Association between pathological and MRI findings in multiple sclerosis

Artificial intelligence applied to MRI data to tackle key challenges in multiple sclerosis

Artificial intelligence (AI) is the branch of science aiming at creating algorithms able to carry out tasks that typically require human intelligence. In medicine, there has been a tremendous increase in AI applications thanks to increasingly powerful computers and the emergence of big data repositories. Multiple sclerosis (MS) is a chronic autoimmune condition affecting the central nervous system with a complex pathogenesis, a challenging diagnostic process strongly relying on magnetic resonance imaging (MRI) and a high and largely unexplained variability across patients. Therefore, AI applications in MS have the great potential of helping us better support the diagnosis, find markers for prognosis to eventually design more powerful randomised clinical trials and improve patient management in clinical practice and eventually understand the mechanisms of the disease. This topical review aims to summarise the recent advances in AI applied to MRI data in MS to illustrate its achievements, limitations and future directions.

Hippocampal subfields and thalamic nuclei associations with clinical outcomes in multiple sclerosis: An ultrahigh field MRI study

BACKGROUND

Previous studies have shown that thalamic and hippocampal neurodegeneration is associated with clinical decline in Multiple Sclerosis (MS). However, contributions of the specific thalamic nuclei and hippocampal subfields require further examination.

OBJECTIVE

Using 7 Tesla (7T) magnetic resonance imaging (MRI), we investigated the cross-sectional associations between functionally grouped thalamic nuclei and hippocampal subfields volumes and T1 relaxation times (T1-RT) and subsequent clinical outcomes in MS.

METHODS

High-resolution T1-weighted and T2-weighted images were acquired at 7T (n=31), preprocessed, and segmented using the Thalamus Optimized Multi Atlas Segmentation (THOMAS, for thalamic nuclei) and the Automatic Segmentation of Hippocampal Subfields (ASHS, for hippocampal subfields) packages. We calculated Pearson correlations between hippocampal subfields and thalamic nuclei volumes and T1-RT and subsequent multi-modal rater-determined and patient-reported clinical outcomes (∼2.5 years after imaging acquisition), correcting for confounders and multiple tests.

RESULTS

Smaller volume bilaterally in the anterior thalamus region correlated with worse performance in gait function, as measured by the Patient Determined Disease Steps (PDDS). Additionally, larger volume in most functional groups of thalamic nuclei correlated with better visual information processing and cognitive function, as measured by the Symbol Digit Modalities Test (SDMT). In bilateral medial and left posterior thalamic regions, there was an inverse association between volumes and T1-RT, potentially indicating higher tissue degeneration in these regions. We also observed marginal associations between the right hippocampal subfields (both volumes and T1-RT) and subsequent clinical outcomes, though they did not survive correction for multiple testing.

CONCLUSION

Ultrahigh field MRI identified markers of structural damage in the thalamic nuclei associated with subsequently worse clinical outcomes in individuals with MS. Longitudinal studies will enable better understanding of the role of microstructural integrity in these brain regions in influencing MS outcomes.

Vulnerability of Thalamic Nuclei at CSF Interface During the Entire Course of Multiple Sclerosis

BACKGROUND AND OBJECTIVES

Thalamic atrophy can be used as a proxy for neurodegeneration in multiple sclerosis (MS). Some data point toward thalamic nuclei that could be affected more than others. However, the dynamic of their changes during MS evolution and the mechanisms driving their differential alterations are still uncertain.

METHODS

We paired a large cohort of 1,123 patients with MS with the same number of healthy controls, all scanned with conventional 3D-T1 MRI. To highlight the main atrophic regions at the thalamic nuclei level, we validated a segmentation strategy consisting of deep learning-based synthesis of sequences, which were used for automatic multiatlas segmentation. Then, through a lifespan-based approach, we could model the dynamics of the 4 main thalamic nuclei groups.

RESULTS

All analyses converged toward a higher rate of atrophy for the posterior and medial groups compared with the anterior and lateral groups. We also demonstrated that focal MS white matter lesions were associated with atrophy of groups of nuclei when specifically located within the associated thalamocortical projections. The volumes of the most affected posterior group, but also of the anterior group, were better associated with clinical disability than the volume of the whole thalamus.

DISCUSSION

These findings point toward the thalamic nuclei adjacent to the third ventricle as more susceptible to neurodegeneration during the entire course of MS through potentiation of disconnection effects by regional factors. Because this information can be obtained even from standard T1-weighted MRI, this paves the way toward such an approach for future monitoring of patients with MS.

Synthesis and biological evaluation of radioiodinated benzoxazole and benzothiazole derivatives for imaging myelin in multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system that results from destruction of the myelin sheath. Due to heterogeneity of the symptoms and course of MS, periodic monitoring of disease activity is important for diagnosis and treatment. In the present study, we synthesized four radioiodinated benzoxazole (BO) and benzothiazole (BT) derivatives, and evaluated their utility as novel myelin imaging probes for single photon emission computed tomography (SPECT). In a biodistribution study using normal mice, three compounds ([125I]BO-1, [125I]BO-2, and [125I]BT-2) displayed moderate brain uptake (2.7, 2.9, and 2.8% ID/g, respectively) at 2 min postinjection. On ex vivo autoradiography using normal mice, [125I]BO-2 showed the most preferable ratio of radioactivity accumulation in white matter (myelin-rich region) versus gray matter (myelin-deficient region). In addition, the radioactivity of [125I]BO-2 was reduced in the lysophosphatidylcholine-induced demyelination region. In conclusion, [123I]BO-2 demonstrated the fundamental characteristics of a myelin imaging probe for SPECT.

Brain connectivity changes underlying depression and fatigue in relapsing-remitting multiple sclerosis: A systematic review

Multiple Sclerosis (MS) is an autoimmune disease affecting the central nervous system, characterised by neuroinflammation and neurodegeneration. Fatigue and depression are common, debilitating, and intertwined symptoms in people with relapsing-remitting MS (pwRRMS). An increased understanding of brain changes and mechanisms underlying fatigue and depression in RRMS could lead to more effective interventions and enhancement of quality of life. To elucidate the relationship between depression and fatigue and brain connectivity in pwRRMS we conducted a systematic review. Searched databases were PubMed, Web-of-Science and Scopus. Inclusion criteria were: studied participants with RRMS (n ≥ 20; ≥ 18 years old) and differentiated between MS subtypes; published between 2001-01-01 and 2023-01-18; used fatigue and depression assessments validated for MS; included brain structural, functional magnetic resonance imaging (fMRI) or diffusion MRI (dMRI). Sixty studies met the criteria: 18 dMRI (15 fatigue, 5 depression) and 22 fMRI (20 fatigue, 5 depression) studies. The literature was heterogeneous; half of studies reported no correlation between brain connectivity measures and fatigue or depression. Positive findings showed that abnormal cortico-limbic structural and functional connectivity was associated with depression. Fatigue was linked to connectivity measures in cortico-thalamic-basal-ganglial networks. Additionally, both depression and fatigue were related to altered cingulum structural connectivity, and functional connectivity involving thalamus, cerebellum, frontal lobe, ventral tegmental area, striatum, default mode and attention networks, and supramarginal, precentral, and postcentral gyri. Qualitative analysis suggests structural and functional connectivity changes, possibly due to axonal and/or myelin loss, in the cortico-thalamic-basal-ganglial and cortico-limbic network may underlie fatigue and depression in pwRRMS, respectively, but the overall results were inconclusive, possibly explained by heterogeneity and limited number of studies. This highlights the need for further studies including advanced MRI to detect more subtle brain changes in association with depression and fatigue. Future studies using optimised imaging protocols and validated depression and fatigue measures are required to clarify the substrates underlying these symptoms in pwRRMS.

Fostering quality of life in young adults living with multiple sclerosis: a pilot study of a co-created integrated intervention

Introduction

Multiple sclerosis (MS) is generally diagnosed at an early age, making the acceptance of this chronic disease challenging. Research dedicated to young adults with MS (YawMS) is still limited. A biopsychosocial co-created intervention for YawMS integrating social, physical and psychological activities was developed (ESPRIMO intervention) in order to improve the quality of life (QoL) and well-being. This pre-post intervention assessment study examines the feasibility of the ESPRIMO intervention and its signal of efficacy.

