Accelerating joint relaxation-diffusion MRI by integrating time division multiplexing and simultaneous multi-slice (TDM-SMS) strategies.

Purpose: To accelerate the acquisition of relaxation-diffusion imaging by integrating time-division multiplexing (TDM) with simultaneous multi-slice (SMS) for EPI and evaluate imaging quality and diffusion measures.

Methods: The time-division multiplexing (TDM) technique and SMS method were integrated to achieve a high slice-acceleration (e.g.

Diffusion-weighted magnetic resonance imaging in rat kidney using two-dimensional navigated, interleaved echo-planar imaging at 7.0 T.

The purpose of this study was to investigate the feasibility of two-dimensional (2D) navigated, interleaved multishot echo-planar imaging (EPI) to enhance kidney diffusion-weighted imaging (DWI) in rats at 7.0 T. Fully sampled interleaved four-shot EPI with 2D navigators was tailored for kidney DWI (Sprague-Dawley rats, n = 7) on a 7.

A 31-channel integrated "AC/DC" B shim and radiofrequency receive array coil for improved 7T MRI.

Purpose: To test an integrated "AC/DC" array approach at 7T, where B inhomogeneity poses an obstacle for functional imaging, diffusion-weighted MRI, MR spectroscopy, and other applications.

Methods: A close-fitting 7T 31-channel (31-ch) brain array was constructed and tested using combined Rx and ΔB shim channels driven by a set of rapidly switchable current amplifiers. The coil was compared to a shape-matched 31-ch reference receive-only array for RF safety, signal-to-noise ratio (SNR), and inter-element noise correlation.

Accelerated diffusion and relaxation-diffusion MRI using time-division multiplexing EPI.

Purpose: To develop a time-division multiplexing echo-planar imaging (TDM-EPI) sequence for approximately two- to threefold acceleration when acquiring joint relaxation-diffusion MRI data with multiple TEs.

Methods: The proposed TDM-EPI sequence interleaves excitation and data collection for up to 3 separate slices at different TEs and uses echo-shifting gradients to disentangle the overlapping echo signals during the readout period. By properly arranging the sequence event blocks for each slice and adjusting the echo-shifting gradients, diffusion-weighted images from separate slices can be acquired.

In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution.

We present a whole-brain in vivo diffusion MRI (dMRI) dataset acquired at 760 μm isotropic resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single healthy participant. The creation of this benchmark dataset is possible through the synergistic use of advanced acquisition hardware and software including the high-gradient-strength Connectom scanner, a custom-built 64-channel phased-array coil, a personalized motion-robust head stabilizer, a recently developed SNR-efficient dMRI acquisition method, and parallel imaging reconstruction with advanced ghost reduction algorithm. With its unprecedented resolution, SNR and image quality, we envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance the understanding of human brain structures and connectivity.

Diets Varying in Carbohydrate Content Differentially Alter Brain Activity in Homeostatic and Reward Regions in Adults.

Background: Obesity has one of the highest refractory rates of all chronic diseases, in part because weight loss induced by calorie restriction, the first-line treatment for obesity, elicits biological adaptations that promote weight regain. Although acute feeding trials suggest a role for macronutrient composition in modifying brain activity related to hunger and satiety, relevance of these findings to weight-loss maintenance has not been studied.

Objectives: We investigated effects of weight-loss maintenance diets varying in macronutrient content on regional cerebral blood flow (rCBF) in brain regions involved in hunger and reward.

Robust autocalibrated structured low-rank EPI ghost correction.

Purpose: We propose and evaluate a new structured low-rank method for echo-planar imaging (EPI) ghost correction called Robust Autocalibrated LORAKS (RAC-LORAKS). The method can be used to suppress EPI ghosts arising from the differences between different readout gradient polarities and/or the differences between different shots. It does not require conventional EPI navigator signals, and is robust to imperfect autocalibration data.

Dynamic distortion correction for functional MRI using FID navigators.

Purpose: To develop a method for slice-wise dynamic distortion correction for EPI using rapid spatiotemporal B field measurements from FID navigators (FIDnavs) and to evaluate the efficacy of this new approach relative to an established data-driven technique.

Methods: A low-resolution reference image was used to create a forward model of FIDnav signal changes to enable estimation of spatiotemporal B inhomogeneity variations up to second order from measured FIDnavs. Five volunteers were scanned at 3 T using a 64-channel coil with FID-navigated EPI.

