Lesion Load Research Articles

Quantitative assessment of thalamic damage and serum neurofilament light chain in relapsing-remitting multiple sclerosis

BackgroundThe study assessed group differences in the thalamus microstructural parameters among healthy individuals and relapsing-remitting multiple sclerosis (RRMS) patients and examined the relationship between quantitative MRI (qMRI) parameters and neurological scores, T2 lesion load, and serum neurofilament light chain (sNfL) levels. MethodsA total of 30 patients with RRMS and 26 age- and sex-matched healthy controls were recruited in this study. The qMRI images were obtained from these individuals. T2 lesion load, thalamic volume, and parameters of thalamic subnuclei were estimated. The neurological functions of participants were assessed using a battery of tests. sNfL concentrations were measured using the single molecule array (SIMOA) technique. ResultsT2 relaxometry in the whole thalamus and its subnuclei were increased, and showed an apparent correlation with T2 lesion load and the severity of MS (EDSS, MSSS, 9HPT, T25FW, SDMT). T1 variability was prolonged in most thalamic subnuclei, and it was correlated with the severity of MS (EDSS, 9HPT, SDMT). Thalamic volumetric parameters of MS patients were smaller than those of healthy controls (p < 0.001) and showed an apparent correlation with MS severity. Surprisingly, sNfL levels showed no correlation with T2 relaxometry, T1 variability, or thalamic volumetric parameters. ConclusionQuantitative synthetic MRI, especially, the metric T2 relaxation times provides a surrogate parameter for assessing underlying thalamic and subnuclei damage in the RRMS group. Integrating structural and quantitative MRI allows a better assessment of the neurodegeneration in the normal-appearing thalamus of RRMS.

Cerebral hemodynamics and oxygen metabolism in patients with milder and severe forms of sickle cell disease and thalassemia.

Silent cerebral infarcts (SCIs) are present in patients with sickle cell disease (SCD) and thalassemia, but the pathophysiology of SCIs is not fully understood. Previous studies mainly focused on cerebral hemodynamics and oxygen metabolism in patients with severe SCD (HbSS/HbSβ°) but not in milder forms of SCD (HbSC/HbSβ+) and thalassemia despite the high prevalence of SCIs in these patients. In this work, we studied the cerebral hemodynamics and oxygen metabolism, and SCI lesion load in 75 severe and 26 mild adult SCD patients, 18 thalassemia patients (as anemic comparison group), and 30 healthy controls before and after a vasodilatory challenge with acetazolamide. Cerebral blood flow was significantly higher in patients with severe SCD and thalassemia compared to patients with mild SCD and controls (p < 0.05). Conversely, oxygen extraction fraction and cerebral metabolic rate of oxygen (CMRO2) were significantly lower in patients with severe SCD and thalassemia compared to other groups (p < 0.01). In contrast, no difference in SCI volumes was found between mild and severe SCD and thalassemia patients. After acetazolamide administration, oxygen delivery increased less in severe SCD and thalassemia patients compared to other groups (p < 0.01) and CMRO2 decreased only in severe SCD patients (p < 0.01). Given the reduced CMRO2 values in severe SCD and thalassemia patients, we conclude that reduced cerebral oxygen consumption in these patient groups is mostly related to anemia. Our data suggest that the pathophysiology of SCIs in patients with milder forms of SCD might be more related to prior episodes of anemia or other sickle cell-related factors.

Determinants of long‐term paramagnetic rim lesion evolution in people with multiple sclerosis

AbstractObjectiveBaseline paramagnetic rim lesion (PRL) load predicts disease progression in people with multiple sclerosis (pwMS). Understanding how PRLs relate to other known MS‐related factors, and the practical utility of PRLs in clinical trials, is crucial for informing clinical decision‐making and guiding development of novel disease‐modifying treatments (DMTs).MethodsThis study included 152 pwMS enrolled in a larger prospective, longitudinal cohort study who had 3T MRI scans and clinical assessments at baseline and 5‐ or 10‐year follow‐ups. PRLs were identified on baseline 3T quantitative susceptibility maps and classified as persisting, disappearing, or newly appearing at follow‐up. The relationships between PRL evolution and clinical, radiological, environmental, and genetic characteristics were assessed, and clinical trial sample sizes were estimated using PRL appearance or disappearance as outcome measures.ResultsDMT use was associated with lower odds of new PRL appearance (for high‐efficacy DMTs: odds ratio = 0.088, p = 0.024), but not disappearance. Current smoking status was associated with greater baseline PRL number (B = 0.527 additional PRLs, p = 0.013). A 24‐month clinical trial in people with progressive MS for a DMT that doubles the rate of PRL rim disappearance would require an estimated 118 people with progressive MS per group at 80% statistical power.InterpretationEarly MS diagnosis and subsequent DMT initiation may reduce new chronic active inflammation. However, the utility of PRL disappearance or new PRL appearance as outcome measures in clinical trials is limited by potentially large sample sizes that are needed for moderate efficacy drugs.

