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Zhang R, Zhang Q, Ji A, Lv P, Acosta-Cabronero J, Fu C, Ding J, Guo D, Teng Z, Lin J. Prediction of new cerebral ischemic lesion after carotid artery stenting: a high-resolution vessel wall MRI-based radiomics analysis. Eur Radiol 2022; 33:4115-4126. [PMID: 36472695 DOI: 10.1007/s00330-022-09302-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/15/2022] [Accepted: 11/15/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVES Carotid artery stenting (CAS) is an established treatment for local stenosis. The most common complication is new ipsilateral ischemic lesions (NIILs). This study aimed to develop models considering lesion morphological and compositional features, and radiomics to predict NIILs. MATERIALS AND METHODS One hundred and forty-six patients who underwent brain MRI and high-resolution vessel wall MR imaging (hrVWI) before and after CAS were retrospectively recruited. Lumen and outer wall boundaries were segmented on hrVWI as well as atherosclerotic components. A traditional model was constructed with patient clinical information, and lesion morphological and compositional features. Least absolute shrinkage and selection operator algorithm was performed to determine key radiomics features for reconstructing a radiomics model. The model in predicting NIILs was trained and its performance was tested. RESULTS Sixty-one patients were NIIL-positive and eighty-five negative. Volume percentage of intraplaque hemorrhage (IPH) and patients' clinical presentation (symptomatic/asymptomatic) were risk factors of NIILs. The traditional model considering these two features achieved an area under the curve (AUC) of 0.778 and 0.777 in the training and test cohorts, respectively. Twenty-two key radiomics features were identified and the model based on these features achieved an AUC of 0.885 and 0.801 in the two cohorts. The AUCs of the combined model considering IPH volume percentage, clinical presentation, and radiomics features were 0.893 and 0.842 in the training and test cohort respectively. CONCLUSIONS Compared with traditional features (clinical and compositional features), the combination of traditional and radiomics features improved the power in predicting NIILs after CAS. KEY POINTS • Volume percentage of IPH and symptomatic events were independent risk factors of new ipsilateral ischemic lesions (NIILs). • Radiomics features derived from carotid artery high-resolution vessel wall imaging had great potential in predicting NIILs after CAS. • The combination model with radiomics and traditional features further improved the diagnostic performance than traditional features alone.
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Affiliation(s)
- Ranying Zhang
- Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, Shanghai, China
| | - Qingwei Zhang
- Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, 145 Middle Shandong Road, Shanghai, China
| | - Aihua Ji
- Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, Shanghai, China
| | - Peng Lv
- Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, Shanghai, China
| | | | - Caixia Fu
- MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | - Jing Ding
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Daqiao Guo
- Department of Vascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhongzhao Teng
- Department of Radiology, University of Cambridge, Cambridge, UK.
- Nanjing Jingsan Medical Science and Technology, Nanjing, China.
| | - Jiang Lin
- Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, Shanghai, China.
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Shribman S, Burrows M, Convery R, Bocchetta M, Sudre CH, Acosta-Cabronero J, Thomas DL, Gillett GT, Tsochatzis EA, Bandmann O, Rohrer JD, Warner TT. Neuroimaging Correlates of Cognitive Deficits in Wilson's Disease. Mov Disord 2022; 37:1728-1738. [PMID: 35723521 PMCID: PMC9542291 DOI: 10.1002/mds.29123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 05/19/2022] [Accepted: 05/23/2022] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Cognitive impairment is common in neurological presentations of Wilson's disease (WD). Various domains can be affected, and subclinical deficits have been reported in patients with hepatic presentations. Associations with imaging abnormalities have not been systematically tested. OBJECTIVE The aim was to determine the neuroanatomical basis for cognitive deficits in WD. METHODS We performed a 16-item neuropsychological test battery and magnetic resonance brain imaging in 40 patients with WD. The scores for each test were compared between patients with neurological and hepatic presentations and with normative data. Associations with Unified Wilson's Disease Rating Scale neurological examination subscores were examined. Quantitative, whole-brain, multimodal imaging analyses were used to identify associations with neuroimaging abnormalities in chronically treated stable patients. RESULTS Abstract reasoning, executive function, processing speed, calculation, and visuospatial function scores were lower in patients with neurological presentations than in those with hepatic presentations and correlated with neurological examination subscores. Deficits in abstract reasoning and phonemic fluency were associated with lower putamen volumes even after controlling for neurological severity. About half of patients with hepatic presentations had poor performance in memory for faces, cognitive flexibility, or associative learning relative to normative data. These deficits were associated with widespread cortical atrophy and/or white matter diffusion abnormalities. CONCLUSIONS Subtle cognitive deficits in patients with seemingly hepatic presentations represent a distinct neurological phenotype associated with diffuse cortical and white matter pathology. This may precede the classical neurological phenotype characterized by movement disorders and executive dysfunction and be associated with basal ganglia damage. A binary phenotypic classification for WD may no longer be appropriate. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Samuel Shribman
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London
| | - Maggie Burrows
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London
| | - Rhian Convery
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Martina Bocchetta
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom.,Centre for Medical Image Computing, University College London, London, United Kingdom.,Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | | | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, United Kingdom.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Godfrey T Gillett
- Department of Clinical Chemistry, Northern General Hospital, Sheffield, United Kingdom
| | - Emmanuel A Tsochatzis
- UCL Institute of Liver and Digestive Health and Royal Free Hospital, London, United Kingdom
| | - Oliver Bandmann
