Purpose Liver T 1 mapping techniques typically require long breath holds or long scan time in free‐breathing, need correction for inhomogeneities and process composite (water and fat) signals. The purpose of this work is to accelerate the multi‐slice acquisition of liver water selective T 1 (wT 1 ) mapping in a single breath hold, improving the k ‐space sampling efficiency. Methods The proposed continuous inversion‐recovery (IR) Look‐Locker methodology combines a single‐shot gradient echo spiral readout, Dixon processing and a dictionary‐based analysis for liver wT 1 mapping at 3 T. The sequence parameters were adapted to obtain short scan times. The influence of fat, inhomogeneities and TE on the estimation of T 1 was first assessed using simulations. The proposed method was then validated in a phantom and in 10 volunteers, comparing it with MRS and the modified Look‐Locker inversion‐recovery (MOLLI) method. Finally, the clinical feasibility was investigated by comparing wT 1 maps with clinical scans in nine patients. Results The phantom results are in good agreement with MRS. The proposed method encodes the IR‐curve for the liver wT 1 estimation, is minimally sensitive to inhomogeneities and acquires one slice in 1.2 s. The volunteer results confirmed the multi‐slice capability of the proposed method, acquiring nine slices in a breath hold of 11 s. The present work shows robustness to inhomogeneities ( , good repeatability ( and is in better agreement with MRS ( than is MOLLI ( . The wT 1 maps in patients captured diverse lesions, thus showing their clinical feasibility. Conclusion A single‐shot spiral acquisition can be combined with a continuous IR Look‐Locker method to perform rapid repeatable multi‐slice liver water T 1 mapping at a rate of 1.2 s per slice without a map. The proposed method is suitable for nine‐slice liver clinical applications acquired in a single breath hold of 11 s.

Purpose T-1 mapping is a widely used quantitative MRI technique, but its tissue-specific values remain inconsistent across protocols, sites, and vendors. The ISMRM Reproducible Research and Quantitative MR study groups jointly launched a challenge to assess the reproducibility of a well-established inversion-recovery T-1 mapping technique, using acquisition details from a seminal T-1 mapping paper on a standardized phantom and in human brains. Methods The challenge used the acquisition protocol from Barral et al. (2010). Researchers collected T-1 mapping data on the ISMRM/NIST phantom and/or in human brains. Data submission, pipeline development, and analysis were conducted using open-source platforms. Intersubmission and intrasubmission comparisons were performed. Results Eighteen submissions (39 phantom and 56 human datasets) on scanners by three MRI vendors were collected at 3 T (except one, at 0.35 T). The mean coefficient of variation was 6.1% for intersubmission phantom measurements, and 2.9% for intrasubmission measurements. For humans, the intersubmission/intrasubmission coefficient of variation was 5.9/3.2% in the genu and 16/6.9% in the cortex. An interactive dashboard for data visualization was also eveloped: https://rrsg2020.dashboards.neurolibre.org. Conclusion The T-1 intersubmission variability was twice as high as the intrasubmission variability in both phantoms and human brains, indicating that the acquisition details in the original paper were insufficient to reproduce a quantitative MRI protocol. This study reports the inherent uncertainty in T-1 measures across independent research groups, bringing us one step closer to a practical clinical baseline of T-1 variations in vivo.

Motivation: Most MR methods for quantifying microvascular properties involve the injection of exogenous contrast agents (CA). Goal(s): We propose an innovative MRI method that simultaneously maps the deoxygenated cerebral blood volume (CBV), microvascular geometry (averaged vessel radius), and relaxometry (T1&T2) without CA injection. Approach: Acquisitions are made using a multi-echo, phase-cycled, bSSFP-sequence acquired in transient and pseudo-steady-state regimes. Reconstruction of the maps is made under the MRFingerprinting framework using realistic 3D microvessel representations. Magnetic field distributions (B1&B0) are also taken into account. Results: Preliminary results on five healthy volunteers are in line with previous measurements made with MRF and PWI with gadolinium injection. Impact: We propose a contrast-free quantification technique of microvascular properties and relaxation times. It could be useful for functional experiments as well as clinical investigations of several cerebrovascular pathologies including stroke and cancer.

