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Oxidative Stress Markers in Cerebrospinal Fluid of Newly Diagnosed Multiple Sclerosis Patients and Their Link to Iron Deposition and Atrophy. Diagnostics (Basel) 2022; 12:diagnostics12061365. [PMID: 35741175 PMCID: PMC9221788 DOI: 10.3390/diagnostics12061365] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 05/30/2022] [Accepted: 05/30/2022] [Indexed: 02/04/2023] Open
Abstract
Oxidative stress has been implied in cellular injury even in the early phases of multiple sclerosis (MS). In this study, we quantified levels of biomarkers of oxidative stress and antioxidant capacity in cerebrospinal fluid (CSF) in newly diagnosed MS patients and their associations with brain atrophy and iron deposits in the brain tissue. Consecutive treatment-naive adult MS patients (n = 103) underwent brain MRI and CSF sampling. Healthy controls (HC, n = 99) had brain MRI. CSF controls (n = 45) consisted of patients with non-neuroinflammatory conditions. 3T MR included isotropic T1 weighted (MPRAGE) and gradient echo (GRE) images that were processed to quantitative susceptibility maps. The volume and magnetic susceptibility of deep gray matter (DGM) structures were calculated. The levels of 8-hydroxy-2′-deoxyguanosine (8-OHdG), 8-iso prostaglandin F2α (8-isoPG), neutrophil gelatinase-associated lipocalin (NGAL), peroxiredoxin-2 (PRDX2), and malondialdehyde and hydroxyalkenals (MDA + HAE) were measured in CSF. Compared to controls, MS patients had lower volumes of thalamus, pulvinar, and putamen, higher susceptibility in caudate nucleus and globus pallidus, and higher levels of 8-OHdG, PRDX2, and MDA + HAE. In MS patients, the level of NGAL correlated negatively with volume and susceptibility in the dentate nucleus. The level of 8-OHdG correlated negatively with susceptibility in the caudate, putamen, and the red nucleus. The level of PRDX2 correlated negatively with the volume of the thalamus and both with volume and susceptibility of the dentate nucleus. From MRI parameters with significant differences between MS and HC groups, only caudate susceptibility and thalamic volume were significantly associated with CSF parameters. Our study shows that increased oxidative stress in CSF detected in newly diagnosed MS patients suggests its role in the pathogenesis of MS.
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152
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Wang C, Martins-Bach AB, Alfaro-Almagro F, Douaud G, Klein JC, Llera A, Fiscone C, Bowtell R, Elliott LT, Smith SM, Tendler BC, Miller KL. Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging. Nat Neurosci 2022; 25:818-831. [PMID: 35606419 PMCID: PMC9174052 DOI: 10.1038/s41593-022-01074-w] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 04/11/2022] [Indexed: 12/17/2022]
Abstract
A key aim in epidemiological neuroscience is identification of markers to assess brain health and monitor therapeutic interventions. Quantitative susceptibility mapping (QSM) is an emerging magnetic resonance imaging technique that measures tissue magnetic susceptibility and has been shown to detect pathological changes in tissue iron, myelin and calcification. We present an open resource of QSM-based imaging measures of multiple brain structures in 35,273 individuals from the UK Biobank prospective epidemiological study. We identify statistically significant associations of 251 phenotypes with magnetic susceptibility that include body iron, disease, diet and alcohol consumption. Genome-wide associations relate magnetic susceptibility to 76 replicating clusters of genetic variants with biological functions involving iron, calcium, myelin and extracellular matrix. These patterns of associations include relationships that are unique to QSM, in particular being complementary to T2* signal decay time measures. These new imaging phenotypes are being integrated into the core UK Biobank measures provided to researchers worldwide, creating the potential to discover new, non-invasive markers of brain health.
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Affiliation(s)
- Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Aurea B Martins-Bach
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Gwenaëlle Douaud
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Alberto Llera
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, the Netherlands
| | - Cristiana Fiscone
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Lloyd T Elliott
- Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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153
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Sibgatulin R, Güllmar D, Deistung A, Enzinger C, Ropele S, Reichenbach JR. Magnetic susceptibility anisotropy in normal appearing white matter in multiple sclerosis from single-orientation acquisition. Neuroimage Clin 2022; 35:103059. [PMID: 35661471 PMCID: PMC9163587 DOI: 10.1016/j.nicl.2022.103059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 05/02/2022] [Accepted: 05/21/2022] [Indexed: 11/19/2022]
Abstract
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.
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Affiliation(s)
- Renat Sibgatulin
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Philosophenweg 3, 07743 Jena, Germany
| | - Daniel Güllmar
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Philosophenweg 3, 07743 Jena, Germany
| | - Andreas Deistung
- University Clinic and Outpatient Clinic for Radiology, Department for Radiation Medicine, University Hospital Halle (Saale), Ernst-Grube-Str. 40, 06120 Halle (Saale), Germany
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036 Graz, Austria
| | - Jürgen R Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Philosophenweg 3, 07743 Jena, Germany; Michael Stifel Center Jena for Data-Driven and Simulation Science, Friedrich-Schiller-University Jena, Jena, Germany
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154
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Brain Iron and Mental Health Symptoms in Youth with and without Prenatal Alcohol Exposure. Nutrients 2022; 14:nu14112213. [PMID: 35684012 PMCID: PMC9183007 DOI: 10.3390/nu14112213] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 05/18/2022] [Accepted: 05/19/2022] [Indexed: 12/18/2022] Open
Abstract
Prenatal alcohol exposure (PAE) negatively affects brain development and increases the risk of poor mental health. We investigated if brain volumes or magnetic susceptibility, an indirect measure of brain iron, were associated with internalizing or externalizing symptoms in youth with and without PAE. T1-weighted and quantitative susceptibility mapping (QSM) MRI scans were collected for 19 PAE and 40 unexposed participants aged 7.5–15 years. Magnetic susceptibility and volume of basal ganglia and limbic structures were extracted using FreeSurfer. Internalizing and Externalizing Problems were assessed using the Behavioural Assessment System for Children (BASC-2-PRS). Susceptibility in the nucleus accumbens was negatively associated with Internalizing Problems, while amygdala susceptibility was positively associated with Internalizing Problems across groups. PAE moderated the relationship between thalamus susceptibility and internalizing symptoms as well as the relationship between putamen susceptibility and externalizing symptoms. Brain volume was not related to internalizing or externalizing symptoms. These findings highlight that brain iron is related to internalizing and externalizing symptoms differently in some brain regions for youth with and without PAE. Atypical iron levels (high or low) may indicate mental health issues across individuals, and iron in the thalamus may be particularly important for behavior in individuals with PAE.
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155
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Beliveau V, Stefani A, Birkl C, Kremser C, Gizewski ER, Högl B, Scherfler C. Revisiting brain iron deficiency in restless legs syndrome using magnetic resonance imaging. Neuroimage Clin 2022; 34:103024. [PMID: 35500370 PMCID: PMC9065426 DOI: 10.1016/j.nicl.2022.103024] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 04/07/2022] [Accepted: 04/24/2022] [Indexed: 12/19/2022]
Abstract
Increased iron in RLS was found in the caudate, putamen and red nucleus. A meta-analysis revealed no significant evidence of reduced iron in RLS as assessed by MRI. Evidence suggestive of publication bias for results on the substantia nigra was found. Our results support the view that brain iron mobilization or homeostasis is impaired in RLS.
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.
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Affiliation(s)
- Vincent Beliveau
- Medical University of Innsbruck, Department of Neurology, Innsbruck, Austria; Medical University of Innsbruck, Neuroimaging Research Core Facility, Innsbruck, Austria
| | - Ambra Stefani
- Medical University of Innsbruck, Department of Neurology, Innsbruck, Austria
| | - Christoph Birkl
- Medical University of Innsbruck, Department of Neuroradiology, Innsbruck, Austria
| | - Christian Kremser
- Medical University of Innsbruck, Department of Radiology, Innsbruck, Austria
| | - Elke R Gizewski
- Medical University of Innsbruck, Department of Neuroradiology, Innsbruck, Austria; Medical University of Innsbruck, Department of Radiology, Innsbruck, Austria
| | - Birgit Högl
- Medical University of Innsbruck, Department of Neurology, Innsbruck, Austria
| | - Christoph Scherfler
- Medical University of Innsbruck, Department of Neurology, Innsbruck, Austria; Medical University of Innsbruck, Neuroimaging Research Core Facility, Innsbruck, Austria.
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156
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Lancione M, Cencini M, Costagli M, Donatelli G, Tosetti M, Giannini G, Zangaglia R, Calandra-Buonaura G, Pacchetti C, Cortelli P, Cosottini M. Diagnostic accuracy of quantitative susceptibility mapping in multiple system atrophy: The impact of echo time and the potential of histogram analysis. Neuroimage Clin 2022; 34:102989. [PMID: 35303599 PMCID: PMC8927993 DOI: 10.1016/j.nicl.2022.102989] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/25/2022] [Accepted: 03/10/2022] [Indexed: 11/07/2022]
Abstract
We performed histogram analysis on χ maps at different TEs on MSA patients and HC. We found altered χ distribution in Pu, SN, GP, CN for MSAp and in SN, DN for MSAc. QSM diagnostic accuracy is TE-dependent and is enhanced at short TEs. Short TEs capture rapidly-decaying contributions of high χ sources. Histogram features detect χ spatial heterogeneities improving diagnostic accuracy.
The non-invasive quantification of iron stores via Quantitative Susceptibility Mapping (QSM) could play an important role in the diagnosis and the differential diagnosis of atypical Parkinsonisms. However, the susceptibility (χ) values measured via QSM depend on echo time (TE). This effect relates to the microstructural organization within the voxel, whose composition can be altered by the disease. Moreover, pathological iron deposition in a brain area may not be spatially uniform, and conventional Region of Interest (ROI)-based analysis may fail in detecting alterations. Therefore, in this work we evaluated the impact of echo time on the diagnostic accuracy of QSM on a population of patients with Multiple System Atrophy (MSA) of either Parkinsonian (MSAp) or cerebellar (MSAc) phenotypes. In addition, we tested the potential of histogram analysis to improve QSM classification accuracy. We enrolled 32 patients (19 MSAp and 13 MSAc) and 16 healthy controls, who underwent a 7T MRI session including a gradient-recalled multi-echo sequence for χ mapping. Nine histogram features were extracted from the χ maps computed for each TE in atlas-based ROIs covering deep brain nuclei, and compared among groups. Alterations of susceptibility distribution were found in the Putamen, Substantia Nigra, Globus Pallidus and Caudate Nucleus for MSAp and in the Substantia Nigra and Dentate Nucleus for MSAc. Increased iron deposition was observed in a larger number of ROIs for the two shortest TEs and the standard deviation, the 75th and the 90th percentile were the most informative features yielding excellent diagnostic accuracy with area under the ROC curve > 0.9. In conclusion, short TEs may enhance QSM diagnostic performances, as they can capture variations in rapidly-decaying contributions of high χ sources. The analysis of histogram features allowed to reveal fine heterogeneities in the spatial distribution of susceptibility alteration, otherwise undetected by a simple evaluation of ROI χ mean values.
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Affiliation(s)
- Marta Lancione
- IRCCS Stella Maris, Pisa, Italy; IMAGO7 Foundation, Pisa, Italy
| | - Matteo Cencini
- IRCCS Stella Maris, Pisa, Italy; IMAGO7 Foundation, Pisa, Italy
| | - Mauro Costagli
- IRCCS Stella Maris, Pisa, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genova, Genova, Italy.
| | - Graziella Donatelli
- IMAGO7 Foundation, Pisa, Italy; Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
| | - Michela Tosetti
- IRCCS Stella Maris, Pisa, Italy; IMAGO7 Foundation, Pisa, Italy
| | - Giulia Giannini
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Roberta Zangaglia
- Parkinson and Movement Disorder Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Giovanna Calandra-Buonaura
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Claudio Pacchetti
- Parkinson and Movement Disorder Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Pietro Cortelli
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy; IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
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157
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Jang J, Kang J, Nam Y. [Brain Iron Imaging in Aging and Cognitive Disorders: MRI Approaches]. TAEHAN YONGSANG UIHAKHOE CHI 2022; 83:527-537. [PMID: 36238502 PMCID: PMC9514519 DOI: 10.3348/jksr.2022.0038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/09/2022] [Accepted: 05/16/2022] [Indexed: 11/23/2022]
Abstract
Iron has a vital role in the human body, including the central nervous system. Increased deposition of iron in the brain has been reported in aging and important neurodegenerative diseases. Owing to the unique magnetic resonance properties of iron, MRI has great potential for in vivo assessment of iron deposition, distribution, and non-invasive quantification. In this paper, we will review the MRI methods for iron assessment and their changes in aging and neurodegenerative diseases, focusing on Alzheimer's disease. In addition, we will summarize the limitations of current approaches and introduce new areas and MRI methods for iron imaging that are expected in the future.
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158
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Motor Band Sign in Motor Neuron Disease: A Marker for Upper Motor Neuron Involvement. Can J Neurol Sci 2022; 50:373-379. [PMID: 35477836 DOI: 10.1017/cjn.2022.52] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND AND OBJECTIVE The prevalence and role of the motor band sign (MBS) remain unclear in motor neuron disease. We report the frequency of MBS in amyotrophic lateral sclerosis (ALS) and primary lateral sclerosis (PLS), its correlation with clinical upper motor neuron (UMN) signs, and prognostic value in ALS. METHODS We conducted a retrospective study of ALS, PLS, and controls with retrievable MRI between 2010 and 2018. We compared the frequencies of MBS across the three groups, and studied correlation between susceptibility-weighted MRI measurements in primary motor cortices and contralateral UMN features. Clinical outcomes were compared between ALS with and without MBS. RESULTS Thirteen ALS, 5 PLS, and 10 controls were included (median age 60 years, IQR 54-66 years; 14/28 males). MBS was present in 9/13 (69.2%, 95% CI 38.9-89.6%) and 4/5 (80.0%, 95% CI 29.9-99.0%) of ALS and PLS, respectively, and none in controls. 2/13 (15.4%, 95% CI 2.7-46.3%) ALS and 3/5 (60.0%, 95% CI 17.0-92.7%) PLS had MBS in the absence of corticospinal T2/FLAIR hyperintensity sign. Susceptibility measurements in left motor cortices had a significantly positive correlation with contralateral UMN signs in ALS (τb = 0.628, p = 0.03). Similar but nonsignificant trends was observed for right motor cortices in ALS (τb = 0.516, p = 0.07). There were no significant differences in mRS at last follow-up, mortality, or time from symptom onset to last follow-up between ALS patients with and without MBS. CONCLUSIONS We provide limited evidence that MBS and susceptibility quantification measurements in motor cortices may serve as surrogate markers of UMN involvement in motor neuron disease.
