Deep Gray Matter Iron Content in Neuromyelitis Optica and Multiple Sclerosis

Atrophy-Independent and Dependent Iron and Myelin Changes in Deep Gray Matter of Multiple Sclerosis: A Longitudinal Study Using χ-Separation Imaging

RATIONALE AND OBJECTIVES

To investigate iron and myelin changes in deep gray matter (DGM) of relapsing-remitting multiple sclerosis (RRMS) patients and their relationship to atrophy by χ-separation imaging.

MATERIALS AND METHODS

33 RRMS patients and 34 healthy controls (HC) were included in this study. The χ-separation map reconstructed from a 3D multi-echo gradient echo scan was used to measure the positive susceptibility (χpos) and negative susceptibility (χneg) of DGM. To take into account the effect of atrophy, susceptibility mass of DGM was calculated by multiplying volume by the mean bulk susceptibility. Differences in MRI metrics between baseline patients, follow-up patients, and HC were compared respectively.

RESULTS

Compared to HC, χpos of basal ganglia were significantly increased in follow-up patients (P < 0.05). The χpos of pallidum was significantly higher in follow-up patients than that in baseline patients (P = 0.006). The χneg of caudate, pallidum and hippocampus in baseline and follow-up patients was significantly higher than that in HC (P < 0.05). When taking into account the effect of atrophy, there was a significant decrease in χpos mass and a significant increase in χneg mass of thalamus, accumbens and amygdala in follow-up patients compared to HC (P < 0.05). The χpos mass of the thalamus was further decreased in follow-up patients compared to baseline patients (P = 0.006).

CONCLUSION

χ-separation imaging could generate independent information on iron and myelin changes in RRMS patients, showing atrophy-dependent iron increase in basal ganglia and atrophy-independent iron and myelin decrease in thalamus.

Putamen iron quantification in diseases with neurodegeneration: a meta-analysis of the quantitative susceptibility mapping technique

Quantitative susceptibility mapping (QSM) is an MRI technique that accurately measures iron concentration in brain tissues. This meta-analysis synthesized evidence from 30 studies that used QSM to quantify the iron levels in the putamen. The PRISMA statement was adhered to when conducting the systematic reviews and meta-analyses. We conducted a meta-analysis using a random-effects model, as well as subgroup analyses (disease type, geographic region, field strength, coil, disease type, age, and sex) and sensitivity analysis. A total of 1247 patients and 1035 controls were included in the study. Pooled results showed a standardized mean difference (SMD) of 0.41 (95% CI 0.19 to 0.64), with the strongest effect seen in Alzheimer's disease (AD) at 1.01 (95% CI 0.50 to 1.52). Relapsing-remitting multiple sclerosis (RRMS) also showed increased putaminal iron at 0.37 (95% CI 0.177 to 0.58). No significant differences were observed in Parkinson's disease (PD). No significant differences were found between subgroups based on geographic region, field strength, coil, disease type, age, and sex. The studies revealed significant heterogeneity, with field strength as the primary source, while other factors, such as disease type, location, age, sex, and coil type, may have contributed. The sensitivity analysis showed that these factors did not have a significant influence on the overall results. In summary, this meta-analysis supports abnormalities in putaminal iron content across different diseases with neurodegeneration, especially AD and RRMS, as measured by QSM. This highlights the potential of QSM as an imaging biomarker to better understand disease mechanisms involving disturbances in brain iron homeostasis.

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.

Iron metabolism disorder and multiple sclerosis: a comprehensive analysis

Background

Multiple sclerosis (MS) is the most common chronic inflammatory disease of the central nervous system. Currently, the pathological mechanisms of MS are not fully understood, but research has suggested that iron metabolism disorder may be associated with the onset and clinical manifestations of MS.

Methods and materials

The study utilized publicly available databases and bioinformatics techniques for gene expression data analysis, including differential expression analysis, weighted correlation network analysis, gene enrichment analysis, and construction of logistic regression models. Subsequently, Mendelian randomization was used to assess the causal relationship between different iron metabolism markers and MS.

Results

This study identified IREB2, LAMP2, ISCU, ATP6V1G1, ATP13A2, and SKP1 as genes associated with multiple sclerosis (MS) and iron metabolism, establishing their multi-gene diagnostic value for MS with an AUC of 0.83. Additionally, Mendelian randomization analysis revealed a potential causal relationship between transferrin saturation and MS (p=2.22E-02; OR 95%CI=0.86 (0.75, 0.98)), as well as serum transferrin and MS (p=2.18E-04; OR 95%CI=1.22 (1.10, 1.36)).

Conclusion

This study comprehensively explored the relationship between iron metabolism and MS through integrated bioinformatics analysis and Mendelian randomization methods. The findings provide important insights for further research into the role of iron metabolism disorder in the pathogenesis of MS and offer crucial theoretical support for the treatment of MS.