Methods

Inclusion criteria were: age 18-45 years, MS diagnosis, Expanded Disability Status Scale score < 3.5. After giving informed consent, YawMS completed a battery of questionnaires, which was repeated after the intervention. The battery included a bespoke feasibility scale, the COOP/WONCA charts, and the Short Form-12 Health Survey (SF-12).

Results

Fifty-three YAwMS were enrolled and 43 (81.1%) completed the intervention. The majority of the sample positively rated the pleasantness, usefulness and feasibility of the intervention. A significant change in the COOP/WONCA "general QoL" chart (t = 3.65; p < 0.01) and SF-12 mental wellbeing component (t = -3.17; p < 0.01) was found.

Discussion

ESPRIMO is an innovative intervention that is feasible; preliminary results show an improvement in QoL and mental wellbeing. Further studies are needed to test its efficacy and evaluate future implementation in health services.Clinical trial registration: ClinicalTrials.gov, NCT04431323.

Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis

BACKGROUND

Quantitative susceptibility mapping (QSM) is a quantitative measure based on magnetic resonance imaging sensitive to iron and myelin content. This makes QSM a promising non-invasive tool for multiple sclerosis (MS) in research and clinical practice.

OBJECTIVE

We performed a systematic review and meta-analysis on the use of QSM in MS.

METHODS

Our review was prospectively registered on PROSPERO (CRD42022309563). We searched five databases for studies published between inception and 30th April 2023. We identified 83 English peer-reviewed studies that applied QSM images on MS cohorts. Fifty-five included studies had at least one of the following outcome measures: deep grey matter QSM values in MS, either compared to healthy controls (HC) (k = 13) or correlated with the score on the Expanded Disability Status Scale (EDSS) (k = 7), QSM lesion characteristics (k = 22) and their clinical correlates (k = 17), longitudinal correlates (k = 11), histological correlates (k = 7), or correlates with other imaging techniques (k = 12). Two meta-analyses on deep grey matter (DGM) susceptibility data were performed, while the remaining findings could only be analyzed descriptively.

RESULTS

After outlier removal, meta-analyses demonstrated a significant increase in the basal ganglia susceptibility (QSM values) in MS compared to HC, caudate (k = 9, standardized mean difference (SDM) = 0.54, 95 % CI = 0.39-0.70, I2 = 46 %), putamen (k = 9, SDM = 0.38, 95 % CI = 0.19-0.57, I2 = 59 %), and globus pallidus (k = 9, SDM = 0.48, 95 % CI = 0.28-0.67, I2 = 60 %), whereas thalamic QSM values exhibited a significant reduction (k = 12, SDM = -0.39, 95 % CI = -0.66--0.12, I2 = 84 %); these susceptibility differences in MS were independent of age. Further, putamen QSM values positively correlated with EDSS (k = 4, r = 0.36, 95 % CI = 0.16-0.53, I2 = 0 %). Regarding rim lesions, four out of seven studies, representing 73 % of all patients, reported rim lesions to be associated with more severe disability. Moreover, lesion development from initial detection to the inactive stage is paralleled by increasing, plateauing (after about two years), and gradually decreasing QSM values, respectively. Only one longitudinal study provided clinical outcome measures and found no association. Histological data suggest iron content to be the primary source of QSM values in DGM and at the edges of rim lesions; further, when also considering data from myelin water imaging, the decrease of myelin is likely to drive the increase of QSM values within WM lesions.

CONCLUSIONS

We could provide meta-analytic evidence for DGM susceptibility changes in MS compared to HC; basal ganglia susceptibility is increased and, in the putamen, associated with disability, while thalamic susceptibility is decreased. Beyond these findings, further investigations are necessary to establish the role of QSM in MS for research or even clinical routine.

The changes of oxygen extraction fraction in different types of lesions in relapsing-remitting multiple sclerosis: A cross-sectional and longitudinal study

OBJECTIVES

To explore the oxygen metabolism level of different types of lesions in relapsing-remitting multiple sclerosis (RRMS) patients by oxygen extraction fraction (OEF) both cross-sectionally and longitudinally.

METHODS

Forty-six RRMS patients and forty-one healthy controls (HC) went MRI examination. The quantitative susceptibility mapping (QSM) and OEF map were reconstructed from a 3D multi-echo gradient echo sequence. MS lesions in white matter were classified as contrast-enhancing lesions (CELs) on post-gadolinium T1-weighted sequence, paramagnetic rim lesions (PRLs), hyperintense lesions and non-hyperintense lesions on QSM, respectively. The susceptibility and OEF of different types of lesions were compared. The susceptibility and OEF values were measured and compared among different types of lesions. Among these RRMS patients, seventeen had follow-up MRI and 232 lesions, and baseline to follow-up longitudinal changes in susceptibility and OEF were measured.

RESULTS

PRLs had higher susceptibility and lower OEF than CELs, hyperintense lesions, and non-hyperintense lesions. The hyperintense lesions had higher susceptibility and lower OEF than non-hyperintense lesions. In longitudinal changes, PRLs had susceptibility increased (P < 0.001) and OEF decreased (P < 0.001). The hyperintense lesions showed significant decreases in susceptibility (P = 0.020), and non-hyperintense lesions showed significant increases in OEF during follow-up (P = 0.005). Notably, hyperintense lesions may convert to PRLs or non-hyperintense lesions as time progresses, accompanied by changes of OEF and susceptibility in the lesions.

CONCLUSION

This study revealed tissue damage and oxygen metabolism level in different types of MS lesions. The OEF may contribute to further understanding the evolution of MS lesions.

T1/T2-weighted ratio: A feasible MRI biomarker in multiple sclerosis

T1/T2-weighted ratio is a novel magnetic resonance imaging (MRI) biomarker based on conventional sequences, related to microstructural integrity and with increasing use in multiple sclerosis (MS) research. Different from other advanced MRI techniques, this method has the advantage of being based on routinely acquired MRI sequences, a feature that enables analysis of retrospective cohorts with considerable clinical value. This article provides an overview of this method, describing the previous cross-sectional and longitudinal findings in the main MS clinical phenotypes and in different brain tissues: focal white matter (WM) lesions, normal-appearing white matter (NAWM), cortical gray matter (GM), and deep normal-appearing gray matter (NAGM). We also discuss the clinical associations, possible reasons for conflicting results, correlations with other MRI-based measures, and histopathological associations. We highlight the limitations of the biomarker itself and the methodology of each study. Finally, we update the reader on its potential use as an imaging biomarker in research.

MR Susceptibility Separation for Quantifying Lesion Paramagnetic and Diamagnetic Evolution in Relapsing-Remitting Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) lesion evolution may involve changes in diamagnetic myelin and paramagnetic iron. Conventional quantitative susceptibility mapping (QSM) can provide net susceptibility distribution, but not the discrete paramagnetic and diamagnetic components.

PURPOSE

To apply susceptibility separation (χ separation) to follow lesion evolution in MS with comparison to R2 */R2 ' /QSM.

STUDY TYPE

Longitudinal, prospective.

SUBJECTS

Twenty relapsing-remitting MS subjects (mean age: 42.5 ± 9.4 years, 13 females; mean years of symptoms: 4.3 ± 1.4 years).

FIELD STRENGTH/SEQUENCE

Three-dimensional multiple echo gradient echo (QSM and R2 * mapping), two-dimensional dual echo fast spin echo (R2 mapping), T2 -weighted fluid attenuated inversion recovery, and T1-weighted magnetization prepared gradient echo sequences at 3 T.

ASSESSMENT

Data were analyzed from two scans separated by a mean interval of 14.4 ± 2.0 months. White matter lesions on fluid-attenuated inversion recovery were defined by an automatic pipeline, then manually refined (by ZZ/AHW, 3/25 years' experience in MRI), and verified by a radiologist (MN, 25 years' experience in MS). Susceptibility separation yielded the paramagnetic and diamagnetic susceptibility content of each voxel. Lesions were classified into four groups based on the variation of QSM/R2 * or separated into positive/negative components from χ separation.

