Multimodal analytical tools for the molecular and elemental characterisation of lesions in brain tissue of multiple sclerosis patients.

Multiple sclerosis (MS) is a prevalent immune-mediated inflammatory disease of the central nervous system inducing a widespread degradation of myelin and resulting in neurological deficits. Recent advances in molecular and atomic imaging provide the means to probe the microenvironment in affected brain tissues at an unprecedented level of detail and may provide new insights. This study showcases state-of-the-art spectroscopic and mass spectrometric techniques to compare distributions of molecular and atomic entities in MS lesions and surrounding brain tissues. MS brains underwent post-mortem magnetic resonance imaging (MRI) to locate and subsequently dissect MS lesions and surrounding white matter. Digests of lesions and unaffected white matter were analysed via ICP-MS/MS revealing significant differences in concentrations of Li, Mg, P, K, Mn, V, Rb, Ag, Gd and Bi. Micro x-ray fluorescence spectroscopy (µXRF) and laser ablation - inductively coupled plasma - time of flight - mass spectrometry (LA-ICP-ToF-MS) were used as micro-analytical imaging techniques to study distributions of both endogenous and xenobiotic elements. The essential trace elements Fe, Cu and Zn were subsequently calibrated using in-house manufactured gelatine standards. Lipid distributions were studied using IR-micro spectroscopy and matrix assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI). MALDI-MSI was complemented with high-resolution tandem mass spectrometry and trapped ion mobility spectroscopy for the annotation of specified phospho- and sphingolipids, revealing specific lipid species decreased in MS lesions compared to surrounding white matter. This explorative study demonstrated that modern molecular and atomic mapping techniques provide high-resolution imaging for relevant bio-indicative entities which may complement our current understanding of the underlying pathophysiological processes.

Attachment Trauma Is Associated with White Matter Fiber Microstructural Alterations in Adolescents with Anorexia Nervosa before and after Exposure to Psychotherapeutic and Nutritional Treatment.

In the present study, we explore the role of attachment for microstructural white matter (WM) changes in adolescents with anorexia nervosa (AN) before and after exposure to short-term and nutritional treatment. The case sample consisted of 22 female adolescent inpatients with AN (mean age: 15.2 ± 1.2 years) and the control sample were 18 gender-matched healthy adolescents (mean age: 16.8 ± 0.9 years). We performed a 3T MRI in the patient group during the acute state of AN and after weight restoration (duration: 2.6 ± 1 months) and compared the data to a healthy control group. To classify attachment patterns, we used the Adult Attachment Projective Picture System. In the patient sample, over 50% were classified with an attachment trauma/unresolved attachment status. Prior to treatment exposure, fractional anisotropy (FA) reductions and concordant mean diffusivity (MD) increases were evident in the fornix, the corpus callosum and WM regions of the thalamus, which normalized in the corpus callosum and the fornix post-therapy in the total patient sample (p < 0.002). In the acute state, patients with an attachment trauma demonstrated significant FA decreases compared to healthy controls, but no MD increases, in the corpus callosum and cingulum bilaterally, which remained decreased after therapy. Attachment patterns seem to be associated with region-specific changes of WM alterations in AN.

Extracellular Matrix Changes in Subcellular Brain Fractions and Cerebrospinal Fluid of Alzheimer's Disease Patients.

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 Aß1-40. Negative correlations were detected with the Aß 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.

Autolysis Affects the Iron Cargo of Ferritins in Neurons and Glial Cells at Different Rates in the Human Brain.

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 proteins involved in iron homeostasis. Here, we focus on ferritin-the primary iron storage protein of the brain. In this study, we aimed to improve a method to measure ferritin-bound iron in the human post-mortem brain, and to discern its distribution in particular cell types and brain regions. Though it is known that glial cells and neurons differ in their ferritin concentration, the change in the number and distribution of iron-filled ferritin cores 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 lose iron from their cores with the progression of autolysis whereas the overall iron concentrations were unaffected. Although the highest concentration of ferritin was found in glial cells, as the total ferritin concentration increased in a patient, ferritin accumulated more in neurons than in glial cells. Summed up, 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 manner in the human brain. The rate of loss of the iron-filled ferritin cores during autolysis is higher in neurons than in glial cells.

The Effects of Wearing a 3-Ply or KN95 Face Mask on Cerebral Blood Flow and Oxygenation.

