Myelin and axon pathology in multiple sclerosis assessed by myelin water and multi-shell diffusion imaging

Quantifying myelin density in the feline auditory cortex

The cerebral cortex comprises many distinct regions that differ in structure, function, and patterns of connectivity. Current approaches to parcellating these regions often take advantage of functional neuroimaging approaches that can identify regions involved in a particular process with reasonable spatial resolution. However, neuroanatomical biomarkers are also very useful in identifying distinct cortical regions either in addition to, or in place of functional measures. For example, differences in myelin density are thought to relate to functional differences between regions, are sensitive to individual patterns of experience, and have been shown to vary across functional hierarchies in a predictable manner. Accordingly, the current study provides quantitative stereological estimates of myelin density for each of the 13 regions that make up the feline auditory cortex. We demonstrate that significant differences can be observed between auditory cortical regions, with the highest myelin density observed in the regions that comprise the auditory core (i.e., the primary auditory cortex and anterior auditory field). Moreover, our myeloarchitectonic map suggests that myelin density varies in a hierarchical fashion that conforms to the traditional model of spatial organization in auditory cortex. Taken together, these results establish myelin as a useful biomarker for parcellating auditory cortical regions, and provide detailed estimates against which other, less invasive methods of quantifying cortical myelination may be compared.

Deep learning enables accurate brain tissue microstructure analysis based on clinically feasible diffusion magnetic resonance imaging

Diffusion magnetic resonance imaging (dMRI) allows non-invasive assessment of brain tissue microstructure. Current model-based tissue microstructure reconstruction techniques require a large number of diffusion gradients, which is not clinically feasible due to imaging time constraints, and this has limited the use of tissue microstructure information in clinical settings. Recently, approaches based on deep learning (DL) have achieved promising tissue microstructure reconstruction results using clinically feasible dMRI. However, it remains unclear whether the subtle tissue changes associated with disease or age are properly preserved with DL approaches and whether DL reconstruction results can benefit clinical applications. Here, we provide the first evidence that DL approaches to tissue microstructure reconstruction yield reliable brain tissue microstructure analysis based on clinically feasible dMRI scans. Specifically, we reconstructed tissue microstructure from four different brain dMRI datasets with only 12 diffusion gradients, a clinically feasible protocol, and the neurite orientation dispersion and density imaging (NODDI) and spherical mean technique (SMT) models were considered. With these results we show that disease-related and age-dependent alterations of brain tissue were accurately identified. These findings demonstrate that DL tissue microstructure reconstruction can accurately quantify microstructural alterations in the brain based on clinically feasible dMRI.

Advanced MRI Measures of Myelin and Axon Volume Identify Repair in Multiple Sclerosis

OBJECTIVE

Pathological studies suggest that multiple sclerosis (MS) lesions endure multiple waves of damage and repair; however, the dynamics and characteristics of these processes are poorly understood in patients living with MS.

METHODS

We studied 128 MS patients (75 relapsing-remitting, 53 progressive) and 72 healthy controls who underwent advanced magnetic resonance imaging and clinical examination at baseline and 2 years later. Magnetization transfer saturation and multi-shell diffusion imaging were used to quantify longitudinal changes in myelin and axon volumes within MS lesions. Lesions were grouped into 4 classes (repair, damage, mixed repair damage, and stable). The frequency of each class was correlated to clinical measures, demographic characteristics, and levels of serum neurofilament light chain (sNfL).

RESULTS

Stable lesions were the most frequent (n = 2,276; 44%), followed by lesions with patterns of "repair" (n = 1,352; 26.2%) and damage (n = 1,214; 23.5%). The frequency of "repair" lesion was negatively associated with disability (β = -0.04; p < 0.001) and sNfL (β = -0.16; p < 0.001) at follow-up. The frequency of the "damage" class was higher in progressive than relapsing-remitting patients (p < 0.05) and was related to disability (baseline: β = -0.078; follow-up: β = -0.076; p < 0.001) and age (baseline: β = -0.078; p < 0.001). Stable lesions were more frequent in relapsing-remitting than in progressive patients (p < 0.05), and in younger patients versus older (β = -0.07; p < 0.001) at baseline. Further, "mixed" lesions were most frequent in older patients (β = 0.004; p < 0.001) at baseline.

INTERPRETATION

These findings show that repair and damage processes within MS lesions occur across the entire disease spectrum and that their frequency correlates with patients disability, age, disease duration, and extent of neuroaxonal damage. ANN NEUROL 2024.

Clinical relevance of paramagnetic rim lesion heterogeneity in multiple sclerosis

OBJECTIVE

Previous studies reveal heterogeneity in terms of paramagnetic rim lesions (PRL) associated tissue damage. We investigated the physiopathology and clinical implications of this heterogeneity.

METHODS

In 103 MS patients (72 relapsing and 31 progressive), brain lesions were manually segmented on 3T 3D-FLAIR and rim visibility was assessed with a visual confidence level score (VCLS) on 3D-EPI phase. Using T1 relaxation time maps, lesions were categorized in long-T1 and short-T1. Lesion age was calculated from time of first gadolinium enhancement (N = 84 lesions). Results on clinical scores were validated in an extended cohort of 167 patients using normalized T1w-MPRAGE lesion values.

RESULTS

Rim visibility (VCLS analysis) was associated with increasing lesional T1 (P/PFDR < 0.001). Of 1680 analyzed lesions, 427 were categorized as PRL. Long-T1 PRL were older than short-T1 PRL (average 0.8 vs. 2.0 years, P/PFDR = 0.005/0.008), and featured larger lesional volume (P/PFDR < 0.0001) and multi-shell diffusion-measured axonal damage (P/PFDR < 0.0001). The total volume of long-T1-PRL versus PRL showed 2× predictive power for both higher MS disability (EDSS; P/PFDR = 0.003/0.005 vs. P/PFDR = 0.042/0.057) and severity (MSSS; P/PFDR = 0.0006/0.001 vs. P/PFDR = 0.004/0.007). In random forest, having ≥1 long-T1-PRL versus ≥4 PRL showed 2-4× higher performance to predict a higher EDSS and MSSS. In the validation cohort, long-T1 PRL outperformed (~2×) PRL in predicting both EDSS and MSSS.

INTERPRETATION

PRL show substantial heterogeneity in terms of intralesional tissue damage. More destructive, likely older, long-T1 PRL improve the association with MS clinical scales. This PRL heterogeneity characterization was replicated using standard T1w MRI, highlighting its potential for clinical translation.

Longitudinal investigation of optic chiasm in patients with traumatic brain injury

BACKGROUND

Traumatic brain injury (TBI) often precipitates a cascade of neurophysiological alterations, impacting structures such as the optic nerve and ocular motor system. However, the literature lacks expansive investigations into the longitudinal changes in the optic chiasm and its relationship with the clinical recovery of visual processing. This study aimed to scrutinize longitudinal changes in optic chiasm volume (OCV) and establish the relationship of OCV with process speed index at 12 months post-injury. Process speed index is derived from Wechsler Adult Intelligence Scale IV.

METHODS

Thorough cross-sectional and longitudinal analyses were executed, involving 42 patients with moderate to severe TBI and 35 healthy controls. OCV was acquired at 3, 6, and 12 months post-injury using T1-weighted images. OCV of healthy controls and that of patients with TBI at 3, 6, and 12 months post-injury were compared using a Mann-Whitney U test. A multiple linear regression model was constructed to assess the association between OCV and PSI and to predict PSI at 12 months post-injury using OCV at 3 months post-injury.

RESULTS

OCV of patients with TBI was significantly larger compared to healthy controls, persisting from 3 to 12 months post-injury (p < 0.05). This increased OCV negatively correlated with PSI at 12 months post-injury, indicating that larger OCV sizes were associated with decreased PSI (p = 0.031). Furthermore, the multiple linear regression model was significant in predicting PSI at 12 months post-injury utilizing OCV at 3 months post-injury (p = 0.024).

CONCLUSION

For the first time, this study elucidates the increased OCV and the significant association between OCV in sub-chronic stage and PSI at 12 months post-injury, potentially providing clinicians with a tool for anticipatory cognitive rehabilitation strategies following TBI.

Quantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions

BACKGROUND AND OBJECTIVES

Myelin and iron play essential roles in remyelination processes of multiple sclerosis (MS) lesions. χ-separation, a novel biophysical model applied to multiecho T2*-data and T2-data, estimates the contribution of myelin and iron to the obtained susceptibility signal. We used this method to investigate myelin and iron levels in lesion and nonlesion brain areas in patients with MS and healthy individuals.

METHODS

This prospective MS cohort study included patients with MS fulfilling the McDonald Criteria 2017 and healthy individuals, aged 18 years or older, with no other neurologic comorbidities. Participants underwent MRI at baseline and after 2 years, including multiecho GRE-(T2*) and FAST-(T2) sequences. Using χ-separation, we generated myelin-sensitive and iron-sensitive susceptibility maps. White matter lesions (WMLs), cortical lesions (CLs), surrounding normal-appearing white matter (NAWM), and normal-appearing gray matter were segmented on fluid-attenuated inversion recovery and magnetization-prepared 2 rapid gradient echo images, respectively. Cross-sectional group comparisons used Wilcoxon rank-sum tests, longitudinal analyses applied Wilcoxon signed-rank tests. Associations with clinical outcomes (disease phenotype, age, sex, disease duration, disability measured by Expanded Disability Status Scale [EDSS], neurofilament light chain levels, and T2-lesion number and volume) were assessed using linear regression models.