STATISTICAL TESTS

Two-sample paired t tests for assessment of longitudinal differences. Spearman correlation coefficients to assess associations between χ separation and R2 */R2 ' /QSM. Significant level: P < 0.005.

RESULTS

A total of 183 lesions were quantified. Categorizing lesions into groups based on χ separation demonstrated significant annual changes in QSM//R2 */R2 ' . When lesions were grouped based on changes in QSM and R2 *, both changing in unison yielded a significant dominant paramagnetic variation and both opposing yielded a dominant diamagnetic variation. Significant Spearman correlation coefficients were found between susceptibility-sensitive MRI indices and χ separation.

DATA CONCLUSION

Susceptibility separation changes in MS lesions may distinguish and quantify paramagnetic and diamagnetic evolution, potentially providing additional insight compared to R2 * and QSM alone.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

MRI features and disability in multiple sclerosis: A systematic review and meta-analysis

BACKGROUND

In this systematic review and meta-analysis, we aimed to investigate the correlation between disability in patients with Multiple sclerosis (MS) measured by the Expanded Disability Status Scale (EDSS) and brain Magnetic Resonance Imaging (MRI) features to provide reliable results on which characteristics in the MRI can predict disability and prognosis of the disease.

METHODS

A systematic literature search was performed using three databases including PubMed, Scopus, and Web of Science. The selected peer-reviewed studies must report a correlation between EDSS scores and MRI features. The correlation coefficients of included studies were converted to the Fisher's z scale, and the results were pooled.

RESULTS

Overall, 105 studies A total of 16,613 patients with MS entered our study. We found no significant correlation between total brain volume and EDSS assessment (95 % CI: -0.37 to 0.08; z-score: -0.15). We examined the potential correlation between the volume of T1 and T2 lesions and the level of disability. A positive significant correlation was found (95 % CI: 0.19 to 0.43; z-score: 0.31), (95 % CI: 0.17 to 0.33; z-score: 0.25). We observed a significant correlation between white matter volume and EDSS score in patients with MS (95 % CI: -0.37 to -0.03; z-score: -0.21). Moreover, there was a significant negative correlation between gray matter volume and disability (95 % CI: -0.025 to -0.07; z-score: -0.16).

CONCLUSION

In conclusion, this systematic review and meta-analysis revealed that disability in patients with MS is linked to extensive changes in different brain regions, encompassing gray and white matter, as well as T1 and T2 weighted MRI lesions.

An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression

INTRODUCTION

While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear.

AREAS COVERED

The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning.

EXPERT OPINION

Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.

Validating a minipig model of reversible cerebral demyelination using human diagnostic modalities and electron microscopy

BACKGROUND

Inflammatory demyelinating diseases of the central nervous system, such as multiple sclerosis, are significant sources of morbidity in young adults despite therapeutic advances. Current murine models of remyelination have limited applicability due to the low white matter content of their brains, which restricts the spatial resolution of diagnostic imaging. Large animal models might be more suitable but pose significant technological, ethical and logistical challenges.

METHODS

We induced targeted cerebral demyelinating lesions by serially repeated injections of lysophosphatidylcholine in the minipig brain. Lesions were amenable to follow-up using the same clinical imaging modalities (3T magnetic resonance imaging, 11C-PIB positron emission tomography) and standard histopathology protocols as for human diagnostics (myelin, glia and neuronal cell markers), as well as electron microscopy (EM), to compare against biopsy data from two patients.

FINDINGS

We demonstrate controlled, clinically unapparent, reversible and multimodally trackable brain white matter demyelination in a large animal model. De-/remyelination dynamics were slower than reported for rodent models and paralleled by a degree of secondary axonal pathology. Regression modelling of ultrastructural parameters (g-ratio, axon thickness) predicted EM features of cerebral de- and remyelination in human data.

INTERPRETATION

We validated our minipig model of demyelinating brain diseases by employing human diagnostic tools and comparing it with biopsy data from patients with cerebral demyelination.

FUNDING

This work was supported by the DFG under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy, ID 390857198) and TRR 274/1 2020, 408885537 (projects B03 and Z01).

Prognostic value of single-subject grey matter networks in early multiple sclerosis

The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P-values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors.

Blood-brain barrier dysfunction in multiple sclerosis: causes, consequences, and potential effects of therapies

Established by brain endothelial cells, the blood-brain barrier (BBB) regulates the trafficking of molecules, restricts immune cell entry into the CNS, and has an active role in neurovascular coupling (the regulation of cerebral blood flow to support neuronal activity). In the early stages of multiple sclerosis, around the time of symptom onset, inflammatory BBB damage is accompanied by pathogenic immune cell infiltration into the CNS. In the later stages of multiple sclerosis, dysregulation of neurovascular coupling is associated with grey matter atrophy. Genetic and environmental factors associated with multiple sclerosis, including dietary habits, the gut microbiome, and vitamin D concentrations, might contribute directly and indirectly to brain endothelial cell dysfunction. Damage to brain endothelial cells leads to an influx of deleterious molecules into the CNS, accelerating leakage across the BBB. Potential future therapeutic approaches might help to prevent BBB damage (eg, monoclonal antibodies targeting cell adhesion molecules and fibrinogen) and help to repair BBB dysfunction (eg, mesenchymal stromal cells) in people with multiple sclerosis.

Influence of cardiorespiratory fitness and MRI measures of neuroinflammation on hippocampal volume in multiple sclerosis

BACKGROUND

The hippocampus is a clinically relevant region where neurogenesis and neuroplasticity occur throughout the whole lifespan. Neuroinflammation and cardiorespiratory fitness (CRF) may influence hippocampal integrity by modulating the processes promoting neurogenesis and neuroprotection that contribute to the preservation of functions. This study aimed to investigate the effects of neuroinflammation and CRF on hippocampal volume in multiple sclerosis (MS) patients with relapsing-remitting (RR) and progressive (P) clinical phenotypes. The influence of neuroinflammation and CRF on brain, grey matter (GM) and thalamic volumes was also assessed to determine whether the effects were specific for the hippocampus.

METHOD

Brain 3T structural MRI scans and maximum oxygen consumption (VO2max), a proxy of CRF, were acquired from 81 MS patients (27 RR and 54 P) and 45 age-matched and sex-matched healthy controls. T2-hyperintense white matter lesion volume (T2-LV) and choroid plexuses volume (CPV) were quantified as neuroinflammatory measures. Associations of demographic, clinical, neuroinflammatory and CRF measures with normalised brain, GM, hippocampal and thalamic volumes in relapsing-remitting MS (RRMS) and progressive MS patients were assessed using Shapley and best subset selection regression.

RESULTS

For most volumetric measures, the largest portions of variance were explained by T2-LV (variable importance (VI)=9.4-39.4) and CPV (VI=4.5-26.2). VO2max explained the largest portion of variance of normalised hippocampal volume only in RRMS patients (VI=16.9) and was retained as relevant predictor (standardised β=0.374, p=0.023) with T2-LV (standardised β=-0.330, p=0.016).

CONCLUSIONS

A higher CRF may play a specific neuroprotective role on MS patients' hippocampal integrity, but only in the RR phase of the disease.

Super-resolution QSM in little or no additional time for imaging (NATIve) using 2D EPI imaging in 3 orthogonal planes

Quantitative Susceptibility Mapping has the potential to provide additional insights into neurological diseases but is typically based on a quite long (5-10 min) 3D gradient-echo scan which is highly sensitive to motion. We propose an ultra-fast acquisition based on three orthogonal (sagittal, coronal and axial) 2D simultaneous multi-slice EPI scans with 1 mm in-plane resolution and 3 mm thick slices. Images in each orientation are corrected for susceptibility-related distortions and co-registered with an iterative non-linear Minimum Deformation Averaging (Volgenmodel) approach to generate a high SNR, super-resolution data set with an isotropic resolution of close to 1 mm. The net acquisition time is 3 times the volume acquisition time of EPI or about 12 s, but the three volumes could also replace "dummy scans" in fMRI, making it feasible to acquire QSM in little or No Additional Time for Imaging (NATIve). NATIve QSM values agreed well with reference 3D GRE QSM in the basal ganglia in healthy subjects. In patients with multiple sclerosis, there was also a good agreement between the susceptibility values within lesions and control ROIs and all lesions which could be seen on 3D GRE QSMs could also be visualized on NATIve QSMs. The approach is faster than conventional 3D GRE by a factor of 25-50 and faster than 3D EPI by a factor of 3-5. As a 2D technique, NATIve QSM was shown to be much more robust to motion than the 3D GRE and 3D EPI, opening up the possibility of studying neurological diseases involving iron accumulation and demyelination in patients who find it difficult to lie still for long enough to acquire QSM data with conventional methods.

