Current and future role of MRI in the diagnosis and prognosis of multiple sclerosis.

In the majority of cases, multiple sclerosis (MS) is characterized by reversible episodes of neurological dysfunction, often followed by irreversible clinical disability. Accurate diagnostic criteria and prognostic markers are critical to enable early diagnosis and correctly identify patients with MS at increased risk of disease progression. The 2017 McDonald diagnostic criteria, which include magnetic resonance imaging (MRI) as a fundamental paraclinical tool, show high sensitivity and accuracy for the diagnosis of MS allowing early diagnosis and treatment. However, their inappropriate application, especially in the context of atypical clinical presentations, may increase the risk of misdiagnosis. To further improve the diagnostic process, novel imaging markers are emerging, but rigorous validation and standardization is still needed before they can be incorporated into clinical practice. This Series article discusses the current role of MRI in the diagnosis and prognosis of MS, while examining promising MRI markers, which could serve as reliable predictors of subsequent disease progression, helping to optimize the management of individual patients with MS. We also explore the potential of new technologies, such as artificial intelligence and automated quantification tools, to support clinicians in the management of patients. Yet, to ensure consistency and improvement in the use of MRI in MS diagnosis and patient follow-up, it is essential that standardized brain and spinal cord MRI protocols are applied, and that interpretation of results is performed by qualified (neuro)radiologists in all countries.

Changes in thalamic functional connectivity in post-Covid patients with and without fatigue.

BACKGROUND: Functional brain alterations in post-Covid-19 condition have been minimally explored to date. Here, we investigate differences in resting-state thalamic functional connectivity among post-Covid patients with and without fatigue, alongside structural brain changes and cognition. METHODS: Thirty-nine post-Covid patients (n = 15 fatigued, n = 24 non-fatigued) participated in our study, undergoing comprehensive cognitive assessments, as well as functional and structural neuroimaging. We conducted a seed-based functional connectivity analysis using the thalamus as a seed region, exploring its connectivity with the entire brain. To further elucidate our findings, correlation analyses were performed using the functional coupling between the thalamus and regions showing different connectivity between the two patient groups. RESULTS: Our results reveal that patients experiencing fatigue exhibit anti-correlated functional coupling between the thalamus and motor-associated regions, including the motor cortex (M1), supplementary motor area (SMA), and anterior cingulate cortex (ACC), compared to non-fatigued patients, who are showing positive functional coupling. Furthermore, this observed coupling was found to correlate with both the fatigue scores obtained from a fatigue questionnaire and performance on the Trail Making Test, Part A, which represents a measure of processing speed. CONCLUSIONS: Our study highlights significant differences in resting-state functional connectivity between post-Covid patients with and without fatigue, particularly within motor-associated brain regions. These findings suggest a potential neural mechanism underlying post-Covid fatigue and underscore the importance of considering both functional and structural brain changes in understanding the symptomatic sequelae of post-Covid-19 condition. Further research is warranted to provide insight into the longitudinal trajectories of these neural alterations.

Fully Automated Hippocampus Segmentation using T2-informed Deep Convolutional Neural Networks.

Hippocampal atrophy (tissue loss) has become a fundamental outcome parameter in clinical trials on Alzheimer's disease. To accurately estimate hippocampus volume and track its volume loss, a robust and reliable segmentation is essential. Manual hippocampus segmentation is considered the gold standard but is extensive, time-consuming, and prone to rater bias. Therefore, it is often replaced by automated programs like FreeSurfer, one of the most commonly used tools in clinical research. Recently, deep learning-based methods have also been successfully applied to hippocampus segmentation. The basis of all approaches are clinically used T1-weighted whole-brain MR images with approximately 1 mm isotropic resolution. However, such T1 images show low contrast-to-noise ratios (CNRs), particularly for many hippocampal substructures, limiting delineation reliability. To overcome these limitations, high-resolution T2-weighted scans are suggested for better visualization and delineation, as they show higher CNRs and usually allow for higher resolutions. Unfortunately, such time-consuming T2-weighted sequences are not feasible in a clinical routine. We propose an automated hippocampus segmentation pipeline leveraging deep learning with T2-weighted MR images for enhanced hippocampus segmentation of clinical T1-weighted images based on a series of 3D convolutional neural networks and a specifically acquired multi-contrast dataset. This dataset consists of corresponding pairs of T1- and high-resolution T2-weighted images, with the T2 images only used to create more accurate manual ground truth annotations and to train the segmentation network. The T2-based ground truth labels were also used to evaluate all experiments by comparing the masks visually and by various quantitative measures. We compared our approach with four established state-of-the-art hippocampus segmentation algorithms (FreeSurfer, ASHS, HippoDeep, HippMapp3r) and demonstrated a superior segmentation performance. Moreover, we found that the automated segmentation of T1-weighted images benefits from the T2-based ground truth data. In conclusion, this work showed the beneficial use of high-resolution, T2-based ground truth data for training an automated, deep learning-based hippocampus segmentation and provides the basis for a reliable estimation of hippocampal atrophy in clinical studies.

