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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.

Detailed pathophysiological mechanisms causing migraine are still elusive, however, there is evidence that iron metabolization might play a role. Studies using R2 (=1/T2) or R2* (=1/T2*) relaxometry, a common magnetic resonance imaging (MRI) based iron mapping technique, reported increased R2 and R2* values in various brain structures of patients with migraine, indicating an iron accumulation compared to healthy controls. The aim of this first-of-its-kind study was to investigate if there are alterations in R2* in the brain caused by the migraine cycle. Therefore, quantitative MRI, including R2* relaxometry and diffusion tensor imaging (DTI) of a patient with migraine was acquired on 21 consecutive days, comprising headache free days and days with a migraine attack. Combining R2* with DTI, allowed to separate isotropic and anisotropic R2* contributions in white matter. A significant difference in R2* between left and right hemisphere was found in the nucleus accumbens (p = 0.02), the amygdala (p < 0.001) and the pallidum (p < 0.001). During a migraine attack, R2* decreased in the amygdala of the left hemisphere by 13.9% (p = 0.01) and in the nucleus accumbens of the right hemisphere by 7.8% (p = 0.01). In contrast, R2* increased in the caudate of the left hemisphere by 5.3% (p = 0.01). In white matter, isotropic R2* increased by approximately 1.9% (p = 0.04) and anisotropic R2* decreased by approximately 30% (p = 0.02) during a migraine attack. Our study revealed a decrease and increase in iron content in various brain regions during the migraine cycle. Furthermore, white mater iron content increased accompanied by a decrease in anisotropic tissue components during a migraine attack. The observed alterations in R2* indicate that the iron content fluctuates over time depending on the migraine phase. However, the altered iron content reaches normal levels after the migraine attack resolved.

Iron is known to accumulate in neurological disorders, so a careful balance of the iron concentration is essential for healthy brain functioning. An imbalance in iron homeostasis could arise due to the dysfunction of the proteins involved in iron homeostasis. Here, we focus on ferritin – the primary iron storage protein of the brain. Though it is known that glial cells and neurons differ in their concentration of ferritin, the change in the number of iron-filled ferritin cores or their distribution between different cell types during autolysis has not been revealed yet. Here, we show the cellular and region-wide distribution of ferritin in the human brain using state-of-the-art analytical electron microscopy. We validated the concentration of iron-filled ferritin cores to the absolute iron concentration measured by quantitative MRI and inductively coupled plasma mass spectrometry. We show that ferritins lost iron from their cores with progressing autolysis whereas the overall iron concentrations were unaffected. Though the highest concentration of ferritins was found in glial cells, we found that as the total ferritin concentration increased in a patient, ferritin accumulated more in neurons than in glial cells. Collectively our findings point out the unique behaviour of neurons in storing iron during autolysis and explain the differences between the absolute iron concentrations and iron-filled ferritin in a cell-type-dependent fashion in the human brain.Significance statementBalance of the iron load of the brain is crucial to preventing neurodegenerative disorders. Our study establishes a relation between autolysis, iron, and ferritin in the human brain with emphasis on the role of different cells in ferritin storage. We demonstrate that the iron load of ferritins does not correlate with mean iron concentrations during autolysis. Neurons retain more iron-loaded ferritin than glial cells with increasing ferritin count, which may make neurons more susceptible and exacerbate neuronal loss during iron overload. Neurons are also depleted of iron-loaded ferritin cores faster than glial cells during autolysis, demonstrating their unique role in iron storage. This paves the way to understanding the respective roles of neurons and glial cells in preventing or promoting neurodegeneration.