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.

From Recognition to Remedy: The Significance of Biomarkers in Neurodegenerative Disease Pathology

With the inexorable aging of the global populace, neurodegenerative diseases (NDs) like Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) pose escalating challenges, which are underscored by their socioeconomic repercussions. A pivotal aspect in addressing these challenges lies in the elucidation and application of biomarkers for timely diagnosis, vigilant monitoring, and effective treatment modalities. This review delineates the quintessence of biomarkers in the realm of NDs, elucidating various classifications and their indispensable roles. Particularly, the quest for novel biomarkers in AD, transcending traditional markers in PD, and the frontier of biomarker research in ALS are scrutinized. Emergent susceptibility and trait markers herald a new era of personalized medicine, promising enhanced treatment initiation especially in cases of SOD1-ALS. The discourse extends to diagnostic and state markers, revolutionizing early detection and monitoring, alongside progression markers that unveil the trajectory of NDs, propelling forward the potential for tailored interventions. The synergy between burgeoning technologies and innovative techniques like -omics, histologic assessments, and imaging is spotlighted, underscoring their pivotal roles in biomarker discovery. Reflecting on the progress hitherto, the review underscores the exigent need for multidisciplinary collaborations to surmount the challenges ahead, accelerate biomarker discovery, and herald a new epoch of understanding and managing NDs. Through a panoramic lens, this article endeavors to provide a comprehensive insight into the burgeoning field of biomarkers in NDs, spotlighting the promise they hold in transforming the diagnostic landscape, enhancing disease management, and illuminating the pathway toward efficacious therapeutic interventions.

The Brainbox-a tool to facilitate correlation of brain magnetic resonance imaging features to histopathology

Magnetic resonance imaging (MRI) has limitations in identifying underlying tissue pathology, which is relevant for neurological diseases such as multiple sclerosis, stroke or brain tumours. However, there are no standardized methods for correlating MRI features with histopathology. Thus, here we aimed to develop and validate a tool that can facilitate the correlation of brain MRI features to corresponding histopathology. For this, we designed the Brainbox, a waterproof and MRI-compatible 3D printed container with an integrated 3D coordinate system. We used the Brainbox to acquire post-mortem ex vivo MRI of eight human brains, fresh and formalin-fixed, and correlated focal imaging features to histopathology using the built-in 3D coordinate system. With its built-in 3D coordinate system, the Brainbox allowed correlation of MRI features to corresponding tissue substrates. The Brainbox was used to correlate different MR image features of interest to the respective tissue substrate, including normal anatomical structures such as the hippocampus or perivascular spaces, as well as a lacunar stroke. Brain volume decreased upon fixation by 7% (P = 0.01). The Brainbox enabled degassing of specimens before scanning, reducing susceptibility artefacts and minimizing bulk motion during scanning. In conclusion, our proof-of-principle experiments demonstrate the usability of the Brainbox, which can contribute to improving the specificity of MRI and the standardization of the correlation between post-mortem ex vivo human brain MRI and histopathology. Brainboxes are available upon request from our institution.

Sex-related differences in upper limb motor function in healthy subjects and multiple sclerosis patients: a multiparametric MRI study

BACKGROUND

We investigated sex-related differences in upper limb motor performance tested with the 9-Hole Peg Test (9HPT) in healthy controls (HC) and multiple sclerosis (MS) patients and their MRI substrates.

MATERIALS AND METHODS

We enrolled 94 HC and 133 MS patients, who underwent neurological examination, 9HPT and brain 3T MRI, with sequences for regional grey matter volume (GMV), white matter (WM) fractional anisotropy (FA) and resting state (RS) functional connectivity (FC) analysis. Associations between MRI variables and 9HPT performance were analyzed with general linear models.

RESULTS

9HPT performance was better in HC vs MS patients, and in female vs male HC. Regional GMV analysis showed: associations between better 9HPT performance and higher GMV in motor and cognitive cortical areas in HC, with stronger positive correlations in females vs males. In MS, worse 9HPT performance correlated with lower volume in motor and cognitive areas. Sex-related differences were minimal and mostly found in cerebellar areas. WM FA analysis disclosed neither associations with 9HPT performance in HC, nor sex-related differences in MS. RS FC analysis showed: in the sensorimotor network, stronger associations of RS FC with 9HPT performance in female vs male HC and no sex-related differences in MS; in the cerebellar network, no sex-related differences in HC but stronger negative correlation in left cerebellum in male vs female MS patients.

CONCLUSIONS

Sex influences 9HPT performance in HC, mainly through differences in volume and RS FC of motor and cognitive areas. Sex-related effects on motor performance become secondary but still present in MS.

Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes

BACKGROUND

We aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct MS phenotypes.

METHODS

Clinical information and brain MRIs were collected from 221 healthy individuals and 823 people with MS at 8 MAGNIMS centres. The patients were divided into four clinical phenotypes: clinically isolated syndrome, relapsing-remitting, secondary progressive and primary progressive. Advanced tractography methods were used to obtain connectivity matrices. Then, differences in whole-brain and nodal graph-derived measures, and in the fractional anisotropy of connections between groups were analysed. Support vector machine algorithms were used to classify groups.

RESULTS

Clinically isolated syndrome and relapsing-remitting patients shared similar network changes relative to controls. However, most global and local network properties differed in secondary progressive patients compared with the other groups, with lower fractional anisotropy in most connections. Primary progressive participants had fewer differences in global and local graph measures compared with clinically isolated syndrome and relapsing-remitting patients, and reductions in fractional anisotropy were only evident for a few connections. The accuracy of support vector machine to discriminate patients from healthy controls based on connection was 81%, and ranged between 64% and 74% in distinguishing among the clinical phenotypes.

CONCLUSIONS

In conclusion, brain connectivity is disrupted in MS and has differential patterns according to the phenotype. Secondary progressive is associated with more widespread changes in connectivity. Additionally, classification tasks can distinguish between MS types, with subcortical connections being the most important factor.

Association of MRI leptomeningeal enhancement with disability worsening in progressive multiple sclerosis: A clinical and post-mortem study

BACKGROUND

Leptomeningeal enhancement (LME) has been described as a biomarker of meningeal inflammation in multiple sclerosis (MS).

OBJECTIVE

The aim of this study was to (1) assess if LME is predictive of disability worsening in progressive MS (pMS) patients and (2) investigate the pathological substrates of LME in an independent post-mortem MS series.

METHODS

In total, 115 pMS patients were imaged yearly with 1.5T MRI, using post-contrast CUBE 3D FLAIR for LME detection. Endpoint: to identify the baseline variables predictive of confirmed disability worsening (CDW) at 24 months follow-up. Post-mortem, inflammation, and structural changes of the leptomeninges were assessed in 12 MS/8 control brains.

RESULTS

LME (27% of patients at baseline) was associated with higher EDSS and lower brain volume (nBV). LME was unchanged in most patients over follow-up. LME at baseline MRI was independently associated with higher risk of 24 months CDW (HR 3.05, 95% CI 1.36-6.84, p = 0.007) in a Cox regression, including age, nBV, T2 lesion volume, high-efficacy treatments, and MRI disease activity. Post-mortem, focal structural changes (fibrosis) of the leptomeninges were observed in MS, usually associated with inflammation (Kendall's Tau 0.315, p < 0.0001).

CONCLUSIONS

LME is frequently detected in pMS patients using 1.5T MRI and is independently predictive of disability progression. LME could result from both focal leptomeningeal post-inflammatory fibrosis and inflammation.

