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Purpose: To evaluate the feasibility and utility of a deep learning (DL)-based reconstruction for improving the SNR of hyperpolarized 129 Xe lung ventilation MRI., Methods: 129 Xe lung ventilation MRI data acquired from patients with asthma and/or chronic obstructive pulmonary disease (COPD) were retrospectively reconstructed with a commercial DL reconstruction pipeline at five different denoising levels. Quantitative imaging metrics of lung ventilation including ventilation defect percentage (VDP) and ventilation heterogeneity index (VH I ) were compared between each set of DL-reconstructed images and alternative denoising strategies including: filtering, total variation denoising and higher-order singular value decomposition. Structural similarity between the denoised and original images was assessed. In a prospective study, the feasibility of using SNR gains from DL reconstruction to allow natural-abundance xenon MRI was evaluated in healthy volunteers., Results: 129 Xe ventilation image SNR was improved with DL reconstruction when compared with conventionally reconstructed images. In patients with asthma and/or COPD, DL-reconstructed images exhibited a slight positive bias in ventilation defect percentage (1.3% at 75% denoising) and ventilation heterogeneity index (˜1.4) when compared with conventionally reconstructed images. Additionally, DL-reconstructed images preserved structural similarity more effectively than data denoised using alternative approaches. DL reconstruction greatly improved image SNR (greater than threefold), to a level that 129 Xe ventilation imaging using natural-abundance xenon appears feasible., Conclusion: DL-based image reconstruction significantly improves 129 Xe ventilation image SNR, preserves structural similarity, and leads to a minor bias in ventilation metrics that can be attributed to differences in the image sharpness. This tool should help facilitate cost-effective 129 Xe ventilation imaging with natural-abundance xenon in the future., (© 2024 GE Healthcare and The Author(s). Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Purpose: To develop a deep-learning model that leverages the spatial and temporal information from dynamic contrast-enhanced magnetic resonance (DCE MR) brain imaging in order to automatically estimate a vascular function (VF) for quantitative pharmacokinetic (PK) modeling., Methods: Patients with glioblastoma multiforme were scanned post-resection approximately every 2 months using a high spatial and temporal resolution DCE MR imaging sequence ( ≈ 5 s and ≈ 2 cm 3 ). A region over the transverse sinus was manually drawn in the dynamic T1-weighted images to provide a ground truth VF. The manual regions and their resulting VF curves were used to train a deep-learning model based on a 3D U-net architecture. The model concurrently utilized the spatial and temporal information in DCE MR images to predict the VF. In order to analyze the contribution of the spatial and temporal terms, different weighted combinations were examined. The manual and deep-learning predicted regions and VF curves were compared., Results: Forty-three patients were enrolled in this study and 155 DCE MR scans were processed. The 3D U-net was trained using a loss function that combined the spatial and temporal information with different weightings. The best VF curves were obtained when both spatial and temporal information were considered. The predicted VF curve was similar to the manual ground truth VF curves., Conclusion: The use of spatial and temporal information improved VF curve prediction relative to when only the spatial information is used. The method generalized well for unseen data and can be used to automatically estimate a VF curve suitable for quantitative PK modeling. This method allows for a more efficient clinical pipeline and may improve automation of permeability mapping., (© 2021 International Society for Magnetic Resonance in Medicine.)

