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Myelin is the protective sheath wrapped around axons, consisting of a phospholipid bilayer with water between the wraps. The measurement of damage to the myelin sheaths, the evaluation of the efficacy of therapies aiming to promote remyelination and monitoring the degree of brain maturation in children all require non-invasive quantitative myelin imaging methods. To date, various myelin imaging techniques have been developed. Five different MRI approaches can be distinguished based on their biophysical principles: (i) imaging of the water between the lipid bilayers directly (e.g. myelin water imaging); (ii) imaging the non-aqueous protons of the phospholipid bilayer directly with ultra-short echo-time techniques; (iii) indirect imaging of the macromolecular content (e.g. magnetization transfer; inhomogeneous magnetization transfer); (iv) mapping of the effects of the myelin sheath’s magnetic susceptibility on the MRI signal (e.g. quantitative susceptibility mapping); and (v) mapping of the effects of the myelin sheath on water diffusion. Myelin imaging with PET uses radioactive molecules with high affinity to specific myelin components, in particular myelin basic protein. This review aims to give an overview of the various myelin imaging techniques, their biophysical principles, image acquisition, data analysis and their validation status.

The SARS-CoV-2 virus has impacted life in many ways, one change being the use of face masks. Their effect on MRI-based measurements of cerebral oxygen levels with quantitative susceptibility mapping (QSM) and cerebral blood flow (CBF) is not known.This study investigated whether wearing a face mask leads to changes in CBF and cerebral venous oxygen saturation measured with MRI.Repeated-measures cohort study.A total of 16 healthy volunteers (eight male, eight female; 22-36 years) were recruited for the 3-ply study. Ten of the 16 participants (five male, five female; 23-36 years) took part in the KN95 study.A 3 T, single-delay 3D gradient-and spin-echo pseudo-continuous arterial spin labeling (pCASL) scan for CBF quantification, and gradient-echo for QSM and oxygenation quantification.Gray matter CBF and magnetic susceptibility were assessed by masking the pCASL CBF map and the QSM map to the TPaired Student's t-tests and Cohen's d effect sizes were used to compare the face mask and no face mask scans for gray matter CBF, gray matter magnetic susceptibility, and cerebral venous oxygen saturation. Standard t-tests were used to assess whether the order of scanning with and without a mask had any impact. A statistical cut off of P 0.05 was used.The 3-ply masks increased gray matter CBF from an average of 43.99 mL/(100 g*min) to 46.81 mL/(100 g*min). There were no significant changes in gray matter magnetic susceptibility (P = 0.07), or cerebral venous oxygen saturation (P = 0.36) for the 3-ply data set. The KN95 masks data set showed no statistically significant changes in gray matter CBF (P = 0.52) and magnetic susceptibility (P = 0.97), or cerebral venous oxygen saturation (P = 0.93).The changes in blood flow and oxygenation due to face masks are small. Only CBF increased significantly due to wearing a 3-ply mask.2 TECHNICAL EFFICACY: Stage 3.

Awareness about climate change has led to policies and regulations but also customer preferences favoring sustainable production. Thus, producing businesses are confronted by this, as they consume a large share of resources. Therefore, when producing, additional dimensions beyond commercial feasibility ought to be considered. Here, literature on sustainability from the field of engineering science is systematically searched and analyzed for approaches leading to actual recommendations for action. Hence, this bottom-up approach, incorporating the production engineers’ point of view, represents an inside view of how the topic of sustainability has arrived at production companies. The focus on commercial feasibility ensures high relevance to practice, as production needs to become both sustainable and competitive. Even though exemplary collections of different approaches addressing the topic of sustainability in production can be found in literature, novelty is provided by the structured manner literature was collected and the special focus on approaches leading to practice-relevant recommendations for action. Thus, a comprehensive overview of approaches applicable to the manufacturing domain is presented.