The ageing central nervous system in multiple sclerosis: the imaging perspective.

The interaction between ageing and multiple sclerosis is complex and carries significant implications for patient care. Managing multiple sclerosis effectively requires an understanding of how ageing and multiple sclerosis impact brain structure and function. Ageing inherently induces brain changes, including reduced plasticity, diminished grey matter volume, and ischaemic lesion accumulation. When combined with multiple sclerosis pathology, these age-related alterations may worsen clinical disability. Ageing may also influence the response of multiple sclerosis patients to therapies and/or their side-effects, highlighting the importance of adjusted treatment considerations. Magnetic resonance MRI is highly sensitive to age- and multiple sclerosis-related processes. Accordingly, MRI can provide insights into the relationship between ageing and multiple sclerosis, enabling a better understanding of their pathophysiological interplay and informing treatment selection. This review summarizes current knowledge on the immuno-pathological and MRI aspects of ageing in the central nervous system in the context of multiple sclerosis. Starting from immunosenescence, ageing-related pathological mechanisms, and specific features like enlarged Virchow-Robin spaces, this review then explores clinical aspects, including late-onset multiple sclerosis, the influence of age on diagnostic criteria, and comorbidity effects on imaging features. The role of MRI in understanding neurodegeneration, iron dynamics, and myelin changes influenced by ageing and how MRI can contribute to defining treatment effects in ageing multiple sclerosis patients, are also discussed.

White matter integrity and functional connectivity of the default mode network in acute stroke are associated with cognitive outcome three months post-stroke.

BACKGROUND: Knowledge about factors that are associated with post-stroke cognitive outcome is important to identify patients with high risk for impairment. We therefore investigated the associations of white matter integrity and functional connectivity (FC) within the brain's default-mode network (DMN) in acute stroke patients with cognitive outcome three months post-stroke. METHODS: Patients aged between 18 and 85 years with an acute symptomatic MRI-proven unilateral ischemic middle cerebral artery infarction, who had received reperfusion therapy, were invited to participate in this longitudinal study. All patients underwent brain MRI within 24-72 h after symptom onset, and participated in a neuropsychological assessment three months post-stroke. We performed hierarchical regression analyses to explore the incremental value of baseline white matter integrity and FC beyond demographic, clinical, and macrostructural information for cognitive outcome. RESULTS: The study cohort comprised 34 patients (mean age: 64 ± 12 years, 35% female). The initial median National Institutes of Health Stroke Scale (NIHSS) score was 10, and significantly improved three months post-stroke to a median NIHSS = 1 (p < .001). Nonetheless, 50% of patients showed cognitive impairment three months post-stroke. FC of the non-lesioned anterior cingulate cortex of the affected hemisphere explained 15% of incremental variance for processing speed (p = .007), and fractional anisotropy of the non-lesioned cingulum of the affected hemisphere explained 13% of incremental variance for cognitive flexibility (p = .033). CONCLUSIONS: White matter integrity and functional MRI markers of the DMN in acute stroke explain incremental variance for post-stroke cognitive outcome beyond demographic, clinical, and macrostructural information.

Three-dimensional EPI with shot-selective CAIPIRIHANA for rapid high-resolution quantitative susceptibility mapping at 3 T.