Purpose: To develop and evaluate an efficient precontrast T 1 mapping technique suitable for quantitative high-resolution whole-brain dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI)., Methods: Variable flip angle (VFA) T 1 mapping was considered that provides 1 × 1 × 2 mm 3 resolution to match a recent high-resolution whole-brain DCE-MRI protocol. Seven FAs were logarithmically spaced from 1.5° to 15°. T 1 and M 0 maps were estimated using model-based reconstruction. This approach was evaluated using an anatomically realistic brain tumor digital reference object (DRO) with noise-mimicking 3T neuroimaging and fully sampled data acquired from one healthy volunteer. Methods were also applied on fourfold prospectively undersampled VFA data from 13 patients with high-grade gliomas., Results: T 1 -mapping precision decreased with undersampling factor R, althoughwhereas bias remained small before a critical R. In the noiseless DRO, T 1 bias was <25 ms in white matter (WM) and <11 ms in brain tumor (BT). T 1 standard deviation (SD) was <119.5 ms in WM (coefficient of variation [COV] ~11.0%) and <253.2 ms in BT (COV ~12.7%). In the noisy DRO, T 1 bias was <50 ms in WM and <30 ms in BT. For R ≤ 10, T 1 SD was <107.1 ms in WM (COV ~9.9%) and <240.9 ms in BT (COV ~12.1%). In the healthy subject, T 1 bias was <30 ms for R ≤ 16. At R = 4, T 1 SD was 171.4 ms (COV ~13.0%). In the prospective brain tumor study, T 1 values were consistent with literature values in WM and BT., Conclusion: High-resolution whole-brain VFA T 1 mapping is feasible with sparse sampling, supporting its use for quantitative DCE-MRI., (© 2021 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Purpose: To demonstrate the feasibility of integrating the magnetization transfer (MT) preparations required for inhomogeneous MT (ihMT) within an MPRAGE-style acquisition. Such a sequence allows for reduced power deposition and easy inclusion of other modules., Methods: An ihMT MPRAGE-style sequence (ihMTRAGE) was initially simulated to investigate acquisition of the 3D ihMT data sequentially, or in an interleaved manner. The ihMTRAGE sequence was implemented on a 3T clinical scanner to acquire ihMT data from the brain and spine., Results: Both simulations and in vivo data provided an ihMT signal that was significantly greater using a sequential ihMTRAGE acquisition, compared with an interleaved implementation. Comparison with a steady-state ihMT acquisition (defined as having one MT RF pulse between successive acquisition modules) demonstrated how ihMTRAGE allows for a reduction in average power deposition, or greater ihMT signal at equal average power deposition. Inclusion of a prospective motion-correction module did not significantly affect the ihMT signal obtained from regions of interest in the brain. The ihMTRAGE acquisition allowed combination with a spatial saturation module to reduce phase wrap artifacts in a cervical spinal cord acquisition., Conclusions: Use of preparations necessary for ihMT experiments within an MPRAGE-style sequence provides a useful alternative for acquiring 3D ihMT data. Compared with our steady-state implementation, ihMTRAGE provided reduced power deposition, while allowing use of the maximum intensity from off-resonance RF pulses. The 3D ihMTRAGE acquisition allowed combination of other modules with the preparation necessary for ihMT experiments, specifically motion compensation and spatial saturation modules., (© 2020 International Society for Magnetic Resonance in Medicine.)

Purpose: To develop and evaluate a model-based reconstruction framework for joint arterial input function (AIF) and kinetic parameter estimation from undersampled brain tumor dynamic contrast-enhanced MRI (DCE-MRI) data., Methods: The proposed method poses the tracer-kinetic (TK) model as a model consistency constraint, enabling the flexible inclusion of different TK models and TK solvers, and the joint estimation of the AIF. The proposed method is evaluated using an anatomic realistic digital reference object (DRO), and nine retrospectively down-sampled brain tumor DCE-MRI datasets. We also demonstrate application to 30-fold prospectively undersampled brain tumor DCE-MRI., Results: In DRO studies with up to 60-fold undersampling, the proposed method provided TK maps with low error that were comparable to fully sampled data and were demonstrated to be compatible with a third-party TK solver. In retrospective undersampling studies, this method provided patient-specific AIF with normalized root mean-squared-error (normalized by the 90th percentile value) less than 8% at up to 100-fold undersampling. In the 30-fold undersampled prospective study, the proposed method provided high-resolution whole-brain TK maps and patient-specific AIF., Conclusion: The proposed model-based DCE-MRI reconstruction enables the use of different TK solvers with a model consistency constraint and enables joint estimation of patient-specific AIF. TK maps and patient-specific AIF with high fidelity can be reconstructed at up to 100-fold undersampling in k,t-space. Magn Reson Med 79:2804-2815, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Purpose: The purpose of this work was to develop and evaluate a T 1 -weighted dynamic contrast enhanced (DCE) MRI methodology where tracer-kinetic (TK) parameter maps are directly estimated from undersampled (k,t)-space data., Theory and Methods: The proposed reconstruction involves solving a nonlinear least squares optimization problem that includes explicit use of a full forward model to convert parameter maps to (k,t)-space, utilizing the Patlak TK model. The proposed scheme is compared against an indirect method that creates intermediate images by parallel imaging and compressed sensing before to TK modeling. Thirteen fully sampled brain tumor DCE-MRI scans with 5-second temporal resolution are retrospectively undersampled at rates R = 20, 40, 60, 80, and 100 for each dynamic frame. TK maps are quantitatively compared based on root mean-squared-error (rMSE) and Bland-Altman analysis. The approach is also applied to four prospectively R = 30 undersampled whole-brain DCE-MRI data sets., Results: In the retrospective study, the proposed method performed statistically better than indirect method at R ≥ 80 for all 13 cases. This approach provided restoration of TK parameter values with less errors in tumor regions of interest, an improvement compared to a state-of-the-art indirect method. Applied prospectively, the proposed method provided whole-brain, high-resolution TK maps with good image quality., Conclusion: Model-based direct estimation of TK maps from k,t-space DCE-MRI data is feasible and is compatible up to 100-fold undersampling. Magn Reson Med 78:1566-1578, 2017. © 2016 International Society for Magnetic Resonance in Medicine., (© 2016 International Society for Magnetic Resonance in Medicine.)