White matter changes measured by multi-component MR Fingerprinting in multiple sclerosis

T2-hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties. We applied a fast, multi-parametric quantitative MRI approach and used a multi-component MR Fingerprinting (MC-MRF) analysis. We assessed the differences in the MRF component representing prolongedrelaxation time between patients with MS and controls and studied the relation between this component's volume and structural white matter damage identified on FLAIR MRI scans in patients with MS. A total of 48 MS patients at two different sites and 12 healthy controls were scanned with FLAIR and MRF-EPI MRI scans. MRF scans were analyzed with a joint-sparsity multi-component analysis to obtain magnetization fraction maps of different components, representing tissues such as myelin water, white matter, gray matter and cerebrospinal fluid. In the MS patients, an additional component was identified with increased transverse relaxation times compared to the white matter, likely representing changes in free water content. Patients with MS had a higher volume of the long- component in the white matter of the brain compared to healthy controls (B (95%-CI) = 0.004 (0.0006-0.008), p = 0.02). Furthermore, this MRF component had a moderate correlation (correlation coefficient R 0.47) with visible structural white matter changes on the FLAIR scans. Also, the component was found to be more extensive compared to structural white matter changes in 73% of MS patients. In conclusion, our MRF acquisition and analysis captured white matter tissue changes in MS patients compared to controls. In patients these tissue changes were more extensive compared to visually detectable white matter changes on FLAIR scans. Our method provides a novel way to quantify the extent of white matter changes in MS patients, which is underestimated using only conventional clinical MRI scans.

Do the current MS clinical course descriptors need to change and if so how? A survey of the MS community

BACKGROUND AND OBJECTIVES

The current clinical course descriptors of multiple sclerosis (MS) include a combination of clinical and magnetic resonance imaging (MRI) features. Recently there has been a growing call to base these descriptors more firmly on biological mechanisms. We investigated the implications of proposing a new mechanism-driven framework for describing MS.

METHODS

In a web-based survey, multiple stakeholders rated the need to change current MS clinical course descriptors, the definitions of disease course and their value in clinical practice and related topics.

RESULTS

We received 502 responses across 49 countries. In all, 77% of the survey respondents supported changing the current MS clinical course descriptors. They preferred a framework that informs treatment decisions, aids the design and conduct of clinical trials, allows patients to understand their disease, and links disease mechanisms and clinical expression of disease. Clinical validation before dissemination and ease of communication to patients were rated as the most important aspects to consider when developing any new framework for describing MS.

CONCLUSION

A majority of MS stakeholders agreed that the current MS clinical course descriptors need to change. Any change process will need to engage a wide range of affected stakeholders and be guided by foundational principles.

Iron in multiple sclerosis - Neuropathology, immunology, and real-world considerations

Iron is an essential element involved in a multitude of bodily processes. It is tightly regulated, as elevated deposition in tissues is associated with diseases such as multiple sclerosis (MS). Iron accumulation in the central nervous system (CNS) of MS patients is linked to neurotoxicity through mechanisms including oxidative stress, glutamate excitotoxicity, misfolding of proteins, and ferroptosis. In the past decade, the combination of MRI and histopathology has enhanced our understanding of iron deposition in MS pathophysiology, including in the pro-inflammatory and neurotoxicity of iron-laden rims of chronic active lesions. In this regard, iron accumulation may not only have an impact on different CNS-resident cells but may also promote the innate and adaptive immune dysfunctions in MS. Although there are discordant results, most studies indicate lower levels of iron but higher amounts of the iron storage molecule ferritin in the circulation of people with MS. Considering the importance of iron, there is a need for evidence-guided recommendation for dietary intake in people living with MS. Potential novel therapeutic approaches include the regulation of iron levels using next generation iron chelators, as well as therapies to interfere with toxic consequences of iron overload including antioxidants in MS.

Transcranial Magnetic Stimulation Measures, Pyramidal Score on Expanded Disability Status Scale and Magnetic Resonance Imaging of Corticospinal Tract in Multiple Sclerosis

Probing the cortic ospinal tract integrity by transcranial magnetic stimulation (TMS) could help to understand the neurophysiological correlations of multiple sclerosis (MS) symptoms. Therefore, the study objective was, first, to investigate TMS measures (resting motor threshold-RMT, motor evoked potential (MEP) latency, and amplitude) of corticospinal tract integrity in people with relapsing-remitting MS (pwMS). Then, the study examined the conformity of TMS measures with clinical disease-related (Expanded Disability Status Scale-EDSS) and magnetic resonance imaging (MRI) results (lesion count) in pwMS. The e-field navigated TMS, MRI, and EDSS data were collected in 23 pwMS and compared to non-clinical samples. The results show that pwMS differed from non-clinical samples in MEP latency for upper and lower extremity muscles. Also, pwMS with altered MEP latency (prolonged or absent MEP response) had higher EDSS, general and pyramidal, functional scores than pwMS with normal MEP latency finding. Furthermore, the RMT intensity for lower extremity muscles was predictive of EDSS functional pyramidal scores. TMS/MEP latency findings classified pwMS as the same as EDSS functional pyramidal scores in 70-83% of cases and were similar to the MRI results, corresponding to EDSS functional pyramidal scores in 57-65% of cases. PwMS with altered MEP latency differed from pwMS with normal MEP latency in the total number of lesions in the brain corticospinal and cervical corticospinal tract. The study provides preliminary results on the correspondence of MRI and TMS corticospinal tract evaluation results with EDSS functional pyramidal score results in MS.

Serum neurofilament light chain is more strongly associated with T2 lesion volume than with number of T2 lesions in patients with multiple sclerosis

BACKGROUND AND PURPOSE

MR imaging provides information on the number and extend of focal lesions in multiple sclerosis (MS) patients. This study explores whether total brain T2 lesion volume or lesion number shows a better correlation with serum and cerebrospinal fluid (CSF) biomarkers of disease activity.

MATERIALS AND METHODS

In total, 52 patients suffering from clinically isolated syndrome (CIS)/relapsing-remitting multiple sclerosis (RRMS) were assessed including MRI markers (total brain T2 lesion volume semi-automatically outlined on 3D DIR/FLAIR sequences, number of lesions), serum and CSF biomarkers at the time of neuroimaging (neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP)), and clinical parameters. After log-transformation and partial correlations adjusted for the covariates patients' age, BMI, EDSS-score and diagnosis, the Fisher's r-to-Z transformation was used to compare different correlation coefficients.

RESULTS

The correlation between lesion volume and serum NfL (r = 0.6, p < 0.001) was stronger compared to the association between the number of T2 lesions and serum NfL (r = 0.4, p < 0.01) (z = -2.0, p < 0.05). With regard to CSF NfL, there was a moderate, positive relationship for both number of T2 lesions and lesion volume (r = 0.5 respectively, p < 0.01). We found no significant association between MRI markers and GFAP levels.

CONCLUSION

Our findings suggest that there is a stronger association between serum NfL and T2 lesion volume, than there is between serum NfL and T2 lesion number. Improving robustness and accuracy of fully-automated lesion volume segmentation tools can expedite implementation into clinical routine and trials.

NfL and GFAP in serum are associated with microstructural brain damage in progressive multiple sclerosis

BACKGROUND

The potential of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) as biomarkers of disease activity and severity in progressive forms of multiple sclerosis (MS) is unclear.

OBJECTIVE

To investigate the relationship between serum concentrations of NfL, GFAP, and magnetic resonance imaging (MRI) in progressive MS.

METHODS

Serum concentrations of NfL and GFAP were measured in 32 healthy controls and 32 patients with progressive MS from whom clinical and MRI data including diffusion tensor imaging (DTI) were obtained during three years of follow-up.

