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Stefan Ropele

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18 papers

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YNIMG Journal 2024 Journal Article

Changes in thalamic functional connectivity in post-Covid patients with and without fatigue

Manuel Leitner
Peter Opriessnig
Stefan Ropele
Reinhold Schmidt
Manuel Leal-Garcia
Maria Fellner
Marisa Koini

BACKGROUND: Functional brain alterations in post-Covid-19 condition have been minimally explored to date. Here, we investigate differences in resting-state thalamic functional connectivity among post-Covid patients with and without fatigue, alongside structural brain changes and cognition. METHODS: Thirty-nine post-Covid patients (n = 15 fatigued, n = 24 non-fatigued) participated in our study, undergoing comprehensive cognitive assessments, as well as functional and structural neuroimaging. We conducted a seed-based functional connectivity analysis using the thalamus as a seed region, exploring its connectivity with the entire brain. To further elucidate our findings, correlation analyses were performed using the functional coupling between the thalamus and regions showing different connectivity between the two patient groups. RESULTS: Our results reveal that patients experiencing fatigue exhibit anti-correlated functional coupling between the thalamus and motor-associated regions, including the motor cortex (M1), supplementary motor area (SMA), and anterior cingulate cortex (ACC), compared to non-fatigued patients, who are showing positive functional coupling. Furthermore, this observed coupling was found to correlate with both the fatigue scores obtained from a fatigue questionnaire and performance on the Trail Making Test, Part A, which represents a measure of processing speed. CONCLUSIONS: Our study highlights significant differences in resting-state functional connectivity between post-Covid patients with and without fatigue, particularly within motor-associated brain regions. These findings suggest a potential neural mechanism underlying post-Covid fatigue and underscore the importance of considering both functional and structural brain changes in understanding the symptomatic sequelae of post-Covid-19 condition. Further research is warranted to provide insight into the longitudinal trajectories of these neural alterations.

YNIMG Journal 2024 Journal Article

Fully Automated Hippocampus Segmentation using T2-informed Deep Convolutional Neural Networks

Maximilian Sackl
Christian Tinauer
Martin Urschler
Christian Enzinger
Rudolf Stollberger
Stefan Ropele

Hippocampal atrophy (tissue loss) has become a fundamental outcome parameter in clinical trials on Alzheimer's disease. To accurately estimate hippocampus volume and track its volume loss, a robust and reliable segmentation is essential. Manual hippocampus segmentation is considered the gold standard but is extensive, time-consuming, and prone to rater bias. Therefore, it is often replaced by automated programs like FreeSurfer, one of the most commonly used tools in clinical research. Recently, deep learning-based methods have also been successfully applied to hippocampus segmentation. The basis of all approaches are clinically used T1-weighted whole-brain MR images with approximately 1 mm isotropic resolution. However, such T1 images show low contrast-to-noise ratios (CNRs), particularly for many hippocampal substructures, limiting delineation reliability. To overcome these limitations, high-resolution T2-weighted scans are suggested for better visualization and delineation, as they show higher CNRs and usually allow for higher resolutions. Unfortunately, such time-consuming T2-weighted sequences are not feasible in a clinical routine. We propose an automated hippocampus segmentation pipeline leveraging deep learning with T2-weighted MR images for enhanced hippocampus segmentation of clinical T1-weighted images based on a series of 3D convolutional neural networks and a specifically acquired multi-contrast dataset. This dataset consists of corresponding pairs of T1- and high-resolution T2-weighted images, with the T2 images only used to create more accurate manual ground truth annotations and to train the segmentation network. The T2-based ground truth labels were also used to evaluate all experiments by comparing the masks visually and by various quantitative measures. We compared our approach with four established state-of-the-art hippocampus segmentation algorithms (FreeSurfer, ASHS, HippoDeep, HippMapp3r) and demonstrated a superior segmentation performance. Moreover, we found that the automated segmentation of T1-weighted images benefits from the T2-based ground truth data. In conclusion, this work showed the beneficial use of high-resolution, T2-based ground truth data for training an automated, deep learning-based hippocampus segmentation and provides the basis for a reliable estimation of hippocampal atrophy in clinical studies.