Simultaneous Motion and Distortion Correction Using Dual-Echo Diffusion-Weighted MRI.

Background And Purpose: Geometric distortions resulting from large pose changes reduce the accuracy of motion measurements and interfere with the ability to generate artifact-free information. Our goal is to develop an algorithm and pulse sequence to enable motion-compensated, geometric distortion compensated diffusion-weighted MRI, and to evaluate its efficacy in correcting for the field inhomogeneity and position changes, induced by large and frequent head motions.

Methods: Dual echo planar imaging (EPI) with a blip-reversed phase encoding distortion correction technique was evaluated in five volunteers in two separate experiments and compared with static field map distortion correction.

ROBUST AUTOCALIBRATED LORAKS FOR EPI GHOST CORRECTION.

Nyquist ghosts are a longstanding problem in a variety of fast MRI experiments that use echo-planar imaging (EPI). Recently, several structured low-rank matrix modeling approaches have been proposed that achieve state-of-the-art ghost-elimination, although the performance of these approaches is still inadequate in several important scenarios. We present a new structured low-rank matrix recovery ghost correction method that we call Robust Autocalibrated LORAKS (RAC-LORAKS).

Multipathway multi-echo (MPME) imaging: all main MR parameters mapped based on a single 3D scan.

Purpose: Quantitative parameter maps, as opposed to qualitative grayscale images, may represent the future of diagnostic MRI. A new quantitative MRI method is introduced here that requires a single 3D acquisition, allowing good spatial coverage to be achieved in relatively short scan times.

Methods: A multipathway multi-echo sequence was developed, and at least 3 pathways with 2 TEs were needed to generate T , T , T , B , and B maps.

Navigator-Free EPI Ghost Correction With Structured Low-Rank Matrix Models: New Theory and Methods.

Structured low-rank matrix models have previously been introduced to enable calibrationless MR image reconstruction from sub-Nyquist data, and such ideas have recently been extended to enable navigator-free echo-planar imaging (EPI) ghost correction. This paper presents a novel theoretical analysis which shows that, because of uniform subsampling, the structured low-rank matrix optimization problems for EPI data will always have either undesirable or non-unique solutions in the absence of additional constraints. This theory leads us to recommend and investigate problem formulations for navigator-free EPI that incorporate side information from either image-domain or k-space domain parallel imaging methods.

Dual-polarity slice-GRAPPA for concurrent ghost correction and slice separation in simultaneous multi-slice EPI.

Purpose: A ghost correction strategy for Simultaneous Multi-Slice (SMS) EPI methods that provides improved ghosting artifact reduction compared to conventional methods is presented. Conventional Nyquist ghost correction methods for SMS-EPI rely on navigator data that contain phase errors from all slices in the simultaneously acquired slice-group. These navigator data may contain spatially nonlinear phase differences near regions of B inhomogeneity, which violates the linear model employed by most EPI ghost correction algorithms, resulting in poor reconstructions.

Sampling and recovery of MRI data using low rank tensor models.

In this paper we investigate the utility of several low-rank models for recovery of Magnetic Resonance Imaging (MRI) data from limited sampling in the k - t space for dynamic imaging. In particular, for 3D temporal (2D space + time) MRI data we employ several tensor factorization techniques and assess the degree of dimensionality reduction, or compressibility, that can be obtained. This algebraic approach is more data adaptive, in contrast to existing compressed sensing (CS) based methods that exploit sparsity in a transform domain, such as wavelets or total variation.

Genetic and neural predictors of behavioral weight loss treatment: A preliminary study.

Objective: To examine neural mechanisms of action in behavioral weight loss treatment (BWL) and explore neural and genetic predictors of BWL.

Methods: Neural activation to milkshake receipt and genetics were compared in 17 women with obesity who received 12 weeks of BWL and 17 women who received no intervention. Participants were scanned twice using functional magnetic resonance imaging at baseline and 12 weeks.

Hybrid MRI-Ultrasound acquisitions, and scannerless real-time imaging.

Purpose: To combine MRI, ultrasound, and computer science methodologies toward generating MRI contrast at the high frame rates of ultrasound, inside and even outside the MRI bore.

Methods: A small transducer, held onto the abdomen with an adhesive bandage, collected ultrasound signals during MRI. Based on these ultrasound signals and their correlations with MRI, a machine-learning algorithm created synthetic MR images at frame rates up to 100 per second.