RESULTS

Serum concentrations of NfL and GFAP at follow-up were higher in progressive MS patients than in healthy controls and serum NfL correlated with the EDSS score. Decreasing fractional anisotropy (FA) in normal-appearing white matter (NAWM) correlated with worsening EDSS scores and higher serum NfL. Higher serum NfL and increasing T2 lesion volume correlated with worsening paced autitory serial addition test scores. In multivariable regression analyses with serum GFAP and NfL as independent factors and DTI measures of NAWM as dependent factors, we showed that high serum NfL at follow-up was independently associated with decreasing FA and increasing MD in NAWM. Moreover, we found that high serum GFAP was independently associated with decreasing MD in NAWM and with decreasing MD and increasing FA in cortical gray matter.

CONCLUSION

Serum concentrations of NfL and GFAP are increased in progressive MS and are associated with distinct microstructural changes in NAWM and CGM.

Leukocyte telomere length in women with multiple sclerosis: Comparison with healthy women during pregnancy and puerperium

OBJECTIVES

Several studies indicated leukocyte telomere length (LTL) as a biomarker of multiple sclerosis (MS) evolution. This study aimed to investigate LTL in women with multiple sclerosis (MS) compared to that in healthy women (HW) across different reproductive phases, and to evaluate its relationship with MS activity.

METHODS

Blood samples were collected from women with MS and HW during the fertile phase, pregnancy, and puerperium. LTL was determined using quantitative fluorescence in situ hybridization (Q-FISH).

RESULTS

Blood samples from 68 women with MS (22 during fertile life, 23 during pregnancy, and 23 post-partum) and 52 HW (23 during fertile life, 20 during pregnancy, and 9 post-partum) were analyzed. During pregnancy, LTL in MS women and HW was 84.7 ± 10.5 and 77.6 ± 11.5, respectively (p < 0.005). Regression analysis showed that shorter LTL was associated with pregnancy in HW (p = 0.021); this relationship was not observed in MS women, for whom shorter LTL was related to a higher EDSS (p = 0.036). A longitudinal analysis was performed in eight MS women, showing LTL shortening from pregnancy to puerperium (p = 0.003), which was related to MS reactivation (p = 0.042).

CONCLUSION

Our results highlight the possible associations between LTL, reproductive biological phases, and MS activity after delivery.

Quantitative magnetic resonance mapping of the myelin bilayer reflects pathology in multiple sclerosis brain tissue

Multiple sclerosis (MS) is a neuroinflammatory disease characterized by loss of myelin (demyelination) and, to a certain extent, subsequent myelin repair (remyelination). To better understand the pathomechanisms underlying de- and remyelination and to monitor the efficacy of treatments aimed at regenerating myelin, techniques offering noninvasive visualizations of myelin are warranted. Magnetic resonance (MR) imaging has long been at the forefront of efforts to visualize myelin, but it has only recently become feasible to access the rapidly decaying resonance signals stemming from the myelin lipid-protein bilayer itself. Here, we show that direct MR mapping of the bilayer yields highly specific myelin maps in brain tissue from patients with MS. Furthermore, examination of the bilayer signal behavior is found to reveal pathological alterations in normal-appearing white and gray matter. These results indicate promise for in vivo implementations of the myelin bilayer mapping technique, with prospective applications in basic research, diagnostics, disease monitoring, and drug development.

CSF Markers of Oxidative Stress Are Associated with Brain Atrophy and Iron Accumulation in a 2-Year Longitudinal Cohort of Early MS

In this prospective longitudinal study, we quantified regional brain volume and susceptibility changes during the first two years after the diagnosis of multiple sclerosis (MS) and identified their association with cerebrospinal fluid (CSF) markers at baseline. Seventy patients underwent MRI (T1 and susceptibility weighted images processed to quantitative susceptibility maps, QSM) with neurological examination at the diagnosis and after two years. In CSF obtained at baseline, the levels of oxidative stress, products of lipid peroxidation, and neurofilaments light chain (NfL) were determined. Brain volumetry and QSM were compared with a group of 58 healthy controls. In MS patients, regional atrophy was identified in the striatum, thalamus, and substantia nigra. Magnetic susceptibility increased in the striatum, globus pallidus, and dentate and decreased in the thalamus. Compared to controls, MS patients developed greater atrophy of the thalamus, and a greater increase in susceptibility in the caudate, putamen, globus pallidus and a decrease in the thalamus. Of the multiple calculated correlations, only the decrease in brain parenchymal fraction, total white matter, and thalamic volume in MS patients negatively correlated with increased NfL in CSF. Additionally, negative correlation was found between QSM value in the substantia nigra and peroxiredoxin-2, and QSM value in the dentate and lipid peroxidation levels.

Microglia in the context of multiple sclerosis

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease that commonly results in nontraumatic disability in young adults. The characteristic pathological hallmark of MS is damage to myelin, oligodendrocytes, and axons. Microglia provide continuous surveillance in the CNS microenvironment and initiate defensive mechanisms to protect CNS tissue. Additionally, microglia participate in neurogenesis, synaptic refinement, and myelin pruning through the expression and release of different signaling factors. Continuous activation of microglia has been implicated in neurodegenerative disorders. We first review the lifetime of microglia, including the origin, differentiation, development, and function of microglia. We then discuss microglia participate in the whole processes of remyelination and demyelination, microglial phenotypes in MS, and the NF-κB/PI3K-AKT signaling pathway in microglia. The damage to regulatory signaling pathways may change the homeostasis of microglia, which would accelerate the progression of MS.

Granzyme B + CD8 + T cells with terminal differentiated effector signature determine multiple sclerosis progression

BACKGROUND

Multiple sclerosis (MS) leads to demyelination and neurodegeneration with autoimmune responses in central nervous system. Patients begin with a relapsing-remitting (RR) course, and more than 80% of them may advance to secondary progressive MS (SPMS), which is characteristic for the gradual decline of neurological functions without demonstrated treating method to prevent. This study aims to investigate the contribution of peripheral CD8 + T cells during the conversion from RRMS to SPMS, as well as reveal potential diagnostic signature in distinguishing SPMS.

METHODS

Single-cell RNA sequencing was employed to reveal the heterogeneity of CD8 + T cells between SPMS and RRMS. In addition, flow cytometry was used to further characterized CD8 + T cell dynamic changes in patients. T cell receptor sequencing was performed to detect the clonal expansion of MS. Using Tbx21 siRNA, T-bet was confirmed to manipulate GzmB expression. The correlation between GzmB + CD8 + T cell subsets and clinical characteristics of MS and their potential diagnostic value for SPMS were evaluated by generalized linear regression models and receiver operating characteristic (ROC) curve respectively.

RESULTS

Other than diminished naïve CD8 + T cell, elevating of activated CD8 + T cell subsets were observed in SPMS patients. Meanwhile, this aberrant amplified peripheral CD8 + T cells not only exhibited terminal differentiated effector (EMRA) phenotype with GzmB expression, but also possessed distinct trajectory from clonal expansion. In addition, T-bet acted as a key transcriptional factor that elicited GzmB expression in CD8 + T_EMRA cells of patients with SPMS. Finally, the expression of GzmB in CD8 + T cells was positively correlated with disability and progression of MS, and could effectively distinguish SPMS from RRMS with a high accuracy.

CONCLUSIONS

Our study mapped peripheral immune cells of RRMS and SPMS patients and provided an evidence for the involvement of GzmB + CD8 + T_EMRA cells in the progression of MS, which could be used as a diagnostic biomarker for distinguishing SPMS from RRMS.

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.

Unraveling the heterogeneous pathological substrates of relapse-onset multiple sclerosis: a multiparametric voxel-wise 3 T MRI study

BACKGROUND

In multiple sclerosis (MS), pathological processes affecting brain gray (GM) and white matter (WM) are heterogeneous.

OBJECTIVE

To apply a multimodal MRI approach to investigate the regional distribution of the different pathological processes occurring in the brain WM and GM of relapse-onset MS patients.

METHODS

Fifty-seven MS patients (forty-two relapsing remitting [RR], fifteen secondary progressive [SP]) and forty-seven age- and sex-matched healthy controls (HC) underwent a multimodal 3 T MRI acquisition. Between-group voxel-wise differences of brain WM and GM volumes, magnetization transfer ratio (MTR), T₁-weighted(w)/T₂w ratio, intracellular volume fraction (ICV_f), and quantitative susceptibility mapping (QSM) maps were investigated.