YNICL Journal 2024 Journal Article

Low-frequency MR elastography reveals altered deep gray matter viscoelasticity in multiple sclerosis

Christian Kiss
Sebastian Wurth
Bettina Heschl
Michael Khalil
Thomas Gattringer
Christian Enzinger
Stefan Ropele

INTRODUCTION: Brain viscoelasticity as assessed by magnetic resonance elastography (MRE) has been discussed as a promising surrogate of microstructural alterations due to neurodegenerative processes. Existing studies indicate that multiple sclerosis (MS) is associated with a global reduction in brain stiffness. However, no study to date systematically investigated the MS-related characteristics of brain viscoelasticity separately in normal-appearing white matter (NAWM), deep gray matter (DGM) and T2-hyperintense white matter (WM) lesions. METHODS: were reconstructed by multifrequency dual elasto-visco (MDEV) inversion and related to structural imaging and clinical parameters. RESULTS: | (p = 0.04) and φ (p = 0.004) in the thalamus of patients. No alteration in NAWM stiffness relative to WM in healthy controls was observed. CONCLUSION: Low-frequency elastography in MS patients reveals age-independent alterations in the viscoelasticity of deep gray matter at early stages of disease.

YNIMG Journal 2023 Journal Article

Super-resolution QSM in little or no additional time for imaging (NATIve) using 2D EPI imaging in 3 orthogonal planes

Beata Bachrata
Steffen Bollmann
Jin Jin
Monique Tourell
Assunta Dal-Bianco
Siegfried Trattnig
Markus Barth
Stefan Ropele

Quantitative Susceptibility Mapping has the potential to provide additional insights into neurological diseases but is typically based on a quite long (5-10 min) 3D gradient-echo scan which is highly sensitive to motion. We propose an ultra-fast acquisition based on three orthogonal (sagittal, coronal and axial) 2D simultaneous multi-slice EPI scans with 1 mm in-plane resolution and 3 mm thick slices. Images in each orientation are corrected for susceptibility-related distortions and co-registered with an iterative non-linear Minimum Deformation Averaging (Volgenmodel) approach to generate a high SNR, super-resolution data set with an isotropic resolution of close to 1 mm. The net acquisition time is 3 times the volume acquisition time of EPI or about 12 s, but the three volumes could also replace "dummy scans" in fMRI, making it feasible to acquire QSM in little or No Additional Time for Imaging (NATIve). NATIve QSM values agreed well with reference 3D GRE QSM in the basal ganglia in healthy subjects. In patients with multiple sclerosis, there was also a good agreement between the susceptibility values within lesions and control ROIs and all lesions which could be seen on 3D GRE QSMs could also be visualized on NATIve QSMs. The approach is faster than conventional 3D GRE by a factor of 25-50 and faster than 3D EPI by a factor of 3-5. As a 2D technique, NATIve QSM was shown to be much more robust to motion than the 3D GRE and 3D EPI, opening up the possibility of studying neurological diseases involving iron accumulation and demyelination in patients who find it difficult to lie still for long enough to acquire QSM data with conventional methods.

YNIMG Journal 2022 Journal Article

Free water diffusion MRI and executive function with a speed component in healthy aging

Martin Berger
Lukas Pirpamer
Edith Hofer
Stefan Ropele
Marco Duering
Benno Gesierich
Ofer Pasternak
Christian Enzinger

Extracellular free water (FW) increases are suggested to better provide pathophysiological information in brain aging than conventional biomarkers such as fractional anisotropy. The aim of the present study was to determine the relationship between conventional biomarkers, FW in white matter hyperintensities (WMH), FW in normal appearing white matter (NAWM) and in white matter tracts and executive functions (EF) with a speed component in elderly persons. We examined 226 healthy elderly participants (median age 69. 83 years, IQR: 56. 99–74. 42) who underwent brain MRI and neuropsychological examination. FW in WMH and in NAWM as well as FW corrected diffusion metrics and measures derived from conventional MRI (white matter hyperintensities, brain volume, lacunes) were used in partial correlation (adjusted for age) to assess their correlation with EF with a speed component. Random forest analysis was used to assess the relative importance of these variables as determinants. Lastly, linear regression analyses of FW in white matter tracts corrected for risk factors of cognitive and white matter deterioration, were used to examine the role of specific tracts on EF with a speed component, which were then ranked with random forest regression. Partial correlation analyses revealed that almost all imaging metrics showed a significant association with EF with a speed component (r = -0. 213 – 0. 266). Random forest regression highlighted FW in WMH and in NAWM as most important among all diffusion and structural MRI metrics. The fornix (R2=0. 421, p = 0. 018) and the corpus callosum (genu (R 2 = 0. 418, p = 0. 021), prefrontal (R 2 = 0. 416, p = 0. 026), premotor (R 2 = 0. 418, p = 0. 021)) were associated with EF with a speed component in tract based regression analyses and had highest variables importance. In a normal aging population FW in WMH and NAWM is more closely related to EF with a speed component than standard DTI and brain structural measures. Higher amounts of FW in the fornix and the frontal part of the corpus callosum leads to deteriorating EF with a speed component.