Hybrid Utrasound and MRI Acquisitions for High-Speed Imaging of Respiratory Organ Motion.

Magnetic Resonance (MR) imaging provides excellent image quality at a high cost and low frame rate. Ultrasound (US) provides poor image quality at a low cost and high frame rate. We propose an instance-based learning system to obtain the best of both worlds: high quality MR images at high frame rates from a low cost single-element US sensor.

Dual-polarity GRAPPA for simultaneous reconstruction and ghost correction of echo planar imaging data.

Purpose: The purpose of this study was to seek improved image quality from accelerated echo planar imaging (EPI) data, particularly at ultrahigh fields. Certain artifacts in EPI reconstructions can be attributed to nonlinear phase differences between data acquired using frequency-encoding gradients of alternating polarity. These errors appear near regions of local susceptibility gradients and typically cannot be corrected with conventional Nyquist ghost correction (NGC) methods.

Accurate field mapping in the presence of B0 inhomogeneities, applied to MR thermometry.

Purpose: To describe how B0 inhomogeneities can cause errors in proton resonance frequency (PRF) shift thermometry, and to correct for these errors.

Methods: With PRF thermometry, measured phase shifts are converted into temperature measurements through the use of a scaling factor proportional to the echo time, TE. However, B0 inhomogeneities can deform, spread, and translate MR echoes, potentially making the "true" echo time vary spatially within the imaged object and take on values that differ from the prescribed TE value.

Prospective motion correction using tracking coils.

Intracavity imaging coils provide higher signal-to-noise than surface coils and have the potential to provide higher spatial resolution in shorter acquisition times. However, images from these coils suffer from physiologically induced motion artifacts, as both the anatomy and the coils move during image acquisition. We developed prospective motion-correction techniques for intracavity imaging using an array of tracking coils.

Rapid full-brain fMRI with an accelerated multi shot 3D EPI sequence using both UNFOLD and GRAPPA.

The desire to understand complex mental processes using functional MRI drives development of imaging techniques that scan the whole human brain at a high spatial and temporal resolution. In this work, an accelerated multishot three-dimensional echo-planar imaging sequence is proposed to increase the temporal resolution of these studies. A combination of two modern acceleration techniques, UNFOLD and GRAPPA is used in the secondary phase encoding direction to reduce the scan time effectively.

Statistical noise analysis in GRAPPA using a parametrized noncentral Chi approximation model.

The characterization of the distribution of noise in the magnitude MR image is a very important problem within image processing algorithms. The Rician noise assumed in single-coil acquisitions has been the keystone for signal-to-noise ratio estimation, image filtering, or diffusion tensor estimation for years. With the advent of parallel protocols such as sensitivity encoding or Generalized Autocalibrated Partially Parallel Acquisitions that allow accelerated acquisitions, this noise model no longer holds.

Retrospectively gated cardiac cine imaging with temporal and spatial acceleration.

Parallel imaging methods are routinely used to accelerate the image acquisition process in cardiac cine imaging. The addition of a temporal acceleration method, whereby k-space is sampled differently for different time frames, has been shown in prior work to improve image quality as compared to parallel imaging by itself. However, such temporal acceleration strategies prove difficult to combine with retrospectively gated cine imaging.

3D GRASE PROPELLER: improved image acquisition technique for arterial spin labeling perfusion imaging.

Arterial spin labeling is a noninvasive technique that can quantitatively measure cerebral blood flow. While traditionally arterial spin labeling employs 2D echo planar imaging or spiral acquisition trajectories, single-shot 3D gradient echo and spin echo (GRASE) is gaining popularity in arterial spin labeling due to inherent signal-to-noise ratio advantage and spatial coverage. However, a major limitation of 3D GRASE is through-plane blurring caused by T(2) decay.

Robust EPI Nyquist ghost elimination via spatial and temporal encoding.

Nyquist ghosts are an inherent artifact in echo planar imaging acquisitions. An approach to robustly eliminate Nyquist ghosts is presented that integrates two previous Nyquist ghost correction techniques: temporal domain encoding (phase labeling for additional coordinate encoding: PLACE and spatial domain encoding (phased array ghost elimination: PAGE). Temporal encoding modulates the echo planar imaging acquisition trajectory from frame to frame, enabling one to interleave data to remove inconsistencies that occur between sampling on positive and negative gradient readouts.