The brain’s extracellular matrix (ECM) is assumed to undergo rearrangements in Alzheimer’s disease (AD). Here, we investigated changes of key components of the hyaluronan-based ECM in independent samples of post-mortem brains (N = 19), cerebrospinal fluids (CSF; N = 70), and RNAseq data (N = 107; from The Aging, Dementia and TBI Study) of AD patients and non-demented controls. Group comparisons and correlation analyses of major ECM components in soluble and synaptosomal fractions from frontal, temporal cortex, and hippocampus of control, low-grade, and high-grade AD brains revealed a reduction in brevican in temporal cortex soluble and frontal cortex synaptosomal fractions in AD. In contrast, neurocan, aggrecan and the link protein HAPLN1 were up-regulated in soluble cortical fractions. In comparison, RNAseq data showed no correlation between aggrecan and brevican expression levels and Braak or CERAD stages, but for hippocampal expression of HAPLN1, neurocan and the brevican-interaction partner tenascin-R negative correlations with Braak stages were detected. CSF levels of brevican and neurocan in patients positively correlated with age, total tau, p-Tau, neurofilament-L and Aβ1-40. Negative correlations were detected with the Aβ ratio and the IgG index. Altogether, our study reveals spatially segregated molecular rearrangements of the ECM in AD brains at RNA or protein levels, which may contribute to the pathogenic process.

Purpose R 2 ∗ imaging of brain white matter is well known for being sensitive to the orientation of nerve fibers with respect to the B0 field of the MRI scanner. The goal of this study was to evaluate whether and to which extent fiber orientation dependent R 2 ∗ differs between in vivo and post mortem in situ examinations, and to investigate the influence of varying temperatures and post mortem intervals (PMI). Methods Post mortem in situ and in vivo MRI scans were conducted at 3T. R 2 ∗ was acquired with a multi-echo gradient-echo sequence, and the orientation of white matter fibers was computed using diffusion tensor imaging (DTI). Fitting of the measured fiber orientation dependent R 2 ∗ was performed using three different formulations of a previously proposed model. Results R 2 ∗ increased with increasing fiber angle for in vivo and post mortem in situ examinations, whereby the orientation dependency was lower post mortem. The different formulations of the fiber orientation model resulted in an identical fit, but showed large variations of the estimated parameters. The higher order orientation dependent R 2 ∗ components significantly decreased with decreasing temperature, while the orientation independent R 2 ∗ components showed no significant correlation with either temperature or PMI. Conclusion Although the mean diffusivity is strongly reduced post mortem, we could successfully estimate the fiber angle using DTI. Due to the strong correlation of the higher order orientation dependent R 2 ∗ components with temperature, the decreased R 2 ∗ fiber orientation dependency post mortem in situ might primarily be attributed to the lower brain temperature.

Homodyne filtering is a standard preprocessing step in the estimation of SWI. Unfortunately, SWI is not quantitative, and QSM cannot be accurately estimated from filtered phase images. Compared with gradient-echo sequences suitable for computing QSM, SWI is more readily available and is often the only susceptibility-sensitive sequence acquired in the clinical setting. In this project, we aimed to quantify susceptibility from the homodyne-filtered phase (HFP), acquired for computing susceptibility-weighted images, using convolutional neural networks to solve the compounded problem of (1) computing the solution to the inverse dipole problem, and (2) compensating for the effects of the homodyne filtering.Two convolutional neural networks, the U-Net and a modified QSMGAN architecture (HFP-QSMGAN), were trained to predict QSM maps at different TEs from HFP images. The QSM maps were quantified from a gradient-echo sequence acquired in the same individuals using total generalized variation (TGV)-QSM. The QSM maps estimated directly from the HFP were also included for comparison. Voxel-wise predictions and, importantly, regional predictions of susceptibility with adjustment to a reference region, were compared.Our results indicate that the U-Net model provides more accurate voxel-wise predictions of susceptibility compared with HFP-QSMGAN and HFP-QSM. However, regional estimates of susceptibility predicted by HFP-QSMGAN are more strongly correlated with the values from TGV-QSM compared with those of U-Net and HFP-QSM.Accurate prediction of susceptibility can be achieved from filtered SWI phase using convolutional neural networks.

The fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) sequence aims at suppressing the signal of the cerebrospinal fluid (CSF) by acquiring images at the time point at which the longitudinal magnetization and therefore the signal of CSF is zero. This time point is also called the null point inversion time (TI

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.