Background Technical improvements in magnetic resonance imaging (MRI) acquisition, such as higher field strength and optimized sequences, lead to better multiple sclerosis (MS) lesion detection and characterization. Multiplication of 3D-FLAIR with 3D-T2 sequences (FLAIR2) results in isovoxel images with increased contrast-to-noise ratio, increased white–gray-matter contrast, and improved MS lesion visualization without increasing MRI acquisition time. The current study aims to assess the potential of 3D-FLAIR2 in detecting cortical/leucocortical (LC), juxtacortical (JC), and white matter (WM) lesions. Objective To compare lesion detection of 3D-FLAIR2 with state-of-the-art 3D-T2-FLAIR and 3D-T2-weighted images. Methods We retrospectively analyzed MRI scans of thirteen MS patients, showing previously noted high cortical lesion load. Scans were acquired using a 3 T MRI scanner. WM, JC, and LC lesions were manually labeled and manually counted after randomization of 3D-T2, 3D-FLAIR, and 3D-FLAIR2 scans using the ITK-SNAP tool. Results LC lesion visibility was significantly improved by 3D-FLAIR2 in comparison to 3D-FLAIR (4 vs 1; p = 0.018) and 3D-T2 (4 vs 1; p = 0.007). Comparing LC lesion detection in 3D-FLAIR2 vs. 3D-FLAIR, 3D-FLAIR2 detected on average 3.2 more cortical lesions (95% CI − 9.1 to 2.8). Comparing against 3D-T2, 3D-FLAIR2 detected on average 3.7 more LC lesions (95% CI 3.3–10.7). Conclusions 3D-FLAIR2 is an easily applicable time-sparing MR post-processing method to improve cortical lesion detection. Larger sampled studies are warranted to validate the sensitivity and specificity of 3D-FLAIR2.

Magnetic resonance imaging (MRI) of focal or diffuse myelin damage or remyelination may provide important insights into disease progression and potential treatment efficacy in multiple sclerosis (MS). We performed post-mortem MRI and histopathological myelin measurements in seven progressive MS cases to evaluate the ability of three myelin-sensitive MRI scans to distinguish different stages of MS pathology, particularly chronic demyelinated and remyelinated lesions.At 3 Tesla, we acquired two different myelin water imaging (MWI) scans and magnetization transfer ratio (MTR) data. Histopathology included histochemical stainings for myelin phospholipids (LFB) and iron as well as immunohistochemistry for myelin proteolipid protein (PLP), CD68 (phagocytosing microglia/macrophages) and BCAS1 (remyelinating oligodendrocytes). Mixed-effects modelling determined which histopathological metric best predicted MWF and MTR in normal appearing and diffusely abnormal white matter, slowly expanding, inactive, remyelinated and ischemic lesions.Both MWI measures correlated well with each other and histology across regions, reflecting the different stages of MS pathology. MTR data showed a considerable influence of components other than myelin and a strong dependency on tissue storage duration. Both MRI and histology revealed increased myelin densities in inactive compared with slowly expanding lesions. Chronic inactive lesions harboured single scattered myelin fibres indicative of low-level remyelination. Mixed-effects modelling showed that smaller differences between white matter areas were linked to PLP densities and only to a smaller extent confounded by iron.MWI reflects differences in myelin lipids and proteins across all levels of myelin densities encountered in MS, including low-level remyelination in chronic inactive lesions.

