Theory and application of static field inhomogeneity effects in gradient-echo imaging

Signatures of microstructure in gradient-echo and spin-echo signals

PURPOSE

To determine whether the spatial scale and magnetic susceptibility of microstructure can be evaluated robustly from the decay of gradient-echo and spin-echo signals.

THEORY AND METHODS

Gradient-echo and spin-echo images were acquired from suspensions of spherical polystyrene microbeads of 10, 20, and 40 μm nominal diameter. The sizes of the beads and their magnetic susceptibility relative to the medium were estimated from the signal decay curves, using a lookup table generated from Monte Carlo simulations and an analytic model based on the Gaussian phase approximation.

RESULTS

Fitting Monte Carlo predictions to spin-echo data yielded acceptable estimates of microstructural parameters for the 20 and 40 μm microbeads. Using gradient-echo data, the Monte Carlo lookup table provided satisfactory parameter estimates for the 20 μm beads but unstable results for the diameter of the largest beads. Neither spin-echo nor gradient-echo data allowed accurate parameter estimation for the smallest beads. The analytic model performed poorly over all bead sizes.

CONCLUSIONS

Microstructural sources of magnetic susceptibility produce distinctive non-exponential signatures in the decay of gradient-echo and spin-echo signals. However, inverting the problem to extract microstructural parameters from the signals is nontrivial and, in certain regimes, ill-conditioned. For microstructure with small characteristic length scales, parameter estimation is hampered by the difficulty of acquiring accurate data at very short echo times. For microstructure with large characteristic lengths, the gradient-echo signal approaches the static-dephasing regime, where it becomes insensitive to size. Applicability of the analytic model was further limited by failure of the Gaussian phase approximation for all but the smallest beads.

In Vivo Measurement of Rat Brain Water Content at 9.4 T MR Using Super-Resolution Reconstruction: Validation With Ex Vivo Experiments

BACKGROUND

Given that changes in brain water content are often correlated with disease, investigating water content non-invasively and in vivo could lead to a better understanding of the pathogenesis of several neurologic diseases.

PURPOSE

To adapt a super-resolution-based technique, previously developed for humans, to the rat brain and report in vivo high-resolution (HR) water content maps in comparison with ex vivo wet/dry methods.

STUDY TYPE

Prospective.

ANIMAL MODEL

Eight healthy male Wistar rats.

FIELD STRENGTH/SEQUENCE

9.4-T, multi-echo gradient-echo (mGRE) sequence.

ASSESSMENT

Using super-resolution reconstruction (SRR), a HR mGRE image (200 μm isotropic) was reconstructed from three low-resolution (LR) orthogonal whole-brain images in each animal, which was followed by water content mapping in vivo. The animals were subsequently sacrificed, the brains excised and divided into five regions (front left, front right, middle left, middle right, and cerebellum-brainstem regions), and the water content was measured ex vivo using wet/dry measurements as the reference standard. The water content values of the in vivo and ex vivo methods were then compared for the whole brain and also for the different regions separately.

STATISTICAL TESTS

Friedman's non-parametric test was used to test difference between the five regions, and Pearson's correlation coefficient was used for correlation between in vivo and ex vivo measurements. A P-value <0.05 was considered statistically significant.

RESULTS

Water content values derived from in vivo MR measurements showed strong correlations with water content measured ex vivo at a regional level (r = 0.902). Different brain regions showed significantly different water content values. Water content values were highest in the frontal brain, followed by the midbrain, and lowest in the cerebellum and brainstem regions.

DATA CONCLUSION

An in vivo technique to achieve HR isotropic water content maps in the rat brain using SRR was adopted in this study. The MRI-derived water content values obtained using the technique showed strong correlations with water content values obtained using ex vivo wet/dry methods.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 1.

Clinical significance of asymmetric hypointense signals in minimum intensity projections of brain magnetic resonance imaging in children with primary headache

PURPOSE

This study aimed to observe the changes of venous continuity using the susceptibility weighted imaging-minimum intensity projection (SWI-MinIP) images in children with primary headache.

METHODS

The headache types were classified following the International Headache Society's diagnostic criteria. Patients with secondary headaches were excluded. The presence of asymmetric vasculature in SWI-MinIP images was visually assessed. Moreover, the relationship between headache patterns and asymmetric hypointense signals was analyzed.

RESULTS

In this single-center, retrospective study from 2016 to 2020, among 251 cases of primary headache (male/female, 108/143; mean age, 11.4 ± 4.0 years), 137 (54.6%), 75 (29.9%), and 39 (15.5%) patients had migraine, tension-type headache, and other primary headaches, respectively. On SWI-MinIP images, 14 (5.6%) patients showed an asymmetric venous pattern. All patients with SWI-MinIP asymmetry were included in the migraine group, accounting for 10.2% of patients with migraine. Five (35.7%) and nine (64.3%) patients were included in the aura and non-aura groups, respectively, without a significant difference in the frequency of asymmetric hypointense signals between the two groups (p = 0.325). All 14 patients with asymmetric hypervascularity had brain MRI within 12 h of headache onset. Ten (71.4%) of the 14 patients showed consistency between the laterality of headache and the hemisphere of predominant vascularity in SWI-MinIP.

CONCLUSION

Patients with migraine had increased cerebral venous perfusion in the most involved region of the headache on the SWI-MinIP view on a 3.0 T scanner, which can be used as a qualitative indicator with low sensitivity and high specificity for the diagnosis of primary headache in the acute phase (< 12 h).

The Role of Calcium in Non-Invasively Imaging Breast Cancer: An Overview of Current and Modern Imaging Techniques

The landscape of breast cancer diagnostics has significantly evolved over the past decade. With these changes, it is possible to provide a comprehensive assessment of both benign and malignant breast calcifications. The biochemistry of breast cancer and calcifications are thoroughly examined to describe the potential to characterize better different calcium salts composed of calcium carbonate, calcium oxalate, or calcium hydroxyapatite and their associated prognostic implications. Conventional mammographic imaging techniques are compared to available ones, including breast tomosynthesis and contrast-enhanced mammography. Additional methods in computed tomography and magnetic resonance imaging are discussed. The concept of using magnetic resonance imaging particularly magnetic susceptibility to characterize the biochemical characteristics of calcifications is described. As we know magnetic resonance imaging is safe and there is no ionization radiation. Experimental findings through magnetic resonance susceptibility imaging techniques are discussed to illustrate the potential for integrating this technique to provide a quantitative assessment of magnetic susceptibility. Under the right magnetic resonance imaging conditions, a distinct phase variability was isolated amongst different types of calcium salts.

Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities

Quantitative susceptibility mapping (QSM) has gained broad interest in the field by extracting bulk tissue magnetic susceptibility, predominantly determined by myelin, iron and calcium from magnetic resonance imaging (MRI) phase measurements in vivo. Thereby, QSM can reveal pathological changes of these key components in a variety of diseases. QSM requires multiple processing steps such as phase unwrapping, background field removal and field-to-source inversion. Current state-of-the-art techniques utilize iterative optimization procedures to solve the inversion and background field correction, which are computationally expensive and require a careful choice of regularization parameters. With the recent success of deep learning using convolutional neural networks for solving ill-posed reconstruction problems, the QSM community also adapted these techniques and demonstrated that the QSM processing steps can be solved by efficient feed forward multiplications not requiring either iterative optimization or the choice of regularization parameters. Here, we review the current status of deep learning-based approaches for processing QSM, highlighting limitations and potential pitfalls, and discuss the future directions the field may take to exploit the latest advances in deep learning for QSM.

Improved magnetic resonance myelin water imaging using multi-channel denoising convolutional neural networks (MCDnCNN)

BACKGROUND

Myelin water imaging (MWI) is powerful and important for studying and diagnosing neurological and psychiatric diseases. In particular, myelin water fraction (MWF) is derived from MWI data for quantifying myelination. However, MWF estimation is typically sensitive to noise. Improving the accuracy of MWF estimation based on WMI data acquired using a magnetic resonance (MR) multiple gradient recalled echo (mGRE) imaging sequence is desired.

METHODS

The proposed method employs a recently introduced the multi-channel denoising convolutional neural networks (MCDnCNN). Five different MCDnCNN models, denoted as Delevel1, Delevel2, Delevel3, Delevel4 and DelevelMix corresponding to five noise levels (Level1, Level2, Level3, Level4 and LevelMix), were trained using the data of the first echo of the mGRE brain images acquired from 15 healthy human subjects. Using simulated noisy data that employed a hollow cylinder model, we first evaluated the improvement in estimating MWF based on data denoised by the five different MCDnCNNs, by comparing the MWF maps calculated from the denoised data with ground truth. Next, we again evaluated the improvement using real-world in vivo datasets of 11 human participants acquired using the mGRE sequence. The datasets were first denoised by five different MCDnCNNs (Delevel1, 2, 3, 4 and DelevelMix), and subsequently their MWF maps were calculated and compared with the MWF maps directly calculated from the raw mGRE images without being denoised.

RESULTS

Experiments using the simulation data denoised by the appropriate MCDnCNN models showed that the standard deviation (SD) of the absolute error (AE) of the derived MWF results was significantly reduced (maximal reduction =15.5%, Level3 simulated noisy data, orientation angle =0, all the five MCDnCNN models). In the test using in vivo data, estimating MWF based on data particularly denoised by the appropriate MCDnCNN models was found to be the best, compared to otherwise not using the appropriate models. The results demonstrated that the appropriate MCDnCNN models may permit high-quality MWF mapping, i.e., substantial reduction of random variation in estimating MWF-maps while preserving accuracy and structural details.

CONCLUSIONS

Appropriate MCDnCNN models as proposed may improve both the accuracy and precision in estimating MWF maps, thereby making it a more clinically feasible alternative.

Quantification and 3D localization of magnetically navigated superparamagnetic particles using MRI in phantom and swine chemoembolization models

OBJECTIVE

Superparamagnetic nanoparticles (SPIONs) can be combined with tumor chemoembolization agents to form magnetic drug-eluting beads (MDEBs), which are navigated magnetically in the MRI scanner through the vascular system. We aim to develop a method to accurately quantify and localize these particles and to validate the method in phantoms and swine models.

METHODS

MDEBs were made of Fe₃O₄ SPIONs. After injected known numbers of MDEBs, susceptibility artifacts in three-dimensional (3D) volumetric interpolated breath-hold examination (VIBE) sequences were acquired in glass and Polyvinyl alcohol (PVA) phantoms, and two living swine. Image processing of VIBE images provided the volume relationship between MDEBs and their artifact at different VIBE acquisitions and post-processing parameters. Simulated hepatic-artery embolization was performed in vivo with an MRI-conditional magnetic-injection system, using the volume relationship to locate and quantify MDEB distribution.

RESULTS

Individual MDEBs were spatially identified, and their artifacts quantified, showing no correlation with magnetic-field orientation or sequence bandwidth, but exhibiting a relationship with echo time and providing a linear volume relationship. Two MDEB aggregates were magnetically steered into desired liver regions while the other 19 had no steering, and 25 aggregates were injected into another swine without steering. The MDEBs were spatially identified and the volume relationship showed accuracy in assessing the number of the MDEBs, with small errors (8.8%).

CONCLUSION AND SIGNIFICANCE

MDEBs were able to be steered into desired body regions and then localized using 3D VIBE sequences. The resulting volume relationship was linear, robust, and allowed for quantitative analysis of the MDEB distribution.

Quantitative effects of off-resonance related distortion on brain mechanical property estimation with magnetic resonance elastography

Off-resonance related geometric distortion can impact quantitative MRI techniques, such as magnetic resonance elastography (MRE), and result in errors to these otherwise sensitive metrics of brain health. MRE is a phase contrast technique to determine the mechanical properties of tissue by imaging shear wave displacements and estimating tissue stiffness through inverse solution of Navier's equation. In this study, we systematically examined the quantitative effects of distortion and corresponding correction approaches on MRE measurements through a series of simulations, phantom models, and in vivo brain experiments. We studied two different k-space trajectories, echo-planar imaging and spiral, and we determined that readout time, off-resonance gradient strength, and the combination of readout direction and off-resonance gradient direction, impact the estimated mechanical properties. Images were also processed through traditional distortion correction pipelines, and we found that each of the correction mechanisms works well for reducing stiffness errors, but are limited in cases of very large distortion. The ability of MRE to detect subtle changes to neural tissue health relies on accurate, artifact-free imaging, and thus off-resonance related geometric distortion must be considered when designing sequences and protocols by limiting readout time and applying correction where appropriate.

Free-breathing contrast-enhanced upper abdominal MRI in children: comparison between Cartesian acquisition and stack-of-stars acquisition with two different fat-suppression techniques

BACKGROUND

Respiratory artifacts impair image quality of magnetic resonance imaging (MRI) in children who cannot hold breath during MRI examination.

PURPOSE

To compare the quality of free-breathing contrast-enhanced 3D T1-weighted (T1W) images of the upper abdomen in children using Cartesian acquisition (Cartesian eTHRIVE), stack-of-stars acquisition with spectral fat suppression (3D VANE eTHRIVE), and stack-of-stars acquisition with fat suppression using modified Dixon (3D VANE mDixon).

MATERIAL AND METHODS

Pediatric patients (aged <19 years) who underwent whole-body MRI with free-breathing contrast-enhanced T1W axial scans of upper abdomen using Cartesian eTHRIVE, 3D VANE eTHRIVE, and 3D VANE mDixon were enrolled. Image quality parameters were assessed including overall image quality, hepatic edge sharpness, hepatic vessel clarity, respiratory artifacts, radial artifacts, lesion conspicuity, and lesion edge sharpness using the Likert scale, where a lower score indicated poorer image quality. The coefficients of variation of signal intensity of liver and spleen were analyzed.

