Diurnal fluctuations in brain volume: Statistical analyses of MRI from large populations

Impact of the day/night cycle on functional connectome in ageing male and female mice

To elucidate how time of day, sex, and age affect functional connectivity (FC) in mice, we aimed to examine whether the mouse functional connectome varied with the day/night cycle and whether it depended on sex and age. We explored C57Bl6/J mice (6♀ and 6♂) at mature age (5 ± 1 months) and middle-age (14 ± 1 months). Each mouse underwent Blood Oxygen-Level-Dependent (BOLD) resting-state functional MRI (rs-fMRI) on a 7T scanner at four different times of the day, two under the light condition and two under the dark condition. Data processing consisted of group independent component analysis (ICA) and region-level analysis using resting-state networks (RSNs) derived from literature. Linear mixed-effect models (LMEM) were used to assess the effects of sex, lighting condition and their interactions for each RSN obtained with group-ICA (RSNs-GICA) and six bilateral RSNs adapted from literature (RSNs-LIT). Our study highlighted new RSNs in mice related to day/night alternation in addition to other networks already reported in the literature. In mature mice, we found sex-related differences in brain activation only in one RSNs-GICA comprising the cortical, hippocampal, midbrain and cerebellar regions of the right hemisphere. In males, brain activity was significantly higher in the left hippocampus, the retrosplenial cortex, the superior colliculus, and the cerebellum regardless of lighting condition; consistent with the role of these structures in memory formation and integration, sleep, and sex-differences in memory processing. Experimental constraints limited the analysis to the impact of light/dark cycle on the RSNs for middle-aged females. We detected significant activation in the pineal gland during the dark condition, a finding in line with the nocturnal activity of this gland. For the analysis of RSNs-LIT, new variables "sexage" (sex and age combined) and "edges" (pairs of RSNs) were introduced. FC was calculated as the Pearson correlation between two RSNs. LMEM revealed no effect of sexage or lighting condition. The FC depended on the edges, but there were no interaction effects between sexage, lighting condition and edges. Interaction effects were detected between i) sex and lighting condition, with higher FC in males under the dark condition, ii) sexage and edges with higher FC in male brain regions related to vision, memory, and motor action. We conclude that time of day and sex should be taken into account when designing, analyzing, and interpreting functional imaging studies in rodents.

Sex, gender diversity, and brain structure in early adolescence

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Effects of sleep quality on diurnal variation of brain volume in older adults: A retrospective cross-sectional study

AIM

Brain volume is influenced by several factors that can change throughout the day. In addition, most of these factors are influenced by sleep quality. This study investigated diurnal variation in brain volume and its relation to overnight sleep quality.

METHODS

We enrolled 1,003 healthy Koreans without any psychiatric disorders aged 60 years or older. We assessed sleep quality and average wake time using the Pittsburgh Sleep Quality Index, and divided sleep quality into good, moderate, and poor groups. We estimated the whole and regional brain volumes from three-dimensional T1-weighted brain MRI scans. We divided the interval between average wake-up time and MRI acquisition time (INT) into tertile groups: short (INT1), medium (INT2), and long (INT3).

RESULTS

Whole and regional brain volumes showed no significance with respect to INT. However, the `interaction between INT and sleep quality showed significance for whole brain, cerebral gray matter, and cerebrospinal fluid volumes (p < .05). The INT2 group showed significantly lower volumes of whole brain, whole gray matter, cerebral gray matter, cortical gray matter, subcortical gray matter, and cerebrospinal fluid than the INT1 and INT3 groups only in the individuals with good sleep quality.

CONCLUSION

Human brain volume changes significantly within a day associated with overnight sleep in the individuals with good sleep quality.

Synchronous functional magnetic resonance eye imaging, video ophthalmoscopy, and eye surface imaging reveal the human brain and eye pulsation mechanisms

The eye possesses a paravascular solute transport pathway that is driven by physiological pulsations, resembling the brain glymphatic pathway. We developed synchronous multimodal imaging tools aimed at measuring the driving pulsations of the human eye, using an eye-tracking functional eye camera (FEC) compatible with magnetic resonance imaging (MRI) for measuring eye surface pulsations. Special optics enabled integration of the FEC with MRI-compatible video ophthalmoscopy (MRcVO) for simultaneous retinal imaging along with functional eye MRI imaging (fMREye) of the BOLD (blood oxygen level dependent) contrast. Upon optimizing the fMREye parameters, we measured the power of the physiological (vasomotor, respiratory, and cardiac) eye and brain pulsations by fast Fourier transform (FFT) power analysis. The human eye pulsated in all three physiological pulse bands, most prominently in the respiratory band. The FFT power means of physiological pulsation for two adjacent slices was significantly higher than in one-slice scans (RESP1 vs. RESP2; df = 5, p = 0.045). FEC and MRcVO confirmed the respiratory pulsations at the eye surface and retina. We conclude that in addition to the known cardiovascular pulsation, the human eye also has respiratory and vasomotor pulsation mechanisms, which are now amenable to study using non-invasive multimodal imaging of eye fluidics.

Brain volume increase after discontinuing natalizumab therapy: Evidence for reversible pseudoatrophy

BACKGROUND

The phenomenon of pseudoatropy after initiation of anti-inflammatory therapy is believed to be reversible, but a rebound in brain volume following cessation of highly-effective therapy has not been reported.

OBJECTIVES

To evaluate brain volume change in a treatment interruption study (RESTORE) in which relapsing-remitting multiple sclerosis (RRMS) patients were randomized to switch from natalizumab to placebo, from natalizumab to once-monthly intravenous methylprednisolone (IVMP), or to remain on natalizumab.

METHODS

T2 lesion volume (T2LV), baseline normalized brain volumes, and follow-up percent brain volume changes (PBVC) were calculated. Approximate T2 relaxation-time (pT2) was calculated within the brain mask and the T2 lesions to estimate changes in water content. Linear mixed effects models were used to detect differences in T2LV, pT2 in whole brain, pT2 in T2-weighted lesions, and PBVC among the placebo, natalizumab, and IVMP groups. We also estimated contributions of T2LV and pT2 (in whole brain and T2 lesions) to PBVC.

RESULTS

T2LV increased in the placebo group (by 0.66 ml/year, p<0.0001) and IVMP (+1.98 ml/year, p = 0.05) groups relative to the natalizumab group. The rates of PBVC were significantly different: -0.239%/year with continued natalizumab and +0.126 %/year after switch to placebo (p = 0.03), while the IVMP group showed brain volume loss (-0.74 %/ year, p = 0.08). pT2 was not statistically different between the groups (p ≥ 0.29) and did not have significant effects on PBVC (p ≥ 0.25).

CONCLUSION

The increase in the brain volume in patients witching from natalizumab to placebo is consistent with reversal of so-called pseudoatrophy after starting natalizumab.

Diurnal oscillations of MRI metrics in the brains of male participants

Regulation of biological processes according to a 24-hr rhythm is essential for the normal functioning of an organism. Temporal variation in brain MRI data has often been attributed to circadian or diurnal oscillations; however, it is not clear if such oscillations exist. Here, we provide evidence that diurnal oscillations indeed govern multiple MRI metrics. We recorded cerebral blood flow, diffusion-tensor metrics, T1 relaxation, and cortical structural features every three hours over a 24-hr period in each of 16 adult male controls and eight adult male participants with bipolar disorder. Diurnal oscillations are detected in numerous MRI metrics at the whole-brain level, and regionally. Rhythmicity parameters in the participants with bipolar disorder are similar to the controls for most metrics, except for a larger phase variation in cerebral blood flow. The ubiquitous nature of diurnal oscillations has broad implications for neuroimaging studies and furthers our understanding of the dynamic nature of the human brain.

Intersite brain MRI volumetric biases persist even in a harmonized multisubject study of multiple sclerosis

BACKGROUND AND PURPOSE

Multicenter study designs involving a variety of MRI scanners have become increasingly common. However, these present the issue of biases in image-based measures due to scanner or site differences. To assess these biases, we imaged 11 volunteers with multiple sclerosis (MS) with scan and rescan data at four sites.

METHODS

Images were acquired on Siemens or Philips scanners at 3 Tesla. Automated white matter lesion detection and whole-brain, gray and white matter, and thalamic volumetry were performed, as well as expert manual delineations of T1 magnetization-prepared rapid acquisition gradient echo and T2 fluid-attenuated inversion recovery lesions. Random-effect and permutation-based nonparametric modeling was performed to assess differences in estimated volumes within and across sites.