Simple Summary Gliobastoma is one of the deadliest tumors overall, yet the most common malignant brain tumor. The new World Health Organization Classification of Brain Tumors brought changes in how we look at this type of malignancy. Now we know that glioblastoma is rather a spectrum of similar tumors, but with some distinct characteristics that include molecular footprint, response to therapy and with that overall survival, among others. We hypothesised that by employing phosphorous magnetic resonance we will be able to show differences in cellular energy metabolism in these various subtypes of glioblastoma. For example, we found indices of faster cell reproduction and tumor growth in MGMT-methylated and EGFR-amplified tumors. These tumors also could have reduced energetic state or tissue oxygenation due to the increased necrosis. Tumors with EGFR-amplification could have increased apoptotic activity regardless of their MGMT status. Our study indicated various differences in energetic metabolism in tumors with different molecular characteristics, which could potentially be important in future therapeutic strategies. Abstract The World Health Organisation’s (WHO) classification of brain tumors requires consideration of both histological appearance and molecular characteristics. Possible differences in brain energy metabolism could be important in designing future therapeutic strategies. Forty-three patients with primary, isocitrate dehydrogenase 1 (IDH1) wild type glioblastomas (GBMs) were included in this study. Pre-operative standard MRI was obtained with additional phosphorous magnetic resonance spectroscopy (31-P-MRS) imaging. Following microsurgical resection of the tumors, biopsy specimens underwent neuropathological diagnostics including standard molecular diagnosis. The spectroscopy results were correlated with epidermal growth factor (EGFR) and O6-Methylguanine-DNA methyltransferase (MGMT) status. EGFR amplified tumors had significantly lower phosphocreatine (PCr) to adenosine triphosphate (ATP)-PCr/ATP and PCr to inorganic phosphate (Pi)-PCr/Pi ratios, and higher Pi/ATP and phosphomonoesters (PME) to phosphodiesters (PDE)-PME/PDE ratio than those without the amplification. Patients with MGMT-methylated tumors had significantly higher cerebral magnesium (Mg) values and PME/PDE ratio, while their PCr/ATP and PCr/Pi ratios were lower than in patients without the methylation. In survival analysis, not-EGFR-amplified, MGMT-methylated GBMs showed the longest survival. This group had lower PCr/Pi ratio when compared to MGMT-methylated, EGFR-amplified group. PCr/Pi ratio was lower also when compared to the MGMT-unmethylated, EGFR not-amplified group, while PCr/ATP ratio was lower than all other examined groups. Differences in energy metabolism in various molecular subtypes of wild-type-GBMs could be important information in future precision medicine approach.

The advent of susceptibility-sensitive MRI techniques, such as susceptibility weighted imaging (SWI), has enabled accurate in vivo visualization and quantification of iron deposition within the human brain. Although previous approaches have been introduced to segment iron-rich brain regions, such as the substantia nigra, subthalamic nucleus, red nucleus, and dentate nucleus, these methods are largely unavailable and manual annotation remains the most used approach to label these regions. Furthermore, given their recent success in outperforming other segmentation approaches, convolutional neural networks (CNN) promise better performances. The aim of this study was thus to evaluate state-of-the-art CNN architectures for the labeling of deep brain nuclei from SW images. We implemented five CNN architectures and considered ensembles of these models. Furthermore, a multi-atlas segmentation model was included to provide a comparison not based on CNN. We evaluated two prediction strategies: individual prediction, where a model is trained independently for each region, and combined prediction, which simultaneously predicts multiple closely located regions. In the training dataset, all models performed with high accuracy with Dice coefficients ranging from 0.80 to 0.95. The regional SWI intensities and volumes from the models' labels were strongly correlated with those obtained from manual labels. Performances were reduced on the external dataset, but were higher or comparable to the intrarater reliability and most models achieved significantly better results compared to multi-atlas segmentation. CNNs can accurately capture the individual variability of deep brain nuclei and represent a highly useful tool for their segmentation from SW images.

