Imaging chronic active lesions in multiple sclerosis: a consensus statement.

Chronic active lesions (CAL) are an important manifestation of chronic inflammation in multiple sclerosis (MS) and have implications for non-relapsing biological progression. In recent years, the discovery of innovative magnetic resonance imaging (MRI) and PET derived biomarkers has made it possible to detect CAL, and to some extent quantify them, in the brain of persons with MS, in vivo. Paramagnetic rim lesions on susceptibility-sensitive MRI sequences, MRI-defined slowly expanding lesions on T1-weighted (T1-w) and T2-w scans, and 18-kDa translocator protein-positive lesions on PET are promising candidate biomarkers of CAL. While partially overlapping, these biomarkers do not have equivalent sensitivity and specificity to histopathological CAL. Standardization in the use of available imaging measures for CAL identification, quantification, and monitoring is lacking. To fast-forward clinical translation of CAL, the North American Imaging in Multiple Sclerosis Cooperative developed a Consensus Statement, which provides guidance for the radiological definition and measurement of CAL. The proposed manuscript presents this Consensus Statement, summarizes the multistep process leading to it, and identifies the remaining major gaps in knowledge.

Maximum spherical mean value filtering for whole-brain QSM.

PURPOSE: To develop a tissue field-filtering algorithm, called maximum spherical mean value (mSMV), for reducing shadow artifacts in QSM of the brain without requiring brain-tissue erosion. THEORY AND METHODS: Residual background field is a major source of shadow artifacts in QSM. The mSMV algorithm filters large field-magnitude values near the border, where the maximum value of the harmonic background field is located. The effectiveness of mSMV for artifact removal was evaluated by comparing existing QSM algorithms in numerical brain simulation as well as using in vivo human data acquired from 11 healthy volunteers and 93 patients. RESULTS: Numerical simulation showed that mSMV reduces shadow artifacts and improves QSM accuracy. Better shadow reduction, as demonstrated by lower QSM variation in the gray matter and higher QSM image quality score, was also observed in healthy subjects and in patients with hemorrhages, stroke, and multiple sclerosis. CONCLUSION: The mSMV algorithm allows QSM maps that are substantially equivalent to those obtained using SMV-filtered dipole inversion without eroding the volume of interest.

Subsecond accurate myelin water fraction reconstruction from FAST-T2 data with 3D UNET.

PURPOSE: To develop a 3D UNET convolutional neural network for rapid extraction of myelin water fraction (MWF) maps from six-echo fast acquisition with spiral trajectory and T2 -prep data and to evaluate its accuracy in comparison with multilayer perceptron (MLP) network. METHODS: The MWF maps were extracted from 138 patients with multiple sclerosis using an iterative three-pool nonlinear least-squares algorithm (NLLS) without and with spatial regularization (srNLLS), which were used as ground-truth labels to train, validate, and test UNET and MLP networks as a means to accelerate data fitting. Network testing was performed in 63 patients with multiple sclerosis and a numerically simulated brain phantom at SNR of 200, 100 and 50. RESULTS: Simulations showed that UNET reduced the MWF mean absolute error by 30.1% to 56.4% and 16.8% to 53.6% over the whole brain and by 41.2% to 54.4% and 21.4% to 49.4% over the lesions for predicting srNLLS and NLLS MWF, respectively, compared to MLP, with better performance at lower SNRs. UNET also outperformed MLP for predicting srNLLS MWF in the in vivo multiple-sclerosis brain data, reducing mean absolute error over the whole brain by 61.9% and over the lesions by 67.5%. However, MLP yielded 41.1% and 51.7% lower mean absolute error for predicting in vivo NLLS MWF over the whole brain and the lesions, respectively, compared with UNET. The whole-brain MWF processing time using a GPU was 0.64 seconds for UNET and 0.74 seconds for MLP. CONCLUSION: Subsecond whole-brain MWF extraction from fast acquisition with spiral trajectory and T2 -prep data using UNET is feasible and provides better accuracy than MLP for predicting MWF output of srNLLS algorithm.

Lesion features on magnetic resonance imaging discriminate multiple sclerosis patients.