RESULTS

Random-effect modeling demonstrated model assumption violations for most comparisons of interest. Nonparametric modeling indicated that site explained >50% of the variation for most estimated volumes. This expanded to >75% when data from both Siemens and Philips scanners were included. Permutation tests revealed significant differences between average inter- and intrasite differences in most estimated brain volumes (P < .05). The automatic activation of spine coil elements during some acquisitions resulted in a shading artifact in these images. Permutation tests revealed significant differences between thalamic volume measurements from acquisitions with and without this artifact.

CONCLUSION

Differences in brain volumetry persisted across MR scanners despite protocol harmonization. These differences were not well explained by variance component modeling; however, statistical innovations for mitigating intersite differences show promise in reducing biases in multicenter studies of MS.

Neurodegeneration and its potential markers in the diagnosing of secondary progressive multiple sclerosis. A review

Approximately 70% of relapsing-remitting multiple sclerosis (RRMS) patients will develop secondary progressive multiple sclerosis (SPMS) within 10-15 years. This progression is characterized by a gradual decline in neurological functionality and increasing limitations of daily activities. Growing evidence suggests that both inflammation and neurodegeneration are associated with various pathological processes throughout the development of MS; therefore, to delay disease progression, it is critical to initiate disease-modifying therapy as soon as it is diagnosed. Currently, a diagnosis of SPMS requires a retrospective assessment of physical disability exacerbation, usually over the previous 6-12 months, which results in a delay of up to 3 years. Hence, there is a need to identify reliable and objective biomarkers for predicting and defining SPMS conversion. This review presents current knowledge of such biomarkers in the context of neurodegeneration associated with MS, and SPMS conversion.

Effect of ibudilast on thalamic magnetization transfer ratio and volume in progressive multiple sclerosis

BACKGROUND

Thalamic volume (TV) is a sensitive biomarker of disease burden of injury in multiple sclerosis (MS) and appears to reflect overall lesion loads. Ibudilast showed significant treatment effect on brain atrophy and magnetization transfer ratio (MTR) of normal-appearing brain tissue but not in new/enlarging T2 lesion in the SPRINT-MS randomized clinical trial.

OBJECTIVE

To evaluate the effect of ibudilast on thalamic tissue integrity and volume in the SPRINT-MS.

METHODS

A total of 255 participants with progressive MS were randomized to oral ibudilast or placebo, and thalamic MTR and normalized TV over 96 weeks were quantified. Mixed-effect modeling assessed treatment effects on the thalamic MTR and TV, separately. Similarly, the measures were compared between the participants with confirmed disability progression (CDP).

RESULTS

Ibudilast's treatment effect was observed compared to placebo for thalamic MTR (p = 0.03) but not for TV (p = 0.68) while TV correlated with T2 lesion volume (p < 0.001). CDP associated with thalamic MTR (p = 0.04) but not with TV (p = 0.7).

CONCLUSION

Ibudilast showed an effect on thalamic MTR, which was associated with CDP, suggesting a clinically relevant effect on thalamic tissue integrity. However, the treatment effect was not observed in TV, suggesting that thalamic atrophy is more closely associated with global inflammatory activity than local tissue integrity.

CLINICALTRIALS.GOV

NCT01982942.

Sex, gender diversity, and brain structure in children ages 9 to 11 years old

There remains little consensus about the relationship between sex and brain structure, particularly in childhood. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest - many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years-old (N=7693). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. The model with sex, but not gender diversity, was the best-fitting model in 75% of gray matter regions and 79% of white matter regions examined. The addition of gender to the sex model explained significantly more variance than sex alone with regard to bilateral cerebellum volume, left precentral cortical thickness, as well as gyrification in the right superior frontal gyrus, right parahippocampal gyrus, and several regions in the left parietal lobe. For mean diffusivity in the left uncinate fasciculus, the model with sex, gender, and their interaction captured the most variance. Nonetheless, the magnitude of variance accounted for by sex was small in all cases and felt-gender score was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years-old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Time of day dependent longitudinal changes in resting-state fMRI

Longitudinal studies have become more common in the past years due to their superiority over cross-sectional samples. In light of the ongoing replication crisis, the factors that may introduce variability in resting-state networks have been widely debated. This publication aimed to address the potential sources of variability, namely, time of day, sex, and age, in longitudinal studies within individual resting-state fMRI data. DCM was used to analyze the fMRI time series, extracting EC connectivity measures and parameters that define the BOLD signal. In addition, a two-way ANOVA was used to assess the change in EC and parameters that define the BOLD signal between data collection waves. The results indicate that time of day and gender have significant model evidence for the parameters that define the BOLD signal but not EC. From the ANOVA analysis, findings indicate that there was a significant change in the two nodes of the DMN and their connections with the fronto-parietal network. Overall, these findings suggest that in addition to age and gender, which are commonly accounted for in the fMRI data collection, studies should note the time of day, possibly treating it as a covariate in longitudinal samples.

Rapid volumetric brain changes after acute psychosocial stress

Stress is an important trigger for brain plasticity: Acute stress can rapidly affect brain activity and functional connectivity, and chronic or pathological stress has been associated with structural brain changes. Measures of structural magnetic resonance imaging (MRI) can be modified by short-term motor learning or visual stimulation, suggesting that they also capture rapid brain changes. Here, we investigated volumetric brain changes (together with changes in T1 relaxation rate and cerebral blood flow) after acute stress in humans as well as their relation to psychophysiological stress measures. Sixty-seven healthy men (25.8±2.7 years) completed a standardized psychosocial laboratory stressor (Trier Social Stress Test) or a control version while blood, saliva, heart rate, and psychometrics were sampled. Structural MRI (T1 mapping / MP2RAGE sequence) at 3T was acquired 45 min before and 90 min after intervention onset. Grey matter volume (GMV) changes were analysed using voxel-based morphometry. Associations with endocrine, autonomic, and subjective stress measures were tested with linear models. We found significant group-by-time interactions in several brain clusters including anterior/mid-cingulate cortices and bilateral insula: GMV was increased in the stress group relative to the control group, in which several clusters showed a GMV decrease. We found a significant group-by-time interaction for cerebral blood flow, and a main effect of time for T1 values (longitudinal relaxation time). In addition, GMV changes were significantly associated with state anxiety and heart rate variability changes. Such rapid GMV changes assessed with VBM may be induced by local tissue adaptations to changes in energy demand following neural activity. Our findings suggest that endogenous brain changes are counteracted by acute psychosocial stress, which emphasizes the importance of considering homeodynamic processes and generally highlights the influence of stress on the brain.

Gadolinium-based contrast agent exposures and physical and cognitive disability in multiple sclerosis

BACKGROUND AND PURPOSE

The clinical correlation of gadolinium-based contrast agents (GBCAs) has not been well studied in multiple sclerosis (MS). We investigated the extent to which the number of GBCA administrations relates to self-reported disability and performance measures.

METHODS

A cohort of MS patients was analyzed in this retrospective observational study. The main outcome was the association between the cumulative number of GBCA exposures (linear or macrocyclic GBCA), Patient-Determined Disease Steps (PDDS), and measures of physical and cognitive performance (walking speed test, manual dexterity test [MDT], and processing speed test [PST]). The analysis was performed first cross-sectionally and then longitudinally.

RESULTS

The cross-sectional data included 1059 MS patients with a mean age of 44.0 years (standard deviation = 11.2). While the contrast ratio in globus pallidus weakly correlated with PDDS, MDT, and PST in a univariate correlational analysis (coefficients, 95% confidence interval [CI] = 0.11 [0.04, 0.18], 0.15 [0.08, 0.21], and -0.16 [-0.10, -0.23], respectively), the associations disappeared after covariate adjustment. A significant association was found between number of linear GBCA administrations and PDDS (coefficient [CI] = -0.131 [-0.196, -0.067]), and MDT associated with macrocyclic GBCA administrations (-0.385 [-0.616, -0.154]), but their signs indicated better outcomes in patients with greater GBCA exposures. The longitudinal data showed no significant detrimental effect of macrocyclic GBCA exposures.

CONCLUSION

No detrimental effects were observed between GBCA exposure and self-reported disability and standardized objective measures of physical and cognitive performance. While several weak associations were found, they indicated benefit on these measures.

The glymphatic system: Current understanding and modeling

We review theoretical and numerical models of the glymphatic system, which circulates cerebrospinal fluid and interstitial fluid around the brain, facilitating solute transport. Models enable hypothesis development and predictions of transport, with clinical applications including drug delivery, stroke, cardiac arrest, and neurodegenerative disorders like Alzheimer’s disease. We sort existing models into broad categories by anatomical function: Perivascular flow, transport in brain parenchyma, interfaces to perivascular spaces, efflux routes, and links to neuronal activity. Needs and opportunities for future work are highlighted wherever possible; new models, expanded models, and novel experiments to inform models could all have tremendous value for advancing the field.