Post mortem in situ and in vivo MRI scans were conducted at 3T.Although the mean diffusivity is strongly reduced post mortem, we could successfully estimate the fiber angle using DTI. Due to the strong correlation of the higher order orientation dependent

The multiexponential T2 decay of the magnetic resonance imaging (MRI) signal from cerebral white matter can be separated into short components sensitive to myelin water and long components related to intra- and extracellular water. In this study we investigated to what degree the myelin water fraction (MWF) depends on the angle between white matter fibers and the main magnetic filed. Maps of MWF were acquired using multi echo CPMG and GRASE sequences. The CPMG sequence was acquired with a TR of 1073 ms, 1500 ms and 2000 ms. The fiber orientation was mapped with diffusion tensor imaging. By angle-wise pooling the voxels across the brain’s white matter, an orientation dependent MWF curve was generated. We found that MWF varied between 25% and 35% across different fiber orientations. The orientation dependency of the MWF is characterized by a dipole-dipole interaction model. Furthermore, the selection of the TR influences the orientation dependent and global white matter MWF. White matter fiber orientation induces a strong systematic bias on the estimation of MWF. This finding has important implications for future research and the interpretation of MWI results in previously published studies.

Purpose Current MRI techniques cannot reliably assess iron content in white matter due to the confounding diamagnetic effect of myelin. The purpose of this study was to validate with histology a novel iron mapping technique that uses the temperature dependency of the paramagnetic susceptibility in multiple sclerosis (MS) brains, where white matter has been reported to show significant variations in iron content. Methods We investigated post mortem brain tissue from three MS patients and one control subject. Temperature-dependent R2* relaxometry was performed between 4°C and 37°C. The resulting temperature coefficient ( TcR2*) maps were compared with immunohistochemical stains for ferritin light chain. Results Good agreement between TcR2* maps and ferritin staining was found by way of visual comparison and quantitative analysis. The highest iron concentrations were detected at the edge of MS lesions and in the basal ganglia. For all regions, except the subcortical U-fibers, there was a significant negative correlation between the TcR2* values and the ferritin count. Conclusion This study provides further evidence that TcR2* may be a reliable measure of white matter iron content due to the elimination of myelin-induced susceptibility changes and is well suited for further research into neurological diseases with distortions of the iron homeostasis. Magn Reson Med 79:1609-1615, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Purpose Formalin fixation prevents tissue autolysis by crosslinking proteins and changes tissue microstructure and MRI signal characteristics. Previous studies showed high variations in MR relaxation time constants of formalin fixed brain tissue, which has been attributed to the use of different formalin concentrations. Our investigations confirmed the influence of formalin concentration on relaxation times and unexpectedly revealed an influence of vendor specific formalin composition, which has not been investigated so far. Methods We systematically analyzed relaxation times of human brain tissue fixed with 4% and 10% formalin compared with unfixed condition at 3 Tesla MRI. Furthermore, we assessed relaxation times of nine formalin solutions from different vendors and performed comparisons of their magnetic susceptibility by SQUID (superconducting quantum interference device) magnetometry. Results Tissue relaxation times decreased approximately twice as fast using 10% than in 4% formalin fixation. The vendor specific composition of the formalin solutions and concentration dependent paramagnetic effects showed a substantial contribution to differences in relaxation times of formalin. Conclusion Our study demonstrates that differences of the formalin composition have substantial effects on MRI signal characteristics after fixation, which can explain the divergence of reported relaxation times beyond the effect of differences in formalin concentration. Magn Reson Med 79:1111-1115, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

In bipolar disorder (BPD), long-term psychotropic drug treatment is often necessary to prevent relapse or recurrence. Nevertheless, adverse drug effects including disturbances in hepatic metabolism are observed and still poorly understood. Here, the association between hepatic gene expression and histopathological changes of the liver was investigated. By the use of microarrays (Affymetrix U133 plus2.0), a genome-wide expression study was performed on BPD patients with psychotropic drug treatment (n = 29) compared to unaffected controls (n = 20) and validated by quantitative real-time PCR. WebGestalt was used to identify over-represented functional pathways of the Reactome database. Association analyses between histopathological changes and differentially expressed genes comprised in the over-represented functional pathways were performed using regression analyses, from which feature-expression heatmaps were drawn. The majority of identified genes were underexpressed and involved in energy supply, metabolism of lipids and proteins, and the innate immune system. Positive associations were found for genes involved in all pathways and degenerative changes. The strongest negative association was observed between genes involved in energy supply and hepatic activity, as well as inflammation. In summary, we found a possible association between gene expression involved in various biological pathways and histopathological changes of the liver in BPD. Further, we found support for the probable primary toxic effect of psychotropic drugs on hepatic injury in BPD. Even if the safety of psychotropic drugs improves, adverse effects especially on hepatic function should not be underestimated.