Cerebello-Cerebral Resting-State Functional Connectivity in Poststroke Aphasia.

Introduction: The influence of the cerebellum in poststroke aphasia recovery is poorly understood. Despite the right cerebellum being identified as a critical region involved in both language and cognitive functions, little is known about functional connections between the cerebellum and bilateral cortical hemispheres following stroke. This study investigated the relationship between chronic poststroke naming deficits and cerebello-cerebral resting-state functional connectivity (FC). Methods: Twenty-five cognitively normal participants and 42 participants with chronic poststroke aphasia underwent resting-state functional magnetic resonance imaging. Participants with aphasia also underwent language assessment. We conducted regions of interest (ROI)-to-ROI analyses to investigate the FC between the right cerebellar Crus I/II (seed ROI; Cereb1r/Cereb2r) and bilateral cortical language regions and compared these results to cognitively normal controls. Single-subject connectivity parameters were extracted and used as independent variables in a stepwise multiple linear regression model associating Boston Naming Test (BNT) score with FC measures. Results: FC analyses demonstrated correlations between the right cerebellar Crus I/II and both left and right cortical regions for both cognitively normal controls and stroke participants. Additionally, aphasia severity and lesion load had an effect on the cerebello-cerebral network connectivity in participants with aphasia. In a stepwise multiple linear regression, controlling for aphasia severity, time poststroke and lesion load, FC between the right Cereb2-left Cereb1 (standardized beta [std B]= -0.255, p < 0.004), right Cereb2-right anterior MTG (std B = 0.259, p < 0.004), and the right Cereb2-left anterior STG (std B = -0.208, p < 0.018) were significant predictors of BNT score. The overall model fit was R2 = 0.786 (p = 0.001). Conclusion: Functional connections between the right cerebellum and residual bilateral cerebral hemisphere regions may play a role in predicting naming ability in poststroke aphasia.

Multi-Omic characterization of the effects of Ocrelizumab in patients with relapsing-remitting multiple sclerosis

The study examined changes in the plasma proteome, metabolome, and lipidome of N = 14 patients with relapsing-remitting multiple sclerosis (RRMS) initiating treatment with ocrelizumab, assayed at baseline, 6 months, and 12 months. Analyses of >4000 circulating biomarkers identified depletion of B-cell associated proteins as the early effect observed following ocrelizumab (OCR) initiation, accompanied by the reduction in plasma abundance of cytokines and cytotoxic proteins, markers of neuronaxonal damage, and biologically active lipids including ceramides and lysophospholipids, at 6 months. B-cell depletion was accompanied by decreases in B-cell receptor and cytokine signaling but a pronounced increase in circulating plasma B-cell activating factor (BAFF). This was followed by an upregulation of a number of signaling and metabolic pathways at 12 months. Patients with higher baseline brain MRI lesion load demonstrated both higher levels of cytotoxic and structural proteins in plasma at baseline and more pronounced biomarker change trajectories over time. Digital cytometry identified a putative increase in myeloid cells and a pro-inflammatory subset of T-cells. Therapeutic effects of ocrelizumab extend beyond CD20-mediated B-cell lysis and implicate metabolic reprogramming, juxtaposing the early normalization of immune activation, cytokine signaling and metabolite and lipid turnover in periphery with changes in the dynamics of immune cell activation or composition. We identify BAFF increase following CD20 depletion as a tentative compensatory mechanism that contributes to the reconstitution of targeted B-cells, necessitating further research.

Advanced Quantitative MRI Unveils Microstructural Thalamic Changes Reflecting Disease Progression in Multiple Sclerosis.