RESULTS

In 41 patients, 3D VANE eTHRIVE showed the highest scores for all image quality parameters (P ≤ 0.001). 3D VANE eTHRIVE also showed higher scores for respiratory (P ≤ 0.001) and radial artefacts than 3D VANE mDixon (P = 0.001). There were no significant differences in coefficients of variation of signal intensity of the liver and spleen between 3D VANE eTHRIVE and 3D VANE mDixon. Acquisition time was longer for 3D VANE eTHRIVE (81.26 ± 16 s) than for Cartesian eTHRIVE (7.87 ± 0.95 s) and 3D VANE mDixon (76.66 ± 12.4 s, P < 0.001).

CONCLUSION

The application of stack-of-stars acquisition to 3D T1W abdominal MRI resulted in better image quality than Cartesian acquisition in free-breathing children. In stack-of-stars acquisition, spectral fat suppression resulted in better image quality and fewer artifacts than mDixon.

Susceptibility-weighted Imaging: Technical Essentials and Clinical Neurologic Applications

Susceptibility-weighted imaging (SWI) evolved from simple two-dimensional T2*-weighted sequences to three-dimensional sequences with improved spatial resolution and enhanced susceptibility contrast. SWI is an MRI sequence sensitive to compounds that distort the local magnetic field (eg, calcium and iron), in which the phase information can differentiate. But the term SWI is colloquially used to denote high-spatial-resolution susceptibility-enhanced sequences across different MRI vendors and sequences even when phase information is not used. The imaging appearance of SWI and related sequences strongly depends on the acquisition technique. Initially, SWI and related sequences were mostly used to improve the depiction of findings already known from standard two-dimensional T2*-weighted neuroimaging: more microbleeds in patients who are aging or with dementia or mild brain trauma; increased conspicuity of superficial siderosis in Alzheimer disease and amyloid angiopathy; and iron deposition in neurodegenerative diseases or abnormal vascular structures, such as capillary telangiectasia. But SWI also helps to identify findings not visible on standard T2*-weighted images: the nigrosome 1 in Parkinson disease and dementia with Lewy bodies, the central vein and peripheral rim signs in multiple sclerosis, the peripheral rim sign in abscesses, arterial signal loss related to thrombus, asymmetrically prominent cortical veins in stroke, and intratumoral susceptibility signals in brain neoplasms.

Depiction of the Periosteum Using Ultrashort Echo Time Pulse Sequence with Three-Dimensional Cone Trajectory and Histologic Correlation in a Porcine Model

Objective

To evaluate the signal intensity of the periosteum using ultrashort echo time pulse sequence with three-dimensional cone trajectory (3D UTE) with or without fat suppression (FS) to distinguish from artifacts in porcine tibias.

Materials and Methods

The periosteum and overlying soft tissue of three porcine lower legs were partially peeled away from the tibial cortex. Another porcine tibia was prepared as three segments: with an intact periosteum outer and inner layer, with an intact periosteum inner layer, and without periosteum. Axial T1 weighted sequence (T1 WI) and 3D UTE (FS) were performed. Another porcine tibia without periosteum was prepared and subjected to 3D UTE (FS) and T1 WI twice, with positional changes. Two radiologists analyzed images to reach a consensus.

Results

The three periosteal tissues that were partially peeled away from the cortex showed a high signal in 3D UTE (FS) and low signal on T1 WI. 3D UTE (FS) showed a high signal around the cortical surface with an intact outer and inner periosteum, and subtle high signals, mainly around the upper cortical surfaces with the inner layer of the periosteum and without periosteum. T1 WI showed no signal around the cortical surfaces, regardless of the periosteum state. The porcine tibia without periosteum showed changes in the high signal area around the cortical surface as the position changed in 3D UTE (FS). No signal was detected around the cortical surface in T1 WI, regardless of the position change.

Conclusion

The periosteum showed a high signal in 3D UTE and 3D UTE FS that overlapped with artifacts around the cortical bone.

Simvastatin-Ezetimibe enhances growth factor expression and attenuates neuron loss in the hippocampus in a model of intracerebral hemorrhage

Intracerebral hemorrhage (ICH) is a common and severe neurological disorder associated with high morbidity and mortality rates. Despite extensive research into its pathology, there are no clinically approved neuroprotective treatments for ICH. Increasing evidence has revealed that inflammatory responses mediate the pathophysiological processes of brain injury following ICH. Experimental ICH was induced by direct infusion of 100 μL fresh (non‐heparinized) autologous whole blood into the right basal ganglia of Sprague–Dawley rats at a constant rate (10 μL/min). The simvastatin group was administered simvastatin (15 mg/kg) and the combination therapy group was administered simvastatin (10 mg/kg) and ezetimibe (10 mg/kg). Magnetic resonance imaging (MRI), the forelimb use asymmetry test, the Morris water maze test, and two biomarkers were used to evaluate the effect of simvastatin and combination therapy. MRI imaging revealed that combination therapy resulted in significantly reduced perihematomal edema. Biomarker analyses revealed that both treatments led to significantly reduced endothelial inflammatory responses. The forelimb use asymmetry test revealed that both treatment groups had significantly improved neurological outcomes. The Morris water maze test revealed improved neurological function after combined therapy, which also led to less neuronal loss in the hippocampal CA1 region. In conclusion, simvastatin–ezetimibe combination therapy can improve neurological function, attenuate the endothelial inflammatory response and lead to less neuronal loss in the hippocampal CA1 region in a rat model of ICH.

Evaluation of the influence of susceptibility-induced magnetic field distortions on the precision of contouring intracranial organs at risk for stereotactic radiosurgery

•

45 data sets (18 on a 1.5 T MR and 27 on a 3 T MR) were evaluated for susceptibility induced distortions.

•

Maximum distortions of up to 1.7 mm were found for organs at risk in standard diagnostic settings.

•

Median distortions ranged between 0.1 and 0.2 mm for all organs at risk.

•

Active shimming was estimated to reduce distortions by a factor of 2.3 to 2.9.

•

A safety margin of 1 mm would have encompassed 99.8% of the distortions.

Background and purpose

Magnetic resonance imaging (MRI) is a crucial factor in optimal treatment planning for stereotactic radiosurgery. To further the awareness of possible errors in MRI, this work aimed to investigate the magnitude of susceptibility induced MRI distortions for intracranial organs at risk (OARs) and test the effectiveness of actively shimming these distortions.

Materials and methods

Distortion maps for 45 exams of 42 patients (18 on a 1.5 T MRI scanner, 27 on a 3 T MRI scanner) were calculated based on a high-bandwidth double-echo gradient echo sequence. The investigated OARs were brainstem, chiasm, eyes, and optic nerves. The influence of active shimming was investigated by comparing unshimmed 1.5 T data with shimmed 3 T data and comparing the results to a model based prediction.