PURPOSE: QSM provides insight into healthy brain aging and neuropathologies such as multiple sclerosis (MS), traumatic brain injuries, brain tumors, and neurodegenerative diseases. Phase data for QSM are usually acquired from 3D gradient-echo (3D GRE) scans with long acquisition times that are detrimental to patient comfort and susceptible to patient motion. This is particularly true for scans requiring whole-brain coverage and submillimeter resolutions. In this work, we use a multishot 3D echo plannar imaging (3D EPI) sequence with shot-selective 2D CAIPIRIHANA to acquire high-resolution, whole-brain data for QSM with minimal distortion and blurring. METHODS: To test clinical viability, the 3D EPI sequence was used to image a cohort of MS patients at 1-mm isotropic resolution at 3 T. Additionally, 3D EPI data of healthy subjects were acquired at 1-mm, 0.78-mm, and 0.65-mm isotropic resolution with varying echo train lengths (ETLs) and compared with a reference 3D GRE acquisition. RESULTS: The appearance of the susceptibility maps and the susceptibility values for segmented regions of interest were comparable between 3D EPI and 3D GRE acquisitions for both healthy and MS participants. Additionally, all lesions visible in the MS patients on the 3D GRE susceptibility maps were also visible on the 3D EPI susceptibility maps. The interplay among acquisition time, resolution, echo train length, and the effect of distortion on the calculated susceptibility maps was investigated. CONCLUSION: We demonstrate that the 3D EPI sequence is capable of rapidly acquiring submillimeter resolutions and providing high-quality, clinically relevant susceptibility maps.

Low-frequency MR elastography reveals altered deep gray matter viscoelasticity in multiple sclerosis.

INTRODUCTION: Brain viscoelasticity as assessed by magnetic resonance elastography (MRE) has been discussed as a promising surrogate of microstructural alterations due to neurodegenerative processes. Existing studies indicate that multiple sclerosis (MS) is associated with a global reduction in brain stiffness. However, no study to date systematically investigated the MS-related characteristics of brain viscoelasticity separately in normal-appearing white matter (NAWM), deep gray matter (DGM) and T2-hyperintense white matter (WM) lesions. METHODS: 70 MS patients and 42 healthy volunteers underwent whole-cerebral MRE using a stimulated echo sequence (DENSE) with a low-frequency mechanical excitation at 20 Hertz. The magnitude |G∗| (Pa) and phase angle φ (rad) of the complex shear modulus G∗ were reconstructed by multifrequency dual elasto-visco (MDEV) inversion and related to structural imaging and clinical parameters. RESULTS: We observed φ in the thalamus to be higher by 4.3 % in patients relative to healthy controls (1.11 ± 0.07 vs. 1.06 ± 0.07, p < 0.0001). Higher Expanded Disability Status Scale (EDSS) scores were negatively associated with φ in the basal ganglia (p = 0.01). We measured φ to be lower in MS lesions compared to surrounding NAWM (p = 0.001), which was most prominent for lesions in the temporal lobe (1.01 ± 0.22 vs. 1.06 ± 0.19, p = 0.003). Age was associated with lower values of |G∗| (p = 0.04) and φ (p = 0.004) in the thalamus of patients. No alteration in NAWM stiffness relative to WM in healthy controls was observed. CONCLUSION: Low-frequency elastography in MS patients reveals age-independent alterations in the viscoelasticity of deep gray matter at early stages of disease.

Evaluation of a self-administered iPad®-based processing speed assessment for people with multiple sclerosis in a clinical routine setting.

BACKGROUND: Limited resources often hinder regular cognitive assessment of people with multiple sclerosis (pwMS) in standard clinical care. A self-administered iPad®-based cognitive screening-tool (Processing Speed Test; PST) might mitigate this problem. OBJECTIVE: To evaluate the PST in clinical routine. METHODS: We investigated the feasibility of the PST in both a quiet and a waiting room setting. We assessed the validity of the PST in comparison with the established Symbol Digit Modalities Test (SDMT). We explored associations between processing speed assessments and the Brief International Cognitive Assessment for MS (BICAMS), magnetic resonance imaging (MRI) parameters, and psychological factors. Additionally, we explored the ability of the PST to detect impairment in processing speed compared to the SDMT. RESULTS: The PST was feasible in the waiting room setting. PST and SDMT correlated comparably with the BICAMS, MRI parameters, and psychological variables. Of 172 pwMS, 50 (30.8%) showed cognitive impairment according to the BICAMS; respective values were 47 (27.3%) for the SDMT and 9 (5.2%) for the PST. CONCLUSIONS: The PST performed in a waiting room setting correlates strongly with established cognitive tests. It thus may be used to assess processing speed in a resource-efficient manner and complement cognitive assessment in clinical routine. Despite comparable validity of the PST and SDMT, we identified more pwMS with impaired processing speed using normative data of the SDMT compared to the PST and advise caution, that the common cut-off score of - 1.5 SD from the current PST is not appropriate in Europe.

