In vivo multi-slice mapping of myelin water content using T2* decay

Multicompartment imaging of the brain using a comprehensive MR imaging protocol

In this study, we describe a comprehensive 3D magnetic resonance imaging (MRI) protocol designed to assess major tissue and fluid components in the brain. The protocol comprises four different sequences: 1) magnetization transfer prepared Cones (MT-Cones) for two-pool MT modeling to quantify macromolecular content; 2) short-TR adiabatic inversion-recovery prepared Cones (STAIR-Cones) for myelin water imaging; 3) proton-density weighted Cones (PDw-Cones) for total water imaging; and 4) highly T2 weighted Cones (T2w-Cones) for free water imaging. By integrating these techniques, we successfully mapped key brain components-namely macromolecules, myelin water, intra/extracellular water, and free water-in ten healthy volunteers and five patients with multiple sclerosis (MS) using a 3T clinical scanner. Brain macromolecular proton fraction (MMPF), myelin water proton fraction (MWPF), intra/extracellular water proton fraction (IEWPF), and free water proton fraction (FWPF) values were generated in white matter (WM), grey matter (GM), and MS lesions. Excellent repeatability of the protocol was demonstrated with high intra-class correlation coefficient (ICC) values. In MS patients, the MMPF and MWPF values of the lesions and normal-appearing WM (NAWM) were significantly lower than those in normal WM (NWM) in healthy volunteers. Moreover, we observed significantly higher FWPF values in MS lesions compared to those in NWM and NAWM regions. This study demonstrates the capability of our technique to volumetrically map major brain components. The technique may have particular value in providing a comprehensive assessment of neuroinflammatory and neurodegenerative diseases of the brain.

Whole brain multiparametric mapping in two minutes using a dual-flip-angle stack-of-stars blipped multi-gradient-echo acquisition

A new MRI technique is presented for three-dimensional fast simultaneous whole brain mapping of myelin water fraction (MWF), T1, proton density (PD), R2*, magnetic susceptibility (QSM), and B1 transmit field (B1+). Phantom and human (N = 9) datasets were acquired using a dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory. Images were reconstructed using a subspace-based algorithm with a locally low-rank constraint. A novel joint-sparsity-constrained multicomponent T2*-T1 spectrum estimation (JMSE) algorithm is proposed to correct for the T1 saturation effect and B1+/B1- inhomogeneities in the quantification of MWF. A tissue-prior-based B1+ estimation algorithm was adapted for B1 correction in the mapping of T1 and PD. In the phantom study, measurements obtained at an acceleration factor (R) of 12 using prospectively under-sampled SOS showed good consistency (R2 > 0.997) with Cartesian reference for R2*/T1app/M0app. In the in vivo study, results of retrospectively under-sampled SOS with R = 6, 12, 18, showed good quality (structure similarity index measure > 0.95) compared with those of fully-sampled SOS. Besides, results of prospectively under-sampled SOS with R = 12 showed good consistency (intraclass correlation coefficient > 0.91) with Cartesian reference for T1/PD/B1+/MWF/QSM/R2*, and good reproducibility (coefficient of variation < 7.0 %) in the test-retest analysis for T1/PD/B1+/MWF/R2*. This study has demonstrated the feasibility of simultaneous whole brain multiparametric mapping with a two-minute scan using the DFA-mGRE SOS sequence, which may overcome a major obstacle for neurological applications of multiparametric MRI.

Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review

Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies.

JUST-Net: Jointly unrolled cross-domain optimization based spatio-temporal reconstruction network for accelerated 3D myelin water imaging

PURPOSE

We introduced a novel reconstruction network, jointly unrolled cross-domain optimization-based spatio-temporal reconstruction network (JUST-Net), aimed at accelerating 3D multi-echo gradient-echo (mGRE) data acquisition and improving the quality of resulting myelin water imaging (MWI) maps.

METHOD

An unrolled cross-domain spatio-temporal reconstruction network was designed. The main idea is to combine frequency and spatio-temporal image feature representations and to sequentially implement convolution layers in both domains. The k-space subnetwork utilizes shared information from adjacent frames, whereas the image subnetwork applies separate convolutions in both spatial and temporal dimensions. The proposed reconstruction network was evaluated for both retrospectively and prospectively accelerated acquisition. Furthermore, it was assessed in simulation studies and real-world cases with k-space corruptions to evaluate its potential for motion artifact reduction.

RESULTS

The proposed JUST-Net enabled highly reproducible and accelerated 3D mGRE acquisition for whole-brain MWI, reducing the acquisition time from fully sampled 15:23 to 2:22 min within a 3-min reconstruction time. The normalized root mean squared error of the reconstructed mGRE images increased by less than 4.0%, and the correlation coefficients for MWI showed a value of over 0.68 when compared to the fully sampled reference. Additionally, the proposed method demonstrated a mitigating effect on both simulated and clinical motion-corrupted cases.

CONCLUSION

The proposed JUST-Net has demonstrated the capability to achieve high acceleration factors for 3D mGRE-based MWI, which is expected to facilitate widespread clinical applications of MWI.

Conversion map from quantitative parameter mapping to myelin water fraction: comparison with R1·R2* and myelin water fraction in white matter

OBJECTIVE

To clarify the relationship between myelin water fraction (MWF) and R1⋅R2* and to develop a method to calculate MWF directly from parameters derived from QPM, i.e., MWF converted from QPM (MWFQPM).

MATERIALS AND METHODS

Subjects were 12 healthy volunteers. On a 3 T MR scanner, dataset was acquired using spoiled gradient-echo sequence for QPM. MWF and R1⋅R2* maps were derived from the multi-gradient-echo (mGRE) dataset. Volume-of-interest (VOI) analysis using the JHU-white matter (WM) atlas was performed. All the data in the 48 WM regions measured VOI were plotted, and quadratic polynomial approximations of each region were derived from the relationship between R1·R2* and the two-pool model-MWF. The R1·R2* map was converted to MWFQPM map. MWF atlas template was generated using converted to MWF from R1·R2* per WM region.

RESULTS

The mean MWF and R1·R2* values for the 48 WM regions were 11.96 ± 6.63%, and 19.94 ± 4.59 s-2, respectively. A non-linear relationship in 48 regions of the WM between MWF and R1·R2* values was observed by quadratic polynomial approximation (R2 ≥ 0.963, P < 0.0001).

DISCUSSION

MWFQPM map improved image quality compared to the mGRE-MWF map. Myelin water atlas template derived from MWFQPM may be generated with combined multiple WM regions.

Myelin water imaging at 0.55 T using a multigradient-echo sequence

PURPOSE

To investigate the prospects of a multigradient-echo (mGRE) acquisition for in vivo myelin water imaging at 0.55 T.

METHODS

Scans were performed on the brain of four healthy volunteers at 0.55 and 3 T, using a 3D mGRE sequence. The myelin water fraction (MWF) was calculated for both field strengths using a nonnegative least squares (NNLS) algorithm, implemented in the qMRLab suite. The quality of these maps as well as single-voxel fits were compared visually for 0.55 and 3 T.

RESULTS

The obtained MWF values at 0.55 T are consistent with previously reported ones at higher field strengths. The MWF maps are a considerable improvement over the ones at 3 T. Example fits show that 0.55 T data is better described by an exponential model than 3 T data, making the assumed multi-exponential model of the NNLS algorithm more accurate.

CONCLUSION

This first assessment shows that mGRE myelin water imaging at 0.55 T is feasible and has the potential to yield better results than at higher fields.

Rapid Whole-Knee Quantification of Cartilage Using T1, T2*, and TRAFF2 Mapping With Magnetic Resonance Fingerprinting

OBJECTIVE

Quantitative Magnetic Resonance Imaging (MRI) holds great promise for the early detection of cartilage deterioration. Here, a Magnetic Resonance Fingerprinting (MRF) framework is proposed for comprehensive and rapid quantification of T1, T2*, and TRAFF2 with whole-knee coverage.