In patients with multiple sclerosis (PwMS), thalamic atrophy occurs during the disease course. However, there is little understanding of the mechanisms leading to volume loss and of the relationship between microstructural thalamic pathology and disease progression. This cross-sectional and longitudinal study aimed to comprehensively characterize in vivo pathologic changes within thalamic microstructure in PwMS using advanced multiparametric quantitative MRI (qMRI). Thalamic microstructural integrity was evaluated using quantitative T1, magnetization transfer saturation, multishell diffusion, and quantitative susceptibility mapping (QSM) in 183 PwMS and 105 healthy controls (HCs). The same qMRI protocol was available for 127 PwMS and 73 HCs after a 2-year follow-up period. Inclusion criteria for PwMS encompassed either an active relapsing-remitting MS (RRMS) or inactive progressive MS (PMS) disease course. Thalamic alterations were compared between PwMS and HCs and among disease phenotypes. In addition, the study investigated the relationship between thalamic damage and clinical and conventional MRI measures of disease severity. Compared with HCs, PwMS exhibited substantial thalamic alterations, indicative of microstructural and macrostructural damage, demyelination, and disruption in iron homeostasis. These alterations extended beyond focal thalamic lesions, affecting normal-appearing thalamic tissue diffusely. Over the follow-up period, PwMS displayed an accelerated decrease in myelin volume fraction [mean difference in annualized percentage change (MD-ApC) = -1.50; p = 0.041] and increase in quantitative T1 (MD-ApC = 0.92; p < 0.0001) values, indicating heightened demyelinating and neurodegenerative processes. The observed differences between PwMS and HCs were substantially driven by the subgroup with PMS, wherein thalamic degeneration was significantly accelerated, even in comparison with patients with RRMS. Thalamic qMRI alterations showed extensive correlations with conventional MRI, clinical, and cognitive disease burden measures. Disability progression over follow-up was associated with accelerated thalamic degeneration, as reflected by enhanced diffusion (β = -0.067; p = 0.039) and QSM (β = -0.077; p = 0.027) changes. Thalamic qMRI metrics emerged as significant predictors of neurologic and cognitive disability even when accounting for other established markers including white matter lesion load and brain and thalamic atrophy. These findings offer deeper insights into thalamic pathology in PwMS, emphasizing the clinical relevance of thalamic damage and its link to disease progression. Advanced qMRI biomarkers show promising potential in guiding interventions aimed at mitigating thalamic neurodegenerative processes.

Dissociation of White Matter Bundles in Different Recovery Measures in Poststroke Aphasia.

Poststroke aphasia (PSA) recovery shows high variability across individuals and at different time points. Although diffusion biomarkers from the ventral and dorsal streams have demonstrated strong predictive power for language outcomes, it is still unclear how these biomarkers relate to the various stages of PSA recovery. In this study, we aim to compare diffusion metrics and language measures as predictors of language recovery in a longitudinal cohort of participants with PSA. Participants were recruited at a stroke unit at the emergency room, and underwent diffusion magnetic resonance imaging scanning and language assessment within 3 days (acute phase) after stroke, with behavioral follow-ups at subacute (10±3 days) and chronic phases (>6 months). We conducted regression analyses on language performance (cross-sectional), Δscores between all time points (acute-subacute, subacute-chronic, acute-chronic), and relative Δscores between all time points (Δscore/language baseline score), with acute diffusion metrics from language-related white matter tracts, lesion size, language baseline scores, and demographic data as predictors. Thirty-nine participants presenting PSA were recruited, and 24 participants (mean age, 73 years; 8 women) completed the 3-time point assessment in total. The best prediction model of performance scores used axial diffusivity from the left arcuate fasciculus in both the subacute (R2=0.785) and chronic stages (R2=0.626). Moreover, the prediction of ∆scores depended on axial diffusivity from the left inferior frontal-occipital fasciculus in the subacute stage (R2=0.5) and depended additionally on axial diffusivity from the right inferior frontal-occipital fasciculus in the chronic stage (R2=0.68). The prediction of mediation analyses showed that the lesion load of the left arcuate fasciculus mediated the relationship between axial diffusivity from the left arcuate fasciculus and chronic language performance. Language performance at subacute and chronic time points could be predicted by the integrity of the left arcuate fasciculus, whereas Δscores in the subacute and chronic phases depended on the left inferior frontal-occipital fasciculus, showing a dissociation of the white matter pathways about language outcomes. These results suggest a functional differentiation of the dual-stream components in PSA recovery.

Severe motor impairment is associated with lower contralesional brain age in chronic stroke.