BACKGROUND: Magnetic resonance imaging (MRI) provides insight into various pathological processes in multiple sclerosis (MS) and may provide insight into patterns of damage among patients. OBJECTIVE: We sought to determine if MRI features have clinical discriminative power among a cohort of MS patients. METHODS: Ninety-six relapsing remitting and seven progressive MS patients underwent myelin water fraction (MWF) imaging and conventional MRI for cortical thickness and thalamic volume. Patients were clustered based on lesion level MRI features using an agglomerative hierarchical clustering algorithm based on principal component analysis (PCA). RESULTS: One hundred and three patients with 1689 MS lesions were analyzed. PCA on MRI features demonstrated that lesion MWF and volume distributions (characterized by 25th, 50th, and 75th percentiles) accounted for 87% of the total variability based on four principal components. The best hierarchical cluster confirmed two distinct patient clusters. The clustering features in order of importance were lesion median MWF, MWF 25th, MWF 75th, volume 75th percentiles, median individual lesion volume, total lesion volume, cortical thickness, and thalamic volume (all p values <0.01368). The clusters were associated with patient Expanded Disability Status Scale (EDSS) (n = 103, p = 0.0338) at baseline and at 5 years (n = 72, p = 0.0337). CONCLUSIONS: These results demonstrate that individual MRI features can identify two patient clusters driven by lesion-based values, and our unique approach is an analysis blinded to clinical variables. The two distinct clusters exhibit MWF differences, most likely representing individual remyelination capabilities among different patient groups. These findings support the concept of patient-specific pathophysiological processes and may guide future therapeutic approaches.

Deep grey matter injury in multiple sclerosis: a NAIMS consensus statement.

Although multiple sclerosis has traditionally been considered a white matter disease, extensive research documents the presence and importance of grey matter injury including cortical and deep regions. The deep grey matter exhibits a broad range of pathology and is uniquely suited to study the mechanisms and clinical relevance of tissue injury in multiple sclerosis using magnetic resonance techniques. Deep grey matter injury has been associated with clinical and cognitive disability. Recently, MRI characterization of deep grey matter properties, such as thalamic volume, have been tested as potential clinical trial end points associated with neurodegenerative aspects of multiple sclerosis. Given this emerging area of interest and its potential clinical trial relevance, the North American Imaging in Multiple Sclerosis (NAIMS) Cooperative held a workshop and reached consensus on imaging topics related to deep grey matter. Herein, we review current knowledge regarding deep grey matter injury in multiple sclerosis from an imaging perspective, including insights from histopathology, image acquisition and post-processing for deep grey matter. We discuss the clinical relevance of deep grey matter injury and specific regions of interest within the deep grey matter. We highlight unanswered questions and propose future directions, with the aim of focusing research priorities towards better methods, analysis, and interpretation of results.

Estimation of Multiple Sclerosis lesion age on magnetic resonance imaging.

We introduce the first-ever statistical framework for estimating the age of Multiple Sclerosis (MS) lesions from magnetic resonance imaging (MRI). Estimating lesion age is an important step when studying the longitudinal behavior of MS lesions and can be used in applications such as studying the temporal dynamics of chronic active MS lesions. Our lesion age estimation models use first order radiomic features over a lesion derived from conventional T1 (T1w) and T2 weighted (T2w) and fluid attenuated inversion recovery (FLAIR), T1w with gadolinium contrast (T1w+c), and Quantitative Susceptibility Mapping (QSM) MRI sequences as well as demographic information. For this analysis, we have a total of 32 patients with 53 new lesions observed at 244 time points. A one or two step random forest model for lesion age is fit on a training set using a lesion volume cutoff of 15 mm3 or 50 mm3. We explore the performance of nine different modeling scenarios that included various combinations of the MRI sequences and demographic information and a one or two step random forest models, as well as simpler models that only uses the mean radiomic feature from each MRI sequence. The best performing model on a validation set is a model that uses a two-step random forest model on the radiomic features from all of the MRI sequences with demographic information using a lesion volume cutoff of 50 mm3. This model has a mean absolute error of 7.23 months (95% CI: [6.98, 13.43]) and a median absolute error of 5.98 months (95% CI: [5.26, 13.25]) in the validation set. For this model, the predicted age and actual age have a statistically significant association (p-value <0.001) in the validation set.