METHODS

A MRF framework was developed to achieve quantification of Relaxation Along a Fictitious Field in the 2nd rotating frame of reference ( TRAFF2) along with T1 and T2*. The proposed sequence acquires 65 measurements of 25 high-resolution slices, interleaved with 7 inversion pulses and 40 RAFF2 trains, for whole-knee quantification in a total acquisition time of 3:25 min. Comparison with reference T1, T2*, and TRAFF2 methods was performed in phantom and in seven healthy subjects at 3 T. Repeatability (test-retest) with and without repositioning was also assessed.

RESULTS

Phantom measurements resulted in good agreement between MRF and the reference with mean biases of -54, 2, and 5 ms for T1, T2*, and TRAFF2, respectively. Complete characterization of the whole-knee cartilage was achieved for all subjects, and, for the femoral and tibial compartments, a good agreement between MRF and reference measurements was obtained. Across all subjects, the proposed MRF method yielded acceptable repeatability without repositioning ( R2 ≥ 0.94) and with repositioning ( R2 ≥ 0.57) for T1, T2*, and TRAFF2.

SIGNIFICANCE

The short scan time combined with the whole-knee coverage makes the proposed MRF framework a promising candidate for the early assessment of cartilage degeneration with quantitative MRI, but further research may be warranted to improve repeatability after repositioning and assess clinical value in patients.

Quantitative myelin water imaging using short TR adiabatic inversion recovery prepared echo-planar imaging (STAIR-EPI) sequence

Introduction

Numerous techniques for myelin water imaging (MWI) have been devised to specifically assess alterations in myelin. The biomarker employed to measure changes in myelin content is known as the myelin water fraction (MWF). The short TR adiabatic inversion recovery (STAIR) sequence has recently been identified as a highly effective method for calculating MWF. The purpose of this study is to develop a new clinical transitional myelin water imaging (MWI) technique that combines STAIR preparation and echo-planar imaging (EPI) (STAIR-EPI) sequence for data acquisition.

Methods

Myelin water (MW) in the brain has shorter T1 and T2 relaxation times than intracellular and extracellular water. In the proposed STAIR-EPI sequence, a short TR (e.g., ≤300 ms) together with an optimized inversion time enable robust long T1 water suppression with a wide range of T1 values [i.e., (600, 2,000) ms]. The EPI allows fast data acquisition of the remaining MW signals. Seven healthy volunteers and seven patients with multiple sclerosis (MS) were recruited and scanned in this study. The apparent myelin water fraction (aMWF), defined as the signal ratio of MW to total water, was measured in the lesions and normal-appearing white matter (NAWM) in MS patients and compared with those measured in the normal white matter (NWM) in healthy volunteers.

Results

As seen in the STAIR-EPI images acquired from MS patients, the MS lesions show lower signal intensities than NAWM do. The aMWF measurements for both MS lesions (3.6 ± 1.3%) and NAWM (8.6 ± 1.2%) in MS patients are significantly lower than NWM (10 ± 1.3%) in healthy volunteers (P < 0.001).

Discussion

The proposed STAIR-EPI technique, which can be implemented in MRI scanners from all vendors, is able to detect myelin loss in both MS lesions and NAWM in MS patients.

Microstructure-Informed Myelin Mapping (MIMM) from Gradient Echo MRI using Stochastic Matching Pursuit

Quantification of the myelin content of the white matter is important for studying demyelination in neurodegenerative diseases such as Multiple Sclerosis (MS), particularly for longitudinal monitoring. A novel noninvasive MRI method, called Microstructure-Informed Myelin Mapping (MIMM), is developed to quantify the myelin volume fraction (MVF) by utilizing a multi gradient echo sequence (mGRE) and a detailed biophysical model of tissue microstructure. Myelin is modeled as anisotropic negative susceptibility source based on the Hollow Cylindrical Fiber Model (HCFM), and iron as isotropic positive susceptibility source in the extracellular region. Voxels with a range of biophysical parameters are simulated to create a dictionary of MR echo time magnitude signals and total susceptibility values. MRI signals measured using a mGRE sequence are then matched voxel-by-voxel to the created dictionary to obtain the spatial distributions of myelin and iron. Three different MIMM versions are presented to deal with the fiber orientation dependent susceptibility effects of the myelin sheaths: a basic variation, which assumes fiber orientation is an unknown to fit, two orientation informed variations, which assume the fiber orientation distribution is available either from a separate diffusion tensor imaging (DTI) acquisition or from a DTI atlas based fiber orientation map. While all showed a significant linear correlation with the reference method based on T2-relaxometry (p < 0.0001), DTI orientation informed and atlas orientation informed variations reduced overestimation at white matter tracts compared to the basic variation. Finally, the implications and usefulness of attaining an additional iron susceptibility distribution map are discussed.

Highlights

novel stochastic matching pursuit algorithm called microstructure-informed myelin mapping (MIMM) is developed to quantify Myelin Volume Fraction (MVF) using Magnetic Resonance Imaging (MRI) and microstructural modeling.utilizes a detailed biophysical model to capture the susceptibility effects on both magnitude and phase to quantify myelin and iron.matter fiber orientation effects are considered for the improved MVF quantification in the major fiber tracts.acquired myelin and iron maps may be utilized to monitor longitudinal disease progress.

REUSED: A deep neural network method for rapid whole-brain high-resolution myelin water fraction mapping from extremely under-sampled MRI

Changes in myelination are a cardinal feature of brain development and the pathophysiology of several central nervous system diseases, including multiple sclerosis and dementias. Advanced magnetic resonance imaging (MRI) methods have been developed to probe myelin content through the measurement of myelin water fraction (MWF). However, the prolonged data acquisition and post-processing times of current MWF mapping methods pose substantial hurdles to their clinical implementation. Recently, fast steady-state MRI sequences have been implemented to produce high-spatial resolution whole-brain MWF mapping within ∼20 min. Despite the subsequent significant advances in the inversion algorithm to derive MWF maps from steady-state MRI, the high-dimensional nature of such inversion does not permit further reduction of the acquisition time by data under-sampling. In this work, we present an unprecedented reduction in the computation (∼30 s) and the acquisition time (∼7 min) required for whole-brain high-resolution MWF mapping through a new Neural Network (NN)-based approach, named NN-Relaxometry of Extremely Under-SamplEd Data (NN-REUSED). Our analyses demonstrate virtually similar accuracy and precision in derived MWF values using NN-REUSED compared to results derived from the fully sampled reference method. The reduction in the acquisition and computation times represents a breakthrough toward clinically practical MWF mapping.

In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods

Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.

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.

Making the invisible visible-ultrashort echo time magnetic resonance imaging: Technical developments and applications

Magnetic resonance imaging (MRI) uses a large magnetic field and radio waves to generate images of tissues in the body. Conventional MRI techniques have been developed to image and quantify tissues and fluids with long transverse relaxation times (T2s), such as muscle, cartilage, liver, white matter, gray matter, spinal cord, and cerebrospinal fluid. However, the body also contains many tissues and tissue components such as the osteochondral junction, menisci, ligaments, tendons, bone, lung parenchyma, and myelin, which have short or ultrashort T2s. After radio frequency excitation, their transverse magnetizations typically decay to zero or near zero before the receiving mode is enabled for spatial encoding with conventional MR imaging. As a result, these tissues appear dark, and their MR properties are inaccessible. However, when ultrashort echo times (UTEs) are used, signals can be detected from these tissues before they decay to zero. This review summarizes recent technical developments in UTE MRI of tissues with short and ultrashort T2 relaxation times. A series of UTE MRI techniques for high-resolution morphological and quantitative imaging of these short-T2 tissues are discussed. Applications of UTE imaging in the musculoskeletal, nervous, respiratory, gastrointestinal, and cardiovascular systems of the body are included.