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159
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Gustavsson J, Papenberg G, Falahati F, Laukka EJ, Kalpouzos G. Contributions of the Catechol-O-Methyltransferase Val158Met Polymorphism to Changes in Brain Iron Across Adulthood and Their Relationships to Working Memory. Front Hum Neurosci 2022; 16:838228. [PMID: 35571998 PMCID: PMC9091601 DOI: 10.3389/fnhum.2022.838228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 03/16/2022] [Indexed: 11/13/2022] Open
Abstract
Ageing is associated with excessive free brain iron, which may induce oxidative stress and neuroinflammation, likely causing cognitive deficits. Lack of dopamine may be a factor behind the increase of iron with advancing age, as it has an important role in cellular iron homoeostasis. We investigated the effect of COMT Val 158 Met (rs4680), a polymorphism crucial for dopamine degradation and proxy for endogenous dopamine, on iron accumulation and working memory in a longitudinal lifespan sample (n = 208, age 20–79 at baseline, mean follow-up time = 2.75 years) using structural equation modelling. Approximation of iron content was assessed using quantitative susceptibility mapping in striatum and dorsolateral prefrontal cortex (DLPFC). Iron accumulated in both striatum and DLPFC during the follow-up period. Greater iron accumulation in DLPFC was associated with more deleterious change in working memory. Older (age 50–79) Val homozygotes (with presumably lower endogenous dopamine) accumulated more iron than older Met carriers in both striatum and DLPFC, no such differences were observed among younger adults (age 20–49). In conclusion, individual differences in genetic predisposition related to low dopamine levels increase iron accumulation, which in turn may trigger deleterious change in working memory. Future studies are needed to better understand how dopamine may modulate iron accumulation across the human lifespan.
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Affiliation(s)
- Jonatan Gustavsson
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- *Correspondence: Jonatan Gustavsson,
| | - Goran Papenberg
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Farshad Falahati
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Erika J. Laukka
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Stockholm Gerontology Research Center, Stockholm, Sweden
| | - Grégoria Kalpouzos
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Grégoria Kalpouzos,
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160
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Mao H, Dou W, Chen K, Wang X, Wang X, Guo Y, Zhang C. Evaluating iron deposition in gray matter nuclei of patients with unilateral middle cerebral artery stenosis using quantitative susceptibility mapping. Neuroimage Clin 2022; 34:103021. [PMID: 35500369 PMCID: PMC9065429 DOI: 10.1016/j.nicl.2022.103021] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 03/17/2022] [Accepted: 04/23/2022] [Indexed: 11/18/2022]
Abstract
Iron mediated oxidative stress is involved in the process of brain injury after long-term ischemia. While increased iron deposition in the affected brain regions was observed in animal models of ischemic stroke, potential changes in the brain iron content in clinical patients with cerebral ischemia remain unclear. Quantitative susceptibility mapping (QSM), a non-invasive magnetic resonance imaging technique, can be used to evaluate iron content in the gray matter (GM) nuclei reliably. In this study, we aimed to quantitatively evaluate iron content changes in GM nuclei of patients with long-term unilateral middle cerebral artery (MCA) stenosis/occlusion-related cerebral ischemia using QSM. Forty-six unilateral MCA stenosis/occlusion patients and 38 age-, sex- and education-matched healthy controls underwent QSM. Clinical variables of history of hypertension, diabetes, hyperlipidemia, hyperhomocysteinemia, smoking, and drinking in all patients were evaluated. The iron-related susceptibility of GM nucleus subregions, including the bilateral caudate nucleus (CN), putamen (PU), globus pallidus (GP), thalamus, substantia nigra (SN), red nucleus, and dentate nucleus, was assessed. Susceptibility was compared between the bilateral GM nuclei in patients and controls. Receiver operating characteristic curve analysis was used to evaluate the efficacy of QSM susceptibility in distinguishing patients with unilateral MCA stenosis/occlusion from healthy controls. Multiple linear regression analysis was used to evaluate the relationship between ipsilateral susceptibility levels and clinical variables. Except for the CN, the susceptibility in most bilateral GM nucleus subregions was comparable in healthy controls, whereas for patients with unilateral MCA stenosis/occlusion, the ipsilateral PU, GP, and SN exhibited significantly higher susceptibility than the contralateral side (all P < 0.05). Compared with controls, susceptibility of the ipsilateral PU, GP, and SN and of contralateral PU in patients were significantly increased (all P < 0.05). The area under the curve (AUC) was greater for the ipsilateral PU than for the GP and SN (AUC = 0.773, 0.662 and 0.681; all P < 0.05). Multiple linear regression analysis showed that the increased susceptibility of the ipsilateral PU was significantly associated with hypertension, of the ipsilateral GP associated with smoking, and of the ipsilateral SN associated with diabetes (all P < 0.05). Our findings provide support for abnormal iron accumulation in the GM nuclei after chronic MCA stenosis/occlusion and its correlation with some cerebrovascular disease risk factors. Therefore, iron deposition in the GM nuclei, as measured by QSM, may be a potential biomarker for long-term cerebral ischemia.
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Affiliation(s)
- Huimin Mao
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Weiqiang Dou
- MR Research, GE Healthcare, Beijing 10076, China
| | - Kunjian Chen
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Xinyu Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Xinyi Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China.
| | - Yu Guo
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China; Shandong First Medical University, Jinan, Shandong Province 250000, China
| | - Chao Zhang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong Province 250014, China
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161
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Lambert M, Tejos C, Langkammer C, Milovic C. Hybrid data fidelity term approach for quantitative susceptibility mapping. Magn Reson Med 2022; 88:962-972. [PMID: 35435267 PMCID: PMC9324845 DOI: 10.1002/mrm.29218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 01/28/2022] [Accepted: 02/16/2022] [Indexed: 11/06/2022]
Abstract
Purpose Methods Results Conclusions
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Affiliation(s)
- Mathias Lambert
- Department of Electrical Engineering Pontificia Universidad Catolica de Chile Santiago Chile
- Biomedical Imaging Center Pontificia Universidad Catolica de Chile Santiago Chile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH) Santiago Chile
| | - Cristian Tejos
- Department of Electrical Engineering Pontificia Universidad Catolica de Chile Santiago Chile
- Biomedical Imaging Center Pontificia Universidad Catolica de Chile Santiago Chile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH) Santiago Chile
| | - Christian Langkammer
- Department of Neurology Medical University of Graz Graz Austria
- BioTechMed Graz Graz Austria
| | - Carlos Milovic
- Department of Electrical Engineering Pontificia Universidad Catolica de Chile Santiago Chile
- Biomedical Imaging Center Pontificia Universidad Catolica de Chile Santiago Chile
- Department of Medical Physics and Biomedical Engineering University College London London UK
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162
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Nikparast F, Ganji Z, Danesh Doust M, Faraji R, Zare H. Brain pathological changes during neurodegenerative diseases and their identification methods: How does QSM perform in detecting this process? Insights Imaging 2022; 13:74. [PMID: 35416533 PMCID: PMC9008086 DOI: 10.1186/s13244-022-01207-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 03/13/2022] [Indexed: 12/14/2022] Open
Abstract
The presence of iron is essential for many biological processes in the body. But sometimes, for various reasons, the amount of iron deposition in different areas of the brain increases, which leads to problems related to the nervous system. Quantitative susceptibility mapping (QSM) is one of the newest magnetic resonance imaging (MRI)-based methods for assessing iron accumulation in target areas. This Narrative Review article aims to evaluate the performance of QSM compared to other methods of assessing iron deposition in the clinical field. Based on the results, we introduced related basic definitions, some neurodegenerative diseases, methods of examining iron deposition in these diseases, and their advantages and disadvantages. This article states that the QSM method can be introduced as a new, reliable, and non-invasive technique for clinical evaluations.
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Affiliation(s)
- Farzaneh Nikparast
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Zohreh Ganji
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Mohammad Danesh Doust
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Reyhane Faraji
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hoda Zare
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. .,Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
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163
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The “Coherent Data Set”: Combining Patient Data and Imaging in a Comprehensive, Synthetic Health Record. ELECTRONICS 2022. [DOI: 10.3390/electronics11081199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
The “Coherent Data Set” is a novel synthetic data set that leverages structured data from Synthea™ to create a longitudinal, “coherent” patient-level electronic health record (EHR). Comprised of synthetic patients, the Coherent Data Set is publicly available, reproducible using Synthea™, and free of the privacy risks that arise from using real patient data. The Coherent Data Set provides complex and representative health records that can be leveraged by health IT professionals without the risks associated with de-identified patient data. It includes familial genomes that were created through a simulation of the genetic reproduction process; magnetic resonance imaging (MRI) DICOM files created with a voxel-based computational model; clinical notes in the style of traditional subjective, objective, assessment, and plan notes; and physiological data that leverage existing System Biology Markup Language (SBML) models to capture non-linear changes in patient health metrics. HL7 Fast Healthcare Interoperability Resources (FHIR®) links the data together. The models can generate clinically logical health data, but ensuring clinical validity remains a challenge without comparable data to substantiate results. We believe this data set is the first of its kind and a novel contribution to practical health interoperability efforts.
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164
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Jung W, Bollmann S, Lee J. Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities. NMR IN BIOMEDICINE 2022; 35:e4292. [PMID: 32207195 DOI: 10.1002/nbm.4292] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 02/04/2020] [Accepted: 02/25/2020] [Indexed: 06/10/2023]
Abstract
Quantitative susceptibility mapping (QSM) has gained broad interest in the field by extracting bulk tissue magnetic susceptibility, predominantly determined by myelin, iron and calcium from magnetic resonance imaging (MRI) phase measurements in vivo. Thereby, QSM can reveal pathological changes of these key components in a variety of diseases. QSM requires multiple processing steps such as phase unwrapping, background field removal and field-to-source inversion. Current state-of-the-art techniques utilize iterative optimization procedures to solve the inversion and background field correction, which are computationally expensive and require a careful choice of regularization parameters. With the recent success of deep learning using convolutional neural networks for solving ill-posed reconstruction problems, the QSM community also adapted these techniques and demonstrated that the QSM processing steps can be solved by efficient feed forward multiplications not requiring either iterative optimization or the choice of regularization parameters. Here, we review the current status of deep learning-based approaches for processing QSM, highlighting limitations and potential pitfalls, and discuss the future directions the field may take to exploit the latest advances in deep learning for QSM.
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Affiliation(s)
- Woojin Jung
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea
| | - Steffen Bollmann
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Australia
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea
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165
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Onukwufor JO, Dirksen RT, Wojtovich AP. Iron Dysregulation in Mitochondrial Dysfunction and Alzheimer’s Disease. Antioxidants (Basel) 2022; 11:antiox11040692. [PMID: 35453377 PMCID: PMC9027385 DOI: 10.3390/antiox11040692] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/21/2022] [Accepted: 03/28/2022] [Indexed: 02/04/2023] Open
Abstract
Alzheimer’s disease (AD) is a devastating progressive neurodegenerative disease characterized by neuronal dysfunction, and decreased memory and cognitive function. Iron is critical for neuronal activity, neurotransmitter biosynthesis, and energy homeostasis. Iron accumulation occurs in AD and results in neuronal dysfunction through activation of multifactorial mechanisms. Mitochondria generate energy and iron is a key co-factor required for: (1) ATP production by the electron transport chain, (2) heme protein biosynthesis and (3) iron-sulfur cluster formation. Disruptions in iron homeostasis result in mitochondrial dysfunction and energetic failure. Ferroptosis, a non-apoptotic iron-dependent form of cell death mediated by uncontrolled accumulation of reactive oxygen species and lipid peroxidation, is associated with AD and other neurodegenerative diseases. AD pathogenesis is complex with multiple diverse interacting players including Aβ-plaque formation, phosphorylated tau, and redox stress. Unfortunately, clinical trials in AD based on targeting these canonical hallmarks have been largely unsuccessful. Here, we review evidence linking iron dysregulation to AD and the potential for targeting ferroptosis as a therapeutic intervention for AD.
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Affiliation(s)
- John O. Onukwufor
- Department of Pharmacology and Physiology, University of Rochester Medical Center, Rochester, NY 14642, USA; (R.T.D.); (A.P.W.)
- Correspondence:
| | - Robert T. Dirksen
- Department of Pharmacology and Physiology, University of Rochester Medical Center, Rochester, NY 14642, USA; (R.T.D.); (A.P.W.)
| | - Andrew P. Wojtovich
- Department of Pharmacology and Physiology, University of Rochester Medical Center, Rochester, NY 14642, USA; (R.T.D.); (A.P.W.)
- Department of Anesthesiology and Perioperative Medicine, University of Rochester Medical Center, Rochester, NY 14642, USA
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166
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Chan KS, Hédouin R, Mollink J, Schulz J, van Cappellen van Walsum AM, Marques JP. Imaging white matter microstructure with gradient-echo phase imaging: Is ex vivo imaging with formalin-fixed tissue a good approximation of the in vivo brain? Magn Reson Med 2022; 88:380-390. [PMID: 35344591 PMCID: PMC9314807 DOI: 10.1002/mrm.29213] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 01/17/2022] [Accepted: 02/10/2022] [Indexed: 11/20/2022]
Abstract
Purpose Ex vivo imaging is a commonly used approach to investigate the biophysical mechanism of orientation‐dependent signal phase evolution in white matter. Yet, how phase measurements are influenced by the structural alteration in the tissue after formalin fixation is not fully understood. Here, we study the effects on magnetic susceptibility, microstructural compartmentalization, and chemical exchange measurement with a postmortem formalin‐fixed whole‐brain human tissue. Methods A formalin‐fixed, postmortem human brain specimen was scanned with multiple orientations to the main magnetic field direction for robust bulk magnetic susceptibility measurement with conventional quantitative susceptibility imaging models. White matter samples were subsequently excised from the whole‐brain specimen and scanned in multiple rotations on an MRI scanner to measure the anisotropic magnetic susceptibility and microstructure‐related contributions in the signal phase and to validate the findings of the whole‐brain data. Results The bulk isotropic magnetic susceptibility of ex vivo whole‐brain imaging is comparable to in vivo imaging, with noticeable enhanced nonsusceptibility contributions. The excised specimen experiment reveals that anisotropic magnetic susceptibility and compartmentalization phase effect were considerably reduced in the formalin‐fixed white matter specimens. Conclusions Formalin‐fixed postmortem white matter exhibits comparable isotropic magnetic susceptibility to previous in vivo imaging findings. However, the measured phase and magnitude data of the fixed white matter tissue shows a significantly weaker orientation dependency and compartmentalization effect. Alternatives to formalin fixation are needed to better reproduce the in vivo microstructural effects in postmortem samples.
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Affiliation(s)
- Kwok-Shing Chan
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Renaud Hédouin
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.,Empenn, INRIA, INSERM, CNRS, Université de Rennes 1, Rennes, France
| | - Jeroen Mollink
- Department of Medical Imaging, Anatomy, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jenni Schulz
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Anne-Marie van Cappellen van Walsum
- Department of Medical Imaging, Anatomy, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - José P Marques
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
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167
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Tendler BC, Hanayik T, Ansorge O, Bangerter-Christensen S, Berns GS, Bertelsen MF, Bryant KL, Foxley S, van den Heuvel MP, Howard AFD, Huszar IN, Khrapitchev AA, Leonte A, Manger PR, Menke RAL, Mollink J, Mortimer D, Pallebage-Gamarallage M, Roumazeilles L, Sallet J, Scholtens LH, Scott C, Smart A, Turner MR, Wang C, Jbabdi S, Mars RB, Miller KL. The Digital Brain Bank, an open access platform for post-mortem imaging datasets. eLife 2022; 11:e73153. [PMID: 35297760 PMCID: PMC9042233 DOI: 10.7554/elife.73153] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
Abstract
Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes-Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.