Brain myelin and iron content are important parameters in neurodegenerative diseases such as multiple sclerosis (MS). Both myelin and iron content influence the brain's R2 * relaxation rate. However, their quantification based on R2 * maps requires a realistic tissue model that can be fitted to the measured data. In structures with low myelin content, such as deep gray matter, R2 * shows a linear increase with increasing iron content. In white matter, R2 * is not only affected by iron and myelin but also by the orientation of the myelinated axons with respect to the external magnetic field. Here, we propose a numerical model which incorporates iron and myelin, as well as fibre orientation, to simulate R2 * decay in white matter. Applying our model to fibre orientation-dependent in vivo R2 * data, we are able to determine a unique solution of myelin and iron content in global white matter. We determine an averaged myelin volume fraction of 16.02 ± 2.07% in non-lesional white matter of patients with MS, 17.32 ± 2.20% in matched healthy controls, and 18.19 ± 2.98% in healthy siblings of patients with MS. Averaged iron content was 35.6 ± 8.9 mg/kg tissue in patients, 43.1 ± 8.3 mg/kg in controls, and 47.8 ± 8.2 mg/kg in siblings. All differences in iron content between groups were significant, while the difference in myelin content between MS patients and the siblings of MS patients was significant. In conclusion, we demonstrate that a model that combines myelin-induced orientation-dependent and iron-induced orientation-independent components is able to fit in vivo R2 * data.

Investigations of the ultrastructural features of neurons and their synapses are only possible with electron microscopy. Especially for comparative studies of the changes in densities and distributions of such features, an unbiased sampling protocol is vital for reliable results. Here, we present a workflow for the image acquisition of brain samples. The workflow allows systematic uniform random sampling within a defined brain region, and the images can be analyzed using a disector. This technique is much faster than extensive examination of serial sections but still presents a feasible approach to estimate the densities and distributions of ultrastructure features. Before embedding, stained vibratome sections were used as a reference to identify the brain region under investigation, which helped speed up the overall specimen preparation process. This approach was used for comparative studies investigating the effect of an enriched-housing environment on several ultrastructural parameters in the mouse brain. Based on the successful use of the workflow, we adapted it for the purpose of elemental analysis of brain samples. We optimized the protocol in terms of the time of user-interaction. Automating all the time-consuming steps by compiling a script for the open source software SerialEM helps the user to focus on the main work of acquiring the elemental maps. As in the original workflow, we paid attention to the unbiased sampling approach to guarantee reliable results.

This study explored whether autoregulatory shifts in cerebral blood volume induce susceptibility changes large enough to be depicted by quantitative susceptibility mapping. Eight healthy subjects underwent fast quantitative susceptibility mapping at 3T while lying down to slowly decrease mean arterial pressure. A linear relationship between mean arterial pressure and susceptibility was observed in cortical and subcortical structures, likely representing vessels involved in autoregulation. The slope of this relationship is assumed to indicate the extent of cerebral vascular compliance.