Quantitative susceptibility mapping identifies inflammation in a subset of chronic multiple sclerosis lesions.

Chronic active multiple sclerosis lesions, characterized by a hyperintense rim of iron-enriched, activated microglia and macrophages, have been linked to greater tissue damage. Post-mortem studies have determined that chronic active lesions are primarily related to the later stages of multiple sclerosis; however, the occurrence of these lesions, and their relationship to earlier disease stages may be greatly underestimated. Detection of chronic active lesions across the patient spectrum of multiple sclerosis requires a validated imaging tool to accurately identify lesions with persistent inflammation. Quantitative susceptibility mapping provides efficient in vivo quantification of susceptibility changes related to iron deposition and the potential to identify lesions harbouring iron-laden inflammatory cells. The PET tracer 11C-PK11195 targets the translocator protein expressed by activated microglia and infiltrating macrophages. Accordingly, this study aimed to validate that lesions with a hyperintense rim on quantitative susceptibility mapping from both relapsing and progressive patients demonstrate a higher level of innate immune activation as measured on 11C-PK11195 PET. Thirty patients were enrolled in this study, 24 patients had relapsing remitting multiple sclerosis, six had progressive multiple sclerosis, and all patients had concomitant MRI with a gradient echo sequence and PET with 11C-PK11195. A total of 406 chronic lesions were detected, and 43 chronic lesions with a hyperintense rim on quantitative susceptibility mapping were identified as rim+ lesions. Susceptibility (relative to CSF) was higher in rim+ (2.42 ± 17.45 ppb) compared to rim- lesions (-14.6 ± 19.3 ppb, P < 0.0001). Among rim+ lesions, susceptibility within the rim (20.04 ± 14.28 ppb) was significantly higher compared to the core (-5.49 ± 14.44 ppb, P < 0.0001), consistent with the presence of iron. In a mixed-effects model, 11C-PK11195 uptake, representing activated microglia/macrophages, was higher in rim+ lesions compared to rim- lesions (P = 0.015). Validating our in vivo imaging results, multiple sclerosis brain slabs were imaged with quantitative susceptibility mapping and processed for immunohistochemistry. These results showed a positive translocator protein signal throughout the expansive hyperintense border of rim+ lesions, which co-localized with iron containing CD68+ microglia and macrophages. In conclusion, this study provides evidence that suggests that a hyperintense rim on quantitative susceptibility measure within a chronic lesion is a correlate for persistent inflammatory activity and that these lesions can be identified in the relapsing patients. Utilizing quantitative susceptibility measure to differentiate chronic multiple sclerosis lesion subtypes, especially chronic active lesions, would provide a method to assess the impact of these lesions on disease progression.

Magnetic susceptibility increases as diamagnetic molecules breakdown: Myelin digestion during multiple sclerosis lesion formation contributes to increase on QSM.

BACKGROUND: The pathological processes in the first weeks of multiple sclerosis (MS) lesion formation include myelin digestion that breaks chemical bonds in myelin lipid layers. This can increase lesion magnetic susceptibility, which is a potentially useful biomarker in MS patient management, but not yet investigated. PURPOSE: To understand and quantify the effects of myelin digestion on quantitative susceptibility mapping (QSM) of MS lesions. STUDY TYPE: Histological and QSM analyses on in vitro models of myelin breakdown and MS lesion formation in vivo. POPULATION/SPECIMENS: Acutely demyelinating white matter lesions from MS autopsy tissue were stained with the lipid dye oil red O. Myelin basic protein (MBP), a major membrane protein of myelin, was digested with trypsin. Purified human myelin was denatured with sodium dodecyl sulfate (SDS). QSM was performed on phantoms containing digestion products and untreated controls. In vivo QSM was performed on five MS patients with newly enhancing lesions, and then repeated within 2 weeks. FIELD STRENGTH/SEQUENCE: 3D T 2 * -weighted spoiled multiecho gradient echo scans performed at 3T. ASSESSMENT: Region of interest analyses were performed by a biochemist and a neuroradiologist to determine susceptibility changes on in vitro and in vivo QSM images. STATISTICAL TESTS: Not applicable. RESULTS: MBP degradation by trypsin increased the QSM measurement by an average of 112 ± 37 ppb, in excellent agreement with a theoretical estimate of 111 ppb. Degradation of human myelin by SDS increased the QSM measurement by 23 ppb. As MS lesions changed from gadolinium enhancing to nonenhancing over an average of 15.8 ± 3.7 days, their susceptibility increased by an average of 7.5 ± 6.3 ppb. DATA CONCLUSION: Myelin digestion in the early stages of MS lesion formation contributes to an increase in tissue susceptibility, detectable by QSM, as a lesion evolves from gadolinium enhancing to nonenhancing. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1281-1287.