The glymphatic system: implications for drugs for central nervous system diseases

In the past decade, evidence for a fluid clearance pathway in the central nervous system known as the glymphatic system has grown. According to the glymphatic system concept, cerebrospinal fluid flows directionally through the brain and non-selectively clears the interstitium of metabolic waste. Importantly, the glymphatic system may be modulated by particular drugs such as anaesthetics, as well as by non-pharmacological factors such as sleep, and its dysfunction has been implicated in central nervous system disorders such as Alzheimer disease. Although the glymphatic system is best described in rodents, reports using multiple neuroimaging modalities indicate that a similar transport system exists in the human brain. Here, we overview the evidence for the glymphatic system and its role in disease and discuss opportunities to harness the glymphatic system therapeutically; for example, by improving the effectiveness of intrathecally delivered drugs.

A daily temperature rhythm in the human brain predicts survival after brain injury

Patients undergo interventions to achieve a 'normal' brain temperature; a parameter that remains undefined for humans. The profound sensitivity of neuronal function to temperature implies the brain should be isothermal, but observations from patients and non-human primates suggest significant spatiotemporal variation. We aimed to determine the clinical relevance of brain temperature in patients by establishing how much it varies in healthy adults. We retrospectively screened data for all patients recruited to the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) High Resolution Intensive Care Unit Sub-Study. Only patients with direct brain temperature measurements and without targeted temperature management were included. To interpret patient analyses, we prospectively recruited 40 healthy adults (20 males, 20 females, 20-40 years) for brain thermometry using magnetic resonance spectroscopy. Participants were scanned in the morning, afternoon, and late evening of a single day. In patients (n = 114), brain temperature ranged from 32.6 to 42.3°C and mean brain temperature (38.5 ± 0.8°C) exceeded body temperature (37.5 ± 0.5°C, P < 0.0001). Of 100 patients eligible for brain temperature rhythm analysis, 25 displayed a daily rhythm, and the brain temperature range decreased in older patients (P = 0.018). In healthy participants, brain temperature ranged from 36.1 to 40.9°C; mean brain temperature (38.5 ± 0.4°C) exceeded oral temperature (36.0 ± 0.5°C) and was 0.36°C higher in luteal females relative to follicular females and males (P = 0.0006 and P < 0.0001, respectively). Temperature increased with age, most notably in deep brain regions (0.6°C over 20 years, P = 0.0002), and varied spatially by 2.41 ± 0.46°C with highest temperatures in the thalamus. Brain temperature varied by time of day, especially in deep regions (0.86°C, P = 0.0001), and was lowest at night. From the healthy data we built HEATWAVE-a 4D map of human brain temperature. Testing the clinical relevance of HEATWAVE in patients, we found that lack of a daily brain temperature rhythm increased the odds of death in intensive care 21-fold (P = 0.016), whilst absolute temperature maxima or minima did not predict outcome. A warmer mean brain temperature was associated with survival (P = 0.035), however, and ageing by 10 years increased the odds of death 11-fold (P = 0.0002). Human brain temperature is higher and varies more than previously assumed-by age, sex, menstrual cycle, brain region, and time of day. This has major implications for temperature monitoring and management, with daily brain temperature rhythmicity emerging as one of the strongest single predictors of survival after brain injury. We conclude that daily rhythmic brain temperature variation-not absolute brain temperature-is one way in which human brain physiology may be distinguished from pathophysiology.

Impact of physiological factors on longitudinal structural MRI measures of the brain

Longitudinal MRI is used in clinical research studies to examine illness progression, neurodevelopment, and the effect of medical interventions. Such studies typically report changes in brain volume of less than 5%. However, there is a concern that these findings could be obscured or confounded by small changes in brain volume estimates caused by physiological factors such as, dehydration, blood pressure, caffeine levels, and circadian rhythm. In this study, MRI scans using the ADNI-III protocol were acquired from 20 participants (11 female) at two time points (mean interval = 20.3 days). Hydration, systolic and diastolic blood pressure, caffeine intake, and time of day were recorded at both visits. Images were processed using FreeSurfer. Three a priori hypothesised brain regions (hippocampus, lateral ventricles, and total brain) were selected, and an exploratory analysis was conducted on FreeSurfer's auto-segmented brain regions. There was no significant effect of the physiological factors on changes in the hypothesised brain regions. We provide estimates for the maximum percentage change in regional brain volumes that could be expected to occur from normal variation in each of the physiological measures. In this study, normal variations in physiological parameters did not have a detectable effect on longitudinal changes in brain volume.

Per1 gene polymorphisms influence the relationship between brain white matter microstructure and depression risk

BACKGROUND

Circadian rhythm was involved in the pathogenesis of depression. The detection of circadian genes and white matter (WM) integrity achieved increasing focus for early prediction and diagnosis of major depressive disorder (MDD). This study aimed to explore the effects of PER1 gene polymorphisms (rs7221412), one of the key circadian genes, on the association between depressive level and WM microstructural integrity.

MATERIALS AND METHODS

Diffusion tensor imaging scanning and depression assessment (Beck Depression Inventory, BDI) were performed in 77 healthy college students. Participants also underwent PER1 polymorphism detection and were divided into the AG group and AA group. The effects of PER1 genotypes on the association between the WM characteristics and BDI were analyzed using tract-based spatial statistics method.

RESULTS

Compared with homozygous form of PER1 gene (AA), more individuals with risk allele G of PER1 gene (AG) were in depression state with BDI cutoff of 14 (χ² = 7.37, uncorrected p = 0.007). At the level of brain imaging, the WM integrity in corpus callosum, internal capsule, corona radiata and fornix was poorer in AG group compared with AA group. Furthermore, significant interaction effects of genotype × BDI on WM characteristics were observed in several emotion-related WM tracts. To be specific, the significant relationships between BDI and WM characteristics in corpus callosum, internal capsule, corona radiata, fornix, external capsule and sagittal stratum were only found in AG group, but not in AA group.

CONCLUSION

Our findings suggested that the PER1 genotypes and emotion-related WM microstructure may provide more effective measures of depression risk at an early phase.

Time-of-Day Effects in Resting-State Functional Magnetic Resonance Imaging: Changes in Effective Connectivity and Blood Oxygenation Level Dependent Signal

Introduction:

In the light of the ongoing replication crisis in the field of neuroimaging, it is necessary to assess the possible exogenous and endogenous factors that may affect functional magnetic resonance imaging (fMRI). The current project investigated time-of-day effects in the spontaneous fluctuations (<0.1 Hz) of the blood oxygenation level dependent (BOLD) signal.

Method:

Using data from the human connectome project release S1200, cross-spectral density dynamic causal modeling (DCM) was used to analyze time-dependent effects on the hemodynamic response and effective connectivity parameters. The DCM analysis covered three networks, namely the default mode network, the central executive network, and the saliency network. Hierarchical group-parametric empirical Bayes (PEB) was used to test varying design-matrices against the time-of-day model.

Results:

Hierarchical group-PEB found no support for changes in effective connectivity, whereas the hemodynamic parameters exhibited a significant time-of-day dependent effect, indicating a diurnal vascular effect that might affect the measured BOLD signal in the absence of any diurnal variations of the underlying neuronal activations and effective connectivity.

Conclusion:

We conclude that these findings urge the need to account for the time of data acquisition in future MRI studies and suggest that time-of-day dependent metabolic variations contribute to reduced reliability in resting-state fMRI studies.

Impact statement

The results from this study suggest that the circadian mechanism influences the blood oxygenation level dependent signal in resting-state functional magnetic resonance imaging (fMRI). The current study urges to record and report the time of fMRI scan acquisition in future research, as it may increase the replicability of findings. Both exploratory and clinical studies would benefit by incorporating this small change in fMRI protocol, which to date has been often overlooked.

Reproducibility of volume and asymmetry measurements of hippocampus, amygdala, and entorhinal cortex on traveling volunteers: a multisite MP2RAGE prospective study

BACKGROUND

Multisite studies can considerably increase the pool of normally aging individuals with neurodegenerative disorders and thereby expedite the associated research. Understanding the reproducibility of the parameters of related brain structures-including the hippocampus, amygdala, and entorhinal cortex-in multisite studies is crucial in determining the impact of healthy aging or neurodegenerative diseases.

PURPOSE

To estimate the reproducibility of the fascinating structures by automatic (FreeSurfer) and manual segmentation methods in a well-controlled multisite dataset.

