Ultrashort echo time (UTE) magnetic resonance imaging of myelin: technical developments and challenges

Yet more evidence that non-aqueous myelin lipids can be directly imaged with ultrashort echo time (UTE) MRI on a clinical 3T scanner: a lyophilized red blood cell membrane lipid study

Direct imaging of semi-solid lipids, such as myelin, is of great interest as a noninvasive biomarker of neurodegenerative diseases. Yet, the short T2 relaxation times of semi-solid lipid protons hamper direct detection through conventional magnetic resonance imaging (MRI) pulse sequences. In this study, we examined whether a three-dimensional ultrashort echo time (3D UTE) sequence can directly acquire signals from membrane lipids. Membrane lipids from red blood cells (RBC) were collected from commercially available blood as a general model of the myelin lipid bilayer and subjected to D2O exchange and freeze-drying for complete water removal. Sufficiently high MR signals were detected with the 3D UTE sequence, which showed an ultrashort T2* of ∼77-271 µs and a short T1 of ∼189 ms for semi-solid RBC membrane lipids. These measurements can guide designing UTE-based sequences for direct in vivo imaging of membrane lipids.

Seeing plants as never before

Imaging has long supported our ability to understand the inner life of plants, their development, and response to a dynamic environment. While optical microscopy remains the core tool for imaging, a suite of novel technologies is now beginning to make a significant contribution to visualize plant metabolism. The purpose of this review was to provide the scientific community with an overview of current imaging methods, which rely variously on either nuclear magnetic resonance (NMR), mass spectrometry (MS) or infrared (IR) spectroscopy, and to present some examples of their application in order to illustrate their utility. In addition to providing a description of the basic principles underlying these technologies, the review discusses their various advantages and limitations, reveals the current state of the art, and suggests their potential application to experimental practice. Finally, a view is presented as to how the technologies will likely develop, how these developments may encourage the formulation of novel experimental strategies, and how the enormous potential of these technologies can contribute to progress in plant science.

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.

Feasibility of MRI Quantification of Myelin Water Fraction in the Fetal Guinea Pig Brain

BACKGROUND

Fetal myelination assessment is important for understanding neurodevelopment and neurodegeneration. Myelin water imaging (MWI) quantifies myelin water fraction (MWF), a validated marker for myelin content, and has been used to assess brain myelin in children and neonates.

PURPOSE

To demonstrate that MWI can quantify MWF in fetal guinea pigs (GPs).

STUDY TYPE

Animal model.

ANIMAL MODEL

Nine pregnant, Dunkin-Hartley GPs with 31 fetuses (mean ± standard deviation = 60 ± 1.5 days gestation).

FIELD STRENGTH/SEQUENCE

3D spoiled gradient echo and balanced steady-state free precession sequences at 3.0 T.

ASSESSMENT

MWF maps were reconstructed for maternal and fetal GP brains using the multicomponent driven equilibrium single pulse observation of T₁ and T₂ (mcDESPOT) approach. Myelin basic protein (MBP) stain provided histological validation of the MWF. Regions of interest were placed in the maternal corpus callosum (CC), maternal fornix (FOR), fetal CC, and fetal FOR in MWF maps and MBP stains.

STATISTICAL TESTS

Linear regression between MWF and MBP stain intensity (SI) of all four regions (coefficient of determination, R² ). A paired t-test compared the MWF of maternal and mean fetal CC, MBP SI of maternal and mean fetal CC, MWF of maternal and mean fetal FOR, MBP SI of maternal and mean fetal FOR. A paired t-test with a linear mixed model compared the MWF of fetal CC and fetal FOR, and MBP SI of fetal CC and fetal FOR. A  P value < 0.0083 was considered statistically significant.

RESULTS

The mean MWF of the analyzed regions are as follows (mean ± standard deviation): 0.338 + 0.016 (maternal CC), 0.340 ± 0.017 (maternal FOR), 0.214 ± 0.016 (fetal CC), and 0.305 ± 0.025 (fetal FOR). MWF correlated with MBP SI in all regions (R²  = 0.81). Significant differences were found between MWF and MBP SI of maternal and fetal CC, and MWF and MBP SI of fetal CC and fetal FOR.

