Leukocortical Lesions Research Articles

Subtypes and location of (juxta)cortical lesions relate to cognitive dysfunction in people with multiple sclerosis

Background: Cortical lesion subtypes’ occurrence and distribution across networks may shed light on cognitive impairment (CI) in multiple sclerosis (MS). Methods: In 332 people with MS, lesions were classified as intracortical, leukocortical or juxtacortical based on artificially generated double inversion-recovery images. Results: CI-related leukocortical lesion count increases were greatest within sensorimotor and cognitive networks (p < 0.001). Only intracortical lesion count could distinguish between cognitive groups (p = 0.024). Effect sizes were two- to four-fold larger than differences between MS phenotypes. Conclusion: In CI-MS, leukocortical lesions predominate, whereas intracortical lesions distinguish cognitive groups. Lesions’ grey matter (GM) involvement might be decisive for cognition in MS, surpassing overall disease burden.

Cortical Lesions as an Early Hallmark of Multiple Sclerosis: Visualization by 7 T MRI.

Compelling evidence indicates a significant involvement of cortical lesions in the progressive phase of multiple sclerosis (MS), significantly contributing to late-stage disability. Despite the promise of ultra-high-field magnetic resonance imaging (MRI) in detecting cortical lesions, current evidence falls short in providing insights into the existence of such lesions during the early stages of MS or their underlying cause. This study delineated, at the early stage of MS, (1) the prevalence and spatial distribution of cortical lesions identified by 7 T MRI, (2) their relationship with white matter lesions, and (3) their clinical implications. Twenty individuals with early-stage relapsing-remitting MS (disease duration <1 year) underwent a 7 T MRI session involving T1-weighted MP2RAGE, T2*-weighted multiGRE, and T2-weighted FLAIR sequences for cortical and white matter segmentation. Disability assessments included the Expanded Disability Status Scale, the Multiple Sclerosis Functional Composite, and an extensive evaluation of cognitive function. Cortical lesions were detected in 15 of 20 patients (75%). MP2RAGE revealed a total of 190 intracortical lesions (median, 4 lesions/case [range, 0-44]) and 216 leukocortical lesions (median, 2 lesions/case [range, 0-75]). Although the number of white matter lesions correlated with the total number of leukocortical lesions (r = 0.91, P < 0.001), no correlation was observed between the number of white matter or leukocortical lesions and the number of intracortical lesions. Furthermore, the number of leukocortical lesions but not intracortical or white-matter lesions was significantly correlated with cognitive impairment (r = 0.63, P = 0.04, corrected for multiple comparisons). This study highlights the notable prevalence of cortical lesions at the early stage of MS identified by 7 T MRI. There may be a potential divergence in the underlying pathophysiological mechanisms driving distinct lesion types, notably between intracortical lesions and white matter/leukocortical lesions. Moreover, during the early disease phase, leukocortical lesions more effectively accounted for cognitive deficits.

White matter paramagnetic rim and non-rim lesions share a periventricular gradient in multiple sclerosis: A 7-T imaging study

Background: Paramagnetic rim white matter (WM) lesions (PRL) are thought to be a main driver of non-relapsing multiple sclerosis (MS) progression. It is unknown whether cerebrospinal fluid (CSF)-soluble factors diffusing from the ventricles contribute to PRL formation. Objective: To investigate the distribution of PRL and non-rim brain WM lesions as a function of distance from ventricular CSF, their relationship with cortical lesions, the contribution of lesion phenotype, and localization to neurological disability. Methods: Lesion count and volume of PRL, non-rim WM, leukocortical lesion (LCL), and subpial/intracortical lesions were obtained at 7-T. The brain WM was divided into 1-mm-thick concentric rings radiating from the ventricles to extract PRL and non-rim WM lesion volume from each ring. Results: In total, 61 MS patients with ⩾1 PRL were included in the study. Both PRL and non-rim WM lesion volumes were the highest in the periventricular WM and declined with increasing distance from ventricles. A CSF distance-independent association was found between non-rim WM lesions, PRL, and LCL, but not subpial/intracortical lesions. Periventricular non-rim WM lesion volume was the strongest predictor of neurological disability. Conclusions: Non-rim and PRL share a gradient of distribution from the ventricles toward the cortex, suggesting that CSF proximity equally impacts the prevalence of both lesion phenotypes.

Associations between cortical lesions, optic nerve damage, and disability at the onset of multiple sclerosis: insights into neurodegenerative processes.