Post-mortem MRI of the brain is increasingly applied in neuroscience for a better understanding of the contrast mechanisms of disease induced tissue changes. However, the influence of chemical processes caused by formalin fixation and differences in temperature may hamper the comparability with results from in vivo MRI. In this study we investigated how formalin fixation and temperature affect T1, T2 and T2* relaxation times of brain tissue. Fixation effects were examined with respect to changes in water content and crosslinking. Relaxometry was performed in brain slices from five deceased subjects at different temperatures. All measurements were repeated after 190 days of formaldehyde immersion. The water content of unfixed and fixed tissue was determined using the wet-to-dry ratio following drying. Protein weight was determined with sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Fixation caused a strong decrease of all relaxation times, the strongest effect being seen on T1, with a reduction of up to 76%. The temperature coefficient of T1 was lower in the fixed than unfixed tissue, which was in contrast to T2, where an increase of the temperature coefficient was observed following fixation. The reduction of the water content after fixation was in the range of 1-6% and thus not sufficient to explain the changes in relaxation time. Results from SDS-PAGE indicated a strong increase of the protein size above 260 kDa in all brain structures examined. Our results suggest that crosslinking induced changes of the macromolecular matrix are responsible for T1 shortening and a decreased temperature dependency. The relaxation times provided in this work should allow optimization of post-mortem MRI protocols for the brain.

A variety of Magnetic Resonance Imaging (MRI) techniques are known to be sensitive to brain iron content. In principle, iron sensitive MRI techniques are based on local magnetic field variations caused by iron particles in tissue. The purpose of this study was to investigate the sensitivity of MR relaxation and magnetization transfer parameters to changes in iron oxidation state compared to changes in iron concentration. Therefore, quantitative MRI parameters including R1, R2, R2∗, quantitative susceptibility maps (QSM) and magnetization transfer ratio (MTR) of post mortem human brain tissue were acquired prior and after chemical iron reduction to change the iron oxidation state and chemical iron extraction to decrease the total iron concentration. All assessed parameters were shown to be sensitive to changes in iron concentration whereas only R2, R2∗ and QSM were also sensitive to changes in iron oxidation state. Mass spectrometry confirmed that iron accumulated in the extraction solution but not in the reduction solution. R2∗ and QSM are often used as markers for iron content. Changes in these parameters do not necessarily reflect variations in iron content but may also be a result of changes in the iron’s oxygenation state from ferric towards more ferrous iron or vice versa.

Background: The month-of-birth-effect (MoBE) describes the finding that multiple sclerosis (MS) patients seem to have been born significantly more frequently in spring, with a rise in May, and significantly less often in autumn and winter with the fewest births in November. Objectives: To analyse if the MoBE can also be found in the Austrian MS population, and if so, whether the pattern is similar to the reported pattern in Canada, United Kingdom, and some Scandinavian countries. Methods: The data of 7886 MS patients in Austria were compared to all live births in Austria from 1940 to 2010, that is, 7.256545 data entries of the Austrian birth registry and analysed in detail. Results: Patterns observed in our MS cohort were not different from patterns in the general population, even when stratifying for gender. However, the noticeable and partly significant ups and downs over the examined years did not follow the distinct specific pattern with highest birth rates in spring and lowest birth rates in autumn that has been described previously for countries above the 49th latitude. Conclusion: After correcting for month-of-birth patterns in the general Austrian population, there is no evidence for the previously described MoBE in Austrian MS patients.

Brain myelin and iron content are important parameters in neurodegenerative diseases such as multiple sclerosis (MS). Both myelin and iron content influence the brain's R