MATERIAL AND METHODS

Three traveling individuals were scanned at 10 sites, which were equipped with the same equipment (3T Prisma Siemens). They used the same scan protocol (two inversion-contrast magnetization-prepared rapid gradient echo sequences) and operators. Validity coefficients (intraclass correlations coefficient [ICC]) and spatial overlap measures (Dice Similarity Coefficient [DSC]) were used to estimate the reproducibility of multisite data.

RESULTS

ICC and DSC values varied substantially among structures and segmentation methods, and values of manual tracing were relatively higher than the automated method. ICC and DSC values of structural parameters were greater than 0.80 and 0.60 across sites, as determined by manual tracing. Low reproducibility was observed in the amygdala parameters by automatic segmentation method (ICC = 0.349-0.529, DSC = 0.380-0.873). However, ICC and DSC scores of the hippocampus were higher than 0.60 and 0.65 by two segmentation methods.

CONCLUSION

This study suggests that a well-controlled multisite study could provide a reliable MRI dataset. Manual tracing of volume assessments is recommended for low reproducibility structures that require high levels of precision in multisite studies.

Clinical and Paraclinical Biomarkers and the Hitches to Assess Conversion to Secondary Progressive Multiple Sclerosis: A Systematic Review

Conversion to secondary progressive (SP) course is the decisive factor for long-term prognosis in relapsing multiple sclerosis (MS), generally considered the clinical equivalent of progressive MS-associated neuroaxonal degeneration. Evidence is accumulating that both inflammation and neurodegeneration are present along a continuum of pathologic processes in all phases of MS. While inflammation is the prominent feature in early stages, its quality changes and relative importance to disease course decreases while neurodegenerative processes prevail with ongoing disease. Consequently, anti-inflammatory disease-modifying therapies successfully used in relapsing MS are ineffective in SPMS, whereas specific treatment for the latter is increasingly a focus of MS research. Therefore, the prevention, but also the (anticipatory) diagnosis of SPMS, is of crucial importance. The problem is that currently SPMS diagnosis is exclusively based on retrospectively assessing the increase of overt physical disability usually over the past 6–12 months. This inevitably results in a delay of diagnosis of up to 3 years resulting in periods of uncertainty and, thus, making early therapy adaptation to prevent SPMS conversion impossible. Hence, there is an urgent need for reliable and objective biomarkers to prospectively predict and define SPMS conversion. Here, we review current evidence on clinical parameters, magnetic resonance imaging and optical coherence tomography measures, and serum and cerebrospinal fluid biomarkers in the context of MS-associated neurodegeneration and SPMS conversion. Ultimately, we discuss the necessity of multimodal approaches in order to approach objective definition and prediction of conversion to SPMS.

Measuring Treatment Response in Progressive Multiple Sclerosis-Considerations for Adapting to an Era of Multiple Treatment Options

Disability in multiple sclerosis accrues predominantly in the progressive forms of the disease. While disease-modifying treatment of relapsing MS has drastically evolved over the last quarter-century, the development of efficient drugs for preventing or at least delaying disability in progressive MS has proven more challenging. In that way, many drugs (especially disease-modifying treatments) have been researched in the aspect of delaying disability progression in patients with a progressive course of the disease. While there are some disease-modifying treatments approved for progressive multiple sclerosis, their effect is moderate and limited mostly to patients with clinical and/or radiological signs of disease activity. Several phase III trials have used different primary outcomes with different time frames to define disease progression and to evaluate the efficacy of a disease-modifying treatment. The lack of sufficiently sensitive outcome measures could be a possible explanation for the negative clinical trials in progressive multiple sclerosis. On the other hand, even with a potential outcome measure that would be sensitive enough to determine disease progression and, thus, the efficacy or failure of a disease-modifying treatment, the question of clinical relevance remains unanswered. In this systematic review, we analyzed outcome measures and definitions of disease progression in phase III clinical trials in primary and secondary progressive multiple sclerosis. We discuss advantages and disadvantages of clinical and paraclinical outcome measures aiming for practical ways of combining them to detect disability progression more sensitively both in future clinical trials and current clinical routine.

Sleep-related and diurnal effects on brain diffusivity and cerebrospinal fluid flow

The question of how waste products are cleared from the brain, and the role which sleep plays in this process, is critical for our understanding of a range of physical and mental illnesses. In rodents, both circadian and sleep-related processes appear to facilitate clearance of waste products. The purpose of this study was to investigate whether overnight changes in diffusivity, brain volumes, and cerebrospinal fluid flow measured with MRI are associated with sleep parameters from overnight high-density sleep EEG, and circadian markers. In healthy adults investigated with MRI before and after sleep EEG, we observed an increase in water diffusivity overnight, which was positively related to the proportion of total sleep time spent in rapid eye movement (REM) sleep, and negatively associated with the fraction of sleep time spent in non rapid eye movement (NREM) sleep. Diffusivity was also associated with the sleep midpoint, a circadian marker. CSF flow increased overnight; this increase was unrelated to sleep or diffusivity measures but was associated with circadian markers. These results provide evidence for both sleep related and diurnal effects on water compartmentalisation within the brain.

Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study

Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g., due to manufacturers) and changes in scanner performance (e.g., due to gradual component aging, software and/or hardware upgrades, etc.). As part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI) and the Canadian Biomarker Integration Network in Depression (CAN-BIND), QA phantom scans were conducted approximately monthly for three to four years at 13 sites across Canada with 3T research MRI scanners. QA parameters were calculated for each scan using the functional Biomarker Imaging Research Network's (fBIRN) QA phantom and pipeline to capture between- and within-scanner variability. We also describe a QA protocol to measure the full-width-at-half-maximum (FWHM) of slice-wise point spread functions (PSF), used in conjunction with the fBIRN QA parameters. Variations in image resolution measured by the FWHM are a primary source of variance over time for many sites, as well as between sites and between manufacturers. We also identify an unexpected range of instabilities affecting individual slices in a number of scanners, which may amount to a substantial contribution of unexplained signal variance to their data. Finally, we identify a preliminary preprocessing approach to reduce this variance and/or alleviate the slice anomalies, and in a small human data set show that this change in preprocessing can have a significant impact on seed-based connectivity measurements for some individual subjects. We expect that other fMRI centres will find this approach to identifying and controlling scanner instabilities useful in similar studies.

Effects of weather and season on human brain volume

We present an exploratory cross-sectional analysis of the effect of season and weather on Freesurfer-derived brain volumes from a sample of 3,279 healthy individuals collected on two MRI scanners in Hartford, CT, USA over a 15 year period. Weather and seasonal effects were analyzed using a single linear regression model with age, sex, motion, scan sequence, time-of-day, month of the year, and the deviation from average barometric pressure, air temperature, and humidity, as covariates. FDR correction for multiple comparisons was applied to groups of non-overlapping ROIs. Significant negative relationships were found between the left- and right- cerebellum cortex and pressure (t = -2.25, p = 0.049; t = -2.771, p = 0.017). Significant positive relationships were found between left- and right- cerebellum cortex and white matter between the comparisons of January/June and January/September. Significant negative relationships were found between several subcortical ROIs for the summer months compared to January. An opposing effect was observed between the supra- and infra-tentorium, with opposite effect directions in winter and summer. Cohen’s d effect sizes from monthly comparisons were similar to those reported in recent psychiatric big-data publications, raising the possibility that seasonal changes and weather may be confounds in large cohort studies. Additionally, changes in brain volume due to natural environmental variation have not been reported before and may have implications for weather-related and seasonal ailments.

Sleep and sleep deprivation differentially alter white matter microstructure: A mixed model design utilising advanced diffusion modelling

Sleep deprivation influences several critical functions, yet how it affects human brain white matter (WM) is not well understood. The aim of the present work was to investigate the effect of 32 hours of sleep deprivation on WM microstructure compared to changes observed in a normal sleep-wake cycle (SWC). To this end, we utilised diffusion weighted imaging (DWI) including the diffusion tensor model, diffusion kurtosis imaging and the spherical mean technique, a novel biophysical diffusion model. 46 healthy adults (23 sleep deprived vs 23 with normal SWC) underwent DWI across four time points (morning, evening, next day morning and next day afternoon, after a total of 32 hours). Linear mixed models revealed significant group × time interaction effects, indicating that sleep deprivation and normal SWC differentially affect WM microstructure. Voxel-wise comparisons showed that these effects spanned large, bilateral WM regions. These findings provide important insight into how sleep deprivation affects the human brain.