BackgroundMultiple sclerosis cortical lesions are areas of demyelination and neuroaxonal loss. Retinal layer thickness, measured with optical coherence tomography (OCT), is an emerging biomarker of neuroaxonal loss. Studies have reported correlations between cortical lesions and retinal layer thinning in established multiple sclerosis, suggesting a shared pathophysiological process. Here, we assessed the correlation between cortical lesions and OCT metrics at the onset of multiple sclerosis, examining, for the first time, associations with physical or cognitive disability. ObjectiveTo examine the relationship between cortical lesions, optic nerve and retinal layer thicknesses, and physical and cognitive disability at the first demyelinating event. MethodsThirty-nine patients and 22 controls underwent 3T-MRI, optical coherence tomography, and clinical tests. We identified cortical lesions on phase-sensitive inversion recovery sequences, including occipital cortex lesions. We measured the estimated total intracranial volume and the white matter lesion volume. OCT metrics included peripapillary retinal nerve fibre layer (pRNFL), ganglion cell and inner plexiform layer (GCIPL) and inner nuclear layer (INL) thicknesses. ResultsHigher total cortical and leukocortical lesion volumes correlated with thinner pRNFL (B = -0.0005, 95 % CI -0.0008 to -0.0001, p = 0.01; B = -0.0005, 95 % CI -0.0008 to -0.0001, p = 0.01, respectively). Leukocortical lesion number correlated with colour vision deficits (B = 0.58, 95 %CI 0.039 to 1,11, p = 0.036). Thinner GCIPL correlated with a higher Expanded Disability Status Scale (B = -0.06, 95 % CI -1.1 to -0.008, p = 0.026). MS diagnosis (n = 18) correlated with higher cortical and leukocortical lesion numbers (p = 0.004 and p = 0.003), thinner GCIPL (p = 0.029) and INL (p = 0.041). ConclusionThe association between cortical lesions and axonal damage in the optic nerve reinforces the role of neurodegenerative processes in MS pathogenesis at onset.

Increased cortical lesion load contributed to pathological changes beyond focal lesion in cortical gray matter of multiple sclerosis: a diffusion kurtosis imaging analysis.

Biomarkers specific to cortical gray matter (cGM) pathological changes of multiple sclerosis (MS) are desperately needed to better understand the disease progression. The cGM damage occurs in cortical lesion (CL) and normal-appearing cGM (NAcGM) areas. While the association between CL load and cGM damage has been reported, little is known about how different CL types, i.e. intracortical lesion (ICL) and leukocortical lesion (LCL) would be associated with cGM damage. In our study, relapsing-remitting MS patients and healthy controls were divided into 4 groups according to CL load level. NAcGM diffusion kurtosis imaging (DKI)/diffusion tensor imaging (DTI) values and cGM volume (cGMV) were used to characterize the pathological changes in cGM. Univariate general linear model was used for group comparisons and stepwise regression analysis was used to assess the effects of ICL volume and LCL volume on NAcGM damage. We found peak values in DKI/DTI values, cGMV and neuropsychological scores in high CL load group. Kurtosis fractional anisotropy (KFA) was the most sensitive in characterizing NAcGM damage, and LCL volume related more to NAcGM damage. Our findings suggested KFA could become a surrogate biomarker to cGM damage, and LCL might be the main factor in whole brain NAcGM damage.

Association between retinal layer thickness and cortical lesions at the onset of clinically isolated syndrome (P11-3.012)

<h3>Objective:</h3> The aim of this study was to evaluate the relationship between retinal layer thickness, cortical lesions (CLs) and disability at the onset of the first demyelinating event (a clinically isolated syndrome (CIS), suggestive of multiple sclerosis (MS). <h3>Background:</h3> Neuroaxonal degeneration is considered the primary cause of permanent disability in patients with MS, thus new biomarkers to quantify neurodegeneration are needed. Reduced retinal layer thickness in MS exists irrespective of optic neuritis (ON) and has been correlated with disability and brain atrophy. In CLs, neuroaxonal degeneration is also present. The relationship between retinal atrophy, CLs and disability in CIS is not well established. <h3>Design/Methods:</h3> We performed a cross-sectional evaluation of thirty-nine patients with CIS known to have CLs as identified on 3T brain MRI, who also underwent Optical Coherence Tomography to quantify retinal layer thickness. We excluded affected eyes in ON patients and used the average values of both eyes in patients without ON. We performed linear regression analyses to evaluate the relationships between the retina measures and CLs characteristics as well as clinical outcomes. Significant results with p&lt;0.05 are reported. <h3>Results:</h3> We found that a thinner combined ganglion cell-inner plexiform layer (GCIPL) was associated with higher juxtacortical lesion numbers and volumes. A thinner peripapillary retinal nerve fiber was associated with higher leukocortical, juxtacortical and total cortical lesion volumes. A thinner GCIPL was correlated with greater disability as measured by the expanded disability status scale. A reduced thickness of GCIPL and inner nuclear layer were associated with MS diagnosis at presentation. <h3>Conclusions:</h3> This study provides support for a relationship between increased cortical damage and retinal layers thinning in CIS suggesting a common pathological process behind these alterations. The association between greater retinal damage and disability confirms the role of GCIPL as a possible biomarker of neurodegeneration even at this early stage of the disease. <b>Disclosure:</b> Dr. Varmpompiti has nothing to disclose. Dr. Chow has nothing to disclose. The institution of Dr. Foster has received research support from Medical Research Council. Dr. Kodali has nothing to disclose. Marios Yiannakas has nothing to disclose. Dr. Kanber has nothing to disclose. Ferran Padros, 8186 has nothing to disclose. Dr. Davagnanam has nothing to disclose. Prof. Ciccarelli has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Novartis. Prof. Ciccarelli has received personal compensation in the range of $0-$499 for serving on a Speakers Bureau for Merck. Prof. Ciccarelli has received personal compensation in the range of $10,000-$49,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for NEUROLOGY Journal. The institution of Ahmed Toosy has received research support from Rosetrees Trust. The institution of Sara Collorone has received research support from Rosetreest Trust. The institution of Sara Collorone has received research support from MAGNIMS/ECTRIMS.

