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Purpose: To shorten CEST acquisition time by leveraging Z‐spectrum undersampling combined with deep learning for CEST map construction from undersampled Z‐spectra. Methods: Fisher information gain analysis identified optimal frequency offsets (termed "Fisher offsets") for the multi‐pool fitting model, maximizing information gain for the amplitude and the FWHM parameters. These offsets guided initial subsampling levels. A U‐NET, trained on undersampled brain CEST images from 18 volunteers, produced CEST maps at 3 T with varied undersampling levels. Feasibility was first tested using retrospective undersampling at three levels, followed by prospective in vivo undersampling (15 of 53 offsets), reducing scan time significantly. Additionally, glioblastoma grade IV pathology was simulated to evaluate network performance in patient‐like cases. Results: Traditional multi‐pool models failed to quantify CEST maps from undersampled images (structural similarity index [SSIM] <0.2, peak SNR <20, Pearson r <0.1). Conversely, U‐NET fitting successfully addressed undersampled data challenges. The study suggests CEST scan time reduction is feasible by undersampling 15, 25, or 35 of 53 Z‐spectrum offsets. Prospective undersampling cut scan time by 3.5 times, with a maximum mean squared error of 4.4e–4, r = 0.82, and SSIM = 0.84, compared to the ground truth. The network also reliably predicted CEST values for simulated glioblastoma pathology. Conclusion: The U‐NET architecture effectively quantifies CEST maps from undersampled Z‐spectra at various undersampling levels. [ABSTRACT FROM AUTHOR]

Purpose: Radiotherapy treatment planning (RTP) using MR has been used increasingly for the abdominal site. Multiple contrast weightings and motion‐resolved imaging are desired for accurate delineation of the target and various organs‐at‐risk and patient‐tailored planning. Current MR protocols achieve these through multiple scans with distinct contrast and variable respiratory motion management strategies and acquisition parameters, leading to a complex and inaccurate planning process. This study presents a standalone MR Multitasking (MT)–based technique to produce volumetric, motion‐resolved, multicontrast images for abdominal radiotherapy treatment planning. Methods: The MT technique resolves motion and provides a wide range of contrast weightings by repeating a magnetization‐prepared (saturation recovery and T2 preparations) spoiled gradient‐echo readout series and adopting the MT image reconstruction framework. The performance of the technique was assessed through digital phantom simulations and in vivo studies of both healthy volunteers and patients with liver tumors. Results: In the digital phantom study, the MT technique presented structural details and motion in excellent agreement with the digital ground truth. The in vivo studies showed that the motion range was highly correlated (R2 = 0.82) between MT and 2D cine imaging. MT allowed for a flexible contrast‐weighting selection for better visualization. Initial clinical testing with interobserver analysis demonstrated acceptable target delineation quality (Dice coefficient = 0.85 ± 0.05, Hausdorff distance = 3.3 ± 0.72 mm). Conclusion: The developed MT‐based, abdomen‐dedicated technique is capable of providing motion‐resolved, multicontrast volumetric images in a single scan, which may facilitate abdominal radiotherapy treatment planning. [ABSTRACT FROM AUTHOR]

Purpose: To develop a self‐supervised learning method to retrospectively estimate T1 and T2 values from clinical weighted MRI. Methods: A self‐supervised learning approach was constructed to estimate T1, T2, and proton density maps from conventional T1‐ and T2‐weighted images. MR physics models were employed to regenerate the weighted images from the network outputs, and the network was optimized based on loss calculated between the synthesized and input weighted images, alongside additional constraints based on prior information. The method was evaluated on healthy volunteer data, with conventional mapping as references. The reproducibility was examined on two 3.0T scanners. Performance in tumor characterization was inspected by applying the method to a public glioblastoma dataset. Results: For T1 and T2 estimation from three weighted images (T1 MPRAGE, T1 gradient echo sequences, and T2 turbo spin echo), the deep learning method achieved global voxel‐wise error ≤9% in brain parenchyma and regional error ≤12.2% in six types of brain tissues. The regional measurements obtained from two scanners showed mean differences ≤2.4% and correlation coefficients >0.98, demonstrating excellent reproducibility. In the 50 glioblastoma patients, the retrospective quantification results were in line with literature reports from prospective methods, and the T2 values were found to be higher in tumor regions, with sensitivity of 0.90 and specificity of 0.92 in a voxel‐wise classification task between normal and abnormal regions. Conclusion: The self‐supervised learning method is promising for retrospective T1 and T2 quantification from clinical MR images, with the potential to improve the availability of quantitative MRI and facilitate brain tumor characterization. [ABSTRACT FROM AUTHOR]

Purpose: To develop a novel low‐rank tensor reconstruction approach leveraging the complete acquired data set to improve precision and repeatability of multiparametric mapping within the cardiovascular MR Multitasking framework. Methods: A novel approach that alternated between estimation of temporal components and spatial components using the entire data set acquired (i.e., including navigator data and imaging data) was developed to improve reconstruction. The precision and repeatability of the proposed approach were evaluated on numerical simulations, 10 healthy subjects, and 10 cardiomyopathy patients at multiple scan times for 2D myocardial T1/T2 mapping with MR Multitasking and were compared with those of the previous navigator‐derived fixed‐basis approach. Results: In numerical simulations, the proposed approach outperformed the previous fixed‐basis approach with lower T1 and T2 error against the ground truth at all scan times studied and showed better motion fidelity. In human subjects, the proposed approach showed no significantly different sharpness or T1/T2 measurement and significantly improved T1 precision by 20%–25%, T2 precision by 10%–15%, T1 repeatability by about 30%, and T2 repeatability by 25%–35% at 90‐s and 50‐s scan times The proposed approach at the 50‐s scan time also showed comparable results with that of the previous fixed‐basis approach at the 90‐s scan time. Conclusion: The proposed approach improved precision and repeatability for quantitative imaging with MR Multitasking while maintaining comparable motion fidelity, T1/T2 measurement, and septum sharpness and had the potential for further reducing scan time from 90 s to 50 s. [ABSTRACT FROM AUTHOR]

Purpose: Widely used conventional 2D T2* approaches that are based on breath‐held, electrocardiogram (ECG)–gated, multi‐gradient‐echo sequences are prone to motion artifacts in the presence of incomplete breath holding or arrhythmias, which is common in cardiac patients. To address these limitations, a 3D, non‐ECG‐gated, free‐breathing T2* technique that enables rapid whole‐heart coverage was developed and validated. Methods: A continuous random Gaussian 3D k‐space sampling was implemented using a low‐rank tensor framework for motion‐resolved 3D T2* imaging. This approach was tested in healthy human volunteers and in swine before and after intravenous administration of ferumoxytol. Results: Spatial‐resolution matched T2* images were acquired with 2–3‐fold reduction in scan time using the proposed T2* mapping approach relative to conventional T2* mapping. Compared with the conventional approach, T2* images acquired with the proposed method demonstrated reduced off‐resonance and flow artifacts, leading to higher image quality and lower coefficient of variation in T2*‐weighted images of the myocardium of swine and humans. Mean myocardial T2* values determined using the proposed and conventional approaches were highly correlated and showed minimal bias. Conclusion: The proposed non‐ECG‐gated, free‐breathing, 3D T2* imaging approach can be performed within 5 min or less. It can overcome critical image artifacts from undesirable cardiac and respiratory motion and bulk off‐resonance shifts at the heart–lung interface. The proposed approach is expected to facilitate faster and improved cardiac T2* mapping in those with limited breath‐holding capacity or arrhythmias. [ABSTRACT FROM AUTHOR]

Purpose: Deep learning superresolution (SR) is a promising approach to reduce MRI scan time without requiring custom sequences or iterative reconstruction. Previous deep learning SR approaches have generated low‐resolution training images by simple k‐space truncation, but this does not properly model in‐plane turbo spin echo (TSE) MRI resolution degradation, which has variable T2 relaxation effects in different k‐space regions. To fill this gap, we developed a T2‐deblurred deep learning SR method for the SR of 3D‐TSE images. Methods: A SR generative adversarial network was trained using physically realistic resolution degradation (asymmetric T2 weighting of raw high‐resolution k‐space data). For comparison, we trained the same network structure on previous degradation models without TSE physics modeling. We tested all models for both retrospective and prospective SR with 3 × 3 acceleration factor (in the two phase‐encoding directions) of genetically engineered mouse embryo model TSE‐MR images. Results: The proposed method can produce high‐quality 3 × 3 SR images for a typical 500‐slice volume with 6–7 mouse embryos. Because 3 × 3 SR was performed, the image acquisition time can be reduced from 15 h to 1.7 h. Compared to previous SR methods without TSE modeling, the proposed method achieved the best quantitative imaging metrics for both retrospective and prospective evaluations and achieved the best imaging‐quality expert scores for prospective evaluation. Conclusion: The proposed T2‐deblurring method improved accuracy and image quality of deep learning–based SR of TSE MRI. This method has the potential to accelerate TSE image acquisition by a factor of up to 9. [ABSTRACT FROM AUTHOR]