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Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Taylor Hanayik
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Olaf Ansorge
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sarah Bangerter-Christensen
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | | | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen ZooFrederiksbergDenmark
| | - Katherine L Bryant
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sean Foxley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Department of Radiology, University of ChicagoChicagoUnited States
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
- Department of Child Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Amy FD Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Alexandre A Khrapitchev
- Medical Research Council Oxford Institute for Radiation Oncology, University of OxfordOxfordUnited Kingdom
| | - Anna Leonte
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Paul R Manger
- School of Anatomical Sciences, Faculty of Health Sciences, University of the WitwatersrandJohannesburgSouth Africa
| | - Ricarda AL Menke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Duncan Mortimer
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Menuka Pallebage-Gamarallage
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- Stem Cell and Brain Research Institute, Université Lyon 1, INSERMBronFrance
| | - Lianne H Scholtens
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Connor Scott
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Martin R Turner
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
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168
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Chiang GC, Cho J, Dyke J, Zhang H, Zhang Q, Tokov M, Nguyen T, Kovanlikaya I, Amoashiy M, de Leon M, Wang Y. Brain oxygen extraction and neural tissue susceptibility are associated with cognitive impairment in older individuals. J Neuroimaging 2022; 32:697-709. [PMID: 35294075 DOI: 10.1111/jon.12990] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 03/02/2022] [Accepted: 03/02/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND AND PURPOSE We investigated the effects of aging, white matter hyperintensities (WMH), and cognitive impairment on brain iron levels and cerebral oxygen metabolism, known to be altered in Alzheimer's disease (AD), using quantitative susceptibility mapping and MR-based cerebral oxygen extraction fraction (OEF). METHODS In 100 individuals over the age of 50 (68/32 cognitively impaired/intact), OEF and neural tissue susceptibility (χn ) were computed retrospectively from MRI multi-echo gradient echo data, obtained on a 3 Tesla MRI scanner. The effects of age and WMH on OEF and χn were assessed within groups, and OEF and χn were assessed between groups, using multivariate regression analyses. RESULTS Cognitively impaired subjects were found to have 19% higher OEF and 34% higher χn than cognitively intact subjects in the cortical gray matter and several frontal, temporal, and parietal regions (p < .05). Increased WMH burden was significantly associated with decreased OEF in the cognitively impaired, but not in the cognitively intact. Older age had a stronger association with decreased OEF in the cognitively intact group. Both older age and increased WMH burden were significantly associated with increased χn in temporoparietal regions in the cognitively impaired. CONCLUSIONS Higher brain OEF and χn in cognitively impaired older individuals may reflect altered oxygen metabolism and iron in areas with underlying AD pathology. Both age and WMH have associations with OEF and χn but are modified by the presence of cognitive impairment.
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Affiliation(s)
- Gloria C Chiang
- Department of Radiology, Division of Neuroradiology, Weill Cornell Medicine, NewYork-Presbyterian Hospital, New York, New York, USA
| | - Junghun Cho
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Jonathan Dyke
- Citigroup Biomedical Imaging Center, Weill Cornell Medicine, New York, New York, USA
| | - Hang Zhang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Qihao Zhang
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA
| | - Michael Tokov
- New York Institute of Technology College of Osteopathic Medicine, Glen Head, New York, USA
| | - Thanh Nguyen
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Ilhami Kovanlikaya
- Department of Radiology, Division of Neuroradiology, Weill Cornell Medicine, NewYork-Presbyterian Hospital, New York, New York, USA
| | - Michael Amoashiy
- Department of Neurology, Weill Cornell Medicine, New York, New York, USA
| | - Mony de Leon
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
| | - Yi Wang
- MRI Research Institute, Department of Radiology, Weill Cornell Medicine, New York, New York, USA
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169
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Reith TP, Prah MA, Choi EJ, Lee J, Wujek R, Al-Gizawiy M, Chitambar CR, Connelly JM, Schmainda KM. Basal Ganglia Iron Content Increases with Glioma Severity Using Quantitative Susceptibility Mapping: A Potential Biomarker of Tumor Severity. Tomography 2022; 8:789-797. [PMID: 35314642 PMCID: PMC8938779 DOI: 10.3390/tomography8020065] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 02/25/2022] [Accepted: 03/08/2022] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND AND PURPOSE Gliomas have been found to alter iron metabolism and transport in ways that result in an expansion of their intracellular iron compartments to support aggressive tumor growth. This study used deep neural network trained quantitative susceptibility mapping to assess basal ganglia iron concentrations in glioma patients. MATERIALS AND METHODS Ninety-two patients with brain lesions were initially enrolled in this study and fifty-nine met the inclusion criteria. Susceptibility-weighted images were collected at 3.0 T and used to construct quantitative susceptibility maps via a deep neural network-based method. The regions of interest were manually drawn within basal ganglia structures and the mean voxel intensities were extracted and averaged across multiple slices. One-way ANCOVA tests were conducted to compare the susceptibility values of groups of patients based on tumor grade while controlling for age, sex, and tumor type. RESULTS The mean basal ganglia susceptibility for patients with grade IV tumors was higher than that for patients with grade II tumors (p = 0.00153) and was also higher for patients with grade III tumors compared to patients with grade II tumors (p = 0.020), after controlling for age, sex, and tumor type. Patient age influenced susceptibility values (p = 0.00356), while sex (p = 0.69) and tumor type (p = 0.11) did not. CONCLUSIONS The basal ganglia iron content increased with glioma severity. Basal ganglia iron levels may thus be a useful biomarker in glioma prognosis and treatment, especially with regard to iron-based cancer therapies.
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Affiliation(s)
- Thomas P. Reith
- Medical College of Wisconsin, Biophysics, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (T.P.R.); (M.A.P.); (M.A.-G.); (C.R.C.)
| | - Melissa A. Prah
- Medical College of Wisconsin, Biophysics, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (T.P.R.); (M.A.P.); (M.A.-G.); (C.R.C.)
| | - Eun-Jung Choi
- Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Korea; (E.-J.C.); (J.L.)
| | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Korea; (E.-J.C.); (J.L.)
| | - Robert Wujek
- Medical College of Wisconsin, Biomedical Engineering, Marquette University, 1515 W. Wisconsin Ave., Milwaukee, WI 53233, USA;
| | - Mona Al-Gizawiy
- Medical College of Wisconsin, Biophysics, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (T.P.R.); (M.A.P.); (M.A.-G.); (C.R.C.)
| | - Christopher R. Chitambar
- Medical College of Wisconsin, Biophysics, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (T.P.R.); (M.A.P.); (M.A.-G.); (C.R.C.)
- Medical College of Wisconsin, Hematology & Oncology, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
| | - Jennifer M. Connelly
- Medical College of Wisconsin, Neurology & Neurosurgery, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA;
| | - Kathleen M. Schmainda
- Medical College of Wisconsin, Biophysics, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA; (T.P.R.); (M.A.P.); (M.A.-G.); (C.R.C.)
- Medical College of Wisconsin, Radiology, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA
- Correspondence:
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170
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Cho H, Lee H, Gong Y, Kim YR, Cho J, Cho HJ. Quantitative susceptibility mapping and R1 measurement: Determination of the myelin volume fraction in the aging ex vivo rat corpus callosum. NMR IN BIOMEDICINE 2022; 35:e4645. [PMID: 34739153 DOI: 10.1002/nbm.4645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 10/03/2021] [Accepted: 10/16/2021] [Indexed: 06/13/2023]
Abstract
In studies of the white matter (WM) in aging brains, both quantitative susceptibility mapping (QSM) and direct R1 measurement offer potentially useful ex vivo MRI tools that allow volumetric characterization of myelin content changes. Despite the technical importance of such MRI methods in numerous age-related diseases, the supposed linear relationship between the estimates of either the QSM or R1 method and age-affected myelin contents has not been validated. In this study, the absolute myelin volume fraction (MVF) was determined by transmission electron microscopy (TEM) as a gold standard measure for comparison with the values obtained by the aforementioned MR methods. To theoretically evaluate and understand the MR signal characteristics, QSM simulations were performed using the finite perturber method (FPM). Specifically, the simulation geometry modeling was based on TEM-derived structures aligned orthogonally to the main magnetic field, the construct of which was used to estimate the magnetic field shift (ΔB) changes arising from the conjectured myelin structures. Experimentally, ex vivo corpus callosum (CC) samples from rat brains obtained at 6 weeks (n = 3), 4 months (n = 3), and 20 months (n = 3) after birth were used to establish the relationship between changes quantified by either QSM or R1 with the absolute MVF by TEM. From the ex vivo brain samples, the scatterplot of mean MVF versus R1 was fitted to a linear equation, where R1mean = 0.7948 × MVFmean + 0.8118 (Pearson's correlation coefficient r = 0.9138; p < 0.01), while the scatterplot of mean MVF versus MRI-derived magnetic susceptibility (χ) was also fitted to a line where χmeasured,mean = -0.1218 × MVFmean - 0.006345 (r = -0.8435; p < 0.01). As a result of the FPM-based QSM simulations, a linearly proportional relationship between the simulated magnetic susceptibility, χsimulated,mean , and MVF (r = -0.9648; p < 0.01) was established. Such a statistically significant linear correlation between MRI-derived values by the QSM (or R1 ) method and MVF demonstrated that variable myelin contents in the WM (i.e., CC) can be quantified across multiple stages of aging. These findings further support that both techniques based on QSM and R1 provide an efficient means of studying the brain-aging process with accurate volumetric quantification of the myelin content in WM.
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Affiliation(s)
- Hwapyeong Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Hansol Lee
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Yelim Gong
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Young Ro Kim
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Hyung Joon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
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Zhang Y, Yang M, Wang F, Chen Y, Liu R, Zhang Z, Jiang Z. Histogram Analysis of Quantitative Susceptibility Mapping for the Diagnosis of Parkinson's Disease. Acad Radiol 2022; 29 Suppl 3:S71-S79. [PMID: 33189552 DOI: 10.1016/j.acra.2020.10.027] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 10/14/2020] [Accepted: 10/26/2020] [Indexed: 11/01/2022]
Abstract
RATIONALE AND OBJECTIVES To investigate the diagnostic performance of histogram analysis combined with quantitative susceptibility mapping (QSM) for differentiating Parkinson's disease (PD) patients from healthy controls. METHODS We included 35 patients with PD diagnosed by two neurologists from August 2019 to January 2020 in our hospital in this prospective study. The clinical diagnosis was based on the Movement Disorder Society Clinical Diagnostic Criteria for PD. At the same time, 23 healthy volunteers matched for age and sex were recruited as controls. The Mini Mental State Examination, the third part of the Parkinson's Disease Rating Scale, the Hoehn & Yahr stages, and disease duration (year) were used to assess the PD patients. QSM was performed using a 3T MR scanner. The regions of interest were depicted according to the head of the caudate nucleus(CN), globus pallidus(GP), putamina (PUT), thalmus(TH), substantia nigra (SN), red nucleus(RN), and dentate nucleus. Then the corresponding histogram features were extracted. The Mann-Whitney U test was used to identify significant histogram features for differentiating PD patients from healthy controls. Area under the receiver operating characteristics curve (AUC) analysis was conducted to evaluate the diagnostic performance of all significant histogram features. Multivariate logistic regression analysis was performed to identify the best combined model for all seven nuclei. Differences among the AUCs were compared pairwise. RESULTS Histogram features in all nuclei except TH showed significant differences between the groups. Among the single features, the 10th percentile of SN (SNP10) yielded the highest AUC of 0.894, with the highest specificity of 86.86% for differentiating PD patients from healthy controls. The 75th percentile of PUT (PUTP75) yielded the highest sensitivity of 97.14%. In the multivariate logistic regression analysis, SNP10 combined with PUTP75 yielded the highest diagnostic performance with the highest AUC of 0.911, the highest specificity of 91.30% and an excellent sensitivity of 92.40%. CONCLUSION QSM combined with histogram analysis successfully distinguished PD patients from healthy controls, and the result was notably superior to the mean value.
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Li Q, Zhu W, Wen X, Zang Z, Da Y, Lu J. Beyond the Motor Cortex: Thalamic Iron Deposition Accounts for Disease Severity in Amyotrophic Lateral Sclerosis. Front Neurol 2022; 13:791300. [PMID: 35280261 PMCID: PMC8907117 DOI: 10.3389/fneur.2022.791300] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 01/12/2022] [Indexed: 11/23/2022] Open
Abstract
Objective Previous studies have reliably identified iron deposition in the motor cortex as potential pathogenesis of amyotrophic lateral sclerosis (ALS). Here, we intended to investigate iron deposition, gray matter (GM) atrophy, and their associations with disease severity in the motor cortex and the thalamus in patients with ALS. Methods A total of 34 patients with ALS (age 51.31 ± 8.24 years, 23 males) and 34 nonneurological controls (age 50.96 ± 9.35 years, 19 males) were enrolled between 2018 and 2020. The Revised ALS Functional Rating Scale (ALSFRS-R) and the Penn upper motor neuron (UMN) score were measured. MRI data included quantitative susceptibility mapping (QSM) for iron deposition and three-dimensional (3D) T1 for gray matter volume. After a between-group comparison, Pearson's correlation coefficient was used for identifying correlations of iron deposition, GM volume, and clinical measurements. Results The two-sample t-tests revealed increased iron deposition in the left precentral gyrus (peak voxel T = 4.78, PSVC = 0.03) and the thalamus (peak voxel: right: T = 6.38, PSVC < 0.001; left: T = 4.64, PSVC = 0.02) in patients with ALS. GM volume of the precentral gyrus (T = −2.42, P = 0.02) and the bilateral thalamus (T = −4.10, P < 0.001) were reduced. Negative correlations were found between the increased QSM values and the decreased GM volume (P < 0.04, one-tailed) in patients with ALS. Iron deposition in the left precentral gyrus was positively correlated with the UMN score (R = 0.40, P = 0.02) and the GM volume was negatively correlated with the UMN score (R = −0.48, P = 0.004). Negative correlation between thalamic iron deposition and the ALSFRS-R (R = −0.36, P = 0.04) score was observed. Discussion Iron deposition in the thalamus, in addition to the motor cortex, is accompanied by GM atrophy and is associated with disease severity in patients with ALS, indicating that the thalamus is also a pathological region in patients with ALS.
