Universal Sampling Denoising (USD) for noise mapping and noise removal of non-Cartesian MRI.

Random matrix theory (RMT) combined with principal component analysis has resulted in a widely used MPPCA noise mapping and denoising algorithm, that utilizes the redundancy in multiple acquisitions and in local image patches. RMT-based denoising relies on the uncorrelated identically distributed noise. This assumption breaks down after regridding of non-Cartesian sampling.

Feasibility of Accelerated Prostate Diffusion-Weighted Imaging on 0.55 T MRI Enabled With Random Matrix Theory Denoising.

Introduction: Prostate cancer diffusion weighted imaging (DWI) MRI is typically performed at high-field strength (3.0 T) in order to overcome low signal-to-noise ratio (SNR). In this study, we demonstrate the feasibility of prostate DWI at low field enabled by random matrix theory (RMT)-based denoising, relying on the MP-PCA algorithm applied during image reconstruction from multiple coils.

Time-dependent diffusivity and kurtosis in phantoms and patients with head and neck cancer.

Purpose: To assess the reliability of measuring diffusivity, diffusional kurtosis, and cellular-interstitial water exchange time with long diffusion times (100-800 ms) using stimulated-echo DWI.

Methods: Time-dependent diffusion MRI was tested on two well-established diffusion phantoms and in 5 patients with head and neck cancer. Measurements were conducted using an in-house diffusion-weighted STEAM-EPI pulse sequence with multiple diffusion times at a fixed TE on three scanners.

Reproducibility of the Standard Model of diffusion in white matter on clinical MRI systems.

Estimating intra- and extra-axonal microstructure parameters, such as volume fractions and diffusivities, has been one of the major efforts in brain microstructure imaging with MRI. The Standard Model (SM) of diffusion in white matter has unified various modeling approaches based on impermeable narrow cylinders embedded in locally anisotropic extra-axonal space. However, estimating the SM parameters from a set of conventional diffusion MRI (dMRI) measurements is ill-conditioned.

Combined diffusion-relaxometry microstructure imaging: Current status and future prospects.

Microstructure imaging seeks to noninvasively measure and map microscopic tissue features by pairing mathematical modeling with tailored MRI protocols. This article reviews an emerging paradigm that has the potential to provide a more detailed assessment of tissue microstructure-combined diffusion-relaxometry imaging. Combined diffusion-relaxometry acquisitions vary multiple MR contrast encodings-such as b-value, gradient direction, inversion time, and echo time-in a multidimensional acquisition space.

Assessment of myofiber microstructure changes due to atrophy and recovery with time-dependent diffusion MRI.

Current clinical MRI evaluation of musculature largely focuses on nonquantitative assessments (including T1-, T2- and PD-weighted images), which may vary greatly between imaging systems and readers. This work aims to determine the efficacy of a quantitative approach to study the microstructure of muscles at the cellular level with the random permeable barrier model (RPBM) applied to time-dependent diffusion tensor imaging (DTI) for varying diffusion time. Patients (N = 15, eight males and seven females) with atrophied calf muscles due to immobilization of one leg in a nonweight-bearing cast, were enrolled after providing informed consent.

Measurement of cellular-interstitial water exchange time in tumors based on diffusion-time-dependent diffusional kurtosis imaging.

Purpose: To assess the feasibility of using diffusion-time-dependent diffusional kurtosis imaging (tDKI) to measure cellular-interstitial water exchange time (τ ) in tumors, both in animals and in humans.

Methods: Preclinical tDKI studies at 7 T were performed with the GL261 glioma model and the 4T1 mammary tumor model injected into the mouse brain. Clinical studies were performed at 3 T with women who had biopsy-proven invasive ductal carcinoma.

Improved Task-based Functional MRI Language Mapping in Patients with Brain Tumors through Marchenko-Pastur Principal Component Analysis Denoising.