BACKGROUND AND PURPOSE: Cerebral venous oxygen saturation can be used as an indirect measure of brain health, yet it often requires either an invasive procedure or a noninvasive technique with poor sensitivity. We aimed to test whether cerebral venous oxygen saturation could be measured using quantitative susceptibility mapping, an MR imaging technique, in 3 distinct groups: healthy term neonates, injured term neonates, and preterm neonates. MATERIALS AND METHODS: We acquired multiecho gradient-echo MR imaging data in 16 neonates with perinatal asphyxia and moderate or severe hypoxic-ischemic encephalopathy (8 term age: average, 40.0 [SD, 0.8] weeks’ gestational age; 8 preterm, 33.5 [SD, 2.0] weeks’ gestational age) and in 8 healthy term-age controls (39.3 [SD, 0.6] weeks, for a total of n = 24. Data were postprocessed as quantitative susceptibility mapping images, and magnetic susceptibility was measured in cerebral veins by thesholding out 99.95% of lower magnetic susceptibility values. RESULTS: The mean magnetic susceptibility value of the cerebral veins was found to be 0.36 (SD, 0.04) ppm in healthy term neonates, 0.36 (SD, 0.06) ppm in term injured neonates, and 0.29 (SD, 0.04) ppm in preterm injured neonates. Correspondingly, the derived cerebral venous oxygen saturation values were 73.6% (SD, 2.8%), 71.5% (SD, 7.4%), and 72.2% (SD, 5.9%). There was no statistically significant difference in cerebral venous oxygen saturation among the 3 groups (P = .751). CONCLUSIONS: Quantitative susceptibility mapping–derived oxygen saturation values in preterm and term neonates agreed well with values in past literature. Cerebral venous oxygen saturation in preterm and term neonates with hypoxic-ischemic encephalopathy, however, was not found to be significantly different between neonates or healthy controls.

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.

Cervical and upper-thoracic spinal cord injury (SCI) commonly results in autonomic cardiovascular impairments. These impairments can lead to alterations in blood flow, cerebral perfusion pressure and ultimately tissue perfusion, which can lead to an elevated risk of stroke and global cognitive deficits. The aim of this study was to assess cerebrovascular reactivity (CVR) in both the grey matter (GM) and brainstem using functional magnetic resonance imaging (fMRI) in participants with SCI compared to non-injured controls. CVR represents the capacity of brain parenchyma to change cerebral blood flow in response to a vasoactive stimulus (e.g. carbon dioxide, CO2) or altered metabolic demand [e.g. neurovascular coupling (NVC)]. Thirteen participants (7 chronic SCI (all male, median age of 42 years), 6 controls (all male, median age of 33 years) were studied cross-sectionally. CVR was measured by assessing the MRI-blood oxygen level–dependent signal with hypercapnic challenge (controlled CO2 inhalation). The CVR outcome measure was assessed in three ways. Initially, CVR was calculated as is standard, via the linear, least-squares fit across the whole gas challenge protocol (CVRwhole). In addition, CVR was further decomposed into its dynamic (tau) and static components (steady state CVR; ssCVR). A 24-hour ambulatory blood pressure monitor was worn to capture free-living blood pressure outcomes. Our results showed a longer tau in the GM of SCI participants compared to controls (median of the difference = 3.0 seconds; pS=-0.77, p=0.041 and RS=-0.76, p=0.049, respectively, where RS is the Spearman’s rank Correlation Coefficient. Neurological level of injury (NLI), modified into an ascending, continuous numeric variable, was positively correlated with GM CVRwhole (RS=0.85, p=0.016), GM ssCVR (RS=0.95, p=0.001) and brainstem ssCVR (RS=0.90, p=0.006). Lower CVRwhole and ssCVR in the SCI-cohort was significantly (PS≥ 0.81) and a higher frequency of hypotensive episodes (RS≥ -0.83). Thus, living with a SCI for a longer period of time, having a higher NLI and lower blood pressure are linked with poorer CVR outcomes. Our preliminary findings reveal an important difference between the cohorts in the dynamic CVR component, tau. Collectively, these results may partially explain the increased cerebrovascular health burden in individuals with SCI.HighlightsCVR is the change in blood flow in response to a vasodilatory stimulus (e.g., hypercapnia).Impaired CVR is linked with increased stroke risk and cognitive deficits.We investigated the dynamic and steady-state components of CVR using fMRI in individuals with a SCI.The dynamic component was significantly different compared to non-injured controls.CVR is significantly correlated with time since injury, level of injury and ambulatory daytime blood pressure.