RESULTS

Of 168 patients with MS (median [interquartile range (IQR)] age 47.0 [21.7] years; 101 women; 6,898 WMLs, 775 CLs) and 103 healthy individuals (age 33.0 [10.5] years, 57 women), 108 and 62 were followed for a median of 2 years, respectively (IQR 0.1; 5,030 WMLs, 485 CLs). At baseline, WMLs had lower myelin (median 0.025 [IQR 0.015] parts per million [ppm]) and iron (0.017 [0.015] ppm) than the corresponding NAWM (myelin 0.030 [0.012]; iron 0.019 [0.011] ppm; both p < 0.001). After 2 years, both myelin (0.027 [0.014] ppm) and iron had increased (0.018 [0.015] ppm; both p < 0.001). Younger age (p < 0.001, b = -5.111 × 10-5), lower disability (p = 0.04, b = -2.352 × 10-5), and relapsing-remitting phenotype (RRMS, 0.003 [0.01] vs primary progressive 0.002 [IQR 0.01], p < 0.001; vs secondary progressive 0.0004 [IQR 0.01], p < 0.001) at baseline were associated with remyelination. Increment of myelin correlated with clinical improvement measured by EDSS (p = 0.015, b = -6.686 × 10-4).

DISCUSSION

χ-separation, a novel mathematical model applied to multiecho T2*-images and T2-images shows that young RRMS patients with low disability exhibit higher remyelination capacity, which correlated with clinical disability over a 2-year follow-up.

Imaging chronic active lesions in multiple sclerosis: a consensus statement

Chronic active lesions (CAL) are an important manifestation of chronic inflammation in multiple sclerosis and have implications for non-relapsing biological progression. In recent years, the discovery of innovative MRI and PET-derived biomarkers has made it possible to detect CAL, and to some extent quantify them, in the brain of persons with multiple sclerosis, in vivo. Paramagnetic rim lesions on susceptibility-sensitive MRI sequences, MRI-defined slowly expanding lesions on T1-weighted and T2-weighted scans, and 18-kDa translocator protein-positive lesions on PET are promising candidate biomarkers of CAL. While partially overlapping, these biomarkers do not have equivalent sensitivity and specificity to histopathological CAL. Standardization in the use of available imaging measures for CAL identification, quantification and monitoring is lacking. To fast-forward clinical translation of CAL, the North American Imaging in Multiple Sclerosis Cooperative developed a consensus statement, which provides guidance for the radiological definition and measurement of CAL. The proposed manuscript presents this consensus statement, summarizes the multistep process leading to it, and identifies the remaining major gaps in knowledge.

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.

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.

Patterns of cerebral damage in multiple sclerosis and aquaporin-4 antibody-positive neuromyelitis optica spectrum disorders-major differences revealed by non-conventional imaging

Multiple sclerosis and aquaporin-4 antibody neuromyelitis optica spectrum disorders are distinct autoimmune CNS disorders with overlapping clinical features but differing pathology. Multiple sclerosis is primarily a demyelinating disease with the presence of widespread axonal damage, while neuromyelitis optica spectrum disorders is characterized by astrocyte injury with secondary demyelination. Diagnosis is typically based on lesion characteristics observed on standard MRI imaging and antibody testing but can be challenging in patients with in-between clinical presentations. Non-conventional MRI techniques can provide valuable diagnostic information by measuring disease processes at the microstructural level. We used non-conventional MRI to measure markers of axonal loss in specific white matter tracts in multiple sclerosis and neuromyelitis optica spectrum disorders, depending on their relationship with focal lesions. Patients with relapsing-remitting multiple sclerosis (n = 20), aquaporin-4 antibody-associated neuromyelitis optica spectrum disorders (n = 20) and healthy controls (n = 20) underwent a 3T brain MRI, including T1-, T2- and diffusion-weighted sequences, quantitative susceptibility mapping and phase-sensitive inversion recovery sequence. Tractometry was used to differentiate tract fibres traversing through white matter lesions from those that did not. Neurite density index was assessed using neurite orientation dispersion and density imaging model. Cortical damage was evaluated using T1 relaxation rates. Cortical lesions and paramagnetic rim lesions were identified using phase-sensitive inversion recovery and quantitative susceptibility mapping. In tracts traversing lesions, only one out of 50 tracts showed a decreased neurite density index in multiple sclerosis compared with neuromyelitis optica spectrum disorders. Among 50 tracts not traversing lesions, six showed reduced neurite density in multiple sclerosis (including three in the cerebellum and brainstem) compared to neuromyelitis optica spectrum disorders. In multiple sclerosis, reduced neurite density was found in the majority of fibres traversing (40/50) and not traversing (37/50) white matter lesions when compared to healthy controls. A negative correlation between neurite density in lesion-free fibres and cortical lesions, but not paramagnetic rim lesions, was observed in multiple sclerosis (39/50 tracts). In neuromyelitis optica spectrum disorders compared to healthy controls, decreased neurite density was observed in a subset of fibres traversing white matter lesions, but not in lesion-free fibres. In conclusion, we identified significant differences between multiple sclerosis and neuromyelitis optica spectrum disorders corresponding to their distinct pathologies. Specifically, in multiple sclerosis, neurite density reduction was widespread across fibres, regardless of their relationship to white matter lesions, while in neuromyelitis optica spectrum disorders, this reduction was limited to fibres passing through white matter lesions. Further studies are needed to evaluate the discriminatory potential of neurite density measures in white matter tracts for differentiating multiple sclerosis from neuromyelitis optica spectrum disorders.

Advanced Brain Imaging in Central Nervous System Demyelinating Diseases

In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.

New Imaging Markers in Multiple Sclerosis and Related Disorders: Smoldering Inflammation and the Central Vein Sign

Concepts of multiple sclerosis (MS) biology continue to evolve, with observations such as "progression independent of disease activity" challenging traditional phenotypic categorization. Iron-sensitive, susceptibility-based imaging techniques are emerging as highly translatable MR imaging sequences that allow for visualization of at least 2 clinically useful biomarkers: the central vein sign and the paramagnetic rim lesion (PRL). Both biomarkers demonstrate high specificity in the discrimination of MS from other mimics and can be seen at 1.5 T and 3 T field strengths. Additionally, PRLs represent a subset of chronic active lesions engaged in "smoldering" compartmentalized inflammation behind an intact blood-brain barrier.

Determinants and Biomarkers of Progression Independent of Relapses in Multiple Sclerosis

Clinical, pathological, and imaging evidence in multiple sclerosis (MS) suggests that a smoldering inflammatory activity is present from the earliest stages of the disease and underlies the progression of disability, which proceeds relentlessly and independently of clinical and radiological relapses (PIRA). The complex system of pathological events driving "chronic" worsening is likely linked with the early accumulation of compartmentalized inflammation within the central nervous system as well as insufficient repair phenomena and mitochondrial failure. These mechanisms are partially lesion-independent and differ from those causing clinical relapses and the formation of new focal demyelinating lesions; they lead to neuroaxonal dysfunction and death, myelin loss, glia alterations, and finally, a neuronal network dysfunction outweighing central nervous system (CNS) compensatory mechanisms. This review aims to provide an overview of the state of the art of neuropathological, immunological, and imaging knowledge about the mechanisms underlying the smoldering disease activity, focusing on possible early biomarkers and their translation into clinical practice. ANN NEUROL 2024;96:1-20.

Longitudinal myelin content measures of slowly expanding lesions using 7T MRI in multiple sclerosis

BACKGROUND AND PURPOSE

Slowly expanding lesions (SELs) are thought to represent a subset of chronic active lesions and have been associated with clinical disability, severity, and disease progression. The purpose of this study was to characterize SELs using advanced magnetic resonance imaging (MRI) measures related to myelin and neurite density on 7 Tesla (T) MRI.

METHODS

The study design was retrospective, longitudinal, observational cohort with multiple sclerosis (n = 15). Magnetom 7T scanner was used to acquire magnetization-prepared 2 rapid acquisition gradient echo and advanced MRI including visualization of short transverse relaxation time component (ViSTa) for myelin, quantitative magnetization transfer (qMT) for myelin, and neurite orientation dispersion density imaging (NODDI). SELs were defined as lesions showing ≥12% of growth over 12 months on serial MRI. Comparisons of quantitative measures in SELs and non-SELs were performed at baseline and over time. Statistical analyses included two-sample t-test, analysis of variance, and mixed-effects linear model for MRI metrics between lesion types.

RESULTS

A total of 1075 lesions were evaluated. Two hundred twenty-four lesions (21%) were SELs, and 216 (96%) of the SELs were black holes. At baseline, compared to non-SELs, SELs showed significantly lower ViSTa (1.38 vs. 1.53, p < .001) and qMT (2.47 vs. 2.97, p < .001) but not in NODDI measures (p > .27). Longitudinally, only ViSTa showed a greater loss when comparing SEL and non-SEL (p = .03).