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Affiliation(s)
- Qianwen Li
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Wenjia Zhu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xinmei Wen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zhenxiang Zang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yuwei Da
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- *Correspondence: Jie Lu
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173
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Meng Q, Liu M, Chen Z. Voxel-Based Intraclass Correlation Coefficient to Evaluate the Inter-Scanner Reproducibility of Quantitative Susceptibility Mapping over the Deep Gray Matter Structure at 3.0T MR. Curr Med Imaging 2022; 18:924-930. [PMID: 35170418 DOI: 10.2174/1573405618666220216120729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 12/04/2021] [Accepted: 12/28/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND The Quantitative susceptibility mapping (QSM) technique can be used to quantitatively evaluate the cerebral iron deposition of the deep gray matter structure (DGM) in clinical practice. However, it could be significantly important to assess the reproducibility of the susceptibility values at different magnetic resonance (MR) scanners before the QSM technique can be widely used in clinical applications. OBJECTIVE To assess the reproducibility of susceptibility value of the deep gray matter structure (DGM) at two different MR systems with the same magnetic strength. METHODS Raw data of 21 normal subjects (M/F = 7/14, median age 29 (21, 63) years) were acquired from a 3D multi-echo enhanced gradient recalled echo sequence at two different 3.0T MR systems, and STI software was used to reconstruct the magnetic susceptibility images. Brain structural images were used to be coregistered with magnitude images to generate normalized parameters and normalized susceptibility images. Voxel-based intraclass correlation coefficient (VB-ICC) was used to evaluate the reproducibility of susceptibility value of DGM at different 3.0T MR systems. RESULTS DGM with ICC > 0.75 located in the bilateral posterior putamen and globus pallidus, bilateral red nuclei and left dental nucleus. DGM with 0.6 < ICC < 0.75 mainly located in the bilateral anterior putamen and globus pallidus, the margin of the bilateral red nuclei, right dental nucleus and the margin of the left dental nucleus. DGM with 0.4 < ICC < 0.6 located in anterior parts of the bilateral putamen, bilateral globus pallidus and substantia nigra, the margin of the bilateral dental nuclei and the inferior part of right dental nucleus. CONCLUSION DGM presented regional dependent reproducibility of susceptibility value at two different 3.0T MR system based on VB-ICC analysis.
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Affiliation(s)
- Qinglin Meng
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - Mengqi Liu
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
- Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
| | - Zhiye Chen
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou China
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174
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Howard CM, Jain S, Cook AD, Packard LE, Mullin HA, Chen N, Liu C, Song AW, Madden DJ. Cortical iron mediates age-related decline in fluid cognition. Hum Brain Mapp 2022; 43:1047-1060. [PMID: 34854172 PMCID: PMC8764476 DOI: 10.1002/hbm.25706] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/20/2021] [Accepted: 10/21/2021] [Indexed: 01/19/2023] Open
Abstract
Brain iron dyshomeostasis disrupts various critical cellular functions, and age-related iron accumulation may contribute to deficient neurotransmission and cell death. While recent studies have linked excessive brain iron to cognitive function in the context of neurodegenerative disease, little is known regarding the role of brain iron accumulation in cognitive aging in healthy adults. Further, previous studies have focused primarily on deep gray matter regions, where the level of iron deposition is highest. However, recent evidence suggests that cortical iron may also contribute to cognitive deficit and neurodegenerative disease. Here, we used quantitative susceptibility mapping (QSM) to measure brain iron in 67 healthy participants 18-78 years of age. Speed-dependent (fluid) cognition was assessed from a battery of 12 psychometric and computer-based tests. From voxelwise QSM analyses, we found that QSM susceptibility values were negatively associated with fluid cognition in the right inferior temporal gyrus, bilateral putamen, posterior cingulate gyrus, motor, and premotor cortices. Mediation analysis indicated that susceptibility in the right inferior temporal gyrus was a significant mediator of the relation between age and fluid cognition, and similar effects were evident for the left inferior temporal gyrus at a lower statistical threshold. Additionally, age and right inferior temporal gyrus susceptibility interacted to predict fluid cognition, such that brain iron was negatively associated with a cognitive decline for adults over 45 years of age. These findings suggest that iron may have a mediating role in cognitive decline and may be an early biomarker of neurodegenerative disease.
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Affiliation(s)
- Cortney M. Howard
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Shivangi Jain
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Psychological and Brain SciencesUniversity of IowaIowa CityIowaUSA
| | - Angela D. Cook
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Lauren E. Packard
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Hollie A. Mullin
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Nan‐kuei Chen
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Biomedical EngineeringUniversity of ArizonaTucsonArizonaUSA
| | - Chunlei Liu
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Electrical Engineering and Computer SciencesUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Allen W. Song
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - David J. Madden
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Department of Psychiatry and Behavioral SciencesDuke University Medical CenterDurhamNorth CarolinaUSA
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175
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Sato R, Kudo K, Udo N, Matsushima M, Yabe I, Yamaguchi A, Tha KK, Sasaki M, Harada M, Matsukawa N, Amemiya T, Kawata Y, Bito Y, Ochi H, Shirai T. A diagnostic index based on quantitative susceptibility mapping and voxel-based morphometry may improve early diagnosis of Alzheimer's disease. Eur Radiol 2022; 32:4479-4488. [PMID: 35137303 DOI: 10.1007/s00330-022-08547-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/25/2021] [Accepted: 12/14/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Voxel-based morphometry (VBM) is widely used to quantify the progression of Alzheimer's disease (AD), but improvement is still needed for accurate early diagnosis. We evaluated the feasibility of a novel diagnosis index for early diagnosis of AD based on quantitative susceptibility mapping (QSM) and VBM. METHODS Thirty-seven patients with AD, 24 patients with mild cognitive impairment (MCI) due to AD, and 36 cognitively normal (NC) subjects from four centers were included. A hybrid sequence was performed by using 3-T MRI with a 3D multi-echo GRE sequence to obtain both a T1-weighted image for VBM and phase images for QSM. The index was calculated from specific voxels in QSM and VBM images by using a linear support vector machine. The method of voxel extraction was optimized to maximize diagnostic accuracy, and the optimized index was compared with the conventional VBM-based index using receiver operating characteristic analysis. RESULTS The index was optimal when voxels were extracted as increased susceptibility (AD > NC) in the parietal lobe and decreased gray matter volume (AD < NC) in the limbic system. The optimized proposed index showed excellent performance for discrimination between AD and NC (AUC = 0.94, p = 1.1 × 10-10) and good performance for MCI and NC (AUC = 0.87, p = 1.8 × 10-6), but poor performance for AD and MCI (AUC = 0.68, p = 0.018). Compared with the conventional index, AUCs were improved for all cases, especially for MCI and NC (p < 0.05). CONCLUSIONS In this preliminary study, the proposed index based on QSM and VBM improved the diagnostic performance between MCI and NC groups compared with the VBM-based index. KEY POINTS • We developed a novel diagnostic index for Alzheimer's disease based on quantitative susceptibility mapping (QSM) and voxel-based morphometry (VBM). • QSM and VBM images can be acquired simultaneously in a single sequence with little increasing scan time. • In this preliminary study, the proposed diagnostic index improved the discriminative performance between mild cognitive impairment and normal control groups compared with the conventional VBM-based index.
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Affiliation(s)
- Ryota Sato
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan.
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan.
| | - Kohsuke Kudo
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Niki Udo
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Masaaki Matsushima
- Department of Neurology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Ichiro Yabe
- Department of Neurology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Akinori Yamaguchi
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Khin Khin Tha
- Global Center for Biomedical Science and Engineering, Hokkaido University Faculty of Medicine, Sapporo, Hokkaido, Japan
| | - Makoto Sasaki
- Institute for Biomedical Sciences, Iwate Medical University, Morioka, Iwate, Japan
| | - Masafumi Harada
- Department of Radiology, Tokushima University, Tokushima, Japan
| | | | - Tomoki Amemiya
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Yasuo Kawata
- Radiation Diagnostic Systems Division, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Yoshitaka Bito
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
- Radiation Diagnostic Systems Division, FUJIFILM Healthcare Corporation, Tokyo, Japan
| | - Hisaaki Ochi
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
| | - Toru Shirai
- Innovative Technology Laboratory, FUJIFILM Healthcare Corporation, Tokyo, Japan
- Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, Sapporo, Hokkaido, Japan
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176
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Yu FF, Yi Huang S, Kumar A, Witzel T, Liao C, Duval T, Cohen-Adad J, Bilgic B. Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps. Magn Reson Med 2022; 87:781-790. [PMID: 34480768 PMCID: PMC8627440 DOI: 10.1002/mrm.28995] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 07/13/2021] [Accepted: 08/10/2021] [Indexed: 02/03/2023]
Abstract
PURPOSE A major obstacle to the clinical implementation of quantitative MR is the lengthy acquisition time required to derive multi-contrast parametric maps. We sought to reduce the acquisition time for QSM and macromolecular tissue volume by acquiring both contrasts simultaneously by leveraging their redundancies. The joint virtual coil concept with GRAPPA (JVC-GRAPPA) was applied to reduce acquisition time further. METHODS Three adult volunteers were imaged on a 3 Tesla scanner using a multi-echo 3D GRE sequence acquired at 3 head orientations. Macromolecular tissue volume, QSM, R2∗ , T1 , and proton density maps were reconstructed. The same sequence (GRAPPA R = 4) was performed in subject 1 with a single head orientation for comparison. Fully sampled data was acquired in subject 2, from which retrospective undersampling was performed (R = 6 GRAPPA and R = 9 JVC-GRAPPA). Prospective undersampling was performed in subject 3 (R = 6 GRAPPA and R = 9 JVC-GRAPPA) using gradient blips to shift k-space sampling in later echoes. RESULTS Subject 1's multi-orientation and single-orientation macromolecular tissue volume maps were not significantly different based on RMSE. For subject 2, the retrospectively undersampled JVC-GRAPPA and GRAPPA generated similar results as fully sampled data. This approach was validated with the prospectively undersampled images in subject 3. Using QSM, R2∗ , and macromolecular tissue volume, the contributions of myelin and iron content to susceptibility were estimated. CONCLUSION We have developed a novel strategy to simultaneously acquire data for the reconstruction of 5 intrinsically coregistered 1-mm isotropic resolution multi-parametric maps, with a scan time of 6 min using JVC-GRAPPA.
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Affiliation(s)
- Fang Frank Yu
- Radiology, University of Texas Southwestern Medical Center, Dallas, TX, United States,,Corresponding author. Fang Frank Yu, MD, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, Ph: 214-648-7813, Fax: 214-648-3904,
| | - Susie Yi Huang
- Department of Radiology, Harvard Medical School, Boston, MA, United States,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Ashwin Kumar
- Vanderbilt University, Nashville, TN, United States
| | | | - Congyu Liao
- Radiological Sciences Laboratory, Stanford Medicine, Stanford, CA, United States
| | - Tanguy Duval
- Institute of Biomedical Engineering, Ecole Polytechnique de Montreal, Montreal, QC, Canada
| | - Julien Cohen-Adad
- Institute of Biomedical Engineering, Ecole Polytechnique de Montreal, Montreal, QC, Canada
| | - Berkin Bilgic
- Department of Radiology, Harvard Medical School, Boston, MA, United States,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
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177
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Chen Z, Zhao H, Chen X, Liu M, Li X, Ma L, Yu S. The increased iron deposition of the gray matter over the whole brain in chronic migraine: an exploratory quantitative susceptibility mapping study. Mol Pain 2022; 18:17448069221074987. [PMID: 35083927 PMCID: PMC8874206 DOI: 10.1177/17448069221074987] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Background Prior studies identified iron deposition in deep brain nuclei and the periaqueductal gray matter region in chronic migraine, and less is known about the cerebral iron deposition over the whole cerebral gray matter in CM. The aim of this case–control study is to investigate the cerebral iron deposition of gray matter in CM using an advanced quantitative susceptibility mapping. Methods A multi-echo gradient echo MR sequence was used to obtain raw quantitative susceptibility mapping data from 12 CM patients and 18 normal controls and the quantitative susceptibility mapping were reconstructed. Three dimensional T1 images were segmented and the gray matter mask was generated to extract the susceptibility value of gray matter over the whole brain. The independent t test and receiver operating characteristic curve Receiver operating characteristics was used to investigate the iron deposition changes in CM patients. Results CM presented a higher susceptibility value (1.44 × 10−3 ppm) compared with NC group (0.47 × 10−3 ppm) (p < 0.0001) over the whole cerebral gray matter. There was no correlation between susceptibility value and the clinical variables including disease duration, Visual Analog Scale (VAS), Migraine Disability Assessment Scale (MIDAS), Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), and Montreal Cognitive Assessment (MoCA) scores (p > 0.05). ROC analysis demonstrated the susceptibility had a high diagnostic efficacy (AUC 0.949, sensitivity 77.78% and specificity 100%) in distinguishing CM from NC. Conclusion CM patients had increased iron deposition in total cerebral gray matter which could be considered as a potential diagnostic and evaluated imaging biomarker in CM.
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Affiliation(s)
| | | | - Xiaoyan Chen
- Department of Neurology104607Chinese PLA General Hospital
| | - Mengqi Liu
- Department of Radiology104607Chinese PLA General Hospital
| | | | - Lin Ma
- Department of Radiology104607Chinese PLA General Hospital
| | - Shengyuan Yu
- Department of Neurology104607Chinese PLA General Hospital
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178
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Mao H, Dou W, Wang X, Chen K, Wang X, Guo Y, Zhang C. Iron Deposition in Gray Matter Nuclei of Patients With Intracranial Artery Stenosis: A Quantitative Susceptibility Mapping Study. Front Neurol 2022; 12:785822. [PMID: 35069414 PMCID: PMC8766754 DOI: 10.3389/fneur.2021.785822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 12/14/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: This study aimed to use quantitative susceptibility mapping (QSM) to systematically investigate the changes of iron content in gray matter (GM) nuclei in patients with long-term anterior circulation artery stenosis (ACAS) and posterior circulation artery stenosis (PCAS). Methods: Twenty-five ACAS patients, 25 PCAS patients, and 25 age- and sex-matched healthy controls underwent QSM examination. Patients were scored using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) to assess the degree of neural function deficiency. On QSM images, iron related susceptibility of GM nuclei, including bilateral caudate nucleus, putamen (PU), globus pallidus (GP), thalamus (TH), substantia nigra (SN), red nucleus, and dentate nucleus (DN), were assessed. Susceptibility was compared between bilateral GM nuclei in healthy controls, ACAS patients, and PCAS patients. Partial correlation analysis, with age as a covariate, was separately performed to assess the relationships of susceptibility with NIHSS and mRS scores. Results: There were no significant differences between the susceptibilities for left and right hemispheres in all seven GM nucleus subregions for healthy controls, ACAS patients, and PCAS patients. Compared with healthy controls, mean susceptibility of bilateral PU, GP, and SN in ACAS patients and of bilateral PU, GP, SN, and DN in PCAS patients were significantly increased (all P < 0.05). In addition, mean susceptibility of bilateral TH and SN in PCAS patients was significantly higher than in ACAS patients (both P < 0.05). With partial correlation analysis, mean susceptibility at bilateral PU of ACAS patients was significantly correlated with mRS score (r = 0.415, P < 0.05), and at bilateral PU in PCAS patients was correlated with NIHSS score (r = 0.424, P < 0.05). Conclusion: Our findings indicated that abnormal iron metabolism may present in different subregions of GM nuclei after long-term ACAS and PCAS. In addition, iron content of PU in patients with ACAS and PCAS was correlated with neurological deficit scores. Therefore, iron quantification measured by QSM susceptibility may provide a new insight to understand the pathological mechanism of ischemic stroke caused by ACAS and PCAS.