RESULTS

Compared to HC, RRMS showed significant WM, deep GM and cortical atrophy, significantly lower MTR and T₁w/T₂w ratio of periventricular and infratentorial WM, deep GM and several cortical areas, lower ICV_f in supratentorial and cerebellar WM and in some cortical areas, and lower QSM values in bilateral periventricular WM (p < 0.001). Compared to RRMS, SPMS patients showed significant deep GM and widespread cortical atrophy, significantly lower MTR of periventricular WM, deep GM and cerebellum, lower T₁w/T₂w ratio of fronto-temporal WM regions, lower ICV_f of some fronto-tempo-occipital WM and cortical areas. They also had increased QSM and T₁w/T₂w ratio in the pallidum, bilaterally (p < 0.001).

CONCLUSION

A periventricular pattern of demyelination and widespread GM and WM neuro-axonal loss are detectable in RRMS and are more severe in SPMS. Higher T₁w/T₂w ratio and QSM in the pallidum, possibly reflecting iron accumulation and neurodegeneration, may represent a relevant MRI marker to differentiate SPMS from RRMS.

Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset

Introduction

Conventional MRI is routinely used for the characterization of pathological changes in multiple sclerosis (MS), but due to its lack of specificity is unable to provide accurate prognoses, explain disease heterogeneity and reconcile the gap between observed clinical symptoms and radiological evidence. Quantitative MRI provides measures of physiological abnormalities, otherwise invisible to conventional MRI, that correlate with MS severity. Analyzing quantitative MRI measures through machine learning techniques has been shown to improve the understanding of the underlying disease by better delineating its alteration patterns.

Methods

In this retrospective study, a cohort of healthy controls (HC) and MS patients with different subtypes, followed up 15 years from clinically isolated syndrome (CIS), was analyzed to produce a multi-modal set of quantitative MRI features encompassing relaxometry, microstructure, sodium ion concentration, and tissue volumetry. Random forest classifiers were used to train a model able to discriminate between HC, CIS, relapsing remitting (RR) and secondary progressive (SP) MS patients based on these features and, for each classification task, to identify the relative contribution of each MRI-derived tissue property to the classification task itself.

Results and discussion

Average classification accuracy scores of 99 and 95% were obtained when discriminating HC and CIS vs. SP, respectively; 82 and 83% for HC and CIS vs. RR; 76% for RR vs. SP, and 79% for HC vs. CIS. Different patterns of alterations were observed for each classification task, offering key insights in the understanding of MS phenotypes pathophysiology: atrophy and relaxometry emerged particularly in the classification of HC and CIS vs. MS, relaxometry within lesions in RR vs. SP, sodium ion concentration in HC vs. CIS, and microstructural alterations were involved across all tasks.

The signal intensity variation of multiple sclerosis (MS) lesions on magnetic resonance imaging (MRI) as a potential biomarker for patients' disability: A feasibility study

Introduction

Although many lesion-based MRI biomarkers in multiple sclerosis (MS) patients were investigated, none of the previous studies dealt with the signal intensity variations (SIVs) of MS lesions. In this study, the SIVs of MS lesions on direct myelin imaging and standard clinical sequences as possible MRI biomarkers for disability in MS patients were assessed.

Methods

Twenty seven MS patients were included in this prospective study. IR-UTE, FLAIR, and MPRAGE sequences were employed on a 3T scanner. Regions of interest (ROIs) were manually drawn within the MS lesions, and the cerebrospinal fluid (CSF) and signal intensity ratios (SIR) were calculated from the derived values. Variations coefficients were determined from the standard deviations (Coeff 1) and the absolute differences (Coeff 2) of the SIRs. Disability grade was assessed by the expanded disability status scale (EDSS). Cortical/gray matter, subcortical, infratentorial, and spinal lesions were excluded.

Results

The mean diameter of the lesions was 7.8 ± 1.97 mm, while the mean EDSS score was 4.5 ± 1.73. We found moderate correlations between the EDSS and Coeff 1 and 2 on IR-UTE and MPRAGE images. Accordingly, Pearson's correlations on IR-UTE were R = 0.51 (p = 0.007) and R = 0.49 (p = 0.01) for Coeff 1 and 2, respectively. For MPRAGE, Pearson's correlations were R = 0.5 (p = 0.008) and R = 0.48 (p = 0.012) for Coeff 1 and 2, respectively. For FLAIR, only poor correlations could be found.

Conclusion

The SIVs of MS lesions on IR-UTE and MPRAGE images, assessed by Coeff 1 and 2, could be used as novel potential MRI biomarkers for patients' disability.

Glia Connect Inflammation and Neurodegeneration in Multiple Sclerosis

Multiple sclerosis (MS) is regarded as a chronic inflammatory disease that leads to demyelination and eventually to neurodegeneration. Activation of innate immune cells and other inflammatory cells in the brain and spinal cord of people with MS has been well described. However, with the innovation of technology in glial cell research, we have a deep understanding of the mechanisms of glial cells connecting inflammation and neurodegeneration in MS. In this review, we focus on the role of glial cells, including microglia, astrocytes, and oligodendrocytes, in the pathogenesis of MS. We mainly focus on the connection between glial cells and immune cells in the process of axonal damage and demyelinating neuron loss.

Glia Connect Inflammation and Neurodegeneration in Multiple Sclerosis

Multiple sclerosis (MS) is regarded as a chronic inflammatory disease that leads to demyelination and eventually to neurodegeneration. Activation of innate immune cells and other inflammatory cells in the brain and spinal cord of people with MS has been well described. However, with the innovation of technology in glial cell research, we have a deep understanding of the mechanisms of glial cells connecting inflammation and neurodegeneration in MS. In this review, we focus on the role of glial cells, including microglia, astrocytes, and oligodendrocytes, in the pathogenesis of MS. We mainly focus on the connection between glial cells and immune cells in the process of axonal damage and demyelinating neuron loss.

Noncancerous disease-targeting AIEgens

Noncancerous diseases include a wide plethora of medical conditions beyond cancer and are a major cause of mortality around the world. Despite progresses in clinical research, many puzzles about these diseases remain unanswered, and new therapies are continuously being sought. The evolution of bio-nanomedicine has enabled huge advancements in biosensing, diagnosis, bioimaging, and therapeutics. The recent development of aggregation-induced emission luminogens (AIEgens) has provided an impetus to the field of molecular bionanomaterials. Following aggregation, AIEgens show strong emission, overcoming the problems associated with the aggregation-caused quenching (ACQ) effect. They also have other unique properties, including low background interferences, high signal-to-noise ratios, photostability, and excellent biocompatibility, along with activatable aggregation-enhanced theranostic effects, which help them achieve excellent therapeutic effects as an one-for-all multimodal theranostic platform. This review provides a comprehensive overview of the overall progresses in AIEgen-based nanoplatforms for the detection, diagnosis, bioimaging, and bioimaging-guided treatment of noncancerous diseases. In addition, it details future perspectives and the potential clinical applications of these AIEgens in noncancerous diseases are also proposed. This review hopes to motivate further interest in this topic and promote ideation for the further exploration of more advanced AIEgens in a broad range of biomedical and clinical applications in patients with noncancerous diseases.

Multimodal-neuroimaging machine-learning analysis of motor disability in multiple sclerosis

Motor disability is a dominant and restricting symptom in multiple sclerosis, yet its neuroimaging correlates are not fully understood. We apply statistical and machine learning techniques on multimodal neuroimaging data to discriminate between multiple sclerosis patients and healthy controls and to predict motor disability scores in the patients. We examine the data of sixty-four multiple sclerosis patients and sixty-five controls, who underwent the MRI examination and the evaluation of motor disability scales. The modalities used comprised regional fractional anisotropy, regional grey matter volumes, and functional connectivity. For analysis, we employ two approaches: high-dimensional support vector machines run on features selected by Fisher Score (aiming for maximal classification accuracy), and low-dimensional logistic regression on the principal components of data (aiming for increased interpretability). We apply analogous regression methods to predict symptom severity. While fractional anisotropy provides the classification accuracy of 96.1% and 89.9% with both approaches respectively, including other modalities did not bring further improvement. Concerning the prediction of motor impairment, the low-dimensional approach performed more reliably. The first grey matter volume component was significantly correlated (R = 0.28-0.46, p < 0.05) with most clinical scales. In summary, we identified the relationship between both white and grey matter changes and motor impairment in multiple sclerosis. Furthermore, we were able to achieve the highest classification accuracy based on quantitative MRI measures of tissue integrity between patients and controls yet reported, while also providing a low-dimensional classification approach with comparable results, paving the way to interpretable machine learning models of brain changes in multiple sclerosis.

