Neuroimaging of Parkinson's disease by quantitative susceptibility mapping.

Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group.

This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.

Hybrid data fidelity term approach for quantitative susceptibility mapping.

PURPOSE: Susceptibility maps are usually derived from local magnetic field estimations by minimizing a functional composed of a data consistency term and a regularization term. The data-consistency term measures the difference between the desired solution and the measured data using typically the L2-norm. It has been proposed to replace this L2-norm with the L1-norm, due to its robustness to outliers and reduction of streaking artifacts arising from highly noisy or strongly perturbed regions. However, in regions with high SNR, the L1-norm yields a suboptimal denoising performance. In this work, we present a hybrid data fidelity approach that uses the L1-norm and subsequently the L2-norm to exploit the strengths of both norms. METHODS: We developed a hybrid data fidelity term approach for QSM (HD-QSM) based on linear susceptibility inversion methods, with total variation regularization. Each functional is solved with ADMM. The HD-QSM approach is a two-stage method that first finds a fast solution of the L1-norm functional and then uses this solution to initialize the L2-norm functional. In both norms we included spatially variable weights that improve the quality of the reconstructions. RESULTS: The HD-QSM approach produced good quantitative reconstructions in terms of structural definition, noise reduction, and avoiding streaking artifacts comparable with nonlinear methods, but with higher computational efficiency. Reconstructions performed with this method achieved first place at the lowest RMS error category in stage 1 of the 2019 QSM Reconstruction Challenge. CONCLUSIONS: The proposed method allows robust and accurate QSM reconstructions, obtaining superior performance to state-of-the-art methods.

Streaking artifact suppression of quantitative susceptibility mapping reconstructions via L1-norm data fidelity optimization (L1-QSM).

PURPOSE: The presence of dipole-inconsistent data due to substantial noise or artifacts causes streaking artifacts in quantitative susceptibility mapping (QSM) reconstructions. Often used Bayesian approaches rely on regularizers, which in turn yield reduced sharpness. To overcome this problem, we present a novel L1-norm data fidelity approach that is robust with respect to outliers, and therefore prevents streaking artifacts. METHODS: QSM functionals are solved with linear and nonlinear L1-norm data fidelity terms using functional augmentation, and are compared with equivalent L2-norm methods. Algorithms were tested on synthetic data, with phase inconsistencies added to mimic lesions, QSM Challenge 2.0 data, and in vivo brain images with hemorrhages. RESULTS: The nonlinear L1-norm-based approach achieved the best overall error metric scores and better streaking artifact suppression. Notably, L1-norm methods could reconstruct QSM images without using a brain mask, with similar regularization weights for different data fidelity weighting or masking setups. CONCLUSION: The proposed L1-approach provides a robust method to prevent streaking artifacts generated by dipole-inconsistent data, renders brain mask calculation unessential, and opens novel challenging clinical applications such asassessing brain hemorrhages and cortical layers.

Adaptive slice-specific z-shimming for 2D spoiled gradient-echo sequences.

PURPOSE: To reduce the misbalance between compensation gradients and macroscopic field gradients, we introduce an adaptive slice-specific z-shimming approach for 2D spoiled multi-echo gradient-echoe sequences in combination with modeling of the signal decay. METHODS: Macroscopic field gradients were estimated for each slice from a fast prescan (15 seconds) and then used to calculate slice-specific compensation moments along the echo train. The coverage of the compensated field gradients was increased by applying three positive and three negative moments. With a forward model, which considered the effect of the slice profile, the z-shim moment, and the field gradient, R2∗ maps were estimated. The method was evaluated in phantom and in vivo measurements at 3 T and compared with a spoiled multi-echo gradient-echo and a global z-shimming approach without slice-specific compensation. RESULTS: The proposed method yielded higher SNR in R2∗ maps due to a broader range of compensated macroscopic field gradients compared with global z-shimming. In global white matter, the mean interquartile range, proxy for SNR, could be decreased to 3.06 s-1 with the proposed approach, compared with 3.37 s-1 for global z-shimming and 3.52 s-1 for uncompensated multi-echo gradient-echo. CONCLUSION: Adaptive slice-specific compensation gradients between echoes substantially improved the SNR of R2∗ maps, and the signal could also be rephased in anatomical areas, where it has already been completely dephased.