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Affiliation(s)
- Huimin Mao
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | | | - Xinyi Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - Kunjian Chen
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | - Xinyu Wang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | - Yu Guo
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.,Postgraduate Department, Shandong First Medical University, Jinan, China
| | - Chao Zhang
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China
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179
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Deistung A, Jäschke D, Draganova R, Pfaffenrot V, Hulst T, Steiner KM, Thieme A, Giordano IA, Klockgether T, Tunc S, Münchau A, Minnerop M, Göricke SL, Reichenbach JR, Timmann D. Quantitative susceptibility mapping reveals alterations of dentate nuclei in common types of degenerative cerebellar ataxias. Brain Commun 2022; 4:fcab306. [PMID: 35291442 PMCID: PMC8914888 DOI: 10.1093/braincomms/fcab306] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 10/28/2021] [Accepted: 01/05/2022] [Indexed: 11/13/2022] Open
Abstract
The cerebellar nuclei are a brain region with high iron content. Surprisingly,
little is known about iron content in the cerebellar nuclei and its possible
contribution to pathology in cerebellar ataxias, with the only exception of
Friedreich’s ataxia. In the present exploratory cross-sectional study,
quantitative susceptibility mapping was used to investigate volume, iron
concentration and total iron content of the dentate nuclei in common types of
hereditary and non-hereditary degenerative ataxias. Seventy-nine patients with
spinocerebellar ataxias of types 1, 2, 3 and 6; 15 patients with
Friedreich’s ataxia; 18 patients with multiple system atrophy, cerebellar
type and 111 healthy controls were also included. All underwent 3 T MRI
and clinical assessments. For each specific ataxia subtype, voxel-based and
volumes-of-interest-based group analyses were performed in comparison with a
corresponding age- and sex-matched control group, both for volume, magnetic
susceptiblity (indicating iron concentration) and susceptibility mass
(indicating total iron content) of the dentate nuclei. Spinocerebellar ataxia of
type 1 and multiple system atrophy, cerebellar type patients showed higher
susceptibilities in large parts of the dentate nucleus but unaltered
susceptibility masses compared with controls. Friedreich’s ataxia
patients and, only on a trend level, spinocerebellar ataxia of type 2 patients
showed higher susceptibilities in more circumscribed parts of the dentate. In
contrast, spinocerebellar ataxia of type 6 patients revealed lower
susceptibilities and susceptibility masses compared with controls throughout the
dentate nucleus. Spinocerebellar ataxia of type 3 patients showed no significant
changes in susceptibility and susceptibility mass. Lower volume of the dentate
nuclei was found to varying degrees in all ataxia types. It was most pronounced
in spinocerebellar ataxia of type 6 patients and least prominent in
spinocerebellar ataxia of type 3 patients. The findings show that alterations in
susceptibility revealed by quantitative susceptibility mapping are common in the
dentate nuclei in different types of cerebellar ataxias. The most striking
changes in susceptibility were found in spinocerebellar ataxia of type 1,
multiple system atrophy, cerebellar type and spinocerebellar ataxia of type 6.
Because iron content is known to be high in glial cells but not in neurons of
the cerebellar nuclei, the higher susceptibility in spinocerebellar ataxia of
type 1 and multiple system atrophy, cerebellar type may be explained by a
reduction of neurons (increase in iron concentration) and/or an increase in
iron-rich glial cells, e.g. microgliosis. Hypomyelination also leads to higher
susceptibility and could also contribute. The lower susceptibility in SCA6
suggests a loss of iron-rich glial cells. Quantitative susceptibility maps
warrant future studies of iron content and iron-rich cells in ataxias to gain a
more comprehensive understanding of the pathogenesis of these diseases.
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Affiliation(s)
- Andreas Deistung
- University Clinic and Outpatient Clinic for Radiology, Department for Radiation Medicine, University Hospital Halle (Saale), Halle (Saale), Germany
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
| | - Dominik Jäschke
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
| | - Rossitza Draganova
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
| | - Viktor Pfaffenrot
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany
| | - Thomas Hulst
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
- Erasmus University College, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Katharina M. Steiner
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
| | - Andreas Thieme
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
| | - Ilaria A. Giordano
- Department of Neurology, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Thomas Klockgether
- Department of Neurology, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Sinem Tunc
- Institute of Systems Motor Science, University of Lübeck, Lübeck, Germany
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | - Alexander Münchau
- Institute of Systems Motor Science, University of Lübeck, Lübeck, Germany
| | - Martina Minnerop
- Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany
- Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, 40225 Duesseldorf, Germany
| | - Sophia L. Göricke
- Institute of Diagnostic and Interventional Radiology and Neuroradiology, Essen University Hospital, Essen, Germany
| | - Jürgen R. Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany
| | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
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Miletić S, Bazin PL, Isherwood SJS, Keuken MC, Alkemade A, Forstmann BU. Charting human subcortical maturation across the adult lifespan with in vivo 7 T MRI. Neuroimage 2022; 249:118872. [PMID: 34999202 DOI: 10.1016/j.neuroimage.2022.118872] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 12/20/2021] [Accepted: 01/03/2022] [Indexed: 12/26/2022] Open
Abstract
The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures and ventricles, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.
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Affiliation(s)
- Steven Miletić
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
| | - Pierre-Louis Bazin
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands; Max Planck Institute for Human Cognitive and Brain Sciences, Departments of Neurophysics and Neurology, Stephanstraße 1A, Leipzig, Germany
| | - Scott J S Isherwood
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Max C Keuken
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Anneke Alkemade
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Birte U Forstmann
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
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181
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Magnetic susceptibility in the deep gray matter may be modulated by apolipoprotein E4 and age with regional predilections: a quantitative susceptibility mapping study. Neuroradiology 2022; 64:1331-1342. [PMID: 34981175 DOI: 10.1007/s00234-021-02859-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 11/09/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE To examine the relationship between apolipoprotein E gene (APOE) mutation status and iron accumulation in the deep gray matter of subjects with cognitive symptoms using quantitative susceptibility mapping (QSM). METHODS A total of 105 patients with cognitive symptoms were enrolled. QSM data were generated from 3D gradient-echo data using an STI Suite algorithm. A region of interest-based analysis with QSM was performed in the deep gray matter. Differences between APOE4 carriers and non-carriers were assessed by analysis of covariance. Multiple regression analysis was performed to identify the factors associated with magnetic susceptibility. RESULTS Clinical characters such as age, education, MMSE, vascular risk burden, and systolic blood pressure differ between APOE4 carrier and non-carrier groups. The APOE4 carrier group had higher magnetic susceptibility values than the non-carrier group, with significant differences in the caudate (p = 0.004), putamen (p < 0.0001), and globus pallidus (p < 0.0001) which imply higher iron accumulation. In a multiple regression analysis, APOE4 status was found to be a predictor of magnetic susceptibility value in the globus pallidus (p = 0.03); age for magnetic susceptibility value in the caudate nucleus (p = 0.0064); and age and hippocampal atrophy for magnetic susceptibility value in the putamen (p < 0.05). CONCLUSION Our study demonstrates that magnetic susceptibility in globus pallidus is related to APOE4 status while those of caudate and putamen are related to other factors including age. It suggests that brain iron accumulation in the deep gray matter is modulated by APOE4 and age with differential regional predilection.
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182
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Aarts E, Akkerman A, Altgassen M, Bartels R, Beckers D, Bevelander K, Bijleveld E, Blaney Davidson E, Boleij A, Bralten J, Cillessen T, Claassen J, Cools R, Cornelissen I, Dresler M, Eijsvogels T, Faber M, Fernández G, Figner B, Fritsche M, Füllbrunn S, Gayet S, van Gelder MMHJ, van Gerven M, Geurts S, Greven CU, Groefsema M, Haak K, Hagoort P, Hartman Y, van der Heijden B, Hermans E, Heuvelmans V, Hintz F, den Hollander J, Hulsman AM, Idesis S, Jaeger M, Janse E, Janzing J, Kessels RPC, Karremans JC, de Kleijn W, Klein M, Klumpers F, Kohn N, Korzilius H, Krahmer B, de Lange F, van Leeuwen J, Liu H, Luijten M, Manders P, Manevska K, Marques JP, Matthews J, McQueen JM, Medendorp P, Melis R, Meyer A, Oosterman J, Overbeek L, Peelen M, Popma J, Postma G, Roelofs K, van Rossenberg YGT, Schaap G, Scheepers P, Selen L, Starren M, Swinkels DW, Tendolkar I, Thijssen D, Timmerman H, Tutunji R, Tuladhar A, Veling H, Verhagen M, Verkroost J, Vink J, Vriezekolk V, Vrijsen J, Vyrastekova J, van der Wal S, Willems R, Willemsen A. Protocol of the Healthy Brain Study: An accessible resource for understanding the human brain and how it dynamically and individually operates in its bio-social context. PLoS One 2021; 16:e0260952. [PMID: 34965252 PMCID: PMC8716054 DOI: 10.1371/journal.pone.0260952] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 11/20/2021] [Indexed: 12/29/2022] Open
Abstract
The endeavor to understand the human brain has seen more progress in the last few decades than in the previous two millennia. Still, our understanding of how the human brain relates to behavior in the real world and how this link is modulated by biological, social, and environmental factors is limited. To address this, we designed the Healthy Brain Study (HBS), an interdisciplinary, longitudinal, cohort study based on multidimensional, dynamic assessments in both the laboratory and the real world. Here, we describe the rationale and design of the currently ongoing HBS. The HBS is examining a population-based sample of 1,000 healthy participants (age 30–39) who are thoroughly studied across an entire year. Data are collected through cognitive, affective, behavioral, and physiological testing, neuroimaging, bio-sampling, questionnaires, ecological momentary assessment, and real-world assessments using wearable devices. These data will become an accessible resource for the scientific community enabling the next step in understanding the human brain and how it dynamically and individually operates in its bio-social context. An access procedure to the collected data and bio-samples is in place and published on https://www.healthybrainstudy.nl/en/data-and-methods/access. Trail registration:https://www.trialregister.nl/trial/7955.
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Affiliation(s)
- Healthy Brain Study consortium
- Radboud University, Nijmegen, The Netherlands
- Radboud University Medical Center, Nijmegen, The Netherlands
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Esther Aarts
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Agnes Akkerman
- Institute for Management Research, Radboud University, Nijmegen, The Netherlands
| | | | - Ronald Bartels
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Debby Beckers
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | | | - Erik Bijleveld
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | | | | | - Janita Bralten
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Toon Cillessen
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Jurgen Claassen
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Roshan Cools
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Martin Dresler
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Myrthe Faber
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Guillén Fernández
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- * E-mail:
| | - Bernd Figner
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Matthias Fritsche
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Sascha Füllbrunn
- Institute for Management Research, Radboud University, Nijmegen, The Netherlands
| | - Surya Gayet
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | | | - Marcel van Gerven
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Sabine Geurts
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Corina U. Greven
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Martine Groefsema
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Koen Haak
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Peter Hagoort
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Yvonne Hartman
- Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Erno Hermans
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Florian Hintz
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | | | - Anneloes M. Hulsman
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Sebastian Idesis
- Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Spain
| | - Martin Jaeger
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Esther Janse
- Centre for Language Studies, Radboud University, Nijmegen, The Netherlands
| | - Joost Janzing
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Roy P. C. Kessels
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Johan C. Karremans
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Willemien de Kleijn
- School of Psychology and Artificial Intelligence, Radboud University, Nijmegen, The Netherlands
| | - Marieke Klein
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Floris Klumpers
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Nils Kohn
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Hubert Korzilius
- Institute for Management Research, Radboud University, Nijmegen, The Netherlands
| | - Bas Krahmer
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Floris de Lange
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Judith van Leeuwen
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Huaiyu Liu
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Maartje Luijten
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Peggy Manders
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Katerina Manevska
- Institute for Management Research, Radboud University, Nijmegen, The Netherlands
| | - José P. Marques
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Jon Matthews
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - James M. McQueen
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Pieter Medendorp
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - René Melis
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Antje Meyer
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Joukje Oosterman
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Lucy Overbeek
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marius Peelen
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Jean Popma
- Interdisciplinary Hub for Security, Privacy and Data Governance, Radboud University, Nijmegen, The Netherlands
| | - Geert Postma
- Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands
| | - Karin Roelofs
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | | | - Gabi Schaap
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Paul Scheepers
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Luc Selen
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Marianne Starren
- Centre for Language Studies, Radboud University, Nijmegen, The Netherlands
| | | | - Indira Tendolkar
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Dick Thijssen
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - Hans Timmerman
- University Medical Center Groningen, Groningen, The Netherlands
| | - Rayyan Tutunji
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anil Tuladhar
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Harm Veling
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Maaike Verhagen
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | | | - Jacqueline Vink
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | | | - Janna Vrijsen
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jana Vyrastekova
- Institute for Management Research, Radboud University, Nijmegen, The Netherlands
| | | | - Roel Willems
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Centre for Language Studies, Radboud University, Nijmegen, The Netherlands
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Zachariou V, Bauer CE, Powell DK, Gold BT. Ironsmith: An Automated Pipeline for QSM-based Data Analyses. Neuroimage 2021; 249:118835. [PMID: 34936923 PMCID: PMC8935985 DOI: 10.1016/j.neuroimage.2021.118835] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 11/27/2021] [Accepted: 12/17/2021] [Indexed: 12/13/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) is an MRI-based, computational method for anatomically localizing and measuring concentrations of specific biomarkers in tissue such as iron. Growing research suggests QSM is a viable method for evaluating the impact of iron overload in neurological disorders and on cognitive performance in aging. Several software toolboxes are currently available to reconstruct QSM maps from 3D GRE MR Images. However, few if any software packages currently exist that offer fully automated pipelines for QSM-based data analyses: from DICOM images to region-of-interest (ROI) based QSM values. Even less QSM-based software exist that offer quality control measures for evaluating the QSM output. Here, we address these gaps in the field by introducing and demonstrating the reliability and external validity of Ironsmith; an open-source, fully automated pipeline for creating and processing QSM maps, extracting QSM values from subcortical and cortical brain regions (89 ROIs) and evaluating the quality of QSM data using SNR measures and assessment of outlier regions on phase images. Ironsmith also features automatic filtering of QSM outlier values and precise CSF-only QSM reference masks that minimize partial volume effects. Testing of Ironsmith revealed excellent intra- and inter-rater reliability. Finally, external validity of Ironsmith was demonstrated via an anatomically selective relationship between motor performance and Ironsmith-derived QSM values in motor cortex. In sum, Ironsmith provides a freely-available, reliable, turn-key pipeline for QSM-based data analyses to support research on the impact of brain iron in aging and neurodegenerative disease.
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Affiliation(s)
- Valentinos Zachariou
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY 40536-0298 United States.
| | - Christopher E Bauer
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY 40536-0298 United States
| | - David K Powell
- Department of Neuroscience, Magnetic Resonance Imaging and Spectroscopy Center, College of Medicine, University of Kentucky, Lexington, KY 40536-0298 United States
| | - Brian T Gold
- Department of Neuroscience, Sanders-Brown Center on Aging, Magnetic Resonance Imaging and Spectroscopy Center, College of Medicine, University of Kentucky, Lexington, KY 40536-0298 United States.