Structural covariance in subcortical regions in multiple sclerosis and neuromyelitis optica spectrum disorders: An MRI-based study with automated brain volumetry

PURPOSE

This study aimed to investigate the alterations of brain volumetry and associated structural covariance in subcortical regions in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD).

MATERIALS AND METHODS

Fourty MS patients, 35 NMOSD patients and 34 healthy controls (HC) underwent 3D T1-weighted image and 3D T2 FLAIR of MRI. The volume differences in subcortical regions were compared between the MS, NMOSD, and HC groups by automated brain volumetry. Structural covariance analysis was performed with each pair of these regions to investigate the alterations of anatomical connections in MS and NMOSD compared to HC.

RESULTS

Compared with HC, MS patients presented significantly smaller volume in some subcortical and infratentorial regions (P<0.05), while NMOSD patients showed no significant difference of volumetry in any of the brain regions (P>0.05), although they had no significant difference in disease duration (MS 3.95±3.73 ys; NMOSD 3.11±4.61 ys; P>0.05). In addition, the structural covariance analyses revealed synergic volume alteration in subcortical regions both in the MS and NMOSD groups. More extensive additional connections compared with HC were found in MS patients and more extensive missing connections compared with HC were found in NMOSD patients.

CONCLUSION

This study revealed distinct patterns of brain structural damage and reorganization in MS and NMOSD, which could facilitate a better distinction between these two entities.

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.

Correspondence among gray matter atrophy and atlas-based neurotransmitter maps is clinically relevant in multiple sclerosis

In multiple sclerosis (MS), gray matter (GM) atrophy progresses in a non-random manner, possibly in regions with a high distribution of specific neurotransmitters involved in several relevant central nervous system functions. We investigated the associations among regional GM atrophy, atlas-based neurotransmitter distributions and clinical manifestations in a large MS patients' group. Brain 3 T MRI scans, neurological examinations and neuropsychological evaluations were obtained from 286 MS patients and 172 healthy controls (HC). Spatial correlations among regional GM volume differences and atlas-based nuclear imaging-derived neurotransmitter maps, and their associations with MS clinical features were investigated using voxel-based morphometry and JuSpace toolbox. Compared to HC, MS patients showed widespread GM atrophy being spatially correlated with the majority of neurotransmitter maps (false discovery rate [FDR]-p ≤ 0.004). Patients with a disease duration ≥ 5 vs < 5 years had significant cortical, subcortical and cerebellar atrophy, being spatially correlated with a higher distribution of serotoninergic and dopaminergic receptors (FDR-p ≤ 0.03). Compared to mildly-disabled patients, those with Expanded Disability Status Scale ≥ 3.0 or ≥ 4.0 had significant cortical, subcortical and cerebellar atrophy being associated with serotonergic, dopaminergic, opioid and cholinergic maps (FDR-p ≤ 0.04). Cognitively impaired vs cognitively preserved patients had widespread GM atrophy being spatially associated with serotonergic, dopaminergic, noradrenergic, cholinergic and glutamatergic maps (FDR-p ≤ 0.04). Fatigued vs non-fatigued MS patients had significant cortical, subcortical and cerebellar atrophy, not associated with neurotransmitter maps. No significant association between GM atrophy and neurotransmitter maps was found for depression. Regional GM atrophy with specific neurotransmitter systems may explain part of MS clinical manifestations, including locomotor disability, cognitive impairment and fatigue.

In vivo quantification of brain soma and neurite density abnormalities in multiple sclerosis

BACKGROUND

Soma and neurite density imaging (SANDI) is a new biophysical model that incorporates soma in addition to neurite density, thus possibly providing more specific information about the complex pathological processes of multiple sclerosis (MS).

PURPOSE

To discriminate the pathological abnormalities of MS white matter (WM) lesions, normal-appearing (NA) WM and cortex and to evaluate the associations among SANDI-derived measures, clinical disability, and conventional MRI variables.

METHODS

Twenty healthy controls (HC) and 23 MS underwent a 3 T brain MRI. Using SANDI on diffusion-weighted sequence, the fractions of neurite (fneurite) and soma (fsoma) were assessed in WM lesions, NAWM, and cortex.

RESULTS

Compared to HC WM, MS NAWM showed lower fneurite (false discovery rate [FDR]-p = 0.011). In MS patients, WM lesions showed lower fneurite and fsoma compared to both HC and MS NAWM (FDR-p < 0.001 for all). In the cortex, MS patients had lower fneurite and fsoma compared to HC (FDR-p ≤ 0.009). Compared to both HC and RRMS, PMS patients had lower fneurite in NAWM (vs HC: FDR-p < 0.001; vs RRMS: FDR-p = 0.003) and cortex (vs HC: FDR-p < 0.001; vs RRMS: p = 0.031, not surviving FDR correction), and lower cortical fsoma (vs HC: FDR-p < 0.001; vs RRMS: FDR-p = 0.009). Compared to HC, PMS also showed a higher fsoma in NAWM (FDR-p = 0.015). Fneurite and fsoma in the different brain compartments were correlated with age, phenotype, disease duration, disability, WM lesion volumes, normalized brain, cortical, and WM volumes (r from - 0.761 to 0.821, FDR-p ≤ 0.4).

CONCLUSIONS

SANDI may represent a clinically relevant model to discriminate different neurodegenerative phenomena that gradually accumulate through MS disease course.

Multiple sclerosis progression: time for a new mechanism-driven framework

Traditionally, multiple sclerosis has been categorised by distinct clinical descriptors-relapsing-remitting, secondary progressive, and primary progressive-for patient care, research, and regulatory approval of medications. Accumulating evidence suggests that the clinical course of multiple sclerosis is better considered as a continuum, with contributions from concurrent pathophysiological processes that vary across individuals and over time. The apparent evolution to a progressive course reflects a partial shift from predominantly localised acute injury to widespread inflammation and neurodegeneration, coupled with failure of compensatory mechanisms, such as neuroplasticity and remyelination. Ageing increases neural susceptibility to injury and decreases resilience. These observations encourage a new consideration of the course of multiple sclerosis as a spectrum defined by the relative contributions of overlapping pathological and reparative or compensatory processes. New understanding of key mechanisms underlying progression and measures to quantify progressive pathology will potentially have important and beneficial implications for clinical care, treatment targets, and regulatory decision-making.

Online hard example mining vs. fixed oversampling strategy for segmentation of new multiple sclerosis lesions from longitudinal FLAIR MRI

Detecting new lesions is a key aspect of the radiological follow-up of patients with Multiple Sclerosis (MS), leading to eventual changes in their therapeutics. This paper presents our contribution to the MSSEG-2 MICCAI 2021 challenge. The challenge is focused on the segmentation of new MS lesions using two consecutive Fluid Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Imaging (MRI). In other words, considering longitudinal data composed of two time points as input, the aim is to segment the lesional areas, which are present only in the follow-up scan and not in the baseline. The backbone of our segmentation method is a 3D UNet applied patch-wise to the images, and in which, to take into account both time points, we simply concatenate the baseline and follow-up images along the channel axis before passing them to the 3D UNet. Our key methodological contribution is the use of online hard example mining to address the challenge of class imbalance. Indeed, there are very few voxels belonging to new lesions which makes training deep-learning models difficult. Instead of using handcrafted priors like brain masks or multi-stage methods, we experiment with a novel modification to online hard example mining (OHEM), where we use an exponential moving average (i.e., its weights are updated with momentum) of the 3D UNet to mine hard examples. Using a moving average instead of the raw model should allow smoothing of its predictions and allow it to give more consistent feedback for OHEM.