CONCLUSIONS

SELs have a lower myelin content relative to non-SELs without a difference in neurite measures. SELs showed a longitudinal decrease in apparent myelin water fraction reflecting greater tissue injury.

Multi-parametric MRI can detect enhanced myelination in the Gli1 -/- mouse brain

This study investigated the potential of combining multiple MR parameters to enhance the characterization of myelin in the mouse brain. We collected ex vivo multi-parametric MR data at 7 Tesla from control and Gli1 -/- mice; the latter exhibit enhanced myelination at postnatal day 10 (P10) in the corpus callosum and cortex. The MR data included relaxivity, magnetization transfer, and diffusion measurements, each targeting distinct myelin properties. This analysis was followed by and compared to myelin basic protein (MBP) staining of the same samples. Although a majority of the MR parameters included in this study showed significant differences in the corpus callosum between the control and Gli1 -/- mice, only T 2 , T 1 /T 2, and radial diffusivity (RD) demonstrated a significant correlation with MBP values. Based on data from the corpus callosum, partial least square regression suggested that combining T 2 , T 1 /T 2 , and inhomogeneous magnetization transfer ratio could explain approximately 80% of the variance in the MBP values. Myelin predictions based on these three parameters yielded stronger correlations with the MBP values in the P10 mouse brain corpus callosum than any single MR parameter. In the motor cortex, combining T 2 , T 1 /T 2, and radial kurtosis could explain over 90% of the variance in the MBP values at P10. This study demonstrates the utility of multi-parametric MRI in improving the detection of myelin changes in the mouse brain.

Multiple Sclerosis Part 2: Advanced Imaging and Emerging Techniques

Multiple advanced imaging methods for multiple sclerosis (MS) have been in investigation to identify new imaging biomarkers for early disease detection, predicting disease prognosis, and clinical trial endpoints. Multiple techniques probing different aspects of tissue microstructure (ie, advanced diffusion imaging, magnetization transfer, myelin water imaging, magnetic resonance spectroscopy, glymphatic imaging, and perfusion) support the notion that MS is a global disease with microstructural changes evident in normal-appearing white and gray matter. These global changes are likely better predictors of disability compared with lesion load alone. Emerging techniques in glymphatic and molecular imaging may improve understanding of pathophysiology and emerging treatments.

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group

This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.

Comparative overview of multi-shell diffusion MRI models to characterize the microstructure of multiple sclerosis lesions and periplaques

In multiple sclerosis (MS), accurate in vivo characterization of the heterogeneous lesional and extra-lesional tissue pathology remains challenging. Marshalling several advanced imaging techniques - quantitative relaxation time (T1) mapping, a model-free average diffusion signal approach and four multi-shell diffusion models - this study investigates the performance of multi-shell diffusion models and characterizes the microstructural damage within (i) different MS lesion types - active, chronic active, and chronic inactive - (ii) their respective periplaque white matter (WM), and (iii) the surrounding normal-appearing white matter (NAWM). In 83 MS participants (56 relapsing-remitting, 27 progressive) and 23 age and sex-matched healthy controls (HC), we analysed a total of 317 paramagnetic rim lesions (PRL+), 232 non-paramagnetic rim lesions (PRL-), 38 contrast-enhancing lesions (CEL). Consistent with previous findings and histology, our analysis revealed the ability of advanced multi-shell diffusion models to characterize the unique microstructural patterns of CEL, and to elucidate their possible evolution into a resolving (chronic inactive) vs smoldering (chronic active) inflammatory stage. In addition, we showed that the microstructural damage extends well beyond the MRI-visible lesion edge, gradually fading out while moving outward from the lesion edge into the immediate WM periplaque and the NAWM, the latter still characterized by diffuse microstructural damage in MS vs HC. This study also emphasizes the critical role of selecting appropriate diffusion models to elucidate the complex pathological architecture of MS lesions and their periplaque. More specifically, multi-compartment diffusion models based on biophysically interpretable metrics such as neurite orientation dispersion and density (NODDI; mean auc=0.8002) emerge as the preferred choice for MS applications, while simpler models based on a representation of the diffusion signal, like diffusion tensor imaging (DTI; mean auc=0.6942), consistently underperformed, also when compared to T1 mapping (mean auc=0.73375).

Chronic Active Lesions and Larger Choroid Plexus Explain Cognition and Fatigue in Multiple Sclerosis

BACKGROUND AND OBJECTIVES

Chronic inflammation may contribute to cognitive dysfunction and fatigue in patients with multiple sclerosis (MS). Paramagnetic rim lesions (PRLs) and choroid plexus (CP) enlargement have been proposed as markers of chronic inflammation in MS being associated with a more severe disease course. However, their relation with cognitive impairment and fatigue has not been fully explored yet. Here, we investigated the contribution of PRL number and volume and CP enlargement to cognitive impairment and fatigue in patients with MS.

METHODS

Brain 3T MRI, neurologic evaluation, and neuropsychological assessment, including the Brief Repeatable Battery of Neuropsychological Tests and Modified Fatigue Impact Scale, were obtained from 129 patients with MS and 73 age-matched and sex-matched healthy controls (HC). PRLs were identified on phase images of susceptibility-weighted imaging, whereas CP volume was quantified using a fully automatic method on brain three-dimensional T1-weighted and fluid-attenuated inversion recovery MRI sequences. Predictors of cognitive impairment and fatigue were identified using random forest.

RESULTS

Thirty-six (27.9%) patients with MS were cognitively impaired, and 31/113 (27.4%) patients had fatigue. Fifty-nine (45.7%) patients with MS had ≥1 PRLs (median = 0, interquartile range = 0;2). Compared with HC, patients with MS showed significantly higher T2-hyperintense white matter lesion (WM) volume; lower normalized brain, thalamic, hippocampal, caudate, cortical, and WM volumes; and higher normalized CP volume (p from <0.001 to 0.040). The predictors of cognitive impairment (relative importance) (out-of-bag area under the curve [OOB-AUC] = 0.707) were normalized brain volume (100%), normalized caudate volume (89.1%), normalized CP volume (80.3%), normalized cortical volume (70.3%), number (67.3%) and volume (66.7%) of PRLs, and T2-hyperintense WM lesion volume (64.0%). Normalized CP volume was the only predictor of the presence of fatigue (OOB-AUC = 0.563).

DISCUSSION

Chronic inflammation, with higher number and volume of PRLs and enlarged CP, may contribute to cognitive impairment in MS in addition to gray matter atrophy. The contribution of enlarged CP in explaining fatigue supports the relevance of immune-related processes in determining this manifestation independently of disease severity. PRLs and CP enlargement may contribute to the pathophysiology of cognitive impairment and fatigue in MS, and they may represent clinically relevant therapeutic targets to limit the impact of these clinical manifestations in MS.

Severity of white matter microstructural damage in a Brazilian relapsing-remitting multiple sclerosis cohort: A possible window to optimize treatment

BACKGROUND

Multiple sclerosis (MS) is an important cause of acquired neurological disability in young adults, characterized by multicentric inflammation, demyelination, and axonal damage.

OBJECTIVE

The objective is to investigate white matter (WM) damage progression in a Brazilian MS patient cohort, using diffusion tensor imaging (DTI) post-processed by tract-based spatial statistics (TBSS).

METHODS

DTI scans were acquired from 76 MS patients and 37 sex-and-age matched controls. Patients were divided into three groups based on disease duration. DTI was performed along 30 non-collinear directions by using a 1.5T imager. For TBSS analysis, the WM skeleton was created, and a 5000 permutation-based inference with a threshold of p < .05 was used, to enable the identification of abnormalities in fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD).

RESULTS

Decreased FA and increased RD, MD, and AD were seen in patients compared to controls and a decreased FA and increased MD and RD were seen, predominantly after the first 5 years of disease, when compared between groups.

CONCLUSION

Progressive WM deterioration is seen over time with a more prominent pattern after 5 years of disease onset, providing evidence that the early years might be a window to optimize treatment and prevent disability.

A translational MRI approach to validate acute axonal damage detection as an early event in multiple sclerosis

Axonal degeneration is a central pathological feature of multiple sclerosis and is closely associated with irreversible clinical disability. Current noninvasive methods to detect axonal damage in vivo are limited in their specificity and clinical applicability, and by the lack of proper validation. We aimed to validate an MRI framework based on multicompartment modeling of the diffusion signal (AxCaliber) in rats in the presence of axonal pathology, achieved through injection of a neurotoxin damaging the neuronal terminal of axons. We then applied the same MRI protocol to map axonal integrity in the brain of multiple sclerosis relapsing-remitting patients and age-matched healthy controls. AxCaliber is sensitive to acute axonal damage in rats, as demonstrated by a significant increase in the mean axonal caliber along the targeted tract, which correlated with neurofilament staining. Electron microscopy confirmed that increased mean axonal diameter is associated with acute axonal pathology. In humans with multiple sclerosis, we uncovered a diffuse increase in mean axonal caliber in most areas of the normal-appearing white matter, preferentially affecting patients with short disease duration. Our results demonstrate that MRI-based axonal diameter mapping is a sensitive and specific imaging biomarker that links noninvasive imaging contrasts with the underlying biological substrate, uncovering generalized axonal damage in multiple sclerosis as an early event.