Results

The median distortion for the different OARs was found to be between 0.13 and 0.18 mm for 1.5 T and between 0.11 and 0.13 mm for 3 T. The maximum distortion was found to be between 1.3 and 1.7 mm for 1.5 T and between 1.1 and 1.4 mm for 3 T. The variation of values was much higher for 1.5 T than for 3 T across all investigated OARs. Active shimming was found to reduce distortions by a factor of 2.3 to 2.9 compared to the expected values.

Conclusions

Using a safety margin for OARs of 1 mm would have encompassed 99.8% of the distortions. Since distortions are inversely proportional to the readout bandwidth, they can be further reduced by increasing the bandwidth. Additional error sources like gradient nonlinearities need to be addressed separately.

Value of High-resolution MRI in Detecting Lymph Node Calcifications in Patients with Rectal Cancer

RATIONALE AND OBJECTIVES

To analyze CT and high-resolution MRI findings of nodal metastasis calcifications and determine the value of high-resolution MRI in detecting nodal calcifications in rectal cancer patients.

MATERIALS AND METHODS

In total, 229 rectal cancer patients were included. The CT was reviewed for the presence of nodal calcifications by two radiologists. High-resolution two-dimensional turbo spin-echo T2-weighted imaging (2D-TSE-T2WI) and fat-suppressed gadolinium-enhanced isotropic high-resolution three-dimensional gradient-echo T1-weighted imaging (3D-GRE-T1WI) were independently reviewed for nodal calcifications by the two radiologists at one-month and two-month intervals, respectively. The sensitivities, specificities and accuracies of the two high-resolution MRI in detecting nodal calcifications were calculated using CT results as a reference.

RESULTS

Regional calcified metastatic lymph nodes were found in 28 patients. The node-to-node evaluation revealed that 55 (98.2%) of the 56 calcified lymph nodes were metastatic. Fifty-one (92.7%) calcified metastatic lymph nodes displayed scattered fine punctate calcifications to different degrees on CT. In both types of high-resolution MRI, the calcifications demonstrated a patchy area of markedly reduced signal intensity in corresponding areas that were larger than those on CT. The sensitivity and accuracy of fat-suppressed gadolinium-enhanced isotropic high-resolution 3D-GRE-T1WI were significantly higher than those of high-resolution 2D-TSE-T2WI (76.8% vs 58.9%, P = 0.013; 98.3% vs 97.9%, P = 0.007; respectively).

CONCLUSION

Metastatic nodal calcifications are characteristic imaging findings in rectal cancer. Calcifications are indicated by markedly reduced signal on high-resolution MRI, which will alert radiologists to scrutinize CT for nodal calcifications and aid in the accurate diagnosis of metastatic lymph nodes.

Contemporary approaches to high-field magnetic resonance imaging with large field inhomogeneity

Despite its importance as a clinical imaging modality, magnetic resonance imaging remains inaccessible to most of the world's population due to its high cost and infrastructure requirements. Substantial effort is underway to develop portable, low-cost systems able to address MRI access inequality and to enable new uses of MRI such as bedside imaging. A key barrier to development of portable MRI systems is increased magnetic field inhomogeneity when using small polarizing magnets, which degrades image quality through distortions and signal dropout. Many approaches address field inhomogeneity by using a low polarizing field, approximately ten to hundreds of milli-Tesla. At low-field, even a large relative field inhomogeneity of several thousand parts-per-million (ppm) results in resonance frequency dispersion of only 1-2 kHz. Under these conditions, with necessarily wide pulse bandwidths, fast spin-echo sequences may be used at low field with negligible subject heating, and a broad range of other available imaging sequences can be implemented. However, high-field MRI, 1.5 T or greater, can provide substantially improved signal-to-noise ratio and image contrast, so that higher spatial resolution, clinical quality images may be acquired in significantly less time than is necessary at low-field. The challenge posed by small, high-field systems is that the relative field inhomogeneity, still thousands of ppm, becomes tens of kilohertz over the imaging volume. This article describes the physical consequences of field inhomogeneity on established gradient- and spin-echo MRI sequences, and suggests ways to reduce signal dropout and image distortion from field inhomogeneity. Finally, the practicality of currently available image contrasts is reviewed when imaging with a high magnetic field with large inhomogeneity.

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.

Improved PRF-based MR thermometry using k-space energy spectrum analysis

PURPOSE

Proton resonance frequency (PRF) thermometry encodes information in the phase of MRI signals. A multiplicative factor converts phase changes into temperature changes, and this factor includes the TE. However, phase variations caused by B₀ and/or B₁ inhomogeneities can effectively change TE in ways that vary from pixel to pixel. This work presents how spatial phase variations affect temperature maps and how to correct for corresponding errors.

METHODS

A method called "k-space energy spectrum analysis" was used to map regions in the object domain to regions in the k-space domain. Focused ultrasound heating experiments were performed in tissue-mimicking gel phantoms under two scenarios: with and without proper shimming. The second scenario, with deliberately de-adjusted shimming, was meant to emulate B₀ inhomogeneities in a controlled manner. The TE errors were mapped and compensated for using k-space energy spectrum analysis, and corrected results were compared with reference results. Furthermore, a volunteer was recruited to help evaluate the magnitude of the errors being corrected.

RESULTS

The in vivo abdominal results showed that the TE and heating errors being corrected can readily exceed 10%. In phantom results, a linear regression between reference and corrected temperatures results provided a slope of 0.971 and R² of 0.9964. Analysis based on the Bland-Altman method provided a bias of -0.0977°C and 95% limits of agreement that were 0.75°C apart.

CONCLUSION

Spatially varying TE errors, such as caused by B₀ and/or B₁ inhomogeneities, can be detected and corrected using the k-space energy spectrum analysis method, for increased accuracy in proton resonance frequency thermometry.

The influence of iron oxidation state on quantitative MRI parameters in post mortem human brain

A variety of Magnetic Resonance Imaging (MRI) techniques are known to be sensitive to brain iron content. In principle, iron sensitive MRI techniques are based on local magnetic field variations caused by iron particles in tissue. The purpose of this study was to investigate the sensitivity of MR relaxation and magnetization transfer parameters to changes in iron oxidation state compared to changes in iron concentration. Therefore, quantitative MRI parameters including R₁, R₂, R₂∗, quantitative susceptibility maps (QSM) and magnetization transfer ratio (MTR) of post mortem human brain tissue were acquired prior and after chemical iron reduction to change the iron oxidation state and chemical iron extraction to decrease the total iron concentration. All assessed parameters were shown to be sensitive to changes in iron concentration whereas only R₂, R₂∗ and QSM were also sensitive to changes in iron oxidation state. Mass spectrometry confirmed that iron accumulated in the extraction solution but not in the reduction solution. R₂∗ and QSM are often used as markers for iron content. Changes in these parameters do not necessarily reflect variations in iron content but may also be a result of changes in the iron's oxygenation state from ferric towards more ferrous iron or vice versa.