Lower-field MR is reemerging as a viable, potentially cost-effective alternative to high-field MR, thanks to advances in hardware, sequence design, and reconstruction over the past decades. Evaluation of lower field strengths, however, is limited by the availability of lower-field systems on the market and their considerable procurement costs. In this work, we demonstrate a low-cost, temporary alternative to purchasing a dedicated lower-field MR system.By ramping down an existing clinical 3 T MRI system to 0.75 T, proton signals can be acquired using repurposed 13C transmit/receive hardware and the multi-nuclei spectrometer interface. We describe the ramp-down procedure and necessary software and hardware changes to the system.Apart from presenting system characterization results, we show in vivo examples of cardiac cine imaging, abdominal two- and three-point Dixon-type water/fat separation, water/fat-separated MR Fingerprinting, and point-resolved spectroscopy. In addition, the ramp-down approach allows unique comparisons of, e.g., gradient fidelity of the same MR system operated at different field strengths using the same receive chain, gradient coils, and amplifiers.Ramping down an existing MR system may be seen as a viable alternative for lower-field MR research in groups that already own multi-nuclei hardware and can also serve as a testing platform for custom-made multi-nuclei transmit/receive coils.

This dataset includes both raw data and processed T1 maps obtained from the 2020 challenge on inversion recovery T1 mapping organized by the International Society in Magnetic Resonance in Medicine (ISMRM) Reproducible Research Study Group (RRSG). For a comprehensive overview of the data distribution submitted for this challenge, please visit https://rrsg2020.db.neurolibre.org. It's important to note that this dataset exclusively comprises ISMRM-NIST system phantom data. Dataset provided for NeuroLibre preprint. Author repo: https://github.com/rrsg2020/paper NeuroLibre fork:https://github.com/roboneurolibre/paper For details, please visit the corresponding NeuroLibre technical screening. https://neurolibre.org

MR fingerprinting (MRF) enables fast multiparametric quantitative imaging with a single acquisition and has been shown to improve diagnosis of prostate cancer. However, most prostate MRF studies were performed with spiral acquisitions that are sensitive to B0 inhomogeneities and consequent blurring. In this work, a radial MRF acquisition with a novel subspace reconstruction technique was developed to enable fast T1/T2 mapping in the prostate in under 4 min. The subspace reconstruction exploits the extensive temporal correlations in the MRF dictionary to pre-compute a low dimensional space for the solution and thus reduce the number of radial spokes to accelerate the acquisition. Iterative reconstruction with the subspace model and additional regularization of the signal representation in the subspace is performed to minimize the number of spokes and maintain matching quality and SNR. Reconstruction accuracy was assessed using the ISMRM NIST phantom. In-vivo validation was performed on two healthy subjects and two prostate cancer patients undergoing radiation therapy. The longi-tudinal repeatability was quantified using the concordance correlation coefficient (CCC) in one of the healthy subjects by repeated scans over 1 year. One prostate cancer patient was scanned at three time points, before initiating therapy and following brachytherapy and external beam radiation. Changes in the T1/T2 maps ob-tained with the proposed method were quantified. The prostate, peripheral and transitional zones, and visible dominant lesion were delineated for each study, and the statistics and distribution of the quantitative mapping values were analyzed. Significant image quality improvements compared with standard reconstruction methods were obtained with the proposed subspace reconstruction method. A notable decrease in the spread of the T1/T2 values without biasing the estimated mean values was observed with the subspace reconstruction and agreed with reported literature values. The subspace reconstruction enabled visualization of small differences in T1/T2 values in the tumor region within the peripheral zone. Longitudinal imaging of a volunteer subject yielded CCC of 0.89 for MRF T1, and 0.81 for MRF T2 in the prostate gland. Longitudinal imaging of the prostate patient confirmed the feasibility of capturing radiation treatment related changes. This work is a proof-of-concept for a high resolution and fast quantitative mapping using golden-angle radial MRF combined with a subspace reconstruction technique for longitudinal treatment response assessment in subjects undergoing radiation treatment.

To evaluate a silent MR active catheter tracking sequence that allows conducting catheter interventions with low acoustic noise levels.