Stroke leads to complex chronic structural and functional brain changes that specifically affect motor outcomes. The brain-predicted age difference (brain-PAD) has emerged as a sensitive biomarker. Our previous study showed higher global brain-PAD associated with poorer motor function post-stroke. However, the relationship between local stroke lesion load, regional brain age, and motor impairment remains unclear. We studied 501 individuals with chronic unilateral stroke (>180 days post-stroke) from the ENIGMA Stroke Recovery Working Group dataset (34 cohorts). Structural T1-weighted MRI scans were used to estimate regional brain-PAD in 18 predefined functional subregions via a graph convolutional network algorithm. Lesion load for each region was calculated based on lesion overlap. Linear mixed-effects models assessed associations between lesion size, local lesion load, and regional brain-PAD. Machine learning classifiers predicted motor outcomes using lesion loads and regional brain-PADs. Structural equation modeling examined directional relationships among corticospinal tract lesion load (CST-LL), ipsilesional brain-PAD, motor outcomes, and contralesional brain-PAD. Larger total lesion size was positively associated with higher ipsilesional regional brain-PADs (older brain age) across most regions (p□<□0.05), and with lower contralesional brain-PAD, notably in the ventral attention-language network (p□<□0.05). Higher local lesion loads showed similar patterns. Specifically, lesion load in the salience network significantly influenced regional brain-PADs across both hemispheres. Machine learning models identified CST-LL, salience network lesion load, and regional brain-PAD in the contralesional frontoparietal network as the top three predictors of motor outcomes. Structural equation modeling revealed that larger stroke damage was associated with poorer motor outcomes (β□=□-0.355, p□<□0.001), which were further linked to younger contralesional brain age (β□=□0.204, p□<□0.001), suggesting that severe motor impairment is linked to compensatory decreases in contralesional brain age. Our findings reveal that larger stroke lesions are associated with accelerated aging in the ipsilesional hemisphere and paradoxically decelerated brain aging in the contralesional hemisphere, suggesting compensatory neural mechanisms. Assessing regional brain age may serve as a biomarker for neuroplasticity and inform targeted interventions to enhance motor recovery after stroke. Micheal J Fox Foundation, National Institutes of Health, Canadian Institutes of Health Research, National Health and Medical Research Council, Australian Brain Foundation, Wicking Trust, Collie Trust, and Sidney and Fiona Myer Family Foundation, National Heart Foundation, Hospital Israelita Albert Einstein, Australian Research Council Future Fellowship, Wellcome Trust, National Institute for Health Research Imperial Biomedical Research Centre, European Research Council, Deutsche Forschungsgemeinschaft, REACT Pilot, National Resource Center, Research Council of Norway, South-Eastern Norway Regional Health Authority, Norwegian Extra Foundation for Health and Rehabilitation, Sunnaas Rehabilitation Hospital HT, University of Oslo, and VA Rehabilitation Research and Development.

Glymphatic dysfunction in multiple sclerosis and its association with disease pathology and disability.

The role of the glymphatic system in multiple sclerosis (MS)-related disability remains underexplored. Diffusion-tensor image analysis along the perivascular space (DTI-ALPS) offers a non-invasive method to assess glymphatic function. To evaluate glymphatic function in MS patients with lower and higher disability. This study included 118 MS patients who underwent structural, diffusion-weighted imaging, and clinical assessment. The participants were divided into lower (MS-L, n = 57) and higher disability (MS-H, n = 61) subgroups. Brain parenchymal fraction (BPF), lesion load (LL), and DTI-ALPS index were measured. Subgroup differences and correlations between DTI-ALPS index and other measures were explored. Logistic regression was performed to evaluate BPF, LL, and DTI-ALPS index in classifying lower and higher disability patients. Significant differences in DTI-ALPS index between MS-H and MS-L (d = -0.71, false discovery rate-corrected p-value (p-FDR) = 0.001) were found. The DTI-ALPS index correlated significantly with disease duration (rp = -0.29, p-FDR = 0.002) and EDSS (rsp = -0.35, p-FDR = 0.0002). It also showed significant correlations with BPF and LL. DTI-ALPS index and LL were significant predictors of disability subgroup (DTI-ALPS: odds ratio (OR) = 1.77, p = 0.04, LL: OR = 0.94, p = 0.02). Our findings highlight DTI-ALPS index as an imaging biomarker in MS, suggesting the involvement of glymphatic impairment in MS pathology, although further research is needed to elucidate its role in contributing to MS-related disability.

Cerebrovascular pulsatility indicates preoperative subcortical cognitive impairment and an increased risk for postoperative delirium in elderly patients undergoing elective spine surgery.