Study protocol: randomised controlled trial evaluating exercise therapy as a supplemental treatment strategy in early multiple sclerosis: the Early Multiple Sclerosis Exercise Study (EMSES)

INTRODUCTION

In the relapsing remitting type of multiple sclerosis (MS) reducing relapses and neurodegeneration is crucial in halting the long-term impact of the disease. Medical disease-modifying treatments have proven effective, especially when introduced early in the disease course. However, patients still experience disease activity and disability progression, and therefore, supplemental early treatment strategies are warranted. Exercise appear to be one of the most promising supplemental treatment strategies, but a somewhat overlooked 'window of opportunity' exist early in the disease course. The objective of this study is to investigate exercise as a supplementary treatment strategy early in the disease course of MS.

METHODS AND ANALYSIS

The presented Early Multiple Sclerosis Exercise Study is a 48-week (plus 1-year follow-up) national multicentre single-blinded parallel group randomised controlled trial comparing two groups receiving usual care plus supervised high-intense exercise or plus health education (active control). Additionally, data will be compared with a population-based control group receiving usual care only obtained from the Danish MS Registry. The primary outcomes are annual relapse rate and MRI derived global brain atrophy. The secondary outcomes are disability progression, physical and cognitive function, MS-related symptoms, and exploratory MRI outcomes. All analyses will be performed as intention to treat.

ETHICS AND DISSEMINATION

The study is approved by The Central Denmark Region Committees on Health Research Ethics (1-10-72-388-17) and registered at the Danish Data Protection Agency (2016-051-000001 (706)). All study findings will be published in scientific peer-reviewed journals and presented at relevant scientific conferences.

TRIAL REGISTRATION NUMBER

NCT03322761.

Replicability, Repeatability, and Long-term Reproducibility of Cerebellar Morphometry

To identify robust and reproducible methods of cerebellar morphometry that can be used in future large-scale structural MRI studies, we investigated the replicability, repeatability, and long-term reproducibility of three fully automated software tools: FreeSurfer, CEREbellum Segmentation (CERES), and automatic cerebellum anatomical parcellation using U-Net with locally constrained optimization (ACAPULCO). Replicability was defined as computational replicability, determined by comparing two analyses of the same high-resolution MRI data set performed with identical analysis software and computer hardware. Repeatability was determined by comparing the analyses of two MRI scans of the same participant taken during two independent MRI sessions on the same day for the Kirby-21 study. Long-term reproducibility was assessed by analyzing two MRI scans of the same participant in the longitudinal OASIS-2 study. We determined percent difference, the image intraclass correlation coefficient, the coefficient of variation, and the intraclass correlation coefficient between two analyses. Our results show that CERES and ACAPULCO use stochastic algorithms that result in surprisingly high differences between identical analyses for ACAPULCO and small differences for CERES. Changes between two consecutive scans from the Kirby-21 study were less than ± 5% in most cases for FreeSurfer and CERES (i.e., demonstrating high repeatability). As expected, long-term reproducibility was lower than repeatability for all software tools. In summary, CERES is an accurate, as demonstrated before, and reproducible tool for fully automated segmentation and parcellation of the cerebellum. We conclude with recommendations for the assessment of replicability, repeatability, and long-term reproducibility in future studies on cerebellar structure.

Time in Brain: How Biological Rhythms Impact on EEG Signals and on EEG-Derived Brain Networks

Electroencephalography (EEG) is a widely employed tool for exploring brain dynamics and is used extensively in various domains, ranging from clinical diagnosis via neuroscience, cognitive science, cognitive psychology, psychophysiology, neuromarketing, neurolinguistics, and pharmacology to research on brain computer interfaces. EEG is the only technique that enables the continuous recording of brain dynamics over periods of time that range from a few seconds to hours and days and beyond. When taking long-term recordings, various endogenous and exogenous biological rhythms may impinge on characteristics of EEG signals. While the impact of the circadian rhythm and of ultradian rhythms on spectral characteristics of EEG signals has been investigated for more than half a century, only little is known on how biological rhythms influence characteristics of brain dynamics assessed with modern EEG analysis techniques. At the example of multiday, multichannel non-invasive and invasive EEG recordings, we here discuss the impact of biological rhythms on temporal changes of various characteristics of human brain dynamics: higher-order statistical moments and interaction properties of multichannel EEG signals as well as local and global characteristics of EEG-derived evolving functional brain networks. Our findings emphasize the need to take into account the impact of biological rhythms in order to avoid erroneous statements about brain dynamics and about evolving functional brain networks.

Comorbidity effect on processing speed test and MRI measures in multiple sclerosis patients

BACKGROUND

Comorbid conditions are known to affect the clinical course of multiple sclerosis (MS). Our objective was to determine the impact of comorbidities on the processing speed test (PST).

METHODS

We conducted a retrospective, longitudinal analysis of all patients who completed PST testing from June 2015 - August 2019 at our center. Our electronic medical record was queried to determine the presence of the following comorbidities: diabetes mellitus (DM), hypertension (HTN), hyperlipidemia (HLD), coronary artery disease, and depression. To help address baseline PST performance and practice effect, patients were also divided into four quartiles by baseline PST scores. Brain MRIs obtained within a 90-day window from the initial clinical assessment were quantitatively analyzed via fully-automated methods to calculate whole brain fraction (WBF), T2 lesion volume (T2LV), gray matter fraction (GMF), and thalamic volume (TV). Univariable and multivariable linear regression models were used to determine the relationship between the comorbidities, PST performance and MRI metrics over time.

RESULTS

A total of 4,344 patients (mean age 49.5 ± 12.4 years, 72.3% female, and 63.7% relapsing remitting MS) were included in the analysis with 13,375 individual patient encounters. Over half the cohort (52.4%) suffered from at least one comorbidity with the most common being depression (37.4%), HLD (20.9%), HTN (19.6%), and DM (6.4%). Patients with one or more comorbidity had lower baseline PST scores. Longitudinally, patients with two comorbidities lost 1.46 points on the PST per year relative to those with no comorbidities (95% CI -2.46 - -0.46, p = 0.004). Individuals with depression had lower PST scores than those without, and this difference persisted over time (β = -2.40, 95% CI -3.08 - -1.73, p < 0.001). At baseline, HLD patients had higher PST scores than non-HLD patients (β = 1.10, 95% CI 0.15 - 2.05, p = 0.022), but this difference did not remain over time. Individuals in the highest PST performance quartile were negatively impacted when diagnosed with depression, HTN, and DM relative to those without the comorbidities. There were no other correlations with PST scores and the remaining comorbidities. Depression was associated with lower baseline WBF (β = -0.0043, 95% CI -0.0084 - -0.0003, p = 0.033) and GMF (β = -0.0046, 95% CI -0.0078 - -0.0015, p = 0.004) along with larger T2LV (β = 0.1605, 95% CI 0.0082 - 0.3128, p = 0.039). HLD patients had more favorable baseline MRI measures, including higher WBF (β = 0.0076, 95% CI 0.0017 - 0.0135, p = 0.012) and TV (β = 0.0002, 95% CI 0.0000 - 0.0005, p = 0.041), with a lower T2LV (β = -0.2963, 95% CI -0.5219 - -0.0706, p = 0.010).

CONCLUSIONS

Comorbidities are common within a MS cohort and adversely impact processing speed. Depression adversely impacted PST scores with worse MRI outcomes. HLD was associated with lower longitudinal PST measures but favorable quantitative MRI metrics. MS patients with faster baseline processing speeds were most sensitive to comorbid conditions. Our findings suggest a complex interplay between cognition and comorbid conditions in MS patients.

Manganese-Enhanced MRI in Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE

Cellular uptake of the manganese ion, when administered as a contrast agent for MR imaging, can noninvasively highlight cellular activity and disease processes in both animals and humans. The purpose of this study was to explore the enhancement profile of manganese in patients with multiple sclerosis.

MATERIALS AND METHODS

Mangafodipir is a manganese chelate that was clinically approved for MR imaging of liver lesions. We present a case series of 6 adults with multiple sclerosis who were scanned at baseline with gadolinium, then injected with mangafodipir, and followed at variable time points thereafter.

RESULTS

Fourteen new lesions formed during or shortly before the study, of which 10 demonstrated manganese enhancement of varying intensity, timing, and spatial pattern. One gadolinium-enhancing extra-axial mass, presumably a meningioma, also demonstrated enhancement with manganese. Most interesting, manganese enhancement was detected in lesions that formed in the days after mangafodipir injection, and this enhancement persisted for several weeks, consistent with contrast coming from intracellular uptake of manganese. Some lesions demonstrated a diffuse pattern of manganese enhancement in an area larger than that of both gadolinium enhancement and T2-FLAIR signal abnormality.