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184
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Vroegindeweij LHP, Wielopolski PA, Boon AJW, Wilson JHP, Verdijk RM, Zheng S, Bonnet S, Bossoni L, van der Weerd L, Hernandez-Tamames JA, Langendonk JG. MR imaging for the quantitative assessment of brain iron in aceruloplasminemia: A postmortem validation study. Neuroimage 2021; 245:118752. [PMID: 34823024 DOI: 10.1016/j.neuroimage.2021.118752] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 10/15/2021] [Accepted: 11/20/2021] [Indexed: 11/18/2022] Open
Abstract
AIMS Non-invasive measures of brain iron content would be of great benefit in neurodegeneration with brain iron accumulation (NBIA) to serve as a biomarker for disease progression and evaluation of iron chelation therapy. Although magnetic resonance imaging (MRI) provides several quantitative measures of brain iron content, none of these have been validated for patients with a severely increased cerebral iron burden. We aimed to validate R2* as a quantitative measure of brain iron content in aceruloplasminemia, the most severely iron-loaded NBIA phenotype. METHODS Tissue samples from 50 gray- and white matter regions of a postmortem aceruloplasminemia brain and control subject were scanned at 1.5 T to obtain R2*, and biochemically analyzed with inductively coupled plasma mass spectrometry. For gray matter samples of the aceruloplasminemia brain, sample R2* values were compared with postmortem in situ MRI data that had been obtained from the same subject at 3 T - in situ R2*. Relationships between R2* and tissue iron concentration were determined by linear regression analyses. RESULTS Median iron concentrations throughout the whole aceruloplasminemia brain were 10 to 15 times higher than in the control subject, and R2* was linearly associated with iron concentration. For gray matter samples of the aceruloplasminemia subject with an iron concentration up to 1000 mg/kg, 91% of variation in R2* could be explained by iron, and in situ R2* at 3 T and sample R2* at 1.5 T were highly correlated. For white matter regions of the aceruloplasminemia brain, 85% of variation in R2* could be explained by iron. CONCLUSIONS R2* is highly sensitive to variations in iron concentration in the severely iron-loaded brain, and might be used as a non-invasive measure of brain iron content in aceruloplasminemia and potentially other NBIA disorders.
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Affiliation(s)
- Lena H P Vroegindeweij
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Piotr A Wielopolski
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Agnita J W Boon
- Department of Neurology, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - J H Paul Wilson
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Rob M Verdijk
- Department of Pathology, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Sipeng Zheng
- Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands
| | - Sylvestre Bonnet
- Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands
| | - Lucia Bossoni
- C.J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Louise van der Weerd
- C.J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands; Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
| | - Janneke G Langendonk
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Erasmus MC, Rotterdam, the Netherlands
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185
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Shibata H, Uchida Y, Inui S, Kan H, Sakurai K, Oishi N, Ueki Y, Oishi K, Matsukawa N. Machine learning trained with quantitative susceptibility mapping to detect mild cognitive impairment in Parkinson's disease. Parkinsonism Relat Disord 2021; 94:104-110. [PMID: 34906915 DOI: 10.1016/j.parkreldis.2021.12.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/24/2021] [Accepted: 12/05/2021] [Indexed: 01/06/2023]
Abstract
BACKGROUND Cognitive decline is commonly observed in Parkinson's disease (PD). Identifying PD with mild cognitive impairment (PD-MCI) is crucial for early initiation of therapeutic interventions and preventing cognitive decline. OBJECTIVE We aimed to develop a machine learning model trained with magnetic susceptibility values based on the multi-atlas label-fusion method to classify PD without dementia into PD-MCI and normal cognition (PD-CN). METHODS This multicenter observational cohort study retrospectively reviewed 61 PD-MCI and 59 PD-CN cases for the internal validation cohort and 22 PD-MCI and 21 PD-CN cases for the external validation cohort. The multi-atlas method parcellated the quantitative susceptibility mapping (QSM) images into 20 regions of interest and extracted QSM-based magnetic susceptibility values. Random forest, extreme gradient boosting, and light gradient boosting were selected as machine learning algorithms. RESULTS All classifiers demonstrated substantial performances in the classification task, particularly the random forest model. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve for this model were 79.1%, 77.3%, 81.0%, and 0.78, respectively. The QSM values in the caudate nucleus, which were important features, were inversely correlated with the Montreal Cognitive Assessment scores (right caudate nucleus: r = -0.573, 95% CI: -0.801 to -0.298, p = 0.003; left caudate nucleus: r = -0.659, 95% CI: -0.894 to -0.392, p < 0.001). CONCLUSIONS Machine learning models trained with QSM values successfully classified PD without dementia into PD-MCI and PD-CN groups, suggesting the potential of QSM values as an auxiliary biomarker for early evaluation of cognitive decline in patients with PD.
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Affiliation(s)
- Haruto Shibata
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan; Department of Neurology, Nagoya City University East Medical Center, Aichi, Japan
| | - Yuto Uchida
- Department of Neurology, Toyokawa City Hospital, Aichi, Japan; Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Aichi, Japan.
| | - Shohei Inui
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Keita Sakurai
- Department of Radiology, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Naoya Oishi
- Medical Innovation Center, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yoshino Ueki
- Department of Rehabilitation Medicine, Nagoya City University Graduate School of Medical Sciences, Aichi, Japan
| | - Kenichi Oishi
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Noriyuki Matsukawa
- Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Aichi, Japan
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186
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The effect of beta-amyloid and tau protein aggregations on magnetic susceptibility of anterior hippocampal laminae in Alzheimer's diseases. Neuroimage 2021; 244:118584. [PMID: 34537383 DOI: 10.1016/j.neuroimage.2021.118584] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 08/27/2021] [Accepted: 09/15/2021] [Indexed: 11/20/2022] Open
Abstract
Previous studies have reported the changes of magnetic susceptibility induced by iron deposition in hippocampus of Alzheimer's disease (AD) brains. It is well-known that hippocampus is divided into well-defined laminar architecture, which, however, is difficult to be resolved with in-vivo MRI due to the limited imaging resolution. The present study aims to investigate layer-specific magnetic susceptibility in the hippocampus of AD patients using high-resolution ex-vivo MRI, and elucidate its relationship with beta amyloid (Aβ) and tau protein histology. We performed quantitative susceptibility mapping (QSM) and T2* mapping on postmortem anterior hippocampus samples from four AD, four Primary Age-Related Tauopathy (PART), and three control brains. We manually segmented each sample into seven layers, including four layers in the cornu ammonis1 (CA1) and three layers in the dentate gyrus (DG), and then evaluated AD-related alterations of susceptibility and T2* values and their correlations with Aβ and tau in each hippocampal layer. Specifically, we found (1) layer-specific variations of susceptibility and T2* measurements in all samples; (2) the heterogeneity of susceptibility were higher in all layers of AD patients compared with the age- and gender-matched PART cases while the heterogeneity of T2* values were lower in four layers of CA1; and (3) voxel-wise MRI-histological correlation revealed both susceptibility and T2* values in the stratum molecular (SM) and stratum lacunosum (SL) layers were correlated with the Aβ content in AD, while the T2* values in the stratum radiatum (SR) layer were correlated with the tau content in the PART but not AD. These findings suggest a selective effect of the Aβ- and tau-pathology on the susceptibility and T2* values in the different layers of anterior hippocampus. Particularly, the alterations of magnetic susceptibility in the SM and SL layers may be associated with Aβ aggregation, while those in the SR layermay reflect the age-related tau protein aggregation.
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Champagne AA, Wen Y, Selim M, Filippidis A, Thomas AJ, Spincemaille P, Wang Y, Soman S. Quantitative Susceptibility Mapping for Staging Acute Cerebral Hemorrhages: Comparing the Conventional and Multiecho Complex Total Field Inversion magnetic resonance imaging MR Methods. J Magn Reson Imaging 2021; 54:1843-1854. [PMID: 34117811 DOI: 10.1002/jmri.27763] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 05/20/2021] [Accepted: 05/21/2021] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND The perceived acuity of intracerebral hemorrhage (ICH) impacts the management of patients, both within emergent and outpatient/urgent settings. Morphology enabled dipole inversion (MEDI) quantitative susceptibility imaging (QSM) has improved characterization of ICH acuity, despite outstanding limitations in distinguishing blood products. PURPOSE/HYPOTHESIS Using improved susceptibility quantification, novel postprocessing QSM method from multiecho complex total field inversion (mcTFI) may better discriminate between acute and subacute ICH, compared to MEDI. STUDY TYPE Retrospective cohort study. SUBJECTS A total of 121 subjects enrolled following positive computerized tomography (CT) findings for ICH. Subjects were grouped based on time between admission and MR imaging: hyperacute (<24 hours), acute (1-3 days), early subacute (3-7 days), and late subacute (7-18 days). FIELD STRENGTH/SEQUENCE A multiecho gradient echo sequence at 3.0 T was paired with clinical noncontrast CT imaging. ASSESSMENT A quantitative index (CTindex ) was derived based on relative intensities of blood on noncontrast CT. All images were co-registered, from which QSM parameters within the ICH area were assessed across groups, as well as the correlation with CTindex . STATISTICAL TESTS Group differences were assessed using ANOVAs. Linear regressions between the CTindex , MEDI, and mcTFI measurements were used to assess their relationships. Statistical significance was set at P < 0.05. RESULTS A total of 21 hyperacute, 72 acute, 21 early subacute, and 7 late-subacute patients were included in this analysis. Significant changes in blood susceptibility were found over time for the MEDI and mcTFI, although mcTFI better differentiated the hyperacute/acute from subacute stages. CTindex values within the ICH were more strongly correlated with mcTFI QSM (r = 0.727) than MEDI (r = 0.412) QSM. DATA CONCLUSION McTFI susceptibility estimation demonstrated better correlation with ICH acuity as suggested by CT, providing an improved method to assess acuity of intracranial blood products in clinical settings to identify cases that may require acute intervention. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Allen A Champagne
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada
- School of Medicine, Queen's University, Kingston, Ontario, Canada
| | - Yan Wen
- Department of Radiology, Weill Cornell Medicine, Ithaca, New York, USA
| | - Magdy Selim
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Aristotelis Filippidis
- Department of Neurosurgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Massachusetts, USA
| | - Ajith J Thomas
- Department of Neurosurgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Massachusetts, USA
| | | | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, Ithaca, New York, USA
| | - Salil Soman
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
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188
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Lancione M, Costagli M, Handjaras G, Tosetti M, Ricciardi E, Pietrini P, Cecchetti L. Complementing canonical fMRI with functional Quantitative Susceptibility Mapping (fQSM) in modern neuroimaging research. Neuroimage 2021; 244:118574. [PMID: 34508897 DOI: 10.1016/j.neuroimage.2021.118574] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 09/03/2021] [Accepted: 09/07/2021] [Indexed: 10/20/2022] Open
Abstract
Functional Quantitative Susceptibility Mapping (fQSM) allows for the quantitative measurement of time-varying magnetic susceptibility across cortical and subcortical brain structures with a potentially higher spatial specificity than conventional fMRI. While the usefulness of fQSM with General Linear Model and "On/Off" paradigms has been assessed, little is known about the potential applications and limitations of this technique in more sophisticated experimental paradigms and analyses, such as those currently used in modern neuroimaging. To thoroughly characterize fQSM activations, here we used 7T MRI, tonotopic mapping, as well as univariate (i.e., GLM and population Receptive Field) and multivariate (Representational Similarity Analysis; RSA) analyses. Although fQSM detected less tone-responsive voxels than fMRI, they were more consistently localized in gray matter. Also, the majority of active gray matter voxels exhibited negative fQSM response, signaling the expected oxyhemoglobin increase, whereas positive fQSM activations were mainly in white matter. Though fMRI- and fQSM-based tonotopic maps were overall comparable, the representation of frequency tunings in tone-sensitive regions was significantly more balanced for fQSM. Lastly, RSA revealed that frequency information from the auditory cortex could be successfully retrieved by using either methods. Overall, fQSM produces complementary results to conventional fMRI, as it captures small-scale variations in the activation pattern which inform multivariate measures. Although positive fQSM responses deserve further investigation, they do not impair the interpretation of contrasts of interest. The quantitative nature of fQSM, its spatial specificity and the possibility to simultaneously acquire canonical fMRI support the use of this technique for longitudinal and multicentric studies and pre-surgical mapping.
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Affiliation(s)
- Marta Lancione
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy; IMAGO7 Foundation, Pisa, Italy.
| | - Mauro Costagli
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Pisa, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Sciences (DINOGMI), University of Genoa, Genoa, Italy
| | - Giacomo Handjaras
- Social and Affective Neuroscience (SANe) Group, MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Michela Tosetti
- IMAGO7 Foundation, Pisa, Italy; Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Pisa, Italy
| | - Emiliano Ricciardi
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Pietro Pietrini
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza San Francesco, 19, Lucca 55100, Italy
| | - Luca Cecchetti
- Social and Affective Neuroscience (SANe) Group, MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
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189
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Xiao B, He N, Wang Q, Shi F, Cheng Z, Haacke EM, Yan F, Shen D. Stability of AI-Enabled Diagnosis of Parkinson's Disease: A Study Targeting Substantia Nigra in Quantitative Susceptibility Mapping Imaging. Front Neurosci 2021; 15:760975. [PMID: 34887722 PMCID: PMC8650720 DOI: 10.3389/fnins.2021.760975] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 10/18/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: Parkinson's disease (PD) diagnosis algorithms based on quantitative susceptibility mapping (QSM) and image algorithms rely on substantia nigra (SN) labeling. However, the difference between SN labels from different experts (or segmentation algorithms) will have a negative impact on downstream diagnostic tasks, such as the decrease of the accuracy of the algorithm or different diagnostic results for the same sample. In this article, we quantify the accuracy of the algorithm on different label sets and then improve the convolutional neural network (CNN) model to obtain a high-precision and highly robust diagnosis algorithm. Methods: The logistic regression model and CNN model were first compared for classification between PD patients and healthy controls (HC), given different sets of SN labeling. Then, based on the CNN model with better performance, we further proposed a novel "gated pooling" operation and integrated it with deep learning to attain a joint framework for image segmentation and classification. Results: The experimental results show that, with different sets of SN labeling that mimic different experts, the CNN model can maintain a stable classification accuracy at around 86.4%, while the conventional logistic regression model yields a large fluctuation ranging from 78.9 to 67.9%. Furthermore, the "gated pooling" operation, after being integrated for joint image segmentation and classification, can improve the diagnosis accuracy to 86.9% consistently, which is statistically better than the baseline. Conclusion: The CNN model, compared with the conventional logistic regression model using radiomics features, has better stability in PD diagnosis. Furthermore, the joint end-to-end CNN model is shown to be suitable for PD diagnosis from the perspectives of accuracy, stability, and convenience in actual use.