Time is myelin: early cortical myelin repair prevents atrophy and clinical progression in multiple sclerosis.

Cortical myelin loss and repair in multiple sclerosis (MS) have been explored in neuropathological studies, but the impact of these processes on neurodegeneration and the irreversible clinical progression of the disease remains unknown. Here, we evaluated in vivo cortical demyelination and remyelination in a large cohort of people with all clinical phenotypes of MS followed up for 5 years using magnetization transfer imaging (MTI), a technique that has been shown to be sensitive to myelin content changes in the cortex. We investigated 140 people with MS (37 clinically isolated syndrome, 71 relapsing-MS, 32 progressive-MS), who were clinically assessed at baseline and after 5 years and, along with 84 healthy controls, underwent a 3 T-MRI protocol including MTI at baseline and after 1 year. Changes in cortical volume over the radiological follow-up were computed with a Jacobian integration method. Magnetization transfer ratio was employed to calculate for each patient an index of cortical demyelination at baseline and of dynamic cortical demyelination and remyelination over the follow-up period. The three indices of cortical myelin content change were heterogeneous across patients but did not significantly differ across clinical phenotypes or treatment groups. Cortical remyelination, which tended to fail in the regions closer to CSF (-11%, P < 0.001), was extensive in half of the cohort and occurred independently of age, disease duration and clinical phenotype. Higher indices of cortical dynamic demyelination (ß = 0.23, P = 0.024) and lower indices of cortical remyelination (ß = -0.18, P = 0.03) were significantly associated with greater cortical atrophy after 1 year, independently of age and MS phenotype. While the extent of cortical demyelination predicted a higher probability of clinical progression after 5 years in the entire cohort [odds ratio (OR) = 1.2; P = 0.043], the impact of cortical remyelination in reducing the risk of accumulating clinical disability after 5 years was significant only in the subgroup of patients with shorter disease duration and limited extent of demyelination in cortical regions (OR = 0.86, P = 0.015, area under the curve = 0.93). In this subgroup, a 30% increase in cortical remyelination nearly halved the risk of clinical progression at 5 years, independently of clinical relapses. Overall, our results highlight the critical role of cortical myelin dynamics in the cascade of events leading to neurodegeneration and to the subsequent accumulation of irreversible disability in MS. Our findings suggest that early-stage myelin repair compensating for cortical myelin loss has the potential to prevent neuro-axonal loss and its long-term irreversible clinical consequences in people with MS.

Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis.

Importance: Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. Objective: To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). Design, Setting, and Participants: This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). Exposures: MS/CIS vs non-MS conditions. Main Outcomes and Measures: Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. Results: The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. Conclusions and Relevance: The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.

Multimodal analytical tools for the molecular and elemental characterisation of lesions in brain tissue of multiple sclerosis patients.

Multiple sclerosis (MS) is a prevalent immune-mediated inflammatory disease of the central nervous system inducing a widespread degradation of myelin and resulting in neurological deficits. Recent advances in molecular and atomic imaging provide the means to probe the microenvironment in affected brain tissues at an unprecedented level of detail and may provide new insights. This study showcases state-of-the-art spectroscopic and mass spectrometric techniques to compare distributions of molecular and atomic entities in MS lesions and surrounding brain tissues. MS brains underwent post-mortem magnetic resonance imaging (MRI) to locate and subsequently dissect MS lesions and surrounding white matter. Digests of lesions and unaffected white matter were analysed via ICP-MS/MS revealing significant differences in concentrations of Li, Mg, P, K, Mn, V, Rb, Ag, Gd and Bi. Micro x-ray fluorescence spectroscopy (µXRF) and laser ablation - inductively coupled plasma - time of flight - mass spectrometry (LA-ICP-ToF-MS) were used as micro-analytical imaging techniques to study distributions of both endogenous and xenobiotic elements. The essential trace elements Fe, Cu and Zn were subsequently calibrated using in-house manufactured gelatine standards. Lipid distributions were studied using IR-micro spectroscopy and matrix assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI). MALDI-MSI was complemented with high-resolution tandem mass spectrometry and trapped ion mobility spectroscopy for the annotation of specified phospho- and sphingolipids, revealing specific lipid species decreased in MS lesions compared to surrounding white matter. This explorative study demonstrated that modern molecular and atomic mapping techniques provide high-resolution imaging for relevant bio-indicative entities which may complement our current understanding of the underlying pathophysiological processes.