Purpose: To develop a deep learning method to synthesize conventional contrast‐weighted images in the brain from MR multitasking spatial factors. Methods: Eighteen subjects were imaged using a whole‐brain quantitative T1‐T2‐T1ρ MR multitasking sequence. Conventional contrast‐weighted images consisting of T1 MPRAGE, T1 gradient echo, and T2 fluid‐attenuated inversion recovery were acquired as target images. A 2D U‐Net–based neural network was trained to synthesize conventional weighted images from MR multitasking spatial factors. Quantitative assessment and image quality rating by two radiologists were performed to evaluate the quality of deep‐learning–based synthesis, in comparison with Bloch‐equation–based synthesis from MR multitasking quantitative maps. Results: The deep‐learning synthetic images showed comparable contrasts of brain tissues with the reference images from true acquisitions and were substantially better than the Bloch‐equation–based synthesis results. Averaging on the three contrasts, the deep learning synthesis achieved normalized root mean square error = 0.184 ± 0.075, peak SNR = 28.14 ± 2.51, and structural‐similarity index = 0.918 ± 0.034, which were significantly better than Bloch‐equation–based synthesis (p < 0.05). Radiologists' rating results show that compared with true acquisitions, deep learning synthesis had no notable quality degradation and was better than Bloch‐equation–based synthesis. Conclusion: A deep learning technique was developed to synthesize conventional weighted images from MR multitasking spatial factors in the brain, enabling the simultaneous acquisition of multiparametric quantitative maps and clinical contrast‐weighted images in a single scan. [ABSTRACT FROM AUTHOR]

Purpose: To extend the MR MultiTasking‐based Multidimensional Assessment of Cardiovascular System (MT‐MACS) technique with larger spatial coverage and water‐fat separation for comprehensive aortocardiac assessment. Methods: MT‐MACS adopts a low‐rank tensor image model for 7D imaging, with three spatial dimensions for volumetric imaging, one cardiac motion dimension for cine imaging, one respiratory motion dimension for free‐breathing imaging, one T2‐prepared inversion recovery time dimension for multi‐contrast assessment, and one T2*‐decay time dimension for water‐fat separation. Nine healthy subjects were recruited for the 3T study. Overall image quality was scored on bright‐blood (BB), dark‐blood (DB), and gray‐blood (GB) contrasts using a 4‐point scale (0‐poor to 3‐excellent) by two independent readers, and their interreader agreement was evaluated. Myocardial wall thickness and left ventricular ejection fraction (LVEF) were quantified on DB and BB contrasts, respectively. The agreement in these metrics between MT‐MACS and conventional breath‐held, electrocardiography‐triggered 2D sequences were evaluated. Results: MT‐MACS provides both water‐only and fat‐only images with excellent image quality (average score = 3.725/3.780/3.835/3.890 for BB/DB/GB/fat‐only images) and moderate to high interreader agreement (weighted Cohen's kappa value = 0.727/0.668/1.000/1.000 for BB/DB/GB/fat‐only images). There were good to excellent agreements in myocardial wall thickness measurements (intraclass correlation coefficients [ICC] = 0.781/0.929/0.680/0.878 for left atria/left ventricle/right atria/right ventricle) and LVEF quantification (ICC = 0.716) between MT‐MACS and 2D references. All measurements were within the literature range of healthy subjects. Conclusion: The refined MT‐MACS technique provides multi‐contrast, phase‐resolved, and water‐fat imaging of the aortocardiac systems and allows evaluation of anatomy and function. Clinical validation is warranted. [ABSTRACT FROM AUTHOR]

Purpose: To develop a novel 3D abdominal CEST MRI technique at 3 T using MR multitasking, which enables entire‐liver coverage with free‐breathing acquisition. Methods: k‐Space data were continuously acquired with repetitive steady‐state CEST (ss‐CEST) modules. The stack‐of‐stars acquisition pattern was used for k‐space sampling. MR multitasking was used to reconstruct motion‐resolved 3D CEST images of 53 frequency offsets with entire‐liver coverage and 2.0 × 2.0 × 6.0 mm3 spatial resolution. The total scan time was 9 min. The sensitivity of amide proton transfer (APT)‐CEST (magnetization transfer asymmetry [MTRasym] at 3.5 ppm) and glycogen CEST (glycoCEST) (mean MTRasym around 1.0 ppm) signals generated with the proposed method were tested with fasting experiments. Results: Both APT‐CEST and glycoCEST signals showed high sensitivity between post‐fasting and post‐meal acquisitions. APT‐CEST and glycoCEST MTRasym signals from post‐mean scans were significantly increased (APT‐CEST: −0.019 ± 0.017 in post‐fasting scans, 0.014 ± 0.021 in post‐meal scans, p < 0.01; glycoCEST: 0.003 ± 0.009 in post‐fasting scans, 0.027 ± 0.021 in post‐meal scans, p < 0.01). Conclusion: The proposed 3D abdominal steady‐state CEST method using MR multitasking can generate CEST images of the entire liver during free breathing. [ABSTRACT FROM AUTHOR]

Purpose: To develop an MR multitasking‐based dynamic imaging for cerebrovascular evaluation (MT‐DICE) technique for simultaneous quantification of permeability and leakage‐insensitive perfusion with a single‐dose contrast injection. Methods: MT‐DICE builds on a saturation‐recovery prepared multi‐echo fast low‐angle shot sequence. The k‐space is randomly sampled for 7.6 min, with single‐dose contrast agent injected 1.5 min into the scan. MR multitasking is used to model the data into six dimensions, including three spatial dimensions for whole‐brain coverage, a saturation‐recovery time dimension, and a TE dimension for dynamic T1$$ {\mathrm{T}}_1 $$ and T2*$$ {\mathrm{T}}_2^{\ast } $$ quantification, respectively, and a contrast dynamics dimension for capturing contrast kinetics. The derived pixel‐wise T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ time series are converted into contrast concentration‐time curves for calculation of kinetic metrics. The technique was assessed for its agreement with reference methods in T1$$ {\mathrm{T}}_1 $$ and T2*$$ {\mathrm{T}}_2^{\ast } $$ measurements in eight healthy subjects and, in three of them, inter‐session repeatability of permeability and leakage‐insensitive perfusion parameters. Its feasibility was also demonstrated in four patients with brain tumors. Results: MT‐DICE T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ values of normal gray matter and white matter were in excellent agreement with reference values (intraclass correlation coefficients = 0.860/0.962 for gray matter and 0.925/0.975 for white matter). Both permeability and perfusion parameters demonstrated good to excellent intersession agreement with the lowest intraclass correlation coefficients at 0.694. Contrast kinetic parameters in all healthy subjects and patients were within the literature range. Conclusion: Based on dynamic T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ mapping, MT‐DICE allows for simultaneous quantification of permeability and leakage‐insensitive perfusion metrics with a single‐dose contrast injection. [ABSTRACT FROM AUTHOR]

Purpose: To develop an automated vessel wall segmentation method on T1‐weighted intracranial vessel wall magnetic resonance images, with a focus on modeling the inclusion relation between the inner and outer boundaries of the vessel wall. Methods: We propose a novel method that estimates the inner and outer vessel wall boundaries simultaneously, using a network with a single output channel resembling the level‐set function height. The network is driven by a unique tiered loss that accounts for data fidelity of the lumen and vessel wall classes and a length regularization to encourage boundary smoothness. Results: Implemented with a 2.5D UNet with a ResNet backbone, the proposed method achieved Dice similarity coefficients (DSC) in 2D of 0.925 ± 0.048, 0.786 ± 0.084, Hausdorff distance (HD) of 0.286 ± 0.436, 0.345 ± 0.419 mm, and mean surface distance (MSD) of 0.083 ± 0.037 and 0.103 ± 0.032 mm for the lumen and vessel wall, respectively, on a test set; compared favorably to a baseline UNet model that achieved DSC 0.924 ± 0.047, 0.794 ± 0.082, HD 0.298 ± 0.477, 0.394 ± 0.431 mm, and MSD 0.087 ± 0.056, 0.119 ± 0.059 mm. Our vessel wall segmentation method achieved substantial improvement in morphological integrity and accuracy compared to benchmark methods. Conclusions: The proposed method provides a systematic approach to model the inclusion morphology and incorporate it into an optimization infrastructure. It can be applied to any application where inclusion exists among a (sub)set of classes to be segmented. Improved feasibility in result morphology promises better support for clinical quantification and decision. [ABSTRACT FROM AUTHOR]

Purpose: To develop a free‐breathing, non‐electrocardiogram technique for simultaneous myocardial T1, T2, T2*, and fat‐fraction (FF) mapping in a single scan. Methods: The MR Multitasking framework is adapted to quantify T1, T2, T2*, and FF simultaneously. A variable TR scheme is developed to preserve temporal resolution and imaging efficiency. The underlying high‐dimensional image is modeled as a low‐rank tensor, which allows accelerated acquisition and efficient reconstruction. The accuracy and/or repeatability of the technique were evaluated on static and motion phantoms, 12 healthy volunteers, and 3 patients by comparing to the reference techniques. Results: In static and motion phantoms, T1/T2/T2*/FF measurements showed substantial consistency (R > 0.98) and excellent agreement (intraclass correlation coefficient > 0.93) with reference measurements. In human subjects, the proposed technique yielded repeatable T1, T2, T2*, and FF measurements that agreed with those from references. Conclusions: The proposed free‐breathing, non‐electrocardiogram, motion‐resolved Multitasking technique allows simultaneous quantification of myocardial T1, T2, T2*, and FF in a single 2.5‐min scan. [ABSTRACT FROM AUTHOR]

