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

Test–Retest Reproducibility of In Vivo Magnetization Transfer Ratio and Saturation Index in Mice at 9.4 Tesla

Background: Magnetization transfer saturation (MTsat) imaging was developed to reduce T1 dependence and improve specificity to myelin, compared to the widely used MT ratio (MTR) approach, while maintaining a feasible scan time. As MTsat imaging is an emerging technique, the reproducibility of MTsat compared to MTR must be evaluated. Purpose: To assess the test–retest reproducibility of MTR and MTsat in the mouse brain at 9.4 T and calculate sample sizes potentially required to detect effect sizes ranging from 6% to 14%. Study Type: Prospective. Subjects: Twelve healthy C57Bl/6 mice. Field Strength/Sequence: 9.4 T; magnetization transfer imaging using FLASH-3D Gradient Echo; T2-weighted TurboRARE spin echo. Assessment: All mice were scanned at two timepoints (5 days apart). MTR and MTsat maps were analyzed using mean region-of-interest (ROIs: corpus callosum [CC], internal capsule [IC], hippocampus [HC], cortex [CX], and thalamus [TH]), and whole brain voxel-wise analysis. Statistical Tests: Bland–Altman plots were used to assess biases between test–retest measurements. Test–retest reproducibility was evaluated via between and within-subject coefficients of variation (bsCV and wsCV, respectively). Sample sizes required were calculated (significance level: 95%; power: 80%), given effect sizes ranging from 6% to 14%, using both between and within-subject approaches. Results were considered statistically significant at P ≤ 0.05. Results: Bland–Altman plots showed negligible biases between test–retest sessions (MTR: 0.0009; MTsat: 0). ROI-based and voxel-wise CVs revealed high reproducibility for both MTR (ROI-bsCV/wsCV: CC—4.5/2.8%; IC—6.1/5.2%; HC—5.7/4.6%; CX—5.1/2.3%; TH—7.4/4.9%) and MTsat (ROI-bsCV/wsCV: CC—6.3/4.8%; IC—7.3/5.1%; HC—9.5/6.4%; CX—6.7/6.5%; TH—7.2/5.3%). With a sample size of 6, changes on the order of 15% could be detected in MTR and MTsat, both between and within subjects, while smaller changes (6%–8%) required sample sizes of 10–15 for MTR, and 15–20 for MTsat. Data Conclusion: MTsat exhibited comparable reproducibility to MTR, while providing sensitivity to myelin with less T1 dependence than MTR. Evidence Level: 2. Technical Efficacy: Stage 1

Data-driven retrospective correction of B1 field inhomogeneity in fast macromolecular proton fraction and R1 mapping

Correction of B1 field non-uniformity is critical for many quantitative MRI methods including variable flip angle (VFA) T1 mapping and single-point macromolecular proton fraction (MPF) mapping. The latter method showed promising results as a fast and robust quantitative myelin imaging approach and involves VFA-based R1 = 1/T1 map reconstruction as an intermediate processing step. The need for B1 correction restricts applications of the above methods, since B1 mapping sequences increase the examination time and are not commonly available in clinics. A new algorithm was developed to enable retrospective data-driven simultaneous B1 correction in VFA R1 and single-point MPF mapping. The principle of the algorithm is based on different mathematical dependences of B1-related errors in R1 and MPF allowing extraction of a surrogate B1 field map from uncorrected R1 and MPF maps. To validate the method, whole-brain R1 and MPF maps with isotropic 1.25 mm3 resolution were obtained on a 3 T MRI scanner from 11 volunteers. Mean parameter values in segmented brain tissues were compared between three reconstruction options including the absence of correction, actual B1 correction, and surrogate B1 correction. Surrogate B1 maps closely reproduced actual patterns of B1 inhomogeneity. Without correction, B1 non-uniformity caused highly significant biases in R1 and MPF (P < 0.001). Surrogate B1 field correction reduced the biases in both R1 and MPF to a non-significant level (0.1 ≤ P ≤ 0.8). The described algorithm obviates the use of dedicated B1 mapping sequences in fast single-point MPF mapping and provides an alternative solution for correction of B1 non-uniformities in VFA R1 mapping