Higher sensitivity for traumatic cerebral microbleeds at 7 T ultra-high field MRI: is it clinically significant for the acute state of the patients and later quality of life?

Background

The present study evaluates the possible prognostic benefits of 7 T susceptibility weighted imaging (SWI) of traumatic cerebral microbleeds (TMBs) over 3 T SWI to predict the acute clinical state and subjective impairments, including health-related quality of life (HRQOL), after closed head injury (CHI).

Methods

The study group comprised 10 participants with known TMBs All subjects underwent 3 T magnetic resonance imaging (MRI) and 7 T MRI, respectively. Location and count of TMBs were independently evaluated by two neuroradiologists. The initial Glasgow Coma Scale (GCS), the duration of coma and further clinical data were taken from the patients records. HRQOL was assessed by means of a questionnaire. Memory complaints and neurological symptoms were inquired at the time of the MRI examinations.

Results

SWI revealed a total of 485 TMBs at 3 T, 584 TMBs at 7 T with similar spatial resolution, and 684 TMBs at 7 T with a factor of 10 higher spatial resolution. The TMBs depicted by 7 T high-resolution SWI were correlated with the duration of coma (Spearman's rho of 0.77). The corresponding association with TMBs in 3 T MRI SWI showed a Spearman's rho of 0.71. The initial GCS score and TMBs correlated with a Spearman's rho of -0.35 at 3 T SWI MRI and a rho of -0.33 at 7 T high-resolution SWI, respectively. The physical aspect of HRQOL correlated substantially with the count of TMBs (rho = 0.44 for 3 T SWI and rho = 0.35 for both 7 T SWI sequences, respectively).

Conclusions

The number of TMBs showed a substantial association with indicators of the acute clinical state and chronic neurobehavioral parameters after CHI, but there was no additional advantage of 7 T MRI. These preliminary findings warrant a larger prospective study for the future.

Myelin water imaging and R2* mapping in neonates: Investigating R2* dependence on myelin and fibre orientation in whole brain white matter

R₂^* relaxation provides a semiquantitative method of detecting myelin, iron and white matter fibre orientation angles. Compared with standard histogram-based analyses, angle-resolved analysis of R₂^* has previously been shown to substantially improve the detection of subtle differences in the brain between healthy siblings of subjects with multiple sclerosis and unrelated healthy controls. Neonates, who are born with very little myelin and iron, and an underdeveloped connectome, provide researchers with an opportunity to investigate whether R₂^* is intimately linked with fibre-angle or myelin content as it is in adults, which may in future studies be explored as a potential white matter developmental biomarker. Five healthy adult volunteers (mean age [±SD] = 31.2 [±8.3] years; three males) were recruited from Vancouver, Canada. Eight term neonates (mean age = 38.6 ± 1.2 weeks; five males) were recruited from the Children's Hospital of Chongqing Medical University neonatal ward. All subjects were scanned on identical 3 T Philips Achieva scanners equipped with an eight-channel SENSE head coil and underwent a multiecho gradient echo scan, a 32-direction DTI scan and a myelin water imaging scan. For both neonates and adults, bin-averaged R₂^* variation across the brain's white matter was found to be best explained by fibre orientation. For adults, this represented a difference in R₂^* values of 3.5 Hz from parallel to perpendicular fibres with respect to the main magnetic field. In neonates, the fibre orientation dependency displayed a cosine wave shape, with a small R₂^* range of 0.4 Hz. This minor relationship in neonates provides further evidence for the key role myelin probably plays in creating this fibre orientation dependence later in life, but suggests limited clinical application in newborn populations. Future studies should investigate fibre-orientation dependency in infants in the first 5 years, when substantial myelin development occurs.

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 role of iron in Parkinson's disease monkeys assessed by susceptibility weighted imaging and inductively coupled plasma mass spectrometry

Mounting evidences indicated that elevated iron levels in the substantia nigra (SN) have been concerned as the underlying mechanisms of neurodegenerative diseases, including Parkinson's disease (PD). The present study used the 1-Methyl-4-phenyl-1, 2, 3, 6 -tetrahydropyridine (MPTP)-treated cynomolgus monkeys for PD to evaluate the usability of SWI for assessing iron deposition in the cerebral nuclei of PD. The results showed that susceptibility-weighted imaging (SWI) phase values of the ipsilateral (MPTP-lesion side) SN of MPTP-treated monkeys were lower than those in the contralateral SN of MPTP-treated monkeys and the same side of Control monkeys, suggesting that iron deposition were elevated in the affected side SN of MPTP-treated monkeys. Whereas MPTP has not effects on the SWI phase values in other detected brain regions of monkeys, including red nucleus (RN), putamen (PUT) and caudate nucleus (CA). Furthermore, ICP-MS results showed that MPTP increased the iron levels in MPTP injection side, but no in the ipsilateral striatum. Additionally, MPTP treatment did not affect the calcium and manganese levels in the detected brain regions of monkeys. However, Pearson correlation analysis results indicated that there were not relationship between SWI phase values in MPTP-lesion side of SN with the behavioral score, tyrosine hydroxylase (TH)-positive cells number and iron levels in the MPTP-lesion side of midbrain. Taken together, the results confirm the involvement of SN iron accumulations in the MPTP-treated monkey models for PD, and indirectly verify the usability of SWI for the measurement of iron deposition in the cerebral nuclei of PD.

Field drift correction of proton resonance frequency shift temperature mapping with multichannel fast alternating nonselective free induction decay readouts

PURPOSE

To demonstrate that proton resonance frequency shift MR thermometry (PRFS-MRT) acquisition with nonselective free induction decay (FID), combined with coil sensitivity profiles, allows spatially resolved B₀ drift-corrected thermometry.

METHODS

Phantom experiments were performed at 1.5T and 3T. Acquisition of PRFS-MRT and FID were performed during MR-guided high-intensity focused ultrasound heating. The phase of the FIDs was used to estimate the change in angular frequency δω_drift per coil element. Two correction methods were investigated: (1) using the average δω_drift over all coil elements (0th-order) and (2) using coil sensitivity profiles for spatially resolved correction. Optical probes were used for independent temperature verification. In-vivo feasibility of the methods was evaluated in the leg of 1 healthy volunteer at 1.5T.

RESULTS

In 30 minutes, B₀ drift led to an apparent temperature change of up to -18°C and -98°C at 1.5T and 3T, respectively. In the sonicated area, both corrections had a median error of 0.19°C at 1.5T and -0.54°C at 3T. At 1.5T, the measured median error with respect to the optical probe was -1.28°C with the 0th-order correction and improved to 0.43°C with the spatially resolved correction. In vivo, without correction the spatiotemporal median of the apparent temperature was at -4.3°C and interquartile range (IQR) of 9.31°C. The 0th-order correction had a median of 0.75°C and IQR of 0.96°C. The spatially resolved method had the lowest median at 0.33°C and IQR of 0.80°C.