Background: A large proportion of Alzheimer’s disease (AD) patients have coexisting subcortical vascular dementia (SVaD), a condition referred to as mixed dementia (MixD). Brain imaging features of MixD presumably include those of cerebrovascular disease and AD pathology, but are difficult to characterize due to their heterogeneity. Objective: To perform an exploratory analysis of conventional and non-conventional structural magnetic resonance imaging (MRI) abnormalities in MixD and to compare them to those observed in AD and SVaD. Methods: We conducted a cross-sectional, region-of-interest-based analysis of 1) hyperintense white-matter signal abnormalities (WMSA) on T2-FLAIR and hypointense WMSA on T1-weighted MRI; 2) diffusion tensor imaging; 3) quantitative susceptibility mapping; and 4) effective transverse relaxation rate (R2*) in N = 17 participants (AD:5, SVaD:5, MixD:7). General linear model was used to explore group differences in these brain imaging measures. Results: Model findings suggested imaging characteristics specific to our MixD group, including 1) higher burden of WMSAs on T1-weighted MRI (versus both AD and SVaD); 2) frontal lobar preponderance of WMSAs on both T2-FLAIR and T1-weighted MRI; 3) higher fractional anisotropy values within normal-appear white-matter tissues (versus SVaD, but not AD); and 4) lower R2* values within the T2-FLAIR WMSA areas (versus both AD and SVaD). Conclusion: These findings suggest a preliminary picture of the location and type of brain imaging characteristics associated with MixD. Future imaging studies may employ region-specific hypotheses to distinguish MixD more rigorously from AD or SVaD.

Cavities in the hippocampus are morphological variants of uncertain significance. Aberrant neurodevelopment along with vascular and inflammatory etiologies have been proposed. We sought to characterize these cavities and their potential risk factors in a marginally housed population, with high rates of viral infection, addiction, and mental illness. (1) The volume of hippocampal cavities (HCavs) is greater in this highly multimorbid population compared to the general population. (2) Conventional vascular risk factors such as greater age and systolic blood pressure are associated with higher HCav volume. (3) Nonprescribed substance-related risk factors such as stimulant use or dependence, and smoking are associated with increased HCav volume independent of vascular risk factors. This is a retrospective analysis of an ongoing prospective study. We analyzed baseline data, including medical history, physical exam, psychiatric diagnosis, and MRI from a total of 375 participants. Hippocampal cavities were defined as spaces isointense to CSF on T1 MRI sequences, bounded on all sides by hippocampal tissue, with a volume of at least 1 mm

Background and Purpose: We aim to describe the burden, characteristics, and cognitive associations of cerebral small vessel disease in a Canadian sample living with multimorbidity in precarious housing. Methods: Participants received T1, T2-fluid-attenuated inversion recovery, and susceptibility-weighted imaging 3T magnetic resonance imaging sequences and comprehensive clinical, laboratory, and cognitive assessments. Cerebral small vessel disease burden was characterized using a modified Small Vessel Disease (mSVD) score. One point each was given for moderate-severe white matter hyperintensities, ≥1 cerebral microbleeds, and ≥1 lacune. Multivariable regression explored associations between mSVD score, risk factors, and cognitive performance. Results: Median age of the 228 participants (77% male) was 44.7 years (range, 23.3–63.2). In n=188 participants with consistent good quality magnetic resonance imaging sequences, mSVD scores were 0 (n=127, 68%), 1 (n=50, 27%), and 2 (n=11, 6%). Overall, one-third had an mSVD ≥1 n=61 (32%); this proportion was unchanged when adding participants with missing sequences n=72/228 (32%). The most prevalent feature was white matter hyperintensities 53/218 (24%) then cerebral microbleed 16/191 (8%) and lacunes 16/228 (7%). Older age (odds ratio, 1.10 [95% CI, 1.05–1.15], P P =0.008), and a history of injection drug use (odds ratio, 3.13 [95% CI, 1.07–9.16], P =0.037) had significant independent associations with a mSVD score of ≥1 in multivariable analysis. mSVD ≥1 was associated with lower performance on tests of verbal memory, sustained attention, and decision-making, contributing 4% to 5% of the variance in each cognitive domain. Conclusions: The 32% prevalence of cerebral small vessel disease in this young, socially marginalized cohort was higher than expected for age and was associated with poorer cognitive performance.

