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Background and Objectives: Accumulating evidence points to worse clinical outcomes among adults with multiple sclerosis (MS) belonging to minority or poverty-affected groups. By contrast, little is known about the outcomes of these populations with pediatric-onset MS (POMS). Individuals with POMS represent 5% of the MS population and are more racially diverse yet have been understudied regarding socioeconomic environment or characteristics. In this study, we investigated the association between childhood social determinants of health (SDOH) and brain MRI outcomes in patients with POMS., Methods: This is a retrospective single-site cohort study of patients with POMS with brain MRI quantitatively analyzed using icobrain software to yield total white matter lesion, black hole, whole brain, white matter, and gray matter volumes. All patients with POMS evaluated at New York University Langone MS Center and who underwent high-quality volumetric MRI scans were included in this study. SDOH indicators of race, ethnicity, health insurance type, parental education, and childhood neighborhood social vulnerability index (SVI) were examined for association with MRI outcomes using linear least absolute shrinkage selection operator penalized regression modeling. Disease-modifying therapy (DMT) timing and DMT efficacy were compared for each SDOH category., Results: A total of 138 patients with POMS (70% female) were included with a mean age of 19.86 years and median disease duration of 4 years at time of scan. Public health insurance, Black race, Hispanic ethnicity, low parental education, and high SVI (greater neighborhood disadvantage) were each associated with white matter lesion and black hole volume. SVI was the strongest individual predictor of total white matter lesion (β = 4.63, p = 0.002) and black hole volume (β = 2.91, p = 0.003). In models incorporating all SDOH variables, public health insurance was the strongest predictor of total lesion (β = 2.48, p = 0.01) and black hole volume (β = 1.50, p = 0.02), attenuating the effect of SVI (β = 1.66, p = 0.33 and β = 1.00, p = 0.39). There were no differences in DMT timing or efficacy between categories of social disadvantage., Discussion: Individual-level and neighborhood-level indicators of social disadvantage are associated with worse brain MRI outcomes in POMS. Further investigation of race, ethnicity, and childhood disadvantage as risk factors of MS susceptibility and severity is needed to reduce MS health disparities.

Automated quantification of brain tissues on MR images has greatly contributed to the diagnosis and follow-up of neurological pathologies across various life stages. However, existing solutions are specifically designed for certain age ranges, limiting their applicability in monitoring brain development from infancy to late adulthood. This retrospective study aims to develop and validate a brain segmentation model across pediatric and adult populations. First, we trained a deep learning model to segment tissues and brain structures using T1-weighted MR images from 390 patients (age range: 2-81 years) across four different datasets. Subsequently, the model was validated on a cohort of 280 patients from six distinct test datasets (age range: 4-90 years). In the initial experiment, the proposed deep learning-based pipeline, icobrain-dl, demonstrated segmentation accuracy comparable to both pediatric and adult-specific models across diverse age groups. Subsequently, we evaluated intra- and inter-scanner variability in measurements of various tissues and structures in both pediatric and adult populations computed by icobrain-dl. Results demonstrated significantly higher reproducibility compared to similar brain quantification tools, including childmetrix, FastSurfer, and the medical device icobrain v5.9 (p-value< 0.01). Finally, we explored the potential clinical applications of icobrain-dl measurements in diagnosing pediatric patients with Cerebral Visual Impairment and adult patients with Alzheimer's Disease., (© 2024. The Author(s).)

Background: The connectome, constituting a unique fingerprint of a person's brain, may be influenced by its prenatal environment, potentially affecting later-life resilience and mental health., Methods: We conducted a prospective resting-state functional Magnetic Resonance Imaging study in 28-year-old offspring (N = 49) of mothers whose anxiety was monitored during pregnancy. Two offspring anxiety subgroups were defined: "High anxiety" (n = 13) group versus "low-to-medium anxiety" (n = 36) group, based on maternal self-reported state anxiety at 12-22 weeks of gestation. To predict resting-state functional connectivity of 32 by 32 ROIs, maternal state anxiety during pregnancy was included as a predictor in general linear models for both ROI-to-ROI and graph theoretical metrics. Sex, birth weight and postnatal anxiety were included as covariates., Results: Higher maternal anxiety was associated with weaker functional connectivity of medial prefrontal cortex with left inferior frontal gyrus (t = 3.45, p FDR < 0.05). Moreover, network-based statistics (NBS) confirmed our finding and revealed an additional association of weaker connectivity between left lateral prefontal cortex with left somatosensory motor gyrus in the offspring. While our results showed a general pattern of lower functional connectivity in adults prenatally exposed to maternal anxiety, we did not observe significant differences in global brain networks between groups., Conclusions: Weaker (medial) prefrontal cortex functional connectivity in the high anxiety adult offspring group suggests a long-term negative impact of prenatal exposure to high maternal anxiety, extending into adulthood. To prevent mental health problems at population level, universal primary prevention strategies should aim at lowering maternal anxiety during pregnancy., (© 2023. The Author(s).)