Advances in spine surgery enable safe interventions in elderly patients, but perioperative neurocognitive disorders (pNCD), such as post-operative delirium (POD) and cognitive dysfunction (POCD), remain a serious concern. Pre-operative cognitive impairment is a major risk factor for pNCD. Comprehensive pre-operative cognitive assessments are not feasible in clinical practice, making effective screening methods desirable. This study investigates whether pre-operative cerebrovascular duplex sonography can assess subcortical (vascular) cognitive impairment and the risk for POD. This prospective single-center study recruited patients aged ≥60 years scheduled for elective spine surgery at a German university hospital. Patients underwent pre-operative assessments including cognitive abilities (CERAD test battery), structural MRI, and cerebrovascular duplex sonography. POD screening was conducted three times daily for at least 3 days. The primary hypothesis, that the mean pulsatility index (PI) of both internal carotid arteries (ICA) predicts POD risk, was tested using logistic regression. Secondary analyses examined the association between POD risk and ICA flow (time-averaged peak velocities, TAPV) and correlations with cognitive profiles and MRI characteristics. POD occurred in 22% of patients (n = 22/99) within three postoperative days. Patients with POD were significantly older (75.9 ± 5.4 vs. 70.0 ± 6.9 years, p < 0.01) but did not differ by gender (p = 0.51). ICA PI significantly predicted POD risk (OR = 5.46 [95%CI: 1.81-16.49], p = 0.003), which remained significant after adjustment for age and duration of surgery (ORadj = 6.38 [95% CI: 1.77-23.03], p = 0.005). TAPV did not inform the POD risk (p = 0.68). ICA PI Pre-operative cognitive scores were significantly associated with ICA PI (mean CERAD score: r = -0.32, p < 0.001). ICA PI was also significantly associated with total white matter lesion volume (τ = 0.19, p = 0.012) and periventricular white matter lesion volume (τ = 0.21, p = 0.007). This is the first study to demonstrate that cerebrovascular duplex sonography can assess the risk for POD in elderly spine surgery patients. Increased ICA PI may indicate subcortical impairment, larger white matter lesion load, and lower white matter volume, predisposing factors for POD. Pre-operative cerebrovascular duplex sonography of the ICA is widely available, easy-to-use, and efficient, offering a promising screening method for POD risk. Increased ICA PI could supplement established predictors like age to adjust surgical and peri-operative procedures to individual risk profiles.

Prognostic factors for disease activity in newly diagnosed teriflunomide-treated patients with multiple sclerosis: a nationwide Danish study

BackgroundClinicians frequently rely on relapse counts, T2 MRI lesion load (T2L) and Expanded Disability Status Scale (EDSS) scores to guide treatment decisions for individuals diagnosed with multiple sclerosis (MS). This...

Consensus of algorithms for lesion segmentation in brain MRI studies of multiple sclerosis

Segmentation of multiple sclerosis (MS) lesions on brain MRI scans is crucial for diagnosis, disease and treatment monitoring but is a time-consuming task. Despite several automated algorithms have been proposed, there is still no consensus on the most effective method. Here, we applied a consensus-based framework to improve lesion segmentation on T1-weighted and FLAIR scans. The framework is designed to combine publicly available state-of-the-art deep learning models, by running multiple segmentation tasks before merging the outputs of each algorithm. To assess the effectiveness of the approach, we applied it to MRI datasets from two different centers, including a private and a public dataset, with 131 and 30 MS patients respectively, with manually segmented lesion masks available. No further training was performed for any of the included algorithms. Overlap and detection scores were improved, with Dice increasing by 4-8% and precision by 3-4% respectively for the private and public dataset. High agreement was obtained between estimated and true lesion load (ρ = 0.92 and ρ = 0.97) and count (ρ = 0.83 and ρ = 0.94). Overall, this framework ensures accurate and reliable results, exploiting complementary features and overcoming some of the limitations of individual algorithms.

Investigating colour vision and its structural correlates 15 years following a first demyelinating event

BackgroundWe investigated the long-term colour and contrast vision outcomes, 15 years after a first demyelinating event, with their structural correlates using optical coherence tomography (OCT) and brain MRI.MethodsPatients recruited with...