CONCLUSION

FID phase information from individual receive coil elements allows spatially resolved B₀ drift correction in PRFS-based MRT.

Distortion-free inside-out imaging for rapid diagnostics of rechargeable Li-ion cells

Safety risks associated with modern high energy-dense rechargeable cells highlight the need for advanced battery screening technologies. A common rechargeable cell exposed to a uniform magnetic field creates a characteristic field perturbation due to the inherent magnetism of electrochemical materials. The perturbation pattern depends on the design, state of charge, accumulated mechanical defects, and manufacturing flaws of the device. The quantification of the induced magnetic field with MRI provides a basis for noninvasive battery diagnostics. MRI distortions and rapid signal decay are the main challenges associated with strongly magnetic components present in most commercial cells. These can be avoided by using Single-Point Ramped Imaging with T ₁ enhancement (SPRITE). The method is immune to image artifacts arising from strong background gradients and eddy currents. Due to its superior image quality, SPRITE is highly sensitive to defects and the state of charge distribution in commercial Li-ion cells.

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.

Three-dimensional MRI sequences in MS diagnosis and research

The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).

SHARQnet - Sophisticated harmonic artifact reduction in quantitative susceptibility mapping using a deep convolutional neural network

Quantitative susceptibility mapping (QSM) reveals pathological changes in widespread diseases such as Parkinson's disease, Multiple Sclerosis, or hepatic iron overload. QSM requires multiple processing steps after the acquisition of magnetic resonance imaging (MRI) phase measurements such as unwrapping, background field removal and the solution of an ill-posed field-to-source-inversion. Current techniques utilize iterative optimization procedures to solve the inversion and background field correction, which are computationally expensive and lead to suboptimal or over-regularized solutions requiring a careful choice of parameters that make a clinical application of QSM challenging. We have previously demonstrated that a deep convolutional neural network can invert the magnetic dipole kernel with a very efficient feed forward multiplication not requiring iterative optimization or the choice of regularization parameters. In this work, we extended this approach to remove background fields in QSM. The prototype method, called SHARQnet, was trained on simulated background fields and tested on 3T and 7T brain datasets. We show that SHARQnet outperforms current background field removal procedures and generalizes to a wide range of input data without requiring any parameter adjustments. In summary, we demonstrate that the solution of ill-posed problems in QSM can be achieved by learning the underlying physics causing the artifacts and removing them in an efficient and reliable manner and thereby will help to bring QSM towards clinical applications.

Data consistency-driven determination of B 0 -fluctuations in gradient-echo MRI

PURPOSE

Introduce a method to estimate B 0 -fluctuations based on the analysis of raw k-space data, without sequence modifications or external hardware, and correct for their detrimental effects in gradient-echo MRI.

THEORY

Inconsistencies in multi-channel raw k-space data can be used to estimate B 0 -fluctuations by exploiting coil-sensitivity information.

METHODS

The proposed method, dubbed consistency navigation, is used to extract B 0 -fluctuations from T 2 * -weighted 3D gradient-echo data. These results are compared with the results from an MR phase navigator and respiratory bellows. The spatial variation of the B 0 -fluctuation amplitude is derived using the sensitivity maps of the coil array and compared with direct measurements based on dynamic 2D gradient-echo data.

RESULTS

B 0 -fluctuations derived from the consistency navigator and MR phase navigator are highly correlated. Images corrected for these fluctuations show marked improvements in homogeneity and tissue delineation. The spatial variation of the B 0 -fluctuation amplitude follows closely the variation directly measured from time-resolved 2D scans.

CONCLUSIONS

Based on the consistency navigator, an accurate estimation of the spatiotemporal characteristics of B 0 -fluctuations and correction of T 2 * -weighted images has been demonstrated.

isoPhasor: a generic and precise marker visualization, localization, and quantification method based on phase saddles in 3D MR imaging

PURPOSE

To derive a generic approach for accurate localization and characterization of susceptibility markers in MRI, compatible with many common types of pulse sequences, sampling trajectories, and acceleration methods.

THEORY AND METHODS

A susceptibility marker's dipolar phase evolution creates 3 saddles in the phase gradient of the spatial encoding, for each sampled data point in k-space. The signal originating from these saddles can be focused at the location of the marker to create positive contrast. The required phase shift can be calculated from the scan parameters and the marker properties, providing a marker detection algorithm generic for different scan types. The method was validated numerically and experimentally for a broad range of spherical susceptibility markers (0.3 < radius < 1.6 mm, 10 < |∆χ| < 3300 ppm), under various conditions.

RESULTS

For all numerical and experimental phantoms, the average localization error was below one third of the voxel size, whereas the average error in magnetic strength quantification was 7%. The experiments included different pulse sequences (gradient echo, spin echo [SE], and free induction decay scans), sampling strategies (Cartesian, radial), and acceleration methods (echo planar imaging EPI, turbo SE).

CONCLUSION

Spherical markers can be identified from their phase saddles, enabling clear visualization, precise localization, and accurate quantification of their magnetic strength, in a wide range of clinically relevant pulse sequences and sampling strategies.

Imperfect magnetic field gradients in radial k-space encoding-Quantification, correction, and parameter dependency

PURPOSE

Sensitivity to imperfections of image-encoding gradient fields may significantly impair widespread use of radial MR data acquisition. Such imperfections can cause individual echo shifts for each spoke acquired in the k-space and may produce severe image artifacts. Therefore, fast and robust methods to quantify and correct for those echo shifts are required.

THEORY AND METHODS

Echo shifts can be induced by inhomogeneities of the static magnetic field (δn_B ) and by imbalances of the imaging gradients (δn_G ) mainly caused by eddy currents. However, mismatch between data acquisition and gradient switching may additionally play a role. From the position of the echo maxima of 2 opposing spokes, δn_G and δn_B can be determined and corrected by adapting the read-dephasing gradient accordantly. This approach was implemented on MR-systems of different field strengths, gradient systems, and vendors, and the dependencies of echo shift and acquisition parameters were analyzed. Data sets of phantoms and of mice under in vivo conditions were obtained using RF-spoiled 2D radial-FLASH.

RESULTS

The presented method allowed for echo-shift detection and correction of < 1 data point, significantly improving the image quality in vitro and in vivo. Moreover, the method separated the effect of imbalanced gradients from those of magnetic inhomogeneities. The observed echo shifts were MR system-specifically dependent on acquisition parameters such as gradient strengths and dwell time.

CONCLUSIONS

By acquiring 12 spokes for a certain set of acquisition parameters, the proposed method successfully corrects echo shift-related image artifacts independently of the MR system.