Background: We evaluated imaging features suggestive of neurodegeneration within the brainstem and upper cervical spinal cord (UCSC) in non-progressive multiple sclerosis (MS)., Methods: Standardized 3-Tesla three-dimensional brain magnetic resonance imaging (MRI) studies were prospectively acquired. Rates of change in volume, surface texture, curvature were quantified at the pons and medulla-UCSC. Whole and regional brain volumes and T2-weighted lesion volumes were also quantified. Independent regression models were constructed to evaluate differences between those of Black or African ancestry (B/AA) and European ancestry (EA) with non-progressive MS., Results: 209 people with MS (pwMS) having at least two MRI studies, 29% possessing 3-6 timepoints, resulted in 487 scans for analysis. Median follow-up time between MRI timepoints was 1.33 (25th-75th percentile: 0.51-1.98) years. Of 183 non-progressive pwMS, 88 and 95 self-reported being B/AA and EA, respectively. Non-progressive pwMS demonstrated greater rates of decline in pontine volume ( p  < 0.0001) in B/AA and in medulla-UCSC volume ( p  < 0.0001) for EA pwMS. Longitudinal surface texture and curvature changes suggesting reduced tissue integrity were observed at the ventral medulla-UCSC ( p  < 0.001), dorsal pons ( p  < 0.0001) and dorsal medulla ( p  < 0.0001) but not the ventral pons ( p  = 0.92) between groups., Conclusions: Selectively vulnerable regions within the brainstem-UCSC may allow for more personalized approaches to disease surveillance and management.

Background: Relatively little is known about how global and regional brain volumes changes in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) compare with Multiple Sclerosis (MS), Neuromyelitis optica spectrum disorder (NMOSD), and healthy controls (HC)., Objective: To compare global and regional brain volumes in MOGAD, MS, NMOSD, and HC cross-sectionally as well as longitudinally in a subset of patients., Methods: We retrospectively reviewed all adult MOGAD and NMOSD patients with brain MRI performed in stable remission and compared them with MS patients and HC. Volumetric parameters were assessed using the FDA-approved icobrain software. adjusted for age and sex., Results: Twenty-four MOGAD, 47 NMOSD, 40 MS patients, and 37 HC were included in the cross-sectional analyses. Relative to HC, the age-adjusted whole brain (WB) volume was significantly lower in patients with MOGAD (p=0.0002), NMOSD (p=0.042), and MS (p=0.01). Longitudinal analysis of a subset of 8 MOGAD, 22 NMOSD, and 34 MS patients showed a reduction in the WB and cortical gray matter (CGM) volumes over time in all three disease groups, without statistically significant differences between groups. The MOGAD group had a greater loss of thalamic volume compared to MS (p=0.028) and NMOSD (p=0.023) and a greater loss of hippocampal volumes compared to MS (p=0.007)., Conclusions: Age-adjusted WB volume loss was evident in all neuroinflammatory conditions relative to HC in cross-sectional comparisons. In longitudinal analyses, MOGAD patients had a higher thalamic atrophy rate relative to MS and NMOSD, and a higher hippocampal atrophy rate relative to MS. Larger studies are needed to validate these findings and to investigate their clinical implications., Competing Interests: Declaration of Competing Interest Itay Lotan – no conflict of interest related to the study. Thibo Billiet- an employee of icometrix. Annemie Ribbens- an employee of icometrix. Win Van Hecke- founder of icometrix. Benny Huang- no conflict of interest related to the study. Ilya Kister- Ilya Kister reports he served on advisory boards for Biogen, Genentech, and Horizon and received research support for investigator-initiated grants from Genentech, Sanofi Genzyme, Biogen, EMD Serono, National MS Society, and Guthy Jackson Charitable Foundation. He received royalties from Walters-Kluwer for 'Top 100 Diagnosis in Neurology'. Eyal Lotan- no conflict of interest related to the study., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background and Purpose: Diffusion tensor imaging (DTI) can detect microstructural changes of white matter in multiple sclerosis (MS) and might clarify mechanisms responsible for disability. Thus, we aimed to compare DTI metrics in relapsing-remitting MS patients (RRMS) with healthy controls (HCs), and explore the correlations between DTI metrics, total brain white matter (TBWM) and white matter lesion (WML) with clinical parameters compared to volumetric measures., Material and Methods: 37 RRMS patients and 19 age/sex-matched HCs were included. All participants had clinical assessments, structural and diffusion scans on a 3T MRI. Volumetric and white matter DTI metrics; fractional anisotropy (FA), mean, radial and axial diffusivities (MD, RD and AD) were estimated and correlated with clinical parameters. The mean group differences were calculated using t-tests, and univariate correlations with Pearson correlation coefficients., Results: Compared to HCs, statistically significant increases in MD (+3.6%), RD (+4.8%), AD (+2.7%) and a decrease in FA (-4.3%) for TBWM in RRMS was observed ( p < .01). MD and RD in TBWM and AD in WML correlated moderately with disability status. Volumetric segmentation indicated a decrease in the total brain volume, GM and WM(-5%) with a reciprocal increase in CSF(+26%) in RRMS( p < .01). Importantly, DTI parameters showed a medium correlation with cognitive domains in contrast to white matter-related volumetric measurements in RRMS(Pearson correlation, p < .05)., Conclusions: Our study shows a correlation of DTI metrics with clinical symptoms of MS, in particular cognition. More generally, these findings indicated that DTI is a useful and unique technique for evaluating the clinical features of white matter disease and warrants further investigation into its clinical role.