Role of Demyelination in the Persistence of Neurological and Mental Impairments after COVID-19

Long-term neurological and mental complications of COVID-19, the so-called post-COVID syndrome or long COVID, affect the quality of life. The most persistent manifestations of long COVID include fatigue, anosmia/hyposmia, insomnia, depression/anxiety, and memory/attention deficits. The physiological basis of neurological and psychiatric disorders is still poorly understood. This review summarizes the current knowledge of neurological sequelae in post-COVID patients and discusses brain demyelination as a possible mechanism of these complications with a focus on neuroimaging findings. Numerous reviews, experimental and theoretical studies consider brain demyelination as one of the mechanisms of the central neural system impairment. Several factors might cause demyelination, such as inflammation, direct effect of the virus on oligodendrocytes, and cerebrovascular disorders, inducing myelin damage. There is a contradiction between the solid fundamental basis underlying demyelination as the mechanism of the neurological injuries and relatively little published clinical evidence related to demyelination in COVID-19 patients. The reason for this probably lies in the fact that most clinical studies used conventional MRI techniques, which can detect only large, clearly visible demyelinating lesions. A very limited number of studies use specific methods for myelin quantification detected changes in the white matter tracts 3 and 10 months after the acute phase of COVID-19. Future research applying quantitative MRI assessment of myelin in combination with neurological and psychological studies will help in understanding the mechanisms of post-COVID complications associated with demyelination.

Myelin water imaging using a short-TR adiabatic inversion-recovery (STAIR) sequence

PURPOSE

To develop a new myelin water imaging (MWI) technique using a short-TR adiabatic inversion-recovery (STAIR) sequence on a clinical 3T MR scanner.

METHODS

Myelin water (MW) in the brain has both a much shorter T₁ and a much shorter T₂ * than intracellular/extracellular water. A STAIR sequence with a short TR was designed to efficiently suppress long T₁ signals from intracellular/extracellular water, and therefore allow selective imaging of MW, which has a much shorter T₁ . Numerical simulation and phantom studies were performed to investigate the effectiveness of long T₁ signal suppression. TheT₂ * in white matter (WM) was measured with STAIR and compared with T₂ * measured with a conventional gradient recall echo in in vivo study. Four healthy volunteers and 4 patients with multiple sclerosis were recruited for qualitative and quantitative MWI. Apparent MW fraction was generated to compare MW in normal WM in volunteers to MW in lesions in patients with multiple sclerosis.

RESULTS

Both simulation and phantom studies showed that when TR was sufficiently short (eg, 250 ms), the STAIR sequence effectively suppressed long T₁ signals from tissues with a broad range of T₁ s using a single TR/TI combination. The volunteer study showed a short T₂ * of 9.5 ± 1.7 ms in WM, which is similar to reported values for MW. Lesions in patients with multiple sclerosis showed a significantly lower apparent MW fraction (4.5% ± 1.0%) compared with that of normal WM (9.2% ± 1.5%) in healthy volunteers (p < 0.05).

CONCLUSIONS

The STAIR sequence provides selective MWI in brain and can quantify reductions in MW content in patients with multiple sclerosis.

Reproducibility of rapid multi-parameter mapping at 3T and 7T with highly segmented and accelerated 3D-EPI

PURPOSE

Quantitative multi-parameter mapping (MPM) has been shown to provide good longitudinal and cross-sectional reproducibility for clinical research. Unfortunately, acquisition times (TAs) are typically infeasible for routine scanning at high resolutions.

METHODS

A fast whole-brain MPM protocol based on interleaved multi-shot 3D-EPI with controlled aliasing (SC-EPI) at 3T and 7T is proposed and compared with MPM using a standard spoiled gradient echo (FLASH) sequence. Four parameters (R₁ , PD, R 2 * $$ {R}_2^{\ast } $$ , and MTsat) were measured in less than 3 min at 1 mm isotropic resolution. Five subjects went through the same scanning sessions twice at each scanner. The intra-subject coefficient of variation (scan-rescan) (CoV) was estimated for each protocol and scanner to assess the longitudinal reproducibility.

RESULTS

At 3T, the CoV of SC-EPI ranged between 1.2%-4.8% for PD and R₁ , 2.8%-10.6% for R 2 * $$ {R}_2^{\ast } $$ and MTsat, which was comparable with FLASH (0.6%-4.9% for PD and R₁ , 2.6%-11.3% for R 2 * $$ {R}_2^{\ast } $$ and MTsat). At 7T, where the SC-EPI TA was reduced to ∼2 min, the CoV of SC-EPI (1.4%-10.6% for PD, R₁ , and R 2 * $$ {R}_2^{\ast } $$ ) was 1.2-2.4 times larger than the CoV of FLASH (1.0%-15%) and MTsat showed much higher variability across subjects. The SC-EPI-MPM protocol at 3T showed high reproducibility and yielded stable quantitative maps at a clinically feasible resolution and scan time, whereas at 7T, MT saturation homogeneity needs to be improved.

CONCLUSION

SC-EPI-based MPM is feasible as an additional MRI modality in clinical or population studies where the parameters offer great potential as biomarkers.

Challenges and Practical Solutions to MRI and Histology Matching and Measurements Using Available ImageJ Software Tools

Traditionally histology is the gold standard for the validation of imaging experiments. Matching imaging slices and histological sections and the precise outlining of corresponding tissue structures are difficult. Challenges are based on differences in imaging and histological slice thickness as well as tissue shrinkage and alterations after processing. Here we describe step-by-step instructions that might be used as a universal pathway to overlay MRI and histological images and for a correlation of measurements between imaging modalities. The free available (Fiji is just) ImageJ software tools were used for regions of interest transformation (ROIT) and alignment using a rat brain MRI as an example. The developed ROIT procedure was compared to a manual delineation of rat brain structures. The ROIT plugin was developed for ImageJ to enable an automatization of the image processing and structural analysis of the rodent brain.

Accelerated 3D myelin water imaging using joint spatio-temporal reconstruction

PURPOSE

To enable acceleration in 3D multi-echo gradient echo (mGRE) acquisition for myelin water imaging (MWI) by combining joint parallel imaging (JPI) and joint deep learning (JDL).

METHODS

We implemented a multistep reconstruction process using both advanced parallel imaging and deep learning network which can utilize joint spatiotemporal components between the multi-echo images to further accelerate 3D mGRE acquisition for MWI. In the first step, JPI was performed to estimate missing k-space lines. Next, JDL was implemented to reduce residual artifacts and produce high-fidelity reconstruction by using variable splitting optimization consisting of spatiotemporal denoiser block, data consistency block, and weighted average block. The proposed method was evaluated for MWI with 2D Cartesian uniform under-sampling for each echo, enabling scan times of up to approximately 2 min for 2 mm × 2 mm × 2 mm $2\ {\rm mm} \times 2\ {\rm mm} \times 2\ {\rm mm}$ 3D coverage.

RESULTS

The proposed method showed acceptable MWI quality with improved quantitative values compared to both JPI and JDL methods individually. The improved performance of the proposed method was demonstrated by the low normalized mean-square error and high-frequency error norm values of the reconstruction with high similarity to the fully sampled MWI.

CONCLUSION

Joint spatiotemporal reconstruction approach by combining JPI and JDL can achieve high acceleration factors for 3D mGRE-based MWI.

R2* relaxometry analysis for mapping of white matter alteration in Parkinson's disease with mild cognitive impairment

•

R2* relaxometry analysis combined with QSM revealed detail of WM alteration in PD-MCI.

•

R2* relaxometry analysis can detect slight demyelination in PD-MCI.

•

R2* value shows potential for early evaluation of cognitive decline in PD.

Background

R2* relaxometry analysis combined with quantitative susceptibility mapping (QSM), which has high sensitivity to iron deposition, can distinguish microstructural changes of the white matter (WM) and iron deposition, thereby providing a sensitive and biologically specific measure of the WM owing to the changes in myelin and its surrounding environment. This study aimed to explore the microstructural WM alterations associated with cognitive impairment in patients with Parkinson’s disease (PD) using R2* relaxometry analysis combined with QSM.

