Free-Breathing Ungated Radial Simultaneous Multi-Slice Cardiac T1 Mapping.

Background: Modified Look-Locker imaging (MOLLI) T1 mapping sequences are acquired during breath-holding and require ECG gating with consistent R-R intervals, which is problematic for patients with atrial fibrillation (AF). Consequently, there is a need for a free-breathing and ungated framework for cardiac T1 mapping.

Purpose: To develop and evaluate a free-breathing ungated radial simultaneous multi-slice (SMS) cardiac T1 mapping (FURST) framework.

Arterial Input Function (AIF) Correction Using AIF Plus Tissue Inputs with a Bi-LSTM Network.

The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time-concentration curve of a contrast agent. Inaccurate AIFs can significantly affect perfusion quantification. When only saturated and biased AIFs are measured, this work investigates multiple ways of leveraging tissue curve information, including using AIF + tissue curves as inputs and optimizing the loss function for deep neural network training.

Technical note: Accuracy and precision of T2 and T2* with a gradient-echo spin-echo (GESE) sequence for cardiac imaging.

Background: The use of a gradient echo spin echo (GESE) method to obtain rapid T2 and T2* estimation in the heart has been proposed. The effect of acquisition parameter settings on T2 and T2* bias and precision have not been investigated in depth.

Purpose: To understand factors impacting the quantification of T2 and T2* values with a gradient echo spin echo (GESE) method using echo planar imaging (EPI) readouts in a reduced field of view acquisition.

Quantitative myocardial perfusion with a hybrid 2D simultaneous multi-slice sequence.

Purpose: To evaluate a novel 2D simultaneous multi-slice (SMS) myocardial perfusion acquisition and compare directly to a published quantitative 3D stack-of-stars (SoS) acquisition.

Methods: A hybrid saturation recovery radial 2D SMS sequence following a single saturation was created for the quantification of myocardial blood flow (MBF). This sequence acquired three slices simultaneously and generated an arterial input function (AIF) using the first 24 rays.

Accelerated cardiac T1 mapping with recurrent networks and cyclic, model-based loss.

Background: Using the spin-lattice relaxation time (T1) as a biomarker, the myocardium can be quantitatively characterized using cardiac T1 mapping. The modified Look-Locker inversion (MOLLI) recovery sequences have become the standard clinical method for cardiac T1 mapping. However, the MOLLI sequences require an 11-heartbeat breath-hold that can be difficult for subjects, particularly during exercise or pharmacologically induced stress.

Jointly estimating parametric maps of multiple diffusion models from undersampled q-space data: A comparison of three deep learning approaches.

Purpose: While advanced diffusion techniques have been found valuable in many studies, their clinical availability has been hampered partly due to their long scan times. Moreover, each diffusion technique can only extract a few relevant microstructural features. Using multiple diffusion methods may help to better understand the brain microstructure, which requires multiple expensive model fittings.

Deep learning for radial SMS myocardial perfusion reconstruction using the 3D residual booster U-net.

Purpose: To develop an end-to-end deep learning solution for quickly reconstructing radial simultaneous multi-slice (SMS) myocardial perfusion datasets with comparable quality to the pixel tracking spatiotemporal constrained reconstruction (PT-STCR) method.

Methods: Dynamic contrast enhanced (DCE) radial SMS myocardial perfusion data were obtained from 20 subjects who were scanned at rest and/or stress with or without ECG gating using a saturation recovery radial CAIPI turboFLASH sequence. Input to the networks consisted of complex coil combined images reconstructed using the inverse Fourier transform of undersampled radial SMS k-space data.

Simultaneous multi-slice image reconstruction using regularized image domain split slice-GRAPPA for diffusion MRI.

The main goal of this work is to improve the quality of simultaneous multi-slice (SMS) reconstruction for diffusion MRI. We accomplish this by developing an image domain method that reaps the benefits of both SENSE and GRAPPA-type approaches and enables image regularization in an optimization framework. We propose a new approach termed regularized image domain split slice-GRAPPA (RI-SSG), which establishes an optimization framework for SMS reconstruction.

Initial investigation of free-breathing 3D whole-heart stress myocardial perfusion MRI.