YNICL Journal 2022 Journal Article

Magnetic susceptibility anisotropy in normal appearing white matter in multiple sclerosis from single-orientation acquisition

Renat Sibgatulin
Daniel Güllmar
Andreas Deistung
Christian Enzinger
Stefan Ropele
Jürgen R. Reichenbach

Quantitative susceptibility mapping (QSM) has been successfully applied to study changes in deep grey matter nuclei as well as in lesional tissue, but its application to white matter has been complicated by the observed orientation dependence of gradient echo signal. The anisotropic susceptibility tensor is thought to be at the origin of this orientation dependence, and magnetic susceptibility anisotropy (MSA) derived from this tensor has been proposed as a marker of the state and integrity of the myelin sheath and may therefore be of particular interest for the study of demyelinating pathologies such as multiple sclerosis (MS). Reconstruction of the susceptibility tensor, however, requires repeated measurements with multiple head orientations, rendering the approach impractical for clinical applications. In this study, we combined single-orientation QSM with fibre orientation information to assess apparent MSA in three white matter tracts, i.e., optic radiation (OR), splenium of the corpus callosum (SCC), and superior longitudinal fascicle (SLF), in two cohorts of 64 healthy controls and 89 MS patients. The apparent MSA showed a significant decrease in optic radiation in the MS cohort compared with healthy controls. It decreased in the MS cohort with increasing lesion load in OR and with disease duration in the splenium. All of this suggests demyelination in normal appearing white matter. However, the apparent MSA observed in the SLF pointed to potential systematic issues that require further exploration to realize the full potential of the presented approach. Despite the limitations of such single-orientation ROI-specific estimation, we believe that our clinically feasible approach to study degenerative changes in WM is worthy of further investigation.

YNICL Journal 2022 Journal Article

Periventricular magnetisation transfer abnormalities in early multiple sclerosis

Lukas Pirpamer
Bálint Kincses
Zsigmond Tamás Kincses
Christian Kiss
Anna Damulina
Michael Khalil
Rudolf Stollberger
Reinhold Schmidt

OBJECTIVE: Recent studies suggested that CSF-mediated factors contribute to periventricular (PV) T2-hyperintense lesion formation in multiple sclerosis (MS) and this in turn correlates with cortical damage. We thus investigated if such PV-changes are observable microstructurally in early-MS and if they correlate with cortical damage. METHODS: We assessed the magnetisation transfer ratio (MTR) in PV normal-appearing white matter (NAWM) and in MS lesions in 44 patients with a clinically isolated syndrome (CIS) suggestive of MS and 73 relapsing-remitting MS (RRMS) patients. Band-wise MTR values were related to cortical mean thickness (CMT) and compared with 49 healthy controls (HCs). For each band, MTR changes were assessed relative to the average MTR values of all HCs. RESULTS: Relative to HCs, PV-MTR was significantly reduced up to 2.63% in CIS and 5.37% in RRMS (p < 0.0001). The MTR decreased towards the lateral ventricles with 0.18%/mm in CIS and 0.31%/mm in RRMS patients, relative to HCs. In RRMS, MTR-values adjacent to the ventricle and in PV-lesions correlated positively with CMT and negatively with EDSS. CONCLUSION: PV-MTR gradients are present from the earliest stage of MS, consistent with more pronounced microstructural WM-damage closer to the ventricles. The positive association between reduced CMT and lower MTR in PV-NAWM suggests a common pathophysiologic mechanism. Together, these findings indicate the potential use of multimodal MRI as refined marker for MS-related tissue changes.