Purpose: To perform fast 3D steady‐state CEST (ss‐CEST) imaging using MR Multitasking. Methods: A continuous acquisition sequence with repetitive ss‐CEST modules was developed. Each ss‐CEST module contains a single‐lobe Gaussian saturation pulse, followed by a spoiler gradient and eight FLASH readouts (one "training line" + seven "imaging lines"). Three‐dimensional Cartesian encoding was used for k‐space acquisition. Reconstructed CEST images were quantified with four‐pool Lorentzian fitting. Results: Steady‐state CEST with whole‐brain coverage was performed in 5.6 s per saturation frequency offset at the spatial resolution of 1.7 × 1.7 × 3.0 mm3. The total scan time was 5.5 min for 55 different frequency offsets. Quantitative CEST maps from multipool fitting showed consistent image quality across the volume. Conclusion: Three‐dimensional ss‐CEST with whole‐brain coverage can be done at 3 T within 5.5 min using MR Multitasking. [ABSTRACT FROM AUTHOR]

Purpose: To develop a new technique that enables simultaneous quantification of whole‐brain T1, T2, T2∗, as well as susceptibility and synthesis of six contrast‐weighted images in a single 9.1‐minute scan. Methods: The technique uses hybrid T2‐prepared inversion‐recovery pulse modules and multi‐echo gradient‐echo readouts to collect k‐space data with various T1, T2, and T2∗ weightings. The underlying image is represented as a six‐dimensional low‐rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi‐echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast‐weighted images was also examined. Results: High quality, co‐registered T1, T2, and T2∗ susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p <.001), T2 (p =.002), and T2∗ (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p =.900). The framework is also capable of synthesizing six contrast‐weighted images. Conclusion: The MR Multitasking–based 3D brain mapping of T1, T2, T2∗, and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging. [ABSTRACT FROM AUTHOR]

Background: Chemical exchange saturation transfer (CEST) is an emerging metabolic MRI technique to map creatine distribution in the myocardium. Purpose To investigate the feasibility of using a contrast‐free CEST technique to evaluate cardiac involvement in amyloid light‐chain (AL) amyloidosis. Study type: Prospective. Population Forty patients with biopsy‐proven AL amyloidosis (age 57.6 ± 9.1 years, 31 males) and 20 healthy controls (age 42.8 ± 13.8 years, 13 males). Field strength/Sequence: A 3.0 T, CEST imaging using a single‐shot FLASH sequence, T1 mapping with a modified Look‐Locker inversion recovery sequence and late gadolinium enhancement (LGE) imaging with a phase‐sensitive inversion recovery gradient echo sequence. Assessment The average CEST was calculated in the basal short‐axis slice of the entire left ventricle and septum. LGE was assessed subjectively (none/patchy/global) and extracellular volume (ECV), CEST and T1 maps generated. Statistical Tests: Comparison between patient groups and healthy controls was performed by one‐way analysis of variance with post hoc Bonferroni correction. Correlation was assessed using the Pearson's r correlation or Spearman ρ correlation. Statistical significance was defined as P < 0.05. Results: Global (0.09 ± 0.03 vs. 0.11 ± 0.02) and septal (0.09 ± 0.03 vs. 0.11 ± 0.03) basal short‐axis CEST was significantly decreased in patients with AL amyloidosis compared to the controls. Global CEST correlated significantly with Mayo stage (ρ = −0.508), NYHA Class (ρ = −0.430), LVEF (r = 0.511), mass index (r = −0.373), LGE (ρ = −0.537), ECV (r = −0.544), and T2 (r = −0.396). Septal CEST correlated significantly with LVEF (r = 0.395), LGE (ρ = −0.330), and ECV (r = −0.391). Data Conclusions: This study highlights the potential of CEST MRI to identify cardiac involvement and evaluate disease burden and to give insight into cellular changes intermediary between function and structure in AL amyloidosis patients. Evidence Level 2 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Purpose: To develop a 3D multitasking multi‐echo (MT‐ME) technique for the comprehensive characterization of liver tissues with 5‐min free‐breathing acquisition; whole‐liver coverage; a spatial resolution of 1.5 × 1.5 × 6 mm3; and simultaneous quantification of T1, water‐specific T1 (T1w), proton density fat fraction (PDFF), and R2∗. Methods: Six‐echo bipolar spoiled gradient echo readouts following inversion recovery preparation was performed to generate T1, water/fat, and R2∗ contrast. MR multitasking was used to reconstruct the MT‐ME images with 3 spatial dimensions: 1 T1 recovery dimension, 1 multi‐echo dimension, and 1 respiratory dimension. A basis function–based approach was developed for T1w quantification, followed by the estimation of R2∗ and T1‐corrected PDFF. The intrasession repeatability and agreement against references of MT‐ME measurements were tested on a phantom and 15 clinically healthy subjects. In addition, 4 patients with confirmed liver diseases were recruited, and the agreement between MT‐ME measurements and references was assessed. Results: MT‐ME produced high‐quality, coregistered T1, T1w, PDFF, and R2∗ maps with good intrasession repeatability and substantial agreement with references on phantom and human studies. The intra‐class coefficients of T1, T1w, PDFF, and R2∗ from the repeat MT‐ME measurements on clinically healthy subjects were 0.989, 0.990, 0.999, and 0.988, respectively. The intra‐class coefficients of T1, PDFF, and R2∗ between the MT‐ME and reference measurements were 0.924, 0.987, and 0.975 in healthy subjects and 0.980, 0.999, and 0.998 in patients. The T1w was independent to PDFF (R = −0.029, P =.904). Conclusion: The proposed MT‐ME technique quantifies T1, T1w, PDFF, and R2∗ simultaneously and is clinically promising for the comprehensive characterization of liver tissue properties. [ABSTRACT FROM AUTHOR]

Purpose: To develop a deep‐learning–based method to quantify multiple parameters in the brain from conventional contrast‐weighted images. Methods: Eighteen subjects were imaged using an MR Multitasking sequence to generate reference T1 and T2 maps in the brain. Conventional contrast‐weighted images consisting of T1 MPRAGE, T1 GRE, and T2 FLAIR were acquired as input images. A U‐Net–based neural network was trained to estimate T1 and T2 maps simultaneously from the contrast‐weighted images. Six‐fold cross‐validation was performed to compare the network outputs with the MR Multitasking references. Results: The deep‐learning T1/T2 maps were comparable with the references, and brain tissue structures and image contrasts were well preserved. A peak signal‐to‐noise ratio >32 dB and a structural similarity index >0.97 were achieved for both parameter maps. Calculated on brain parenchyma (excluding CSF), the mean absolute errors (and mean percentage errors) for T1 and T2 maps were 52.7 ms (5.1%) and 5.4 ms (7.1%), respectively. ROI measurements on four tissue compartments (cortical gray matter, white matter, putamen, and thalamus) showed that T1 and T2 values provided by the network outputs were in agreement with the MR Multitasking reference maps. The mean differences were smaller than ±1%, and limits of agreement were within ±5% for T1 and within ±10% for T2 after taking the mean differences into account. Conclusion: A deep‐learning–based technique was developed to estimate T1 and T2 maps from conventional contrast‐weighted images in the brain, enabling simultaneous qualitative and quantitative MRI without modifying clinical protocols. [ABSTRACT FROM AUTHOR]

Purpose: To address head motion in brain MRI with a novel motion‐resolved imaging framework, with application to motion‐robust quantitative multiparametric mapping. Methods: MR multitasking conceptualizes the underlying multiparametric image in the presence of motion as a multidimensional low‐rank tensor. By incorporating a motion‐state dimension into the parameter dimensions and introducing unsupervised motion‐state binning and outlier motion reweighting mechanisms, the brain motion can be readily resolved for motion‐robust quantitative imaging. A numerical motion phantom was used to simulate different discrete and periodic motion patterns under various translational and rotational scenarios, as well as investigate the sensitivity to exceptionally small and large displacements. In vivo brain MRI was performed to also evaluate different real discrete and periodic motion patterns. The effectiveness of motion‐resolved imaging for simultaneous T1/T2/T1ρ mapping in the brain was investigated. Results: For all 14 simulation scenarios of small, intermediate, and large motion displacements, the motion‐resolved approach produced T1/T2/T1ρ maps with less absolute difference errors against the ground truth, lower RMSE, and higher structural similarity index measure of T1/T2/T1ρ measurements compared to motion removal, and no motion handling. For in vivo experiments, the motion‐resolved approach produced T1/T2/T1ρ maps with the best image quality free from motion artifacts under random discrete motion, tremor, periodic shaking, and nodding patterns compared to motion removal and no motion handling. The proposed method also yielded T1/T2/T1ρ measurement distributions closest to the motion‐free reference, with minimal measurement bias and variance. Conclusion: Motion‐resolved quantitative brain imaging is achieved with multitasking, which is generalizable to various head motion patterns without explicit need for registration‐based motion correction. [ABSTRACT FROM AUTHOR]

