Imaging of osteoarthritis from the ankle through the midfoot.

Ankle, hindfoot, and midfoot osteoarthritis (OA) is most commonly posttraumatic and tends to become symptomatic in younger patients. It often results from instability due to insufficiency of supportive soft tissue structures, such as ligaments and tendons. Diagnostic imaging can be helpful to detect and characterize the distribution of OA, and to assess the integrity of these supportive structures, which helps determine prognosis and guide treatment.

Cancellation of streak artifacts in radial abdominal imaging using interference null space projection.

Purpose: In radial abdominal imaging, it has been commonly observed that signal from the arms cause streaks due to system imperfections. We previously introduced a streak removal technique (B-STAR), which is inherently spatially variant and limited to work in image space. In this work, we propose a spatially invariant streak cancellation technique (CACTUS), which can be applied in either image space or k-space and is compatible with iterative reconstructions.

Abdominal T2-Weighted Imaging and T2 Mapping Using a Variable Flip Angle Radial Turbo Spin-Echo Technique.

Background: T2 mapping is of great interest in abdominal imaging but current methods are limited by low resolution, slice coverage, motion sensitivity, or lengthy acquisitions.

Purpose: Develop a radial turbo spin-echo technique with refocusing variable flip angles (RADTSE-VFA) for high spatiotemporal T2 mapping and efficient slice coverage within a breath-hold and compare to the constant flip angle counterpart (RADTSE-CFA).

Study Type: Prospective technical efficacy.

Rapid high-resolution volumetric T mapping using a highly accelerated stack-of-stars Look Locker technique.

Purpose: To develop a fast volumetric T mapping technique.

Materials And Methods: A stack-of-stars (SOS) Look Locker technique based on the acquisition of undersampled radial data (>30× relative to Nyquist) and an efficient multi-slab excitation scheme is presented. A principal-component based reconstruction is used to reconstruct T maps.

Improving subspace constrained radial fast spin echo MRI using block matching driven non-local low rank regularization.

Subspace-constrained reconstruction methods restrict the relaxation signals (of size M) in the scene to a pre-determined subspace (of size K≪M) and allow multi-contrast imaging and parameter mapping from accelerated acquisitions. However, these constraints yield poor image quality at some imaging contrasts, which can impact the parameter mapping performance. Additional regularization such as the use of joint-sparse (JS) or locally-low-rank (LLR) constraints can help improve the recovery of these images but are not sufficient when operating at high acceleration rates.

A multi-scale residual network for accelerated radial MR parameter mapping.

A deep learning MR parameter mapping framework which combines accelerated radial data acquisition with a multi-scale residual network (MS-ResNet) for image reconstruction is proposed. The proposed supervised learning strategy uses input image patches from multi-contrast images with radial undersampling artifacts and target image patches from artifact-free multi-contrast images. Subspace filtering is used during pre-processing to denoise input patches.

An efficient 3D stack-of-stars turbo spin echo pulse sequence for simultaneous T2-weighted imaging and T2 mapping.

Purpose: To design a pulse sequence for efficient 3D T2-weighted imaging and T2 mapping.

Methods: A stack-of-stars turbo spin echo pulse sequence with variable refocusing flip angles and a flexible pseudorandom view ordering is proposed for simultaneous T2-weighted imaging and T2 mapping. An analytical framework is introduced for the selection of refocusing flip angles to maximize relative tissue contrast while minimizing T2 estimation errors and maintaining low specific absorption rate.

Radial streak artifact reduction using phased array beamforming.

Purpose: A new method for streak artifact reduction in radial MRI based on phased array filtering.

Theory: Radial imaging in applications that require large fields-of-view can be susceptible to streaking artifacts due to gradient nonlinearities. Coil removal methods prune the coils contributing the most to streaking artifacts at the expense of signal loss.

Rapid high-resolution T mapping using a highly accelerated radial steady-state free-precession technique.

Background: T mapping is often used in some clinical protocols. Existing techniques are limited in slice coverage, and/or spatial-temporal resolution, or require long acquisitions. Here we present a multi-slice inversion-recovery (IR) radial steady-state free precession (radSSFP) pulse sequence combined with a principal component (PC) based reconstruction that overcomes these limitations.

A multi-band double-inversion radial fast spin-echo technique for T2 cardiovascular magnetic resonance mapping of the heart.

Background: Double inversion recovery (DIR) fast spin-echo (FSE) cardiovascular magnetic resonance (CMR) sequences are used clinically for black-blood T2-weighted imaging. However, these sequences suffer from slice inefficiency due to the non-selective inversion pulses. We propose a multi-band (MB) encoded DIR radial FSE (MB-DIR-RADFSE) technique to simultaneously excite two slices.

Accelerated MR parameter mapping with a union of local subspaces constraint.

Purpose: A new reconstruction method for multi-contrast imaging and parameter mapping based on a union of local subspaces constraint is presented.

Theory: Subspace constrained reconstructions use a predetermined subspace to explicitly constrain the relaxation signals. The choice of subspace size impacts the approximation error vs noise-amplification tradeoff associated with these methods.

Validation of Peripheral Quantitative Computed Tomography-Derived Thigh Adipose Tissue Subcompartments in Young Girls Using a 3 T MRI Scanner.