CONCLUSIONS

This work demonstrates the first use of a manganese-based contrast agent to enhance MS lesions on MR imaging. Multiple sclerosis lesions were enhanced with a temporal and spatial profile distinct from that of gadolinium. Further experiments are necessary to uncover the mechanism of manganese contrast enhancement as well as cell-specific uptake.

Brain Volume: An Important Determinant of Functional Outcome After Acute Ischemic Stroke

OBJECTIVE

To determine whether brain volume is associated with functional outcome after acute ischemic stroke (AIS).

PATIENTS AND METHODS

This study was conducted between July 1, 2014, and March 16, 2019. We analyzed cross-sectional data of the multisite, international hospital-based MRI-Genetics Interface Exploration study with clinical brain magnetic resonance imaging obtained on admission for index stroke and functional outcome assessment. Poststroke outcome was determined using the modified Rankin Scale score (0-6; 0 = asymptomatic; 6 = death) recorded between 60 and 190 days after stroke. Demographic characteristics and other clinical variables including acute stroke severity (measured as National Institutes of Health Stroke Scale score), vascular risk factors, and etiologic stroke subtypes (Causative Classification of Stroke system) were recorded during index admission.

RESULTS

Utilizing the data from 912 patients with AIS (mean ± SD age, 65.3±14.5 years; male, 532 [58.3%]; history of smoking, 519 [56.9%]; hypertension, 595 [65.2%]) in a generalized linear model, brain volume (per 155.1 cm³) was associated with age (β -0.3 [per 14.4 years]), male sex (β 1.0), and prior stroke (β -0.2). In the multivariable outcome model, brain volume was an independent predictor of modified Rankin Scale score (β -0.233), with reduced odds of worse long-term functional outcomes (odds ratio, 0.8; 95% CI, 0.7-0.9) in those with larger brain volumes.

CONCLUSION

Larger brain volume quantified on clinical magnetic resonance imaging of patients with AIS at the time of stroke purports a protective mechanism. The role of brain volume as a prognostic, protective biomarker has the potential to forge new areas of research and advance current knowledge of the mechanisms of poststroke recovery.

Cognitive processing speed in multiple sclerosis clinical practice: association with patient-reported outcomes, employment and magnetic resonance imaging metrics

BACKGROUND AND PURPOSE

To analyze the relationship between cognitive processing speed, patient-reported outcome measures (PROMs), employment and magnetic resonance imaging (MRI) metrics in a large multiple sclerosis cohort.

METHODS

Cross-sectional clinical data, PROMs, employment and MRI studies within 90 days of completion of the Processing Speed Test (PST), a technology-enabled adaptation of the Symbol Digit Modalities Test, were collected. MRI was analyzed using semi-automated methods. Correlations of PST score with PROMs and MRI metrics were examined using Spearman's rho. Wilcoxon rank sum testing compared MRI metrics across PST score quartiles and linear regression models identified predictors of PST performance. Effects of employment and depression were also investigated.

RESULTS

In 721 patients (mean age 47.6 ± 11.4 years), PST scores were significantly correlated with all MRI metrics, including cord atrophy and deep gray matter volumes. Linear regression demonstrated self-reported physical disability, cognitive function, fatigue and social domains (adjusted R²  = 0.44, P < 0.001) as the strongest clinical predictors of PST score, whereas that of MRI variables included T2 lesion volume, whole-brain fraction and cord atrophy (adjusted R²  = 0.42, P < 0.001). An inclusive model identified T2 lesion volume, whole-brain fraction, self-reported upper extremity function, cognition and social participation as the strongest predictors of PST score (adjusted R²  = 0.51, P < 0.001). There was significant effect modification by depression on the relationship between self-reported cognition and PST performance. Employment status was associated with PST scores independent of age and physical disability.

CONCLUSION

The PST score correlates with PROMs, MRI measures of focal and diffuse brain injury, and employment. The PST score is a feasible and meaningful measure for routine multiple sclerosis care.

Inclusion of the Symbol Digit Modalities Test in a revised assessment of 'no evidence of disease activity-4 (NEDA-4)' in Latin-American patients with multiple sclerosis

BACKGROUND

In relapsing-remitting multiple sclerosis (RRMS), no evidence of disease activity-3 (NEDA-3) is defined as the absence of: (1) relapses; (2) disability progression; (3) MRI activity (new/enlarged T2 lesions and/or gadolinium-enhanced T1 lesions). NEDA-4 status is defined as meeting all NEDA-3 criteria plus having an annualized percentage brain volume change (a-PBVC) >-0.4%. In individual patients, brain volume assessment is confounded with normal aging, methodological limitations and fluid-shift related fluctuations in brain volume. Cognitive impairment has been proposed as another component that should be integrated into therapeutic algorithms for RRMS. We aim to determine the proportion of patients failing to meet NEDA-4 criteria and to appraise whether the Symbol Digit Modalities Test (SDMT) is capable of replacing a-PBVC as one of the components of NEDA-4. We hypothesize that NEDA-4 has the potential to capture the impact of DMT therapies in RRMS.

METHODS

Forty-five patients were prospectively followed 1 and 2 years after their baseline assessment at the University of Chile Hospital. SIENA software was used to assess a-PBVC.

RESULTS

At baseline, the patients had a mean age of 33.0 years (range 18-57), disease duration of 1.9 years (0.4-4), Expanded Disability Status Scale score of 1.3 (0-4), and 67% were female. The majority had RRMS (91% while 9% had clinically isolated syndrome (CIS)). Seventy-three percent were on the so-called first line DMTs such as interferons (53%), glatiramer acetate (13%), teriflunomide (9%), and 18% were on fingolimod. There was a serial decline in the proportion of NEDA: after 1 and 2 years of follow-up 60% and 47% met NEDA-3 status, and 38% and 27% met NEDA-4, respectively. At the last follow-up 21% remained on interferons, 47% were now on fingolimod, 4% on alemtuzumab and 2% on natalizumab. At year 1 and year 2, with the replacement of a-PBVC by SDMT, 53% and 40% of patients achieved a putative NEDA-4 status, respectively.

CONCLUSION

Brain volumetric MRI has yet to be translated into clinical practice and SDMT may qualify as the fourth component of NEDA-4 definition. NEDA-4 has the potential to capture the impact of DMT therapies in RRMS earlier in the disease course of RRMS.

Brain volume loss in individuals over time: Source of variance and limits of detectability

BACKGROUND

Brain volume loss measured from magnetic resonance imaging (MRI) is a marker of neurodegeneration and predictor of disability progression in MS, and is commonly used to assess drug efficacy at the group level in clinical trials. Whether measures of brain volume loss could be useful to help guide management of individual patients depends on the relative magnitude of the changes over a given interval to physiological and technical sources of variability.

GOAL

To understand the relative contributions of neurodegeneration vs. physiological and technical sources of variability to measurements of brain volume loss in individuals.

MATERIAL AND METHODS

Multiple T1-weighted 3D MPRAGE images were acquired from a healthy volunteer and MS patient over varying time intervals: 7 times on the first day (before breakfast at 7:30AM and then every 2 ​h for 12 ​h), each day for the next 6 working days, and 6 times over the remainder of the year, on 2 ​Siemens MRI scanners: 1.5T Sonata (S1) and 3.0T TIM Trio (S2). Scan-reposition-rescan data were acquired on S2 for daily, monthly and 1-year visits. Percent brain volume change (PBVC) was measured from baseline to each follow-up scan using FSL/SIENA. We estimated the effect of physiologic fluctuations on brain volume using linear regression of the PBVC values over hourly and daily intervals. The magnitude of the physiological effect was estimated by comparing the root-mean-square error (RMSE) of the regression of all the data points relative to the regression line, for the hourly scans vs the daily scans. Variance due to technical sources was assessed as the RMSE of the regression over time using the intracranial volume as a reference.

RESULTS

The RMSE of PBVC over 12 ​h, for both scanners combined, ("Hours", 0.15%), was similar to the day-to-day variation over 1 week ("Days", 0.14%), and both were smaller than the RMS error over the year (0.21%). All of these variations, however, were smaller than the scan-reposition-rescan RMSE (0.32%). The variability of PBVC for the individual scanners followed the same trend. The standard error of the mean (SEM) for PBVC was 0.26 for S1, and 0.22 for S2. From these values, we computed the minimum detectable change (MDC) to be 0.7% on S1 and 0.6% on S2. The location of the brain along the z-axis of the magnet inversely correlated with brain volume change for hourly and daily brain volume fluctuations (p ​< ​0.01).

