Ultra-high-resolution mapping of myelin and g-ratio in a panel of Mbp enhancer-edited mouse strains using microstructural MRI.

Non-invasive myelin water fraction (MWF) and g-ratio mapping using microstructural MRI have the potential to offer critical insights into brain microstructure and our understanding of neuroplasticity and neuroinflammation. By leveraging a unique panel of variably hypomyelinating mouse strains, we validated a high-resolution, model-free image reconstruction method for whole-brain MWF mapping. Further, by employing a bipolar gradient echo MRI sequence, we achieved high spatial resolution and robust mapping of MWF and g-ratio across the whole mouse brain. Our regional white matter-tract specific analyses demonstrated a graded decrease in MWF in white matter tracts which correlated strongly with myelin basic protein gene (Mbp) mRNA levels. Using these measures, we derived the first sensitive calibrations between MWF and Mbp mRNA in the mouse. Minimal changes in axonal density supported our hypothesis that observed MWF alterations stem from hypomyelination. Overall, our work strongly emphasizes the potential of non-invasive, MRI-derived MWF and g-ratio modeling for both preclinical model validation and ultimately translation to humans.

Unveiling metabolic patterns in dementia: Insights from high-resolution quantitative blood-oxygenation-level-dependent MRI.

BACKGROUND: Oxygen extraction fraction (OEF) and deoxyhemoglobin (DoHb) levels reflect variations in cerebral oxygen metabolism in demented patients. PURPOSE: Delineating the metabolic profiles evident throughout different phases of dementia necessitates an integrated analysis of OEF and DoHb levels. This is enabled by leveraging high-resolution quantitative blood oxygenation level dependent (qBOLD) analysis of magnitude images obtained from a multi-echo gradient-echo MRI (mGRE) scan performed on a 3.0 Tesla scanner. METHODS: Achieving superior spatial resolution in qBOLD necessitates the utilization of an mGRE scan with only four echoes, which in turn limits the number of measurements compared to the parameters within the qBOLD model. Consequently, it becomes imperative to discard non-essential parameters to facilitate further analysis. This process entails transforming the qBOLD model into a format suitable for fitting the log-magnitude difference (L-MDif) profiles of the four echo magnitudes present in each brain voxel. In order to bolster spatial specificity, the log-difference qBOLD model undergoes refinement into a representative form, termed as r-qBOLD, particularly when applied to class-averaged L-MDif signals derived through k-means clustering of L-MDif signals from all brain voxels into a predetermined number of clusters. The agreement between parameters estimated using r-qBOLD for different cluster sizes is validated using Bland-Altman analysis, and the model's goodness-of-fit is evaluated using a χ 2 ${\chi ^2}$ -test. Retrospective MRI data of Alzheimer's disease (AD), mild cognitive impairment (MCI), and non-demented patients without neuropathological disorders, pacemakers, other implants, or psychiatric disorders, who completed a minimum of three visits prior to MRI enrolment, are utilized for the study. RESULTS: Utilizing a cohort comprising 30 demented patients aged 65-83 years in stages 4-6 representing mild, moderate, and severe stages according to the clinical dementia rating (CDR), matched with an age-matched non-demented control group of 18 individuals, we conducted joint observations of OEF and DoHb levels estimated using r-qBOLD. The observations elucidate metabolic signatures in dementia based on OEF and DoHb levels in each voxel. Our principal findings highlight the significance of spatial patterns of metabolic profiles (metabolic patterns) within two distinct regimes: OEF levels exceeding the normal range (S1-regime), and OEF levels below the normal range (S2-regime). The S1-regime, accompanied by low DoHb levels, predominantly manifests in fronto-parietal and perivascular regions with increase in dementia severity. Conversely, the S2-regime, accompanied by low DoHb levels, is observed in medial temporal (MTL) regions. Other regions with abnormal metabolic patterns included the orbitofrontal cortex (OFC), medial-orbital prefrontal cortex (MOPFC), hypothalamus, ventro-medial prefrontal cortex (VMPFC), and retrosplenial cortex (RSP). Dysfunction in the OFC and MOPFC indicated cognitive and emotional impairment, while hypothalamic involvement potentially indicated preclinical dementia. Reduced metabolic activity in the RSP suggested early-stage AD related functional abnormalities. CONCLUSIONS: Integrated analysis of OEF and DoHb levels using r-qBOLD reveals distinct metabolic signatures across dementia phases, highlighting regions susceptible to neuronal loss, vascular involvement, and preclinical indicators.

MR Imaging of the Pelvic Bones: The Current and Cutting-Edge Techniques.