The ability to assess skeletal muscle adipose tissue is important given the negative clinical implications associated with greater fat infiltration of the muscle. Computed tomography and magnetic resonance imaging (MRI) are highly accurate for measuring appendicular soft tissue and muscle composition, but have limitations. Peripheral quantitative computed tomography (pQCT) is an alternative that investigators find valuable because of its low radiation, fast scan time, and comparatively lower costs.

Reproducible automated breast density measure with no ionizing radiation using fat-water decomposition MRI.

Background: Increased breast density is a significant independent risk factor for breast cancer, and recent studies show that this risk is modifiable. Hence, breast density measures sensitive to small changes are desired.

Purpose: Utilizing fat-water decomposition MRI, we propose an automated, reproducible breast density measurement, which is nonionizing and directly comparable to mammographic density (MD).

Segmentation of the right ventricle in four chamber cine cardiac MR images using polar dynamic programming.

The four chamber plane is currently underutilized in the right ventricular segmentation community. Four chamber information can be useful to determine ventricular short axis stacks and provide a rough estimate of the right ventricle in short axis stacks. In this study, we develop and test a semi-automated technique for segmenting the right ventricle in four chamber cine cardiac magnetic resonance images.

Multiresolution imaging using golden angle stack-of-stars and compressed sensing for dynamic MR urography.

Purpose: To develop a novel multiresolution MRI methodology for accurate estimation of glomerular filtration rate (GFR) in vivo.

Materials And Methods: A three-dimensional golden-angle radial stack-of-stars (SoS) trajectory was used for data acquisition on a 3 Tesla MRI scanner. Multiresolution reconstruction and analysis was performed using arterial input function reconstructed at 1-s.

Dynamic Programming Using Polar Variance for Image Segmentation.

When using polar dynamic programming (PDP) for image segmentation, the object size is one of the main features used. This is because if size is left unconstrained the final segmentation may include high-gradient regions that are not associated with the object. In this paper, we propose a new feature, polar variance, which allows the algorithm to segment the objects of different sizes without the need for training data.

Task-based optimization of flip angle for fibrosis detection in T1-weighted MRI of liver.

Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. The current reference standard for diagnosing HF is biopsy followed by pathologist examination; however, this is limited by sampling error and carries a risk of complications. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads.

Volumetric MRI of the lungs during forced expiration.

Purpose: Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging.

T2 mapping of the heart with a double-inversion radial fast spin-echo method with indirect echo compensation.

Background: The abnormal signal intensity in cardiac T2-weighted images is associated with various pathologies including myocardial edema. However, the assessment of pathologies based on signal intensity is affected by the acquisition parameters and the sensitivities of the receiver coils. T2 mapping has been proposed to overcome limitations of T2-weighted imaging, but most methods are limited in spatial and/or temporal resolution.

Automated breast segmentation of fat and water MR images using dynamic programming.

Rationale And Objectives: To develop and test an algorithm that outlines the breast boundaries using information from fat and water magnetic resonance images.

Materials And Methods: Three algorithms were implemented and tested using registered fat and water magnetic resonance images. Two of the segmentation algorithms are simple extensions of the techniques used for contrast-enhanced images: one algorithm uses clustering and local gradient (CLG) analysis and the other algorithm uses a Hessian-based sheetness filter (HSF).

Pattern recognition for rapid T2 mapping with stimulated echo compensation.

Indirect echoes (such as stimulated echoes) are a source of signal contamination in multi-echo spin-echo T2 quantification and can lead to T2 overestimation if a conventional exponential T2 decay model is assumed. Recently, nonlinear least square fitting of a slice-resolved extended phase graph (SEPG) signal model has been shown to provide accurate T2 estimates with indirect echo compensation. However, the iterative nonlinear least square fitting is computationally expensive and the T2 map generation time is long.

Correcting partial volume effects in biexponential T2 estimation of small lesions.

Purpose: T2 mapping provides a quantitative approach for focal liver lesion characterization. For small lesions, a biexponential model should be used to account for partial volume effects (PVE). However, conventional biexponential fitting suffers from large uncertainty of the fitted parameters when noise is present.

T2 relaxometry with indirect echo compensation from highly undersampled data.

Purpose: To develop an algorithm for fast and accurate T2 estimation from highly undersampled multi-echo spin-echo data.

Methods: The algorithm combines a model-based reconstruction with a signal decay based on the slice-resolved extended phase graph (SEPG) model with the goal of reconstructing T2 maps from highly undersampled radial multi-echo spin-echo data with indirect echo compensation. To avoid problems associated with the nonlinearity of the SEPG model, principal component decomposition is used to linearize the signal model.

T2 mapping from highly undersampled data by reconstruction of principal component coefficient maps using compressed sensing.

Recently, there has been an increased interest in quantitative MR parameters to improve diagnosis and treatment. Parameter mapping requires multiple images acquired with different timings usually resulting in long acquisition times. While acquisition time can be reduced by acquiring undersampled data, obtaining accurate estimates of parameters from undersampled data is a challenging problem, in particular for structures with high spatial frequency content.

Automated registration of sequential breath-hold dynamic contrast-enhanced MR images: a comparison of three techniques.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly in use as an investigational biomarker of response in cancer clinical studies. Proper registration of images acquired at different time points is essential for deriving diagnostic information from quantitative pharmacokinetic analysis of these data. Motion artifacts in the presence of time-varying intensity due to contrast enhancement make this registration problem challenging.