QSM reconstruction challenge 2.0: Design and report of results.

PURPOSE: The aim of the second quantitative susceptibility mapping (QSM) reconstruction challenge (Oct 2019, Seoul, Korea) was to test the accuracy of QSM dipole inversion algorithms in simulated brain data. METHODS: A two-stage design was chosen for this challenge. The participants were provided with datasets of multi-echo gradient echo images synthesized from two realistic in silico head phantoms using an MR simulator. At the first stage, participants optimized QSM reconstructions without ground truth data available to mimic the clinical setting. At the second stage, ground truth data were provided for parameter optimization. Submissions were evaluated using eight numerical metrics and visual ratings. RESULTS: A total of 98 reconstructions were submitted for stage 1 and 47 submissions for stage 2. Iterative methods had the best quantitative metric scores, followed by deep learning and direct inversion methods. Priors derived from magnitude data improved the metric scores. Algorithms based on iterative approaches and total variation (and its derivatives) produced the best overall results. The reported results and analysis pipelines have been made public to allow researchers to compare new methods to the current state of the art. CONCLUSION: The synthetic data provide a consistent framework to test the accuracy and robustness of QSM algorithms in the presence of noise, calcifications and minor voxel dephasing effects. Total Variation-based algorithms produced the best results among all metrics. Future QSM challenges should assess whether this good performance with synthetic datasets translates to more realistic scenarios, where background fields and dipole-incompatible phase contributions are included.

QSM reconstruction challenge 2.0: A realistic in silico head phantom for MRI data simulation and evaluation of susceptibility mapping procedures.

PURPOSE: To create a realistic in silico head phantom for the second QSM reconstruction challenge and for future evaluations of processing algorithms for QSM. METHODS: We created a digital whole-head tissue property phantom by segmenting and postprocessing high-resolution (0.64 mm isotropic), multiparametric MRI data acquired at 7 T from a healthy volunteer. We simulated the steady-state magnetization at 7 T using a Bloch simulator and mimicked a Cartesian sampling scheme through Fourier-based processing. Computer code for generating the phantom and performing the MR simulation was designed to facilitate flexible modifications of the phantom in the future, such as the inclusion of pathologies as well as the simulation of a wide range of acquisition protocols. Specifically, the following parameters and effects were implemented: TR and TE, voxel size, background fields, and RF phase biases. Diffusion-weighted imaging phantom data are provided, allowing future investigations of tissue-microstructure effects in phase and QSM algorithms. RESULTS: The brain part of the phantom featured realistic morphology with spatial variations in relaxation and susceptibility values similar to the in vivo setting. We demonstrated some of the phantom's properties, including the possibility of generating phase data with nonlinear evolution over TE due to partial-volume effects or complex distributions of frequency shifts within the voxel. CONCLUSION: The presented phantom and computer programs are publicly available and may serve as a ground truth in future assessments of the faithfulness of quantitative susceptibility reconstruction algorithms.

Cross-sectional and Longitudinal Assessment of Brain Iron Level in Alzheimer Disease Using 3-T MRI.