LLDT-8 ameliorates experimental autoimmune encephalomyelitis by mediating macrophage functions in the priming stage

Multiple sclerosis (MS) is an inflammatory demyelinating disease in the central nervous system caused by T cell activation mediated by peripheral macrophages, resulting in severe neurological deficits and disability. Due to the currently limited and expensive treatments for MS, we here introduce an economic Chinese medicine extract, (5R)-5-Hydroxytriptolide (LLDT-8), which shows low toxicity and high immunosuppressive activity. We used the widely accepted mouse model of MS, experimental autoimmune encephalomyelitis (EAE), to examine the immunosuppressive effect of LLDT-8 in vivo. Through the RNA-sequence analysis of peripheral macrophages in EAE mice, we discovered that LLDT-8 alleviates the symptoms of EAE by inhibiting the proinflammatory effect of macrophages, thereby blocking the activation and proliferation of T cells. In all, we found that LLDT-8 could be a potential treatment for MS.

Advanced diffusion imaging reveals microstructural characteristics of primary CNS lymphoma, allowing differentiation from glioblastoma

Background

Primary CNS lymphoma (PCNSL) and glioblastoma (GBM) both represent frequent intracranial malignancies with differing clinical management. However, distinguishing PCNSL from GBM with conventional MRI can be challenging when atypical imaging features are present. We employed advanced dMRI for noninvasive characterization of the microstructure of PCNSL and differentiation from GBM as the most frequent primary brain malignancy.

Methods

Multiple dMRI metrics including Diffusion Tensor Imaging, Neurite Orientation Dispersion and Density Imaging, and Diffusion Microstructure Imaging were extracted from the contrast-enhancing tumor component in 10 PCNSL and 10 age-matched GBM on 3T MRI. Imaging findings were correlated with cell density and axonal markers obtained from histopathology.

Results

We found significantly increased intra-axonal volume fractions (V-intra and intracellular volume fraction) and microFA in PCNSL compared to GBM (all P < .001). In contrast, mean diffusivity (MD), axial diffusivity (aD), and microADC (all P < .001), and also free water fractions (V-CSF and V-ISO) were significantly lower in PCNSL (all P < .01). Receiver-operating characteristic analysis revealed high predictive values regarding the presence of a PCNSL for MD, aD, microADC, V-intra, ICVF, microFA, V-CSF, and V-ISO (area under the curve [AUC] in all >0.840, highest for MD and ICVF with an AUC of 0.960). Comparative histopathology between PCNSL and GBM revealed a significantly increased cell density in PCNSL and the presence of axonal remnants in a higher proportion of samples.

Conclusions

Advanced diffusion imaging enables the characterization of the microstructure of PCNSL and reliably distinguishes PCNSL from GBM. Both imaging and histopathology revealed a relatively increased cell density and a preserved axonal microstructure in PCNSL.

Treatment reduces the incidence of newly appearing multiple sclerosis lesions evolving into chronic active, slowly expanding lesions: A retrospective analysis

BACKGROUND AND PURPOSE

Newly appearing lesions in multiple sclerosis (MS) may evolve into chronically active, slowly expanding lesions (SELs), leading to sustained disability progression. The aim of this study was to evaluate the incidence of newly appearing lesions developing into SELs, and their correlation to clinical evolution and treatment.

METHODS

A retrospective analysis of a fingolimod trial in primary progressive MS (PPMS; INFORMS, NCT00731692) was undertaken. Data were available from 324 patients with magnetic resonance imaging scans up to 3 years after screening. New lesions at year 1 were identified with convolutional neural networks, and SELs obtained through a deformation-based method. Clinical disability was assessed annually by Expanded Disability Status Scale (EDSS), Nine-Hole Peg Test, Timed 25-Foot Walk, and Paced Auditory Serial Addition Test. Linear, logistic, and mixed-effect models were used to assess the relationship between the Jacobian expansion in new lesions and SELs, disability scores, and treatment status.

RESULTS

One hundred seventy patients had ≥1 new lesions at year 1 and had a higher lesion count at screening compared to patients with no new lesions (median = 27 vs. 22, p = 0.007). Among the new lesions (median = 2 per patient), 37% evolved into definite or possible SELs. Higher SEL volume and count were associated with EDSS worsening and confirmed disability progression. Treated patients had lower volume and count of definite SELs (β = -0.04, 95% confidence interval [CI] = -0.07 to -0.01, p = 0.015; β = -0.36, 95% CI = -0.67 to -0.06, p = 0.019, respectively).

CONCLUSIONS

Incident chronic active lesions are common in PPMS, and fingolimod treatment can reduce their number.

A systematic review of microstructural abnormalities in multiple sclerosis detected with NODDI and DTI models of diffusion-weighted magnetic resonance imaging

Multiple sclerosis (MS), namely the phenotype of the relapsing-remitting form, is the most common white matter disease and is mostly characterized by demyelination and inflammation, which lead to neurodegeneration and cognitive decline. Its diagnosis and monitoring are performed through conventional structural MRI, in which T2-hyperintense lesions can be identified, but this technique lacks sensitivity and specificity, mainly in detecting damage to normal appearing tissues. Models of diffusion-weighted MRI such as diffusion-tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) allow to uncover microstructural abnormalities that occur in MS, mainly in normal appearing tissues such as the normal appearing white matter (NAWM), which allows to overcome limitations of conventional MRI. DTI is the standard method used for modelling this kind of data, but it has limitations, which can be tackled by using more complex diffusion models, such as NODDI, which provides additional information on morphological properties of tissues. Although there are several studies in MS using both diffusion models, there is no formal assessment that summarizes the findings of both methods in lesioned and normal appearing tissues, and whether one is more advantageous than the other. Hence, this systematic review aims to identify what microstructural abnormalities are seen in lesions and/or NAWM in relapsing-remitting MS while using two different approaches to modelling diffusion data, namely DTI and NODDI, and if one of them is more appropriate than the other or if they are complementary to each other. The search was performed using PubMed, which was last searched on November 2022, and aimed at finding studies that either utilized both DTI and NODDI in the same dataset, or only one of the methods. Eleven articles were included in this review, which included cohorts with a relatively low sample size (total number of patients = 254, total number of healthy controls = 240), and patients with a moderate disease duration, all with relapsing-remitting MS. Overall, studies found decreased fractional anisotropy (FA), neurite density index (NDI) and orientation dispersion index (ODI), and increased mean, axial and radial diffusivities (MD, AD and RD, respectively) in lesions, when compared to contralateral NAWM and healthy controls' white matter. Compared to healthy controls' white matter, NAWM showed lower FA and NDI and higher MD, AD, RD, and ODI. Results from the included articles confirm that there is active demyelination and inflammation in both lesions and NAWM, as well as loss in neurites, and that structural damage is not confined to focal lesions, which is in concordance with histological findings and results from other imaging techniques. Furthermore, NODDI is suggested to have higher sensitivity and specificity, as seen by inspecting imaging results, compared to DTI, while still being clinically feasible. The use of biomarkers derived from such advanced diffusion models in clinical practice could imply a better understanding of treatment efficacy and disease progression, without relying on the manifestation of clinical symptoms, such as relapses.

Non-lesional white matter in relapsing-remitting multiple sclerosis assessed by multicomponent T2 relaxation

INTRODUCTION

The purpose of the study is to investigate, by T2 relaxation, non-lesional white matter (WM) in relapsing-remitting (RR) multiple sclerosis (MS).

METHODS

Twenty stable RR MS patients underwent 1.5T Magnetic Resonance Imaging (MRI) with 3D Fluid-Attenuated Inversion-Recovery (FLAIR), 3D-T1-weighted, and T2-relaxation multi-echo sequences. The Lesion Segmentation Tool processed FLAIR images to identify focal lesions (FLs), whereas T1 images were segmented to identify WM and FL sub-volumes with T1 hypo-intensity. Non-lesional WM was obtained as the segmented WM, excluding FL volumes. The multi-echo sequence allowed decomposition into myelin water, intra-extracellular water, and free water (Fw), which were evaluated on the segmented non-lesional WM. Correlation analysis was performed between the non-lesional WM relaxation parameters and Expanded Disability Status Scale (EDSS), disease duration, patient age, and T1 hypo-intense FL volumes.

RESULTS

The T1 hypo-intense FL volumes correlated with EDSS. On the non-lesional WM, the median Fw correlated with EDSS, disease duration, age, and T1 hypo-intense FL volumes. Bivariate EDSS correlation of FL volumes and WM T2-relaxation parameters did not improve significance.

CONCLUSION

T2 relaxation allowed identifying subtle WM alterations, which significantly correlated with EDSS, disease duration, and age but do not seem to be EDSS-predictors independent from FL sub-volumes in stable RR patients. Particularly, the increase in the Fw component is suggestive of an uninvestigated prodromal phenomenon in brain degeneration.