Purpose: We propose the use of a retrospectively gated cine fast spin echo (FSE) sequence for characterization of carotid artery dynamics. The aim of this study was to compare cine FSE measures of carotid dynamics with measures obtained on prospectively gated FSE images., Methods: The common carotid arteries in 10 volunteers were imaged using two temporally resolved sequences: (i) cine FSE and (ii) prospectively gated FSE. Three raters manually traced a common carotid artery area for all cardiac phases on both sequences. Measured areas and systolic-diastolic area changes were calculated and compared. Inter- and intra-rater reliability were assessed for both sequences., Results: No significant difference between cine FSE and prospectively gated FSE areas were observed (P = 0.36). Both sequences produced repeatable cross-sectional area measurements: inter-rater intraclass correlation coefficient (ICC) = 0.88 on cine FSE images and 0.87 on prospectively gated FSE images. Minimum detectable difference (MDD) in systolic-diastolic area was 4.9 mm(2) with cine FSE and 6.4 mm(2) with prospectively gated FSE., Conclusion: This cine FSE method produced repeatable dynamic carotid artery measurements with less artifact and greater temporal efficiency compared with prospectively gated FSE., (© 2014 Wiley Periodicals, Inc.)

Purpose: To investigate the feasibility of real-time 3D magnetic resonance imaging (MRI) with simultaneous recording of physiological signals for identifying sites of airway obstruction during natural sleep in pediatric patients with sleep-disordered breathing., Methods: Experiments were performed using a three-dimensional Fourier transformation (3DFT) gradient echo sequence with prospective undersampling based on golden-angle radial spokes, and L1-norm regularized iterative self-consistent parallel imaging (L1-SPIRiT) reconstruction. This technique was demonstrated in three healthy adult volunteers and five pediatric patients with sleep-disordered breathing. External airway occlusion was used to induce partial collapse of the upper airway on inspiration and test the effectiveness of the proposed imaging method. Apneic events were identified using information available from synchronized recording of mask pressure and respiratory effort., Results: Acceptable image quality was obtained in seven of eight subjects. Temporary airway collapse induced via inspiratory loading was successfully imaged in all three volunteers, with average airway volume reductions of 63.3%, 52.5%, and 33.7%. Central apneic events and associated airway narrowing/closure were identified in two pediatric patients. During central apneic events, airway obstruction was observed in the retropalatal region in one pediatric patient., Conclusion: Real-time 3D MRI of the pharyngeal airway with synchronized recording of physiological signals is feasible and may provide valuable information about the sites and nature of airway narrowing/collapse during natural sleep., (Copyright © 2013 Wiley Periodicals, Inc.)

Purpose: Dynamic contrast-enhanced imaging provides unique physiological information, notably the endothelial permeability (K(trans)), and may improve the diagnosis and management of multiple pathologies. Current acquisition methods provide limited spatial-temporal resolution and field-of-view, often preventing characterization of the entire pathology and precluding measurement of the arterial input function. We present a method for highly accelerated dynamic imaging and demonstrate its utility for dynamic contrast-enhanced modeling., Methods: We propose a novel Poisson ellipsoid sampling scheme and enforce multiple spatial and temporal l1-norm constraints during image reconstruction. Retrospective and prospective analyses were performed to validate the approach., Results: Retrospectively, no mean bias or diverging trend was observed as the acceleration rate was increased from 3× to 18×; less than 10% error was measured in K(trans) at any individual rates in this range. Prospectively accelerated images at a rate of 36× enabled full brain coverage with 0.94 × 0.94 × 1.9 mm(3) spatial and 4.1 s temporal resolutions. Images showed no visible degradation and provided accurate K(trans) values when compared to a clinical population., Conclusion: Highly accelerated dynamic MRI using compressed sensing and parallel imaging provides accurate permeability modeling and enables full brain, high resolution acquisitions., (Copyright © 2013 Wiley Periodicals, Inc.)