DATA CONCLUSION

This study demonstrated the feasibility of MWI in assessing fetal brain myelin content.

EVIDENCE LEVEL

2 Technical Efficacy: Stage 1.

Advances and opportunities in nanoimaging agents for the diagnosis of inflammatory lung diseases

The development of rapid, noninvasive diagnostics to detect lung diseases is a great need after the COVID-2019 outbreak. The nanotechnology-based approach has improved imaging and facilitates the early diagnosis of inflammatory lung diseases. The multifunctional properties of nanoprobes enable better spatial-temporal resolution and a high signal-to-noise ratio in imaging. Targeted nanoimaging agents have been used to bind specific tissues in inflammatory lungs for early-stage diagnosis. However, nanobased imaging approaches for inflammatory lung diseases are still in their infancy. This review provides a solution-focused approach to exploring medical imaging technologies and nanoprobes for the detection of inflammatory lung diseases. Prospects for the development of contrast agents for lung disease detection are also discussed.

Primary Multiparametric Quantitative Brain MRI: State-of-the-Art Relaxometric and Proton Density Mapping Techniques

This review on brain multiparametric quantitative MRI (MP-qMRI) focuses on the primary subset of quantitative MRI (qMRI) parameters that represent the mobile ("free") and bound ("motion-restricted") proton pools. Such primary parameters are the proton densities, relaxation times, and magnetization transfer parameters. Diffusion qMRI is also included because of its wide implementation in complete clinical MP-qMRI application. MP-qMRI advances were reviewed over the past 2 decades, with substantial progress observed toward accelerating image acquisition and increasing mapping accuracy. Areas that need further investigation and refinement are identified as follows: (a) the biologic underpinnings of qMRI parameter values and their changes with age and/or disease and (b) the theoretical limitations implicitly built into most qMRI mapping algorithms that do not distinguish between the different spatial scales of voxels versus spin packets, the central physical object of the Bloch theory. With rapidly improving image processing techniques and continuous advances in computer hardware, MP-qMRI has the potential for implementation in a wide range of clinical applications. Currently, three emerging MP-qMRI applications are synthetic MRI, macrostructural qMRI, and microstructural tissue modeling.

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.

Initial evidence of abnormal brain plasticity in anorexia nervosa: an ultra-high field study

Anorexia Nervosa has been associated with white matter abnormalities implicating subcortical abnormal myelination. Extending these findings to intracortical myelin has been challenging but ultra-high field neuroimaging offers new methodological opportunities. To test the integrity of intracortical myelin in AN we used 7 T neuroimaging to acquire T1-weighted images optimized for intracortical myelin from seven females with AN (age range: 18-33) and 11 healthy females (age range: 23-32). Intracortical T₁ values (inverse index of myelin concentration) were extracted from 148 cortical regions at ten depth-levels across the cortical ribbon. Across all cortical regions, these levels were averaged to generate estimates of total intracortical myelin concentration and were clustered using principal component analyses into two clusters; the outer cluster comprised T₁ values across depth-levels ranging from the CSF boundary to the middle of the cortical regions and the inner cluster comprised T₁ values across depth-levels ranging from the middle of the cortical regions to the gray/white matter boundary. Individuals with AN exhibited higher T₁ values (i.e., decreased intracortical myelin concentration) in all three metrics. It remains to be established if these abnormalities result from undernutrition or specific lipid nutritional imbalances, or are trait markers; and whether they may contribute to neurobiological deficits seen in AN.

Mapping the rest of the human connectome: Atlasing the spinal cord and peripheral nervous system

The emergence of diffusion, structural, and functional neuroimaging methods has enabled major multi-site efforts to map the human connectome, which has heretofore been defined as containing all neural connections in the central nervous system (CNS). However, these efforts are not structured to examine the richness and complexity of the peripheral nervous system (PNS), which arguably forms the (neglected) rest of the connectome. Despite increasing interest in an atlas of the spinal cord (SC) and PNS which is simultaneously stereotactic, interactive, electronically dissectible, scalable, population-based and deformable, little attention has thus far been devoted to this task of critical importance. Nevertheless, the atlasing of these complete neural structures is essential for neurosurgical planning, neurological localization, and for mapping those components of the human connectome located outside of the CNS. Here we recommend a modification to the definition of the human connectome to include the SC and PNS, and argue for the creation of an inclusive atlas to complement current efforts to map the brain's human connectome, to enhance clinical education, and to assist progress in neuroscience research. In addition to providing a critical overview of existing neuroimaging techniques, image processing methodologies and algorithmic advances which can be combined for the creation of a full connectome atlas, we outline a blueprint for ultimately mapping the entire human nervous system and, thereby, for filling a critical gap in our scientific knowledge of neural connectivity.