Clinical quantitative susceptibility mapping (QSM): Biometal imaging and its emerging roles in patient care.

Quantitative susceptibility mapping (QSM) has enabled magnetic resonance imaging (MRI) of tissue magnetic susceptibility to advance from simple qualitative detection of hypointense blooming artifacts to precise quantitative measurement of spatial biodistributions. QSM technology may be regarded to be sufficiently developed and validated to warrant wide dissemination for clinical applications of imaging isotropic susceptibility, which is dominated by metals in tissue, including iron and calcium. These biometals are highly regulated as vital participants in normal cellular biochemistry, and their dysregulations are manifested in a variety of pathologic processes. Therefore, QSM can be used to assess important tissue functions and disease. To facilitate QSM clinical translation, this review aims to organize pertinent information for implementing a robust automated QSM technique in routine MRI practice and to summarize available knowledge on diseases for which QSM can be used to improve patient care. In brief, QSM can be generated with postprocessing whenever gradient echo MRI is performed. QSM can be useful for diseases that involve neurodegeneration, inflammation, hemorrhage, abnormal oxygen consumption, substantial alterations in highly paramagnetic cellular iron, bone mineralization, or pathologic calcification; and for all disorders in which MRI diagnosis or surveillance requires contrast agent injection. Clinicians may consider integrating QSM into their routine imaging practices by including gradient echo sequences in all relevant MRI protocols. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2017;46:951-971.

No evidence of disease activity in patients receiving daclizumab versus intramuscular interferon beta-1a for relapsing-remitting multiple sclerosis in the DECIDE study.

BACKGROUND: No evidence of disease activity (NEDA) is a composite endpoint being increasingly applied as an outcome measure in clinical trials as well as proposed for individual therapeutic decisions in multiple sclerosis (MS). OBJECTIVE: Assess the proportion of patients with relapsing-remitting MS achieving NEDA in the DECIDE study of daclizumab 150 mg subcutaneous versus intramuscular interferon beta-1a 30 µg for 96-144 weeks. METHODS: NEDA was defined as no relapses, no onset of 12-week confirmed disability progression (CDP), no new/newly enlarging T2 hyperintense lesions (NET2), and no gadolinium-enhancing (Gd+) lesions. Logistic regression models adjusted for baseline covariates compared treatment groups for baseline to week 96, weeks 0-24, and weeks 24-96. RESULTS: From baseline to week 96, more daclizumab versus intramuscular interferon beta-1a patients achieved NEDA (24.6% vs 14.2%; odds ratio (OR; 95% confidence interval): 2.059 (1.592-2.661); p < 0.0001). ORs for clinical NEDA (no relapses, no CDP) and magnetic resonance imaging (MRI) NEDA (no NET2, no Gd+ lesions) were 1.651 (1.357-2.007; p < 0.0001) and 2.051 (1.628-2.582; p < 0.0001), respectively. ORs in favor of daclizumab for weeks 24-96 were consistently higher than for weeks 0-24. CONCLUSION: More daclizumab versus intramuscular interferon beta-1a patients achieved NEDA early in DECIDE, with effects increasing over time.

Quantifying the Susceptibility Variation of Normal-Appearing White Matter in Multiple Sclerosis by Quantitative Susceptibility Mapping.