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Affiliation(s)
- Bin Xiao
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Naying He
- Department of Radiology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qian Wang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Feng Shi
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Zenghui Cheng
- Department of Radiology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ewart Mark Haacke
- Department of Radiology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Department of Radiology, Wayne State University, Detroit, MI, United States
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Dinggang Shen
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
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190
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Raab P, Ropele S, Bültmann E, Salcher R, Lanfermann H, Wattjes MP. Analysis of deep grey nuclei susceptibility in early childhood: a quantitative susceptibility mapping and R2* study at 3 Tesla. Neuroradiology 2021; 64:1021-1031. [PMID: 34787698 PMCID: PMC9005446 DOI: 10.1007/s00234-021-02846-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 10/24/2021] [Indexed: 11/18/2022]
Abstract
Purpose Aging is the most significant determinant for brain iron accumulation in the deep grey matter. Data on brain iron evolution during brain maturation in early childhood are limited. The purpose of this study was to investigate age-related iron deposition in the deep grey matter in children using quantitative susceptibility (QSM) and R2* mapping. Methods We evaluated brain MRI scans of 74 children (age 6–154 months, mean 40 months). A multi-echo gradient-echo sequence obtained at 3 Tesla was used for the QSM and R2* calculation. Susceptibility of the pallidum, head of caudate nucleus, and putamen was correlated with age and compared between sexes. Results Susceptibility changes in all three nuclei correlated with age (correlation coefficients for QSM/R2*: globus pallidus 0.955/0.882, caudate nucleus 0.76/0.65, and putamen 0.643/0.611). During the first 2 years, the R2* values increased more rapidly than the QSM values, indicating a combined effect of iron deposition and myelination, followed by a likely dominating effect of iron deposition. There was no significant gender difference. Conclusion QSM and R2* can monitor myelin maturation processes and iron accumulation in the deep grey nuclei of the brain in early life and may be a promising tool for the detection of deviations of this normal process. Susceptibility in the deep nuclei is almost similar early after birth and increases more quickly in the pallidum. The combined use of QSM and R2* analysis is beneficial.
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Affiliation(s)
- Peter Raab
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
| | - Stefan Ropele
- Clinical Department of Neurology, Medical University of Graz, Graz, Austria
| | - Eva Bültmann
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Rolf Salcher
- Clinic for Laryngology, Rhinology and Otology, Hannover Medical School, Hannover, Germany
| | - Heinrich Lanfermann
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Mike P Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
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191
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Xu J, Guan X, Wen J, Wang T, Zhang M, Xu X. Substantia nigra iron affects functional connectivity networks modifying working memory performance in younger adults. Eur J Neurosci 2021; 54:7959-7973. [PMID: 34779047 DOI: 10.1111/ejn.15532] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 11/09/2021] [Accepted: 11/10/2021] [Indexed: 01/19/2023]
Abstract
Brain iron affects working memory (WM) but the impact of iron content in deep grey matter nuclei on WM networks is unknown. We aimed to test whether deep grey matter nuclei iron concentration can affect resting-state functional connectivity (rsFC) within brain networks modifying WM performance. An N-back WM paradigm was applied in a hundred healthy younger adults. The participants then underwent a resting-state functional magnetic resonance imaging (fMRI) for brain network analysis and quantitative susceptibility mapping (QSM) imaging for assessment of deep grey matter nuclei iron concentration. Higher substantia nigra (SN) iron concentration was associated with lower rsFC between SN and brain regions of the temporal/frontal lobe but with better WM performance after controlling for age, gender and education. A follow-up mediation analysis also indicated that functional connectivity may mediate the link between SN iron and WM performance. Our results suggest that high SN iron concentration may affect communication between the SN and temporal/frontal lobe and is associated with strengthened WM performance in younger adults.
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Affiliation(s)
- Jingjing Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiaqi Wen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tao Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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192
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Fan W, Wang X, Zhang X, Liu M, Meng Q, Chen Z. Investigating Optimal Echo Times for Quantitative Susceptibility Mapping of Basal Ganglia Nuclei in the Healthy Brain. Curr Med Imaging 2021; 16:991-996. [PMID: 33081660 DOI: 10.2174/1573405615666191219102044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2019] [Revised: 11/21/2019] [Accepted: 12/02/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND Quantitative susceptibility mapping (QSM) technique had been used to measure the magnetic susceptibility of brain tissue in clinical practice. However, QSM presented echo-time (TE) dependence, and an appropriate number of echo-times (nTEs) for QSM became more important to obtain the reliable susceptibility value. OBJECTIVE The aim of the study was to explore the optimal nTEs for quantitative susceptibility mapping (QSM) measurements of basal ganglia nuclei in the healthy brain. METHODS 3D multi-echo enhanced gradient recalled echo T2 star weighted angiography (ESWAN) sequence was acquired on a 3.0T MR scanner for QSM analysis. Regions of interests (ROIs) were drawn along the margin of the head of the caudate nucleus (HCN), putamen (Pu) and globus pallidus (GP). The mean susceptibility value and standard deviation of the ROIs were derived from the pixels within each region. RESULTS CV analysis demonstrated that TE6, TE8 and TE14 ESWAN sequences presented consistent lower CV value (< 1) for QSM measure of HCN, Pu and GP. ANOVA identified that susceptibility value showed no significant difference between TE6 and TE8 in HCN, Pu and GP (P > 0.05). ICC analysis demonstrated that the susceptibility value of TE6-TE8 had the highest ICC value as compared with TE6-TE14 and TE8-TE14 in HCN, Pu and GP. Combined with the timeefficiency of MRI scanning, TE6 sequence could not only provide the reliable QSM measurement but also short imaging time. CONCLUSION The current study identified that the optimal nTEs of ESWAN were 6 TEs (2.9ms ~ 80.9ms) for QSM measurement of basal ganglia nuclei in the healthy brain.
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Affiliation(s)
- Wenping Fan
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - Xue Wang
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - Xingwen Zhang
- Department of Neurology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
| | - Mengqi Liu
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China,Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
| | - Qinglin Meng
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - Zhiye Chen
- Department of Radiology, Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China,Department of Radiology, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
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193
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Bossoni L, Hegeman-Kleinn I, van Duinen SG, Bulk M, Vroegindeweij LHP, Langendonk JG, Hirschler L, Webb A, van der Weerd L. Off-resonance saturation as an MRI method to quantify mineral- iron in the post-mortem brain. Magn Reson Med 2021; 87:1276-1288. [PMID: 34655092 PMCID: PMC9293166 DOI: 10.1002/mrm.29041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 09/17/2021] [Accepted: 09/20/2021] [Indexed: 12/24/2022]
Abstract
Purpose To employ an off‐resonance saturation method to measure the mineral‐iron pool in the postmortem brain, which is an endogenous contrast agent that can give information on cellular iron status. Methods An off‐resonance saturation acquisition protocol was implemented on a 7 Tesla preclinical scanner, and the contrast maps were fitted to an established analytical model. The method was validated by correlation and Bland‐Altman analysis on a ferritin‐containing phantom. Mineral‐iron maps were obtained from postmortem tissue of patients with neurological diseases characterized by brain iron accumulation, that is, Alzheimer disease, Huntington disease, and aceruloplasminemia, and validated with histology. Transverse relaxation rate and magnetic susceptibility values were used for comparison. Results In postmortem tissue, the mineral‐iron contrast colocalizes with histological iron staining in all the cases. Iron concentrations obtained via the off‐resonance saturation method are in agreement with literature. Conclusions Off‐resonance saturation is an effective way to detect iron in gray matter structures and partially mitigate for the presence of myelin. If a reference region with little iron is available in the tissue, the method can produce quantitative iron maps. This method is applicable in the study of diseases characterized by brain iron accumulation and can complement existing iron‐sensitive parametric methods.
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Affiliation(s)
- Lucia Bossoni
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Sjoerd G van Duinen
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marjolein Bulk
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Neurology, Alzheimer Center, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lena H P Vroegindeweij
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Janneke G Langendonk
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Porphyria Center Rotterdam, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lydiane Hirschler
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Andrew Webb
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Louise van der Weerd
- C. J. Gorter Center for High field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
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194
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Lee H, Cho H, Lee MJ, Kim TH, Roh J, Lee JH. Differential Effect of Iron and Myelin on Susceptibility MRI in the Substantia Nigra. Radiology 2021; 301:682-691. [PMID: 34609198 DOI: 10.1148/radiol.2021210116] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background The heterogeneous composition of substantia nigra (SN), including iron, nigrosome-1 substructure, and myelinated white matter, complicates the interpretation of MRI signals. Purpose To investigate R2* and quantitative susceptibility mapping (QSM) in the SN subdivisions of participants with Parkinson disease and healthy control subjects. Materials and Methods In this prospective study conducted from November 2018 to November 2019, participants with Parkinson disease and sex-matched healthy control subjects underwent 3-T MRI. R2* and QSM values were measured and compared in the anterior SN and posterior SN at the rostral (superior) and caudal (inferior) levels. Postmortem MRI and histology correlation of midbrain tissues was evaluated to investigate the effect of myelin and iron in the SN on R2* and QSM values. Results Forty individuals were evaluated: 20 healthy control subjects (mean age, 61 years ± 3 [standard deviation]; 10 men) and 20 participants with Parkinson disease (mean age, 61 years ± 4; 10 men). The R2* values of participants with Parkinson disease were higher in all subdivisions of the SN compared with R2* values in healthy control subjects (all P < .05). For QSM, no evidence of a difference was found in the rostral posterior SN (healthy control subjects, 54.1 ppb ± 21.0; Parkinson disease, 62.2 ppb ± 19.8; P = .49). The combination of rostral R2* and caudal QSM values resulted in an area under the receiver operating characteristic curve of 0.84. R2* values showed higher correlation with QSM values at the caudal level than at the rostral level within each group (all P < .001). Postmortem investigation demonstrated that R2* and QSM values showed weak correlation in the myelin-rich areas (r = 0.22 and r = 0.36, P < .001) and strong correlation in myelin-scanty areas (r ranged from approximately 0.52 to approximately 0.78, P < .001) in the SN. Conclusion Considering the iron and myelin distribution in the substantia nigra subdivisions, the subdivisional analysis of substantia nigra using R2* and quantitative susceptibility mapping might aid in specifically differentiating individuals with Parkinson disease from healthy control subjects. © RSNA, 2021 Online supplemental material is available for this article.
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Affiliation(s)
- Hansol Lee
- From the Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea (H.L., H.J.C.); Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan, South Korea (M.J.L); and Research Institute for Convergence of Biomedical Science and Technology (T.H.K.) and Departments of Radiology (J.R.) and Neurology (J.H.L.), Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, 20 Geumo-ro, Mulgeum-eup, Yangsan-si, Gyeongsangnam-do, South Korea
| | - HyungJoon Cho
- From the Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea (H.L., H.J.C.); Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan, South Korea (M.J.L); and Research Institute for Convergence of Biomedical Science and Technology (T.H.K.) and Departments of Radiology (J.R.) and Neurology (J.H.L.), Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, 20 Geumo-ro, Mulgeum-eup, Yangsan-si, Gyeongsangnam-do, South Korea
| | - Myung Jun Lee
- From the Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea (H.L., H.J.C.); Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan, South Korea (M.J.L); and Research Institute for Convergence of Biomedical Science and Technology (T.H.K.) and Departments of Radiology (J.R.) and Neurology (J.H.L.), Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, 20 Geumo-ro, Mulgeum-eup, Yangsan-si, Gyeongsangnam-do, South Korea
| | - Tae-Hyung Kim
- From the Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea (H.L., H.J.C.); Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan, South Korea (M.J.L); and Research Institute for Convergence of Biomedical Science and Technology (T.H.K.) and Departments of Radiology (J.R.) and Neurology (J.H.L.), Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, 20 Geumo-ro, Mulgeum-eup, Yangsan-si, Gyeongsangnam-do, South Korea
| | - Jieun Roh
- From the Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea (H.L., H.J.C.); Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan, South Korea (M.J.L); and Research Institute for Convergence of Biomedical Science and Technology (T.H.K.) and Departments of Radiology (J.R.) and Neurology (J.H.L.), Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, 20 Geumo-ro, Mulgeum-eup, Yangsan-si, Gyeongsangnam-do, South Korea
| | - Jae-Hyeok Lee
- From the Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea (H.L., H.J.C.); Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan, South Korea (M.J.L); and Research Institute for Convergence of Biomedical Science and Technology (T.H.K.) and Departments of Radiology (J.R.) and Neurology (J.H.L.), Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, 20 Geumo-ro, Mulgeum-eup, Yangsan-si, Gyeongsangnam-do, South Korea
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Jang J, Nam Y, Jung SW, Riew TR, Kim SH, Kim IB. Paradoxical paramagnetic calcifications in the globus pallidus: An ex vivo MR investigation and histological validation study. NMR IN BIOMEDICINE 2021; 34:e4571. [PMID: 34129267 DOI: 10.1002/nbm.4571] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 04/12/2021] [Accepted: 05/26/2021] [Indexed: 06/12/2023]
Abstract
MR images based on phase contrast images have gained clinical interest as an in vivo tool for assessing anatomical and histological findings. The globus pallidus is an area of major iron metabolism and storage in the brain tissue. Calcium, another important metal in the body, is frequently deposited in the globus pallidus as well. Recently, we observed dense paramagnetic deposition with paradoxical calcifications in the globus pallidus and putamen. In this work, we explore detailed MR findings on these structures, and the histological source of the related findings using ex vivo CT and MR images. Ex vivo MR was obtained with a maximum 100 μm3 isotropic resolution using a 15.2 T MR system. 3D gradient echo images and quantitative susceptibility mapping were used because of their good sensitivity to metallic deposition, high signal-to-noise ratio, and excellent contrast to iron and calcium. We found dense paramagnetic deposition along the perforating arteries in the globus pallidus. This paramagnetic deposition was hyperdense on ex vivo CT scans. Histological studies confirmed this finding, and simultaneous deposition of iron and calcium, although more iron dominant, was observed along the vessel walls of the globus pallidus. This was an exclusive finding for the penetrating arteries of the globus pallidus. Thus, our results suggest that several strong and paradoxical paramagnetic sources at the globus pallidus can be associated with vascular degeneration.