Complement activation and increased anaphylatoxin receptor expression are associated with cortical grey matter lesions and the compartmentalised inflammatory response of multiple sclerosis.

The extent of cortical pathology is an important determinant of multiple sclerosis (MS) severity. Cortical demyelination and neurodegeneration are related to inflammation of the overlying leptomeninges, a more inflammatory CSF milieu and with parenchymal microglia and astroglia activation. These are all components of the compartmentalised inflammatory response. Compartmentalised inflammation is a feature of progressive MS, which is not targeted by disease modifying therapies. Complement is differentially expressed in the MS CSF and complement, and complement receptors, are associated with demyelination and neurodegeneration. To better understand if complement activation in the leptomeninges is associated with underlying cortical demyelination, inflammation, and microglial activation, we performed a neuropathological study of progressive MS (n = 22, 14 females), neuroinflammatory (n = 8), and non-neurological disease controls (n = 10). We then quantified the relative extent of demyelination, connective tissue inflammation, complement, and complement receptor positive microglia/macrophages. Complement was elevated at the leptomeninges, subpial, and within and around vessels of the cortical grey matter. The extent of complement C1q immunoreactivity correlated with connective tissue infiltrates, whilst activation products C4d, Bb, and C3b associated with grey matter demyelination, and C3a receptor 1+ and C5a receptor 1+ microglia/macrophages closely apposed C3b labelled cells. The density of C3a receptor 1+ and C5a receptor 1+ cells was increased at the expanding edge of subpial and leukocortical lesions. C5a receptor 1+ cells expressed TNFα, iNOS and contained puncta immunoreactive for proteolipid protein, neurofilament and synaptophysin, suggesting their involvement in grey matter lesion expansion. The presence of products of complement activation at the brain surfaces, their association with the extent of underlying pathology and increased complement anaphylatoxin receptor positive microglia/macrophages at expanding cortical grey matter lesions, could represent a target to modify compartmentalised inflammation and cortical demyelination.

An investigation of the association between focal damage and global network properties in cognitively impaired and cognitively preserved patients with multiple sclerosis.

The presence of focal cortical and white matter damage in patients with multiple sclerosis (pwMS) might lead to specific alterations in brain networks that are associated with cognitive impairment. We applied microstructure-weighted connectomes to investigate (i) the relationship between global network metrics and information processing speed in pwMS, and (ii) whether the disruption provoked by focal lesions on global network metrics is associated to patients' information processing speed. Sixty-eight pwMS and 92 healthy controls (HC) underwent neuropsychological examination and 3T brain MRI including multishell diffusion (dMRI), 3D FLAIR, and MP2RAGE. Whole-brain deterministic tractography and connectometry were performed on dMRI. Connectomes were obtained using the Spherical Mean Technique and were weighted for the intracellular fraction. We identified white matter lesions and cortical lesions on 3D FLAIR and MP2RAGE images, respectively. PwMS were subdivided into cognitively preserved (CPMS) and cognitively impaired (CIMS) using the Symbol Digit Modalities Test (SDMT) z-score at cut-off value of -1.5 standard deviations. Statistical analyses were performed using robust linear models with age, gender, and years of education as covariates, followed by correction for multiple testing. Out of 68 pwMS, 18 were CIMS and 50 were CPMS. We found significant changes in all global network metrics in pwMS vs HC (p < 0.05), except for modularity. All global network metrics were positively correlated with SDMT, except for modularity which showed an inverse correlation. Cortical, leukocortical, and periventricular lesion volumes significantly influenced the relationship between (i) network density and information processing speed and (ii) modularity and information processing speed in pwMS. Interestingly, this was not the case, when an exploratory analysis was performed in the subgroup of CIMS patients. Our study showed that cortical (especially leukocortical) and periventricular lesions affect the relationship between global network metrics and information processing speed in pwMS. Our data also suggest that in CIMS patients increased focal cortical and periventricular damage does not linearly affect the relationship between network properties and SDMT, suggesting that other mechanisms (e.g. disruption of local networks, loss of compensatory processes) might be responsible for the development of processing speed deficits.