YNICL Journal 2021 Journal Article

Development and evaluation of a manual segmentation protocol for deep grey matter in multiple sclerosis: Towards accelerated semi-automated references

Alexandra de Sitter
Jessica Burggraaff
Fabian Bartel
Miklos Palotai
Yaou Liu
Jorge Simoes
Serena Ruggieri
Katharina Schregel

BACKGROUND: Deep grey matter (dGM) structures, particularly the thalamus, are clinically relevant in multiple sclerosis (MS). However, segmentation of dGM in MS is challenging; labeled MS-specific reference sets are needed for objective evaluation and training of new methods. OBJECTIVES: This study aimed to (i) create a standardized protocol for manual delineations of dGM; (ii) evaluate the reliability of the protocol with multiple raters; and (iii) evaluate the accuracy of a fast-semi-automated segmentation approach (FASTSURF). METHODS: A standardized manual segmentation protocol for caudate nucleus, putamen, and thalamus was created, and applied by three raters on multi-center 3D T1-weighted MRI scans of 23 MS patients and 12 controls. Intra- and inter-rater agreement was assessed through intra-class correlation coefficient (ICC); spatial overlap through Jaccard Index (JI) and generalized conformity index (CIgen). From sparse delineations, FASTSURF reconstructed full segmentations; accuracy was assessed both volumetrically and spatially. RESULTS: All structures showed excellent agreement on expert manual outlines: intra-rater JI > 0.83; inter-rater ICC ≥ 0.76 and CIgen ≥ 0.74. FASTSURF reproduced manual references excellently, with ICC ≥ 0.97 and JI ≥ 0.92. CONCLUSIONS: The manual dGM segmentation protocol showed excellent reproducibility within and between raters. Moreover, combined with FASTSURF a reliable reference set of dGM segmentations can be produced with lower workload.

YNIMG Journal 2021 Journal Article

In vivo assessment of anisotropy of apparent magnetic susceptibility in white matter from a single orientation acquisition

Renat Sibgatulin
Daniel Güllmar
Andreas Deistung
Stefan Ropele
Jürgen R. Reichenbach

Multiple studies have reported a significant dependence of the effective transverse relaxation rate constant ( R 2 * ) and the phase of gradient-echo based (GRE) signal on the orientation of white matter fibres in the human brain. It has also been hypothesized that magnetic susceptibility, as obtained by single-orientation quantitative susceptibility mapping (QSM), exhibits such a dependence. In this study, we investigated this hypothesized relationship in a cohort of healthy volunteers. We show that R 2 * follows the predicted orientation dependence consistently across white matter regions, whereas the apparent magnetic susceptibility is related differently to fibre orientation across the brain and often in a complex non-monotonic manner. In addition, we explored the effect of fractional anisotropy measured by diffusion-weighted MRI on the strength of the orientation dependence and observed only a limited influence in many regions. However, with careful consideration of such an impact and the limitations imposed by the ill-posed nature of the dipole inversion process, it is possible to study magnetic susceptibility anisotropy in specific brain regions with a single orientation acquisition.

YNICL Journal 2021 Journal Article

Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study

Jessica Burggraaff
Yao Liu
Juan C. Prieto
Jorge Simoes
Alexandra de Sitter
Serena Ruggieri
Iman Brouwer
Birgit I. Lissenberg-Witte

BACKGROUND AND RATIONALE: Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. METHODS: Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. RESULTS: In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. CONCLUSION: Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings.

YNIMG Journal 2020 Journal Article

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

Christoph Birkl
Anna Maria Birkl-Toeglhofer
Christian Kames
Walter Goessler
Johannes Haybaeck
Franz Fazekas
Stefan Ropele
Alexander Rauscher

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.