Imaging of the Spinal Cord in Multiple Sclerosis: Past, Present, Future

Spinal cord imaging in multiple sclerosis (MS) plays a significant role in diagnosing and tracking disease progression. The spinal cord is one of four key areas of the central nervous system where documenting the dissemination in space in the McDonald criteria for diagnosing MS. Spinal cord lesion load and the severity of cord atrophy are believed to be more relevant to disability than white matter lesions in the brain in different phenotypes of MS. Axonal loss contributes to spinal cord atrophy in MS and its degree correlates with disease severity and prognosis. Therefore, measures of axonal loss are often reliable biomarkers for monitoring disease progression. With recent technical advances, more and more qualitative and quantitative MRI techniques have been investigated in an attempt to provide objective and reliable diagnostic and monitoring biomarkers in MS. In this article, we discuss the role of spinal cord imaging in the diagnosis and prognosis of MS and, additionally, we review various techniques that may improve our understanding of the disease.

New options for increasing the sensitivity, specificity and scope of synergistic contrast magnetic resonance imaging (scMRI) using Multiplied, Added, Subtracted and/or FiTted (MASTIR) pulse sequences

This paper reviews magnetic resonance (MR) pulse sequences in which the same or different tissue properties (TPs) such as T1 and T2 are used to contribute synergistically to lesion contrast. It also shows how synergistic contrast can be created with Multiplied, Added, Subtracted and/or fiTted Inversion Recovery (MASTIR) sequences, and be used to improve the sensitivity, specificity and scope of clinical magnetic resonance imaging (MRI) protocols. Synergistic contrast can be created from: (i) the same TP, e.g., T1 used twice or more in a pulse sequence; (ii) different TPs such as ρm, T1, T2, and D* used once or more within a sequence, and (iii) additional suppression or reduction of signals from tissues and/or fluids such as fat, long T2 tissues and cerebrospinal fluid (CSF). The short inversion time (TI) inversion recovery (IR) (STIR) and double IR (DIR) sequences usually show synergistic positive contrast for lesions which have increases in both T1 and T2. The diffusion weighted pulsed gradient spin echo (PGSE) sequence shows synergistic contrast for lesions which have an increase in T2 and a decrease in D*; the sequence is both positively weighted for T2 and negatively weighted for D*. In the brain, when an IR sequence nulling white matter has subtracted from it an IR sequence nulling gray matter to form the subtracted IR (SIR) sequence, increases in the single TP T1 between the two nulling points of the original two sequences generate high synergistic positive contrast. In addition, the subtraction to produce the SIR sequence reduces fat and CSF signals. To provide high sensitivity to changes in TPs in disease the SIR sequence can be used (i) alone to provide synergistic T1 contrast as above; (ii) with T2-weighting to provide synergistic T1 and T2 contrast, and (iii) with T2- and D*-weighting to provide synergistic T1, T2, and D* contrast. The SIR sequence can also be used in reversed form (longer TI form minus shorter TI form) to produce very high positive synergistic T1 contrast for reductions in T1, and so increase the positive contrast enhancement produced by clinical gadolinium-based contrast agents (GBCAs) when they reduce T1. The specificity of MRI examinations can be improved by using the reversed SIR sequence with a long echo time (TE) gradient echo as well as echo subtraction to show synergistic high contrast from T1 and T2* shortening produced by organic iron. Other added and subtracted forms of the MASTIR sequence can be used synergistically to selectively show myelin, myelin water and fluids including blood and CSF. Protocols using MASTIR sequences to provide synergistic contrast in MRI of the brain, prostate and articular cartilage are included as illustrative examples, and the features of synergistic contrast MRI (scMRI) are compared to those of multiparametric MRI (mpMRI) and functional MRI (fMRI).