Understanding the Pathophysiology and Magnetic Resonance Imaging of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders

Magnetic resonance imaging (MRI) has been extensively applied in the study of multiple sclerosis (MS), substantially contributing to diagnosis, differential diagnosis, and disease monitoring. MRI studies have significantly contributed to the understanding of MS through the characterization of typical radiological features and their clinical or prognostic implications using conventional MRI pulse sequences and further with the application of advanced imaging techniques sensitive to microstructural damage. Interpretation of results has often been validated by MRI-pathology studies. However, the application of MRI techniques in the study of neuromyelitis optica spectrum disorders (NMOSD) remains an emerging field, and MRI studies have focused on radiological correlates of NMOSD and its pathophysiology to aid in diagnosis, improve monitoring, and identify relevant prognostic factors. In this review, we discuss the main contributions of MRI to the understanding of MS and NMOSD, focusing on the most novel discoveries to clarify differences in the pathophysiology of focal inflammation initiation and perpetuation, involvement of normal-appearing tissue, potential entry routes of pathogenic elements into the CNS, and existence of primary or secondary mechanisms of neurodegeneration.

Increased cortical lesion load contributed to pathological changes beyond focal lesion in cortical gray matter of multiple sclerosis: a diffusion kurtosis imaging analysis

Biomarkers specific to cortical gray matter (cGM) pathological changes of multiple sclerosis (MS) are desperately needed to better understand the disease progression. The cGM damage occurs in cortical lesion (CL) and normal-appearing cGM (NAcGM) areas. While the association between CL load and cGM damage has been reported, little is known about how different CL types, i.e. intracortical lesion (ICL) and leukocortical lesion (LCL) would be associated with cGM damage. In our study, relapsing-remitting MS patients and healthy controls were divided into 4 groups according to CL load level. NAcGM diffusion kurtosis imaging (DKI)/diffusion tensor imaging (DTI) values and cGM volume (cGMV) were used to characterize the pathological changes in cGM. Univariate general linear model was used for group comparisons and stepwise regression analysis was used to assess the effects of ICL volume and LCL volume on NAcGM damage. We found peak values in DKI/DTI values, cGMV and neuropsychological scores in high CL load group. Kurtosis fractional anisotropy (KFA) was the most sensitive in characterizing NAcGM damage, and LCL volume related more to NAcGM damage. Our findings suggested KFA could become a surrogate biomarker to cGM damage, and LCL might be the main factor in whole brain NAcGM damage.

Paramagnetic rim lesions lead to pronounced diffuse periplaque white matter damage in multiple sclerosis

BACKGROUND

Paramagnetic rim lesions (PRLs) are an imaging biomarker in multiple sclerosis (MS), associated with a more severe disease.

OBJECTIVES

To determine quantitative magnetic resonance imaging (MRI) metrics of PRLs, lesions with diffuse susceptibility-weighted imaging (SWI)-hypointense signal (DSHLs) and SWI-isointense lesions (SILs), their surrounding periplaque area (PPA) and the normal-appearing white matter (NAWM).

METHODS

In a cross-sectional study, quantitative MRI metrics were measured in people with multiple sclerosis (pwMS) using the multi-dynamic multi-echo (MDME) sequence post-processing software "SyMRI."

RESULTS

In 30 pwMS, 59 PRLs, 74 DSHLs, and 107 SILs were identified. Beside longer T1 relaxation times of PRLs compared to DSHLs and SILs (2030.5 (1519-2540) vs 1615.8 (1403.3-1953.5) vs 1199.5 (1089.6-1334.6), both p < 0.001), longer T1 relaxation times were observed in the PRL PPA compared to the SIL PPA and the NAWM but not the DSHL PPA. Patients with secondary progressive multiple sclerosis (SPMS) had longer T1 relaxation times in PRLs compared to patients with late relapsing multiple sclerosis (lRMS) (2394.5 (2030.5-3040) vs 1869.3 (1491.4-2451.3), p = 0.015) and also in the PRL PPA compared to patients with early relapsing multiple sclerosis (eRMS) (982 (927-1093.5) vs 904.3 (793.3-958.5), p = 0.013).

CONCLUSION

PRLs are more destructive than SILs, leading to diffuse periplaque white matter (WM) damage. The quantitative MRI-based evaluation of the PRL PPA could be a marker for silent progression in pwMS.

Neurite Orientation Dispersion and Density Imaging in Multiple Sclerosis: A Systematic Review

Diffusion-weighted imaging has been applied to investigate alterations in multiple sclerosis (MS). In the last years, advanced diffusion models were used to identify subtle changes and early lesions in MS. Among these models, neurite orientation dispersion and density imaging (NODDI) is an emerging approach, quantifying specific neurite morphology in both grey (GM) and white matter (WM) tissue and increasing the specificity of diffusion imaging. In this systematic review, we summarized the NODDI findings in MS. A search was conducted on PubMed, Scopus, and Embase, which yielded a total number of 24 eligible studies. Compared to healthy tissue, these studies identified consistent alterations in NODDI metrics involving WM (neurite density index), and GM lesions (neurite density index), or normal-appearing WM tissue (isotropic volume fraction and neurite density index). Despite some limitations, we pointed out the potential of NODDI in MS to unravel microstructural alterations. These results might pave the way to a deeper understanding of the pathophysiological mechanism of MS. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 3.

Mapping tissue microstructure across the human brain on a clinical scanner with soma and neurite density image metrics

Soma and neurite density image (SANDI) is an advanced diffusion magnetic resonance imaging biophysical signal model devised to probe in vivo microstructural information in the gray matter (GM). This model requires acquisitions that include b values that are at least six times higher than those used in clinical practice. Such high b values are required to disentangle the signal contribution of water diffusing in soma from that diffusing in neurites and extracellular space, while keeping the diffusion time as short as possible to minimize potential bias due to water exchange. These requirements have limited the use of SANDI only to preclinical or cutting-edge human scanners. Here, we investigate the potential impact of neglecting water exchange in the SANDI model and present a 10-min acquisition protocol that enables to characterize both GM and white matter (WM) on 3 T scanners. We implemented analytical simulations to (i) evaluate the stability of the fitting of SANDI parameters when diminishing the number of shells; (ii) estimate the bias due to potential exchange between neurites and extracellular space in such reduced acquisition scheme, comparing it with the bias due to experimental noise. Then, we demonstrated the feasibility and assessed the repeatability and reproducibility of our approach by computing microstructural metrics of SANDI with AMICO toolbox and other state-of-the-art models on five healthy subjects. Finally, we applied our protocol to five multiple sclerosis patients. Results suggest that SANDI is a practical method to characterize WM and GM tissues in vivo on performant clinical scanners.

B cell depletion therapy does not resolve chronic active multiple sclerosis lesions

BACKGROUND

Chronic active lesions (CAL) in multiple sclerosis (MS) have been observed even in patients taking high-efficacy disease-modifying therapy, including B-cell depletion. Given that CAL are a major determinant of clinical progression, including progression independent of relapse activity (PIRA), understanding the predicted activity and real-world effects of targeting specific lymphocyte populations is critical for designing next-generation treatments to mitigate chronic inflammation in MS.

METHODS

We analyzed published lymphocyte single-cell transcriptomes from MS lesions and bioinformatically predicted the effects of depleting lymphocyte subpopulations (including CD20 B-cells) from CAL via gene-regulatory-network machine-learning analysis. Motivated by the results, we performed in vivo MRI assessment of PRL changes in 72 adults with MS, 46 treated with anti-CD20 antibodies and 26 untreated, over ∼2 years.

FINDINGS

Although only 4.3% of lymphocytes in CAL were CD20 B-cells, their depletion is predicted to affect microglial genes involved in iron/heme metabolism, hypoxia, and antigen presentation. In vivo, tracking 202 PRL (150 treated) and 175 non-PRL (124 treated), none of the treated paramagnetic rims disappeared at follow-up, nor was there a treatment effect on PRL for lesion volume, magnetic susceptibility, or T1 time. PIRA occurred in 20% of treated patients, more frequently in those with ≥4 PRL (p = 0.027).

INTERPRETATION

Despite predicted effects on microglia-mediated inflammatory networks in CAL and iron metabolism, anti-CD20 therapies do not fully resolve PRL after 2-year MRI follow up. Limited tissue turnover of B-cells, inefficient passage of anti-CD20 antibodies across the blood-brain-barrier, and a paucity of B-cells in CAL could explain our findings.

FUNDING

Intramural Research Program of NINDS, NIH; NINDS grants R01NS082347 and R01NS082347; Dr. Miriam and Sheldon G. Adelson Medical Research Foundation; Cariplo Foundation (grant #1677), FRRB Early Career Award (grant #1750327); Fund for Scientific Research (FNRS).

Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group

This article provides recommendations for implementing quantitative susceptibility mapping (QSM) for clinical brain research. It is a consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available give rise to the need in the neuroimaging community for guidelines on implementation. This article describes relevant considerations and provides specific implementation recommendations for all steps in QSM data acquisition, processing, analysis, and presentation in scientific publications. We recommend that data be acquired using a monopolar 3D multi-echo GRE sequence, that phase images be saved and exported in DICOM format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields should be removed within the brain mask using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of whole brain as a region of interest in the analysis, and QSM results should be reported with - as a minimum - the acquisition and processing specifications listed in the last section of the article. These recommendations should facilitate clinical QSM research and lead to increased harmonization in data acquisition, analysis, and reporting.

Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice

MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.

Detection of grey matter microstructural substrates of neurodegeneration in multiple sclerosis

Multiple sclerosis features complex pathological changes in grey matter that begin early and eventually lead to diffuse atrophy. Novel approaches to image grey-matter microstructural alterations in vivo are highly sought after and would enable more sensitive monitoring of disease activity and progression. This cross-sectional study aimed to assess the sensitivity of high-gradient diffusion MRI for microstructural tissue damage in cortical and deep grey matter in people with multiple sclerosis and test the hypothesis that reduced cortical cell body density is associated with cortical and deep grey-matter volume loss. Forty-one people with multiple sclerosis (age 24-72, 14 females) and 37 age- and sex-matched healthy controls were scanned on a 3 T Connectom MRI scanner equipped with 300 mT/m gradients using a multi-shell diffusion MRI protocol. The soma and neurite density imaging model was fitted to high-gradient diffusion MRI data to obtain estimates of intra-neurite, intra-cellular and extra-cellular signal fractions and apparent soma radius. Cortical and deep grey-matter microstructural imaging metrics were compared between multiple sclerosis and healthy controls and correlated with grey-matter volume, clinical disability and cognitive outcomes. People with multiple sclerosis showed significant cortical and deep grey-matter volume loss compared with healthy controls. People with multiple sclerosis showed trends towards lower cortical intra-cellular signal fraction and significantly lower intra-cellular and higher extra-cellular signal fractions in deep grey matter, especially the thalamus and caudate, compared with healthy controls. Changes were most pronounced in progressive disease and correlated with the Expanded Disability Status Scale, but not the Symbol Digit Modalities Test. In multiple sclerosis, normalized thalamic volume was associated with thalamic microstructural imaging metrics. Whereas thalamic volume loss did not correlate with cortical volume loss, cortical microstructural imaging metrics were significantly associated with thalamic volume, and not with cortical volume. Compared with the short diffusion time (Δ = 19 ms) achievable on the Connectom scanner, at the longer diffusion time of Δ = 49 ms attainable on clinical scanners, multiple sclerosis-related changes in imaging metrics were generally less apparent with lower effect sizes in cortical and deep grey matter. Soma and neurite density imaging metrics obtained from high-gradient diffusion MRI data provide detailed grey-matter characterization beyond cortical and thalamic volumes and distinguish multiple sclerosis-related microstructural pathology from healthy controls. Cortical cell body density correlates with thalamic volume, appears sensitive to the microstructural substrate of neurodegeneration and reflects disability status in people with multiple sclerosis, becoming more pronounced as disability worsens.

CarveMix: A simple data augmentation method for brain lesion segmentation

Brain lesion segmentation provides a valuable tool for clinical diagnosis and research, and convolutional neural networks (CNNs) have achieved unprecedented success in the segmentation task. Data augmentation is a widely used strategy to improve the training of CNNs. In particular, data augmentation approaches that mix pairs of annotated training images have been developed. These methods are easy to implement and have achieved promising results in various image processing tasks. However, existing data augmentation approaches based on image mixing are not designed for brain lesions and may not perform well for brain lesion segmentation. Thus, the design of this type of simple data augmentation method for brain lesion segmentation is still an open problem. In this work, we propose a simple yet effective data augmentation approach, dubbed as CarveMix, for CNN-based brain lesion segmentation. Like other mixing-based methods, CarveMix stochastically combines two existing annotated images (annotated for brain lesions only) to obtain new labeled samples. To make our method more suitable for brain lesion segmentation, CarveMix is lesion-aware, where the image combination is performed with a focus on the lesions and preserves the lesion information. Specifically, from one annotated image we carve a region of interest (ROI) according to the lesion location and geometry with a variable ROI size. The carved ROI then replaces the corresponding voxels in a second annotated image to synthesize new labeled images for network training, and additional harmonization steps are applied for heterogeneous data where the two annotated images can originate from different sources. Besides, we further propose to model the mass effect that is unique to whole brain tumor segmentation during image mixing. To evaluate the proposed method, experiments were performed on multiple publicly available or private datasets, and the results show that our method improves the accuracy of brain lesion segmentation. The code of the proposed method is available at https://github.com/ZhangxinruBIT/CarveMix.git.

Myelin heterogeneity for assessing normal appearing white matter myelin damage in multiple sclerosis

BACKGROUND AND PURPOSE

Conventional MRI measures of multiple sclerosis (MS) disease severity, such as lesion volume and brain atrophy, do not provide information about microstructural tissue changes, which may be driving physical and cognitive progression. Myelin damage in normal-appearing white matter (NAWM) is likely an important contributor to MS disability. Myelin water fraction (MWF) provides quantitative measurements of myelin. Mean MWF reflects average myelin content, while MWF standard deviation (SD) describes variation in myelin within regions. The myelin heterogeneity index (MHI = SD/mean MWF) is a composite metric of myelin content and myelin variability. We investigated how mean MWF, SD, and MHI compare in differentiating MS from controls and their associations with physical and cognitive disability.

METHODS

Myelin water imaging data were acquired from 91 MS participants and 31 healthy controls (HC). Segmented whole-brain NAWM and corpus callosum (CC) NAWM, mean MWF, SD, and MHI were compared between groups. Associations of mean MWF, SD, and MHI with Expanded Disability Status Scale and Symbol Digit Modalities Test were assessed.

RESULTS

NAWM and CC MHI had the highest area under the curve: .78 (95% confidence interval [CI]: .69, .86) and .84 (95% CI: .76, .91), respectively, distinguishing MS from HC.

CONCLUSIONS

Mean MWF, SD, and MHI provide complementary information when assessing regional and global NAWM abnormalities in MS and associations with clinical outcome measures. Examining all three metrics (mean MWF, SD, and MHI) enables a more detailed interpretation of results, depending on whether regions of interest include areas that are more heterogeneous, earlier in the demyelination process, or uniformly injured.

Korean Red Ginseng and Rb1 facilitate remyelination after cuprizone diet-induced demyelination

Background

Demyelination has been observed in neurological disorders, motivating researchers to search for components for enhancing remyelination. Previously we found that Rb1, a major ginsenoside in Korean Red Ginseng (KRG), enhances myelin formation. However, it has not been studied whether Rb1 or KRG function in remyelination after demyelination in vivo.

Methods

Mice were fed 0.2% cuprizone-containing chow for 5 weeks and returned to normal chow with daily oral injection of vehicle, KRG, or Rb1 for 3 weeks. Brain sections were stained with luxol fast blue (LFB) staining or immunohistochemistry. Primary oligodendrocyte or astrocyte cultures were subject to normal or stress condition with KRG or Rb1 treatment to measure gene expressions of myelin, endoplasmic reticulum (ER) stress, antioxidants and leukemia inhibitory factor (LIF).

Results

Compared to the vehicle, KRG or Rb1 increased myelin levels at week 6.5 but not 8, when measured by the LFB⁺ or GST-pi⁺ area within the corpus callosum. The levels of oligodendrocyte precursor cells, astrocytes, and microglia were high at week 5, and reduced afterwards but not changed by KRG or Rb1. In primary oligodendrocyte cultures, KRG or Rb1 increased expression of myelin genes, ER stress markers, and antioxidants. Interestingly, under cuprizone treatment, elevated ER stress markers were counteracted by KRG or Rb1. Under rotenone treatment, reduced myelin gene expressions were recovered by Rb1. In primary astrocyte cultures, KRG or Rb1 decreased LIF expression.

Conclusion

KRG and Rb1 may improve myelin regeneration during the remyelination phase in vivo, potentially by directly promoting myelin gene expression.

NODDI, diffusion tensor microstructural abnormalities and atrophy of brain white matter and gray matter contribute to cognitive impairment in multiple sclerosis

BACKGROUND

Pathologically specific MRI measures may elucidate in-vivo the heterogeneous processes contributing to cognitive impairment in multiple sclerosis (MS).

PURPOSE

Using diffusion tensor and neurite orientation dispersion and density imaging (NODDI), we explored the contribution of focal lesions and normal-appearing (NA) tissue microstructural abnormalities to cognitive impairment in MS.

METHODS

One hundred and fifty-two MS patients underwent 3 T brain MRI and a neuropsychological evaluation. Forty-eight healthy controls (HC) were also scanned. Fractional anisotropy (FA), mean diffusivity (MD), intracellular volume fraction (ICV_f) and orientation dispersion index (ODI) were assessed in cortical and white matter (WM) lesions, thalamus, NA cortex and NAWM. Predictors of cognitive impairment were identified using random forest.