High spatial resolution BOLD fMRI using simultaneous multislice excitation with echo-shifting gradient echo at 7 Tesla

We introduce an accelerated gradient echo (GRE) sequence combining simultaneous multislice excitation (SMS) with echo-shifting technique for high spatial resolution blood oxygen level dependent (BOLD) functional MRI (fMRI). The simulation was conducted to optimize scan parameters. To validate the feasibility of the proposed technique, the visual and motor task experiments were performed at 7.0 Tesla (T). The single-shot EPI sequence was also applied in comparison with the proposed technique. The simulation results showed that an optimized flip angle of 9° provided maximal BOLD contrast for our scanning scheme, allowing low power deposition and SMS acceleration factor of 5. Additionally, parallel acquisition imaging with acceleration factor of 2 was utilized, which allowed a total acceleration factor of 10 in volunteer study. The experiment results showed that geometric distortion-free BOLD images with voxel size of 1.0 × 1.0 × 2.5 mm³ were obtained. Significant brain activation was identified in both visual and motor task experiments, which were in accordance with previous investigations. The proposed technique has potential for high spatial resolution fMRI at ultra-high field because of its sufficient BOLD sensitivity as well as improved acquisition speed over conventional GRE-based techniques.

Iron deposition quantification: Applications in the brain and liver

Iron has long been implicated in many neurological and other organ diseases. It is known that over and above the normal increases in iron with age, in certain diseases there is an excessive iron accumulation in the brain and liver. MRI is a noninvasive means by which to image the various structures in the brain in three dimensions and quantify iron over the volume of the object of interest. The quantification of iron can provide information about the severity of iron-related diseases as well as quantify changes in iron for patient follow-up and treatment monitoring. This article provides an overview of current MRI-based methods for iron quantification, specifically for the brain and liver, including: signal intensity ratio, R₂ , R2*, R2', phase, susceptibility weighted imaging and quantitative susceptibility mapping (QSM). Although there are numerous approaches to measuring iron, R₂ and R2* are currently preferred methods in imaging the liver and QSM has become the preferred approach for imaging iron in the brain.

LEVEL OF EVIDENCE

5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018. J. MAGN. RESON. IMAGING 2018;48:301-317.

Signal compartments in ultra-high field multi-echo gradient echo MRI reflect underlying tissue microstructure in the brain

Gradient recalled echo magnetic resonance imaging (GRE-MRI) at ultra-high field holds great promise for new contrast mechanisms and delineation of putative tissue compartments that contribute to the multi-echo GRE-MRI signal may aid structural characterization. Several studies have adopted the three water-pool compartment model to study white matter brain regions, associating individual compartments with myelin, axonal and extracellular water. However, the number and identifiability of GRE-MRI signal compartments has not been fully explored. We undertook this task for human brain imaging data. Multiple echo time GRE-MRI data were acquired in five healthy participants, specific anatomical structures were segmented in each dataset (substantia nigra, caudate, insula, putamen, thalamus, fornix, internal capsule, corpus callosum and cerebrospinal fluid), and the signal fitted with models comprising one to six signal compartments using a complex-valued plane wave formulation. Information criteria and cluster analysis methods were used to ascertain the number of distinct compartments within the signal from each structure and to determine their respective frequency shifts. We identified five principal signal compartments with different relative contributions to each structure's signal. Voxel-based maps of the volume fraction of each of these compartments were generated and demonstrated spatial correlation with brain anatomy.

Graph theory reveals amygdala modules consistent with its anatomical subdivisions

Similarities on the cellular and neurochemical composition of the amygdaloid subnuclei suggests their clustering into subunits that exhibit unique functional organization. The topological principle of community structure has been used to identify functional subnetworks in neuroimaging data that reflect the brain effective organization. Here we used modularity to investigate the organization of the amygdala using resting state functional magnetic resonance imaging (rsfMRI) data. Our goal was to determine whether such topological organization would reliably reflect the known neurobiology of individual amygdaloid nuclei, allowing for human imaging studies to accurately reflect the underlying neurobiology. Modularity analysis identified amygdaloid elements consistent with the main anatomical subdivisions of the amygdala that embody distinct functional and structural properties. Additionally, functional connectivity pathways of these subunits and their correlation with task-induced amygdala activation revealed distinct functional profiles consistent with the neurobiology of the amygdala nuclei. These modularity findings corroborate the structure–function relationship between amygdala anatomical substructures, supporting the use of network analysis techniques to generate biologically meaningful partitions of brain structures.

Susceptibility weighted imaging and quantitative susceptibility mapping of the cerebral vasculature using ferumoxytol

PURPOSE

To demonstrate the potential of imaging cerebral arteries and veins with ferumoxytol using susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM).

MATERIALS AND METHODS

The relationships between ferumoxytol concentration and the apparent susceptibility at 1.5T, 3T, and 7T were determined using phantom data; the ability of visualizing subvoxel vessels was evaluated using simulations; and the feasibility of using ferumoxytol to enhance the visibility of small vessels was confirmed in three healthy volunteers at 7T(with doses 1 mg/kg to 4 mg/kg). The visualization of the lenticulostriate arteries and the medullary veins was assessed by two raters and the contrast-to-noise ratios (CNRs) of these vessels were measured.

RESULTS

The relationship between ferumoxytol concentration and susceptibility was linear with a slope 13.3 ± 0.2 ppm·mg^-1 ·mL at 7T. Simulations showed that SWI data with an increased dose of ferumoxytol, higher echo time (TE), and higher imaging resolution improved the detection of smaller vessels. With 4 mg/kg ferumoxytol, voxel aspect ratio = 1:8, TE = 10 ms, the diameter of the smallest detectable artery was approximately 50μm. The rating score for arteries was improved from 1.5 ± 0.5 (precontrast) to 3.0 ± 0.0 (post-4 mg/kg) in the in vivo data and the apparent susceptibilities of the arteries (0.65 ± 0.02 ppm at 4 mg/kg) agreed well with the expected susceptibility (0.71 ± 0.05 ppm).

CONCLUSION

The CNR for cerebral vessels with ferumoxytol can be enhanced using SWI, and the apparent susceptibilities of the arteries can be reliably quantified using QSM. This approach improves the imaging of the entire vascular system outside the capillaries and may be valuable for a variety of neurodegenerative diseases which involve the microvasculature.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:621-633.