This review presents an overview of the spectrum of the current and cutting-edge MRI techniques for pelvic bone imaging in clinical practice. The current MRI sequences and their advantages, disadvantages and usefullness in the imaging of this complex anatomical region are addressed. Finally, cutting-edge techniques are discussed, including susceptibility weighted MRI, ultrashort echo time MRI, zero echo time MRI and a deep learning-based multiparametric MRI technique named 'synthetic CT,' creating CT-like images without ionizing radiaton. Main Points: GRE, SWI, UTE, ZTE MRI and synthetic CT sequences depict the cortical outline of the bones better in comparison to conventional MR images.MRI-based synthetic CT can create HU maps and allows for automated segmentation of pelvic bones.The current and cutting-edge MR techniques for bone imaging are complementary in the characterization of a variety of musculoskeletal disorders.

Self-labelled encoder-decoder (SLED) for multi-echo gradient echo-based myelin water imaging.

PURPOSE: Reconstruction of high quality myelin water imaging (MWI) maps is challenging, particularly for data acquired using multi-echo gradient echo (mGRE) sequences. A non-linear least squares fitting (NLLS) approach has often been applied for MWI. However, this approach may produce maps with limited detail and, in some cases, sub-optimal signal to noise ratio (SNR), due to the nature of the voxel-wise fitting. In this study, we developed a novel, unsupervised learning method called self-labelled encoder-decoder (SLED) to improve gradient echo-based MWI data fitting. METHODS: Ultra-high resolution, MWI data was collected from five mouse brains with variable levels of myelination, using a mGRE sequence. Imaging data was acquired using a 7T preclinical MRI system. A self-labelled, encoder-decoder network was implemented in TensorFlow for calculation of myelin water fraction (MWF) based on the mGRE signal decay. A simulated MWI phantom was also created to evaluate the performance of MWF estimation. RESULTS: Compared to NLLS, SLED demonstrated improved MWF estimation, in terms of both stability and accuracy in phantom tests. In addition, SLED produced less noisy MWF maps from high resolution MR microscopy images of mouse brain tissue. It specifically resulted in lower noise amplification for all mouse genotypes that were imaged and yielded mean MWF values in white matter ROIs that were highly correlated with those derived from standard NLLS fitting. Lastly, SLED also exhibited higher tolerance to low SNR data. CONCLUSION: Due to its unsupervised and self-labeling nature, SLED offers a unique alternative to analyze gradient echo-based MWI data, providing accurate and stable MWF estimations.

Dynamic cerebellar herniation in Chiari patients during the cardiac cycle evaluated by dynamic magnetic resonance imaging.

PURPOSE: Cerebellar herniation in Chiari patients can be dynamic, following the cerebrospinal fluid pulsatility during the cardiac cycle. We present a voxel intensity distribution method (VIDM) to automatically extract the pulsatility-dependent herniation in time-resolved MRI (CINE MRI) and compare it to the simple linear measurements. The degree of herniation is furthermore compared on CINE and static sequences, and the cerebellar movement is correlated to the presence of hydrocephalus and syringomyelia. METHODS: The cerebellar movement in 27 Chiari patients is analyzed with VIDM and the results were compared to linear measurements on an image viewer (visual inspection, VI) using a paired t test. Second, an ANOVA test is applied to compare the degree of herniation on static 3D MRI and CINE. Finally, the Pearson's correlation coefficient is calculated for the correlation between cerebellar movement and the presence of hydrocephalus and syringomyelia. RESULTS: VIDM showed significant movement in 85% of our patients. Assuming that movement < 1 mm cannot be detected reliably on an image viewer, VI identified movement in 29.6% of the patients (p = 0.002). The herniation was greater on static sequences than on CINE in most cases, but this was not statistically significant. The cerebellar movement was not correlated with hydrocephalus or syringomyelia (Pearson's coefficient < 0.3). CONCLUSIONS: VIDM is a sensitive method to detect tissue movement on CINE MRI and could be used for Chiari patients, but also for the evaluation of cyst membranes, ventriculostomies, etc. The cerebellar movement appears not to correlate with hydrocephalus and syringomyelia in Chiari patients.

Temporal Profile of CT and T2*-Weighted Gradient-Echo MRI in a Patient with Unilateral Thalamostriate Vein Thrombosis.

Deep cerebral venous system thrombosis (DCVST) is an uncommon variety of thrombosis that accounts for 11% of cases of cerebral venous thrombosis. Thalamostriate vein (TSV) thrombosis is further rare among patients with DCVST. Although patients with cerebral venous thrombosis commonly have characteristic neurological deficits including headache, deterioration of consciousness, and seizures, patients with DCVST do not necessarily show such symptoms. Therefore, diagnose of DCVST is sometimes difficult. Here we report a case of TSV thrombosis with a unilateral basal ganglion lesion presenting with right-sided hemiparesis. A 61-year-old Japanese female was referred to our hospital. On neurological examination, she had no headache but presented with right facial paresis with dysarthria. Her right hemiparesis was present in the upper and lower extremities. We repeatedly performed brain computed tomography (CT) and T2*-weighted conventional gradient-echo (GRE) magnetic resonance imaging, and conclusively diagnosed as left TSV thrombosis. We firstly report a case of unilateral DCVST associated with TSV thrombosis in which a temporal profile of CT and T2*-weighted GRE images was obtained. Although DCVST is a rare clinical entity, physicians should be aware that repeated radiological observations can be useful for the diagnosis and early medical treatment for DCVST.