Efficacy assessment of an active tau immunotherapy in Alzheimer's disease patients with amyloid and tau pathology: a post hoc analysis of the "ADAMANT" randomised, placebo-controlled, double-blind, multi-centre, phase 2 clinical trial.

BACKGROUND: Tau pathology correlates with and predicts clinical decline in Alzheimer's disease. Approved tau-targeted therapies are not available. METHODS: ADAMANT, a 24-month randomised, placebo-controlled, parallel-group, double-blinded, multicenter, Phase 2 clinical trial (EudraCT2015-000630-30, NCT02579252) enrolled 196 participants with Alzheimer's disease; 119 are included in this post-hoc subgroup analysis. AADvac1, active immunotherapy against pathological tau protein. A machine learning model predicted likely Amyloid+Tau+ participants from baseline MRI. STATISTICAL METHODS: MMRM for change from baseline in cognition, function, and neurodegeneration; linear regression for associations between antibody response and endpoints. RESULTS: The prediction model achieved PPV of 97.7% for amyloid, 96.2% for tau. 119 participants in the full analysis set (70 treatment and 49 placebo) were classified as A+T+. A trend for CDR-SB 104-week change (estimated marginal means [emm] = -0.99 points, 95% CI [-2.13, 0.13], p = 0.0825]) and ADCS-MCI-ADL (emm = 3.82 points, CI [-0.29, 7.92], p = 0.0679) in favour of the treatment group was seen. Reduction was seen in plasma NF-L (emm = -0.15 log pg/mL, CI [-0.27, -0.03], p = 0.0139). Higher antibody response to AADvac1 was related to slowing of decline on CDR-SB (rho = -0.10, CI [-0.21, 0.01], p = 0.0376) and ADL (rho = 0.15, CI [0.03, 0.27], p = 0.0201), and related to slower brain atrophy (rho = 0.18-0.35, p < 0.05 for temporal volume, whole cortex, and right and left hippocampus). CONCLUSIONS: In the subgroup of ML imputed or CSF identified A+T+, AADvac1 slowed AD-related decline in an antibody-dependent manner. Larger anti-tau trials are warranted. FUNDING: AXON Neuroscience SE.

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.

Psychological factors and brain magnetic resonance imaging metrics associated with fatigue in persons with multiple sclerosis.

BACKGROUND: Besides demographics and clinical factors, psychological variables and brain-tissue changes have been associated with fatigue in persons with multiple sclerosis (pwMS). Identifying predictors of fatigue could help to improve therapeutic approaches for pwMS. Therefore, we investigated predictors of fatigue using a multifactorial approach. METHODS: 136 pwMS and 49 normal controls (NC) underwent clinical, neuropsychological, and magnetic resonance imaging examinations. We assessed fatigue using the "Fatigue Scale for Motor and Cognitive Functions", yielding a total, motor, and cognitive fatigue score. We further analyzed global and subcortical brain volumes, white matter lesions and microstructural changes (examining fractional anisotropy; FA) along the cortico striatal thalamo cortical (CSTC) loop. Potential demographic, clinical, psychological, and magnetic resonance imaging predictors of total, motor, and cognitive fatigue were explored using multifactorial linear regression models. RESULTS: 53% of pwMS and 20% of NC demonstrated fatigue. Besides demographics and clinical data, total fatigue in pwMS was predicted by higher levels of depression and reduced microstructural tissue integrity in the CSTC loop (adjusted R2 = 0.52, p < 0.001). More specifically, motor fatigue was predicted by lower education, female sex, higher physical disability, higher levels of depression, and self-efficacy (adjusted R2 = 0.54, p < 0.001). Cognitive fatigue was also predicted by higher levels of depression and lower self-efficacy, but in addition by FA reductions in the CSTC loop (adjusted R2 = 0.45, p < 0.001). CONCLUSIONS: Our results indicate that depression and self-efficacy strongly predict fatigue in MS. Incremental variance in total and cognitive fatigue was explained by microstructural changes along the CSTC loop, beyond demographics, clinical, and psychological variables.