RESULTS

Fifty-two MS patients were cognitively impaired. Compared to cognitively preserved, impaired MS patients had higher WM lesion volume (LV), lower normalized brain volume (NBV), cortical volume (NCV), thalamic volume (NTV), and WM volume (p ≤ 0.021). They also showed lower NAWM FA, higher NAWM, NA cortex and thalamic MD, lower NAWM ICV_f, lower WM lesion ODI, and higher NAWM ODI (false discovery rate-p ≤ 0.026). Cortical lesion number and microstructural abnormalities were not significantly different. The best MRI predictors of cognitive impairment (relative importance) (out-of-bag area under the curve = 0.727) were NAWM FA (100%), NTV (96.0%), NBV (84.7%), thalamic MD (43.4%), NCV (40.6%), NA cortex MD (26.0%), WM LV (23.2%) and WM lesion ODI (17.9%).

CONCLUSIONS

Our multiparametric MRI study including NODDI measures suggested that neuro-axonal damage and loss of microarchitecture integrity in focal WM lesions, NAWM, and GM contribute to cognitive impairment in MS.

Associations between myelin water imaging and measures of fall risk and functional mobility in multiple sclerosis

BACKGROUND AND PURPOSE

Myelin water fraction (MWF) deficits as measured by myelin water imaging (MWI) have been related to worse motor function in persons with multiple sclerosis (PwMS). However, it is unknown if measures from MWI metrics in motor areas relate to fall risk measures in PwMS. The objective of this study was to examine the relationship between MWI measures in motor areas to performance on clinical measures of fall risk and disability in PwMS.

METHODS

Sixteen individuals with relapsing-remitting MS participated (1 male, 15 female; age 47.1 years [12.3]; Expanded Disability Status Scale 4.0 [range 0-6.5]) and completed measures of walking and fall risk (Timed 25 Foot Walk [T25FW] and Timed Up and Go). MWF and the geometric mean of the intra-/extracellular water T₂ (geomT_2IEW ) values reflecting myelin content and contribution of large-diameter axons/density, respectively, were assessed in three motor-related regions.

RESULTS

The geomT_2IEW of the corticospinal tract (r = -.599; p = .018) and superior cerebellar peduncles (r = -.613; p = .015) demonstrated significant inverse relationships with T25FW, suggesting that decreased geomT_2IEW was related to slower walking. Though not significant, MWF in the corticospinal tract and superior cerebellar peduncles also demonstrated fair relationships with the T25FW, suggesting that worse performance on the T25FW was associated with lower MWF values.

CONCLUSIONS

MWI of key motor regions was associated with walking performance in PwMS. Further MWI studies are needed to identify relationships between pathology and clinical function in PwMS to guide targeted rehabilitation therapies aimed at preventing falls.

Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective

In recent years, the use of magnetic resonance imaging (MRI) for the diagnostic work-up of multiple sclerosis (MS) has evolved considerably. The 2017 McDonald criteria show high sensitivity and accuracy in predicting a second clinical attack in patients with a typical clinically isolated syndrome and allow an earlier diagnosis of MS. They have been validated, are evidence-based, simplify the clinical use of MRI criteria and improve MS patients' management. However, to limit the risk of misdiagnosis, they should be applied by expert clinicians only after the careful exclusion of alternative diagnoses. Recently, new MRI markers have been proposed to improve diagnostic specificity for MS and reduce the risk of misdiagnosis. The central vein sign and chronic active lesions (i.e., paramagnetic rim lesions) may increase the specificity of MS diagnostic criteria, but further effort is necessary to validate and standardize their assessment before implementing them in the clinical setting. The feasibility of subpial demyelination assessment and the clinical relevance of leptomeningeal enhancement evaluation in the diagnostic work-up of MS appear more limited. Artificial intelligence tools may capture MRI attributes that are beyond the human perception, and, in the future, artificial intelligence may complement human assessment to further ameliorate the diagnostic work-up and patients' classification. However, guidelines that ensure reliability, interpretability, and validity of findings obtained from artificial intelligence approaches are still needed to implement them in the clinical scenario. This review provides a summary of the most recent updates regarding the application of MRI for the diagnosis of MS.

Personalized maps of T1 relaxometry abnormalities provide correlates of disability in multiple sclerosis patients

OBJECTIVES AND AIMS

Quantitative MRI (qMRI) has greatly improved the sensitivity and specificity of microstructural brain pathology in multiple sclerosis (MS) when compared to conventional MRI (cMRI). More than cMRI, qMRI also provides means to assess pathology within the normal-appearing and lesion tissue. In this work, we further developed a method providing personalized quantitative T1 (qT1) abnormality maps in individual MS patients by modeling the age dependence of qT1 alterations. In addition, we assessed the relationship between qT1 abnormality maps and patients' disability, in order to evaluate the potential value of this measurement in clinical practice.

METHODS

We included 119 MS patients (64 relapsing-remitting MS (RRMS), 34 secondary progressive MS (SPMS), 21 primary progressive MS (PPMS)), and 98 Healthy Controls (HC). All individuals underwent 3T MRI examinations, including Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) for qT1 maps and High-Resolution 3D Fluid Attenuated Inversion Recovery (FLAIR) imaging. To calculate personalized qT1 abnormality maps, we compared qT1 in each brain voxel in MS patients to the average qT1 obtained in the same tissue (grey/white matter) and region of interest (ROI) in healthy controls, hereby providing individual voxel-based Z-score maps. The age dependence of qT1 in HC was modeled using linear polynomial regression. We computed the average qT1 Z-scores in white matter lesions (WMLs), normal-appearing white matter (NAWM), cortical grey matter lesions (GMcLs) and normal-appearing cortical grey matter (NAcGM). Lastly, a multiple linear regression (MLR) model with the backward selection including age, sex, disease duration, phenotype, lesion number, lesion volume and average Z-score (NAWM/NAcGM/WMLs/GMcLs) was used to assess the relationship between qT1 measures and clinical disability (evaluated with EDSS).

RESULTS

The average qT1 Z-score was higher in WMLs than in NAWM. (WMLs: 1.366 ± 0.409, NAWM: -0.133 ± 0.288, [mean ± SD], p < 0.001). The average Z-score in NAWM in RRMS patients was significantly lower than in PPMS patients (p = 0.010). The MLR model showed a strong association between average qT1 Z-scores in white matter lesions (WMLs) and EDSS (R² = 0.549, β = 0.178, 97.5 % CI = 0.030 to 0.326, p = 0.019). Specifically, we measured a 26.9 % increase in EDSS per unit of qT1 Z-score in WMLs in RRMS patients (R² = 0.099, β = 0.269, 97.5 % CI = 0.078 to 0.461, p = 0.007).

CONCLUSIONS

We showed that personalized qT1 abnormality maps in MS patients provide measures related to clinical disability, supporting the use of those maps in clinical practice.

T1w/FLAIR ratio standardization as a myelin marker in MS patients

INTRODUCTION

Calculation of a T1w/T2w ratio was introduced as a proxy for myelin integrity in the brain of multiple sclerosis (MS) patients. Since nowadays 3D FLAIR is commonly used for lesion detection instead of T2w images, we introduce a T1w/FLAIR ratio as an alternative for the T1w/T2w ratio.

OBJECTIVES

Bias and intensity variation are widely present between different scanners, between subjects and within subjects over time in T1w, T2w and FLAIR images. We present a standardized method for calculating a histogram calibrated T1w/FLAIR ratio to reduce bias and intensity variation in MR sequences from different scanners and at different time-points.

MATERIAL AND METHODS

207 Relapsing Remitting MS patients were scanned on 4 different 3 T scanners with a protocol including 3D T1w, 2D T2w and 3D FLAIR images. After bias correction, T1w/FLAIR ratio maps and T1w/T2w ratio maps were calculated in 4 different ways: without calibration, with linear histogram calibration as described by Ganzetti et al. (2014), and by using 2 methods of non-linear histogram calibration. The first nonlinear calibration uses a template of extra-cerebral tissue and cerebrospinal fluid (CSF) brought from Montreal Neurological Institute (MNI) space to subject space; for the second nonlinear method we used an extra-cerebral tissue and CSF template of our own subjects. Additionally, we segmented several brain structures such as Normal Appearing White Matter (NAWM), Normal Appearing Grey Matter (NAGM), corpus callosum, thalami and MS lesions using Freesurfer and Samseg.

RESULTS

The coefficient of variation of T1w/FLAIR ratio in NAWM for the no calibrated, linear, and 2 nonlinear calibration methods were respectively 24, 19.1, 9.5, 13.8. The nonlinear methods of calibration showed the best results for calculating the T1w/FLAIR ratio with a smaller dispersion of the data and a smaller overlap of T1w/FLAIR ratio in the different segmented brain structures. T1w/T2w and T1w/FLAIR ratios showed a wider range of values compared to MTR values.

CONCLUSIONS

Calibration of T1w/T2w and T1w/FLAIR ratio maps is imperative to account for the sources of variation described above. The nonlinear calibration methods showed the best reduction of between-subject and within-subject variability. The T1w/T2w and T1w/FLAIR ratio seem to be more sensitive to smaller changes in tissue integrity than MTR. Future work is needed to determine the exact substrate of T1w/FLAIR ratio and to obtain correlations with clinical outcome.

Longitudinal microstructural MRI markers of demyelination and neurodegeneration in early relapsing-remitting multiple sclerosis: Magnetisation transfer, water diffusion and g-ratio

INTRODUCTION

Quantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS.

METHODS

Seventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained. 3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated. Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values.