Materials and methods

We enrolled 24 patients with PD and mild cognitive impairment (PD-MCI), 22 patients with PD and normal cognition (PD-CN), and 19 age- and sex-matched healthy controls (HC). All participants underwent Montreal Cognitive Assessment (MoCA) and brain magnetic resonance imaging, including structural three-dimensional T1-weighted images and multiple spoiled gradient echo sequence (mGRE). The R2* and susceptibility maps were estimated from the multiple magnitude images of mGRE. The susceptibility maps were used for verifying iron deposition in the WM. The voxel-based R2* of the entire WM and its correlation with cognitive performance were analyzed.

Results

In the voxel-based group comparisons, the R2* in the PD-MCI group was lower in some WM regions, including the corpus callosum, than R2* in the PD-CN and HC groups. The mean susceptibility values in almost all brain regions were negative and close-to-zero values, indicating no detectable paramagnetic iron deposition in the WM of all subjects. There was a significant positive correlation between R2* and MoCA in some regions of the WM, mainly the corpus callosum and left hemisphere.

Conclusion

R2* relaxometry analysis for WM microstructural changes provided further biologic insights on demyelination and changes in the surrounding environment, supported by the QSM results demonstrating no iron existence. This analysis highlighted the potential for the early evaluation of cognitive decline in patients with PD.

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.

Insights into human cerebral white matter maturation and degeneration across the adult lifespan

White matter (WM) microstructural properties change across the adult lifespan and with neuronal diseases. Understanding microstructural changes due to aging is paramount to distinguish them from neuropathological changes. Conducted on a large cohort of 147 cognitively unimpaired subjects, spanning a wide age range of 21 to 94 years, our study evaluated sex- and age-related differences in WM microstructure. Specifically, we used diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) indices, sensitive measures of myelin and axonal density in WM, and myelin water fraction (MWF), a measure of the fraction of the signal of water trapped within the myelin sheets, to probe these differences. Furthermore, we examined regional correlations between MWF and DTI indices to evaluate whether the DTI metrics provide information complementary to MWF. While sexual dimorphism was, overall, nonsignificant, we observed region-dependent differences in MWF, that is, myelin content, and axonal density with age and found that both exhibit nonlinear, but distinct, associations with age. Furthermore, DTI indices were moderately correlated with MWF, indicating their good sensitivity to myelin content as well as to other constituents of WM tissue such as axonal density. The microstructural differences captured by our MRI metrics, along with their weak to moderate associations with MWF, strongly indicate the potential value of combining these outcome measures in a multiparametric approach. Furthermore, our results support the last-in-first-out and the gain-predicts-loss hypotheses of WM maturation and degeneration. Indeed, our results indicate that the posterior WM regions are spared from neurodegeneration as compared to anterior regions, while WM myelination follows a temporally symmetric time course across the adult life span.

Myelin-Weighted Imaging Presents Reduced Apparent Myelin Water in Patients with Alzheimer’s Disease

The purpose of this study was to investigate myelin loss in both AD and mild cognitive impairment (MCI) patients with a new myelin water mapping technique within reasonable scan time and evaluate the clinical relevance of the apparent myelin water fraction (MWF) values by assessing the relationship between decreases in myelin water and the degree of memory decline or aging. Twenty-nine individuals were assigned to the cognitively normal (CN) elderly group, 32 participants were assigned to the MCI group, and 31 patients were assigned to the AD group. A 3D visualization of the short transverse relaxation time component (ViSTa)-gradient and spin-echo (GraSE) sequence was developed to map apparent MWF. Then, the MWF values were compared between the three participant groups and was evaluated the relationship with the degree of memory loss. The AD group showed a reduced apparent MWF compared to the CN and MCI groups. The largest AUC (area under the curve) value was in the corpus callosum and used to classify the CN and AD groups using the apparent MWF. The ViSTa-GraSE sequence can be a useful tool to map the MWF in a reasonable scan time. Combining the MWF in the corpus callosum with the detection of atrophy in the hippocampus can be valuable for group classification.

Macromolecular Proton Fraction as a Myelin Biomarker: Principles, Validation, and Applications

Macromolecular proton fraction (MPF) is a quantitative MRI parameter describing the magnetization transfer (MT) effect and defined as a relative amount of protons bound to biological macromolecules with restricted molecular motion, which participate in magnetic cross-relaxation with water protons. MPF attracted significant interest during past decade as a biomarker of myelin. The purpose of this mini review is to provide a brief but comprehensive summary of MPF mapping methods, histological validation studies, and MPF applications in neuroscience. Technically, MPF maps can be obtained using a variety of quantitative MT methods. Some of them enable clinically reasonable scan time and resolution. Recent studies demonstrated the feasibility of MPF mapping using standard clinical MRI pulse sequences, thus substantially enhancing the method availability. A number of studies in animal models demonstrated strong correlations between MPF and histological markers of myelin with a minor influence of potential confounders. Histological studies validated the capability of MPF to monitor both demyelination and re-myelination. Clinical applications of MPF have been mainly focused on multiple sclerosis where this method provided new insights into both white and gray matter pathology. Besides, several studies used MPF to investigate myelin role in other neurological and psychiatric conditions. Another promising area of MPF applications is the brain development studies. MPF demonstrated the capabilities to quantitatively characterize the earliest stage of myelination during prenatal brain maturation and protracted myelin development in adolescence. In summary, MPF mapping provides a technically mature and comprehensively validated myelin imaging technology for various preclinical and clinical neuroscience applications.

Improved Multi-Echo Gradient-Echo-Based Myelin Water Fraction Mapping Using Dimensionality Reduction

Multi-echo gradient-echo (mGRE)-based myelin water fraction (MWF) mapping is a promising myelin water imaging (MWI) modality but is vulnerable to noise and artifact corruption. The linear dimensionality reduction (LDR) method has recently shown improvements with regard to these challenges. However, the magnitude value based low rank operators have been shown to misestimate the MWF for regions with [Formula: see text] anisotropy. This paper presents a nonlinear dimensionality reduction (NLDR) method to estimate the MWF map better by encouraging nonlinear low dimensionality of mGRE signal sources. Specifically, we implemented a fully connected deep autoencoder to extract the low-dimensional features of complex-valued signals and incorporated a sparse regularization to separate the anomaly sources that do not reside in the low-dimensional manifold. Simulations and in vivo experiments were performed to evaluate the accuracy of the MWF map under various situations. The proposed NLDR-based MWF improves the accuracy of the MWF map over the conventional nonlinear least-squares method and the LDR-based MWF and maintains robustness against noise and artifact corruption.

Brain myelin water fraction is associated with APOE4 allele status in patients with cognitive impairment

BACKGROUND AND PURPOSE

Apolipoprotein E4 (APOE4) is a major genetic risk factor for Alzheimer's disease. However, the effect of APOE4 status on myelin remains unclear. This study investigated the effect of APOE4 on myelin content in cognitively impaired individuals using T2* gradient echo (GRE)-based myelin water fraction (MWF) imaging.

METHODS

Between August 2017 and January 2019, we evaluated 39 cognitively impaired patients (median age, 75 years; male:female = 8:31; Alzheimer's disease: mild cognitive impairment = 11:28). We obtained brain MWF values from white matter hyperintensities (WMHs) and normal-appearing white matter (NAWM). Linear regression analysis was performed to investigate the relationship between the APOE4 status and MWF and cognitive function and MWF.

RESULTS

Among the 39 cognitively impaired patients, nine (23.1%) were APOE4 carriers and 30 (76.9%) were noncarriers. APOE4 carriers had a lower hippocampal volume than noncarriers (p = .045), but other brain volume parameters were not differed. After age adjustment, the APOE4 status was significantly associated with reduced MWF in NAWM (β = -0.310 per allele; p = .049) but not in WMH (β = -0.258 per allele; p = .113). After age adjustment, MWF in NAWM was significantly associated with Mini-Mental State Examination score (β = 0.313, p = .031).