Competing Interests: Michiel Bronswijk has received grants from Prion Medical, Taewoong, and Takeda, and has consultancy agreements with Prion Medical and Taewoong. Diederik Persyn, Thomas Billiet, and Ruben Spitaels declare no conflicts of interest. Hannah van Malenstein has consultancy agreements with Boston Scientific. Schalk Van der Merwe holds the Cook and Boston-Scientific chair in interventional endoscopy and holds consultancy agreements with Cook, Pentax, and Olympus.

The free water elimination (FWE) model and its kurtosis variant (DKI-FWE) can separate tissue and free water signal contributions, thus providing tissue-specific diffusional information. However, a downside of these models is that the associated parameter estimation problem is ill-conditioned, necessitating the use of advanced estimation techniques that can potentially bias the parameter estimates. In this work, we propose the T 2 -DKI-FWE model that exploits the T 2 relaxation properties of both compartments, thereby better conditioning the parameter estimation problem and providing, at the same time, an additional potential biomarker (the T 2 of tissue). In our approach, the T 2 of tissue is estimated as an unknown parameter, whereas the T 2 of free water is assumed known a priori and fixed to a literature value (1573 ms). First, the error propagation of an erroneous assumption on the T 2 of free water is studied. Next, the improved conditioning of T 2 -DKI-FWE compared to DKI-FWE is illustrated using the Cramér-Rao lower bound matrix. Finally, the performance of the T 2 -DKI-FWE model is compared to that of the DKI-FWE and T 2 -DKI models on both simulated and real datasets. The error due to a biased approximation of the T 2 of free water was found to be relatively small in various diffusion metrics and for a broad range of erroneous assumptions on its underlying ground truth value. Compared to DKI-FWE, using the T 2 -DKI-FWE model is beneficial for the identifiability of the model parameters. Our results suggest that the T 2 -DKI-FWE model can achieve precise and accurate diffusion parameter estimates, through effective reduction of free water partial volume effects and by using a standard nonlinear least squares approach. In conclusion, incorporating T 2 relaxation properties into the DKI-FWE model improves the conditioning of the model fitting, while only requiring an acquisition scheme with at least two different echo times., Competing Interests: Declaration of Competing Interest VA has a collaboration agreement with icometrix. JV is co-inventor of a patent on the denoising methodology that was used in this study (US10698065B2). TB is employee of icometrix. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022. Published by Elsevier Inc.)

Diffusion-weighted imaging studies have repeatedly shown that white matter correlates with reading throughout development. However, the neurobiological interpretation of this relationship is constrained by the limited microstructural specificity of diffusion imaging. A critical component of white matter microstructure is myelin, which can be investigated noninvasively using MRI. Here, we examined the link between myelin water fraction (MWF) and reading ability in 10-year-old children (n = 69). To better understand this relationship, we additionally investigated how these two variables relate to fractional anisotropy (FA; a common index of diffusion-weighted imaging). Our analysis revealed that lower MWF coheres with better reading scores in left-hemispheric tracts relevant for reading. While we replicated previous reports on a positive relationship between FA and MWF, we did not find any evidence for an association between reading and FA. Together, these findings contrast previous research suggesting that poor reading abilities might be rooted in lower myelination and emphasize the need for further longitudinal research to understand how this relationship evolves throughout reading development. Altogether, this study contributes important insights into the role of myelin-related processes in the relationship between reading and white matter structure., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Competing Interests: The authors declare that they have no conflict of interest.