Gadolinium-based MRI characterization of leptomeningeal inflammation in multiple sclerosis.
Ontology highlight
ABSTRACT: Objective
To determine the frequency and nature of leptomeningeal contrast enhancement in multiple sclerosis (MS) via in vivo 3-tesla postcontrast T2-weighted, fluid-attenuated inversion recovery (FLAIR) MRI and 7-tesla postmortem MRI-pathology correlation.Methods
Brain MRI, using the postcontrast T2-weighted, FLAIR technique, was prospectively collected in 299 MS cases and 37 age-matched neurologically healthy controls. Expert raters evaluated focal gadolinium enhancement in the leptomeningeal compartment. Two progressive MS cases came to autopsy after in vivo MRI characterization. Pathologic and immunohistochemical examination assessed the association of enhancement with leptomeningeal inflammation and adjacent cortical demyelination.Results
Focal contrast enhancement was detected in the leptomeningeal compartment in 74 of 299 MS cases (25%) vs 1 of 37 neurologically healthy controls (2.7%; p = 0.001). Enhancement was nearly twice as frequent (p = 0.009) in progressive MS (39/118 cases, 33%) as in relapsing-remitting MS (35/181, 19%). Enhancing foci generally remained stable throughout the evaluation period (up to 5.5 years). Pathology showed perivascular lymphocytic and mononuclear infiltration in the enhancing areas in association with flanking subpial cortical demyelination.Conclusion
Leptomeningeal contrast enhancement occurs frequently in MS and is a noninvasive, in vivo marker of inflammation and associated subpial demyelination. It might therefore enable testing of new treatments aimed at eliminating this inflammation and potentially arresting progressive MS.
SUBMITTER: Absinta M
PROVIDER: S-EPMC4501940 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundAutopsy data suggest a causative link between meningeal inflammation and cortical lesions (CLs) in multiple sclerosis (MS).ObjectiveTo use leptomeningeal enhancement (LME) and CLs on 7-Tesla (7T) magnetic resonance imaging (MRI) to investigate associations between meningeal inflammation and cortical pathology.MethodsForty-one participants with MS underwent 7T MRI of the brain. CLs and foci of LME were quantified.ResultsAll MS participants had CLs; 27 (65.8%) had >1 focus of LME. Except for hippocampal CL count (ρ = 0.32 with spread/fill-sulcal pattern LME, p = 0.042), no significant correlations were seen between LME and CLs. Mean cortical thickness correlated with the number of LME foci (ρ = -0.43, p = 0.005). Participants with relapsing-remitting multiple sclerosis (RRMS) showed no correlation with neocortical CLs, but significant correlations were seen between LME and hippocampal lesion count (ρ = 0.39, p = 0.030), normalized cortical gray matter (GM) volume (ρ = -0.49, p = 0.005), and mean cortical thickness (ρ = -0.59, p < 0.001).ConclusionThis study supports a relationship between LME and cortical GM atrophy but does not support an association of LME and neocortical CLs. This may indicate that meningeal inflammation is involved with neurodegenerative inflammatory processes, rather than focal lesion development.
| S-EPMC7021560 | biostudies-literature
Project description:Gadolinium-enhancing lesions reflect active disease and are critical for in-patient monitoring in multiple sclerosis (MS). In this work, we have developed the first fully automated method to segment and count the gadolinium-enhancing lesions from routine clinical MRI of MS patients. The proposed method first segments the potential lesions using 2D-UNet from multi-channel scans (T1 post-contrast, T1 pre-contrast, FLAIR, T2, and proton-density) and classifies the lesions using a random forest classifier. The algorithm was trained and validated on 600 MRIs with manual segmentation. We compared the effect of loss functions (Dice, cross entropy, and bootstrapping cross entropy) and number of input contrasts. We compared the lesion counts with those by radiologists using 2,846 images. Dice, lesion-wise sensitivity, and false discovery rate with full 5 contrasts were 0.698, 0.844, and 0.307, which improved to 0.767, 0.969, and 0.00 in large lesions (>100 voxels). The model using bootstrapping loss function provided a statistically significant increase of 7.1% in sensitivity and of 2.3% in Dice compared with the model using cross entropy loss. T1 post/pre-contrast and FLAIR were the most important contrasts. For large lesions, the 2D-UNet model trained using T1 pre-contrast, FLAIR, T2, PD had a lesion-wise sensitivity of 0.688 and false discovery rate 0.083, even without T1 post-contrast. For counting lesions in 2846 routine MRI images, the model with 2D-UNet and random forest, which was trained with bootstrapping cross entropy, achieved accuracy of 87.7% using T1 pre-contrast, T1 post-contrast, and FLAIR when lesion counts were categorized as 0, 1, and 2 or more. The model performs well in routine non-standardized MRI datasets, allows large-scale analysis of clinical datasets, and may have clinical applications.
