Purpose Quantitative susceptibility mapping (QSM) has found increasing clinical applications. However, to reduce scan time, clinical acquisitions often use reduced resolution and coverage, particularly in the through‐slice dimension. The effect of these factors on QSM has begun to be assessed using only balloon phantoms and downsampled brain images. Here, we investigate the effects (and their sources) of low resolution or coverage on QSM using both simulated and acquired images. Methods Brain images were acquired at 1 mm isotropic resolution and full brain coverage, and low resolution (up to 6 mm slice thickness) or coverage (down to 20 mm) in 5 healthy volunteers. Images at reduced resolution or coverage were also simulated in these volunteers and in a new, anthropomorphic, numerical phantom. Mean susceptibilities in 5 brain regions, including white matter, were investigated over varying resolution and coverage. Results The susceptibility map contrast decreased with increasing slice thickness and spacing, and with decreasing coverage below ~40 mm for 2 different QSM pipelines. Our simulations showed that calculated susceptibility values were erroneous at low resolution or very low coverage, because of insufficient sampling and overattenuation of the susceptibility‐induced field perturbations. Susceptibility maps calculated from simulated and acquired images showed similar behavior. Conclusions Both low resolution and low coverage lead to loss of contrast and errors in susceptibility maps. The widespread clinical practice of using low resolution and coverage does not provide accurate susceptibility maps. Simulations in images of healthy volunteers and in a new, anthropomorphic numerical phantom were able to accurately model low‐resolution and low‐coverage acquisitions.

Purpose Quantitative Susceptibility Mapping (QSM) is an emerging technique sensitive to disease‐related changes including oxygenation. It is extensively used in brain studies and has increasing clinical applications outside the brain. Here we present the first MRI acquisition protocol and QSM pipeline optimized for the head‐and‐neck region together with a repeatability analysis performed in healthy volunteers. Methods We investigated both the intrasession and the intersession repeatability of the optimized method in 10 subjects. We also implemented two, Tikhonov‐regularisation‐based susceptibility calculation techniques that were found to have higher contrast‐to‐noise than existing methods in the head‐and‐neck region. Repeatability was evaluated by calculating the distributions of susceptibility differences between repeated scans and the corresponding minimum detectable effect sizes (MDEs). Results Deep brain regions had higher QSM repeatability than neck regions. As expected, intrasession repeatability was generally better than intersession repeatability. Susceptibility maps calculated using projection onto dipole fields for background field removal were more repeatable than using the Laplacian boundary value method in the head‐and‐neck region. Small (short‐axis diameter <5 mm) lymph nodes had the lowest repeatability (MDE = 0.27 ppm) as imperfect segmentation included some of the surrounding paramagnetic fatty fascia, highlighting the importance of accurate region delineation. MDEs in the larger lymph nodes (0.16 ppm), submandibular glands (0.10 ppm), and especially the parotid glands (0.06 ppm) were much lower, comparable to those of the brain regions. Conclusions The high repeatability of the acquisition and pipeline optimized for QSM will facilitate clinical studies in the head‐and‐neck region.

Purpose Multi‐echo gradient‐recalled echo acquisitions for QSM enable optimizing the SNR for several tissue types through multi‐echo (TE) combination or investigating temporal variations in the susceptibility (potentially reflecting tissue microstructure) by calculating one QSM image at each TE (TE‐dependent QSM). In contrast with multi‐echo QSM, applying Laplacian‐based methods (LBMs) for phase unwrapping and background field removal to single TEs could introduce nonlinear temporal variations (independent of tissue microstructure) into the measured susceptibility. Here, we aimed to compare the effect of LBMs on the QSM susceptibilities in TE‐dependent versus multi‐echo QSM. Methods TE–dependent recalled echo data simulated in a numerical head phantom and gradient‐recalled echo images acquired at 3 T in 10 healthy volunteers. Several QSM pipelines were tested, including four distinct LBMs: sophisticated harmonic artifact reduction for phase data (SHARP), variable‐radius sophisticated harmonic artifact reduction for phase data (V‐SHARP), Laplacian boundary value background field removal (LBV), and one‐step total generalized variation (TGV). Results from distinct pipelines were compared using visual inspection, summary statistics of susceptibility in deep gray matter/white matter/venous regions of interest, and, in the healthy volunteers, regional susceptibility bias analysis and nonparametric tests. Results Multi‐echo versus TE‐dependent QSM had higher regional accuracy, especially in high‐susceptibility regions and at shorter TEs. Everywhere except in the veins, a processing pipeline incorporating TGV provided the most temporally stable TE‐dependent QSM results with an accuracy similar to multi‐echo QSM. Conclusions For TE‐dependent QSM, carefully choosing LBMs can minimize the introduction of LBM‐related nonlinear temporal susceptibility variations.