Myocardial first-pass perfusion imaging with MRI is well-established clinically. However, it is potentially weakened by limited myocardial coverage compared to nuclear medicine. Clinical evaluations of whole-heart MRI perfusion by 3D methods, while promising, have to date had the limit of breathhold requirements at stress.

Whole-heart, ungated, free-breathing, cardiac-phase-resolved myocardial perfusion MRI by using Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state (CRIMP).

Purpose: To develop a whole-heart, free-breathing, non-electrocardiograph (ECG)-gated, cardiac-phase-resolved myocardial perfusion MRI framework (CRIMP; Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state) and test its quantification feasibility.

Methods: CRIMP used interleaved radial simultaneous multi-slice (SMS) slice groups to cover the whole heart in 9 or 12 short-axis slices. The sequence continuously acquired data without magnetization preparation, ECG gating or breath-holding, and captured multiple cardiac phases.

Coil-combined split slice-GRAPPA for simultaneous multi-slice diffusion MRI.

Objective: To develop a kernel optimization method called coil-combined split slice-GRAPPA (CC-SSG) to improve the accuracy of the reconstructed coil-combined images for simultaneous multi-slice (SMS) diffusion weighted imaging (DWI) data.

Methods: The CC-SSG method optimizes the tuning parameters in the k-space SSG kernels to achieve an optimal trade-off between the intra-slice artifact and inter-slice leakage after the root-sum-of-squares (rSOS) coil combining of the de-aliased SMS DWI data. A detailed analysis is conducted to evaluate the contributions of the intra-slice artifact and inter-slice leakage to the total reconstruction error after coil combining.

Quantitative 3D myocardial perfusion with an efficient arterial input function.

Purpose: The purpose of this study was to further develop and combine several innovative sequence designs to achieve quantitative 3D myocardial perfusion. These developments include an optimized 3D stack-of-stars readout (150 ms per beat), efficient acquisition of a 2D arterial input function, tailored saturation pulse design, and potential whole heart coverage during quantitative stress perfusion.

Theory And Methods: All studies were performed free-breathing on a Prisma 3T MRI scanner.

Predicting Motor Outcomes in Stroke Patients Using Diffusion Spectrum MRI Microstructural Measures.

Improved understanding of neuroimaging signal changes and their relation to patient outcomes after ischemic stroke is needed to improve ability to predict motor improvement and make therapy recommendations. The posterior limb of the internal capsule (PLIC) is a hub of afferent and efferent motor signaling and this work proposes new, image-based methods for prognosis based on interhemispheric differences in the PLIC. In this work, nine acute supratentorial ischemic stroke patients with motor impairment received a baseline, 203-direction diffusion brain MRI and a clinical assessment 3-12 days post-stroke and were compared to nine age-matched healthy controls.

Feasibility of multiple-view myocardial perfusion MRI using radial simultaneous multi-slice acquisitions.

Purpose: Dynamic contrast enhanced MRI of the heart typically acquires 2-4 short-axis (SA) slices to detect and characterize coronary artery disease. This acquisition scheme is limited by incomplete coverage of the left ventricle. We studied the feasibility of using radial simultaneous multi-slice (SMS) technique to achieve SA, 2-chamber and/or 4-chamber long-axis (2CH LA and/or 4CH LA) coverage with and without electrocardiography (ECG) gating using a motion-robust reconstruction framework.

Simultaneous NODDI and GFA parameter map generation from subsampled q-space imaging using deep learning.

Purpose: To develop a robust multidimensional deep-learning based method to simultaneously generate accurate neurite orientation dispersion and density imaging (NODDI) and generalized fractional anisotropy (GFA) parameter maps from undersampled q-space datasets for use in stroke imaging.

Methods: Traditional diffusion spectrum imaging (DSI) capable of producing accurate NODDI and GFA parameter maps requires hundreds of q-space samples which renders the scan time clinically untenable. A convolutional neural network (CNN) was trained to generated NODDI and GFA parameter maps simultaneously from 10× undersampled q-space data.

Effect of slice excitation profile on ungated steady state cardiac perfusion imaging.