Current MRI techniques cannot reliably assess iron content in white matter due to the confounding diamagnetic effect of myelin. The purpose of this study was to validate with histology a novel iron mapping technique that uses the temperature dependency of the paramagnetic susceptibility in multiple sclerosis (MS) brains, where white matter has been reported to show significant variations in iron content.We investigated post mortem brain tissue from three MS patients and one control subject. Temperature-dependent R2* relaxometry was performed between 4°C and 37°C. The resulting temperature coefficient ( TcR2*) maps were compared with immunohistochemical stains for ferritin light chain.Good agreement between TcR2* maps and ferritin staining was found by way of visual comparison and quantitative analysis. The highest iron concentrations were detected at the edge of MS lesions and in the basal ganglia. For all regions, except the subcortical U-fibers, there was a significant negative correlation between the TcR2* values and the ferritin count.This study provides further evidence that TcR2* may be a reliable measure of white matter iron content due to the elimination of myelin-induced susceptibility changes and is well suited for further research into neurological diseases with distortions of the iron homeostasis. Magn Reson Med 79:1609-1615, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Formalin fixation prevents tissue autolysis by crosslinking proteins and changes tissue microstructure and MRI signal characteristics. Previous studies showed high variations in MR relaxation time constants of formalin fixed brain tissue, which has been attributed to the use of different formalin concentrations. Our investigations confirmed the influence of formalin concentration on relaxation times and unexpectedly revealed an influence of vendor specific formalin composition, which has not been investigated so far.We systematically analyzed relaxation times of human brain tissue fixed with 4% and 10% formalin compared with unfixed condition at 3 Tesla MRI. Furthermore, we assessed relaxation times of nine formalin solutions from different vendors and performed comparisons of their magnetic susceptibility by SQUID (superconducting quantum interference device) magnetometry.Tissue relaxation times decreased approximately twice as fast using 10% than in 4% formalin fixation. The vendor specific composition of the formalin solutions and concentration dependent paramagnetic effects showed a substantial contribution to differences in relaxation times of formalin.Our study demonstrates that differences of the formalin composition have substantial effects on MRI signal characteristics after fixation, which can explain the divergence of reported relaxation times beyond the effect of differences in formalin concentration. Magn Reson Med 79:1111-1115, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Purpose The assessment of iron content in brain white matter (WM) is of high importance for studying neurodegenerative diseases. While R2* mapping and quantitative susceptibility mapping is suitable for iron mapping in gray matter, iron mapping in WM still remains an unsolved problem. We propose a new approach for iron mapping, independent of diamagnetic contributions of myelin by assessing the temperature dependency of the paramagnetic susceptibility. Theory and Methods We used unfixed human brain slices for relaxometry and calculated R2′ as a measure for microscopic susceptibility variations at several temperatures (4°C–37°C) at 3 Tesla. The temperature coefficient of R2′ (TcR2p) was calculated by linear regression and related to the iron concentration found by subsequent superconducting quantum interference device (SQUID) magnetometry and by inductively coupled plasma mass spectrometry. Results In line with SQUID measurements, R2′ mapping showed a linear temperature dependency of the bulk susceptibility with the highest slope in gray matter. Even in WM, TcR2p yielded a high linear correlation with the absolute iron concentration. Conclusion According to Curie's law, only paramagnetic matter exhibits a temperature dependency while the diamagnetism shows no effect. We have demonstrated that the temperature coefficient (TcR2p) can be used as a measure of the paramagnetic susceptibility despite of an unknown diamagnetic background. Magn Reson Med 73:1282–1288, 2015. © 2014 Wiley Periodicals, Inc.

Purpose Magnetic resonance relaxation times of most tissues are expected to depend on temperature, which can impact findings in postmortem magnetic resonance imaging or when using magnetic resonance imaging for relaxation-based thermometry. The purpose of this study was to investigate the exact temperature dependency of the relaxation times T1, T2, T2*, and the magnetization transfer ratio in different structures of the human brain. Methods To prevent fixation and autolysis effects, this study was performed with fresh postmortem brain tissues. Following autopsy, coronal brain slices from five deceased subjects were subjected to relaxometry at 3T in a temperature range between 4°C and 37°C. Heating of the tissue was achieved by flushing the vacuum packed brain slices with water at a predefined temperature. Results T1 showed a linear dependency on temperature with the highest temperature coefficient in the cortex (17.4 ms/°C) and the lowest in the white matter (3.4 ms/°C). T2 did not depend on temperature. T2* and magnetization transfer ratio scaled with temperature only in deep gray matter. Conclusion The temperature coefficient for T1 is higher than expected from previous reports and varies across brain structures. The coefficients obtained in this study can serve as reference for thermometry or for correcting quantitative postmortem magnetic resonance imaging. Magn Reson Med 71:1575–1580, 2014. © 2013 Wiley Periodicals, Inc.