Purpose Myelin water imaging (MWI) provides a valuable biomarker for myelin, but clinical application has been restricted by long acquisition times. Accelerating the standard multi-echo T2 acquisition with gradient echoes (GRASE) or by 2D multi-slice data collection results in image blurring, contrast changes, and other issues. Compressed sensing (CS) can vastly accelerate conventional MRI. In this work, we assessed the use of CS for in vivo human MWI, using a 3D multi spin-echo sequence. Methods We implemented multi-echo T2 relaxation imaging with compressed sensing (METRICS) and METRICS with partial Fourier acceleration (METRICS-PF). Scan-rescan data were acquired from 12 healthy controls for assessment of repeatability. MWI data were acquired for METRICS in 9 m:58 s and for METRICS-PF in 7 m:25 s, both with 1.5 × 2 × 3 mm3 voxels, 56 echoes, 7 ms ΔTE, and 240 × 240 × 170 mm3 FOV. METRICS was compared with a novel multi-echo spin-echo gold-standard (MSE-GS) MWI acquisition, acquired for a single additional subject in 2 h:2 m:40 s. Results METRICS/METRICS-PF myelin water fraction had mean: repeatability coefficient 1.5/1.1, coefficient of variation 6.2/4.5%, and intra-class correlation coefficient 0.79/0.84. Repeatability metrics comparing METRICS with METRICS-PF were similar, and both sequences agreed with reference values from literature. METRICS images and quantitative maps showed excellent qualitative agreement with those of MSE-GS. Conclusion METRICS and METRICS-PF provided highly repeatable MWI data without the inherent disadvantages of GRASE or 2D multi-slice acquisition. CS acceleration allows MWI data to be acquired rapidly with larger FOV, higher estimated SNR, more isotropic voxels and more echoes than with previous techniques. The approach introduced here generalizes to any multi-component T2 mapping application.

BackgroundHomeless or precariously housed individuals live with poor health and experience premature mortality compared with the general population, yet little is known about age-related brain changes among these individuals. We evaluated whether MRI measures of brain structure are differentially associated with age and selected risk factors among individuals who are homeless or precariously housed compared with a general population sample.MethodsWe compared T1-weighted and diffusion tensor imaging measures of brain macrostructure and white matter microstructure in a well-characterised sample of 312 precariously housed participants with a publicly available dataset of 382 participants recruited from the general population. We used piecewise and multiple linear regression to examine differential associations between MRI measures and between the samples, and to explore associations with risk factors in the precariously housed sample.ResultsCompared with the general population sample, older age in the precariously housed sample was associated with more whole-brain atrophy (β=−0.20, p=0.0029), lower whole-brain fractional anisotropy (β=−0.32, pConclusionsOlder age is associated with adverse MRI measures of brain structure among homeless and precariously housed individuals compared with the general population. Education, improvements in care provision and policy may help to reduce the health disparities experienced by these individuals.

ImportanceHomeless or precariously housed individuals live with poor health and experience premature mortality compared to the general population. With an increasing average age among this demographic, syndromes associated with neurogenerative disease are also increasing. Quantitative MRI measures may help define the roles of age and risk factors for poor brain health among these individuals.ObjectiveTo evaluate whether MRI measures of brain structure are differentially associated with age and selected risk factors among individuals who are homeless or precariously housed compared to a general population sample.Design, setting, and participantsCross sectional comparison of baseline data from 312 community-based, precariously housed participants with a publicly available dataset of 382 participants recruited from the general population.Exposure(s)The primary exposure was housing status (precariously housed vs general population). Risk factors in the precariously housed sample included mental illness, substance dependence, intravenous drug use, HIV, and history of traumatic brain injury.Main outcome(s) and measure(s)The main outcomes were MRI measures of whole-brain tissue- to-intracranial volume ratio, fractional anisotropy, and mean diffusivity. Multiple linear regression and piecewise regression were used to evaluate differences in associations between MRI measures and age between the samples, and to explore associations with risk factors in the precariously housed sample.ResultsCompared to the general population sample, older age in the precariously housed sample was associated with more whole-brain atrophy (β=-0.20, p=0.0029), lower whole-brain FA (β=-0.32, pβ=0.69, pConclusions and relevanceOlder age is associated with adverse MRI measures of brain structure among homeless and precariously housed individuals compared to the general population. Education, improvements in care provision and policy may help to reduce the health disparities experienced by these individuals.