CONCLUSIONS

T2* GRE-based MWF imaging can reveal myelin loss, particularly in NAWM, in cognitively impaired patients among APOE4 carriers. In vivo MWF in NAWM might be a novel imaging marker of Alzheimer's disease, for clarifying the interactions between the white matter and cognitive dysfunction with respect to the APOE4 status.

Direct imaging of white matter ultrashort T2∗ components at 7 Tesla

PURPOSE

To demonstrate direct imaging of the white matter ultrashort T₂^∗ components at 7 Tesla using inversion recovery (IR)-enhanced ultrashort echo time (UTE) MRI. To investigate its characteristics, potentials and limitations, and to establish a clinical protocol.

MATERIAL AND METHODS

The IR UTE technique suppresses long T₂^∗ signals within white matter by using adiabatic inversion in combination with dual-echo difference imaging. Artifacts arising at 7 T from long T₂^∗ scalp fat components were reduced by frequency shifting the IR pulse such that those frequencies were inverted likewise. For 8 healthy volunteers, the T₂^∗ relaxation times of white matter were then quantified. In 20 healthy volunteers, the UTE difference and fraction contrast were evaluated. Finally, in 6 patients with multiple sclerosis (MS), the performance of the technique was assessed.

RESULTS

A frequency shift of -1.2 ppm of the IR pulse (i.e. towards the fat frequency) provided a good suppression of artifacts. With this, an ultrashort compartment of (68 ± 6) % with a T₂^∗ time of (147 ± 58) μs was quantified with a chemical shift of (-3.6 ± 0.5) ppm from water. Within healthy volunteers' white matter, a stable ultrashort T₂^∗ fraction contrast was calculated. For the MS patients, a significant fraction reduction in the identified lesions as well as in the normal-appearing white matter was observed.

CONCLUSIONS

The quantification results indicate that the observed ultrashort components arise primarily from myelin tissue. Direct IR UTE imaging of the white matter ultrashort T₂^∗ components is thus feasible at 7 T with high quantitative inter-subject repeatability and good detection of signal loss in MS.

Assessing the differential sensitivities of wave-CAIPI ViSTa myelin water fraction and magnetization transfer saturation for efficiently quantifying tissue damage in MS

BACKGROUND

Wave-CAIPI Visualization of Short Transverse relaxation time component (ViSTa) is a recently developed, short-T₁-sensitized MRI method for fast quantification of myelin water fraction (MWF) in the human brain. It represents a promising technique for the evaluation of subtle, early signals of demyelination in the cerebral white matter of multiple sclerosis (MS) patients. Currently however, few studies exist that robustly assess the utility of ViSTa MWF measures of myelin compared to more conventional MRI measures of myelin in the brain of MS patients. Moreover, there are no previous studies evaluating the sensitivity of ViSTa MWF for the non-invasive detection of subtle tissue damage in both normal-appearing white matter (NAWM) and white matter lesions of MS patients. As a result, a central purpose of this study was to systematically evaluate the relationship between myelin sensitivity of T₁-based ViSTa MWF mapping and a more generally recognized metric, Magnetization Transfer Saturation (MT_sat), in healthy control and MS brain white matter.

METHODS

ViSTa MWF and MT_sat values were evaluated in automatically-classified normal appearing white matter (NAWM), white matter (WM) lesion tissue, cortical gray matter, and deep gray matter of 29 MS patients and 10 healthy controls using 3T MRI. MWF and MT _sat were also assessed in a tract-specific manner using the Johns Hopkins University WM atlas. MRI-derived measures of cerebral myelin content were uniquely compared by employing non-normal distribution-specific measures of median, interquartile range and skewness. Separate analyses of variance were applied to test tissue-specific differences in MT_sat and ViSTa MWF distribution metrics. Non-parametric tests were utilized when appropriate. All tests were corrected for multiple comparisons using the False Discovery Rate method at the level, α=0.05.

RESULTS

Differences in whole NAWM MS tissue damage were detected with a higher effect size when using ViSTa MWF (q = 0.0008; ƞ² = 0.34) compared to MT_sat (q = 0.02; ƞ²= 0.24). We also observed that, as a possible measure of WM pathology, ViSTa-derived NAWM MWF voxel distributions of MS subjects were consistently skewed towards lower MWF values, while MT_sat voxel distributions showed reduced skewness values. We further identified tract-specific reductions in mean ViSTa MWF of MS patients compared to controls that were not observed with MT_sat. However, MT_sat (q = 1.4 × 10^-21; ƞ² = 0.88) displayed higher effect sizes when differentiating NAWM and MS lesion tissue. Using regression analysis at the group level, we identified a linear relationship between MT_sat and ViSTa MWF in NAWM (R² = 0.46; p = 7.8 × 10^-4) lesions (R² = 0.30; p = 0.004), and with all tissue types combined (R² = 0.71; p = 8.4 × 10^-45). The linear relationship was also observed in most of the WM tracts we investigated. ViSTa MWF in NAWM of MS patients correlated with both disease duration (p = 0.02; R² = 0.27) and WM lesion volume (p = 0.002; R² = 0.34).

CONCLUSION

Because ViSTa MWF and MT_sat metrics exhibit differential sensitivities to tissue damage in MS white matter, they can be collected in combination to provide an efficient, comprehensive measure of myelin water and macromolecular pool proton signals. These complementary measures may offer a more sensitive, non-invasive biopsy of early precursor signals in NAWM that occur prior to lesion formation. They may also aid in monitoring the efficacy of remyelination therapies.

Library-driven approach for fast implementation of the voxel spread function to correct magnetic field inhomogeneity artifacts for gradient-echo sequences

PURPOSE

Previously developed Voxel Spread Function (VSF) method (Yablonskiy, et al, MRM, 2013;70:1283) provides solution to correct artifacts induced by macroscopic magnetic field inhomogeneity in the images obtained by multi-Gradient-Recalled-Echo (mGRE) techniques. The goal of this study was to develop a library-driven approach for fast VSF implementation.

METHODS

The VSF approach describes the contribution of the magnetic field inhomogeneity effects on the mGRE signal decay in terms of the F-function calculated from mGRE phase and magnitude images. A pre-calculated library accounting for a variety of background field gradients caused by magnetic field inhomogeneity was used herein to speed up the calculation of F-function. Quantitative R2* maps from the mGRE data collected from two healthy volunteers were generated using the library as validation.

RESULTS

As compared with direct calculation of the F-function based on a voxel-wise approach, the new library-driven method substantially reduces computational time from several hours to few minutes, while, at the same time, providing similar accuracy of R2* mapping.

CONCLUSION

The new procedure proposed in this study provides a fast post-processing algorithm that can be incorporated in the quantitative analysis of mGRE data to account for background field inhomogeneity artifacts, thus can facilitate the applications of mGRE-based quantitative techniques in clinical practices.

Inversion Recovery Ultrashort TE MR Imaging of Myelin is Significantly Correlated with Disability in Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE

MR imaging has been widely used for the noninvasive evaluation of MS. Although clinical MR imaging sequences are highly effective in showing focal macroscopic tissue abnormalities in the brains of patients with MS, they are not specific to myelin and correlate poorly with disability. We investigated direct imaging of myelin using a 2D adiabatic inversion recovery ultrashort TE sequence to determine its value in assessing disability in MS.

MATERIALS AND METHODS

The 2D inversion recovery ultrashort TE sequence was evaluated in 14 healthy volunteers and 31 patients with MS. MPRAGE and T2-FLAIR images were acquired for comparison. Advanced Normalization Tools were used to correlate inversion recovery ultrashort TE, MPRAGE, and T2-FLAIR images with disability assessed by the Expanded Disability Status Scale.