Concomitant gradient fields are transverse magnetic field components that are necessarily present to satisfy Maxwell's equations when magnetic field gradients are utilized in magnetic resonance imaging. They can have deleterious effects that are more prominent at lower static fields and/or higher gradient strengths. In diffusion tensor imaging schemes that employ large gradients that are not symmetric about a refocusing radiofrequency pulse (unlike Stejskal-Tanner, which is symmetric), concomitant fields may cause phase accrual that could corrupt the diffusion measurement. Theory predicting the error from this dephasing is described and experimentally validated for both Reese twice-refocused and split gradient single spin-echo diffusion gradient schemes. Bias in apparent diffusion coefficient values was experimentally found to worsen with distance from isocenter and with increasing duration of gradient asymmetry in both a phantom and in the brain. The amount of error from concomitant gradient fields depends on many variables, including the diffusion gradient pattern, pulse sequence timing, maximum effective gradient amplitude, static magnetic field strength, voxel size, slice distance from isocenter, and partial Fourier fraction. A prospective correction scheme that can reduce concomitant gradient errors is proposed and verified for diffusion imaging., (Copyright © 2011 Wiley Periodicals, Inc.)

Presented is a fitting model for transverse relaxometry data acquired with the multiple-refocused spin-echo sequence. The proposed model, requiring no additional data input or pulse sequence modifications, compensates for imperfections in the transmit field and radiofrequency (RF) profiles. Exploiting oscillatory echo behavior to estimate alternate coherence pathways, the model compensates for prolonged signal decay from stimulated echo pathways yielding precise monoexponential T(2) quantification. Verified numerically and experimentally at 4.7 T in phantoms and the human brain, over 95% accuracy is readily attainable in realistic imaging situations without sacrificing multislice capabilities or requiring composite or adiabatic RF pulses. The proposed model allows T(2) quantitation in heterogeneous transmit fields and permits thin refocusing widths for efficient multislice imaging.

An implementation of fast spin echo at 4.7 T designed for versatile and time-efficient T(2)-weighted imaging of the human brain is presented. Reduced refocusing angles (alpha < 180 degrees) were employed to overcome specific absorption rate (SAR) constraints and their effects on image quality assessed. Image intensity and tissue contrast variations from heterogeneous RF transmit fields and incidental magnetization transfer effects were investigated at reduced refocusing angles. We found that intraslice signal variations are minimized with refocusing angles near 180 degrees, but apparent gray/white matter contrast is independent of refocusing angle. Incidental magnetization transfer effects from multislice acquisitions were shown to attenuate white matter intensity by 25% and gray matter intensity by 15% at 180 degrees; less than 5% attenuation was seen in all tissues at flip angles below 60 degrees. We present multislice images acquired without excess delay time for SAR mitigation using a variety of protocols. Subsecond half Fourier acquisition single-shot turbo spin echo (HASTE) images were obtained with a novel variable refocusing angle echo train (20 degrees < alpha < 58 degrees) and high-resolution scans with a voxel volume of 0.18 mm(3) were acquired in 6.5 min with refocusing angles of 100 degrees., ((c) 2009 Wiley-Liss, Inc.)

We present a simple and intuitive means for determining the flip angles (FAs) required for smooth transitions between static pseudo steady states (SPSSs) in fast spin echo (FSE) imaging with variable FA (VFA) echo trains. We demonstrate the effectiveness of single and multiple transition pulses to successfully vary refocusing FAs while retaining high signal levels. The graphical interpretation presented here is consistent with previous analytical techniques and permits accurate signal-intensity predictions along the echo train., ((c) 2007 Wiley-Liss, Inc.)

Magnetic resonance microscopy using magnetically labeled cells is an emerging discipline offering the potential for non-destructive studies targeting numerous cellular events in medical research. The present work develops a technique to quantify superparamagnetic iron-oxide (SPIO) loaded cells using fully balanced steady state free precession (b-SSFP) imaging. An analytic model based on phase cancellation was derived for a single particle and extended to predict mono-exponential decay versus echo time in the presence of multiple randomly distributed particles. Numerical models verified phase incoherence as the dominant contrast mechanism and evaluated the model using a full range of tissue decay rates, repetition times, and flip angles. Numerical simulations indicated a relaxation rate enhancement (DeltaR(2b)=0.412 gamma . LMD) proportional to LMD, the local magnetic dose (the additional sample magnetization due to the SPIO particles), a quantity related to the concentration of contrast agent. A phantom model of SPIO loaded cells showed excellent agreement with simulations, demonstrated comparable sensitivity to gradient echo DeltaR(*) (2) enhancements, and 14 times the sensitivity of spin echo DeltaR(2) measurements. We believe this model can be used to facilitate the generation of quantitative maps of targeted cell populations., (Magn Reson Med, 2006. (c) 2006 Wiley-Liss, Inc.)