Purpose To develop a deep neural network to recover filtered phase from clinical MR phase images to enable the computation of QSMs. Methods Eighteen deep learning networks were trained to recover combinations of 13 SWI phase-filtering pipelines. SWI-filtered data were computed offline from five multiorientation, multiecho MRI scans yielding 132 3D volumes (118/7/7 training/validation/testing). Two experiments were conducted to show the efficacy of the networks. First, using QSM processing, local fields were computed from the raw phase and subsequently filtered using the SWI-filtering pipelines. The networks were then trained to invert the filtering operation. Second, the trained networks were fine-tuned to recover unfiltered local fields from filtered local fields computed by applying QSM processing to the SWI-filtered phase. Susceptibility maps were computed from the recovered fields and compared with gold standard multiple orientation sampling reconstructions. Results Susceptibility maps computed from the raw phase using standard QSM processing have a normalized root mean square error (NRMSE) of 0.732 ± 0.095. Susceptibility maps computed from the recovered phase obtained NRMSEs of 0.725 ± 0.095. The network trained using all 13 processing methods generalized well, obtaining NRMSEs of 0.725 ± 0.89 on filters it has not seen, while matching the reconstruction accuracy of networks trained to recover a single filter. Conclusion It is feasible to recover SWI-filtered phase using deep learning. QSM can be computed from the recovered phase from SWI acquisition with comparable accuracy to standard QSM processing.

Pain and related consequences could contribute to comorbid illness and premature mortality in homeless and precariously housed persons. We analyzed longitudinal data from an ongoing naturalistic prospective study of a community-based sample (n = 370) to characterize risk factors and consequences of bodily pain. The aims were to describe bodily pain and associations with symptoms and psychosocial function, investigate factors that may increase or ameliorate pain, and examine the consequences of pain for symptoms, functioning, and all-cause mortality. Bodily pain severity and impact were rated with the 36-item Short Form Health Survey Bodily Pain Scale monthly over 5 years. Mixed-effects linear regression models estimated the effects of time-invariant and time-varying risk factors for pain, verified by reverse causality and multiple imputation analysis. Regression models estimated the associations between overall person-mean pain severity and subsequent functioning and suicidal ideation, and Cox proportional hazard models assessed association with all-cause mortality. Bodily pain of at least moderate severity persisted (3 months) in 64% of participants, exceeding rates expected in the general population. Greater pain severity was associated with depressive symptom severity and month-to-month opioid use, overlaid on enduring risk associated with age, arthritis, and posttraumatic stress disorder. The frequency of prescribed and nonprescribed opioid use had nonlinear relationships with pain: intermittent use was associated with severe pain, without reverse association or change with the overdose epidemic. Greater longitudinal mean pain severity was associated with premature mortality, poorer functioning, and suicidal ideation. Considering the relationships between pain, intermittent opioid use, and depressive symptoms could improve health care for precariously housed patients.