| S-EPMC8409666 | biostudies-literature
Project description:IntroductionLocal microstructural pathology in multiple sclerosis patients might influence their clinical performance. This study applied multicontrast MRI to quantify inflammation and neurodegeneration in MS lesions. We explored the impact of MRI-based lesion pathology in cognition and disability.Methods36 relapsing-remitting MS subjects and 18 healthy controls underwent neurological, cognitive, behavioural examinations and 3 T MRI including (i) fluid attenuated inversion recovery, double inversion recovery, and magnetization-prepared gradient echo for lesion count; (ii) T1, T2, and T2(*) relaxometry and magnetisation transfer imaging for lesion tissue characterization. Lesions were classified according to the extent of inflammation/neurodegeneration. A generalized linear model assessed the contribution of lesion groups to clinical performances.ResultsFour lesion groups were identified and characterized by (1) absence of significant alterations, (2) prevalent inflammation, (3) concomitant inflammation and microdegeneration, and (4) prevalent tissue loss. Groups 1, 3, 4 correlated with general disability (Adj-R (2) = 0.6; P = 0.0005), executive function (Adj-R (2) = 0.5; P = 0.004), verbal memory (Adj-R (2) = 0.4; P = 0.02), and attention (Adj-R (2) = 0.5; P = 0.002).ConclusionMulticontrast MRI provides a new approach to infer in vivo histopathology of plaques. Our results support evidence that neurodegeneration is the major determinant of patients' disability and cognitive dysfunction.
| S-EPMC4532805 | biostudies-literature
Project description:IntroductionBoth aging and multiple sclerosis (MS) cause central nervous system (CNS) atrophy. Excess brain atrophy in MS has been interpreted as "accelerated aging." Current paper tests an alternative hypothesis: MS causes CNS atrophy by mechanism(s) different from physiological aging. Thus, subtracting effects of physiological confounders on CNS structures would isolate MS-specific effects.MethodsStandardized brain MRI and neurological examination were acquired prospectively in 646 participants enrolled in ClinicalTrials.gov Identifier: NCT00794352 protocol. CNS volumes were measured retrospectively, by automated Lesion-TOADS algorithm and by Spinal Cord Toolbox, in a blinded fashion. Physiological confounders identified in 80 healthy volunteers were regressed out by stepwise multiple linear regression. MS specificity of confounder-adjusted MRI features was assessed in non-MS cohort (n = 158). MS patients were randomly split into training (n = 277) and validation (n = 131) cohorts. Gradient boosting machine (GBM) models were generated in MS training cohort from unadjusted and confounder-adjusted CNS volumes against four disability scales.ResultsConfounder adjustment highlighted MS-specific progressive loss of CNS white matter. GBM model performance decreased substantially from training to cross-validation, to independent validation cohorts, but all models predicted cognitive and physical disability with low p-values and effect sizes that outperform published literature based on recent meta-analysis. Models built from confounder-adjusted MRI predictors outperformed models from unadjusted predictors in the validation cohort.ConclusionGBM models from confounder-adjusted volumetric MRI features reflect MS-specific CNS injury, and due to stronger correlation with clinical outcomes compared to brain atrophy these models should be explored in future MS clinical trials.
| S-EPMC10365278 | biostudies-literature
Project description:The properties of a novel Gd(3+)-based MRI zinc sensor are reported. Unlike previously reported Gd(3+)-based MRI contrast agents, this agent (GdL) differs in that the agent alone binds only weakly with human serum albumin (HSA), while the 1:2 GdL:Zn(2+) ternary complex binds strongly to HSA resulting in a substantial, 3-fold increase in water proton relaxivity. The GdL complex is shown to have a relatively strong binding affinity for Zn(2+) (K(D) = 33.6 nM), similar to the affinity of the Zn(2+) ion with HSA alone. The agent detects as little as 30 microM Zn(2+) in the presence of HSA by MRI in vitro, a value slightly more than the total Zn(2+) concentration in blood (approximately 20 microM). This combination of binding affinity constants and the high relaxivity of the agent when bound to HSA suggests that this new agent may be useful for detection of free Zn(2+) ions in vivo without disrupting other important biological processes involving Zn(2+).