Fluid and White Matter Suppression: New Sensitive 3 T Magnetic Resonance Imaging Contrasts for Cortical Lesion Detection in Multiple Sclerosis.

Cortical lesions are common in multiple sclerosis (MS), but their visualization is challenging on conventional magnetic resonance imaging. The uniform image derived from magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE uni ) detects cortical lesions with a similar rate as the criterion standard sequence, double inversion recovery. Fluid and white matter suppression (FLAWS) provides multiple reconstructed contrasts acquired during a single acquisition. These contrasts include FLAWS minimum image (FLAWS min ), which provides an exquisite sensitivity to the gray matter signal and therefore may facilitate cortical lesion identification, as well as high contrast FLAWS (FLAWS hco ), which gives a contrast that is similar to one of MP2RAGE uni . In this study, we compared the manual detection rate of cortical lesions on MP2RAGE uni , FLAWS min , and FLAWS hco in MS patients. Furthermore, we assessed whether the combined detection rate on FLAWS min and FLAWS hco was superior to MP2RAGE uni for cortical lesions identification. Last, we compared quantitative T1 maps (qT1) provided by both MP2RAGE and FLAWS in MS lesions. We included 30 relapsing-remitting MS patients who underwent MP2RAGE and FLAWS magnetic resonance imaging with isotropic spatial resolution of 1 mm at 3 T. Cortical lesions were manually segmented by consensus of 3 trained raters and classified as intracortical or leukocortical lesions on (1) MP2RAGE uniform/flat images, (2) FLAWS min , and (3) FLAWS hco . In addition, segmented lesions on FLAWS min and FLAWS hco were merged to produce a union lesion map (FLAWS min + hco ). Number and volume of all cortical, intracortical, and leukocortical lesions were compared among MP2RAGE uni , FLAWS min , and FLAWS hco using Friedman test and between MP2RAGE uni and FLAWS min + hco using Wilcoxon signed rank test. The FLAWS T1 maps were then compared with the reference MP2RAGE T1 maps using relative differences in percentage. In an exploratory analysis, individual cortical lesion counts of the 3 raters were compared, and interrater variability was quantified using Fleiss ϰ. In total, 633 segmentations were made on the 3 contrasts, corresponding to 355 cortical lesions. The median number and volume of single cortical, intracortical, and leukocortical lesions were comparable among MP2RAGE uni , FLAWS min , and FLAWS hco . In patients with cortical lesions (22/30), median cumulative lesion volume was larger on FLAWS min (587 μL; IQR, 1405 μL) than on MP2RAGE uni (490 μL; IQR, 990 μL; P = 0.04), whereas there was no difference between FLAWS min and FLAWS hco , or FLAWS hco and MP2RAGE uni . FLAWS min + hco showed significantly greater numbers of cortical (median, 4.5; IQR, 15) and leukocortical (median, 3.5; IQR, 12) lesions than MP2RAGE uni (median, 3; IQR, 10; median, 2.5; IQR, 7; both P < 0.001). Interrater agreement was moderate on MP2RAGE uni (ϰ = 0.582) and FLAWS hco (ϰ = 0.584), but substantial on FLAWS min (ϰ = 0.614). qT1 in lesions was similar between MP2RAGE and FLAWS. Cortical lesions identification in FLAWS min and FLAWS hco was comparable to MP2RAGE uni . The combination of FLAWS min and FLAWS hco allowed to identify a higher number of cortical lesions than MP2RAGE uni , whereas qT1 maps did not differ between the 2 acquisition schemes.

Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.

Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter‐rater reliability. To accelerate this task, we developed a deep‐learning‐based framework (CLAIMS: Cortical Lesion AI‐Based Assessment in Multiple Sclerosis) for the automated detection and classification of MS CLs with 7 T MRI. Two 7 T datasets, acquired at different sites, were considered. The first consisted of 60 scans that include 0.5 mm isotropic MP2RAGE acquired four times (MP2RAGE×4), 0.7 mm MP2RAGE, 0.5 mm T 2*‐weighted GRE, and 0.5 mm T 2*‐weighted EPI. The second dataset consisted of 20 scans including only 0.75 × 0.75 × 0.9 mm3 MP2RAGE. CLAIMS was first evaluated using sixfold cross‐validation with single and multi‐contrast 0.5 mm MRI input. Second, the performance of the model was tested on 0.7 mm MP2RAGE images after training with either 0.5 mm MP2RAGE×4, 0.7 mm MP2RAGE, or alternating the two. Third, its generalizability was evaluated on the second external dataset and compared with a state‐of‐the‐art technique based on partial volume estimation and topological constraints (MSLAST). CLAIMS trained only with MP2RAGE×4 achieved results comparable to those of the multi‐contrast model, reaching a CL true positive rate of 74% with a false positive rate of 30%. Detection rate was excellent for leukocortical and subpial lesions (83%, and 70%, respectively), whereas it reached 53% for intracortical lesions. The correlation between disability measures and CL count was similar for manual and CLAIMS lesion counts. Applying a domain‐scanner adaptation approach and testing CLAIMS on the second dataset, the performance was superior to MSLAST when considering a minimum lesion volume of 6 μL (lesion‐wise detection rate of 71% versus 48%). The proposed framework outperforms previous state‐of‐the‐art methods for automated CL detection across scanners and protocols. In the future, CLAIMS may be useful to support clinical decisions at 7 T MRI, especially in the field of diagnosis and differential diagnosis of MS patients.

Cortical and white matter lesion topology influences focal corpus callosum atrophy in multiple sclerosis.

Background and PurposeCorpus callosum (CC) atrophy is a strong predictor of multiple sclerosis (MS) disability but the contributing pathological mechanisms remain uncertain. We aimed to apply advanced MRI to explore what drives the often nonuniform callosal atrophy.MethodsProspective brain 7 Tesla and 3 Tesla Human Connectom Scanner MRI were performed in 92 MS patients. White matter, leukocortical, and intracortical lesions were manually segmented. FreeSurfer was used to segment the CC and topographically classify lesions per lobe or as deep white matter lesions. Regression models were calculated to predict focal CC atrophy.ResultsThe frontal and parietal lobes contained the majority (≥80%) of all lesion classifications in both relapsing‐remitting and secondary progressive MS subtypes. The anterior subsection of the CC had the smallest proportional volume difference between subtypes (11%). Deep, temporal, and occipital white matter lesions, and occipital intracortical lesions were the strongest predictors of middle‐posterior callosal atrophy (adjusted R 2 = .54‐.39, P < .01).ConclusionsBoth white matter and cortical lesions contribute to regional corpus callosal atrophy. The lobe‐specific lesion topology does not fully explain the inhomogeneous CC atrophy.

Cortical lesion hotspots and association of subpial lesions with disability in multiple sclerosis

Background: Dramatic improvements in visualization of cortical (especially subpial) multiple sclerosis (MS) lesions allow assessment of impact on clinical course. Objective: Characterize cortical lesions by 7 tesla (T) T2*-/T1-weighted magnetic resonance imaging (MRI); determine relationship with other MS pathology and contribution to disability. Methods: Sixty-four adults with MS (45 relapsing–remitting/19 progressive) underwent 3 T brain/spine MRI, 7 T brain MRI, and clinical testing. Results: Cortical lesions were found in 94% (progressive: median 56/range 2–203; relapsing–remitting: 15/0–168; p = 0.004). Lesion distribution across 50 cortical regions was nonuniform (p = 0.006), with highest lesion burden in supplementary motor cortex and highest prevalence in superior frontal gyrus. Leukocortical and white matter lesion volumes were strongly correlated (r = 0.58, p < 0.0001), while subpial and white matter lesion volumes were moderately correlated (r = 0.30, p = 0.002). Leukocortical (p = 0.02) but not subpial lesions (p = 0.40) were correlated with paramagnetic rim lesions; both were correlated with spinal cord lesions (p = 0.01). Cortical lesion volumes (total and subtypes) were correlated with expanded disability status scale, 25-foot timed walk, nine-hole peg test, and symbol digit modality test scores. Conclusion: Cortical lesions are highly prevalent and are associated with disability and progressive disease. Subpial lesion burden is not strongly correlated with white matter lesions, suggesting differences in inflammation and repair mechanisms.