Background and purpose Myelin water fraction (MWF) is a histopathologically validated in vivo myelin marker. As MWF is the proportion of water with a short T2 relative to the total water, increases in water from edema and inflammation may confound MWF determination in multiple sclerosis (MS) lesions. Total water content (TWC) measurement enables calculation of absolute myelin water content (MWC) and can be used to distinguish edema/inflammation from demyelination. We assessed what influence changes in total water might have on MWF by calculating MWC values in new MS lesions. Methods 3T 32-echo T2 relaxation data were collected monthly for 6 months from six relapsing-remitting MS participants. TWC was determined and multiplied with MWF images to calculate corrected MWC images. The effect of this water content correction was examined in 20 new lesions by comparing mean MWF and MWC over time. Results On average, at lesion first appearance, lesion TWC increased by 6.4% (p = .003; range: -1% to +21%), MWF decreased by 24% (p = .006; range: -70% to +12%), and MWC decreased by 20% (p = .026; range: -68% to +21%), relative to prelesion values. Average TWC in lesions then gradually decreased, whereas MWF and MWC remained low. The shape of the MWF and MWC lesion evolution curves was nearly identical, differing only by an offset. Conclusion MWF mirrors MWC and is able to monitor myelin in new lesions. Even after taking into account water content increases, MWC still decreased at lesion first appearance attributed to demyelination.

Background and purpose Cognitive impairment is a core symptom in multiple sclerosis (MS). Damage to normal appearing white matter (NAWM) is likely involved. We sought to determine if greater myelin heterogeneity in NAWM is associated with decreased cognitive performance in MS. Methods A total of 27 participants with MS and 13 controls matched for age, sex, and education underwent myelin water imaging (MWI) from which the myelin water fraction (MWF) was calculated. Corpus callosum, superior longitudinal fasciculus, and cingulum were chosen as regions of interest (ROIs) a priori based on their involvement in MS-related cognitive impairment. Cognitive performance was assessed using the Symbol Digit Modalities Test (SDMT). Pearson s product moment correlations were performed to assess relationships between cognitive performance and myelin heterogeneity (variance of MWF within an ROI). Results In MS, myelin heterogeneity in all three ROIs was significantly associated with performance on the SDMT. These correlations ranged from moderate (r = -.561) to moderately strong (r = -.654) and were highly significant (P values ranged from .001 to .0002). Conversely, myelin heterogeneity was not associated with SDMT performance in controls in any ROI (P > .108). Conclusion Increased myelin heterogeneity in NAWM is associated with decreased cognitive processing speed performance in MS.

Schizophrenia and stimulant-induced psychosis (SIP) represent two different forms of psychotic disorder, with different etiologies. While many of the symptoms of psychosis are common to both disorders, there have been few direct comparisons between these conditions, especially when controlling for stimulant use in individuals with schizophrenia. We directly compared both psychotic disorders with a comprehensive battery of clinical, neurocognitive and neuroanatomical measures. This included one group with SIP (and concurrent stimulant dependence) and two groups with schizophrenia (either with or without concurrent stimulant dependence). Ninety-six participants were recruited from a marginalized urban population, which included 39 with SIP (and concurrent stimulant dependence), 18 with schizophrenia (without stimulant dependence), and 39 with schizophrenia (with concurrent stimulant dependence). All subjects had extensive clinical and neurocognitive evaluations, complemented with structural MRI including diffusion tensor imaging (DTI) sequences to determine regional brain volumes and white matter connectivity. Both positive and negative symptoms were greater in the SZ-dependent group than the other two. Neurocognitive function was broadly similar. The structural brain imaging revealed lateralized changes to the left parietal/temporal lobe, in which regional volumes were smaller in the SZ-dependent than the SZ-non-dependent group. DTI analysis indicated extensive decreases in fractional anisotropy, with parallel increases in radial diffusivity, in the SIP group compared to the SZ-dependent group. These findings reveal both similarities and differences between SIP and schizophrenia. Furthermore, schizophrenia with concurrent stimulant dependence may be associated with a different clinical and neuroanatomical profile as compared to schizophrenia alone.

The most recent guidelines for magnetic resonance imaging (MRI) in multiple sclerosis (MS) recommend three-dimensional (3D) MRI sequences over their two-dimensional (2D) counterparts. This development has been made possible by advances in MRI scanner hardware and software. In this article, we review the 3D versions of conventional sequences, including T1-weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR), as well as more advanced scans, including double inversion recovery (DIR), FLAIR2, FLAIR*, phase-sensitive inversion recovery, and susceptibility weighted imaging (SWI).