Purpose Magnetic resonance fingerprinting (MRF) offers rapid quantitative imaging but may be subject to confounding effects (CE) if these are not included in the model‐based reconstruction. This study characterizes the influence of in‐plane , slice profile and diffusion effects on T 1 and T 2 estimation in the female breast at 1.5T. Methods Simulations were used to predict the influence of each CE on the accuracy of MRF and to investigate the influence of electronic noise and spiral aliasing artefacts. The experimentally observed bias in regions of fibroglandular tissue (FGT) and fatty tissue (FT) was analyzed for undersampled spiral breast MRF data of 6 healthy volunteers by performing MRF reconstruction with and without a CE. Results Theoretic analysis predicts T 1 under‐/T 2 overestimation if the nominal flip angles are underestimated and inversely, T 1 under‐/T 2 overestimation if omitting slice profile correction, and T 1 under‐/T 2 underestimation if omitting diffusion in the signal model. Averaged over repeated signal simulations, including spiral aliasing artefacts affected precision more than accuracy. Strong in‐plane effects occurred in vivo, causing T 2 left–right inhomogeneity between both breasts. Their correction decreased the T 2 difference from 29 to 5 ms in FGT and from 29 to 9 ms in FT. Slice profile correction affected FGT T 2 most strongly, resulting in −22% smaller values. For the employed spoiler gradient strengths, diffusion did not affect the parameter maps, corresponding well with theoretic predictions. Conclusion Understanding CEs and their relative significance for an MRF sequence is important when defining an MRF signal model for accurate parameter mapping.

PURPOSE:To develop a novel respiratory motion compensated three-dimensional (3D) cardiac magnetic resonance fingerprinting (cMRF) approach for whole-heart myocardial T1 and T2 mapping from a free-breathing scan.METHODS:Two-dimensional (2D) cMRF has been recently proposed for simultaneous, co-registered T1 and T2 mapping from a breath-hold scan; however, coverage is limited. Here we propose a novel respiratory motion compensated 3D cMRF approach for whole-heart myocardial T1 and T2 tissue characterization from a free-breathing scan. Variable inversion recovery and T2 preparation modules are used for parametric encoding, respiratory bellows driven localized autofocus is proposed for beat-to-beat translation motion correction and a subspace regularized reconstruction is employed to accelerate the scan. The proposed 3D cMRF approach was evaluated in a standardized T1 /T2 phantom in comparison with reference spin echo values and in 10 healthy subjects in comparison with standard 2D MOLLI, SASHA and T2 -GraSE mapping techniques at 1.5 T.RESULTS:3D cMRF T1 and T2 measurements were generally in good agreement with reference spin echo values in the phantom experiments, with relative errors of 2.9% and 3.8% for T1 and T2 (T2 < 100 ms), respectively. in vivo left ventricle (LV) myocardial T1 values were 1054 ± 19 ms for MOLLI, 1146 ± 20 ms for SASHA and 1093 ± 24 ms for the proposed 3D cMRF; corresponding T2 values were 51.8 ± 1.6 ms for T2-GraSE and 44.6 ± 2.0 ms for 3D cMRF. LV coefficients of variation were 7.6 ± 1.6% for MOLLI, 12.1 ± 2.7% for SASHA and 5.8 ± 0.8% for 3D cMRF T1 , and 10.5 ± 1.4% for T2-GraSE and 11.7 ± 1.6% for 3D cMRF T2 .CONCLUSION:The proposed 3D cMRF can provide whole-heart, simultaneous and co-registered T1 and T2 maps with accuracy and precision comparable to those of clinical standards in a single free-breathing scan of about 7 min.

Demyelination is the key pathological process in multiple sclerosis (MS). The extent of demyelination can be quantified with magnetic resonance imaging by assessing the myelin water fraction (MWF). However, long computation times and high noise sensitivity hinder the translation of MWF imaging to clinical practice. In this work, we introduce a more efficient and noise robust method to determine the MWF using a joint sparsity constraint and a pre-computed B1+-T2 dictionary.A single component analysis with this dictionary is used in an initial step to obtain a B1+ map. The T2 distribution is then determined from a reduced dictionary corresponding to the estimated B1+ map using a combination of a non-negativity and a joint sparsity constraint.The non-negativity constraint ensures that a feasible solution with non-negative contribution of each T2 component is obtained. The joint sparsity constraint restricts the T2 distribution to a small set of T2 relaxation times shared between all voxels and reduces the noise sensitivity.The applied Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm can be implemented efficiently, reducing the computation time by a factor of 50 compared to the commonly used regularized non-negative least squares algorithm. The proposed method was validated in simulations and in 8 healthy subjects with a 3D multi-echo gradient- and spin echo scan at 3 ​T. In simulations, the absolute error in the MWF decreased from 0.031 to 0.013 compared to the regularized NNLS algorithm for SNR ​= ​250. The in vivo results were consistent with values reported in literature and improved MWF-quantification was obtained especially in the frontal white matter. The maximum standard deviation in mean MWF in different regions of interest between subjects was smaller for the proposed method (0.0193) compared to the regularized NNLS algorithm (0.0266). In conclusion, the proposed method for MWF estimation is less computationally expensive and less susceptible to noise compared to state of the art methods. These improvements might be an important step towards clinical translation of MWF measurements.