OBJECTIVE: The purpose of this study is to evaluate the magnetic susceptibility of normal-appearing white matter (NAWM) in patients with multiple sclerosis (MS) using quantitative susceptibility mapping. MATERIALS AND METHODS: Ninety-four patients with relapse-remitting MS (RRMS) (37 with gadolinium-enhancing lesions and 57 with only gadolinium-nonenhancing lesions) and 55 healthy control subjects were included in this retrospective study. The susceptibility values of NAWM relative to CSF in patients with MS were compared with those of white matter (WM) in healthy control subjects and were correlated with the patient status of gadolinium-enhancing lesions, disease duration, and expanded disability status scale scores. RESULTS: All 37 patients with RRMS and gadolinium-enhancing lesions also had gadolinium-nonenhancing lesions. Susceptibility values of NAWM in patients with MS and only gadolinium-nonenhancing lesions (-18.29 ± 8.03 parts per billion [ppb]) were higher than those for WM in healthy control subjects (-25.81 ± 6.02 ppb; p < 0.001) and NAWM in patients with gadolinium-enhancing lesions (-25.64 ± 6.55 ppb; p < 0.001). Susceptibility values of NAWM in patients with MS with gadolinium-enhancing lesions were similar to those for WM in healthy control subjects (p = 0.91). This trend was dependent on neither NAWM region nor disease duration when the data were controlled for age. NAWM susceptibility was not correlated with either disease duration or expanded disability status scale (p > 0.05). CONCLUSION: In patients with RRMS and gadolinium-nonenhancing lesions, the susceptibility values of NAWM decrease when gadolinium-enhancing lesions appear, approaching values similar to those of WM in healthy control subjects, suggesting that NAWM may contribute to the iron accumulation observed in early active MS lesions.

Profilometry: A new statistical framework for the characterization of white matter pathways, with application to multiple sclerosis.

AIMS: describe a new "profilometry" framework for the multimetric analysis of white matter tracts, and demonstrate its application to multiple sclerosis (MS) with radial diffusivity (RD) and myelin water fraction (MWF). METHODS: A cohort of 15 normal controls (NC) and 141 MS patients were imaged with T1, T2 FLAIR, T2 relaxometry and diffusion MRI (dMRI) sequences. T1 and T2 FLAIR allowed for the identification of patients having lesion(s) on the tracts studied, with a special focus on the forceps minor. T2 relaxometry provided MWF maps, while dMRI data yielded RD maps and the tractography required to compute MWF and RD tract profiles. The statistical framework combined a multivariate analysis of covariance (MANCOVA) and a linear discriminant analysis (LDA) both accounting for age and gender, with multiple comparison corrections. RESULTS: In the single-case case study the profilometry visualization showed a clear departure of MWF and RD from the NC normative data at the lesion location(s). Group comparison from MANCOVA demonstrated significant differences at lesion locations, and a significant age effect in several tracts. The follow-up LDA analysis suggested MWF better discriminates groups than RD. DISCUSSION AND CONCLUSION: While progress has been made in both tract-profiling and metrics for white matter characterization, no single framework for a joint analysis of multimodality tract profiles accounting for age and gender is known to exist. The profilometry analysis and visualization appears to be a promising method to compare groups using a single score from MANCOVA while assessing the contribution of each metric with LDA.

Feasibility and reproducibility of whole brain myelin water mapping in 4 minutes using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) at 3T.

PURPOSE: To develop and measure the reproducibility of 4-min whole brain myelin water fraction (MWF) mapping using fast acquisition with spiral trajectory and T2prep (FAST-T2) sequence at 3T. METHODS: Experiments were performed on phantoms, 13 volunteers, and 16 patients with multiple sclerosis. MWF maps were extracted using a spatially constrained non-linear algorithm. The proposed adiabatic modified BIR-4 (mBIR-4) T2prep was compared with the conventional composite T2prep (COMP). The effect of reducing the number of echo times (TEs) from 15 to 6 (reducing scan time from 10 to 4 min) was evaluated. Reproducibility was assessed using correlation analysis, coefficient of variation (COV), and Bland-Altman plots. RESULTS: Compared with COMP, mBIR-4 provided more accurate T2 in phantoms and better MWF maps in human brains. Reducing the number of TEs had a negligible effect on MWF map quality, with a regional MWF difference of <0.8%. Regional MWFs obtained by repeated scans showed excellent correlation (R = 0.99), low COV (1.3%-2.4%), and negligible bias within ±1% limits of agreement. On a voxel-wise basis, the agreement remained strong (correlation R = 0.89 ± 0.03, bias = 0.01% ± 0.29%, limits of agreement = [-3.35% ± 0.73%, 3.33% ± 0.61%]). CONCLUSION: Whole brain MWF mapping with adiabatic FAST-T2 is feasible in 4 min and provides good intrasite reproducibility. Magn Reson Med 76:456-465, 2016. © 2015 Wiley Periodicals, Inc.