Frequency and predictors of poststroke epilepsy after mechanical thrombectomy for large vessel occlusion stroke: results from a multicenter cohort study.

BACKGROUND: Poststroke epilepsy (PSE) represents an important complication of stroke. Data regarding the frequency and predictors of PSE in patients with large-vessel occlusion stroke receiving mechanical thrombectomy (MT) are scarce. Furthermore, information on acute and preexisting lesion characteristics on brain MRI has not yet been systematically considered in risk prediction of PSE. This study thus aims to assess PSE risk after acute ischemic stroke treated with MT, based on clinical and MRI features. METHODS: In this multicenter study from two tertiary stroke centers, we included consecutive acute ischemic stroke patients who had received MT for acute intracranial large vessel occlusion (LVO) between 2011 and 2017, in whom post-interventional brain MRI and long term-follow-up data were available. Infarct size, affected cerebrovascular territory, hemorrhagic complications and chronic cerebrovascular disease features were assessed on MRI (blinded to clinical information). The primary outcome was the occurrence of PSE (> 7 days after stroke onset) assessed by systematic follow-up via phone interview or electronic records. RESULTS: Our final study cohort comprised 348 thrombectomy patients (median age: 67 years, 45% women) with a median long-term follow-up of 78 months (range 0-125). 32 patients (9%) developed PSE after a median of 477 days (range 9-2577 days). In univariable analyses, larger postinterventional infarct size, infarct location in the parietal, frontal or temporal lobes and cerebral microbleeds were associated with PSE. Multivariable Cox regression analysis confirmed larger infarct size (HR 3.49; 95% CI 1.67-7.30) and presence of cerebral microbleeds (HR 2.56; 95% CI 1.18-5.56) as independent predictors of PSE. CONCLUSION: In our study, patients with large vessel occlusion stroke receiving MT had a 9% prevalence of PSE over a median follow-up period of 6.5 years. Besides larger infarct size, presence of cerebral microbleeds on brain MRI predicted PSE occurrence.

Long-term risk of recurrent vascular events and mortality in young stroke patients: Insights from a multicenter study.

BACKGROUND: Although the incidence of stroke in the young is rising, data on long-term outcomes in these patients are scarce. We thus aimed to investigate the long-term risk of recurrent vascular events and mortality in a multicenter study. METHODS: We followed 396 consecutive patients aged 18-55 years with ischemic stroke (IS) or transient ischemic attack (TIA) enrolled in three European centers during the period 2007-2010. A detailed outpatient clinical follow-up assessment was performed between 2018 and 2020. When an in-person follow-up visit was not possible, outcome events were assessed using electronic records and registry data. RESULTS: During a median follow-up of 11.8 (IQR 10.4-12.7) years, 89 (22.5%) patients experienced any recurrent vascular event, 62 (15.7%) had any cerebrovascular event, 34 (8.6%) had other vascular events, and 27 (6.8%) patients died. Cumulative 10-year incidence rate per 1000 person-years was 21.6 (95% CI 17.1-26.9) for any recurrent vascular event and 14.9 (95% CI 11.3-19.3) for any cerebrovascular event. The prevalence of cardiovascular risk factors increased over time, and 22 (13.5%) patients lacked any secondary preventive medication at the in-person follow-up. After adjustment for demographics and comorbidities, atrial fibrillation at baseline was found to be significantly associated with recurrent vascular events. CONCLUSIONS: This multicenter study shows a considerable risk of recurrent vascular events in young IS and TIA patients. Further studies should investigate whether detailed individual risk assessment, modern secondary preventive strategies, and better patient adherence may reduce recurrence risk.

Autolysis Affects the Iron Cargo of Ferritins in Neurons and Glial Cells at Different Rates in the Human Brain.