BACKGROUND: 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. PURPOSE: This study investigated whether wearing a face mask leads to changes in CBF and cerebral venous oxygen saturation measured with MRI. STUDY TYPE: Repeated-measures cohort study. POPULATION: 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. FIELD STRENGTH/SEQUENCE: 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. ASSESSMENT: Gray matter CBF and magnetic susceptibility were assessed by masking the pCASL CBF map and the QSM map to the T1 -weighted gray matter tissue segmentation. Venous oxygenation was determined from venous segmentation of QSM maximum intensity projections. STATISTICAL TESTS: Paired 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. RESULTS: 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). DATA CONCLUSION: The changes in blood flow and oxygenation due to face masks are small. Only CBF increased significantly due to wearing a 3-ply mask. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Technical note: Quantitative optimization of the FLAIR sequence in post mortem magnetic resonance imaging.

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 (TInull). However, the FLAIR sequence is impaired by the temperature dependency of TInull in post mortem MRI due to the lower body temperature of the deceased subject. Therefore, the temperature correction of TInull is crucial for correctly suppressing the CSF signal in post mortem FLAIR imaging. Thus, the goal of this study was to determine the temperature effect on post mortem TInull for achieving a robust suppression of the CSF signal in in situ post mortem MRI using the FLAIR sequence. For this purpose, nine deceased subjects underwent an in situ MRI brain examination on a 3 T MRI scanner. TInull of CSF was determined quantitatively based on different FLAIR acquisitions using varying inversion times. The brain and rectal temperatures were determined prior to the MRI scan. A significant positive linear relation was found between TInull of CSF and the brain temperature, as well as between TInull of CSF and the rectal temperature. The found linear relations between TInull and both brain and rectal temperatures allow correcting TInull for varying temperatures of the deceased. This in turn enables an optimal suppression of the CSF signal in future post mortem FLAIR MRI acquisitions.

Orientation dependence of R2 relaxation in the newborn brain.

In MRI the transverse relaxation rate, R2 = 1/T2, shows dependence on the orientation of ordered tissue relative to the main magnetic field. In previous studies, orientation effects of R2 relaxation in the mature brain's white matter have been found to be described by a susceptibility-based model of diffusion through local magnetic field inhomogeneities created by the diamagnetic myelin sheaths. Orientation effects in human newborn white matter have not yet been investigated. The newborn brain is known to contain very little myelin and is therefore expected to exhibit a decrease in orientation dependence driven by susceptibility-based effects. We measured R2 orientation dependence in the white matter of human newborns. R2 data were acquired with a 3D Gradient and Spin Echo (GRASE) sequence and fiber orientation was mapped with diffusion tensor imaging (DTI). We found orientation dependence in newborn white matter that is not consistent with the susceptibility-based model and is best described by a model of residual dipolar coupling. In the near absence of myelin in the newborn brain, these findings suggest the presence of residual dipolar coupling between rotationally restricted water molecules. This has important implications for quantitative imaging methods such as myelin water imaging, and suggests orientation dependence of R2 as a potential marker in early brain development.

Revisiting brain iron deficiency in restless legs syndrome using magnetic resonance imaging.

STUDY OBJECTIVES: Studies on brain iron content in restless legs syndrome (RLS) using magnetic resonance imaging (MRI) are heterogeneous. In this study, we sought to leverage the availability of a large dataset including a range of iron-sensitive MRI techniques to reassess the association between brain iron content and RLS with added statistical power and to compare these results to previous studies. METHODS: The relaxation rates R2, R2', and R2* and quantitative susceptibility are MRI parameters strongly correlated to iron content. In general, these parameters are sensitive to magnetic field variations caused by iron particles. These parameters were quantified within iron-rich brain regions using a fully automatized approach in a cohort of 72 RLS patients and individually age and gender-matched healthy controls identified from an existing dataset acquired at the Sleep Laboratory of the Department of Neurology, Medical University of Innsbruck. 3 T-MRI measures were corrected for age and volume of the segmented brain nuclei and results were compared with previous findings in a meta-analysis. RESULTS: In our cohort, RLS patients had increased R2* signal in the caudate and increased quantitative susceptibility signal in the putamen and the red nucleus compared to controls, suggesting increased iron content in these areas. The meta-analysis revealed no significant pooled effect across all brain regions. Furthermore, potential publication bias was identified for the substantia nigra. CONCLUSIONS: Normal and increased iron content of subcortical brain areas detected in this study is not in line with the hypothesis of reduced brain iron storage, but favors CSF investigations and post mortem studies indicating alteration of brain iron mobilization and homeostasis in RLS.

HFP-QSMGAN: QSM from homodyne-filtered phase images.

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: Accurate prediction of susceptibility can be achieved from filtered SWI phase using convolutional neural networks.

High-resolution neural network-driven mapping of multiple diffusion metrics leveraging asymmetries in the balanced steady-state free precession frequency profile.