RESULTS

In NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and -0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF.

DISCUSSION

G-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility.

CONCLUSION

MTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed.

High cortical iron is associated with the disruption of white matter tracts supporting cognitive function in healthy older adults

Aging is associated with brain iron accumulation, which has been linked to cognitive decline. However, how brain iron affects the structure and function of cognitive brain networks remains unclear. Here, we explored the possibility that iron load in gray matter is associated with disruption of white matter (WM) microstructure within a network supporting cognitive function, in a cohort of 95 cognitively normal older adults (age range: 60-86). Functional magnetic resonance imaging was used to localize a set of brain regions involved in working memory and diffusion tensor imaging based probabilistic tractography was used to identify a network of WM tracts connecting the functionally defined regions. Brain iron concentration within these regions was evaluated using quantitative susceptibility mapping and microstructural properties were assessed within the identified tracts using neurite orientation dispersion and density imaging. Results indicated that high brain iron concentration was associated with low neurite density (ND) within the task-relevant WM network. Further, regional associations were observed such that brain iron in cortical regions was linked with lower ND in neighboring but not distant WM tracts. Our results provide novel evidence suggesting that age-related increases in brain iron concentration are associated with the disruption of WM tracts supporting cognitive function in normal aging.

From pathology to MRI and back: Clinically relevant biomarkers of multiple sclerosis lesions

Focal lesions in both white and gray matter are characteristic of multiple sclerosis (MS). Histopathological studies have helped define the main underlying pathological processes involved in lesion formation and evolution, serving as a gold standard for many years. However, histopathology suffers from an intrinsic bias resulting from over-reliance on tissue samples from late stages of the disease or atypical cases and is inadequate for routine patient assessment. Pathological-radiological correlative studies have established advanced MRI's sensitivity to several relevant MS-pathological substrates and its practicality for assessing dynamic changes and following lesions over time. This review focuses on novel imaging techniques that serve as biomarkers of critical pathological substrates of MS lesions: the central vein, chronic inflammation, remyelination and repair, and cortical lesions. For each pathological process, we address the correlative value of MRI to MS pathology, its contribution in elucidating MS pathology in vivo, and the clinical utility of the imaging biomarker.

A whole-brain 3D myeloarchitectonic atlas: Mapping the Vogt-Vogt legacy to the cortical surface

Building precise and detailed parcellations of anatomically and functionally distinct brain areas has been a major focus in Neuroscience. Pioneer anatomists parcellated the cortical manifold based on extensive histological studies of post-mortem brain, harnessing local variations in cortical cyto- and myeloarchitecture to define areal boundaries. Compared to the cytoarchitectonic field, where multiple neuroimaging studies have recently translated this old legacy data into useful analytical resources, myeloarchitectonics, which parcellate the cortex based on the organization of myelinated fibers, has received less attention. Here, we present the neocortical surface-based myeloarchitectonic atlas based on the histology-derived maps of the Vogt-Vogt school and its 2D translation by Nieuwenhuys. In addition to a myeloarchitectonic parcellation, our package includes intracortical laminar profiles of myelin content based on Vogt-Vogt-Hopf original publications. Histology-derived myelin density mapped on our atlas demonstrated a close overlap with in vivo quantitative MRI markers for myelin and relates to cytoarchitectural features. Complementing the existing battery of approaches for digital cartography, the whole-brain myeloarchitectonic atlas offers an opportunity to validate imaging surrogate markers of myelin in both health and disease.

A comparative assessment of myelin-sensitive measures in multiple sclerosis patients and healthy subjects

INTRODUCTION

Multiple Sclerosis (MS) is a common neurological disease primarily characterized by myelin damage in lesions and in normal - appearing white and gray matter (NAWM, NAGM). Several quantitative MRI (qMRI) methods are sensitive to myelin characteristics by measuring specific tissue biophysical properties. However, there are currently few studies assessing the relative reproducibility and sensitivity of qMRI measures to MS pathology in vivo in patients.

METHODS

We performed two studies. The first study assessed of the sensitivity of qMRI measures to MS pathology: in this work, we recruited 150 MS and 100 healthy subjects, who underwent brain MRI at 3 T including quantitative T1 mapping (qT1), quantitative susceptibility mapping (QSM), magnetization transfer saturation imaging (MTsat) and myelin water imaging for myelin water fraction (MWF). The sensitivity of qMRIs to MS focal pathology (MS lesions vs peri-plaque white/gray matter (PPWM/PPGM)) was studied lesion-wise; the sensitivity to diffuse normal appearing (NA) pathology was measured using voxel-wise threshold-free cluster enhancement (TFCE) in NAWM and vertex-wise inflated cortex analysis in NAGM. Furthermore, the sensitivity of qMRI to the identification of lesion tissue was investigated using a voxel-wise logistic regression analysis to distinguish MS lesion and PP voxels. The second study assessed the reproducibility of myelin-sensitive qMRI measures in a single scanner. To evaluate the intra-session and inter-session reproducibility of qMRI measures, we have investigated 10 healthy subjects, who underwent two brain 3 T MRIs within the same day (without repositioning), and one after 1-week interval. Five region of interest (ROIs) in white and deep grey matter areas were segmented, and inter- and intra- session reproducibility was studied using the intra-class correlation coefficient (ICC). Further, we also investigated the voxel-wise reproducibility of qMRI measures in NAWM and NAGM.

RESULTS

qT1 and QSM showed the highest sensitivity to distinguish MS focal WM and cortical pathology from peri-plaque WM (P < 0.0001), although QSM also showed the highest variance when applied to lesions. MWF and MTsat exhibited the highest sensitivity to NAWM pathology (P < 0.01). On the other hand, qT1 appeared to be the most sensitive measure to NAGM pathology (P < 0.01). All myelin-sensitive qMRI measures exhibited high inter/intra sessional ICCs in various WM and deep GM ROIs, in NAWM and in NAGM (ICC 0.82 ± 0.12).

CONCLUSION

This work shows that the applied qT1, MWF, MTsat and QSM are highly reproducible and exhibit differential sensitivity to focal and diffuse WM and GM pathology in MS patients.

Advanced diffusion MRI and image texture analysis detect widespread brain structural differences between relapsing-remitting and secondary progressive multiple sclerosis

Introduction

Disease development in multiple sclerosis (MS) causes dramatic structural changes, but the exact changing patterns are unclear. Our objective is to investigate the differences in brain structure locally and spatially between relapsing-remitting MS (RRMS) and its advanced form, secondary progressive MS (SPMS), through advanced analysis of diffusion magnetic resonance imaging (MRI) and image texture.

Methods

A total of 20 patients with RRMS and nine patients with SPMS from two datasets underwent 3T anatomical and diffusion tensor imaging (DTI). The DTI was harmonized, augmented, and then modeled, which generated six voxel- and sub-voxel-scale measures. Texture analysis focused on T2 and FLAIR MRI, which produced two phase-based measures, namely, phase congruency and weighted mean phase. Data analysis was 3-fold, i.e., histogram analysis of whole-brain normal appearing white matter (NAWM); region of interest (ROI) analysis of NAWM and lesions within three critical white matter tracts, namely, corpus callosum, corticospinal tract, and optic radiation; and along-tract statistics. Furthermore, by calculating the z-score of core-rim pathology within lesions based on diffusion measures, we developed a novel method to define chronic active lesions and compared them between cohorts.

Results

Histogram features from diffusion and all but one texture measure differentiated between RRMS and SPMS. Within-tract ROI analysis detected cohort differences in both NAWM and lesions of the corpus callosum body in three measures of neurite orientation and anisotropy. Along-tract statistics detected cohort differences from multiple measures, particularly lesion extent, which increased significantly in SPMS in posterior corpus callosum and optic radiations. The number of chronic active lesions were also significantly higher (by 5-20% over z-scores 0.5 and 1.0) in SPMS than RRMS based on diffusion anisotropy, neurite content, and diameter.

Conclusion

Advanced diffusion MRI and texture analysis may be promising approaches for thorough understanding of brain structural changes from RRMS to SPMS, thereby providing new insight into disease development mechanisms in MS.

Update on myelin imaging in neurological syndromes

PURPOSE OF REVIEW

Myelin water imaging (MWI) is generally regarded as the most rigorous approach for noninvasive, in-vivo measurement of myelin content, which has been histopathologically validated. As such, it has been increasingly applied to neurological diseases with white matter involvement, especially those affecting myelin. This review provides an overview of the most recent research applying MWI in neurological syndromes.

RECENT FINDINGS

Myelin water imaging has been applied in neurological syndromes including multiple sclerosis, Alzheimer's disease, Huntington's disease, traumatic brain injury, Parkinson's disease, cerebral small vessel disease, leukodystrophies and HIV. These syndromes generally showed alterations observable with MWI, with decreased myelin content tending to correlate with lower cognitive scores and worse clinical presentation. MWI has also been correlated with genetic variation in the APOE and PLP1 genes, demonstrating genetic factors related to myelin health.

SUMMARY

MWI can detect and quantify changes not observable with conventional imaging, thereby providing insight into the pathophysiology and disease mechanisms of a diverse range of neurological syndromes.