Prediction models of the aphasia severity after stroke by lesion load of cortical language areas and white matter tracts: An atlas-based study

ObjectiveTo construct relatively objective, atlas-based multivariate models for predicting early aphasia severity after stroke, using structural magnetic resonance imaging. MethodsWe analyzed the clinical and imaging data of 46 patients with post-stroke aphasia. The aphasia severity was identified with a Western Aphasia Battery Aphasia Quotient. The assessments of stroke lesions were indicated by the lesion load of both the cortical language areas (Areas-LL) and four white matter tracts (i.e., the superior longitudinal fasciculus, SLF-LL; the inferior frontal occipital fasciculi, IFOF-LL; the inferior longitudinal, ILF-LL; and the uncinate fasciculi, UF-LL) extracted from human brain atlas. Correlation analyses and multiple linear regression analyses were conducted to evaluate the correlations between demographic, stroke- and lesion-related variables and aphasia severity. The predictive models were then established according to the identified significant variables. Finally, the receiver operating characteristic (ROC) curve was utilized to assess the accuracy of the predictive models. ResultsThe variables including Areas-LL, the SLF-LL, and the IFOF-LL were significantly negatively associated with aphasia severity (p < 0.05). In multiple linear regression analyses, these variables accounted for 59.4 % of the variance (p < 0.05). The ROC curve analyses yielded the validated area under the curve (AUC) 0.84 both for Areas-LL and SLF-LL and 0.76 for IFOF-LL, indicating good predictive performance (p < 0.01). Adding the combination of SLF-LL and IFOF-LL to this model increased the explained variance to 62.6 % and the AUC to 0.92. ConclusionsThe application of atlas-based multimodal lesion assessment may help predict the aphasia severity after stroke, which needs to be further validated and generalized for the prediction of more outcome measures in populations with various brain injuries.

Analysis of white matter hyperintensities in Alzheimer’s disease and vascular dementia with magnetic resonance imaging

Objectives: The study aimed to analyze the brain white matter hyperintensities (WMHs) of patients with vascular dementia (VaD) and Alzheimer’s disease (AD) using magnetic resonance imaging to determine whether white matter lesions in the brain could be detected by a computer using image processing methods. Patients and methods: In this retrospective observational study, a unimodal, unsupervised, and automatic method was developed, and magnetic resonance imaging of 35 patients were examined. Of the 35 patients, 19 (14 males, 5 females; mean age: 73.2±6.7 years; range, 56 to 83 years) were picked from patients with AD or VaD who were admitted to a neurology clinic between January 2016 and December 2022 (Group 1). The remaining 16 patients (10 females, 5 males; mean age: 80.4±5.4 years; range, 69 to 92 years) were included from the ABVIB (Aging Brain: Vasculature, Ischemia, and Behavior) study from the ADNI (Alzheimer’s Disease Neuroimaging Initiative) database (Group 2). To calculate the volume of WMHs, a detailed analysis was conducted. Initially, skull stripping was performed, and then the brain was segmented. Afterward, two types of masks (Mask1 and Mask-2) were obtained by applying painting, decreasing, and blurring processes to the segmented white matter. These masks limited the region that was searched for WMHs. With this limitation, false positives that could arise from gray matter intensities were tried to be prevented. To evaluate the accuracy of WMH detection, a user interface was developed, and manual marking was conducted by an expert neurologist. After WMH detection, WMH volumes were calculated. Results: For Group 1, the similarity index was found to be 0.76 for Mask-1 and 0.80 for Mask-2, while for Group 2, the similarity index was 0.71 for Mask-1 and 0.87 for Mask-2. In patients with AD, the mean WMH lesion load (LL) was 15.16±16.59 mL. In patients with VaD, who were expected to suffer more from WMHs, the mean WMH LL was 29.22±11.40 mL. In Group 2, the mean WMH LL was 17.77±12.26 mL. Conclusion: This study may contribute to the literature since it is an automatic, unimodal, and unsupervised method that was applied to both a completely unique data set with many different scanning parameters and an open database data set.

Prediction of Upper Limb Motor Recovery by the PREP2 Algorithm in a Nonselected Population: External Validation and Influence of Cognitive Syndromes