Closed-form expressions for flip angle variation that maximize total signal in T1-weighted rapid gradient echo MRI.

PURPOSE: Magnetization-prepared rapid gradient-echo (MPRAGE) sequences are commonly employed for T1-weighted structural brain imaging. Following a contrast preparation radiofrequency (RF) pulse, the data acquisition proceeds under nonequilibrium conditions of the relaxing longitudinal magnetization. Variation of the flip angle can be used to maximize total available signal. Simulated annealing or greedy algorithms have so far been published to numerically solve this problem, with signal-to-noise ratios optimized for clinical imaging scenarios by adhering to a predefined shape of the signal evolution. We propose an unconstrained optimization of the MPRAGE experiment that employs techniques from resource allocation theory. A new dynamic programming solution is introduced that yields closed-form expressions for optimal flip angle variation. METHODS: Flip angle series are proposed that maximize total transverse magnetization (Mxy) for a range of physiologic T1 values. A 3D MPRAGE sequence is modified to allow for a controlled variation of the excitation angle. Experiments employing a T1 contrast phantom are performed at 3T. 1D acquisitions without phase encoding permit measurement of the temporal development of Mxy. Image mean signal and standard deviation for reference flip angle trains are compared in 2D measurements. Signal profiles at sharp phantom edges are acquired to access image blurring related to nonuniform Mxy development. RESULTS: A novel closed-form expression for flip angle variation is found that constitutes the optimal policy to reach maximum total signal. It numerically equals previously published results of other authors when evaluated under their simplifying assumptions. Longitudinal magnetization (Mz) is exhaustively used without causing abrupt changes in the measured MR signal, which is a prerequisite for artifact free images. Phantom experiments at 3T verify the expected benefit for total accumulated k-space signal when compared with published flip angle series. CONCLUSIONS: Describing the MR signal collection in MPRAGE sequences as a Bellman problem is a new concept. By means of recursively solving a series of overlapping subproblems, this leads to an elegant solution for the problem of maximizing total available MR signal in k-space. A closed-form expression for flip angle variation avoids the complexity of numerical optimization and eases access to controlled variation in an attempt to identify potential clinical applications.

Susceptibility tensor imaging (STI) of the brain.

Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility and magnetic susceptibility anisotropy can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping to remove such dependence. Similar to diffusion tensor imaging, STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of the susceptibility anisotropy in brain white matter is myelin. Another unique feature of the susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in the myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research. Copyright © 2016 John Wiley & Sons, Ltd.

Fast dynamic imaging technique to identify obstructive lesions in the CSF space: report of 2 cases.

Disorders of CSF dynamics such as syringomyelia and obstructive hydrocephalus can be caused by thin mobile obstructive lesions not visible on traditional MRI sequences. New imaging techniques with balanced steady-state free precession (bSSFP) and dynamic imaging with bSSFP cine allow visualization of these pulsatile structures within the CSF space. The authors present 2 cases involving pediatric patients-one who developed presumed idiopathic syringomyelia and one with presumed communicating hydrocephalus in association with Pfeiffer syndrome-who harbored thin dynamic obstructive lesions seen on bSSFP cine studies using 1.5-T MRI. In combination with traditional CSF cine studies and bSSFP, bSSFP cine sequence was able to detect dynamic membranous adhesions not seen on traditional MRI sequences. These previously undetectable lesions on traditional MRI sequences were the etiology of CSF obstruction, and tailored surgical approaches were performed to avoid shunting in both patients. These reports demonstrate the clinical utility for using these novel imaging tools for the detection of thin adhesions and dynamic lesions in the central nervous system. Balanced SSFP cine sequences can supplement conventional MR modalities to identify these otherwise poorly visualized lesions responsible for presumed communicating hydrocephalus or idiopathic syringomyelia.

Effects of white matter microstructure on phase and susceptibility maps.