Purpose To minimize the known biases introduced by fat in rapid T 1 and T 2 quantification in muscle using a single‐run magnetic resonance fingerprinting (MRF) water–fat separation sequence. Methods The single‐run MRF acquisition uses an alternating in‐phase/out‐of‐phase TE pattern to achieve water–fat separation based on a 2‐point DIXON method. Conjugate phase reconstruction and fat deblurring were applied to correct for B 0 inhomogeneities and chemical shift blurring. Water and fat signals were matched to the on‐resonance MRF dictionary. The method was first tested in a multicompartment phantom. To test whether the approach is capable of measuring small in vivo dynamic changes in relaxation times, experiments were run in 9 healthy volunteers; parameter values were compared with and without water–fat separation during muscle recovery after plantar flexion exercise. Results Phantom results show the robustness of the water–fat resolving MRF approach to undersampling. Parameter maps in volunteers show a significant ( P < .01) increase in T 1 (105 ± 94 ms) and decrease in T 2 (14 ± 6 ms) when using water–fat‐separated MRF, suggesting improved parameter quantification by reducing the well‐known biases introduced by fat. Exercise results showed smooth T 1 and T 2 recovery curves. Conclusion Water–fat separation using conjugate phase reconstruction is possible within a single‐run MRF scan. This technique can be used to rapidly map relaxation times in studies requiring dynamic scanning, in which the presence of fat is problematic.

Parkinson's disease (PD) affects more than six million people, but reliable MRI biomarkers with which to diagnose patients have not been established. Magnetic resonance fingerprinting (MRF) is a recent quantitative technique that can provide relaxometric maps from a single sequence. The purpose of this study is to assess the potential of MRF to identify PD in patients and their disease severity, as well as to evaluate comfort during MRF. Twenty‐five PD patients and 25 matching controls underwent 3 T MRI, including an axial 2D spoiled gradient echo MRF sequence. T1 and T2 maps were generated by voxel‐wise matching the measured MRF signal to a precomputed dictionary. All participants also received standard inversion recovery T1 and multi‐echo T2 mapping. An ROI‐based analysis of relaxation times was performed. Differences between patients and controls as well as techniques were determined by logistic regression, Spearman correlation and t‐test. Patients were asked to estimate the subjective comfort of the MRF sequence. Both MRF‐based T1 and T2 mapping discriminated patients from controls: T1 relaxation times differed most in cortical grey matter (PD 1337 ± 38 vs. control 1386 ± 37 ms; mean ± SD; P = .0001) and, in combination with normal‐appearing white matter, enabled correct discrimination in 85.7% of cases (sensitivity 83.3%; specificity 88.0%; receiver‐operating characteristic [ROC]) area under the curve [AUC] 0.87), while for T2 mapping the left putamen was the strongest classifier (40.54 ± 6.28 vs. 34.17 ± 4.96 ms; P = .0001), enabling differentiation of groups in 84.0% of all cases (sensitivity 80.0%; specificity 88.0%; ROC AUC 0.87). Relaxation time differences were not associated with disease severity. Standard mapping techniques generated significantly different relaxation time values and identified other structures as different between groups other than MRF. Twenty‐three out of 25 PD patients preferred the MRF examination instead of a standard MRI. MRF‐based mapping can identify PD patients with good comfort but needs further assessment regarding disease severity identification and its potential for comparability with standard mapping technique results.