Longitudinal change in magnetic susceptibility of new enhanced multiple sclerosis (MS) lesions measured on serial quantitative susceptibility mapping (QSM).

PURPOSE: To measure the longitudinal change in multiple sclerosis (MS) lesion susceptibility using quantitative susceptibility mapping (QSM). MATERIALS AND METHODS: The study was approved by our Institutional Review Board. Longitudinal changes in quantitative susceptibility values of new enhanced-with-Gd MS lesions were measured at baseline magnetic resonance imaging (MRI) and on a follow-up MRI in 29 patients within 2 years using a 3D multiple echo gradient echo sequence on a 3T scanner. Paired t-test and the generalized estimating equations (GEE) model was used to analyze the longitudinal change. RESULTS: Lesion susceptibility values relative to normal-appearing white matter (NAWM) changed from 3.61 ± 6.11 ppb when enhanced-with-Gd at the baseline MRI to 20.42 ± 10.23 ppb when not-enhanced-with-Gd at the follow-up MRI (P < 0.001). CONCLUSION: MS lesion susceptibility value increases significantly as the lesion evolves from enhanced-with-Gd to not-enhanced-with-Gd, serving as a disease biomarker. J. Magn. Reson. Imaging 2016;44:426-432.

Multiple sclerosis lesion geometry in quantitative susceptibility mapping (QSM) and phase imaging.

PURPOSE: To demonstrate the phase and quantitative susceptibility mapping (QSM) patterns created by solid and shell spatial distributions of magnetic susceptibility in multiple sclerosis (MS) lesions. MATERIALS AND METHODS: Numerical simulations and experimental phantoms of solid- and shell-shaped magnetic susceptibility sources were used to generate magnitude, phase, and QSM images. Imaging of 20 consecutive MS patients was also reviewed for this Institutional Review Board (IRB)-approved MRI study to identify the appearance of solid and shell lesions on phase and QSM images. RESULTS: Solid and shell susceptibility sources were correctly reconstructed in QSM images, while the corresponding phase images depicted both geometries with shell-like patterns, making the underlying susceptibility distribution difficult to determine using phase alone. In MS patients, of the 60 largest lesions identified on T2 , 30 lesions were detected on both QSM and phase, of which 83% were solid and 17% were shells on QSM, and of which 30% were solid and 70% were shell on phase. Of the 21 shell-like lesions on phase, 76% appeared solid on QSM, 24% appeared shell on QSM. Of the five shell-like lesions on QSM, all were shell-like on phase. CONCLUSION: QSM accurately depicts both solid and shell patterns of magnetic susceptibility, while phase imaging fails to distinguish them.

Quantitative susceptibility mapping of multiple sclerosis lesions at various ages.

PURPOSE: To assess multiple sclerosis (MS) lesions at various ages by using quantitative susceptibility mapping (QSM) and conventional magnetic resonance (MR) imaging. MATERIALS AND METHODS: Retrospectively selected were 32 clinically confirmed MS patients (nine men and 23 women; 39.3 years ± 10.9) who underwent two MR examinations (interval, 0.43 years ± 0.16) with three-dimensional gradient-echo sequence from August 2011 to August 2012. To estimate the ages of MS lesions, MR examinations performed 0.3-10.6 years before study examinations were studied. Hyperintensity on T2-weighted images was used to define MS lesions. QSM images were reconstructed from gradient-echo data. Susceptibility of MS lesions and temporal rates of change were obtained from QSM images. Lesion susceptibilities were analyzed by t test with intracluster correlation adjustment and Bonferroni correction in multiple comparisons. RESULTS: MR imaging of 32 patients depicted 598 MS lesions, of which 162 lesions (27.1%) in 23 patients were age measurable and six (1.0%) were only visible at QSM. The susceptibilities relative to normal-appearing white matter (NAWM) were 0.53 ppb ± 3.34 for acute enhanced lesions, 38.43 ppb ± 13.0 (positive; P < .01) for early to intermediately aged nonenhanced lesions, and 4.67 ppb ± 3.18 for chronic nonenhanced lesions. Temporal rates of susceptibility changes relative to cerebrospinal fluid were 12.49 ppb/month ± 3.15 for acute enhanced lesions, 1.27 ppb/month ± 2.31 for early to intermediately aged nonenhanced lesions, and -0.004 ppb/month ± 0 for chronic nonenhanced lesions. CONCLUSION: Magnetic susceptibility of MS lesions increased rapidly as it changed from enhanced to nonenhanced, it attained a high susceptibility value relative to NAWM during its initial few years (approximately 4 years), and it gradually dissipated back to susceptibility similar to that of NAWM as it aged, which may provide new insight into pathophysiologic features of MS lesions. Online supplemental material is available for this article.