Iron is known to accumulate in neurological disorders, so a careful balance of the iron concentration is essential for healthy brain functioning. An imbalance in iron homeostasis could arise due to the dysfunction of proteins involved in iron homeostasis. Here, we focus on ferritin-the primary iron storage protein of the brain. In this study, we aimed to improve a method to measure ferritin-bound iron in the human post-mortem brain, and to discern its distribution in particular cell types and brain regions. Though it is known that glial cells and neurons differ in their ferritin concentration, the change in the number and distribution of iron-filled ferritin cores between different cell types during autolysis has not been revealed yet. Here, we show the cellular and region-wide distribution of ferritin in the human brain using state-of-the-art analytical electron microscopy. We validated the concentration of iron-filled ferritin cores to the absolute iron concentration measured by quantitative MRI and inductively coupled plasma mass spectrometry. We show that ferritins lose iron from their cores with the progression of autolysis whereas the overall iron concentrations were unaffected. Although the highest concentration of ferritin was found in glial cells, as the total ferritin concentration increased in a patient, ferritin accumulated more in neurons than in glial cells. Summed up, our findings point out the unique behaviour of neurons in storing iron during autolysis and explain the differences between the absolute iron concentrations and iron-filled ferritin in a cell-type-dependent manner in the human brain. The rate of loss of the iron-filled ferritin cores during autolysis is higher in neurons than in glial cells.

High serum neurofilament light chain levels correlate with brain atrophy and physical disability in multiple sclerosis.

BACKGROUND AND PURPOSE: Serum neurofilament light chain (sNfL) is a promising biomarker of neuroaxonal damage in persons with multiple sclerosis (pwMS). In cross-sectional studies, sNfL has been associated with disease activity and brain magnetic resonance imaging (MRI) changes; however, it is still unclear to what extent in particular high sNfL levels impact on subsequent disease evolution. METHODS: sNfL was quantified by an ultrasensitive single molecule array (Simoa) in 199 pwMS (median age = 34.2 years, 64.3% female) and 49 controls. All pwMS underwent 3-T MRI to assess global and compartmental normalized brain volumes, T2-lesion load, and cortical mean thickness. Follow-up data and serum samples were available in 144 pwMS (median follow-up time = 3.8 years). Linear and binary logistic models were used to estimate the independent contribution of sNfL for changes in MRI and Expanded Disability Status Scale (EDSS). Age-corrected sNfL z-scores from a normative database of healthy controls were used for sensitivity analyses. RESULTS: High sNfL levels at baseline were associated with atrophy measures of the whole brain (standardized beta coefficient ßj = -0.352, p < 0.001), white matter (ßj = -0.229, p = 0.007), thalamus (ßj = -0.372, p = 0.004), and putamen (ßj = -1.687, p = 0.012). pwMS with high levels of sNfL at baseline and follow-up had a greater risk of EDSS worsening (p = 0.007). CONCLUSIONS: Already single time point elevation of sNfL has a distinct effect on brain volume changes over a short-term period, and repeated high levels of sNfL indicate accumulating physical disability. Serial assessment of sNfL may provide added value in the clinical management of pwMS.

Radiomics-Derived Brain Age Predicts Functional Outcome After Acute Ischemic Stroke.

BACKGROUND AND OBJECTIVES: While chronological age is one of the most influential determinants of poststroke outcomes, little is known of the impact of neuroimaging-derived biological "brain age." We hypothesized that radiomics analyses of T2-FLAIR images texture would provide brain age estimates and that advanced brain age of patients with stroke will be associated with cardiovascular risk factors and worse functional outcomes. METHODS: We extracted radiomics from T2-FLAIR images acquired during acute stroke clinical evaluation. Brain age was determined from brain parenchyma radiomics using an ElasticNet linear regression model. Subsequently, relative brain age (RBA), which expresses brain age in comparison with chronological age-matched peers, was estimated. Finally, we built a linear regression model of RBA using clinical cardiovascular characteristics as inputs and a logistic regression model of favorable functional outcomes taking RBA as input. RESULTS: We reviewed 4,163 patients from a large multisite ischemic stroke cohort (mean age = 62.8 years, 42.0% female patients). T2-FLAIR radiomics predicted chronological ages (mean absolute error = 6.9 years, r = 0.81). After adjustment for covariates, RBA was higher and therefore described older-appearing brains in patients with hypertension, diabetes mellitus, a history of smoking, and a history of a prior stroke. In multivariate analyses, age, RBA, NIHSS, and a history of prior stroke were all significantly associated with functional outcome (respective adjusted odds ratios: 0.58, 0.76, 0.48, 0.55; all p-values < 0.001). Moreover, the negative effect of RBA on outcome was especially pronounced in minor strokes. DISCUSSION: T2-FLAIR radiomics can be used to predict brain age and derive RBA. Older-appearing brains, characterized by a higher RBA, reflect cardiovascular risk factor accumulation and are linked to worse outcomes after stroke.