Several very rare forms of dementia are associated with characteristic focal atrophy predominantly of the frontal and/or temporal lobes and currently lack imaging solutions to monitor disease. Magnetic resonance fingerprinting (MRF) is a recently developed technique providing quantitative relaxivity maps and images with various tissue contrasts out of a single sequence acquisition. This pilot study explores the utility of MRF‐based T1 and T2 mapping to discover focal differences in relaxation times between patients with frontotemporal lobe degenerative dementia and healthy controls. 8 patients and 30 healthy controls underwent a 3 T MRI including an axial 2D spoiled gradient echo MRF sequence. T1 and T2 relaxation maps were generated based on an extended phase graphs algorithm‐founded dictionary involving inner product pattern matching. A region of interest (ROI)‐based analysis of T1 and T2 relaxation times was performed with FSL and ITK‐SNAP. Depending on the brain region analyzed, T1 relaxation times were up to 10.28% longer in patients than in controls reaching significant differences in cortical gray matter (P = .047) and global white matter (P = .023) as well as in both hippocampi (P = .001 left; P = .027 right). T2 relaxation times were similarly longer in the hippocampus by up to 19.18% in patients compared with controls. The clinically most affected patient had the most control‐deviant relaxation times. There was a strong correlation of T1 relaxation time in the amygdala with duration of the clinically manifest disease (Spearman Rho = .94; P = .001) and of T1 relaxation times in the left hippocampus with disease severity (Rho = .90, P = .002). In conclusion, MRF‐based relaxometry is a promising and time‐saving new MRI tool to study focal cerebral alterations and identify patients with frontotemporal lobe degeneration. To validate the results of this pilot study, MRF is worth further exploration as a diagnostic tool in neurodegenerative diseases.

PURPOSE:To develop an efficient algorithm for multi-component analysis of magnetic resonance fingerprinting (MRF) data without making a priori assumptions about the exact number of tissues or their relaxation properties.METHODS:Different tissues or components within a voxel are potentially separable in MRF because of their distinct signal evolutions. The observed signal evolution in each voxel can be described as a linear combination of the signals for each component with a non-negative weight. An assumption that only a small number of components are present in the measured field of view is usually imposed in the interpretation of multi-component data. In this work, a joint sparsity constraint is introduced to utilize this additional prior knowledge in the multi-component analysis of MRF data. A new algorithm combining joint sparsity and non-negativity constraints is proposed and compared to state-of-the-art multi-component MRF approaches in simulations and brain MRF scans of 11 healthy volunteers.RESULTS:Simulations and in vivo measurements show reduced noise in the estimated tissue fraction maps compared to previously proposed methods. Applying the proposed algorithm to the brain data resulted in 4 or 5 components, which could be attributed to different brain structures, consistent with previous multi-component MRF publications.CONCLUSIONS:The proposed algorithm is faster than previously proposed methods for multi-component MRF and the simulations suggest improved accuracy and precision of the estimated weights. The results are easier to interpret compared to voxel-wise methods, which combined with the improved speed is an important step toward clinical evaluation of multi-component MRF.

Purpose: Magnetic resonance fingerprinting (MRF) with spiral readout enables rapid quantification of tissue relaxation times. However, it is prone to blurring because of off-resonance effects. Hence, fat blurring into adjacent regions might prevent identification of small tumors by their quantitative T-1 and T-2 values. This study aims to correct for the blurring artifacts, thereby enabling fast quantitative mapping in the female breast. Methods: The impact of fat blurring on spiral MRF results was first assessed by simulations. Then, MRF was combined with 3-point Dixon water-fat separation and spiral blurring correction based on conjugate phase reconstruction. The approach was assessed in phantom experiments and compared to Cartesian reference measurements, namely inversion recovery (IR), multi-echo spin echo (MESE), and Cartesian MRF, by normalized root-mean-square error (NRMSE) and SD calculations. Feasibility is further demonstrated in vivo for quantitative breast measurements of 6 healthy female volunteers, age range 24-31 y. Results: In the phantom experiment, the blurring correction reduced the NRMSE per phantom vial on average from 16% to 8% for T-1 and from 18% to 11% for T-2 when comparing spiral MRF to IR/MESE sequences. When comparing to Cartesian MRF, the NRMSE reduced from 15% to 8% for T-1 and from 12% to 7% for T-2. Furthermore, SDs decreased. In vivo, the blurring correction removed fat bias on T-1/T-2 from a rim of similar to 7-8 mm width adjacent to fatty structures. Conclusion: The blurring correction for spiral MRF yields improved quantitative maps in the presence of water and fat.