RESULTS

Weak correlations were observed between normal-appearing white matter volume (R = -0.03, P = .88), lesion load (R = 0.22, P = .24), and age (R = 0.14, P = .44), and disability. The MPRAGE signal in normal-appearing white matter showed a weak correlation with age (R = -0.10, P = .49) and disability (R = -0.19, P = .31). The T2-FLAIR signal in normal-appearing white matter showed a weak correlation with age (R = 0.01, P = .93) and disability (R = 0.13, P = .49). The inversion recovery ultrashort TE signal was significantly negatively correlated with age (R = -0.38, P = .009) and disability (R = -0.44; P = .01).

CONCLUSIONS

Direct imaging of myelin correlates with disability in patients with MS better than indirect imaging of long-T2 water in WM using conventional clinical sequences.

Myelination may be impaired in neonates following birth asphyxia

•

Myelination is a developmental process that intensifies after birth during the first years of life.

•

We used a T2* mapping sequence to assess myelination in healthy and critically ill neonates with neonatal encephalopathy.

•

Birth asphyxia, in addition to causing the previously well-described direct injury to the brain, may impair myelination.

Background

Myelination is a developmental process that begins during the end of gestation, intensifies after birth over the first years of life, and continues well into adolescence. Any event leading to brain injury around the time of birth and during the perinatal period, such as birth asphyxia, may impair this critical process. Currently, the impact of such brain injury related to birth asphyxia on the myelination process is unknown.

Objective

To assess the myelination pattern over the first month of life in neonates with neonatal encephalopathy (NE) developing brain injury, compared to neonates without injury (i.e., healthy neonates and neonates with NE who do not develop brain injury).

Methods

Brain magnetic resonance imaging (MRI) was performed around day of life 2, 10, and 30 in healthy neonates and near-term/term neonates with NE who were treated with hypothermia. We evaluated myelination in various regions of interest using a T2* mapping sequence. In each region of interest, we compared the T2* values of the neonates with NE with brain injury to the values of the neonates without injury, according to the MRI timing, by using a repeated measures generalized linear mixed model.

Results

We obtained 74 MRI scans over the first month of life for 6 healthy neonates, 17 neonates with NE who were treated with hypothermia and did not develop brain injury, and 16 neonates with NE who were treated with hypothermia and developed brain injury. The T2* values significantly increased in the neonates with NE who developed injury in the posterior limbs of the internal capsule (day 2: p < 0.001; day 10: p < 0.001; and day 30: p < 0.001), the thalami (day 2: p = 0.001; day 10: p = 0.006; and day 30: p = 0.016), the lentiform nuclei (day 2: p = 0.005), the anterior white matter (day 2: p = 0.002; day 10: p = 0.006; and day 30: p = 0.002), the posterior white matter (day 2: p = 0.001; day 10: p = 0.008; and day 30: p = 0.03), the genu of the corpus callosum (day 2: p = 0.01; and day 10: p = 0.006), and the optic radiations (day 30: p < 0.001).

Conclusion

In the neonates with NE who were treated with hypothermia and developed brain injury, birth asphyxia impaired myelination in the regions that are myelinated at birth or soon after birth (the posterior limbs of internal capsule, the thalami, and the lentiform nuclei), in the regions where the myelination process begins only after the perinatal period (optic radiations), and in the regions where this process does not occur until months after birth (anterior/posterior white matter), which suggests that birth asphyxia, in addition to causing the previously well-described direct injury to the brain, may impair myelination.

Whole Brain Myelin Water Mapping in One Minute Using Tensor Dictionary Learning With Low-Rank Plus Sparse Regularization

The quantification of myelin water content in the brain can be obtained by the multi-echo [Formula: see text] weighted images ( [Formula: see text]WIs). To accelerate the long acquisition, a novel tensor dictionary learning algorithm with low-rank and sparse regularization (TDLLS) is proposed to reconstruct the [Formula: see text]WIs from the undersampled data. The proposed algorithm explores the local and nonlocal similarity and the global temporal redundancy in the real and imaginary parts of the complex relaxation signals. The joint application of the low-rank constraints on the dictionaries and the sparse constraints on the core coefficient tensors improves the performance of the tensor-based recovery. Parallel imaging is incorporated into the TDLLS algorithm (pTDLLS) for further acceleration. A pulse sequence is proposed to prospectively undersample the Ky-t space to obtain the whole brain high-quality myelin water fraction (MWF) maps within 1 minute at an undersampling rate (R) of 6.

Brain ultrashort T2 component imaging using a short TR adiabatic inversion recovery prepared dual-echo ultrashort TE sequence with complex echo subtraction (STAIR-dUTE-ES)

Long T₂ water contamination is a major challenge with direct in vivo UTE imaging of ultrashort T₂ components in the brain since water contributes most of the signal detected from white and gray matter. The Short TR Adiabatic Inversion Recovery prepared Ultrashort TE (STAIR-UTE) sequence can significantly suppress water signals and simultaneously image ultrashort T₂ components. However, the TR used may not be sufficiently short to allow the STAIR preparation to completely suppress all the water signals in the brain due to specific absorption rate (SAR) limitations on clinical MR scanners. In this study, we describe a STAIR prepared dual-echo UTE sequence with complex Echo Subtraction (STAIR-dUTE-ES) which improves water suppression for selective ultrashort T₂ imaging compared with that achieved with the STAIR-UTE sequence. Numerical simulations showed that the STAIR-dUTE-ES technique can effectively suppress water signals and allow accurate quantification of ultrashort T₂ protons. Volunteer and Multiple Sclerosis (MS) patient studies demonstrated the feasibility of the STAIR-dUTE-ES technique for selective imaging and quantification of ultrashort T₂ components in vivo. A significantly lower mean UltraShort T₂ Proton Fraction (USPF) was found in lesions in MS patients (5.7 ± 0.7%) compared with that in normal white matter of healthy volunteers (8.9 ± 0.6%). The STAIR-dUTE-ES sequence provides robust water suppression for volumetric imaging and quantitation of ultrashort T₂ component. The reduced USPF in MS lesions shows the clinical potential of the sequence for diagnosis and monitoring treatment in MS.

Parsimonious discretization for characterizing multi-exponential decay in magnetic resonance

We address the problem of analyzing noise-corrupted magnetic resonance transverse decay signals as a superposition of underlying independently decaying monoexponentials of positive amplitude. First, we indicate the manner in which this is an ill-conditioned inverse problem, rendering the analysis unstable with respect to noise. Second, we define an approach to this analysis, stabilized solely by the nonnegativity constraint without regularization. This is made possible by appropriate discretization, which is coarser than that often used in practice. Thirdly, we indicate further stabilization by inspecting the plateaus of cumulative distributions. We demonstrate our approach through analysis of simulated myelin water fraction measurements, and compare the accuracy with more conventional approaches. Finally, we apply our method to brain imaging data obtained from a human subject, showing that our approach leads to maps of the myelin water fraction which are much more stable with respect to increasing noise than those obtained with conventional approaches.

Myelin water fraction estimation using small-tip fast recovery MRI

PURPOSE

To demonstrate the feasibility of an optimized set of small-tip fast recovery (STFR) MRI scans for rapidly estimating myelin water fraction (MWF) in the brain.

METHODS

We optimized a set of STFR scans to minimize the Cramér-Rao Lower Bound of MWF estimates. We evaluated the RMSE of MWF estimates from the optimized scans in simulation. We compared STFR-based MWF estimates (both modeling exchange and not modeling exchange) to multi-echo spin echo (MESE)-based estimates. We used the optimized scans to acquire in vivo data from which a MWF map was estimated. We computed the STFR-based MWF estimates using PERK, a recently developed kernel regression technique, and the MESE-based MWF estimates using both regularized non-negative least squares (NNLS) and PERK.