| S-EPMC2745615 | biostudies-literature
Project description:Concerns have arisen about the long-term health effects of repeat gadolinium injections in patients with multiple sclerosis and the incomplete characterization of MS lesion pathophysiology that results from relying on enhancement characteristics alone.Our aim was to perform a systematic review and meta-analysis analyzing whether noncontrast MR imaging biomarkers can distinguish enhancing and nonenhancing brain MS lesions.Our sources were Ovid MEDLINE, Ovid Embase, and the Cochrane data base from inception to August 2016.We included 37 journal articles on 985 patients with MS who had MR imaging in which T1-weighted postcontrast sequences were compared with noncontrast sequences obtained during the same MR imaging examination by using ROI analysis of individual MS lesions.We performed random-effects meta-analyses comparing the standard mean difference of each MR imaging metric taken from enhancing-versus-nonenhancing lesions.DTI-based fractional anisotropy values are significantly different between enhancing and nonenhancing lesions (P = .02), with enhancing lesions showing decreased fractional anisotropy compared with nonenhancing lesions. Of the other most frequently studied MR imaging biomarkers (mean diffusivity, magnetization transfer ratio, or ADC), none were significantly different (P values of 0.30, 0.47, and 0.19. respectively) between enhancing and nonenhancing lesions. Of the limited studies providing diagnostic accuracy measures, gradient-echo-based quantitative susceptibility mapping had the best performance in discriminating enhancing and nonenhancing MS lesions.MR imaging techniques and patient characteristics were variable across studies. Most studies did not provide diagnostic accuracy measures. All imaging metrics were not studied in all 37 studies.Noncontrast MR imaging techniques, such as DTI-based FA, can assess MS lesion acuity without gadolinium.
| S-EPMC5509500 | biostudies-literature
Project description:ObjectiveThe aim of this study is to assess the performance of deep learning convolutional neural networks (CNNs) in segmenting gadolinium-enhancing lesions using a large cohort of multiple sclerosis (MS) patients.MethodsA three-dimensional (3D) CNN model was trained for segmentation of gadolinium-enhancing lesions using multispectral magnetic resonance imaging data (MRI) from 1006 relapsing-remitting MS patients. The network performance was evaluated for three combinations of multispectral MRI used as input: (U5) fluid-attenuated inversion recovery (FLAIR), T2-weighted, proton density-weighted, and pre- and post-contrast T1-weighted images; (U2) pre- and post-contrast T1-weighted images; and (U1) only post-contrast T1-weighted images. Segmentation performance was evaluated using the Dice similarity coefficient (DSC) and lesion-wise true-positive (TPR) and false-positive (FPR) rates. Performance was also evaluated as a function of enhancing lesion volume.ResultsThe DSC/TPR/FPR values averaged over all the enhancing lesion sizes were 0.77/0.90/0.23 using the U5 model. These values for the largest enhancement volumes (>500 mm3) were 0.81/0.97/0.04. For U2, the average DSC/TPR/FPR values were 0.72/0.86/0.31. Comparable performance was observed with U1. For all types of input, the network performance degraded with decreased enhancement size.ConclusionExcellent segmentation of enhancing lesions was observed for enhancement volume ⩾70 mm3. The best performance was achieved when the input included all five multispectral image sets.