Magnetic resonance imaging detection of deep gray matter iron deposition in multiple sclerosis: A systematic review

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease involving immune-mediated damage. Iron deposition in deep gray matter (DGM) structures like the thalamus and basal ganglia have been suggested to play a role in MS pathogenesis. Magnetic Resonance Imaging (MRI) imaging methods like T2 and T2* imaging, susceptibility-weighted imaging, and quantitative susceptibility mapping can track iron deposition storage in the brain primarily from ferritin and hemosiderin (paramagnetic iron storage proteins) with varying levels of tissue contrast and sensitivity. In this systematic review, we evaluated the role of DGM iron deposition as detected by MRI techniques in relation to MS-related neuroinflammation and its potential as a novel therapeutic target. We searched through PubMed, Embase, and Web of Science databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, against predetermined inclusion and exclusion criteria. We included 89 articles (n = 6630 patients), and then grouped them into different categories: i) methodological techniques to measure DGM iron, ii) cross-sectional and group comparison of DGM iron content, iii) longitudinal comparisons of DGM iron, iv) associations between DGM iron and other imaging and neurobiological markers, v) associations with disability, and vi) associations with cognitive impairment. The review revealed that iron deposition in DGM is independent yet concurrent with demyelination, and that these iron deposits contribute to MS-related cognitive impairment and disability. Variability in iron distributions appears to rely on a positive feedback loop between inflammation, and release of iron by oligodendrocytes. DGM iron seems to be a promising prognostic biomarker for MS pathophysiology.

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.

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.

Quantitative MRI in Multiple Sclerosis: From Theory to Application

Quantitative MR imaging techniques allow evaluating different aspects of brain microstructure, providing meaningful information about the pathophysiology of damage in CNS disorders. In the study of patients with MS, quantitative MR imaging techniques represent an invaluable tool for studying changes in myelin and iron content occurring in the context of inflammatory and neurodegenerative processes. In the first section of this review, we summarize the physics behind quantitative MR imaging, here defined as relaxometry and quantitative susceptibility mapping, and describe the neurobiological correlates of quantitative MR imaging findings. In the second section, we focus on quantitative MR imaging application in MS, reporting the main findings in both the gray and white matter compartments, separately addressing macroscopically damaged and normal-appearing parenchyma.

Sex bias in multiple sclerosis and neuromyelitis optica spectrum disorders: How it influences clinical course, MRI parameters and prognosis

This review is a condensed summary of representative articles addressing the sex/gender bias in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD). The strong effects of sex on the incidence and possibly also the activity and progression of these disorders should be implemented in the evaluation of any phase of clinical research and also in treatment choice consideration in clinical practice and evaluation of MRI parameters. Some relationships between clinical variables and gender still remain elusive but with further understanding of sex/gender-related differences, we should be able to provide appropriate patient-centered care and research.

CAU-Net: A Deep Learning Method for Deep Gray Matter Nuclei Segmentation

The abnormal iron deposition of the deep gray matter nuclei is related to many neurological diseases. With the quantitative susceptibility mapping (QSM) technique, it is possible to quantitatively measure the brain iron content in vivo. To assess the magnetic susceptibility of the deep gray matter nuclei in the QSM, it is mandatory to segment the nuclei of interest first, and many automatic methods have been proposed in the literature. This study proposed a contrast attention U-Net for nuclei segmentation and evaluated its performance on two datasets acquired using different sequences with different parameters from different MRI devices. Experimental results revealed that our proposed method was superior on both datasets over other commonly adopted network structures. The impacts of training and inference strategies were also discussed, which showed that adopting test time augmentation during the inference stage can impose an obvious improvement. At the training stage, our results indicated that sufficient data augmentation, deep supervision, and nonuniform patch sampling contributed significantly to improving the segmentation accuracy, which indicated that appropriate choices of training and inference strategies were at least as important as designing more advanced network structures.

Cerebral Iron Deposition in Neurodegeneration

Disruption of cerebral iron regulation appears to have a role in aging and in the pathogenesis of various neurodegenerative disorders. Possible unfavorable impacts of iron accumulation include reactive oxygen species generation, induction of ferroptosis, and acceleration of inflammatory changes. Whole-brain iron-sensitive magnetic resonance imaging (MRI) techniques allow the examination of macroscopic patterns of brain iron deposits in vivo, while modern analytical methods ex vivo enable the determination of metal-specific content inside individual cell-types, sometimes also within specific cellular compartments. The present review summarizes the whole brain, cellular, and subcellular patterns of iron accumulation in neurodegenerative diseases of genetic and sporadic origin. We also provide an update on mechanisms, biomarkers, and effects of brain iron accumulation in these disorders, focusing on recent publications. In Parkinson’s disease, Friedreich’s disease, and several disorders within the neurodegeneration with brain iron accumulation group, there is a focal siderosis, typically in regions with the most pronounced neuropathological changes. The second group of disorders including multiple sclerosis, Alzheimer’s disease, and amyotrophic lateral sclerosis shows iron accumulation in the globus pallidus, caudate, and putamen, and in specific cortical regions. Yet, other disorders such as aceruloplasminemia, neuroferritinopathy, or Wilson disease manifest with diffuse iron accumulation in the deep gray matter in a pattern comparable to or even more extensive than that observed during normal aging. On the microscopic level, brain iron deposits are present mostly in dystrophic microglia variably accompanied by iron-laden macrophages and in astrocytes, implicating a role of inflammatory changes and blood–brain barrier disturbance in iron accumulation. Options and potential benefits of iron reducing strategies in neurodegeneration are discussed. Future research investigating whether genetic predispositions play a role in brain Fe accumulation is necessary. If confirmed, the prevention of further brain Fe uptake in individuals at risk may be key for preventing neurodegenerative disorders.