Purpose: To develop a single‐scan method for B1+‐corrected T1 mapping and apply it for free‐breathing (FB) cardiac MR multitasking without electrocardiogram (ECG) triggering. Methods: One dual flip‐angle (2FA) inversion recovery (IR)‐FLASH scan provides two observations of T1∗ (apparent T1) corresponding to two distinct combinations of the nominal FA α and B1+. Spatiotemporally coregistered T1 and B1+ spin history maps are obtained by fitting the 2FA signal model. T1 estimate accuracy and repeatability for single flip‐angle (1FA) and 2FA IR‐FLASH sequence MR multitasking were evaluated at 3T. A T1 phantom was first imaged on the scanner table, then on two human subjects' thoraxes in both breath‐hold (BH) and FB conditions. IR‐turbo spin echo (IR‐TSE) static phantom T1 measurements served as reference. In 10 healthy subjects, myocardial T1 was evaluated with ECG‐free, FB multitasking sequences alongside ECG‐triggered BH MOLLI. Results: For phantom‐on‐table T1 estimates, 2FA agreed better with IR‐TSE (intraclass correlation coefficient [ICC] = 0.996, mean error ± SD = −1.6% ± 1.9%) than did 1FA (ICC = 0.922; mean error ± SD = −4.3% ± 12%). For phantom‐on‐thorax, 2FA was more repeatable and robust to respiration than 1FA (coefficient of variation [CoV] = 1.2% 2FA, = 11.3% 1FA). In vivo, in intrasession T1 repeatability, 2FA (septal CoV = 2.4%, six‐segment CoV = 4.4%) outperformed 1FA (septal CoV = 3.1%, six‐segment CoV = 5.5%). In six‐segment T1 homogeneity, 2FA (CoV = 7.9%) also outperformed 1FA (CoV = 11.1%). Conclusion: The 2FA IR‐FLASH improves T1 estimate accuracy and repeatability over 1FA IR‐FLASH, and enables single‐scan B1+‐corrected T1 mapping without BHs or ECG when used with MR multitasking. [ABSTRACT FROM AUTHOR]

Purpose: (1) To investigate the effect of internal localized movement on 3DMR intracranial vessel wall imaging and (2) to develop a novel motion‐compensation approach combining volumetric navigator (vNav) and self‐gating (SG) to simultaneously compensate for bulk and localized movements. Methods: A 3D variable‐flip‐angle turbo spin‐echo (ie, SPACE) sequence was modified to incorporate vNav and SG modules. The SG signals from the center k‐space line are acquired at the beginning of each TR to detect localized motion‐affected TRs. The vNavs from low‐resolution 3D EPI are acquired to identify bulk head motion. Fifteen healthy subjects and 3 stroke patients were recruited in this study. Overall image quality (0‐poor to 4‐excellent) and vessel wall sharpness were compared among the scenarios with and without bulk and/or localized motion and/or the proposed compensation strategies. Results: Localized motion reduced wall sharpness, which was significantly mitigated by SG (ie, outer boundary of basilar artery: 0.68 ± 0.27 vs 0.86 ± 0.17; P =.037). When motion occurred, the overall image quality and vessel wall sharpness obtained with vNav‐SG SPACE were significantly higher than those obtained with conventional SPACE (ie, basilarartery outer boundary sharpness: 0.73 ± 0.24 vs 0.94 ± 0.24; P =.033), yet comparable to those obtained in motion‐free scans (ie, basilarartery outer boundary sharpness: 0.94 ± 0.24 vs 0.96 ± 0.31; P =.815). Conclusion: Localized movements can induce considerable artifacts in intracranial vessel wall imaging. The vNav‐SG approach is capable of compensating for both bulk and localized motions. [ABSTRACT FROM AUTHOR]

Purpose: To develop a low‐dose Multitasking DCE technique (LD‐MT‐DCE) for breast imaging, enabling dynamic T1 mapping–based quantitative characterization of tumor blood flow and vascular properties with whole‐breast coverage, a spatial resolution of 0.9 × 0.9 × 1.1 mm3, and a temporal resolution of 1.4 seconds using a 20% gadolinium dose (0.02 mmol/kg). Methods: Magnetic resonance Multitasking was used to reconstruct 5D images with three spatial dimensions, one T1 recovery dimension for dynamic T1 quantification, and one DCE dimension for contrast kinetics. Kinetic parameters Fp, vp, Ktrans, and ve were estimated from dynamic T1 maps using the two‐compartment exchange model. The LD‐MT‐DCE repeatability and agreement against standard‐dose MT‐DCE were evaluated in 20 healthy subjects. In 7 patients with triple‐negative breast cancer, LD‐MT‐DCE image quality and diagnostic results were compared with that of standard‐dose clinical DCE in the same imaging session. One‐way unbalanced analysis of variance with Tukey test was performed to evaluate the statistical significance of the kinetic parameters between control and patient groups. Results: The LD‐MT‐DCE technique was repeatable, agreed with standard‐dose MT‐DCE, and showed excellent image quality. The diagnosis using LD‐MT‐DCE matched well with clinical results. The values of Fp, vp, and Ktrans were significantly different between malignant tumors and normal breast tissue (P <.001, <.001, and <.001, respectively), and between malignant and benign tumors (P =.020,.003, and <.001, respectively). Conclusion: The LD‐MT‐DCE technique was repeatable and showed excellent image quality and equivalent diagnosis compared with standard‐dose clinical DCE. The estimated kinetic parameters were capable of differentiating between normal breast tissue and benign and malignant tumors. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to develop a novel free‐breathing cardiac diffusion tensor MRI (DT‐MRI) approach, M2‐MT‐MOCO, capable of whole left ventricular coverage that leverages second‐order motion compensation (M2) diffusion encoding and multitasking (MT) framework to efficiently correct for respiratory motion (MOCO). Methods: Imaging was performed in 16 healthy volunteers and 3 heart failure patients with symptomatic dyspnea. The healthy volunteers were scanned to compare the accuracy of interleaved multislice coverage of the entire left ventricle with a single‐slice acquisition and the accuracy of the free‐breathing conventional MOCO and MT‐MOCO approaches with reference breath‐hold DT‐MRI. Mean diffusivity (MD), fractional anisotropy (FA), helix angle transmurality (HAT), and intrascan repeatability were quantified and compared. Results: In all subjects, free‐breathing M2‐MT‐MOCO DT‐MRI yielded DWI of the entire left ventricle without bulk motion‐induced signal loss. No significant differences were seen in the global values of MD, FA, and HAT in the multislice and single‐slice acquisitions. Furthermore, global quantification of MD, FA, and HAT were also not significantly different between the MT‐MOCO and breath‐hold, whereas conventional MOCO yielded significant differences in MD, FA, and HAT with MT‐MOCO and FA with breath‐hold. In heart failure patients, M2‐MT‐MOCO DT‐MRI was feasible yielding higher MD, lower FA, and lower HAT compared with healthy volunteers. Substantial agreement was found between repeated scans across all subjects for MT‐MOCO. Conclusion: M2‐MT‐MOCO enables free‐breathing DT‐MRI of the entire left ventricle in 10 min, while preserving quantification of myocardial microstructure compared to breath‐held and single‐slice acquisitions and is feasible in heart failure patients. [ABSTRACT FROM AUTHOR]

Purpose: To develop a 3D whole‐brain simultaneous T1/T2/T1ρ quantification method with MR Multitasking that provides high quality, co‐registered multiparametric maps in 9 min. Methods: MR Multitasking conceptualizes T1/T2/T1ρ relaxations as different time dimensions, simultaneously resolving all three dimensions with a low‐rank tensor image model. The proposed method was validated on a phantom and in healthy volunteers, comparing quantitative measurements against corresponding reference methods and evaluating the scan‐rescan repeatability. Initial clinical validation was performed in age‐matched relapsing‐remitting multiple sclerosis (RRMS) patients to examine the feasibility of quantitative tissue characterization and to compare with the healthy control cohort. The feasibility of synthesizing six contrast‐weighted images was also examined. Results: Our framework produced high quality, co‐registered T1/T2/T1ρ maps that closely resemble the reference maps. Multitasking T1/T2/T1ρ measurements showed substantial agreement with reference measurements on the phantom and in healthy controls. Bland‐Altman analysis indicated good in vivo repeatability of all three parameters. In RRMS patients, lesions were conspicuously delineated on all three maps and on four synthetic weighted images (T2‐weighted, T2‐FLAIR, double inversion recovery, and a novel "T1ρ‐FLAIR" contrast). T1 and T2 showed significant differences for normal appearing white matter between patients and controls, while T1ρ showed significant differences for normal appearing white matter, cortical gray matter, and deep gray matter. The combination of three parameters significantly improved the differentiation between RRMS patients and healthy controls, compared to using any single parameter alone. Conclusion: MR Multitasking simultaneously quantifies whole‐brain T1/T2/T1ρ and is clinically promising for quantitative tissue characterization of neurological diseases, such as MS. [ABSTRACT FROM AUTHOR]

Background: Cardiac MRI is an emerging modality for evaluating left ventricular (LV) diastolic dysfunction (LVDD), a pathological condition that is prevalent in aging populations. However, there is a lack of reports of MRI‐derived LV diastolic properties in late diastole. Purpose: To test the hypothesis that cine MRI‐derived motion/deformation indices can be used to characterize age‐related changes on LV relaxation patterns in late diastole. Study Type: Retrospective. Population: In all, 412 participants (72.5 ± 4.6 years old, range 65–84) without a documented history of cardiovascular diseases. Field Strength/Sequence: Balanced steady‐state free precession(bSSFP) acquired at 1.5T. Assessment: Participants were divided into younger (65–74 years old, n = 275) and older (75–84 years old, n = 137) groups. Status of diabetes mellitus (DM), hypertension (HTN), and lipid disorders were recorded for each participant. Cine MRI datasets were analyzed by using heart deformation analysis (HDA). LV motion/deformation indices (displacement, velocity, strain, and strain rate) were measured through 22 phases within a cardiac cycle. Statistical Tests: The prevalence of traditional cardiovascular risk conditions, LV ejection fraction (LVEF), peak LV regional displacement, velocity, and strain rates at early and late diastole were compared between two participant groups using chi‐square tests or t‐tests. Results: Older participants had a significantly lower peak early radial displacement (0.797 ± 0.249 cm vs. 0.876 ± 0.286 cm), radial velocity (19.3 ± 6.3 mm/s vs. 17.5 ± 5.2 mm/s), and circumferential strain rate (64.6 ± 15.7%/s vs. 70.1 ± 17%/s) but a higher peak late circumferential strain rate (69.8 ± 16.3 %/s vs. 66 ± 15.8 %/s) than their younger counterparts. Data Conclusion: Cine MRI can be used to characterize age‐related LV relaxation patterns in late diastole. Level of Evidence: 3. Technical Efficacy Stage: 1. [ABSTRACT FROM AUTHOR]