Background Functional MRI improves preoperative planning in patients with brain tumors, but task-correlated signal intensity changes are only 2%-3% above baseline. This makes accurate functional mapping challenging. Marchenko-Pastur principal component analysis (MP-PCA) provides a novel strategy to separate functional MRI signal from noise without requiring user input or prior data representation.

Training a neural network for Gibbs and noise removal in diffusion MRI.

Purpose: To develop and evaluate a neural network-based method for Gibbs artifact and noise removal.

Methods: A convolutional neural network (CNN) was designed for artifact removal in diffusion-weighted imaging data. Two implementations were considered: one for magnitude images and one for complex images.

Exploratory study of geometric distortion correction of prostate diffusion-weighted imaging using B map acquisition.

Background: Evaluation of prostate MRI relies on diffusion-weighted imaging (DWI), commonly distorted by susceptibility artifacts, thereby creating a need for approaches to correct such distortion.

Purpose: To compare geometric distortion on prostate MRI between standard DWI and a geometric distortion correction method for DWI described as static distortion correction DWI (SDC DWI).

Study Type: Retrospective case study.

Characterization of prostate microstructure using water diffusion and NMR relaxation.

For many pathologies, early structural tissue changes occur at the cellular level, on the scale of micrometers or tens of micrometers. Magnetic resonance imaging (MRI) is a powerful non-invasive imaging tool used for medical diagnosis, but its clinical hardware is incapable of reaching the cellular length scale directly. In spite of this limitation, microscopic tissue changes in pathology can potentially be captured indirectly, from macroscopic imaging characteristics, by studying water diffusion.

Characteristics of the Most Recently Awarded Magnetic Resonance Imaging Patents in the United States.

Purpose: To characterize recent magnetic resonance imaging (MRI) technical development and innovation based on data regarding MRI-related patents awarded in 2016.

Methods: The US Patent and Trademark Office website was searched for patents awarded in 2016 and an abstract containing "magnetic resonance." Patent characteristics were summarized.

Validation of surface-to-volume ratio measurements derived from oscillating gradient spin echo on a clinical scanner using anisotropic fiber phantoms.

A diffusion measurement in the short-time surface-to-volume ratio (S/V) limit (Mitra et al., Phys Rev Lett. 1992;68:3555) can disentangle the free diffusion coefficient from geometric restrictions to diffusion.

Time-Dependent Diffusion in Prostate Cancer.

Objective: Prior studies in prostate diffusion-weighted magnetic resonance imaging (MRI) have largely explored the impact of b-value and diffusion directions on estimated diffusion coefficient D. Here we suggest varying diffusion time, t, to study time-dependent D(t) in prostate cancer, thereby adding an extra dimension in the development of prostate cancer biomarkers.

Methods: Thirty-eight patients with peripheral zone prostate cancer underwent 3-T MRI using an external-array coil and a diffusion-weighted image sequence acquired for b = 0, as well as along 12 noncollinear gradient directions for b = 500 s/mm using stimulated echo acquisition mode (STEAM) diffusion tensor imaging (DTI).

In vivo measurement of membrane permeability and myofiber size in human muscle using time-dependent diffusion tensor imaging and the random permeable barrier model.

The time dependence of the diffusion coefficient is a hallmark of tissue complexity at the micrometer level. Here we demonstrate how biophysical modeling, combined with a specifically tailored diffusion MRI acquisition performing diffusion tensor imaging (DTI) for varying diffusion times, can be used to determine fiber size and membrane permeability of muscle fibers in vivo. We describe the random permeable barrier model (RPBM) and its assumptions, as well as the details of stimulated echo DTI acquisition, signal processing steps, and potential pitfalls.

In vivo observation and biophysical interpretation of time-dependent diffusion in human white matter.

The presence of micrometer-level restrictions leads to a decrease of diffusion coefficient with diffusion time. Here we investigate this effect in human white matter in vivo. We focus on a broad range of diffusion times, up to 600 ms, covering diffusion length scales up to about 30 μm.