YNIMG Journal 2017 Journal Article

Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study

Alexandra de Sitter
Martijn D. Steenwijk
Aurélie Ruet
Adriaan Versteeg
Yaou Liu
Ronald A. van Schijndel
Petra J.W. Pouwels
Iris D. Kilsdonk

Background and Purpose In vivoidentification of white matter lesions plays a key-role in evaluation of patients with multiple sclerosis (MS). Automated lesion segmentation methods have been developed to substitute manual outlining, but evidence of their performance in multi-center investigations is lacking. In this work, five research-domain automated segmentation methods were evaluated using a multi-center MS dataset. Methods 70 MS patients (median EDSS of 2. 0 [range 0. 0–6. 5]) were included from a six-center dataset of the MAGNIMS Study Group (www. magnims. eu) which included 2D FLAIR and 3D T1 images with manual lesion segmentation as a reference. Automated lesion segmentations were produced using five algorithms: Cascade; Lesion Segmentation Toolbox (LST) with both the Lesion growth algorithm (LGA) and the Lesion prediction algorithm (LPA); Lesion-Topology preserving Anatomical Segmentation (Lesion-TOADS); and k-Nearest Neighbor with Tissue Type Priors (kNN-TTP). Main software parameters were optimized using a training set (N = 18), and formal testing was performed on the remaining patients (N = 52). To evaluate volumetric agreement with the reference segmentations, intraclass correlation coefficient (ICC) as well as mean difference in lesion volumes between the automated and reference segmentations were calculated. The Similarity Index (SI), False Positive (FP) volumes and False Negative (FN) volumes were used to examine spatial agreement. All analyses were repeated using a leave-one-center-out design to exclude the center of interest from the training phase to evaluate the performance of the method on ‘unseen’ center. Results Compared to the reference mean lesion volume (4. 85 ± 7. 29 mL), the methods displayed a mean difference of 1. 60 ± 4. 83 (Cascade), 2. 31 ± 7. 66 (LGA), 0. 44 ± 4. 68 (LPA), 1. 76 ± 4. 17 (Lesion-TOADS) and −1. 39 ± 4. 10 mL (kNN-TTP). The ICCs were 0. 755, 0. 713, 0. 851, 0. 806 and 0. 723, respectively. Spatial agreement with reference segmentations was higher for LPA (SI = 0. 37 ± 0. 23), Lesion-TOADS (SI = 0. 35 ± 0. 18) and kNN-TTP (SI = 0. 44 ± 0. 14) than for Cascade (SI = 0. 26 ± 0. 17) or LGA (SI = 0. 31 ± 0. 23). All methods showed highly similar results when used on data from a center not used in software parameter optimization. Conclusion The performance of the methods in this multi-center MS dataset was moderate, but appeared to be robust even with new datasets from centers not included in training the automated methods.

YNIMG Journal 2015 Journal Article

Association between increased magnetic susceptibility of deep gray matter nuclei and decreased motor function in healthy adults

Wei Li
Christian Langkammer
Ying-hui Chou
Katja Petrovic
Reinhold Schmidt
Allen W. Song
David J. Madden
Stefan Ropele

In the human brain, iron is more prevalent in gray matter than in white matter, and deep gray matter structures, particularly the globus pallidus, putamen, caudate nucleus, substantia nigra, red nucleus, and dentate nucleus, exhibit especially high iron content. Abnormally elevated iron levels have been found in various neurodegenerative diseases. Additionally, iron overload and related neurodegeneration may also occur during aging, but the functional consequences are not clear. In this study, we explored the correlation between magnetic susceptibility — a surrogate marker of brain iron — of these gray matter structures with behavioral measures of motor and cognitive abilities, in 132 healthy adults aged 40–83years. Latent variables corresponding to manual dexterity and executive functions were obtained using factor analysis. The factor scores for manual dexterity declined significantly with increasing age. Independent of gender, age, and global cognitive function, increasing magnetic susceptibility in the globus pallidus and red nuclei was associated with decreasing manual dexterity. This finding suggests the potential value of magnetic susceptibility, a non-invasive quantitative imaging marker of iron, for the study of iron-related brain function changes.