In cardiac perfusion imaging, choice of flip angle is an important factor for steady state acquisition. This work focuses on presenting an analytical framework for understanding how non-ideal slice excitation profiles affect contrast in ungated 2D steady state cardiac perfusion studies, and to study a technique for estimating flip angle that maximizes enhanced/unenhanced myocardial contrast-to-noise ratio (CNR) in single slice and multi-slice acquisitions. A numerical simulation of ungated 2D golden ratio radial spoiled gradient echo (SPGR) was created that takes into consideration the actual (Bloch simulated) slice excitation profile.

Estimating extraction fraction and blood flow by combining first-pass myocardial perfusion and T1 mapping results.

Background: Quantifying myocardial perfusion is complicated by the complexity of pharmacokinetic model being used and the reliability of perfusion parameter estimates. More complex modeling provides more information about the underlying physiology, but too many parameters in complex models introduce a new problem of reliable estimation. To overcome the problem of multiple parameters, we have developed a technique that combines knowledge from two different cardiac magnetic resonance (MR) imaging techniques: dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and T1 mapping.

Validation of highly accelerated real-time cardiac cine MRI with radial k-space sampling and compressed sensing in patients at 1.5T and 3T.

Purpose: To validate an optimal 12-fold accelerated real-time cine MRI pulse sequence with radial k-space sampling and compressed sensing (CS) in patients at 1.5T and 3T.

Methods: We used two strategies to reduce image artifacts arising from gradient delays and eddy currents in radial k-space sampling with balanced steady-state free precession readout.

Technical Note: Evaluation of pre-reconstruction interpolation methods for iterative reconstruction of radial k-space data.

Purpose: To evaluate the use of three different pre-reconstruction interpolation methods to convert non-Cartesian k-space data to Cartesian samples such that iterative reconstructions can be performed more simply and more rapidly.

Methods: Phantom as well as cardiac perfusion radial datasets were reconstructed by four different methods. Three of the methods used pre-reconstruction interpolation once followed by a fast Fourier transform (FFT) at each iteration.

Rapid rest/stress regadenoson ungated perfusion CMR for detection of coronary artery disease in patients with atrial fibrillation.

Cardiovascular magnetic resonance (CMR) perfusion has been established as a useful imaging modality for the detection of coronary artery disease (CAD). However, there are several limitations when applying standard, ECG-gated stress/rest perfusion CMR to patients with atrial fibrillation (AF). In this study we investigate an approach with no ECG gating and a rapid rest/stress perfusion protocol to determine its accuracy for detection of CAD in patients with AF.

Radial simultaneous multi-slice CAIPI for ungated myocardial perfusion.

Objective: Simultaneous multi-slice (SMS) imaging is a slice acceleration technique that acquires multiple slices in the same time as a single slice. Radial controlled aliasing in parallel imaging results in higher acceleration (radial CAIPIRINHA or CAIPI) is a promising SMS method with less severe slice aliasing artifacts as compared to its Cartesian counterpart. Here we use radial CAIPI with data undersampling and constrained reconstruction to improve the utility of ungated cardiac perfusion acquisitions.

Compressed sensing for rapid late gadolinium enhanced imaging of the left atrium: A preliminary study.

Current late gadolinium enhancement (LGE) imaging of left atrial (LA) scar or fibrosis is relatively slow and requires 5-15min to acquire an undersampled (R=1.7) 3D navigated dataset. The GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) based parallel imaging method is the current clinical standard for accelerating 3D LGE imaging of the LA and permits an acceleration factor ~R=1.

Interstudy repeatability of self-gated quantitative myocardial perfusion MRI.

Purpose: To evaluate the interstudy repeatability of multislice quantitative cardiovascular magnetic resonance myocardial blood flow (MBF), myocardial perfusion reserve (MPR), and extracellular volume (ECV). A unique saturation recovery self-gated acquisition was used for the perfusion scans.

Materials And Methods: An ungated golden angle radial turboFLASH pulse sequence was used to scan 10 subjects on two separate days on a 3T scanner.

MRI reconstruction of multi-image acquisitions using a rank regularizer with data reordering.

Purpose: To improve rank constrained reconstructions for undersampled multi-image MRI acquisitions.

Methods: Motivated by the recent developments in low-rank matrix completion theory and its applicability to rapid dynamic MRI, a new reordering-based rank constrained reconstruction of undersampled multi-image data that uses prior image information is proposed. Instead of directly minimizing the nuclear norm of a matrix of estimated images, the nuclear norm of reordered matrix values is minimized.