CONCLUSION

Consistent diurnal brain volume fluctuations attributable to physiological shifts were not detectable in this small study. Technical sources of variation dominate measured changes in brain volume in individuals until the volume loss exceeds around 0.6-0.7%. Reliable interpretation of measured brain volume changes as pathological (greater than normal aging) in individuals over 1 year requires changes in excess of about 1.1% (depending on the scanner). Reliable brain atrophy detection in an individual may be feasible if the rate of brain volume loss is large, or if the measurement interval is sufficiently long.

MAGNIMS consensus recommendations on the use of brain and spinal cord atrophy measures in clinical practice

Early evaluation of treatment response and prediction of disease evolution are key issues in the management of people with multiple sclerosis (MS). In the past 20 years, MRI has become the most useful paraclinical tool in both situations and is used clinically to assess the inflammatory component of the disease, particularly the presence and evolution of focal lesions - the pathological hallmark of MS. However, diffuse neurodegenerative processes that are at least partly independent of inflammatory mechanisms can develop early in people with MS and are closely related to disability. The effects of these neurodegenerative processes at a macroscopic level can be quantified by estimation of brain and spinal cord atrophy with MRI. MRI measurements of atrophy in MS have also been proposed as a complementary approach to lesion assessment to facilitate the prediction of clinical outcomes and to assess treatment responses. In this Consensus statement, the Magnetic Resonance Imaging in MS (MAGNIMS) study group critically review the application of brain and spinal cord atrophy in clinical practice in the management of MS, considering the role of atrophy measures in prognosis and treatment monitoring and the barriers to clinical use of these measures. On the basis of this review, the group makes consensus statements and recommendations for future research.

Time of day is associated with paradoxical reductions in global signal fluctuation and functional connectivity

The brain exhibits substantial diurnal variation in physiology and function, but neuroscience studies rarely report or consider the effects of time of day. Here, we examined variation in resting-state functional MRI (fMRI) in around 900 individuals scanned between 8 AM and 10 PM on two different days. Multiple studies across animals and humans have demonstrated that the brain’s global signal (GS) amplitude (henceforth referred to as “fluctuation”) increases with decreased arousal. Thus, in accord with known circadian variation in arousal, we hypothesised that GS fluctuation would be lowest in the morning, increase in the midafternoon, and dip in the early evening. Instead, we observed a cumulative decrease in GS fluctuation as the day progressed. Although respiratory variation also decreased with time of day, control analyses suggested that this did not account for the reduction in GS fluctuation. Finally, time of day was associated with marked decreases in resting-state functional connectivity across the whole brain. The magnitude of decrease was significantly stronger than associations between functional connectivity and behaviour (e.g., fluid intelligence). These findings reveal time of day effects on global brain activity that are not easily explained by expected arousal state or physiological artefacts. We conclude by discussing potential mechanisms for the observed diurnal variation in resting brain activity and the importance of accounting for time of day in future studies.

The brain exhibits substantial diurnal variation in physiology and function. A large-scale fMRI study reveals that the brain’s global signal amplitude, typically elevated during drowsy states, unexpectedly reduces steadily as the day progresses.

Glymphatic System Function in Relation to Anesthesia and Sleep States

The brain is one of the most metabolically active organs in the body. The brain's high energy demand associated with wakefulness persists during rapid eye movement sleep, and even during non-rapid eye movement sleep, cerebral oxygen consumption is only reduced by 20%. The active bioenergetic state parallels metabolic waste production at a higher rate than in other organs, and the lack of lymphatic vasculature in brain parenchyma is therefore a conundrum. A common assumption has been that with a tight blood-brain barrier restricting solute and fluid movements, a lymphatic system is superfluous in the central nervous system. Cerebrospinal fluid (CSF) flow has long been thought to facilitate central nervous system tissue "detoxification" in place of lymphatics. Nonetheless, while CSF production and transport have been studied for decades, the exact processes involved in toxic waste clearance remain poorly understood. Over the past 5 years, emerging data have begun to shed new light on these processes in the form of the "glymphatic system," a novel brain-wide perivascular transit passageway dedicated to CSF transport and metabolic waste drainage from the brain. Here, we review the key anatomical components and operational drivers of the brain's glymphatic system, with a focus on its unique functional dependence on the state of arousal and anesthetic regimens. We also discuss evidence for why clinical exploration of this novel system may in the future provide valuable insight into new strategies for preventing delirium and cognitive dysfunction in perioperative and critical care settings.

Fluid Flow and Mass Transport in Brain Tissue

Despite its small size, the brain consumes 25% of the body’s energy, generating its own weight in potentially toxic proteins and biological debris each year. The brain is also the only organ lacking lymph vessels to assist in removal of interstitial waste. Over the past 50 years, a picture has been developing of the brain’s unique waste removal system. Experimental observations show cerebrospinal fluid, which surrounds the brain, enters the brain along discrete pathways, crosses a barrier into the spaces between brain cells, and flushes the tissue, carrying wastes to routes exiting the brain. Dysfunction of this cerebral waste clearance system has been demonstrated in Alzheimer’s disease, traumatic brain injury, diabetes, and stroke. The activity of the system is observed to increase during sleep. In addition to waste clearance, this circuit of flow may also deliver nutrients and neurotransmitters. Here, we review the relevant literature with a focus on transport processes, especially the potential role of diffusion and advective flows.

Prospective Assessment of No Evidence of Disease Activity-4 Status in Early Disease Stages of Multiple Sclerosis in Routine Clinical Practice

Background: In relapsing-remitting multiple sclerosis, no evidence of disease activity-3 (NEDA-3) is defined as no relapses, no disability progression and no MRI activity. NEDA-4 status is defined as meeting all NEDA-3 criteria plus having an annualized brain volume loss (a-BVL) of ≤0.4%. Prospective real-world studies presenting data on NEDA-4 are scarce. Objective: To determine the proportion of patients failing to meet one or more NEDA-4 criteria and the contribution of each component to this failure. Methods: Forty-eight patients were followed for 12 months. Structural image evaluation, using normalization, of atrophy was used to assess a-BVL. Results: The patients had a mean age of 33.0 years (range 18-57), disease duration of 1.7 years (0.4-4) and Expanded Disability Status Scale score of 1.3 (0-4); 71% were women. All patients were on disease-modifying therapies. During follow-up, 21% of the patients had at least one relapse, 21% had disability progression, 8% had new T2 lesions, and 10% had gadolinium-enhanced lesions. Fifty-eight percent (28/48) achieved NEDA-3 status. a-BVL of >0.4% was observed in 52% (25/48). Only 29% (14/48) achieved NEDA-4 status. Conclusion: a-BVL is a good marker to detect subclinical disease activity. a-BVL is parameter to continue investigating for guiding clinical practice in relapsing-remitting multiple sclerosis.

Clinical correlates of longitudinal MRI changes in CADASIL

Previous studies showed that various types of cerebral lesions, as assessed on MRI, largely contribute to the clinical severity of CADASIL. However, the clinical impact of longitudinal changes of classical markers of small vessel disease on conventional MRI has been only poorly investigated. One hundred sixty NOTCH3 mutation carriers (mean age ± SD, 49.8 ± 10.9 years) were followed over three years. Validated methods were used to determine the percent brain volume change (PBVC), number of incident lacunes, change of volume of white matter hyperintensities and change of number of cerebral microbleeds. Multivariable logistic regression analyses were performed to assess the independent association between changes of these MRI markers and incident clinical events. Mixed-effect multiple linear regression analyses were used to assess their association with changes of clinical scales. Over a mean period of 3.1 ± 0.2 years, incident lacunes are found independently associated with incident stroke and change of Trail Making Test Part B. PBVC is independently associated with all incident events and clinical scale changes except the modified Rankin Scale at three years. Our results suggest that, on conventional MRI, PBVC and the number of incident lacunes are the most sensitive and independent correlates of clinical worsening over three years in CADASIL.