Recent Magnetic Resonance Imaging (MRI) techniques, such as Quantitative magnetic Susceptibility Mapping (QSM), employ the signal phase to reveal disease-related changes in tissue composition including iron or calcium content. The MRI phase is also routinely used in functional and diffusion MRI for distortion correction. However, phase images are wrapped into a range of 2π radians. PRELUDE is the gold standard method for robust, spatial, 3-dimensional, MRI phase unwrapping. Unfortunately, PRELUDE's computation time can reach 15 minutes for a severely wrapped brain image and nearly 10 hours to unwrap a full head-and-neck image on a standard PC. Here we develop a Speedy rEgion-Growing algorithm for Unwrapping Estimated phase (SEGUE) based on similar principles to PRE-LUDE, implemented with additional methods for acceleration. We compared PRELUDE and SEGUE in numerical phantoms, and using in-vivo images of the brain, head-and-neck, and pelvis acquired in 4-5 healthy volunteers and at 4-6 echo times. To overcome chemical-shift-induced errors within the head-and-neck and pelvic images, we also investigated applying both techniques within fat and water masks separately. SEGUE provided almost identical unwrapped phase maps to the gold standard PRELUDE. SEGUE was (1.5 to 70 times) faster than PRELUDE, especially in severely wrapped images at later echoes as well as in the headand-neck and pelvic images. Applying these techniques within fat and water masks separately successfully removed chemical-shiftinduced errors. SEGUE's MATLAB implementation is available for download. SEGUE is a general unwrapping algorithm not specific to MRI and could, therefore, be used in images acquired with other modalities.

Purpose To evaluate the relationship between bone mineral density (BMD) and magnetic susceptibility, and between proton density fat fraction and susceptibility, in inflamed trabecular bone. Methods Two different phantoms modeling the fat fraction (FF) and BMD values of healthy bone marrow and disease states were scanned using a multiecho gradient echo acquisition at 3T. After correction for fat‐water chemical shift, susceptibility mapping was performed, and susceptibility measurements were compared with BMD and FF values using linear regression. Patients with spondyloarthritis were scanned using the same protocol, and susceptibility values were calculated in areas of inflamed bone (edema) and fat metaplasia, both before and after accounting for the contribution of fat to the total susceptibility. Results Susceptibility values in the phantoms were accurately described by a 2D linear function, with a negative correlation between BMD and susceptibility and a positive correlation between FF and susceptibility (adjusted R 2 = 0.77; P = 3·10 −5 ). In patients, significant differences in susceptibility were observed between fat metaplasia and normal marrow, but these differences were eliminated by removing the fat contribution to the total susceptibility. Conclusions BMD and proton density fat fraction both influence the total susceptibility of bone marrow and failure to account for the fat contribution could lead to errors in BMD quantification. We propose a method for removing the fat contribution from the total susceptibility, based on the observed linear relationship between susceptibility and FF. In inflamed bone, the overall increase in susceptibility in areas of fat metaplasia is at least partly due to increased fat content.

The low temperature microwave absorption anomaly reported by Corzilius et al. [Phys. Rev. B 75, 235416 (2007)] in singlewall carbon nanotubes (SWCNTs) is revisited. It was originally reported that the microwave absorption of CVD grown SWCNTs shows an unexpected increase below $20 K (using flow cryostats) which depends on the microwave power. The original observation was made using the microwave cavity perturbation method while sweeping the microwave frequency. We reproduced this effect on arc-discharge based SWCNTs, using static cryogenic conditions with cooled microwave cavities, and employing a stable frequency source locked to the cavity resonance. Our observation shows that the microwave absorption anomaly is robust against the tube type and the experimental conditions.

PurposeQuantitative susceptibility mapping (QSM) is increasingly used for clinical research where oblique image acquisition is commonplace but its effects on QSM accuracy are not well understood.Theory and MethodsThe QSM processing pipeline involves defining the unit magnetic dipole kernel, which requires knowledge of the direction of the main magnetic field with respect to the acquired image volume axes. The direction of is dependent upon the axis and angle of rotation in oblique acquisition. Using both a numerical brain phantom and in-vivo acquisitions, we analysed the effects of oblique acquisition on magnetic susceptibility maps. We compared three tilt correction schemes at each step in the QSM pipeline: phase unwrapping, background field removal and susceptibility calculation, using the root-mean-squared error and QSM-tuned structural similarity index (XSIM).ResultsRotation of wrapped phase images gave severe artefacts. Background field removal with projection onto dipole fields gave the most accurate susceptibilities when the field map was first rotated into alignment with . LBV and VSHARP background field removal methods gave accurate results without tilt correction. For susceptibility calculation, thresholded k-space division, iterative Tikhonov regularisation and weighted linear total variation regularisation all performed most accurately when local field maps were rotated into alignment with before susceptibility calculation.ConclusionFor accurate QSM, oblique acquisition must be taken into account. Rotation of images into alignment with should be carried out after phase unwrapping and before background field removal. We provide open-source tilt-correction code to incorporate easily into existing pipelines: https://github.com/o-snow/QSM_TiltCorrection.git.

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