PURPOSE: To investigate the effects on quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI) of the frequency variation produced by the microstructure of white matter (WM). METHODS: The frequency offsets in a WM tissue sample that are not explained by the effect of bulk isotropic or anisotropic magnetic susceptibility, but rather result from the local microstructure, were characterized for the first time. QSM and STI were then applied to simulated frequency maps that were calculated using a digitized whole-brain, WM model formed from anatomical and diffusion tensor imaging data acquired from a volunteer. In this model, the magnitudes of the frequency contributions due to anisotropy and microstructure were derived from the results of the tissue experiments. RESULTS: The simulations suggest that the frequency contribution of microstructure is much larger than that due to bulk effects of anisotropic magnetic susceptibility. In QSM, the microstructure contribution introduced artificial WM heterogeneity. For the STI processing, the microstructure contribution caused the susceptibility anisotropy to be significantly overestimated. CONCLUSION: Microstructure-related phase offsets in WM yield artifacts in the calculated susceptibility maps. If susceptibility mapping is to become a robust MRI technique, further research should be carried out to reduce the confounding effects of microstructure-related frequency contributions.

In-phase signal intensity loss in solid renal masses on dual-echo gradient-echo MRI: association with malignancy and pathologic classification.

OBJECTIVE: The purposes of this study were to determine the prevalence of in-phase signal intensity loss on dual-echo gradient-echo MRI in solid renal masses using visual and quantitative techniques and to test for any association between in-phase signal intensity loss and pathologic classification. MATERIALS AND METHODS: The renal MRI studies of 177 patients (192 solid masses consisting of 166 renal cell carcinomas [RCCs], four malignant non-RCCs, and 22 benign tumors) were qualitatively reviewed by two blinded readers for visual evidence of relative in-phase signal intensity loss. For lesions without visual evidence, whole-lesion ROIs were used to attempt quantification of subtle signal intensity loss between opposed- and in-phase images (signal intensity loss index). RESULTS: Visual in-phase signal intensity loss was noted in 18% of clear cell RCC, 42% of papillary RCC, and no benign lesions. There was significant correlation between malignancy and visual signal intensity loss (Fisher exact test, p = 0.0092). Visual signal intensity loss was predictive of papillary RCC over clear cell RCC (odds ratio, 5.79; p = 0.0002) in logistic regression analysis of all RCCs, controlling for size. Quantitative assessment of remaining lesions provided no additional diagnostic benefit. CONCLUSION: Visible in-phase signal intensity loss is relatively common within solid renal masses and was associated with RCC and particularly papillary RCC (among all RCCs) in our population. Quantitative analysis in lesions without visible signal intensity loss was not predictive of RCC. Further work should be performed to validate the usefulness of this additional imaging parameter to help characterize renal masses and to determine the impact of this finding on imaging techniques potentially sensitive to susceptibility effects.

Gradient echo based fiber orientation mapping using R2* and frequency difference measurements.

Fiber orientation mapping through diffusion tensor imaging (DTI) is a powerful MRI-based technique for visualising white matter (WM) microstructure in the brain. Although DTI provides a robust way to measure fiber orientation, it has some limitations linked to the use of EPI read-outs and long diffusion encoding periods, including relatively low spatial resolution. Development of alternative MRI-based methods for fiber orientation mapping is therefore valuable, in part to allow validation of DTI results. In this study, we used the orientation dependence of R2* (1/T2*) and frequency difference measurements to generate three dimensional maps of the fiber orientation in WM from multi-echo gradient-echo (GE) images acquired from post mortem brain tissue samples oriented at multiple angles to B0. Through analytical derivation and numerical simulation, the relationships connecting variations in R2* and frequency difference values to the angle between the underlying WM fiber orientation and the direction of B0 were characterised. High resolution 3D fiber orientation maps (FOM) were then formed by comparing R2* and frequency difference data, acquired with the sample at multiple orientations to the field, to generalised models based on the derived expressions for the angular dependence of each parameter. By comparing the resulting GE-based FOM with DTI-based FOM from the same tissue sample, we demonstrate that fiber orientation mapping based on gradient echo MRI has the potential to become an important tool for investigating microstructure in brain tissue.

Cerebral microbleeds: their associated factors, radiologic findings, and clinical implications.

Cerebral microbleeds (CMBs) are tiny, round dark-signal lesions that are most often detected on gradient-echo MR images. CMBs consist of extravasations of blood components through fragile microvascular walls characterized by lipohyalinosis and surrounding macrophages. The prevalence of CMBs in elderly subjects with no history of cerebrovascular disease is around 5%, but is much higher in patients with ischemic or hemorrhagic stroke. Development of CMBs is closely related to various vascular risk factors; in particular, lobar CMBs are thought to be associated with cerebral amyloid angiopathy. The presence of CMBs has been hypothesized to reflect cerebral-hemorrhage-prone status in patients with hypertension or amyloid microangiopathy. Stroke survivors with CMBs have been consistently found to have an elevated risk of subsequent hemorrhagic stroke or an antithrombotic-related hemorrhagic complication, although studies have failed to establish a link between CMBs and hemorrhagic transformation after thrombolytic treatment. A large prospective study is required to clarify the clinical significance of CMBs and their utility in a decision-making index.