Background Deep gray matter structures in patients with Alzheimer disease (AD) contain higher brain iron concentrations. However, few studies have included neocortical areas, which are challenging to assess with MRI. Purpose To investigate baseline and change in brain iron levels using MRI at 3 T with R2* relaxation rate mapping in individuals with AD compared with healthy control (HC) participants. Materials and Methods In this prospective study, participants with AD recruited between 2010 and 2016 and age-matched HC participants selected from 2010 to 2014 were evaluated. Of 100 participants with AD, 56 underwent subsequent neuropsychological testing and brain MRI at a mean follow-up of 17 months. All participants underwent 3-T MRI, including R2* mapping corrected for macroscopic B0 field inhomogeneities. Anatomic structures were segmented, and median R2* values were calculated in the neocortex and cortical lobes, basal ganglia (BG), hippocampi, and thalami. Multivariable linear regression analysis was applied to study the difference in R2* levels between groups and the association between longitudinal changes in R2* values and cognition in the AD group. Results A total of 100 participants with AD (mean age, 73 years ± 9 [standard deviation]; 58 women) and 100 age-matched HC participants (mean age, 73 years ± 9; 60 women) were evaluated. Median R2* levels were higher in the AD group than in the HC group in the BG (HC, 29.0 sec-1; AD, 30.2 sec-1; P = .01) and total neocortex (HC, 17.0 sec-1; AD, 17.4 sec-1; P < .001) and regionally in the occipital (HC, 19.6 sec-1; AD, 20.2 sec-1; P = .007) and temporal (HC, 16.4 sec-1; AD, 18.1 sec-1; P < .001) lobes. R2* values in the temporal lobe were associated with longitudinal changes in Consortium to Establish a Registry for Alzheimer's Disease total score (ß = -3.23 score/sec-1, P = .003) in participants with AD independent of longitudinal changes in brain volume. Conclusion Iron concentration in the deep gray matter and neocortical regions was higher in patients with Alzheimer disease than in healthy control participants. Change in iron levels over time in the temporal lobe was associated with cognitive decline in individuals with Alzheimer disease. © RSNA, 2020 Online supplemental material is available for this article.

Assessment and correction of macroscopic field variations in 2D spoiled gradient-echo sequences.

PURPOSE: To model and correct the dephasing effects in the gradient-echo signal for arbitrary RF excitation pulses with large flip angles in the presence of macroscopic field variations. METHODS: The dephasing of the spoiled 2D gradient-echo signal was modeled using a numerical solution of the Bloch equations to calculate the magnitude and phase of the transverse magnetization across the slice profile. Additionally, regional variations of the transmit RF field and slice profile scaling due to macroscopic field gradients were included. Simulations, phantom, and in vivo measurements at 3 T were conducted for R2∗ and myelin water fraction (MWF) mapping. RESULTS: The influence of macroscopic field gradients on R2∗ and myelin water fraction estimation can be substantially reduced by applying the proposed model. Moreover, it was shown that the dephasing over time for flip angles of 60° or greater also depends on the polarity of the slice-selection gradient because of phase variation along the slice profile. CONCLUSION: Substantial improvements in R2∗ accuracy and myelin water fraction mapping coverage can be achieved using the proposed model if higher flip angles are required. In this context, we demonstrated that the phase along the slice profile and the polarity of the slice-selection gradient are essential for proper modeling of the gradient-echo signal in the presence of macroscopic field variations.

The 2016 QSM Challenge: Lessons learned and considerations for a future challenge design.

PURPOSE: The 4th International Workshop on MRI Phase Contrast and QSM (2016, Graz, Austria) hosted the first QSM Challenge. A single-orientation gradient recalled echo acquisition was provided, along with COSMOS and the χ33 STI component as ground truths. The submitted solutions differed more than expected depending on the error metric used for optimization and were generally over-regularized. This raised (unanswered) questions about the ground truths and the metrics utilized. METHODS: We investigated the influence of background field remnants by applying additional filters. We also estimated the anisotropic contributions from the STI tensor to the apparent susceptibility to amend the χ33 ground truth and to investigate the impact on the reconstructions. Lastly, we used forward simulations from the COSMOS reconstruction to investigate the impact noise had on the metric scores. RESULTS: Reconstructions compared against the amended STI ground truth returned lower errors. We show that the background field remnants had a minor impact in the errors. In the absence of inconsistencies, all metrics converged to the same regularization weights, whereas structural similarity index metric was more insensitive to such inconsistencies. CONCLUSION: There was a mismatch between the provided data and the ground truths due to the presence of unaccounted anisotropic susceptibility contributions and noise. Given the lack of reliable ground truths when using in vivo acquisitions, simulations are suggested for future QSM Challenges.

DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping.

Quantitative susceptibility mapping (QSM) is based on magnetic resonance imaging (MRI) phase measurements and has gained broad interest because it yields relevant information on biological tissue properties, predominantly myelin, iron and calcium in vivo. Thereby, QSM can also reveal pathological changes of these key components in widespread diseases such as Parkinson's disease, Multiple Sclerosis, or hepatic iron overload. While the ill-posed field-to-source-inversion problem underlying QSM is conventionally assessed by the means of regularization techniques, we trained a fully convolutional deep neural network - DeepQSM - to directly invert the magnetic dipole kernel convolution. DeepQSM learned the physical forward problem using purely synthetic data and is capable of solving the ill-posed field-to-source inversion on in vivo MRI phase data. The magnetic susceptibility maps reconstructed by DeepQSM enable identification of deep brain substructures and provide information on their respective magnetic tissue properties. In summary, DeepQSM can invert the magnetic dipole kernel convolution and delivers robust solutions to this ill-posed problem.

Weak-harmonic regularization for quantitative susceptibility mapping.

PURPOSE: Background-field removal is a crucial preprocessing step for quantitative susceptibility mapping (QSM). Remnants from this step often contaminate the estimated local field, which in turn leads to erroneous tissue-susceptibility reconstructions. The present work aimed to mitigate this undesirable behavior with the development of a new approach that simultaneously decouples background contributions and local susceptibility sources on QSM inversion. METHODS: Input phase data for QSM can be seen as a composite scalar field of local effects and residual background components. We developed a new weak-harmonic regularizer to constrain the latter and to separate the 2 components. The resulting optimization problem was solved with the alternating directions of multipliers method framework to achieve fast convergence. In addition, for convenience, a new alternating directions of multipliers method-based preconditioned nonlinear projection onto dipole fields solver was developed to enable initializations with wrapped-phase distributions. Weak-harmonic QSM, with and without nonlinear projection onto dipole fields preconditioning, was compared with the original (alternating directions of multipliers method-based) total variation QSM algorithm in phantom and in vivo experiments. RESULTS: Weak-harmonic QSM returned improved reconstructions regardless of the method used for background-field removal, although the proposed nonlinear projection onto dipole fields method often obtained better results. Streaking and shadowing artifacts were substantially suppressed, and residual background components were effectively removed. CONCLUSION: Weak-harmonic QSM with field preconditioning is a robust dipole inversion technique and has the potential to be extended as a single-step formulation for initialization with uncombined multi-echo data.

Nigral iron deposition in common tremor disorders.

OBJECTIVE: We investigated R2* relaxation rates as a marker of iron content in the substantia nigra in patients with common tremor disorders and explored their diagnostic properties. METHODS: Mean nigral R2* rates were measured in 40 patients with tremor-dominant Parkinson's disease (PD), 15 with tremor in dystonia, 25 with essential tremor, and 25 healthy controls. RESULTS: Tremor-dominant PD patients had significantly higher nigral R2* values (34.1 ± 5.7) than those with tremor in dystonia (30.0 ± 3.9), essential tremor (30.6 ± 4.8), and controls (30.0 ± 2.8). An R2* threshold of 31.15 separated tremor-dominant PD from controls with a sensitivity and specificity of 67.5% and 72%. The sensitivity and specificity for discrimination between PD and non-PD tremor patients was 67.5% and 60%. CONCLUSION: Iron content in the substantia nigra is significantly higher in tremor-dominant PD than in tremor in dystonia, essential tremor, and controls. Because of the considerable overlap, nigral R2* cannot be suggested as a useful diagnostic tool. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

The impact of vascular risk factors on brain volume and lesion load in patients with early multiple sclerosis.