Purpose: To develop an MR multitasking‐based multidimensional assessment of cardiovascular system (MT‐MACS) with electrocardiography‐free and navigator‐free data acquisition for a comprehensive evaluation of thoracic aortic diseases. Methods: The MT‐MACS technique adopts a low‐rank tensor image model with a cardiac time dimension for phase‐resolved cine imaging and a T2‐prepared inversion‐recovery dimension for multicontrast assessment. Twelve healthy subjects and 2 patients with thoracic aortic diseases were recruited for the study at 3 T, and both qualitative (image quality score) and quantitative (contrast‐to‐noise ratio between lumen and wall, lumen and wall area, and aortic strain index) analyses were performed in all healthy subjects. The overall image quality was scored based on a 4‐point scale: 3, excellent; 2, good; 1, fair; and 0, poor. Statistical analysis was used to test the measurement agreement between MT‐MACS and its corresponding 2D references. Results: The MT‐MACS images reconstructed from acquisitions as short as 6 minutes demonstrated good or excellent image quality for bright‐blood (2.58 ± 0.46), dark‐blood (2.58 ± 0.50), and gray‐blood (2.17 ± 0.53) contrast weightings, respectively. The contrast‐to‐noise ratios for the three weightings were 49.2 ± 12.8, 20.0 ± 5.8 and 2.8 ± 1.8, respectively. There were good agreements in the lumen and wall area (intraclass correlation coefficient = 0.993, P <.001 for lumen; intraclass correlation coefficient = 0.969, P <.001 for wall area) and strain (intraclass correlation coefficient = 0.947, P <.001) between MT‐MACS and conventional 2D sequences. Conclusion: The MT‐MACS technique provides high‐quality, multidimensional images for a comprehensive assessment of the thoracic aorta. Technical feasibility was demonstrated in healthy subjects and patients with thoracic aortic diseases. Further clinical validation is warranted. [ABSTRACT FROM AUTHOR]

Purpose: Segmentation of multiple organs‐at‐risk (OARs) is essential for magnetic resonance (MR)‐only radiation therapy treatment planning and MR‐guided adaptive radiotherapy of abdominal cancers. Current practice requires manual delineation that is labor‐intensive, time‐consuming, and prone to intra‐ and interobserver variations. We developed a deep learning (DL) technique for fully automated segmentation of multiple OARs on clinical abdominal MR images with high accuracy, reliability, and efficiency. Methods: We developed Automated deep Learning‐based abdominal multiorgan segmentation (ALAMO) technique based on two‐dimensional U‐net and a densely connected network structure with tailored design in data augmentation and training procedures such as deep connection, auxiliary supervision, and multiview. The model takes in multislice MR images and generates the output of segmentation results. 3.0‐Tesla T1 VIBE (Volumetric Interpolated Breath‐hold Examination) images of 102 subjects were used in our study and split into 66 for training, 16 for validation, and 20 for testing. Ten OARs were studied, including the liver, spleen, pancreas, left/right kidneys, stomach, duodenum, small intestine, spinal cord, and vertebral bodies. An experienced radiologist manually labeled each OAR, followed by reediting, if necessary, by a senior radiologist, to create the ground‐truth. The performance was measured using volume overlapping and surface distance. Results: The ALAMO technique generated segmentation labels in good agreement with the manual results. Specifically, among the ten OARs, nine achieved high dice similarity coefficients (DSCs) in the range of 0.87–0.96, except for the duodenum with a DSC of 0.80. The inference completed within 1 min for a three‐dimensional volume of 320 × 288 × 180. Overall, the ALAMO model matched the state‐of‐the‐art techniques in performance. Conclusion: The proposed ALAMO technique allows for fully automated abdominal MR segmentation with high accuracy and practical memory and computation time demands. [ABSTRACT FROM AUTHOR]

Purpose: To develop a quantitative DCE MRI technique enabling entire‐abdomen coverage, free‐breathing acquisition, 1‐second temporal resolution, and T1‐based quantification of contrast agent concentration and kinetic modeling for the characterization of pancreatic ductal adenocarcinoma (PDAC). Methods: Segmented FLASH readouts following saturation‐recovery preparation with randomized 3D Cartesian undersampling was used for incoherent data acquisition. MR Multitasking was used to reconstruct 6‐dimensional images with 3 spatial dimensions, 1 T1 recovery dimension for dynamic T1 quantification, 1 respiratory dimension to resolve respiratory motion, and 1 DCE time dimension to capture the contrast kinetics. Sixteen healthy subjects and 14 patients with pathologically confirmed PDAC were recruited for the in vivo studies, and kinetic parameters vp, Ktrans, ve, and Kep were evaluated for each subject. Intersession repeatability of Multitasking DCE was assessed in 8 repeat healthy subjects. One‐way unbalanced analysis of variance was performed between control and patient groups. Results: In vivo studies demonstrated that vp, Ktrans, and Kep of PDAC were significantly lower compared with nontumoral regions in the patient group (P =.002,.003,.004, respectively) and normal pancreas in the control group (P =.011, <.001, <.001, respectively), while ve was significantly higher than nontumoral regions (P <.001) and healthy pancreas (P <.001). The kinetic parameters showed good in vivo repeatability (interclass correlation coefficient: vp, 0.95; Ktrans, 0.98; ve, 0.96; Kep, 0.99). Conclusion: The proposed Multitasking DCE is promising for the quantification of vascular properties of PDAC. Quantitative DCE parameters were repeatable in vivo and showed significant differences between normal pancreas and both tumor and nontumoral regions in patients with PDAC. [ABSTRACT FROM AUTHOR]

Purpose: To develop a simultaneous T1, T2, and ADC mapping method that provides co‐registered, distortion‐free images and enables multiparametric quantification of 3D brain coverage in a clinically feasible scan time with the MR Multitasking framework. Methods: The T1/T2/diffusion weighting was generated by a series of T2 preparations and diffusion preparations. The underlying multidimensional image containing 3 spatial dimensions, 1 T1 weighting dimension, 1 T2‐preparation duration dimension, 1 b‐value dimension, and 1 diffusion direction dimension was modeled as a 5‐way low‐rank tensor. A separate real‐time low‐rank model incorporating time‐resolved phase correction was also used to compensate for both inter‐shot and intra‐shot phase inconsistency induced by physiological motion. The proposed method was validated on both phantom and 16 healthy subjects. The quantification of T1/T2/ADC was evaluated for each case. Three post‐surgery brain tumor patients were scanned for demonstration of clinical feasibility. Results: Multitasking T1/T2/ADC maps were perfectly co‐registered and free from image distortion. Phantom studies showed substantial quantitative agreement (R2=0.999) with reference protocols for T1/T2/ADC. In vivo studies showed nonsignificant T1 (P =.248), T2 (P =.97), ADC (P =.328) differences among the frontal, parietal, and occipital regions. Although Multitasking showed significant differences of T1 (P =.03), T2 (P <.001), and ADC (P =.001) biases against the references, the mean bias estimates were small (ΔT1% < 5%, ΔT2% < 7%, ΔADC% < 5%), with all intraclass correlation coefficients greater than 0.82 indicating "excellent" agreement. Patient studies showed that Multitasking T1/T2/ADC maps were consistent with the clinical qualitative images. Conclusion: The Multitasking approach simultaneously quantifies T1/T2/ADC with substantial agreement with the references and is promising for clinical applications. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to evaluate the thrombus characteristics affecting the extent of recanalization to identify patients with severe cerebral venous sinus thrombus (CVT) more likely to benefit from endovascular therapy. Methods: Severe CVT patients scheduled for endovascular treatment were prospectively recruited into the study. Each thrombosed venous segment was evaluated regarding complete or partial recanalization based on digital subtraction angiography (DSA) after treatment. Magnetic resonance black‐blood thrombus imaging (MRBTI) was performed 1 day before endovascular treatment. The signal‐to‐noise ratio (SNR) of the clot, age of the clot, and baseline volume of the clot were compared between the complete and partial recanalization groups. A logistic regression analysis was performed to identify the association between these clot characteristics and recanalization status. Results: Twenty‐one CVT patients undergoing endovascular therapy were prospectively included. There were 110 thrombosed segments, 54 of these segments were completely recanalized after endovascular treatment. An acute clot sign (ACS) was found in 39 segments and a subacute clot sign (SCS) was found in 71 segments. There was no significant difference on baseline volume of the clot (1638.8 ± 1432.2 mm3 vs. 1957.5 ± 2056.1 mm3, P > 0.05) between the complete and partial recanalization groups. Logistic regression analysis showed that ACS on MRBTI was associated with complete recanalization (P < 0.001, odds ratio = 3.937, 95% confidence interval, 1.6–9.5). Interpretation: ACS can be used to predict complete recanalization in patients undergoing endovascular treatment. MRBTI provides a robust method to define clot composition and is potentially useful in selecting the most appropriate CVT patients for endovascular treatment. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the accuracy and repeatability of a free‐breathing, non‐electrocardiogram (ECG), continuous myocardial T1 and extracellular volume (ECV) mapping technique adapted from the Multitasking framework. Methods: The Multitasking framework is adapted to quantify both myocardial native T1 and ECV with a free‐breathing, non‐ECG, continuous acquisition T1 mapping method. We acquire interleaved high–spatial resolution image data and high–temporal resolution auxiliary data following inversion‐recovery pulses at set intervals and perform low‐rank tensor imaging to reconstruct images at 344 inversion times, 20 cardiac phases, and 6 respiratory phases. The accuracy and repeatability of Multitasking T1 mapping in generating native T1 and ECV maps are compared with conventional techniques in a phantom, a simulation, 12 healthy subjects, and 10 acute myocardial infarction patients. Results: In phantoms, Multitasking T1 mapping correlated strongly with the gold‐standard spin‐echo inversion recovery (R2 = 0.99). A simulation study demonstrated that Multitasking T1 mapping has similar myocardial sharpness to the fully sampled ground truth. In vivo native T1 and ECV values from Multitasking T1 mapping agree well with conventional MOLLI values and show good repeatability for native T1 and ECV mapping for 60 seconds, 30 seconds, or 15 seconds of data. Multitasking native T1 and ECV in myocardial infarction patients correlate positively with values from MOLLI. Conclusion: Multitasking T1 mapping can quantify native T1 and ECV in the myocardium with free‐breathing, non‐ECG, continuous scans with good image quality and good repeatability in vivo in healthy subjects, and correlation with MOLLI T1 and ECV in acute myocardial infarction patients. [ABSTRACT FROM AUTHOR]