MRI quantification of multiple sclerosis pathology

Background: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease and a common cause of neurologic disability. MS pathology is characterized by demyelination, neuroaxonal loss and atrophy. Magnetic Resonance Imaging (MRI) is an essential tool in diagnosing and monitoring MS, but its clinical value could be even further expanded by more advanced and quantitative MRI methods, which may also provide additional pathophysiological insights. Purpose: The overall aim of this thesis was to quantify MS pathology using volumetric brain MRI, ultra-high field brain and cervical spinal cord MRI as well as a newly developed rapid myelin imaging technique in relation to cognitive and physical MS disability. Study I, a prospective 17-year longitudinal study of 37 MS participants with 23 age/sex- matched healthy controls for comparison at the last follow-up. Longitudinal volumetric brain 1.5 Tesla MRI during the second half of the study showed that lesion accumulation and corpus callosum atrophy were the most strongly associated neuroanatomical correlates of cognitive disability, with the lesion fraction being an independent predictor of cognitive performance 8.5 years later. Study II, a prospective cross-sectional study of 35 MS participants and 11 age-matched healthy controls using 3 and 7 Tesla MRI. The study demonstrated involvement of both grey and white matter in MS, not only the brain but also the cervical spinal cord, associated with MS disability. Lesions appeared in proximity to the cerebrospinal fluid (CSF), with special predilection to the periventricular and grey matter surrounding the central canal in secondary progressive MS. Study III, a prospective in vivo (71 MS participants and 21 age/sex-matched healthy controls) and ex vivo (brain tissue from 3 MS donors) study at 3 Tesla, showed that a new clinically approved and feasible rapid myelin imaging technique correlates well with myelin stainings and produces robust in vivo myelin quantification that is related to both current and future cognitive and physical disability in MS. Study IV, an in-depth topographical analysis based on Study III, mapped the distribution of demyelination, both in vivo and ex vivo, in the periventricular and perilesional regions of the brain. A gradient of demyelination with predominance near the CSF spaces was seen. Measures of clinical disability were consistently and more strongly associated with the myelin content in normal-appearing tissue compared to the intralesional myelin content. Conclusions: Lesions and atrophy contribute to cognitive and physical disability in MS but to a varying degree, likely dependent on the relative involvement of white vs. grey matter. Both focal lesions/demyelination as well as diffuse demyelination in normal-appearing white matter shows an apparent gradient from the CSF, which differ between relapsing-remitting and progressive MS subtypes/phases. The growing utility and clinical availability of advanced and quantitative MRI techniques holds promise for improved monitoring of MS pathology and likely represents a vital tool for assessing the efficacy of potential remyelinating/reparative therapies in MS

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 demyelinatio

Moving beyond the tensor: Advanced characterisation of white matter microstructure in Huntington’s Disease using translational neuroimaging

Huntington’s disease (HD) is a genetic neurodegenerative disorder leading to devastating cognitive, psychiatric and motor symptoms. Currently, this disease cannot be cured, and a research priority is to increase the understanding of its pathogenesis and to provide biomarkers for evaluating the efficacy of targeted therapies. Subtle and progressive white matter (WM) alterations have been observed early in HD progression, before clinical onset of the disease. However the aetiology of WM degeneration and its role in disease pathogenesis remain unclear. The assessment of early WM microstructural changes in the HD brain is therefore of fundamental importance, as this might prove useful for the identification of disease-related biomarkers and for measuring responsiveness to pharmaceutical and other therapeutic approaches. The primary aim of this work was to exploit both ultra-strong gradients (300 mT/m) and ultra-high field (7 Tesla, 9.4 Tesla) to assess WM microstructure in HD, using a variety of MRI techniques in premanifest and manifest patients, as well as in a mouse model of the disease. Specifically, this Thesis moved beyond the diffusion tensor framework, with the application of advanced WM microstructural imaging. Using these advanced MR techniques I was able to provide a comprehensive and detailed characterisation of WM microstructural alterations in the HD brain, and to better tease apart changes in apparent myelin from alterations in axon microstructure. Assessing both human patients and a mouse model of HD allowed for direct cross-species comparisons and bi-directional translation of results. Additionally, I was able to exploit the improved compartmental specificity obtained by complementing standard DTI metrics with advanced MRI measurements, to study the effects of two months of a novel drumming training on WM plasticity in patients with manifest HD

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'

Nanotools for Neuroscience and Brain Activity Mapping

Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function