Altered brain structure with preserved cortical motor activity after exertional hypohydration: a MRI study

Hypohydration exceeding 2% body mass can impair endurance capacity. It is postulated that the brain could be perturbed by hypohydration, leading to impaired motor performance. We investigated the neural effects of hypohydration with magnetic resonance imaging (MRI). Ten men were dehydrated to approximately −3% body mass by running on a treadmill at 65% maximal oxygen consumption (V̇o2max) before drinking to replace either 100% [euhydration (EU)] or 0% [hypohydration (HH)] of fluid losses. MRI was performed before start of trial (baseline) and after rehydration phase (post) to evaluate brain structure, cerebral perfusion, and functional activity. Endurance capacity assessed with a time-to-exhaustion run at 75% V̇o2max was reduced with hypohydration (EU: 45.2 ± 9.3 min, HH: 38.4 ± 10.7 min; P = 0.033). Mean heart rates were comparable between trials (EU: 162 ± 5 beats/min, HH: 162 ± 4 beats/min; P = 0.605), but the rate of rise in rectal temperature was higher in HH trials (EU: 0.06 ± 0.01°C/min, HH: 0.07 ± 0.02°C/min; P < 0.01). In HH trials, a reduction in total brain volume (EU: +0.7 ± 0.6%, HH: −0.7 ± 0.9%) with expansion of ventricles (EU: −2.7 ± 1.6%, HH: +3.7 ± 3.3%) was observed, and vice versa in EU trials. Global and regional cerebral perfusion remained unchanged between conditions. Functional activation in the primary motor cortex in left hemisphere during a plantar-flexion task was similar between conditions (EU: +0.10 ± 1.30%, HH: −0.11 ± 0.31%; P = 0.637). Our findings demonstrate that with exertional hypohydration, brain volumes were altered but the motor-related functional activity was unperturbed.

NEW & NOTEWORTHY Dehydration occurs rapidly during prolonged or intensive physical activity, leading to hypohydration if fluid replenishment is insufficient to replace sweat losses. Altered hydration status poses an osmotic challenge for the brain, leading to transient fluctuations in brain tissue and ventricle volumes. Therefore, the amount of fluid ingestion during exercise plays a critical role in preserving the integrity of brain architecture. These structural changes, however, did not translate directly to motor functional deficits in a simple motor task.

Identifying predictors of within-person variance in MRI-based brain volume estimates

Adequate reliability of measurement is a precondition for investigating individual differences and age-related changes in brain structure. One approach to improve reliability is to identify and control for variables that are predictive of within-person variance. To this end, we applied both classical statistical methods and machine-learning-inspired approaches to structural magnetic resonance imaging (sMRI) data of six participants aged 24-31 years gathered at 40-50 occasions distributed over 6-8 months from the Day2day study. We explored the within-person associations between 21 variables covering physiological, affective, social, and environmental factors and global measures of brain volume estimated by VBM8 and FreeSurfer. Time since the first scan was reliably associated with Freesurfer estimates of grey matter volume and total cortex volume, in line with a rate of annual brain volume shrinkage of about 1 percent. For the same two structural measures, time of day also emerged as a reliable predictor with an estimated diurnal volume decrease of, again, about 1 percent. Furthermore, we found weak predictive evidence for the number of steps taken on the previous day and testosterone levels. The results suggest a need to control for time-of-day effects in sMRI research. In particular, we recommend that researchers interested in assessing longitudinal change in the context of intervention studies or longitudinal panels make sure that, at each measurement occasion, (a) a given participant is measured at the same time of day; (b) all participants are measured at about the same time of day. Furthermore, the potential effects of physical activity, including moderate amounts of aerobic exercise, and testosterone levels on MRI-based measures of brain structure deserve further investigation.

Finding the baby in the bath water - evidence for task-specific changes in resting state functional connectivity evoked by training

Resting-state functional connectivity (rsFC) between brain regions has been used for studying training-related changes in brain function during the offline period of skill learning. However, it is difficult to infer whether the observed training-related changes in rsFC measured between two scans occur as a consequence of task performance, whether they are specific to a given task, or whether they reflect confounding factors such as diurnal fluctuations in brain physiology that impact the MRI signal. Here, we sought to elucidate whether task-specific changes in rsFC are dissociable from time-of-day related changes by evaluating rsFC changes after participants were provided training in either a visuospatial task or a motor sequence task compared to a non-training condition. Given the nature of the tasks, we focused on changes in rsFC of the hippocampal and sensorimotor cortices after short-term training, while controlling for the effect of time-of-day. We also related the change in rsFC of task-relevant brain regions to performance improvement in each task. Our results demonstrate that, even in the absence of any experimental manipulation, significant changes in rsFC can be detected between two resting state functional MRI scans performed just a few hours apart, suggesting time-of-day has a significant impact on rsFC. However, by estimating the magnitude of the time-of-day effect, our findings also suggest that task-specific changes in rsFC can be dissociated from the changes attributed to time-of-day. Taken together, our results show that rsFC can provide insights about training-related changes in brain function during the offline period of skill learning. However, demonstrating the specificity of the changes in rsFC to a given task requires a rigorous experimental design that includes multiple active and passive control conditions, and robust behavioral measures.

Cerebral blood flow changes after a day of wake, sleep, and sleep deprivation

Elucidating the neurobiological effects of sleep and wake is an important goal of the neurosciences. Whether and how human cerebral blood flow (CBF) changes during the sleep-wake cycle remain to be clarified. Based on the synaptic homeostasis hypothesis of sleep and wake, we hypothesized that a day of wake and a night of sleep deprivation would be associated with gray matter resting CBF (rCBF) increases and that sleep would be associated with rCBF decreases. Thirty-eight healthy adult males (age 22.1 ± 2.5 years) underwent arterial spin labeling perfusion magnetic resonance imaging at three time points: in the morning after a regular night's sleep, the evening of the same day, and the next morning, either after total sleep deprivation (n = 19) or a night of sleep (n = 19). All analyses were adjusted for hematocrit and head motion. rCBF increased from morning to evening and decreased after a night of sleep. These effects were most prominent in bilateral hippocampus, amygdala, thalamus, and in the occipital and sensorimotor cortices. Group × time interaction analyses for evening versus next morning revealed significant interaction in bilateral lateral and medial occipital cortices and in bilateral insula, driven by rCBF increases in the sleep deprived individuals and decreases in the sleepers, respectively. Furthermore, group × time interaction analyses for first morning versus next morning showed significant effects in medial and lateral occipital cortices, in anterior cingulate gyrus, and in the insula, in both hemispheres. These effects were mainly driven by CBF increases from TP1 to TP3 in the sleep deprived individuals. There were no associations between the rCBF changes and sleep characteristics, vigilant attention, or subjective sleepiness that remained significant after adjustments for multiple analyses. Altogether, these results encourage future studies to clarify mechanisms underlying sleep-related rCBF changes.

Improving the SIENA performance using BEaST brain extraction

We present an improved image analysis pipeline to detect the percent brain volume change (PBVC) using SIENA (Structural Image Evaluation, using Normalization, of Atrophy) in populations with Alzheimer’s dementia. Our proposed approach uses the improved brain extraction mask from BEaST (Brain Extraction based on nonlocal Segmentation Technique) instead of the conventional BET (Brain Extraction Tool) for SIENA. We compared four varying options of BET as well as BEaST and applied these five methods to analyze scan-rescan MRIs in ADNI from 332 subjects, longitudinal ADNI MRIs from the same 332 subjects, their repeat scans over time, and OASIS longitudinal MRIs from 123 subjects. The results showed that BEaST brain masks were consistent in scan-rescan reproducibility. The cross-sectional scan-rescan error in the absolute percent brain volume difference measured by SIENA was smallest (p≤0.0187) with the proposed BEaST-SIENA. We evaluated the statistical power in terms of effect size, and the best performance was achieved with BEaST-SIENA (1.2789 for ADNI and 1.095 for OASIS). The absolute difference in PBVC between scan-dataset (volume change from baseline to year-1) and rescan-dataset (volume change from baseline repeat scan to year-1 repeat scan) was also the smallest with BEaST-SIENA compared to the BET-based SIENA and had the highest correlation when compared to the BET-based SIENA variants. In conclusion, our study shows that BEaST was robust in terms of reproducibility and consistency and that SIENA’s reproducibility and statistical power are improved in multiple datasets when used in combination with BEaST.

Magnetic Resonance Imaging in Multiple Sclerosis

Since its technical development in the early 1980s, magnetic resonance imaging (MRI) has quickly been adopted as an essential tool in supporting the diagnosis, longitudinal monitoring, evaluation of therapeutic response, and scientific investigations in multiple sclerosis (MS). The clinical usage of MRI has increased in parallel with technical innovations in the technique itself; the widespread adoption of clinically routine MRI at 1.5T has allowed sensitive qualitative and quantitative assessments of macroscopic central nervous system (CNS) inflammatory demyelinating lesions and tissue atrophy. However, conventional MRI lesion measures lack specificity for the underlying MS pathology and only weakly correlate with clinical status. Higher field strength units and newer, advanced MRI techniques offer increased sensitivity and specificity in the detection of disease activity and disease severity. This review summarizes the current status and future prospects regarding the role of MRI in the characterization of MS-related brain and spinal cord involvement.