Purpose: To develop a dynamic contrast‐enhanced (DCE) MRI method capable of high spatiotemporal resolution, 3D carotid coverage, and T1‐based quantification of contrast agent concentration for the assessment of carotid atherosclerosis using a newly developed Multitasking technique. Methods: 5D imaging with 3 spatial dimensions, 1 T1 recovery dimension, and 1 DCE time dimension was performed using MR Multitasking based on low‐rank tensor modeling, which allows direct T1 quantification with high spatiotemporal resolution (0.7 mm isotropic and 595 ms, respectively). Saturation recovery preparations followed by 3D segmented fast low angle shot readouts were implemented with Gaussian‐density random 3D Cartesian sampling. A bulk motion removal scheme was developed to improve image quality. The proposed protocol was tested in phantom and human studies. In vivo scans were performed on 14 healthy subjects and 7 patients with carotid atherosclerosis. Kinetic parameters including area under the concentration versus time curve (AUC), vp, Ktrans, and ve were evaluated for each case. Results: Phantom experiments showed that T1 measurements using the proposed protocol were in good agreement with reference value (R2=0.96). In vivo studies demonstrated that AUC, vp, and Ktrans in the patient group were significantly higher than in the control group (0.63 ± 0.13 versus 0.42 ± 0.12, P < 0.001; 0.14 ± 0.05 versus 0.11 ± 0.03, P = 0.034; and 0.13 ± 0.04 versus 0.08 ± 0.02, P < 0.001, respectively). Results from repeated subjects showed good interscan reproducibility (intraclass correlation coefficient: vp, 0.83; Ktrans, 0.87; ve, 0.92; AUC, 0.94). Conclusion: Multitasking DCE is a promising approach for quantitatively assessing the vascularity properties of the carotid vessel wall. [ABSTRACT FROM AUTHOR]

Purpose: There is an increased interest to determine the exchange rate using CEST to provide pH information. However, current CEST quantification methods require lengthy scan times and do not address magnetization transfer effects. The purpose of this work was to apply the magnetic resonance fingerprinting (MRF) concept to CEST to achieve more efficient and accurate exchange rate quantification. Methods: The proposed CEST fingerprinting method used varying saturation powers and saturation times to create unique signal evolutions for different exchange rates. The acquired signal was matched to a predefined dictionary to determine the exchange rate. The magnetization transfer effects were also addressed in the framework of CEST fingerprinting: The simulated dictionary could predict the signal curves without magnetization transfer effects, and comparing the dictionary to the acquired signals allowed the correction of the magnetization transfer effects. The CEST fingerprinting method was compared with the conventional pulsed quantitative CEST method using omega plots in the creatine phantom study. Results: The CEST fingerprinting method has a significantly reduced scan time (10 minutes versus 50 minutes) while providing more accurate exchange rate quantification using literature values as the reference. Conclusion: In this study, we demonstrate that CEST fingerprinting is more efficient (5 times faster) compared with pulsed quantitative CEST. It is also shown that the results of the proposed CEST fingerprinting technique are much closer to the literature values than pulsed quantitative CEST at 3 T. [ABSTRACT FROM AUTHOR]

Purpose In radiation treatment planning for thoracic and abdominal tumors, 4D- MRI has shown promise in respiratory motion characterization with improved soft-tissue contrast compared to clinical standard, 4D computed tomography (4D- CT). This study aimed to further improve vessel-tissue contrast and overall image quality in 3D radial sampling-based 4D- MRI using a slab-selective ( SS) excitation approach. Methods The technique was implemented in a 3D radial sampling with self-gating-based k-space sorting sequence. The SS excitation approach was compared to a non-selective ( NS) approach in six cancer patients and two healthy volunteers at 3T. Improvements in vessel-tissue contrast ratio ( CR) and vessel signal-to-noise ratio ( SNR) were analyzed in five of the eight subjects. Image quality was visually assessed in all subjects on a 4-point scale (0: poor; 3: excellent). Tumor (patients) and pancreas (healthy) motion trajectories were compared between the two imaging approaches. Results Compared with NS-4D- MRI, SS-4D- MRI significantly improved the overall vessel-tissue CR (2.60 ± 3.97 vs. 1.03 ± 1.44, P < 0.05), SNR (63.33 ± 38.45 vs. 35.74 ± 28.59, P < 0.05), and image quality score (2.6 ± 0.5 vs. 1.4 ± 0.5, P = 0.02). Motion trajectories from the two approaches exhibited strong correlation in the superior-inferior (0.96 ± 0.06), but weaker in the anterior-posterior (0.78 ± 0.24) and medial-lateral directions (0.46 ± 0.44). Conclusions The proposed 4D- MRI with slab-selectively excited 3D radial sampling allows for improved blood SNR, vessel-tissue CR, and image quality. [ABSTRACT FROM AUTHOR]

Aim. To investigate the clinical relevance of plaque’s morphological characteristics and distribution pattern using 3.0 T high-resolution magnetic resonance imaging (HRMRI) in patients with moderate or severe basilar artery (BA) atherosclerosis stenosis. Materials and Methods. Fifty-seven patients (33 symptomatic patients and 24 asymptomatic patients) were recruited for 3.0 T HRMRI scan; all of them had >50% stenosis on the BA. The intraplaque hemorrhage (IPH), contrast-enhancement pattern, and distribution of BA plaques were compared between the symptomatic and asymptomatic groups. Factors potentially associated with posterior ischemic stroke were calculated by multivariate analyses. Results. Enhancement of BA plaque was more frequently observed in symptomatic than in asymptomatic patients (27/33, 81.8% versus 11/24, 45.8%; p<0.01). In multivariate regression analysis, plaque enhancement (OR = 7.193; 95% CI: 1.880–27.517; p=0.004) and smoking (OR = 4.402; 95% CI: 2.218–15.909; p=0.024) were found to be independent risk factors of posterior ischemic events in patients with BA stenosis >50%. Plaques were mainly distributed at the ventral site (39.3%) or involved more than two arcs (21.2%) in the symptomatic group but were mainly distributed at left (33.3%) and right (25.0%) sites in the asymptomatic group. [ABSTRACT FROM AUTHOR]

Purpose: To propose and evaluate a parameter tune-up solution to expedite a three-dimensional (3D) variable-flip-angle turbo spin-echo (TSE) sequence for whole-brain intracranial vessel wall (IVW) imaging.Materials and Methods: Elliptical k-space sampling and prolonged echo train length (ETL), were used to expedite a 3D variable-flip-angle TSE-based sequence. To compensate for the potential loss in vessel wall signal, optimal combination of prescribed T2 and ETL was experimentally investigated on 22 healthy volunteers at 3 Tesla. The optimized protocol (7-8 min) was then compared with a previous protocol (reference protocol, 11-12 min) in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel wall sharpness, and wall delineation quality on a 4-point scale (0:poor; 3:excellent) in 10 healthy volunteers. A pilot study of five patients was performed and lesion delineation score was used to demonstrate the diagnostic quality.Results: A protocol with ETL = 52 and prescribed T2  = 170 ms was deemed an optimized one, which, compared with the reference protocol, provided significantly improved wall SNR (12.0 ± 1.3 versus 10.0 ± 1.1; P = 0.002), wall-lumen CNR (9.7 ± 1.2 versus 8.0 ± 0.9; P = 0.002), wall-CSF CNR (2.8 ± 1.0 versus 1.7 ± 1.0; P = 0.026), similar vessel wall sharpness at both inner (1.59 ± 0.18 versus 1.58 ± 0.14, P = 0.87) and outer (1.71 ± 0.25 versus 1.83 ± 0.30; P = 0.18) boundaries, and comparable vessel wall delineation score for individual segments (1.95-3; P > 0.06). In all patients, atherosclerotic plaques (10) or wall dissection (5) were identified with a delineation score of 3 or 2.Conclusion: A parameter tune-up solution can accelerate 3D variable-flip-angle TSE acquisitions, particularly allowed for expedited whole-brain IVW imaging with preserved wall delineation quality.Level Of Evidence: 2. Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:751-757. [ABSTRACT FROM AUTHOR]