Larger lesion volume in people with multiple sclerosis is associated with increased transition energies between brain states and decreased entropy of brain activity.

Quantifying the relationship between the brain's functional activity patterns and its structural backbone is crucial when relating the severity of brain pathology to disability in multiple sclerosis (MS). Network control theory (NCT) characterizes the brain's energetic landscape using the structural connectome and patterns of brain activity over time. We applied NCT to investigate brain-state dynamics and energy landscapes in controls and people with MS (pwMS). We also computed entropy of brain activity and investigated its association with the dynamic landscape's transition energy and lesion volume. Brain states were identified by clustering regional brain activity vectors, and NCT was applied to compute the energy required to transition between these brain states. We found that entropy was negatively correlated with lesion volume and transition energy, and that larger transition energies were associated with pwMS with disability. This work supports the notion that shifts in the pattern of brain activity in pwMS without disability results in decreased transition energies compared to controls, but, as this shift evolves over the disease, transition energies increase beyond controls and disability occurs. Our results provide the first evidence in pwMS that larger lesion volumes result in greater transition energy between brain states and decreased entropy of brain activity.

Association of brain tissue cerebrospinal fluid fraction with age in healthy cognitively normal adults.

Background and purpose: Our objective was to apply multi-compartment T2 relaxometry in cognitively normal individuals aged 20-80 years to study the effect of aging on the parenchymal CSF fraction (CSFF), a potential measure of the subvoxel CSF space. Materials and methods: A total of 60 volunteers (age range, 22-80 years) were enrolled. Voxel-wise maps of short-T2 myelin water fraction (MWF), intermediate-T2 intra/extra-cellular water fraction (IEWF), and long-T2 CSFF were obtained using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) sequence and three-pool non-linear least squares fitting. Multiple linear regression analyses were performed to study the association between age and regional MWF, IEWF, and CSFF measurements, adjusting for sex and region of interest (ROI) volume. ROIs include the cerebral white matter (WM), cerebral cortex, and subcortical deep gray matter (GM). In each model, a quadratic term for age was tested using an ANOVA test. A Spearman's correlation between the normalized lateral ventricle volume, a measure of organ-level CSF space, and the regional CSFF, a measure of tissue-level CSF space, was computed. Results: Regression analyses showed that there was a statistically significant quadratic relationship with age for CSFF in the cortex (p = 0.018), MWF in the cerebral WM (p = 0.033), deep GM (p = 0.017) and cortex (p = 0.029); and IEWF in the deep GM (p = 0.033). There was a statistically highly significant positive linear relationship between age and regional CSFF in the cerebral WM (p < 0.001) and deep GM (p < 0.001). In addition, there was a statistically significant negative linear association between IEWF and age in the cerebral WM (p = 0.017) and cortex (p < 0.001). In the univariate correlation analysis, the normalized lateral ventricle volume correlated with the regional CSFF measurement in the cerebral WM (ρ = 0.64, p < 0.001), cortex (ρ = 0.62, p < 0.001), and deep GM (ρ = 0.66, p < 0.001). Conclusion: Our cross-sectional data demonstrate that brain tissue water in different compartments shows complex age-dependent patterns. Parenchymal CSFF, a measure of subvoxel CSF-like water in the brain tissue, is quadratically associated with age in the cerebral cortex and linearly associated with age in the cerebral deep GM and WM.