Cortical involvement and leptomeningeal inflammation in myelin oligodendrocyte glycoprotein antibody disease: A three-dimensional fluid-attenuated inversion recovery MRI study

Background: Cortical demyelination and meningeal inflammation have been detected neuropathologically in multiple sclerosis (MS) and recently in myelin oligodendrocyte glycoprotein antibody disease (MOGAD). Objectives: To assess in vivo cortical and leptomeningeal involvement in MOGAD. Methods: We prospectively evaluated 11 MOGAD and 12 relapsing-remitting MS (RRMS) patients combining three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) and 3D-T1-weighted (3D-T1w) sequences at 3-Tesla magnetic resonance imaging (MRI). Leptomeningeal contrast enhancement (LMCE) was assessed on 3D-FLAIR post-gadolinium (3D-FLAIRGd). Cerebral cortical lesions (CCLs) were classified as either intracortical–subpial (IC–SP) or leukocortical (LC). Results: CCLs were present in 8/11 MOGAD and 12/12 RRMS patients, with the number of CCLs being significantly lower in MOGAD (median (interquartile range (IQR)) 3 (0.5–4) vs 12 (4.75–19), p = 0.0032). In MOGAD, IC–SP lesions were slightly more prevalent than LC lesions (2 (0–2.5) vs 1 (0–2), p = 0.6579); whereas in RRMS, IC–SP lesions were less prevalent than LC lesions (3.5 (2.75–5.5) vs 9 (2–12.75), p = 0.27). LMCE was observed in 3/11 MOGAD and 1/12 RRMS patients; MOGAD with LMCE showed an increased median number of CCLs compared with MOGAD without LMCE (8 (4–9) vs 2.5 (0.75–3.25), p = 0.34). No correlation was observed between MOGAD MRI findings and (a) MOGAD duration, (b) serum MOG-immunoglobulin G1 titers, and (c) oligoclonal band presence. Conclusion: We described cortical lesion topography and detected for the first time LMCE using 3D-FLAIRGd sequences in MOGAD patients.

Cortical and phase rim lesions on 7 T MRI as markers of multiple sclerosis disease progression.

In multiple sclerosis, individual lesion-type patterns on magnetic resonance imaging might be valuable for predicting clinical outcome and monitoring treatment effects. Neuropathological and imaging studies consistently show that cortical lesions contribute to disease progression. The presence of chronic active white matter lesions harbouring a paramagnetic rim on susceptibility-weighted magnetic resonance imaging has also been associated with an aggressive form of multiple sclerosis. It is, however, still uncertain how these two types of lesions relate to each other, or which one plays a greater role in disability progression. In this prospective, longitudinal study in 100 multiple sclerosis patients (74 relapsing-remitting, 26 secondary progressive), we used ultra-high field 7-T susceptibility imaging to characterize cortical and rim lesion presence and evolution. Clinical evaluations were obtained over a mean period of 3.2 years in 71 patients, 46 of which had a follow-up magnetic resonance imaging. At baseline, cortical and rim lesions were identified in 96% and 63% of patients, respectively. Rim lesion prevalence was similar across disease stages. Patients with rim lesions had higher cortical and overall white matter lesion load than subjects without rim lesions (P = 0.018-0.05). Altogether, cortical lesions increased by both count and volume (P = 0.004) over time, while rim lesions expanded their volume (P = 0.023) whilst lacking new rim lesions; rimless white matter lesions increased their count but decreased their volume (P = 0.016). We used a modern machine learning algorithm based on extreme gradient boosting techniques to assess the cumulative power as well as the individual importance of cortical and rim lesion types in predicting disease stage and disability progression, alongside with more traditional imaging markers. The most influential imaging features that discriminated between multiple sclerosis stages (area under the curve±standard deviation = 0.82 ± 0.08) included, as expected, the normalized white matter and thalamic volume, white matter lesion volume, but also leukocortical lesion volume. Subarachnoid cerebrospinal fluid and leukocortical lesion volumes, along with rim lesion volume were the most important predictors of Expanded Disability Status Scale progression (area under the curve±standard deviation = 0.69 ± 0.12). Taken together, these results indicate that while cortical lesions are extremely frequent in multiple sclerosis, rim lesion development occurs only in a subset of patients. Both, however, persist over time and relate to disease progression. Their combined assessment is needed to improve the ability of identifying multiple sclerosis patients at risk of progressing disease.

Inversion Recovery Susceptibility Weighted Imaging With Enhanced T2 Weighting at 3 T Improves Visualization of Subpial Cortical Multiple Sclerosis Lesions.