Multimodal MEMPRAGE, FLAIR, and [Formula: see text] Segmentation to Resolve Dura and Vessels from Cortical Gray Matter

While widely in use in automated segmentation approaches for the detection of group differences or of changes associated with continuous predictors in gray matter volume, T1-weighted images are known to represent dura and cortical vessels with signal intensities similar to those of gray matter. By considering multiple signal sources at once, multimodal segmentation approaches may be able to resolve these different tissue classes and address this potential confound. We explored here the simultaneous use of FLAIR and apparent transverse relaxation rates (a signal related to T2* relaxation maps and having similar contrast) with T1-weighted images. Relative to T1-weighted images alone, multimodal segmentation had marked positive effects on 1. the separation of gray matter from dura, 2. the exclusion of vessels from the gray matter compartment, and 3. the contrast with extracerebral connective tissue. While obtainable together with the T1-weighted images without increasing scanning times, apparent transverse relaxation rates were less effective than added FLAIR images in providing the above mentioned advantages. FLAIR images also improved the detection of cortical matter in areas prone to susceptibility artifacts in standard MPRAGE T1-weighted images, while the addition of transverse relaxation maps exacerbated the effect of these artifacts on segmentation. Our results confirm that standard MPRAGE segmentation may overestimate gray matter volume by wrongly assigning vessels and dura to this compartment and show that multimodal approaches may greatly improve the specificity of cortical segmentation. Since multimodal segmentation is easily implemented, these benefits are immediately available to studies focusing on translational applications of structural imaging.

Susceptibility-weighted imaging: current status and future directions

Susceptibility-weighted imaging (SWI) is a method that uses the intrinsic nature of local magnetic fields to enhance image contrast in order to improve the visibility of various susceptibility sources and to facilitate diagnostic interpretation. It is also the precursor to the concept of the use of phase for quantitative susceptibility mapping (QSM). Nowadays, SWI has become a widely used clinical tool to image deoxyhemoglobin in veins, iron deposition in the brain, hemorrhages, microbleeds and calcification. In this article, we review the basics of SWI, including data acquisition, data reconstruction and post-processing. In particular, the source of cusp artifacts in phase images is investigated in detail and an improved multi-channel phase data combination algorithm is provided. In addition, we show a few clinical applications of SWI for the imaging of stroke, traumatic brain injury, carotid vessel wall, siderotic nodules in cirrhotic liver, prostate cancer, prostatic calcification, spinal cord injury and intervertebral disc degeneration. As the clinical applications of SWI continue to expand both in and outside the brain, the improvement of SWI in conjunction with QSM is an important future direction of this technology. Copyright © 2016 John Wiley & Sons, Ltd.

Overview of quantitative susceptibility mapping

Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and represents an important parameter in the field of MRI. With the recently introduced method of quantitative susceptibility mapping (QSM) and its conceptual extension to susceptibility tensor imaging (STI), the non-invasive assessment of this important physical quantity has become possible with MRI. Both methods solve the ill-posed inverse problem to determine the magnetic susceptibility from local magnetic fields. Whilst QSM allows the extraction of the spatial distribution of the bulk magnetic susceptibility from a single measurement, STI enables the quantification of magnetic susceptibility anisotropy, but requires multiple measurements with different orientations of the object relative to the main static magnetic field. In this review, we briefly recapitulate the fundamental theoretical foundation of QSM and STI, as well as computational strategies for the characterization of magnetic susceptibility with MRI phase data. In the second part, we provide an overview of current methodological and clinical applications of QSM with a focus on brain imaging. Copyright © 2016 John Wiley & Sons, Ltd.

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.

Magnetic susceptibility-induced echo-time shifts: Is there a bias in age-related fMRI studies?

PURPOSE

To evaluate the potential for bias in functional magnetic resonance imaging (fMRI) aging studies resulting from age-related differences in magnetic field distributions that can impact echo time and functional contrast.

MATERIALS AND METHODS

Magnetic field maps were taken on 31 younger adults (age: 22 ± 2.9 years) and 46 older adults (age: 66 ± 4.5 years) on a 3T scanner. Using the spatial gradients of the magnetic field map for each participant, an echo planar imaging (EPI) trajectory was simulated. The effective echo time, time at which the k-space trajectory is the closest to the center of k-space, was calculated. This was used to examine both within-subject and across-age-group differences in the effective echo time maps. The blood oxygenation level-dependent (BOLD) percent signal change resulting from those echo time shifts was also calculated to determine their impact on fMRI aging studies.

RESULTS

For a single subject, the effective echo time varied as much as ±5 msec across the brain. An unpaired t-test between the effective echo time across age groups resulted in significant differences in several regions of the brain (P < 0.01). The difference in echo time was only ∼1 msec, however, which is not expected to have an important impact on BOLD fMRI percent signal change (<4%).

CONCLUSION

Susceptibility-induced magnetic field gradients induce local echo-time shifts in gradient echo fMRI images, which can cause variable BOLD sensitivity across the brain. However, the age-related differences in BOLD signal are expected to be small for an fMRI study at 3T.

LEVEL OF EVIDENCE

1 J. Magn. Reson. Imaging 2017;45:207-214.

Tracking and Quantification of Magnetically Labeled Stem Cells using Magnetic Resonance Imaging

Stem cell based therapies have critical impacts on treatments and cures of diseases such as neurodegenerative or cardiovascular disease. In vivo tracking of stem cells labeled with magnetic contrast agents is of particular interest and importance as it allows for monitoring of the cells' bio-distribution, viability, and physiological responses. Herein, recent advances are introduced in tracking and quantification of super-paramagnetic iron oxide (SPIO) nanoparticles-labeled cells with magnetic resonance imaging, a noninvasive approach that can longitudinally monitor transplanted cells. This is followed by recent translational research on human stem cells that are dual-labeled with green fluorescence protein (GFP) and SPIO nanoparticles, then transplanted and tracked in a chicken embryo model. Cell labeling efficiency, viability, and cell differentiation are also presented.

Spatial Precision in Magnetic Resonance Imaging-Guided Radiation Therapy: The Role of Geometric Distortion

Because magnetic resonance imaging-guided radiation therapy (MRIgRT) offers exquisite soft tissue contrast and the ability to image tissues in arbitrary planes, the interest in this technology has increased dramatically in recent years. However, intrinsic geometric distortion stemming from both the system hardware and the magnetic properties of the patient affects MR images and compromises the spatial integrity of MRI-based radiation treatment planning, given that for real-time MRIgRT, precision within 2 mm is desired. In this article, we discuss the causes of geometric distortion, describe some well-known distortion correction algorithms, and review geometric distortion measurements from 12 studies, while taking into account relevant imaging parameters. Eleven of the studies reported phantom measurements quantifying system-dependent geometric distortion, while 2 studies reported simulation data quantifying magnetic susceptibility-induced geometric distortion. Of the 11 studies investigating system-dependent geometric distortion, 5 reported maximum measurements less than 2 mm. The simulation studies demonstrated that magnetic susceptibility-induced distortion is typically smaller than system-dependent distortion but still nonnegligible, with maximum distortion ranging from 2.1 to 2.6 mm at a field strength of 1.5 T. As expected, anatomic landmarks containing interfaces between air and soft tissue had the largest distortions. The evidence indicates that geometric distortion reduces the spatial integrity of MRI-based radiation treatment planning and likely diminishes the efficacy of MRIgRT. Better phantom measurement techniques and more effective distortion correction algorithms are needed to achieve the desired spatial precision.