Background Early prediction of poststroke motor recovery is challenging in clinical settings. The Prediction recovery potential (PREP2) algorithm is the most accurate approach for prediction of Upper Limb function available to date but lacks external validation. Objectives (i) To externally validate the PREP2 algorithm in a prospective cohort, (ii) to study the characteristics of patients misclassified by the algorithm, and (iii) to compare the performance according to the presence of cognitive syndromes (aphasia, neglect, cognitive disorders). Methods We enrolled 143 patients with stroke and upper extremity weakness persistent at Day 3. Evaluation to predict the recovery status according to the PREP2 algorithm included age, SAFE and NIHSS scores at Day 3 and transcranial magnetic stimulation to determine the presence of the motor-evoked potential before day seven. Actual recovery (excellent, good, limited, or poor) was defined based on the Action Research Arm test score at 3 months. Accuracy was computed by comparing the predictions of the PREP2 and the actual category of the patient. Additionally, to investigate misclassifications and the impact of cognitive syndromes, we recorded SAFE and NIHSS scores at Day 7, the Montreal Cognitive Assessment (MoCA) score, the presence of aphasia and neglect and Magnetic Resonance Imaging was used to evaluate the corticospinal tract lesion load. Results The PREP2 algorithm showed a very good predictive value with 78% accuracy [95% CI: 71.2%-86.1%], especially for the extreme categories of recovery (EXCELLENT 87.5% [95% CI: 78.9%-96.2%] and POOR 94.9% [95% CI: 87.9%-100%]), and only 46.5% [95% CI: 19.05%-73.25%] for the GOOD category and even worse than chance for the LIMITED category 0%. Pessimistic predictions (false-negative cases) had a drastic improvement in the SAFE score acutely compared to that of well-predicted patients with unfavorable recovery (P < 001). The predictive value of PREP2 decreased significantly when patients had cognitive disorders (MoCA score <24) versus not (69.4% [95% CI: 52.8%-86.1%] vs 93.1% [95% CI: 83.9%-100%], P = .01). Conclusion Our study provides an external validation of the PREP2 algorithm in a prospective population and underlines the importance of taking into account cognitive syndromes in motor recovery prediction.

Fatigue in early multiple sclerosis: MRI metrics of neuroinflammation, relapse and neurodegeneration.

Multiple sclerosis (MS) is a neuroinflammatory and neurodegenerative disease affecting the brain and spinal cord. Fatigue is a common disabling symptom from MS onset, however the mechanisms by which underlying disease processes cause fatigue remain unclear. Improved pathophysiological understanding offers potential for improved treatments for MS-related fatigue. MRI provides insights into in vivo neuroinflammatory activity and neurodegeneration, although existing evidence for imaging correlates of MS fatigue is mixed. We explore associations between fatigue and MRI measures in the brain and spinal cord to identify neuroinflammatory and regional neurodegenerative substrates of fatigue in early relapsing-remitting MS (RRMS). Recently diagnosed (<6 months), treatment-naive people with RRMS (n = 440) were recruited to a longitudinal multi-centre nationally representative cohort study. Participants underwent 3-Tesla brain MRI at baseline and one year. We calculated global and regional white and grey matter volumes, white matter lesion (WML) load and upper cervical spinal cord cross-sectional area levels C2-3, and assessed new/enlarging WMLs visually. Participants were classed as fatigued or non-fatigued at baseline according to the Fatigue Severity Scale (>/≤36). Disability and depression were assessed with the expanded-disability status scale and Patient Health Questionnaire, respectively. MRI measures were compared between fatigue groups, both cross-sectionally and longitudinally, using regression analyses. Higher disability and depression scores were observed for participants with fatigue, with a higher number of fatigued participants receiving disease-modifying treatments at follow-up. Structural MRI data for brain were available for n = 313 (45% fatigued) and for spinal cord for n = 324 (46% fatigued). Cervical spinal cord cross-sectional area 2-3, white and grey matter volumes decreased, and WML volume increased, over time for both groups (q < 0.05). However, no significant between-group differences in these measures were found either cross-sectionally or longitudinally (q > 0.05). The presence of new/enlarging WMLs (49% in fatigued; 51% in non-fatigued) at follow-up also did not differ between groups (q > 0.05). Our results suggest that fatigue is not driven by neuroinflammation or neurodegeneration measurable by current structural MRI in early RRMS. This novel negative finding in a large multi-centre cohort of people with recently diagnosed RRMS helps to resolve uncertainty in existing literature. Notably, we showed that fatigue is prevalent in patients without brain radiological relapse, who may be considered to have inactive disease. This suggests that symptom detection and treatment should remain a clinical priority regardless of neuroinflammatory disease activity. More sensitive objective biomarkers are needed to elucidate fatigue mechanisms in RRMS, and ultimately facilitate development of effective targeted treatments for this important 'hidden disability'.