Cortical demyelination is common in multiple sclerosis (MS) and can be extensive. Cortical lesions contribute to disability independently from white matter lesions and may form via a distinct mechanism. However, current magnetic resonance imaging methods at 3 T are insensitive to cortical, and especially subpial cortical, lesions. Subpial lesions are well seen on T2*-weighted imaging at 7 T, but T2*-weighted methods on 3 T scanners are limited by poor lesion-to-cortex and cerebrospinal fluid-to-lesion contrast. We aimed to develop and evaluate a cerebrospinal fluid-suppressed, T2*-weighted sequence optimized for subpial cortical lesion visualization. We developed a new magnetic resonance imaging sequence, inversion recovery susceptibility weighted imaging with enhanced T2 weighting (IR-SWIET; 0.8 mm × 0.8 mm in plane, 0.64 mm slice thickness with whole brain coverage, acquisition time ~5 minutes). We compared cortical lesion visualization independently on IR-SWIET (median signal from 4 acquisitions), magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE), double inversion recovery (DIR), T2*-weighted segmented echo-planar imaging, and phase-sensitive inversion recovery images for 10 adults with MS. We also identified cortical lesions with a multicontrast reading of IR-SWIET (median of 2 acquisitions), MP2RAGE, and fluid-attenuated inversion recovery (FLAIR) images for each case. Lesions identified on 3 T images were verified on "gold standard" 7 T T2* and MP2RAGE images. Cortical, and particularly subpial, lesions appeared much more conspicuous on IR-SWIET compared with other 3 T methods. A total of 101 true-positive subpial lesions were identified on IR-SWIET (average per-participant sensitivity vs 7 T, 29% ± 8%) versus 36 on MP2RAGE (5% ± 2%; comparison to IR-SWIET sensitivity, P = 0.07), 17 on FLAIR (2% ± 1%; P < 0.05), 28 on DIR (6% ± 2%; P < 0.05), 42 on T2*-weighted segmented echo-planar imaging (11% ± 5%; P < 0.05), and 13 on phase-sensitive inversion recovery (4% ± 2%; P < 0.05). When a combination of IR-SWIET, MP2RAGE, and FLAIR images was used, a total of 147 subpial lesions (30% ± 5%) were identified versus 83 (16% ± 3%, P < 0.01) on a combination of DIR, MP2RAGE, and FLAIR. More cases had at least 1 subpial lesion on IR-SWIET, and IR-SWIET improved cortical lesion subtyping accuracy and correlation with 7 T subpial lesion number. Subpial lesions are better visualized on IR-SWIET compared with other 3 T methods. A 3 T protocol combining IR-SWIET with MP2RAGE, in which leukocortical lesions are well seen, improves cortical lesion visualization over existing approaches. Therefore, IR-SWIET may enable improved MS diagnostic specificity and a better understanding of the clinical implications of cortical demyelination.

Contribution of cortical lesions to cognitive impairment in Japanese patients with multiple sclerosis

Cortical lesions (CLs) have a low prevalence and are associated with physical disabilities in Japanese patients with multiple sclerosis (MS). However, the contribution of CLs to cognitive impairment remains unclear in Asian MS. Sixty-one prospectively enrolled MS patients underwent three-dimensional double inversion recovery MR imaging, the Brief Repeatable Battery of Neuropsychological Tests (BRB-N), the Apathy Scale (AS), the Fatigue Questionnaire (FQ), and the Hospital Anxiety and Depression Scale (HADS) within a 1-week period. The cognitive impairment index (CII) score was calculated to measure patients’ overall cognitive impairment. MS patients with CLs had poorer scores than those without CLs in most BRB-N tests, but scored comparably in the FQ, AS, and HADS. The number of CLs correlated negatively with all BRB-N test scores and positively with total CII scores. Leukocortical lesions were more extensively associated with cognitive dysfunction in various domains than intracortical lesions. Stepwise multiple regression analysis revealed that potential confounding factors for the highest quartile of CII score were the number of CLs (odds ratio 2.38, p = 0.0070) and the Expanded Disability Severity Scale score (odds ratio 2.13, p = 0.0003). Our results demonstrate that the presence and number of CLs are robustly associated with cognitive dysfunction in Asian MS patients.

