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.

Improving temporal resolution of pulmonary perfusion imaging in rats using the partially separable functions model.

Dynamic contrast-enhanced MRI (or DCE-MRI) is a useful tool for measuring blood flow and perfusion, and it has found use in the study of pulmonary perfusion in animal models. However, DCE-MRI experiments are difficult in small animals such as rats. A recently developed method known as Interleaved Radial Imaging and Sliding window-keyhole (IRIS) addresses this problem by using a data acquisition scheme that covers (k,t)-space with data acquired from multiple bolus injections of a contrast agent. However, the temporal resolution of IRIS is limited by the effects of temporal averaging inherent in the sliding window and keyhole operations. This article describes a new method to cover (k,t)-space based on the theory of partially separable functions (PSF). Specifically, a sparse sampling of (k,t)-space is performed to acquire two data sets, one with high-temporal resolution and the other with extended k-space coverage. The high-temporal resolution training data are used to determine the temporal basis functions of the PSF model, whereas the other data set is used to determine the spatial variations of the model. The proposed method was validated by simulations and demonstrated by an experimental study. In this particular study, the proposed method achieved a temporal resolution of 32 msec.

Dynamic imaging of speech and swallowing with MRI.

Dynamic imaging with MRI holds great promise for visualizing soft tissue structures in the oropharyngeal region during speech and swallowing studies. However, MRI suffers from historically slow acquisition speed and sensitivity to significant magnetic susceptibility differences in this region. In this work, we describe our efforts in creating high temporal resolution, serial acquisitions of the muscles of the oropharyngeal region. We describe our imaging approach that leads to acquisition rates of up to 21 frames per second. Additionally, we compare the serial acquisition scheme to gated acquisitions that suffer from temporal blur due to limited repeatability of the dynamic action.

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.

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.