagnetic iron oxide (SPIO) nanoparticles are increasingly being used to noninvasively track cells, target specific molecules and monitor gene expression in vivo. Contrast changes that are subtle relative to intrinsic sources of contrast present a significant detection challenge. Here, we describe a postprocessing algorithm, called Phase map cross-correlation Detection and Quantification (PDQ), with the purpose of automating identification and quantification of localized accumulations of SPIO agents. The method is designed to sacrifice little flexibility - it works on previously acquired data and allows the use of conventional high-SNR pulse sequences with no extra scan time. We first investigated the theoretical detection limits of PDQ using a simulated dipole field. This method was then applied to three-dimensional (3D) MRI data sets of agarose gel containing isolated dipoles and ex vivo transplanted allogenic rat hearts infiltrated by numerous iron-oxide-labeled macrophages as a result of organ rejection. A simulated dipole field showed this method to be robust in very low signal-to-noise ratio images. Analysis of agarose gel and allogenic rat heart shows that this method can automatically identify and count dipoles while visualizing their biodistribution in 3D renderings. In the heart, this information was used to calculate a quantitative index that may indicate its degree of cellular infiltration.

Real-time cardiac MRI without triggering, gating, or breath holding.

State-of-the-art cardiac MRI can perform real-time 2D scans without cardiac triggering during a single breath hold; however, real-time cardiac MRI in rats is difficult due to the high heart rate (330 bpm) and presence of respiratory motion. These challenges are overcome by using a dynamic imaging method based on Partially Separable Function (PSF) theory with an acceleration factor of 256. This paper demonstrates that this method can be used in the study of transplanted rat hearts for both anatomical and perfusion applications. The study was carried out with a 200 microm in-plane resolution with a 17.2 msec temporal resolution, and the results show improved spatial resolution (2x) and reduced acquisition time (3x) relative to Electrocardiogram (ECG) triggered, respiratory gated cine imaging.