Purpose Although three-dimensional (3D) turbo spin echo (TSE) with variable flip angles has proven to be useful for intracranial vessel wall imaging, it is associated with inadequate suppression of cerebrospinal fluid (CSF) signals and limited spatial coverage at 3 Tesla (T). This work aimed to modify the sequence and develop a protocol to achieve whole-brain, CSF-attenuated T1-weighted vessel wall imaging. Methods Nonselective excitation and a flip-down radiofrequency pulse module were incorporated into a commercial 3D TSE sequence. A protocol based on the sequence was designed to achieve T1-weighted vessel wall imaging with whole-brain spatial coverage, enhanced CSF-signal suppression, and isotropic 0.5-mm resolution. Human volunteer and pilot patient studies were performed to qualitatively and quantitatively demonstrate the advantages of the sequence. Results Compared with the original sequence, the modified sequence significantly improved the T1-weighted image contrast score (2.07 ± 0.19 versus 3.00 ± 0.00, P = 0.011), vessel wall-to-CSF contrast ratio (0.14 ± 0.16 versus 0.52 ± 0.30, P = 0.007) and contrast-to-noise ratio (1.69 ± 2.18 versus 4.26 ± 2.30, P = 0.022). Significant improvement in vessel wall outer boundary sharpness was observed in several major arterial segments. Conclusions The new 3D TSE sequence allows for high-quality T1-weighted intracranial vessel wall imaging at 3 T. It may potentially aid in depicting small arteries and revealing T1-mediated high-signal wall abnormalities. Magn Reson Med 77:1142-1150, 2017. © 2016 International Society for Magnetic Resonance in Medicine [ABSTRACT FROM AUTHOR]

Purpose: The presence of subendocardial dark-rim artifact (DRA) remains an ongoing challenge in first-pass perfusion (FPP) cardiac magnetic resonance imaging (MRI). We propose a free-breathing FPP imaging scheme with Cartesian sampling that is optimized to minimize the DRA and readily enables near-instantaneous image reconstruction.Materials and Methods: The proposed FPP method suppresses Gibbs ringing effects-a major underlying factor for the DRA-by "shaping" the underlying point spread function through a two-step process: 1) an undersampled Cartesian sampling scheme that widens the k-space coverage compared to the conventional scheme; and 2) a modified parallel-imaging scheme that incorporates optimized apodization (k-space data filtering) to suppress Gibbs-ringing effects. Healthy volunteer studies (n = 10) were performed to compare the proposed method against the conventional Cartesian technique-both using a saturation-recovery gradient-echo sequence at 3T. Furthermore, FPP imaging studies using the proposed method were performed in infarcted canines (n = 3), and in two symptomatic patients with suspected coronary microvascular dysfunction for assessment of myocardial hypoperfusion.Results: Width of the DRA and the number of DRA-affected myocardial segments were significantly reduced in the proposed method compared to the conventional approach (width: 1.3 vs. 2.9 mm, P < 0.001; number of segments: 2.6 vs. 8.7; P < 0.0001). The number of slices with severe DRA was markedly lower for the proposed method (by 10-fold). The reader-assigned image quality scores were similar (P = 0.2), although the quantified myocardial signal-to-noise ratio was lower for the proposed method (P < 0.05). Animal studies showed that the proposed method can detect subendocardial perfusion defects and patient results were consistent with the gold-standard invasive test.Conclusion: The proposed free-breathing Cartesian FPP imaging method significantly reduces the prevalence of severe DRAs compared to the conventional approach while maintaining similar resolution and image quality.Level Of Evidence: 2 J. Magn. Reson. Imaging 2017;45:542-555. [ABSTRACT FROM AUTHOR]

Purpose To investigate the feasibility of blood pressure difference measurement, ΔP, across the coronary artery using phase contrast (PC)-MRI for potential noninvasive assessment of the functional significance of coronary artery stenosis. Methods Three-directional velocities in the coronary arteries acquired using 2D-PC-MRI were used with the Navier-Stokes equations to derive ΔP. Repeat phantom studies were performed to assess the reproducibility of flow velocity and ΔP. ΔP derived using PC-MRI (ΔPMR) and that obtained using pressure transducer (ΔPPT) were compared. Reproducibility of coronary flow velocity was assessed in healthy controls (n = 11). Patients with suspected coronary artery disease (n = 6) were studied to evaluate the feasibility of ΔPMR measurement across a coronary stenosis. Results Phantom: Good overall reproducibility of flow velocity and ΔP measurements and excellent correlation (ΔPMR vs ΔPPT) was observed: intraclass correlation (ICC) of 0.95(Vz), 0.72(Vx), 0.73(Vy), and 0.87(ΔPMR) and R2 = 0.94, respectively. Human: Good reproducibility of coronary flow velocity was observed: ICC of 0.94/0.95(Vz), 0.76/0.74(Vx), and 0.80/0.77(Vy) at cardiac phase 1/2. Significant ( p = 0.025) increase in ΔPMR was observed in patients (6.40 ± 4.43 mmHg) versus controls (0.70 ± 0.57 mmHg). Conclusion ΔPMR in the coronary arteries is feasible. Upon further validation using the invasive measure, ΔPMR has the potential for noninvasive assessment of coronary artery stenosis. Magn Reson Med 77:529-537, 2017. © 2016 International Society for Magnetic Resonance in Medicine. [ABSTRACT FROM AUTHOR]

Purpose Previous studies have associated low pH in intervertebral discs (IVDs) with discogenic back pain. The purpose of this study was to determine whether quantitative CEST (qCEST) MRI can be used to detect pH changes in IVDs in vivo. Methods The exchange rate ksw between glycosaminoglycan (GAG) protons and water protons was determined from qCEST analysis. Its dependence on pH value was investigated in GAG phantoms with varying pH and concentrations. The relationship between ksw and pH was studied further in vivo in a porcine model on a 3T MR scanner and validated using a pH meter. Sodium lactate was injected into the IVDs to induce various pH values within the discs ranging from 5 to 7. Results Phantom and animal results revealed that ksw measured using qCEST MRI is highly correlated with pH level. In the animal studies, the relationship can be described as ksw =9.2 × 106 × 10−pH + 196.9, R2 = 0.7883. Conclusion The exchange rate between GAG and water protons determined from qCEST MRI is closely correlated with pH value. This technique has the potential to noninvasively measure pH in the IVDs of patients with discogenic pain. Magn Reson Med 76:1677-1683, 2016. © 2016 International Society for Magnetic Resonance in Medicine [ABSTRACT FROM AUTHOR]

Purpose: To pathologically verify the correlation between native T1 mapping, postcontrast T1 mapping, and extracellular volume fraction (ECV) and myocardial diffuse fibrosis, as determined by collagen volume fraction (CVF).Materials and Methods: Thirty New Zealand white rabbits were randomly divided into the control group (n = 6), diabetes 3 months group (n = 8), diabetes 6 months group (n = 8), and diabetes 9 months group (n = 8). All the rabbits underwent clinical 3.0T magnetic resonance (MR) examinations with pre- and postcontrast modified Look-Locker inversion recovery T1 mapping. For the histological study, each rabbit was sacrificed after MR scanning, hematoxylin and eosin and Masson staining of the left ventricular myocardium were performed, and CVF was calculated. Pre- and postcontrast T1 values and ECV were compared to CVF using Pearson's correlation coefficients.Results: Two rabbits died in each diabetes group, thus each group included six rabbits. ECV calculated from pre- and postcontrast T1 values showed a very strong correlation with CVF (r = 0.876, P < 0.001), whereas postcontrast T1 values exhibited a moderate correlation with CVF (r = -0.564, P = 0.004). In contrast, precontrast T1 values showed no correlation with CVF (r = 0.311, P = 0.139).Conclusion: ECV has a very strong correlation with pathological CVF, and can be used to assess the degree of diffuse myocardial fibrosis better than the postcontrast T1 value. Precontrast T1 value has no significant correlation with diffuse myocardial fibrosis. J. Magn. Reson. Imaging 2016;44:1179-1185. [ABSTRACT FROM AUTHOR]

Purpose To optimize a diffusion-prepared balanced steady-state free precession cardiac MRI (CMR) technique to perform diffusion-tensor CMR (DT-CMR) in humans on a 3 Tesla clinical scanner Methods A previously developed second order motion compensated (M2) diffusion-preparation scheme was significantly shortened (40%) yielding sufficient signal-to-noise ratio for DT-CMR imaging. In 20 healthy volunteers and 3 heart failure (HF) patients, DT-CMR was performed comparing no motion compensation (M0), first order motion compensation (M1), and the optimized M2. Mean diffusivity (MD), fractional anisotropy (FA), helix angle (HA), and HA transmural slope (HATS) were calculated. Reproducibility and success rate (SR) were investigated. Results M2-derived left ventricular (LV) MD, FA, and HATS (1.4 ± 0.2 μm2/ms, 0.28 ± 0.06, −1.0 ± 0.2 °/%trans) were significantly ( P < 0.001) less than M1 (1.8 ± 0.3 μm2/ms, 0.46 ± 0.14, −0.1 ± 0.3 °/%trans) and M0 (4.8 ± 1.0 μm2/ms, 0.70 ± 0.14, 0.1 ± 0.3 °/%trans) indicating less motion corruption and yielding values more consistent with previous literature. M2-derived DT-CMR parameters had higher reproducible (ICC > 0.85) and SR (82%) than M1 (ICC = 0.20-0.85; SR = 37%) and M0 (ICC = 0.20-0.30; SR = 11%). M2 DT-CMR was able to yield HA maps with smooth transmural transition from endocardium to epicardium. Conclusion The proposed M2 DT-CMR reproducibly yielded bulk motion robust estimations of mean LV MD, FA, HA, and HATS on a 3T clinical scanner. Magn Reson Med 76:1354-1363, 2016. © 2016 International Society for Magnetic Resonance in Medicine [ABSTRACT FROM AUTHOR]