| S-EPMC7680286 | biostudies-literature
Project description:ObjectiveTo estimate longitudinal changes in a quantitative whole-brain and tract-specific MRI study of multiple sclerosis (MS), with the intent of assessing the feasibility of this approach in clinical trials.MethodsA total of 78 individuals with MS underwent a median of 3 scans over 2 years. Diffusion tensor imaging indices, magnetization transfer ratio, and T2 relaxation time were analyzed in supratentorial brain, corpus callosum, optic radiations, and corticospinal tracts by atlas-based tractography. Linear mixed-effect models estimated annualized rates of change for each index, and sample size estimates for potential clinical trials were determined.ResultsThere were significant changes over time in fractional anisotropy and perpendicular diffusivity in the supratentorial brain and corpus callosum, mean diffusivity in the supratentorial brain, and magnetization transfer ratio in all areas studied. Changes were most rapid in the corpus callosum, where fractional anisotropy decreased 1.7% per year, perpendicular diffusivity increased 1.2% per year, and magnetization transfer ratio decreased 0.9% per year. The T2 relaxation time changed more rapidly than diffusion tensor imaging indices and magnetization transfer ratio but had higher within-participant variability. Magnetization transfer ratio in the corpus callosum and supratentorial brain declined at an accelerated rate in progressive MS relative to relapsing-remitting MS. Power analysis yielded reasonable sample sizes (on the order of 40 participants per arm or fewer) for 1- or 2-year trials.ConclusionsLongitudinal changes in whole-brain and tract-specific diffusion tensor imaging indices and magnetization transfer ratio can be reliably quantified, suggesting that small clinical trials using these outcome measures are feasible.
| S-EPMC3030233 | biostudies-literature
Project description:Diffusion magnetic resonance imaging can reveal quantitative information about the tissue changes in multiple sclerosis. The recently developed multi-compartment spherical mean technique can map different microscopic properties based only on local diffusion signals, and it may provide specific information on the underlying microstructural modifications that arise in multiple sclerosis. Given that the lesions in multiple sclerosis may reflect different degrees of damage, we hypothesized that quantitative diffusion maps may help characterize the severity of lesions "in vivo" and correlate these to an individual's clinical profile. We evaluated this in a cohort of 59 multiple sclerosis patients (62% female, mean age 44.7 years), for whom demographic and disease information was obtained, and who underwent a comprehensive physical and cognitive evaluation. The magnetic resonance imaging protocol included conventional sequences to define focal lesions, and multi-shell diffusion imaging was used with b-values of 1000, 2000 and 3000 s/mm2 in 180 encoding directions. Quantitative diffusion properties on a macro- and micro-scale were used to discriminate distinct types of lesions through a k-means clustering algorithm, and the number and volume of those lesion types were correlated with parameters of the disease. The combination of diffusion tensor imaging metrics (fractional anisotropy and radial diffusivity) and multi-compartment spherical mean technique values (microscopic fractional anisotropy and intra-neurite volume fraction) differentiated two type of lesions, with a prediction strength of 0.931. The B-type lesions had larger diffusion changes compared to the A-type lesions, irrespective of their location (P < 0.001). The number of A and B type lesions was similar, although in juxtacortical areas B-type lesions predominated (60%, P < 0.001). Also, the percentage of B-type lesion volume was higher (64%, P < 0.001), indicating that these lesions were larger. The number and volume of B-type lesions was related to the severity of disease evolution, clinical disability and cognitive decline (P = 0.004, Bonferroni correction). Specifically, more and larger B-type lesions were correlated with a worse Multiple Sclerosis Severity Score, cerebellar function and cognitive performance. Thus, by combining several microscopic and macroscopic diffusion properties, the severity of damage within focal lesions can be characterized, further contributing to our understanding of the mechanisms that drive disease evolution. Accordingly, the classification of lesion types has the potential to permit more specific and better-targeted treatment of patients with multiple sclerosis.
| S-EPMC7502564 | biostudies-literature
Project description:The pathogenesis of multiple sclerosis is characterized by a cascade of pathobiologic events, ranging from focal lymphocytic infiltration and microglia activation to demyelination and axonal degeneration. MS has several of the hallmarks of an inflammatory autoimmune disorder, including breakdown of the BBB. Gadolinium-enhanced MR imaging is currently the reference standard to detect active inflammatory lesions in MS. Knowledge of the patterns and mechanisms of contrast enhancement is vital to limit the radiologic differential diagnosis in the staging and evaluation of MS lesion activity. The aim of this review was the following: 1) to outline the pathophysiology of the effect of lymphocyte-driven inflammation in MS, 2) to describe the effects of gadolinium on the BBB and glymphatic system, and 3) to describe gadolinium enhancement patterns and artifacts that can mimic lesions in MS.
| S-EPMC7655403 | biostudies-literature