Radix Isatidis polysaccharide (RIP) alleviates QX-genotype infectious bronchitis virus-induced interstitial nephritis through the Nrf2/NLRP3/Caspase-3 signaling pathway

Interstitial nephritis is the primary cause of mortality in IBV-infected chickens. Our previous research has demonstrated that Radix Isatidis polysaccharide (RIP) could alleviate this form of interstitial nephritis. To explore the mechanism, SPF chickens and chicken embryonic kidney cells (CEKs) were pre-treated with RIP and subsequently infected with QX-genotype IBV strain. Kidneys were sampled for transcriptomic and metabolomic analyses, and the cecum contents were collected for 16S rRNA gene sequencing. Results showed that pre-treatment with RIP led to a 50 % morbidity reduction in infected-chickens, along with decreased tissue lesion and viral load in the kidneys. Multi-omics analysis indicated three possible pathways (including antioxidant, anti-inflammatory and anti-apoptosis) which associated with RIP's efficacy against interstitial nephritis. Following further validation both in vivo and in vitro, the results showed that pre-treatment with RIP could activate the antioxidant transcription factor Nrf2, stimulate antioxidant enzyme expression, and consequently inhibit oxidative stress. Pre-treatment with RIP could also significantly reduce the expression of NLRP3 inflammasome and apoptosis-associated proteins (including Bax, Caspase-3, and Caspase-9). Additionally, RIP was also observed to promote the growth of beneficial bacteria in the intestine. Overall, pretreatment with RIP can alleviate QX-genotype IBV-induced interstitial nephritis via the Nrf2/NLRP3/Caspase-3 signaling pathway. This study lays the groundwork for the potential use of RIP in controlling avian infectious bronchitis (IB).

Comparison between the diagnostic utility of three-dimensional fluid attenuated inversion recovery (3D FLAIR) and three dimensional double inversion recovery (3D DIR) magnetic resonance sequences in the assessment of overall load of multiple sclerosis lesions in the brain

BackgroundMultiple sclerosis (MS) is a complex CNS demyelinating disease. Assessment of MS plaques in specific anatomic locations in the brain was challenging to detect by conventional MRI sequences. So, this study aimed to compare the diagnostic accuracy of 3D FLAIR (Fluid attenuation inversion recovery), or 3D DIR (Double inversion recovery) sequences to conventional 2D FLAIR and T2 sequences in detecting MS plaques in different anatomic sites, as well as counting the total lesion burden.MethodsA comparative cross-sectional study enrolled 30 MS patients on the basis of McDonald’s criteria 2017. All participants underwent a brain MRI study including 3D FLAIR or 3D DIR sequences, conventional 2D FLAIR, and T2 sequences.ResultsNo statistically significant difference between the 3D DIR and 3D FLAIR in total lesion (plaque) burden results; however, when each is compared to the conventional ones, both are superior. 3D FLAIR detected the most significant number of plaques in the periventricular region, followed by 2D FLAIR and T2W sequences, with 3D DIR being the least accurate in this region. Meanwhile, 3D DIR was the most precise and can detect a statistically significant number of cortical plaques compared to the 3D FLAIR and the conventional sequences. No statistically significant results on which sequence is best in regard to infratentorial plaque detection.Conclusion3D FLAIR and 3D DIR were superior to 2D FLAIR and T2 sequences in detecting overall lesion burden in MS. Moreover, the 3D DIR sequence was the most precise in the detection of the cortical plaques.

DXA-Measured Abdominal Adipose Depots and Structural Brain Integrity in Postmenopausal Women.

This study extends prior research from the MRI substudy of the Women's Health Initiative Memory Study (WHIMS-MRI) linking BMI to reduced brain atrophy and ischemic lesion load by examining DXA-based measurements of total body fat, total abdominal adipose tissue (TAT), abdominal visceral (VAT) and subcutaneous (SAT) adipose tissue, gynoid fat, and overall leg fat. The analytic sample consisted of 61 postmenopausal women (baseline mean age 69.5 [3.6]) enrolled in WHIMS-MRI who had undergone DXA scans. DXA scans were completed at years 0, 3, and 6, and MRI scans were conducted ~8 years after baseline. Adjusted linear regression models were used to analyze the association between adiposity averaged across the 3-time points and volumes of brain regions previously linked to dementia. Higher levels of total body fat, TAT, VAT, SAT, gynoid, and overall leg fat were associated with larger hippocampal volume (β 0.02 [95% CI, 0.004-0.04]; 0.11 [0.02-0.21]; 0.26 [0.04-0.47]; 0.18 [0.03-0.33]; 0.18 [0.05-0.30]; 0.07 [0.009-0.12], respectively). No other significant associations were observed. Higher levels of adiposity were positively associated with hippocampal volume. Additional research with larger sample sizes is needed to ascertain the significance of this association.