BACKGROUND: Vascular risk factors (VRF) in multiple sclerosis (MS) patients have been associated with lower brain volumes. It is currently unknown if this association already exists in early MS and how it develops over time. METHODS: We identified 82 patients with clinically isolated syndrome (CIS) ( n = 61) or with early relapsing-remitting MS ( n = 21) and assessed their VRF including arterial hypertension, hyperlipidaemia, diabetes mellitus and smoking. We analysed T2-lesion load, normalized brain volume (NBV), cortical grey (cGMV) and white matter volumes (WMV), thalamic and basal ganglia volumes at baseline and follow-up magnetic resonance imaging (MRI) and assessed the percentage of brain volume change (PBVC) using SIENA. RESULTS: Patient mean age was 32.4 (±8.7) years and 54 (65%) were women. Median follow-up period was 42 (29-54) months. In total, 26 patients (31.7%) had one or more VRF (VRF+). At baseline, VRF+ patients had a lower NBV (1530.9 cm3 vs 1591.2 cm3, p = 0.001), a lower cGMV (628.5 cm3 vs 668.6 cm3, p = 0.002) and WMV (752.2 cm3 vs 783.9 cm3, p = 0.009) than VRF-negative patients. Similar results were obtained at follow-up. PBVC was comparable between patients with and without VRF. CONCLUSION: VRF are associated with lower brain volume already in early MS but do not lead to increased brain volume loss during 3.5 years of follow-up.

Assessment of ferritin content in multiple sclerosis brains using temperature-induced R*2 changes.

PURPOSE: Current MRI techniques cannot reliably assess iron content in white matter due to the confounding diamagnetic effect of myelin. The purpose of this study was to validate with histology a novel iron mapping technique that uses the temperature dependency of the paramagnetic susceptibility in multiple sclerosis (MS) brains, where white matter has been reported to show significant variations in iron content. METHODS: We investigated post mortem brain tissue from three MS patients and one control subject. Temperature-dependent R2* relaxometry was performed between 4°C and 37°C. The resulting temperature coefficient ( TcR2*) maps were compared with immunohistochemical stains for ferritin light chain. RESULTS: Good agreement between TcR2* maps and ferritin staining was found by way of visual comparison and quantitative analysis. The highest iron concentrations were detected at the edge of MS lesions and in the basal ganglia. For all regions, except the subcortical U-fibers, there was a significant negative correlation between the TcR2* values and the ferritin count. CONCLUSION: This study provides further evidence that TcR2* may be a reliable measure of white matter iron content due to the elimination of myelin-induced susceptibility changes and is well suited for further research into neurological diseases with distortions of the iron homeostasis. Magn Reson Med 79:1609-1615, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Effects of concentration and vendor specific composition of formalin on postmortem MRI of the human brain.

PURPOSE: Formalin fixation prevents tissue autolysis by crosslinking proteins and changes tissue microstructure and MRI signal characteristics. Previous studies showed high variations in MR relaxation time constants of formalin fixed brain tissue, which has been attributed to the use of different formalin concentrations. Our investigations confirmed the influence of formalin concentration on relaxation times and unexpectedly revealed an influence of vendor specific formalin composition, which has not been investigated so far. METHODS: We systematically analyzed relaxation times of human brain tissue fixed with 4% and 10% formalin compared with unfixed condition at 3 Tesla MRI. Furthermore, we assessed relaxation times of nine formalin solutions from different vendors and performed comparisons of their magnetic susceptibility by SQUID (superconducting quantum interference device) magnetometry. RESULTS: Tissue relaxation times decreased approximately twice as fast using 10% than in 4% formalin fixation. The vendor specific composition of the formalin solutions and concentration dependent paramagnetic effects showed a substantial contribution to differences in relaxation times of formalin. CONCLUSION: Our study demonstrates that differences of the formalin composition have substantial effects on MRI signal characteristics after fixation, which can explain the divergence of reported relaxation times beyond the effect of differences in formalin concentration. Magn Reson Med 79:1111-1115, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge.