Comparison of Multiple Sclerosis Cortical Lesion Types Detected by Multicontrast 3T and 7T MRI

Our aims were the following: 1) to compare multicontrast cortical lesion detection using 3T and 7T MR imaging, 2) to compare cortical lesion type frequency in relapsing-remitting and secondary-progressive MS, and 3) to assess whether detectability is related to the magnetization transfer ratio, an imaging marker sensitive to myelin content. Multicontrast 3T and 7T MR images from 10 participants with relapsing-remitting MS and 10 with secondary-progressive MS. We used the following 3T contrast sequences: 3D-T1-weighted, quantitative T1, FLAIR, magnetization-transfer, and 2D proton-density- and T2-weighted. We used the following 7T contrast sequences: 3D-T1-weighted, quantitative T1, and 2D-T2*-weighted. Cortical lesion counts at 7T were the following: 720 total cortical lesions, 420 leukocortical lesions (58%), 27 intracortical lesions (4%), and 273 subpial lesions (38%). Cortical lesion counts at 3T were the following: 424 total cortical, 393 leukocortical (93%), zero intracortical, and 31 subpial (7%) lesions. Total, intracortical, and subpial 3T lesion counts were significantly lower than the 7T counts (P < .002). Leukocortical lesion counts were not significantly different between scanners. Total and leukocortical lesion counts were significantly higher in secondary-progressive MS, at 3T and 7T (P ≤ .02). Subpial lesions were significantly higher in secondary-progressive MS at 7T (P = .006). The magnetization transfer ratio values of leukocortical lesions visible on both scanners were significantly lower than the magnetization transfer ratio values of leukocortical lesions visible only at 3T. No significant difference was found in magnetization transfer ratio values between subpial lesions visible only at 7T and subpial lesions visible on both 3T and 7T. Detection of leukocortical lesions at 3T is comparable with that at 7T MR imaging. Imaging at 3T is less sensitive to intracortical and subpial lesions. Leukocortical lesions not visible on 7T T2*-weighted MRI may be associated with less demyelination than those that are visible. Detectability of subpial lesions does not appear to be related to the degree of demyelination.

Editors' note: Journal Club: MRI reveals acute inflammation in cortical lesions during early MS

In “Journal Club: MRI reveals acute inflammation in cortical lesions during early MS,” Bateman et al. discussed an article that showed evidence of early leukocortical lesions in multiple sclerosis (MS), suggesting that gray matter pathology may be related to blood–brain barrier breakdown. Commenting on the journal club article, Drs. Cyprian Olchowy and Anna Olchowy point to the fact that patients in the study discussed received triple the recommended dose of gadolinium-based contrast agent (GBCA). They explain that the study started before the link between gadolinium administrations and increased signal intensity in the dentate nucleus and globus pallidus was discovered in the human brain. They add that currently, a study with monthly injections of triple-dose GBCA would not be possible due to justified safety concerns. In “Journal Club: MRI reveals acute inflammation in cortical lesions during early MS,” Bateman et al. discussed an article that showed evidence of early leukocortical lesions in multiple sclerosis (MS), suggesting that gray matter pathology may be related to blood–brain barrier breakdown. Commenting on the journal club article, Drs. Cyprian Olchowy and Anna Olchowy point to the fact that patients in the study discussed received triple the recommended dose of gadolinium-based contrast agent (GBCA).

Detection and clinical correlation of leukocortical lesions in pediatric-onset multiple sclerosis on multi-contrast MRI

Objective: To determine the frequency of cortical lesions (CLs) in patients with pediatric-onset multiple sclerosis (POMS) using multi-contrast magnetic resonance imaging (MRI), and the relationship between frontal CL load and upper limb dexterity assessed with the Nine-Hole Peg Test (9-HPT). Methods: Participants completed the 9-HPT and were imaged on a 3T MRI scanner to collect T1-weighted three-dimensional (3D) magnetization prepared rapid gradient echo (MPRAGE), proton density–weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR) images. CLs were manually segmented using all MRI contrasts. Results: We enrolled 24 participants with POMS (mean (standard deviation) age at first symptom: 13.3 (±2.7) years; mean age at scan: 18.8 (±3) years; mean disease duration of 5 (±3.2) years). A total of 391 CLs (mean, 16.3 ± 27.2; median, 7) were identified in 19 of 24 POMS patients (79%). The total number of CLs was positively associated with white matter lesion volume (p = 0.04) but not with thalamic volume, age at the time of the scan, or disease duration. The number of frontal CLs was associated with slower performance on the 9-HPT (p = 0.05). Conclusion: Multi-contrast 3T MRI led to a high rate of CL detection, demonstrating that cortical pathology occurs even in pediatric-onset disease. Frontal lobe CL count was associated with reduced manual dexterity, indicating that these CLs are clinically relevant.

Journal Club: MRI reveals acute inflammation in cortical lesions during early MS.

Early multiple sclerosis is characterized by immune-associated demyelination of CNS axons. In a recent Neurology® article, Maranzano et al. evaluated MRI scans of patients with early multiple sclerosis to study the evolution of leukocortical lesions. Their novel data suggest that acute inflammation after blood-brain barrier leakage may contribute to gray matter cortical lesions in early multiple sclerosis.