Post-mortem MRI of the brain is increasingly applied in neuroscience for a better understanding of the contrast mechanisms of disease induced tissue changes. However, the influence of chemical processes caused by formalin fixation and differences in temperature may hamper the comparability with results from in vivo MRI. In this study we investigated how formalin fixation and temperature affect T1, T2 and T2* relaxation times of brain tissue. Fixation effects were examined with respect to changes in water content and crosslinking. Relaxometry was performed in brain slices from five deceased subjects at different temperatures. All measurements were repeated after 190 days of formaldehyde immersion. The water content of unfixed and fixed tissue was determined using the wet-to-dry ratio following drying. Protein weight was determined with sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Fixation caused a strong decrease of all relaxation times, the strongest effect being seen on T1, with a reduction of up to 76%. The temperature coefficient of T1 was lower in the fixed than unfixed tissue, which was in contrast to T2, where an increase of the temperature coefficient was observed following fixation. The reduction of the water content after fixation was in the range of 1-6% and thus not sufficient to explain the changes in relaxation time. Results from SDS-PAGE indicated a strong increase of the protein size above 260 kDa in all brain structures examined. Our results suggest that crosslinking induced changes of the macromolecular matrix are responsible for T1 shortening and a decreased temperature dependency. The relaxation times provided in this work should allow optimization of post-mortem MRI protocols for the brain.

The assessment of iron content in brain white matter (WM) is of high importance for studying neurodegenerative diseases. While R2 * mapping and quantitative susceptibility mapping is suitable for iron mapping in gray matter, iron mapping in WM still remains an unsolved problem. We propose a new approach for iron mapping, independent of diamagnetic contributions of myelin by assessing the temperature dependency of the paramagnetic susceptibility.We used unfixed human brain slices for relaxometry and calculated R2 ' as a measure for microscopic susceptibility variations at several temperatures (4°C-37°C) at 3 Tesla. The temperature coefficient of R2 ' (TcR2p) was calculated by linear regression and related to the iron concentration found by subsequent superconducting quantum interference device (SQUID) magnetometry and by inductively coupled plasma mass spectrometry.In line with SQUID measurements, R2 ' mapping showed a linear temperature dependency of the bulk susceptibility with the highest slope in gray matter. Even in WM, TcR2p yielded a high linear correlation with the absolute iron concentration.According to Curie's law, only paramagnetic matter exhibits a temperature dependency while the diamagnetism shows no effect. We have demonstrated that the temperature coefficient (TcR2p) can be used as a measure of the paramagnetic susceptibility despite of an unknown diamagnetic background.

MR relaxation times of most tissues are ex- pected to depend on temperature which can impact find- ings in post mortem MRI or MRI based thermometry. The purpose of this study was to investigate the exact tem- perature dependency of the T1 relaxation in different structures in unfixed and fixed human brain samples. Following autopsy, coronal brain slices from five de- ceased subjects underwent MRI at 3T in a temperature range between 4°C and 37°C. T1 showed a linear depend- ency on temperature with the highest temperature coeffi- cient in the cortex (17 ms/°C) and the lowest in the white matter (3ms/°C). The fixation of the tissue lowered T1 and additionally the temperature coefficient in all regions investigated. The temperature coefficients obtained in this study serve as reference for thermometry and for correct- ing quantitative post mortem MRI.

Magnetic resonance relaxation times of most tissues are expected to depend on temperature, which can impact findings in postmortem magnetic resonance imaging or when using magnetic resonance imaging for relaxation-based thermometry. The purpose of this study was to investigate the exact temperature dependency of the relaxation times T(1), T(2), T(2) *, and the magnetization transfer ratio in different structures of the human brain.To prevent fixation and autolysis effects, this study was performed with fresh postmortem brain tissues. Following autopsy, coronal brain slices from five deceased subjects were subjected to relaxometry at 3T in a temperature range between 4°C and 37°C. Heating of the tissue was achieved by flushing the vacuum packed brain slices with water at a predefined temperature.T1 showed a linear dependency on temperature with the highest temperature coefficient in the cortex (17.4 ms/°C) and the lowest in the white matter (3.4 ms/°C). T(2) did not depend on temperature. T(2) * and magnetization transfer ratio scaled with temperature only in deep gray matter.The temperature coefficient for T(1) is higher than expected from previous reports and varies across brain structures. The coefficients obtained in this study can serve as reference for thermometry or for correcting quantitative postmortem magnetic resonance imaging.