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Affiliation(s)
- Jinhee Jang
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Yoonho Nam
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Gyeonggi-do, South Korea
| | - Sung Won Jung
- Department of Anatomy, Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Tae-Ryong Riew
- Department of Anatomy, Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, South Korea
- Catholic Neuroscience Institute, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Sang Hyun Kim
- Department of Anatomy, Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - In-Beom Kim
- Department of Anatomy, Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, South Korea
- Catholic Neuroscience Institute, College of Medicine, The Catholic University of Korea, Seoul, South Korea
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196
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Zimmer TS, David B, Broekaart DWM, Schidlowski M, Ruffolo G, Korotkov A, van der Wel NN, van Rijen PC, Mühlebner A, van Hecke W, Baayen JC, Idema S, François L, van Eyll J, Dedeurwaerdere S, Kessels HW, Surges R, Rüber T, Gorter JA, Mills JD, van Vliet EA, Aronica E. Seizure-mediated iron accumulation and dysregulated iron metabolism after status epilepticus and in temporal lobe epilepsy. Acta Neuropathol 2021; 142:729-759. [PMID: 34292399 PMCID: PMC8423709 DOI: 10.1007/s00401-021-02348-6] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 07/02/2021] [Accepted: 07/12/2021] [Indexed: 12/12/2022]
Abstract
Neuronal dysfunction due to iron accumulation in conjunction with reactive oxygen species (ROS) could represent an important, yet underappreciated, component of the epileptogenic process. However, to date, alterations in iron metabolism in the epileptogenic brain have not been addressed in detail. Iron-related neuropathology and antioxidant metabolic processes were investigated in resected brain tissue from patients with temporal lobe epilepsy and hippocampal sclerosis (TLE-HS), post-mortem brain tissue from patients who died after status epilepticus (SE) as well as brain tissue from the electrically induced SE rat model of TLE. Magnetic susceptibility of the presumed seizure-onset zone from three patients with focal epilepsy was compared during and after seizure activity. Finally, the cellular effects of iron overload were studied in vitro using an acute mouse hippocampal slice preparation and cultured human fetal astrocytes. While iron-accumulating neurons had a pyknotic morphology, astrocytes appeared to acquire iron-sequestrating capacity as indicated by prominent ferritin expression and iron retention in the hippocampus of patients with SE or TLE. Interictal to postictal comparison revealed increased magnetic susceptibility in the seizure-onset zone of epilepsy patients. Post-SE rats had consistently higher hippocampal iron levels during the acute and chronic phase (when spontaneous recurrent seizures are evident). In vitro, in acute slices that were exposed to iron, neurons readily took up iron, which was exacerbated by induced epileptiform activity. Human astrocyte cultures challenged with iron and ROS increased their antioxidant and iron-binding capacity, but simultaneously developed a pro-inflammatory phenotype upon chronic exposure. These data suggest that seizure-mediated, chronic neuronal iron uptake might play a role in neuronal dysfunction/loss in TLE-HS. On the other hand, astrocytes sequester iron, specifically in chronic epilepsy. This function might transform astrocytes into a highly resistant, pro-inflammatory phenotype potentially contributing to pro-epileptogenic inflammatory processes.
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Affiliation(s)
- Till S Zimmer
- Department of (Neuro)Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Bastian David
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Diede W M Broekaart
- Department of (Neuro)Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Martin Schidlowski
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Gabriele Ruffolo
- Laboratory affiliated to Istituto Pasteur Italia, Department of Physiology and Pharmacology, University of Rome Sapienza, Rome, Italy
| | - Anatoly Korotkov
- Department of (Neuro)Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - Nicole N van der Wel
- Department Cell Biology and Histology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department Electron Microscopy Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Peter C van Rijen
- Department of Neurosurgery, Brain Centre, Rudolf Magnus Institute for Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Angelika Mühlebner
- Department of (Neuro)Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Wim van Hecke
- Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Johannes C Baayen
- Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Sander Idema
- Department of Neurosurgery, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Liesbeth François
- Neurosciences Therapeutic Area, UCB Pharma, Braine-l'Alleud, Belgium
| | - Jonathan van Eyll
- Neurosciences Therapeutic Area, UCB Pharma, Braine-l'Alleud, Belgium
| | | | - Helmut W Kessels
- Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Rainer Surges
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Theodor Rüber
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Jan A Gorter
- Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - James D Mills
- Department of (Neuro)Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Department of Clinical and Experimental Epilepsy, UCL, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Erwin A van Vliet
- Department of (Neuro)Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Eleonora Aronica
- Department of (Neuro)Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands.
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197
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Liu Y, Xiao B, Zhang C, Li J, Lai Y, Shi F, Shen D, Wang L, Sun B, Li Y, Jin Z, Wei H, Haacke EM, Zhou H, Wang Q, Li D, He N, Yan F. Predicting Motor Outcome of Subthalamic Nucleus Deep Brain Stimulation for Parkinson's Disease Using Quantitative Susceptibility Mapping and Radiomics: A Pilot Study. Front Neurosci 2021; 15:731109. [PMID: 34557069 PMCID: PMC8452872 DOI: 10.3389/fnins.2021.731109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 08/17/2021] [Indexed: 12/02/2022] Open
Abstract
Background Emerging evidence indicates that iron distribution is heterogeneous within the substantia nigra (SN) and it may reflect patient-specific trait of Parkinson’s Disease (PD). We assume it could account for variability in motor outcome of subthalamic nucleus deep brain stimulation (STN-DBS) in PD. Objective To investigate whether SN susceptibility features derived from radiomics with machine learning (RA-ML) can predict motor outcome of STN-DBS in PD. Methods Thirty-three PD patients underwent bilateral STN-DBS were recruited. The bilateral SN were segmented based on preoperative quantitative susceptibility mapping to extract susceptibility features using RA-ML. MDS-UPDRS III scores were recorded 1–3 days before and 6 months after STN-DBS surgery. Finally, we constructed three predictive models using logistic regression analyses: (1) the RA-ML model based on radiomics features, (2) the RA-ML+LCT (levodopa challenge test) response model which combined radiomics features with preoperative LCT response, (3) the LCT response model alone. Results For the predictive performances of global motor outcome, the RA-ML model had 82% accuracy (AUC = 0.85), while the RA-ML+LCT response model had 74% accuracy (AUC = 0.83), and the LCT response model alone had 58% accuracy (AUC = 0.55). For the predictive performance of rigidity outcome, the accuracy of the RA-ML model was 80% (AUC = 0.85), superior to those of the RA-ML+LCT response model (76% accuracy, AUC = 0.82), and the LCT response model alone (58% accuracy, AUC = 0.42). Conclusion Our findings demonstrated that SN susceptibility features from radiomics could predict global motor and rigidity outcomes of STN-DBS in PD. This RA-ML predictive model might provide a novel approach to counsel candidates for STN-DBS.
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Affiliation(s)
- Yu Liu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bin Xiao
- School of Biomedical Engineering, Institute for Medical Imaging Technology, Shanghai Jiao Tong University, Shanghai, China
| | - Chencheng Zhang
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junchen Li
- Department of Radiology, Changshu Hospital Affiliated to Nanjing University of Chinese Medicine, Changshu, China
| | - Yijie Lai
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Feng Shi
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Dinggang Shen
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China.,School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.,Department of Artificial Intelligence, Korea University, Seoul, South Korea
| | - Linbin Wang
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bomin Sun
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Li
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhijia Jin
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Ewart Mark Haacke
- Department of Radiology, Wayne State University, Detroit, MI, United States
| | - Haiyan Zhou
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qian Wang
- School of Biomedical Engineering, Institute for Medical Imaging Technology, Shanghai Jiao Tong University, Shanghai, China
| | - Dianyou Li
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Naying He
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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198
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Lorio S, Sedlacik J, So PW, Parkes HG, Gunny R, Löbel U, Li YF, Ogunbiyi O, Mistry T, Dixon E, Adler S, Cross JH, Baldeweg T, Jacques TS, Shmueli K, Carmichael DW. Quantitative MRI susceptibility mapping reveals cortical signatures of changes in iron, calcium and zinc in malformations of cortical development in children with drug-resistant epilepsy. Neuroimage 2021; 238:118102. [PMID: 34058334 PMCID: PMC8350142 DOI: 10.1016/j.neuroimage.2021.118102] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 04/14/2021] [Accepted: 04/19/2021] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE Malformations of cortical development (MCD), including focal cortical dysplasia (FCD), are the most common cause of drug-resistant focal epilepsy in children. Histopathological lesion characterisation demonstrates abnormal cell types and lamination, alterations in myelin (typically co-localised with iron), and sometimes calcification. Quantitative susceptibility mapping (QSM) is an emerging MRI technique that measures tissue magnetic susceptibility (χ) reflecting it's mineral composition. We used QSM to investigate abnormal tissue composition in a group of children with focal epilepsy with comparison to effective transverse relaxation rate (R2*) and Synchrotron radiation X-ray fluorescence (SRXRF) elemental maps. Our primary hypothesis was that reductions in χ would be found in FCD lesions, resulting from alterations in their iron and calcium content. We also evaluated deep grey matter nuclei for changes in χ with age. METHODS QSM and R2* maps were calculated for 40 paediatric patients with suspected MCD (18 histologically confirmed) and 17 age-matched controls. Patients' sub-groups were defined based on concordant electro-clinical or histopathology data. Quantitative investigation of QSM and R2* was performed within lesions, using a surface-based approach with comparison to homologous regions, and within deep brain regions using a voxel-based approach with regional values modelled with age and epilepsy as covariates. Synchrotron radiation X-ray fluorescence (SRXRF) was performed on brain tissue resected from 4 patients to map changes in iron, calcium and zinc and relate them to MRI parameters. RESULTS Compared to fluid-attenuated inversion recovery (FLAIR) or T1-weighted imaging, QSM improved lesion conspicuity in 5% of patients. In patients with well-localised lesions, quantitative profiling demonstrated decreased χ, but not R2*, across cortical depth with respect to the homologous regions. Contra-lateral homologous regions additionally exhibited increased χ at 2-3 mm cortical depth that was absent in lesions. The iron decrease measured by the SRXRF in FCDIIb lesions was in agreement with myelin reduction observed by Luxol Fast Blue histochemical staining. SRXRF analysis in two FCDIIb tissue samples showed increased zinc and calcium in one patient, and decreased iron in the brain region exhibiting low χ and high R2* in both patients. QSM revealed expected age-related changes in the striatum nuclei, substantia nigra, sub-thalamic and red nucleus. CONCLUSION QSM non-invasively revealed cortical/sub-cortical tissue alterations in MCD lesions and in particular that χ changes in FCDIIb lesions were consistent with reduced iron, co-localised with low myelin and increased calcium and zinc content. These findings suggest that measurements of cortical χ could be used to characterise tissue properties non-invasively in epilepsy lesions.
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Affiliation(s)
- Sara Lorio
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK; Wellcome EPSRC Centre for Medical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London SE1 7EH, UK
| | - Jan Sedlacik
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Po-Wah So
- Department of Neuroimaging, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Harold G Parkes
- Department of Neuroimaging, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Roxana Gunny
- Department of Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Ulrike Löbel
- Department of Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Yao-Feng Li
- Developmental Biology and Cancer Programme, UCL Great Ormond Street Institute of Child Health, University College London and Department of Histopathology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK; Pathology Department, Tri-Service General Hospital and National Defence Medical Centre, Taipei, Taiwan, ROC
| | - Olumide Ogunbiyi
- Developmental Biology and Cancer Programme, UCL Great Ormond Street Institute of Child Health, University College London and Department of Histopathology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Talisa Mistry
- Developmental Biology and Cancer Programme, UCL Great Ormond Street Institute of Child Health, University College London and Department of Histopathology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Emma Dixon
- MRI Group, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Sophie Adler
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - J Helen Cross
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Torsten Baldeweg
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Thomas S Jacques
- Developmental Biology and Cancer Programme, UCL Great Ormond Street Institute of Child Health, University College London and Department of Histopathology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Karin Shmueli
- MRI Group, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - David W Carmichael
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK; Wellcome EPSRC Centre for Medical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London SE1 7EH, UK.
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199
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Chen Q, Boeve BF, Forghanian-Arani A, Senjem ML, Jack CR, Przybelski SA, Lesnick TG, Kremers WK, Fields JA, Schwarz CG, Gunter JL, Trzasko JD, Graff-Radford J, Savica R, Knopman DS, Dickson DW, Ferman TJ, Graff-Radford N, Petersen RC, Kantarci K. MRI quantitative susceptibility mapping of the substantia nigra as an early biomarker for Lewy body disease. J Neuroimaging 2021; 31:1020-1027. [PMID: 34033185 PMCID: PMC8440493 DOI: 10.1111/jon.12878] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/10/2021] [Accepted: 05/01/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND AND PURPOSE Neurodegeneration of the substantia nigra in Lewy body disease is associated with iron deposition, which increases the magnetic susceptibility of the substantia nigra on MRI. Our objective was to measure iron deposition in the substantia nigra in patients with probable dementia with Lewy bodies (pDLB) and patients who are at risk for pDLB by quantitative susceptibility mapping (QSM). METHODS Participants included pDLB (n = 36), mild cognitive impairment with at least one core feature of DLB (MCI-LB; n = 15), idiopathic rapid eye movement sleep behavior disorder (iRBD; n = 11), and an age-and gender-matched clinically unimpaired control group (n = 102). QSM was derived from multi-echo 3D gradient recalled echo MRI at 3T, and groups were compared on mean susceptibility values of the substantia nigra and its relation to parkinsonism severity. RESULTS Patients with pDLB had higher susceptibility in the substantia nigra compared to controls (p< 0.001) and MCI-LB (p = 0.043). The susceptibility of substantia nigra showed an increasing trend from controls to iRBD and MCI-LB, and to pDLB (p< 0.001). Parkinsonism severity was not associated with the mean susceptibility in the substantia nigra in the patient groups. CONCLUSIONS Our data suggested that QSM is sensitive to the increased magnetic susceptibility due to higher iron content in the substantia nigra in pDLB. The trend of increasing susceptibility from controls to iRBD and MCI-LB, and to pDLB suggests that iron deposition in the substantia nigra starts to increase as early as the prodromal stage in DLB and continues to increase as the disease progresses, independent of parkinsonism severity.
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Affiliation(s)
- Qin Chen
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | | | - Scott A. Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Timothy G. Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Walter K. Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Julie A. Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | | | - Rodolfo Savica
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | | | | | - Tanis J. Ferman
- Department of Psychology and Psychiatry, Mayo Clinic, Jacksonville, Florida
| | | | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
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200
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Bilgic B, Langkammer C, Marques JP, Meineke J, Milovic C, Schweser F. QSM reconstruction challenge 2.0: Design and report of results. Magn Reson Med 2021; 86:1241-1255. [PMID: 33783037 DOI: 10.1002/mrm.28754] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 01/25/2021] [Accepted: 02/08/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE The aim of the second quantitative susceptibility mapping (QSM) reconstruction challenge (Oct 2019, Seoul, Korea) was to test the accuracy of QSM dipole inversion algorithms in simulated brain data. METHODS A two-stage design was chosen for this challenge. The participants were provided with datasets of multi-echo gradient echo images synthesized from two realistic in silico head phantoms using an MR simulator. At the first stage, participants optimized QSM reconstructions without ground truth data available to mimic the clinical setting. At the second stage, ground truth data were provided for parameter optimization. Submissions were evaluated using eight numerical metrics and visual ratings. RESULTS A total of 98 reconstructions were submitted for stage 1 and 47 submissions for stage 2. Iterative methods had the best quantitative metric scores, followed by deep learning and direct inversion methods. Priors derived from magnitude data improved the metric scores. Algorithms based on iterative approaches and total variation (and its derivatives) produced the best overall results. The reported results and analysis pipelines have been made public to allow researchers to compare new methods to the current state of the art. CONCLUSION The synthetic data provide a consistent framework to test the accuracy and robustness of QSM algorithms in the presence of noise, calcifications and minor voxel dephasing effects. Total Variation-based algorithms produced the best results among all metrics. Future QSM challenges should assess whether this good performance with synthetic datasets translates to more realistic scenarios, where background fields and dipole-incompatible phase contributions are included.
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Affiliation(s)
- Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA
| | | | - José P Marques
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands
| | | | - Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Ferdinand Schweser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, USA
- Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, New York, USA
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