RESULTS

In simulation, the optimized STFR scans led to estimates of MWF with low RMSE across a range of tissue parameters and across white matter and gray matter. The STFR-based MWF estimates that modeled exchange compared well to MESE-based MWF estimates in simulation. When the optimized scans were tested in vivo, the MWF map that was estimated using a 3-compartment model with exchange was closer to the MESE-based MWF map.

CONCLUSIONS

The optimized STFR scans appear to be well suited for estimating MWF in simulation and in vivo when we model exchange in training. In this case, the STFR-based MWF estimates are close to the MESE-based estimates.

Probing myelin content of the human brain with MRI: A review

Rapid and efficient transmission of electric signals among neurons of vertebrates is ensured by myelin-insulating sheaths surrounding axons. Human cognition, sensation, and motor functions rely on the integrity of these layers, and demyelinating diseases often entail serious cognitive and physical impairments. Magnetic resonance imaging radically transformed the way these disorders are monitored, offering an irreplaceable tool to noninvasively examine the brain structure. Several advanced techniques based on MRI have been developed to provide myelin-specific contrasts and a quantitative estimation of myelin density in vivo. Here, the vast offer of acquisition strategies developed to date for this task is reviewed. Advantages and pitfalls of the different approaches are compared and discussed.

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.

Myelin Imaging in Human Brain Using a Short Repetition Time Adiabatic Inversion Recovery Prepared Ultrashort Echo Time (STAIR-UTE) MRI Sequence in Multiple Sclerosis

Background Water signal contamination is a major challenge for direct ultrashort echo time (UTE) imaging of myelin in vivo because water contributes most of the signals detected in white matter. Purpose To validate a new short repetition time (TR) adiabatic inversion recovery (STAIR) prepared UTE (STAIR-UTE) sequence designed to suppress water signals and to allow imaging of ultrashort T2 protons of myelin in white matter using a clinical 3-T scanner. Materials and Methods In this prospective study, an optimization framework was used to obtain the optimal inversion time for nulling water signals using STAIR-UTE imaging at different TRs. Numeric simulation and phantom studies were performed. Healthy volunteers and participants with multiple sclerosis (MS) underwent MRI between November 2018 and October 2019 to compare STAIR-UTE and a clinical T2-weighted fluid-attenuated inversion recovery sequence for assessment of MS lesions. UTE measures of myelin were also performed to allow comparison of signals in lesions and with those in normal-appearing white matter (NAWM) in patients with MS and in normal white matter (NWM) in healthy volunteers. Results Simulation and phantom studies both suggest that the proposed STAIR-UTE technique can effectively suppress long T2 tissues with a broad range of T1s. Ten healthy volunteers (mean age, 33 years ± 8 [standard deviation]; six women) and 10 patients with MS (mean age, 51 years ± 16; seven women) were evaluated. The three-dimensional STAIR-UTE sequence effectively suppressed water components in white matter and selectively imaged myelin, which had a measured T2* value of 0.21 msec ± 0.04 in the volunteer study. A much lower mean UTE measure of myelin proton density was found in MS lesions (3.8 mol/L ± 1.5), and a slightly lower mean UTE measure was found in NAWM (7.2 mol/L ± 0.8) compared with that in NWM (8.0 mol/L ± 0.8) in the healthy volunteers (P < .001 for both comparisons). Conclusion The short repetition time adiabatic inversion recovery-prepared ultrashort echo time sequence provided efficient water signal suppression for volumetric imaging of myelin in the brain and showed excellent myelin signal contrast as well as marked ultrashort echo time signal reduction in multiple sclerosis lesions and a smaller reduction in normal-appearing white matter compared with normal white matter in volunteers. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Messina and Port in this issue.

Sensitivity to myelin using model-free analysis of the water resonance line-shape in postmortem mouse brain

PURPOSE

Dysmyelinating diseases are characterized by abnormal myelin formation and function. Such microstructural abnormalities in myelin have been demonstrated to produce measurable effects on the MR signal. This work examines these effects on measurements of voxel-wise, high-resolution water spectra acquired using a 3D echo-planar spectroscopic imaging (EPSI) pulse sequence from both postmortem fixed control mouse brains and a dysmyelination mouse brain model.

METHODS

Perfusion fixed, resected control (n = 5) and shiverer (n = 4) mouse brains were imaged using 3D-EPSI with 100 µm isotropic resolution. The free induction decay (FID) was sampled every 2.74 ms over 192 echoes, for a total sampling duration of 526.08 ms. Voxel-wise FIDs were Fourier transformed to produce water spectra with 1.9 Hz resolution. Spectral asymmetry was computed and compared between the two tissue types.

RESULTS

The water resonance is more asymmetrically broadened in the white matter of control mouse brain compared with dysmyelinated white matter. In control brain, this is modulated by and consistent with previously reported orientationally dependent effects of white matter relative to B₀ . Similar sensitivity to orientation is observed in dysmyelinated white matter as well; however, the magnitude of the resonance asymmetry is much lower across all directions.

CONCLUSION

Results demonstrate that components of the spectra are specifically differentially affected by myelin concentration. This suggests that water proton spectra may be sensitive to the presence of myelin, and as such, could serve as a MRI-based biomarker of dysmyelinating disease, free of mathematical models.

Artificial neural network for multi-echo gradient echo-based myelin water fraction estimation

PURPOSE

To demonstrate robust myelin water fraction (MWF) mapping using an artificial neural network (ANN) with multi-echo gradient-echo (GRE) signal.

METHODS

Multi-echo gradient-echo signals simulated with a three-pool exponential model were used to generate the training data set for the ANN, which was designed to yield the MWF. We investigated the performance of our proposed ANN for various conditions using both numerical simulations and in vivo data. Simulations were conducted with various SNRs to investigate the performance of the ANN. In vivo data with high spatial resolutions were applied in the analyses, and results were compared with MWFs derived by the nonlinear least-squares algorithm using a complex three-pool exponential model.

RESULTS

The network results for the simulations show high accuracies against noise compared with nonlinear least-squares MWFs: RMS-error value of 5.46 for the nonlinear least-squares MWF and 3.56 for the ANN MWF at an SNR of 150 (relative gain = 34.80%). These effects were also found in the in vivo data, with reduced SDs in the region-of-interest analyses. These effects of the ANN demonstrate the feasibility of acquiring high-resolution myelin water images.

CONCLUSION

The simulation results and in vivo data suggest that the ANN facilitates more robust MWF mapping in multi-echo gradient-echo sequences compared with the conventional nonlinear least-squares method.

Three-dimensional fast single-point macromolecular proton fraction mapping of the human brain at 0.5 Tesla

Fast single-point macromolecular proton fraction (MPF) mapping is a recent magnetic resonance imaging (MRI) method enabling quantitative assessment of myelin content in neural tissues. To date, the reported technical implementations of MPF mapping utilized high-field MRI equipment (1.5 T or higher), while low-field applications might pose challenges due to signal-to-noise ratio (SNR) limitations and short T₁ . This study aimed to evaluate the feasibility of MPF mapping of the human brain at 0.5 T. The three-dimensional MPF mapping protocol was implemented according to the single-point synthetic-reference method, which includes three spoiled gradient-echo sequences providing proton density, T₁ , and magnetization transfer contrast weightings. Whole-brain MPF maps were obtained from three healthy volunteers with spatial resolution of 1.5×1.5×2 mm³ and the total scan time of 19 minutes. MPF values were measured in a series of white and gray matter structures and compared with literature data for 3 T magnetic field. MPF maps enabled high contrast between white and gray matter with notable insensitivity to paramagnetic effects in iron-rich structures, such as globus pallidus, substantia nigra, and dentate nucleus. MPF values at 0.5 T appeared in close agreement with those at 3 T. This study demonstrates the feasibility of fast MPF mapping with low-field MRI equipment and the independence of brain MPF values of magnetic field. The presented results confirm the utility of MPF as an absolute scale for MRI-based myelin content measurements across a wide range of magnetic field strengths and extend the applicability of fast MPF mapping to inexpensive low-field MRI hardware.