YNIMG Journal 2015 Journal Article

Fast quantitative susceptibility mapping using 3D EPI and total generalized variation

Christian Langkammer
Kristian Bredies
Benedikt A. Poser
Markus Barth
Gernot Reishofer
Audrey Peiwen Fan
Berkin Bilgic
Franz Fazekas

Quantitative susceptibility mapping (QSM) allows new insights into tissue composition and organization by assessing its magnetic property. Previous QSM studies have already demonstrated that magnetic susceptibility is highly sensitive to myelin density and fiber orientation as well as to para- and diamagnetic trace elements. Image resolution in QSM with current approaches is limited by the long acquisition time of 3D scans and the need for high signal to noise ratio (SNR) to solve the dipole inversion problem. We here propose a new total-generalized-variation (TGV) based method for QSM reconstruction, which incorporates individual steps of phase unwrapping, background field removal and dipole inversion in a single iteration, thus yielding a robust solution to the reconstruction problem. This approach has beneficial characteristics for low SNR data, allowing for phase data to be rapidly acquired with a 3D echo planar imaging (EPI) sequence. The proposed method was evaluated with a numerical phantom and in vivo at 3 and 7T. Compared to total variation (TV), TGV–QSM enforced higher order smoothness which yielded solutions closer to the ground truth and prevented stair-casing artifacts. The acquisition time for images with 1mm isotropic resolution and whole brain coverage was 10s on a clinical 3Tesla scanner. In conclusion, 3D EPI acquisition combined with single-step TGV reconstruction yields reliable QSM images of the entire brain with 1mm isotropic resolution in seconds. The short acquisition time combined with the robust reconstruction may enable new QSM applications in less compliant populations, clinical susceptibility tensor imaging, and functional resting state examinations.

YNICL Journal 2015 Journal Article

Predictive value of different conventional and non-conventional MRI-parameters for specific domains of cognitive function in multiple sclerosis

Daniela Pinter
Michael Khalil
Alexander Pichler
Christian Langkammer
Stefan Ropele
Peter B. Marschik
Siegrid Fuchs
Franz Fazekas

OBJECTIVE: While many studies correlated cognitive function with changes in brain morphology in multiple sclerosis (MS), few of them used a multi-parametric approach in a single dataset so far. We thus here assessed the predictive value of different conventional and quantitative MRI-parameters both for overall and domain-specific cognitive performance in MS patients from a single center. METHODS: 69 patients (17 clinically isolated syndrome, 47 relapsing-remitting MS, 5 secondary-progressive MS) underwent the "Brief Repeatable Battery of Neuropsychological Tests" assessing overall cognition, cognitive efficiency and memory function as well as MRI at 3 Tesla to obtain T2-lesion load (T2-LL), normalized brain volume (global brain volume loss), normalized cortical volume (NCV), normalized thalamic volume (NTV), normalized hippocampal volume (NHV), normalized caudate nuclei volume (NCNV), basal ganglia R2* values (iron deposition) and magnetization transfer ratios (MTRs) for cortex and normal appearing brain tissue (NABT). RESULTS: Regression models including clinical, demographic variables and MRI-parameters explained 22-27% of variance of overall cognition, 17-26% of cognitive efficiency and 22-23% of memory. NCV, T2-LL and MTR of NABT were the strongest predictors of overall cognitive function. Cognitive efficiency was best predicted by NCV, T2-LL and iron deposition in the basal ganglia. NTV was the strongest predictor for memory function and NHV was particularly related to memory function. CONCLUSIONS: The predictive value of distinct MRI-parameters differs for specific domains of cognitive function, with a greater impact of cortical volume, focal and diffuse white matter abnormalities on overall cognitive function, an additional role of basal ganglia iron deposition on cognitive efficiency, and thalamic and hippocampal volume on memory function. This suggests the usefulness of using multiparametric MRI to assess (micro)structural correlates of different cognitive constructs.

YNIMG Journal 2012 Journal Article

Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study

Christian Langkammer
Ferdinand Schweser
Nikolaus Krebs
Andreas Deistung
Walter Goessler
Eva Scheurer
Karsten Sommer
Gernot Reishofer

Quantitative susceptibility mapping (QSM) is a novel technique which allows determining the bulk magnetic susceptibility distribution of tissue in vivo from gradient echo magnetic resonance phase images. It is commonly assumed that paramagnetic iron is the predominant source of susceptibility variations in gray matter as many studies have reported a reasonable correlation of magnetic susceptibility with brain iron concentrations in vivo. Instead of performing direct comparisons, however, all these studies used the putative iron concentrations reported in the hallmark study by Hallgren and Sourander (1958) for their analysis. Consequently, the extent to which QSM can serve to reliably assess brain iron levels is not yet fully clear. To provide such information we investigated the relation between bulk tissue magnetic susceptibility and brain iron concentration in unfixed (in situ) post mortem brains of 13 subjects using MRI and inductively coupled plasma mass spectrometry. A strong linear correlation between chemically determined iron concentration and bulk magnetic susceptibility was found in gray matter structures (r=0. 84, p<0. 001), whereas the correlation coefficient was much lower in white matter (r=0. 27, p<0. 001). The slope of the overall linear correlation was consistent with theoretical considerations of the magnetism of ferritin supporting that most of the iron in the brain is bound to ferritin proteins. In conclusion, iron is the dominant source of magnetic susceptibility in deep gray matter and can be assessed with QSM. In white matter regions the estimation of iron concentrations by QSM is less accurate and more complex because the counteracting contribution from diamagnetic myelinated neuronal fibers confounds the interpretation.