Quantitative Susceptibility Mapping-Derived Radiomic Features in Discriminating Multiple Sclerosis From Neuromyelitis Optica Spectrum Disorder

Objectives: To implement a machine learning model using radiomic features extracted from quantitative susceptibility mapping (QSM) in discriminating multiple sclerosis (MS) from neuromyelitis optica spectrum disorder (NMOSD).

Materials and Methods: Forty-seven patients with MS (mean age = 40.00 ± 13.72 years) and 36 patients with NMOSD (mean age = 42.14 ± 12.34 years) who underwent enhanced gradient-echo T₂*-weighted angiography (ESWAN) sequence in 3.0-T MRI were included between April 2017 and October 2019. QSM images were reconstructed from ESWAN, and QSM-derived radiomic features were obtained from seven regions of interest (ROIs), including bilateral putamen, globus pallidus, head of the caudate nucleus, thalamus, substantia nigra, red nucleus, and dentate nucleus. A machine learning model (logistic regression) was applied to classify MS and NMOSD, which combined radiomic signatures and demographic information to assess the classification accuracy using the area under the receiver operating characteristic (ROC) curve (AUC).

Results: The radiomics-only models showed better discrimination performance in almost all deep gray matter (DGM) regions than the demographic information-only model, with the highest AUC in DN of 0.902 (95% CI: 0.840–0.955). Moreover, the hybrid model combining radiomic signatures and demographic information showed the highest discrimination performance which achieved the AUC of 0.927 (95% CI: 0.871–0.984) with fivefold cross-validation.

Conclusion: The hybrid model based on QSM and powered with machine learning has the potential to discriminate MS from NMOSD.

Age-related magnetic susceptibility changes in deep grey matter and cerebral cortex of normal young and middle-aged adults depicted by whole brain analysis

Background

Iron accumulates in brain tissue in healthy subjects during aging. Our goal was to conduct a detailed analysis of iron deposition patterns in the cerebral deep grey matter and cortex using region-based and whole-brain analyses of brain magnetic susceptibility.

Methods

Brain MRI was performed in 95 healthy individuals aged between 21 and 58 years on a 3T scanner. MRI protocol included T1-weighted (T1W) magnetization-prepared rapid acquisition with gradient echo images and 3D flow-compensated multi-echo gradient-echo images for quantitative susceptibility mapping (QSM). In the region-based analysis, QSM and T1W images entered an automated multi-atlas segmentation pipeline and regional mean bulk susceptibility values were calculated. The whole-brain analysis included a non-linear transformation of QSM images to the standard MNI template. For the whole-brain analysis voxel-wise maps of linear regression slopes β and P values were calculated. Regional masks of cortical voxels with a significant association between susceptibility and age were created and further analyzed.

Results

In cortical regions, the highest increase of susceptibility values with age was found in areas involved in motor functions (precentral and postcentral areas, premotor cortex), in cognitive processing (prefrontal cortex, superior temporal gyrus, insula, precuneus), and visual processing (occipital gyri, cuneus, posterior cingulum, fusiform, calcarine and lingual gyrus). Thalamic susceptibility increased until the fourth decade and decreased thereafter with the exception of the pulvinar where susceptibility increase was observed throughout the adult lifespan. Deep grey matter structures with the highest increase of susceptibility values with age included the red nucleus, putamen, substantia nigra, dentate nucleus, external globus pallidus, caudate nucleus, and the subthalamic nucleus in decreasing order.

Conclusions

Accumulation of iron in basal ganglia follows a linear pattern whereas in the thalamus, pulvinar, precentral cortex, and precuneus, it follows a quadratic or exponential pattern. Age-related changes of iron content are different in the pulvinar and the rest of the thalamus as well as in internal and external globus pallidus. In the cortex, areas involved in motor and cognitive functions and visual processing show the highest iron increase with aging. We suggest that the departure from normal patterns of regional brain iron trajectories during aging may be helpful in the detection of subtle neurodegenerative and neuroinflammatory processes.