Purpose To improve the coronary visualization quality of four-dimensional (4D) coronary MR angiography (MRA) through cardiac motion correction and iterative reconstruction. Methods A contrast-enhanced, spoiled gradient echo sequence with 3D radial trajectory and self-gating was used for 4D coronary MRA data acquisition at 3 Tesla. A whole-heart 16-phase cine series was reconstructed with respiratory motion correction. Nonrigid registration was performed between the identified quiescent phases and a reference. The motion information of all included phases was then used along with the corresponding k-space data to iteratively reconstruct the final image. Healthy volunteer studies (N = 13) were conducted to compare the proposed method with the conventional strategy, which accepts data from a single, contiguous window out of the original 16-phase data. Apparent signal-to-noise ratio (aSNR) and coronary sharpness were used as the image quality metrics. Results The proposed method significantly improved aSNR (11.89 ± 3.76 to 13.97 ± 5.21; P = 0.005) and scan efficiency (18.8% ± 6.0% to 40.9% ± 9.7%; P < 0.001), compared with the conventional strategy. Sharpness of left main ( P = 0.002), proximal ( P = 0.04), and middle ( P = 0.02) right coronary artery, and proximal left anterior descending ( P = 0.04) was also significantly improved. Conclusion The proposed cardiac motion-corrected reconstruction significantly improved the achievable quality of coronary visualization from 4D coronary MRA. Magn Reson Med 76:1345-1353, 2016. © 2016 International Society for Magnetic Resonance in Medicine [ABSTRACT FROM AUTHOR]

Purpose The purpose of this study was to develop a three-dimensional black blood imaging method for simultaneously evaluating the carotid and intracranial arterial vessel walls with high spatial resolution and excellent blood suppression with and without contrast enhancement. Methods The delay alternating with nutation for tailored excitation (DANTE) preparation module was incorporated into three-dimensional variable flip angle turbo spin echo (SPACE) sequence to improve blood signal suppression. Simulations and phantom studies were performed to quantify image contrast variations induced by DANTE. DANTE-SPACE, SPACE, and two-dimensional turbo spin echo were compared for apparent signal-to-noise ratio, contrast-to-noise ratio, and morphometric measurements in 14 healthy subjects. Preliminary clinical validation was performed in six symptomatic patients. Results Apparent residual luminal blood was observed in five (pre-contrast) and nine (post-contrast) subjects with SPACE and only two (post-contrast) subjects with DANTE-SPACE. DANTE-SPACE showed 31% (pre-contrast) and 100% (post-contrast) improvement in wall-to-blood contrast-to-noise ratio over SPACE. Vessel wall area measured from SPACE was significantly larger than that from DANTE-SPACE due to possible residual blood signal contamination. DANTE-SPACE showed the potential to detect vessel wall dissection and identify plaque components in patients. Conclusion DANTE-SPACE significantly improved arterial and venous blood suppression compared with SPACE. Simultaneous high-resolution carotid and intracranial vessel wall imaging to potentially identify plaque components was feasible with a scan time under 6 min. Magn Reson Med 75:2286-2294, 2016. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Purpose Accurate quantification of myocardial perfusion is dependent on reliable electrocardiogram (ECG) triggering. Measuring myocardial blood flow (MBF) in patients with arrhythmias or poor ECGs is currently infeasible with MR. The purpose of this study was to demonstrate the feasibility of a non-ECG-triggered method with clinically useful three-slice ventricular coverage for measurement of MBF in healthy volunteers. Methods A saturation recovery magnetization-prepared gradient recalled echo acquisition was continuously repeated during first-pass imaging. A slice-interleaved radial trajectory was employed to enable image-based retrospective triggering. The arterial input function was generated using a beat-by-beat T1 estimation method. The proposed technique was validated against a conventional ECG-triggered dual-bolus technique in 10 healthy volunteers. The technique was further demonstrated under adenosine stress in 12 healthy volunteers. Results The proposed method produced MBF with no significant difference compared with the ECG-triggered technique. The proposed method yielded mean myocardial perfusion reserve comparable to published literature. Conclusion We have developed a non-ECG-triggered quantitative perfusion imaging method. In this preliminary study, our results demonstrate that our method yields comparable MBF compared with the conventional ECG-triggered method and that it is feasible for stress imaging. Magn Reson Med 75:2112-2120, 2016. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Purpose: To develop a four-dimensional MRI (4D-MRI) technique to characterize the average respiratory tumor motion for abdominal radiotherapy planning. Methods: A continuous spoiled gradient echo sequence was implemented with 3D radial trajectory and 1D self-gating for respiratory motion detection. Data were retrospectively sorted into different respiratory phases based on their temporal locations within a respiratory cycle, and each phase was reconstructed by means of a self-calibrating CG-SENSE program. Motion phantom, healthy volunteer and patient studies were performed to validate the respiratory motion detected by the proposed method against that from a 2D real-time protocol. Results: The proposed method successfully visualized the respiratory motion in phantom and human subjects. The 4DMRI and real-time 2D-MRI yielded comparable superior-inferior (SI) motion amplitudes (intraclass correlation=0.935) with up-to one pixel mean absolute differences in SI displacements over 10 phases and high cross-correlation between phaseresolved displacements (phantom: 0.985; human: 0.937- 0.985). Comparable anterior-posterior and left-right displacements of the tumor or gold fiducial between 4D and real-time 2D-MRI were also observed in the two patients, and the hysteresis effect was shown in their 3D trajectories. Conclusion: We demonstrated the feasibility of the proposed 4D-MRI technique to characterize abdominal respiratory motion, which may provide valuable information for radiotherapy planning. [ABSTRACT FROM AUTHOR]

Purpose Three-dimensional (3D) dark-blood MRI has shown great potential in coronary artery plaque evaluation. However, substantial variability in quantification could result from superficial calcification because of its low signal. To address this issue, a 3D coronary dark-blood interleaved with gray-blood (cDIG) technique was developed. Methods cDIG is based on a balanced steady-state free precession readout combined with a local re-inversion-based double-inversion-recovery (LocReInv-DIR) preparation. The LocReInv-DIR is applied every two RR intervals. Dark-blood and gray-blood contrasts are collected in the first and second RR interval, respectively. To improve the respiratory gating efficiency, two independent navigators were developed to separately gate the respiratory motion for the two interleaved acquisitions. In vivo experiments in eight healthy subjects and one patient were conducted to validate the technique. Results cDIG provided dual-contrasts without compromise in scan time. The dark-blood images with cDIG demonstrated excellent wall and lumen signal performances and morphological measurements. Advantageously, cDIG yielded a second contrast that was shown to help identify the superficial calcification in the coronary plaque of a patient. Conclusion A novel technique was developed for obtaining 3D coronary vessel wall and gray lumen images. The additional contrast may aid in identifying calcified nodules and thus potentially improve the evaluation of coronary plaque burden. Magn Reson Med 75:997-1007, 2016. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Background: To develop and assess a sequence using DANTE dark-blood preparation combined with FLASH readout (DANTE-FLASH) for rapid isotropic-resolution three-dimensional (3D) peripheral vessel wall imaging at 3 Tesla (T).Methods: Numerical simulations were first conducted to optimize imaging parameters for maximizing the wall-lumen contrast. The sequence, implemented at 3T, was then assessed in the bilateral superficial femoral arteries of eight healthy volunteers and three patients who were undergoing non-contrast-enhanced MRA due to known peripheral artery disease. Conventional 2D dark-blood turbo spin echo (DB-TSE) was performed as a reference in all subjects. Image quality on a 5-point scale, apparent wall signal-to-noise ratio, apparent wall-lumen contrast-to-noise ratio, wall thickness, wall area and lumen area were assessed or measured in all healthy subjects. Additionally, the agreement in the depiction of wall thickening or luminal stenosis between DANTE-FLASH and DB-TSE, or MRA was assessed using a 4-point scale in the patient study.Results: DANTE-FLASH allowed for a 30-cm-long coverage within 4 min, whereas DB-TSE took approximately 7 min for a 9-cm-long coverage. Good image quality was obtained by DANTE-FLASH (score > 3). The wall thickness, wall area, and lumen area were all comparable (t-test; P = 0.334, 0.224 and 0.136) and showed excellent agreement between DANTE-FLASH and DB-TSE (intra-class correlation = 0.81, 0.85, and 0.98). The atherosclerotic plaques and luminal stenosis identified by DANTE-FLASH were in accordance with the findings by 2D DB-TSE or MRA.Conclusion: DANTE-FLASH is a 3D dark-blood MR sequence allowing for rapid isotropic-resolution imaging of the peripheral vessel wall at 3T. [ABSTRACT FROM AUTHOR]