YNIMG Journal 2012 Journal Article

Susceptibility induced gray–white matter MRI contrast in the human brain

Christian Langkammer
Nikolaus Krebs
Walter Goessler
Eva Scheurer
Kathrin Yen
Franz Fazekas
Stefan Ropele

MR phase images have shown significantly improved contrast between cortical gray and white matter regions compared to magnitude images obtained with gradient echo sequences. A variety of underlying biophysical mechanisms (including iron, blood, myelin content, macromolecular chemical exchange, and fiber orientation) have been suggested to account for this observation but assessing the individual contribution of these factors is limited in vivo. For a closer investigation of iron and myelin induced susceptibility changes, postmortem MRI of six human corpses (age range at death: 56–80years) was acquired in situ. Following autopsy, the iron concentrations in the frontal and occipital cortex as well as in white matter regions were chemically determined. The magnetization transfer ratio (MTR) was used as an indirect measure for myelin content. Susceptibility effects were assessed separately by determining R2* relaxation rates and quantitative phase shifts. Contributions of myelin and iron to local variations of the susceptibility were assessed by univariate and multivariate linear regression analysis. Mean iron concentration was lower in the frontal cortex than in frontal white matter (26±6 vs. 45±6mg/kg wet tissue) while an inverse relation was found in the occipital lobe (cortical gray matter: 41±10 vs. white matter: 34±10mg/kg wet tissue). Multiple regression analysis revealed iron and MTR as independent predictors of the effective transverse relaxation rate R2* but solely MTR was identified as source of MR phase contrast. R2* was correlated with iron concentrations in cortical gray matter only (r=0. 42, p<0. 05). In conclusion, MR phase contrast between cortical gray and white matter can be mainly attributed to variations in myelin content, but not to iron concentration. Both, myelin and iron impact the effective transverse relaxation rate R2* significantly. Magnitude contrast is limited because it only reflects the extent but not the direction of the susceptibility shift.

YNIMG Journal 2008 Journal Article

Segmentation of age-related white matter changes in a clinical multi-center study

Tim B. Dyrby
Egill Rostrup
William F.C. Baaré
Elisabeth C.W. van Straaten
Frederik Barkhof
Hugo Vrenken
Stefan Ropele
Reinhold Schmidt

Age-related white matter changes (WMC) are thought to be a marker of vascular pathology, and have been associated with motor and cognitive deficits. In the present study, an optimized artificial neural network was used as an automatic segmentation method to produce probabilistic maps of WMC in a clinical multi-center study. The neural network uses information from T1- and T2-weighted and fluid attenuation inversion recovery (FLAIR) magnetic resonance (MR) scans, neighboring voxels and spatial location. Generalizability of the neural network was optimized by including the Optimal Brain Damage (OBD) pruning method in the training stage. Six optimized neural networks were produced to investigate the impact of different input information on WMC segmentation. The automatic segmentation method was applied to MR scans of 362 non-demented elderly subjects from 11 centers in the European multi-center study Leukoaraiosis And Disability (LADIS). Semi-manually delineated WMC were used for validating the segmentation produced by the neural networks. The neural network segmentation demonstrated high consistency between subjects and centers, making it a promising technique for large studies. For WMC volumes less than 10 ml, an increasing discrepancy between semi-manual and neural network segmentation was observed using the similarity index (SI) measure. The use of all three image modalities significantly improved cross-center generalizability compared to neural networks using the FLAIR image only. Expert knowledge not available to the neural networks was a minor source of discrepancy, while variation in MR scan quality constituted the largest source of error.