Blind Source Separation for Myelin Water Fraction Mapping Using Multi-Echo Gradient Echo Imaging

In conventional gradient-echo myelin water imaging (GRE-MWI), myelin water fraction (MWF) is estimated by fitting the multi-echo gradient recalled echo (mGRE) signal to a pre-assumed numerical model (e.g., multi-component exponential curves or three component exponential curves). However, in mGRE, imaging artifacts (e.g., voxel spread function and physiological noise) and noise render the signal to deviate from the numerical model, leading to misfit of the model parameters. Here, as an alternative to the model-based GRE-MWI, a blind source separation (BSS) technique for the separation of multi-exponential mGRE signal is proposed. Among the various BSS techniques, a modified robust principal component analysis (rPCA) is presented to separate signal sources by enforcing the data-driven properties such as "low rankness" and "sparsity." Considering the signal evolution of T₂^∗ relaxation (i.e., non-negative exponential decay), low rankness of exponential decay was enforced by nonnegative matrix factorization (NMF) and hankelization. This method provides the separation of slow-decaying, fast-decaying exponential components and artifact components from mGRE images. After the separation, MWF map is reconstructed as the ratio of the fast-decaying component to the total decaying components. The proposed method was demonstrated in numerical simulations and in vivo scans. The method provided a robust estimation of MWF in the presence of statistical noise and imaging artifacts.

Influence of 7T GRE-MRI Signal Compartment Model Choice on Tissue Parameters

Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders. Ultra-high field magnetic resonance imaging (MRI) data obtained using a multi-echo gradient echo sequence have been shown to contain information on myelin, axonal, and extracellular compartments in tissue. Quantitative assessment of water fraction, relaxation time (T₂*), and frequency shift using multi-compartment models has been shown to be useful in studying white matter properties via specific tissue parameters. It remains unclear how tissue parameters vary with model selection based on 7T multiple echo time gradient-recalled echo (GRE) MRI data. We applied existing signal compartment models to the corpus callosum and investigated whether a three-compartment model can be reduced to two compartments and still resolve white matter parameters [i.e., myelin water fraction (MWF) and g-ratio]. We show that MWF should be computed using a three-compartment model in the corpus callosum, and the g-ratios obtained using three compartment models are consistent with previous reports. We provide results for other parameters, such as signal compartment frequency shifts.

So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging

Myelin water imaging (MWI) is an MRI imaging biomarker for myelin. This method can generate an in vivo whole-brain myelin water fraction map in approximately 10 minutes. It has been applied in various applications including neurodegenerative disease, neurodevelopmental, and neuroplasticity studies. In this review we start with a brief introduction of myelin biology and discuss the contributions of myelin in conventional MRI contrasts. Then the MRI properties of myelin water and four different MWI methods, which are categorized as T₂ -, T₂ *-, T₁ -, and steady-state-based MWI, are summarized. After that, we cover more practical issues such as availability, interpretation, and validation of these methods. To illustrate the utility of MWI as a clinical research tool, MWI studies for two diseases, multiple sclerosis and neuromyelitis optica, are introduced. Additional topics about imaging myelin in gray matter and non-MWI methods for myelin imaging are also included. Although technical and physiological limitations exist, MWI is a potent surrogate biomarker of myelin that carries valuable and useful information of myelin. Evidence Level: 5 Technical Efficacy: 1 J. MAGN. RESON. IMAGING 2021;53:360-373.

Whole-Brain Myelin Imaging Using 3D Double-Echo Sliding Inversion Recovery Ultrashort Echo Time (DESIRE UTE) MRI

Background Signal contamination from long T2 water is a major challenge in direct imaging of myelin with MRI. Nulling of the unwanted long T2 signals can be achieved with an inversion recovery (IR) preparation pulse to null long T2 white matter within the brain. The remaining ultrashort T2 signal from myelin can be detected with an ultrashort echo time (UTE) sequence. Purpose To develop patient-specific whole-brain myelin imaging with a three-dimensional double-echo sliding inversion recovery (DESIRE) UTE sequence. Materials and Methods The DESIRE UTE sequence generates a series of IR images with different inversion times during a single scan. The optimal inversion time for nulling long T2 signal is determined by finding minimal signal on the second echo. Myelin images are generated by subtracting the second echo image from the first UTE image. To validate this method, a prospective study was performed in phantoms, cadaveric brain specimens, healthy volunteers, and patients with multiple sclerosis (MS). A total of 20 healthy volunteers (mean age, 40 years ± 13 [standard deviation], 10 women) and 20 patients with MS (mean age, 58 years ± 8; 15 women) who underwent MRI between November 2017 and February 2019 were prospectively included. Analysis of variance was performed to evaluate the signal difference between MS lesions and normal-appearing white matter in patients with MS. Results High signal intensity and corresponding T2* and T1 of the extracted myelin vesicles provided evidence for direct imaging of ultrashort-T2 myelin protons using the UTE sequence. Gadobenate dimeglumine phantoms with a wide range of T1 values were selectively suppressed with DESIRE UTE. In the ex vivo brain study of MS lesions, signal loss was observed in MS lesions and was conformed with histologic analysis. In the human study, there was a significant reduction in normalized signal intensity in MS lesions compared with that in normal-appearing white matter (0.19 ± 0.10 vs 0.76 ± 0.11, respectively; P < .001). Conclusion The double-echo sliding inversion recovery ultrashort echo time sequence can generate whole-brain myelin images specifically with a clinical 3-T scanner. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Port in this issue.

Myelin water imaging data analysis in less than one minute

PURPOSE

Based on a deep learning neural network (NN) algorithm, a super fast and easy to implement data analysis method was proposed for myelin water imaging (MWI) to calculate the myelin water fraction (MWF).

METHODS

A NN was constructed and trained on MWI data acquired by a 32-echo 3D gradient and spin echo (GRASE) sequence. Ground truth labels were created by regularized non-negative least squares (NNLS) with stimulated echo corrections. Voxel-wise GRASE data from 5 brains (4 healthy, 1 multiple sclerosis (MS)) were used for NN training. The trained NN was tested on 2 healthy brains, 1 MS brain with segmented lesions, 1 healthy spinal cord, and 1 healthy brain acquired from a different scanner.

RESULTS

Production of whole brain MWF maps in approximately 33 ​s can be achieved by a trained NN without graphics card acceleration. For all testing regions, no visual differences between NN and NNLS MWF maps were observed, and no obvious regional biases were found. Quantitatively, all voxels exhibited excellent agreement between NN and NNLS (all R²>0.98, p ​< ​0.001, mean absolute error <0.01).

CONCLUSION

The time for accurate MWF calculation can be dramatically reduced to less than 1 ​min by the proposed NN, addressing one of the barriers facing future clinical feasibility of MWI.

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.

Multi-Exponential Relaxometry Using l1 -Regularized Iterative NNLS (MERLIN) With Application to Myelin Water Fraction Imaging

A new parameter estimation algorithm, MERLIN, is presented for accurate and robust multi-exponential relaxometry using magnetic resonance imaging, a tool that can provide valuable insight into the tissue microstructure of the brain. Multi-exponential relaxometry is used to analyze the myelin water fraction and can help to detect related diseases. However, the underlying problem is ill-conditioned, and as such, is extremely sensitive to noise and measurement imperfections, which can lead to less precise and more biased parameter estimates. MERLIN is a fully automated, multi-voxel approach that incorporates state-of-the-art l₁ -regularization to enforce sparsity and spatial consistency of the estimated distributions. The proposed method is validated in simulations and in vivo experiments, using a multi-echo gradient-echo (MEGE) sequence at 3 T. MERLIN is compared to the conventional single-voxel l₂ -regularized NNLS (rNNLS) and a multi-voxel extension with spatial priors (rNNLS + SP), where it consistently showed lower root mean squared errors of up to 70 percent for all parameters of interest in these simulations.