We propose to utilize the rich information content about microstructural tissue properties entangled in asymmetric balanced steady-state free precession (bSSFP) profiles to estimate multiple diffusion metrics simultaneously by neural network (NN) parameter quantification. A 12-point bSSFP phase-cycling scheme with high-resolution whole-brain coverage is employed at 3 and 9.4 T for NN input. Low-resolution target diffusion data are derived based on diffusion-weighted spin-echo echo-planar-imaging (SE-EPI) scans, that is, mean, axial, and radial diffusivity (MD, AD, and RD), fractional anisotropy (FA), as well as the spherical coordinates (azimuth Φ and inclination Ï´) of the principal diffusion eigenvector. A feedforward NN is trained with incorporated probabilistic uncertainty estimation. The NN predictions yielded highly reliable results in white matter (WM) and gray matter structures for MD. The quantification of FA, AD, and RD was overall in good agreement with the reference but the dependence of these parameters on WM anisotropy was somewhat biased (e.g. in corpus callosum). The inclination Ï´ was well predicted for anisotropic WM structures, while the azimuth Φ was overall poorly predicted. The findings were highly consistent across both field strengths. Application of the optimized NN to high-resolution input data provided whole-brain maps with rich structural details. In conclusion, the proposed NN-driven approach showed potential to provide distortion-free high-resolution whole-brain maps of multiple diffusion metrics at high to ultrahigh field strengths in clinically relevant scan times.

Recovering SWI-filtered phase data using deep learning.

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.

Phosphorous Magnetic Resonance Spectroscopy and Molecular Markers in IDH1 Wild Type Glioblastoma.

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.

Automated segmentation of deep brain nuclei using convolutional neural networks and susceptibility weighted imaging.

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.

Sensitivity of fiber orientation dependent R2∗ to temperature and post mortem interval.

PURPOSE: R2∗ 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 R2∗ 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. R2∗ 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 R2∗ was performed using three different formulations of a previously proposed model. RESULTS: R2∗ 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 R2∗ components significantly decreased with decreasing temperature, while the orientation independent R2∗ 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 R2∗ components with temperature, the decreased R2∗ fiber orientation dependency post mortem in situ might primarily be attributed to the lower brain temperature.

Myelin water imaging depends on white matter fiber orientation in the human brain.

PURPOSE: The multi-exponential T2 decay of the MRI signal from cerebral white matter can be separated into short T2 components related to myelin water and long T2 components related to intracellular and extracellular water. In this study, we investigated to what degree the apparent myelin water fraction (MWF) depends on the angle between white matter fibers and the main magnetic field. METHODS: Maps of the apparent MWF were acquired using multi-echo Carr-Purcell-Meiboom-Gill and gradient-echo spin-echo sequences. The Carr-Purcell-Meiboom-Gill sequence was acquired with a TR of 1073 ms, 1500 ms, and 2000 ms. The fiber orientation was mapped with DTI. By angle-wise pooling the voxels across the brain's white matter, orientation-dependent apparent MWF curves were generated. RESULTS: We found that the apparent MWF varied between 25% and 35% across different fiber orientations. Furthermore, the selection of the TR influences the apparent MWF. CONCLUSION: White matter fiber orientation induces a strong systematic bias on the estimation of the apparent MWF. This finding has implications for future research and the interpretation of MWI results in previously published studies.

The influence of iron oxidation state on quantitative MRI parameters in post mortem human 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.

Correction: Hepatic gene expression explains primary drug toxicity in bipolar disorder.

The original Article had an incomplete acknowledgements list. The following sentence has now been added to the HTML and PDF versions of this Article: "This study was performed within the framework of the PhD program Molecular Medicine of the Medical University of Graz. This work was supported by the Medical University of Graz within the Open Access Publishing Funding Program."

Hepatic gene expression explains primary drug toxicity in bipolar disorder.

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.

The influence of brain iron on myelin water imaging.

With myelin playing a vital role in normal brain integrity and function and thus in various neurological disorders, myelin sensitive magnetic resonance imaging (MRI) techniques are of great importance. In particular, multi-exponential T2 relaxation was shown to be highly sensitive to myelin. The myelin water imaging (MWI) technique allows to separate the T2 decay into short components, specific to myelin water, and long components reflecting the intra- and extracellular water. The myelin water fraction (MWF) is the ratio of the short components to all components. In the brain's white matter (WM), myelin and iron are closely linked via the presence of iron in the myelin generating oligodendrocytes. Iron is known to decrease T2 relaxation times and may therefore mimic myelin. In this study, we investigated if variations in WM iron content can lead to apparent MWF changes. We performed MWI in post mortem human brain tissue prior and after chemical iron extraction. Histology for iron and myelin confirmed a decrease in iron content and no change in myelin content after iron extraction. In MRI, iron extraction lead to a decrease in MWF by 26%-28% in WM. Thus, a change in MWF does not necessarily reflect a change in myelin content. This observation has important implications for the interpretation of MWI findings in previously published studies and future research.

The role of iron and myelin in orientation dependent R2* of white matter.

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.