Prospectively accelerated dynamic speech magnetic resonance imaging at 3 T using a self-navigated spiral-based manifold regularized scheme.

This work develops and evaluates a self-navigated variable density spiral (VDS)-based manifold regularization scheme to prospectively improve dynamic speech magnetic resonance imaging (MRI) at 3 T. Short readout duration spirals (1.3-ms long) were used to minimize sensitivity to off-resonance.

Reducing MRI-guided radiotherapy planning and delivery times via efficient leaf sequencing and segment shape optimization algorithms.

Extended treatment session times are an operational limitation in magnetic resonance imaging guided adaptive radiotherapy (MRIgRT). In this study a novel leaf sequencing algorithm called optimal fluence levels (OFL) and an optimization algorithm called pseudo gradient descent (PGD) are evaluated with respect to plan quality, beam complexity, and the ability to reduce treatment session times on the Elekta Unity MRIgRT system.Ten total patients were evaluated on this Institutional Review Board approved study: three with prostate cancer, three with oligometastases, two with pancreatic cancer, and two with liver cancer.

DYNAMIC IMAGING USING DEEP BILINEAR UNSUPERVISED LEARNING (DEBLUR).

Bilinear models such as low-rank and compressed sensing, which decompose the dynamic data to spatial and temporal factors, are powerful and memory efficient tools for the recovery of dynamic MRI data. These methods rely on sparsity and energy compaction priors on the factors to regularize the recovery. Motivated by deep image prior, we introduce a novel bilinear model, whose factors are regularized using convolutional neural networks.

DEEP GENERATIVE STORM MODEL FOR DYNAMIC IMAGING.

We introduce a novel generative smoothness regularization on manifolds (SToRM) model for the recovery of dynamic image data from highly undersampled measurements. The proposed generative framework represents the image time series as a smooth non-linear function of low-dimensional latent vectors that capture the cardiac and respiratory phases. The non-linear function is represented using a deep convolutional neural network (CNN).

Dynamic Imaging Using a Deep Generative SToRM (Gen-SToRM) Model.

We introduce a generative smoothness regularization on manifolds (SToRM) model for the recovery of dynamic image data from highly undersampled measurements. The model assumes that the images in the dataset are non-linear mappings of low-dimensional latent vectors. We use the deep convolutional neural network (CNN) to represent the non-linear transformation.

MULTI-ECHO RECOVERY WITH FIELD INHOMOGENEITY COMPENSATION USING STRUCTURED LOW-RANK MATRIX COMPLETION.

Echo-planar imaging (EPI), which is the main workhorse of functional MRI, suffers from field inhomogeneity-induced geometric distortions. The amount of distortion is proportional to the readout duration, which restricts the maximum achievable spatial resolution. The spatially varying nature of the decay makes it challenging for EPI schemes with a single echo time to obtain good sensitivity to functional activations in different brain regions.

Three-Dimensional GRE T mapping of the brain using tailored variable flip-angle scheduling.

Purpose: To introduce a new approach called tailored variable flip-angle (VFA) scheduling for SNR-efficient 3D T mapping of the brain using a magnetization-prepared gradient-echo sequence.

Methods: Simulations were used to assess the relative SNR efficiency, quantitative accuracy, and spatial blurring of tailored VFA scheduling for T mapping of brain tissue compared with magnetization-prepared angle-modulated partitioned k-space spoiled gradient-echo snapshots (MAPSS), a state-of-the-art technique for accurate 3D gradient-echo T mapping. Simulations were also used to calculate optimal imaging parameters for tailored VFA scheduling versus MAPSS, without and with nulling of CSF.

Ventilation defect percent in helium-3 magnetic resonance imaging as a biomarker of severe outcomes in asthma.

Ventilation defect percent (VDP) measured in asthmatics with hyperpolarized helium-3 MRI was more strongly associated with ED visits and hospitalizations due to asthma exacerbation than were conventional biomarkers of lung function and inflammation.

Semiautomated Ventilation Defect Quantification in Exercise-induced Bronchoconstriction Using Hyperpolarized Helium-3 Magnetic Resonance Imaging: A Repeatability Study.

Rationale And Objectives: This study aimed to compare the performance of a semiautomated ventilation defect segmentation approach, adaptive K-means, with manual segmentation of hyperpolarized helium-3 magnetic resonance imaging in subjects with exercise-induced bronchoconstriction (EIB).

Materials And Methods: Six subjects with EIB underwent hyperpolarized helium-3 magnetic resonance imaging and spirometry tests at baseline, post exercise, and recovery over two separate visits. Ventilation defects were analyzed by two methods.

Functional imaging of the lungs with gas agents.

This review focuses on the state-of-the-art of the three major classes of gas contrast agents used in magnetic resonance imaging (MRI)-hyperpolarized (HP) gas, molecular oxygen, and fluorinated gas--and their application to clinical pulmonary research. During the past several years there has been accelerated development of pulmonary MRI. This has been driven in part by concerns regarding ionizing radiation using multidetector computed tomography (CT).

Oxygen-enhanced 3D radial ultrashort echo time magnetic resonance imaging in the healthy human lung.

The purpose of this work was to use 3D radial ultrashort echo time (UTE) MRI to perform whole-lung oxygen-enhanced (OE) imaging in humans. Eight healthy human subjects underwent two 3D radial UTE MRI acquisitions (TE = 0.08 ms): one while breathing 21% O2 and the other while breathing 100% O2.

Hyperpolarized Helium-3 MRI of exercise-induced bronchoconstriction during challenge and therapy.

Purpose: To investigate the utility of hyperpolarized He-3 MRI for detecting regional lung ventilated volume (VV) changes in response to exercise challenge and leukotriene inhibitor montelukast, human subjects with exercise induced bronchoconstriction (EIB) were recruited. This condition is described by airway constriction following exercise leading to reduced forced expiratory volume in 1 second (FEV1) coinciding with ventilation defects on hyperpolarized He-3 MRI.

Materials And Methods: Thirteen EIB subjects underwent spirometry and He-3 MRI at baseline, postexercise, and postrecovery at multiple visits.

Markers of vascular perturbation correlate with airway structural change in asthma.

Rationale: Air trapping and ventilation defects on imaging are characteristics of asthma. Airway wall thickening occurs in asthma and is associated with increased bronchial vascularity and vascular permeability. Vascular endothelial cell products have not been explored as a surrogate to mark structural airway changes in asthma.

Exercise-induced bronchoconstriction: reproducibility of hyperpolarized 3He MR imaging.

Purpose: To quantitatively evaluate interday, interreader, and intersite agreement of readers of hyperpolarized helium 3 (HPHe) MR images in patients with exercise-induced bronchoconstriction.

Materials And Methods: This HIPAA-compliant, institutional review board approved study included 13 patients with exercise-induced bronchoconstriction. On two separate days, HPHe MR imaging of the lungs was performed at baseline, immediately after a 10-minute exercise challenge (postchallenge), and 45 minutes after exercise (recovery).