Purpose Cardiac magnetic resonance fingerprinting (cMRF) has been recently introduced to simultaneously provide T 1 , T 2 , and M 0 maps. Here, we develop a 3‐point Dixon‐cMRF approach to enable simultaneous water specific T 1 , T 2 , and M 0 mapping of the heart and fat fraction (FF) estimation in a single breath‐hold scan. Methods Dixon‐cMRF is achieved by combining cMRF with several innovations that were previously introduced for other applications, including a 3‐echo GRE acquisition with golden angle radial readout and a high‐dimensional low‐rank tensor constrained reconstruction to recover the highly undersampled time series images for each echo. Water–fat separation of the Dixon‐cMRF time series is performed to allow for water‐ and fat‐specific T 1 , T 2 , and M 0 estimation, whereas FF estimation is extracted from the M 0 maps. Dixon‐cMRF was evaluated in a standardized T 1 –T 2 phantom, in a water–fat phantom, and in healthy subjects in comparison to current clinical standards: MOLLI, SASHA, T 2 ‐GRASE, and 6‐point Dixon proton density FF (PDFF) mapping. Results Dixon‐cMRF water T 1 and T 2 maps showed good agreement with reference T 1 and T 2 mapping techniques (R 2 > 0.99 and maximum normalized RMSE ~5%) in a standardized phantom. Good agreement was also observed between Dixon‐cMRF FF and reference PDFF (R 2 > 0.99) and between Dixon‐cMRF water T 1 and T 2 and water selective T 1 and T 2 maps (R 2 > 0.99) in a water–fat phantom. In vivo Dixon‐cMRF water T 1 values were in good agreement with MOLLI and water T 2 values were slightly underestimated when compared to T 2 ‐GRASE. Average myocardium septal T 1 values were 1129 ± 38 ms, 1026 ± 28 ms, and 1045 ± 32 ms for SASHA, MOLLI, and the proposed water Dixon‐cMRF. Average T 2 values were 51.7 ± 2.2 ms and 42.8 ± 2.6 ms for T 2 ‐GRASE and water Dixon‐cMRF, respectively. Dixon‐cMRF FF maps showed good agreement with in vivo PDFF measurements (R 2 > 0.98) and average FF in the septum was measured at 1.3%. Conclusion The proposed Dixon‐cMRF allows to simultaneously quantify myocardial water T 1 , water T 2 , and FF in a single breath‐hold scan, enabling multi‐parametric T 1 , T 2 , and fat characterization. Moreover, reduced T 1 and T 2 quantification bias caused by water–fat partial volume was demonstrated in phantom experiments.

PURPOSE:To explore the feasibility of MR Fingerprinting (MRF) to rapidly quantify relaxation times in the human eye at 7T, and to provide a data acquisition and processing framework for future tissue characterization in eye tumor patients. METHODS:In this single-element receive coil MRF approach with Cartesian sampling, undersampling is used to shorten scan time and, therefore, to reduce the degree of motion artifacts. For reconstruction, approaches based on compressed sensing (CS) and matrix completion (MC) were used, while their effects on the quality of the MRF parameter maps were studied in simulations and experiments. Average relaxation times in the eye were measured in 6 healthy volunteers. One uveal melanoma patient was included to show the feasibility of MRF in a clinical context. RESULTS:Simulation results showed that an MC-based reconstruction enables large undersampling factors and also results in more accurate parameter maps compared with using CS. Experiments in 6 healthy volunteers used a reduction in scan time from 7:02 to 1:16 min, producing images without visible loss of detail in the parameter maps when using the MC-based reconstruction. Relaxation times from 6 healthy volunteers are in agreement with values obtained from fully sampled scans and values in literature, and parameter maps in a uveal melanoma patient show clear difference in relaxation times between tumor and healthy tissue. CONCLUSION:Cartesian-based MRF is feasible in the eye at 7T. High undersampling factors can be achieved by means of MC, significantly shortening scan time and increasing patient comfort, while also mitigating the risk of motion artifacts.