PURPOSE: The aim of the 2016 quantitative susceptibility mapping (QSM) reconstruction challenge was to test the ability of various QSM algorithms to recover the underlying susceptibility from phase data faithfully. METHODS: Gradient-echo images of a healthy volunteer acquired at 3T in a single orientation with 1.06 mm isotropic resolution. A reference susceptibility map was provided, which was computed using the susceptibility tensor imaging algorithm on data acquired at 12 head orientations. Susceptibility maps calculated from the single orientation data were compared against the reference susceptibility map. Deviations were quantified using the following metrics: root mean squared error (RMSE), structure similarity index (SSIM), high-frequency error norm (HFEN), and the error in selected white and gray matter regions. RESULTS: Twenty-seven submissions were evaluated. Most of the best scoring approaches estimated the spatial frequency content in the ill-conditioned domain of the dipole kernel using compressed sensing strategies. The top 10 maps in each category had similar error metrics but substantially different visual appearance. CONCLUSION: Because QSM algorithms were optimized to minimize error metrics, the resulting susceptibility maps suffered from over-smoothing and conspicuity loss in fine features such as vessels. As such, the challenge highlighted the need for better numerical image quality criteria. Magn Reson Med 79:1661-1673, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Iron quantification with susceptibility.

Iron is an essential trace element involved in a variety of biological mechanisms in the human body. Disturbances of iron homeostasis have been observed in several inflammatory and degenerative diseases, which have raised strong interest in non-invasive iron mapping techniques. Numerous MRI techniques have been proposed so far, mostly based on the field changes induced by the magnetic properties of iron. Each of these approaches has a specific sensitivity for iron and its microstructural environment. Quantitative susceptibility mapping is the latest development and provides a direct measure of bulk susceptibility. However, field changes induced by iron are not always directly related to the concentration of iron, but rather reflect the structure of iron compounds and its cellular distribution. This review provides an overview of the most relevant iron compounds in the human body, their magnetic properties and their cellular distribution. In addition, MRI methods based on direct or indirect susceptibility changes are presented and discussed with respect to technical aspects and clinical applicability. Copyright © 2016 John Wiley & Sons, Ltd.

Accelerated mapping of magnetic susceptibility using 3D planes-on-a-paddlewheel (POP) EPI at ultra-high field strength.

With the advent of ultra-high field MRI scanners in clinical research, susceptibility based MRI has recently gained increasing interest because of its potential to assess subtle tissue changes underlying neurological pathologies/disorders. Conventional, but rather slow, three-dimensional (3D) spoiled gradient-echo (GRE) sequences are typically employed to assess the susceptibility of tissue. 3D echo-planar imaging (EPI) represents a fast alternative but generally comes with echo-time restrictions, geometrical distortions and signal dropouts that can become severe at ultra-high fields. In this work we assess quantitative susceptibility mapping (QSM) at 7 T using non-Cartesian 3D EPI with a planes-on-a-paddlewheel (POP) trajectory, which is created by rotating a standard EPI readout train around its own phase encoding axis. We show that the threefold accelerated non-Cartesian 3D POP EPI sequence enables very fast, whole brain susceptibility mapping at an isotropic resolution of 1 mm and that the high image quality has sufficient signal-to-noise ratio in the phase data for reliable QSM processing. The susceptibility maps obtained were comparable with regard to QSM values and geometric distortions to those calculated from a conventional 4 min 3D GRE scan using the same QSM processing pipeline. Copyright © 2016 John Wiley & Sons, Ltd.