PurposeBoth dynamic magnetic resonance angiography (4D-MRA) and perfusion imaging can be acquired by using arterial spin labeling (ASL). While 4D-MRA highlights large vessel pathology, such as stenosis or collateral blood flow patterns, perfusion imaging provides information on the microvascular status. Therefore, a complete picture of the cerebral hemodynamic condition could be obtained by combining the two techniques. Here, we propose a novel technique for simultaneous acquisition of 4D-MRA and perfusion imaging using time-encoded pseudo-continuous arterial spin labeling. MethodsThe time-encoded pseudo-continuous arterial spin labeling module consisted of a first subbolus that was optimized for perfusion imaging by using a labeling duration of 1800 ms, whereas the other six subboli of 130 ms were used for encoding the passage of the labeled spins through the arterial system for 4D-MRA acquisition. After the entire labeling module, a multishot 3D turbo-field echo-planar-imaging readout was executed for the 4D-MRA acquisition, immediately followed by a single-shot, multislice echo-planar-imaging readout for perfusion imaging. The optimal excitation flip angle for the 3D turbo-field echo-planar-imaging readout was investigated by evaluating the image quality of the 4D-MRA and perfusion images as well as the accuracy of the estimated cerebral blood flow values. ResultsWhen using 36 excitation radiofrequency pulses with flip angles of 5 or 7.5 degrees, the saturation effects of the 3D turbo-field echo-planar-imaging readout on the perfusion images were relatively moderate and after correction, there were no statistically significant differences between the obtained cerebral blood flow values and those from traditional time-encoded pseudo-continuous arterial spin labeling. ConclusionsThis study demonstrated that simultaneous acquisition of 4D-MRA and perfusion images can be achieved by using time-encoded pseudo-continuous arterial spin labeling. Magn Reson Med 79:2676-2684, 2018. (c) 2017 International Society for Magnetic Resonance in Medicine.

Purpose: The aim of this study was to investigate a technique for improving the performance of Magnetic Resonance Fingerprinting (MRF) in repetitive sampling schemes, in particular for 3D MRF acquisition, by shortening relaxation intervals between MRF pulse train repetitions.Material and Methods: A calculation method for MRF dictionaries adapted to short relaxation intervals and non-relaxed initial spin states is presented, based on the concept of stationary fingerprints. The method is applicable to many different k-space sampling schemes in 2D and 3D. For accuracy analysis, T-1 and T-2 values of a phantom are determined by single-slice Cartesian MRF for different relaxation intervals and are compared with quantitative reference measurements. The relevance of slice profile effects is also investigated in this case. To further illustrate the capabilities of the method, an application to in-vivo spiral 3D MRF measurements is demonstrated.Results: The proposed computation method enables accurate parameter estimation even for the shortest relaxation intervals, as investigated for different sampling patterns in 2D and 3D. In 2D Cartesian measurements, we achieved a scan acceleration of more than a factor of two, while maintaining acceptable accuracy: The largest T-1 values of a sample set deviated from their reference values by 0.3% (longest relaxation interval) and 2.4% (shortest relaxation interval). The largest T-2 values showed systematic deviations of up to 10% for all relaxation intervals, which is discussed. The influence of slice profile effects for multislice acquisition is shown to become increasingly relevant for short relaxation intervals. In 3D spiral measurements, a scan time reduction of 36% was achieved, maintaining the quality of in-vivo T1 and T2 maps.Conclusions: Reducing the relaxation interval between MRF sequence repetitions using stationary fingerprint dictionaries is a feasible method to improve the scan efficiency of MRF sequences. The method enables fast implementations of 3D spatially resolved MRF. (C) 2017 Elsevier Inc. All rights reserved.

PurposeTo propose a simultaneous acquisition sequence for improved hepatic pharmacokinetics quantification accuracy (SAHA) method for liver dynamic contrast‐enhanced MRI.MethodsThe proposed SAHA simultaneously acquired high temporal‐resolution 2D images for vascular input function extraction using Cartesian sampling and 3D large‐coverage high spatial‐resolution liver dynamic contrast‐enhanced images using golden angle stack‐of‐stars acquisition in an interleaved way. Simulations were conducted to investigate the accuracy of SAHA in pharmacokinetic analysis. A healthy volunteer and three patients with cirrhosis or hepatocellular carcinoma were included in the study to investigate the feasibility of SAHA in vivo.ResultsSimulation studies showed that SAHA can provide closer results to the true values and lower root mean square error of estimated pharmacokinetic parameters in all of the tested scenarios. The in vivo scans of subjects provided fair image quality of both 2D images for arterial input function and portal venous input function and 3D whole liver images. The in vivo fitting results showed that the perfusion parameters of healthy liver were significantly different from those of cirrhotic liver and HCC.ConclusionsThe proposed SAHA can provide improved accuracy in pharmacokinetic modeling and is feasible in human liver dynamic contrast‐enhanced MRI, suggesting that SAHA is a potential tool for liver dynamic contrast‐enhanced MRI. Magn Reson Med 79:2629–2641, 2018. © 2017 International Society for Magnetic Resonance in Medicine.