- Sheffield Institute of Translational Neuroscience, Sheffield, United Kingdom
| | - Jonathan D Rohrer
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Thomas T Warner
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London
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Shribman S, Bocchetta M, Sudre CH, Acosta-Cabronero J, Burrows M, Cook P, Thomas DL, Gillett GT, Tsochatzis EA, Bandmann O, Rohrer JD, Warner TT. Neuroimaging correlates of brain injury in Wilson's disease: a multimodal, whole-brain MRI study. Brain 2022; 145:263-275. [PMID: 34289020 PMCID: PMC8967100 DOI: 10.1093/brain/awab274] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 06/25/2021] [Accepted: 07/04/2021] [Indexed: 11/23/2022] Open
Abstract
Wilson's disease is an autosomal-recessive disorder of copper metabolism with neurological and hepatic presentations. Chelation therapy is used to 'de-copper' patients but neurological outcomes remain unpredictable. A range of neuroimaging abnormalities have been described and may provide insights into disease mechanisms, in addition to prognostic and monitoring biomarkers. Previous quantitative MRI analyses have focused on specific sequences or regions of interest, often stratifying chronically treated patients according to persisting symptoms as opposed to initial presentation. In this cross-sectional study, we performed a combination of unbiased, whole-brain analyses on T1-weighted, fluid-attenuated inversion recovery, diffusion-weighted and susceptibility-weighted imaging data from 40 prospectively recruited patients with Wilson's disease (age range 16-68). We compared patients with neurological (n = 23) and hepatic (n = 17) presentations to determine the neuroradiological sequelae of the initial brain injury. We also subcategorized patients according to recent neurological status, classifying those with neurological presentations or deterioration in the preceding 6 months as having 'active' disease. This allowed us to compare patients with active (n = 5) and stable (n = 35) disease and identify imaging correlates for persistent neurological deficits and copper indices in chronically treated, stable patients. Using a combination of voxel-based morphometry and region-of-interest volumetric analyses, we demonstrate that grey matter volumes are lower in the basal ganglia, thalamus, brainstem, cerebellum, anterior insula and orbitofrontal cortex when comparing patients with neurological and hepatic presentations. In chronically treated, stable patients, the severity of neurological deficits correlated with grey matter volumes in similar, predominantly subcortical regions. In contrast, the severity of neurological deficits did not correlate with the volume of white matter hyperintensities, calculated using an automated lesion segmentation algorithm. Using tract-based spatial statistics, increasing neurological severity in chronically treated patients was associated with decreasing axial diffusivity in white matter tracts whereas increasing serum non-caeruloplasmin-bound ('free') copper and active disease were associated with distinct patterns of increasing mean, axial and radial diffusivity. Whole-brain quantitative susceptibility mapping identified increased iron deposition in the putamen, cingulate and medial frontal cortices of patients with neurological presentations relative to those with hepatic presentations and neurological severity was associated with iron deposition in widespread cortical regions in chronically treated patients. Our data indicate that composite measures of subcortical atrophy provide useful prognostic biomarkers, whereas abnormal mean, axial and radial diffusivity are promising monitoring biomarkers. Finally, deposition of brain iron in response to copper accumulation may directly contribute to neurodegeneration in Wilson's disease.
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Affiliation(s)
- Samuel Shribman
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London WC1N 1PJ, UK
| | - Martina Bocchetta
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing, University College London, London WC1E 7HB, UK
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
- Biomedical Engineering and Imaging Sciences, King’s College London, London WC2R 2LS, UK
| | | | - Maggie Burrows
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London WC1N 1PJ, UK
| | - Paul Cook
- Department of Clinical Biochemistry, Southampton General Hospital, Southampton SO16 6YD, UK
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3AR, UK
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Godfrey T Gillett
- Department of Clinical Chemistry, Northern General Hospital, Sheffield S5 7AU, UK
| | - Emmanuel A Tsochatzis
- UCL Institute of Liver and Digestive Health and Royal Free Hospital, London NW3 2PF, UK
| | - Oliver Bandmann
- Sheffield Institute of Translational Neuroscience, Sheffield S10 2HQ, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Thomas T Warner
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London WC1N 1PJ, UK
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Thomas GEC, Zarkali A, Ryten M, Shmueli K, Gil-Martinez AL, Leyland LA, McColgan P, Acosta-Cabronero J, Lees AJ, Weil RS. Regional brain iron and gene expression provide insights into neurodegeneration in Parkinson's disease. Brain 2021; 144:1787-1798. [PMID: 33704443 PMCID: PMC8320305 DOI: 10.1093/brain/awab084] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 11/20/2020] [Accepted: 12/14/2020] [Indexed: 12/11/2022] Open
Abstract
The mechanisms responsible for the selective vulnerability of specific neuronal populations in Parkinson's disease are poorly understood. Oxidative stress secondary to brain iron accumulation is one postulated mechanism. We measured iron deposition in 180 cortical regions of 96 patients with Parkinson's disease and 35 control subjects using quantitative susceptibility mapping. We estimated the expression of 15 745 genes in the same regions using transcriptomic data from the Allen Human Brain Atlas. Using partial least squares regression, we then identified the profile of gene transcription in the healthy brain that underlies increased cortical iron in patients with Parkinson's disease relative to controls. Applying gene ontological tools, we investigated the biological processes and cell types associated with this transcriptomic profile and identified the sets of genes with spatial expression profiles in control brains that correlated significantly with the spatial pattern of cortical iron deposition in Parkinson's disease. Gene ontological analyses revealed that these genes were enriched for biological processes relating to heavy metal detoxification, synaptic function and nervous system development and were predominantly expressed in astrocytes and glutamatergic neurons. Furthermore, we demonstrated that the genes differentially expressed in Parkinson's disease are associated with the pattern of cortical expression identified in this study. Our findings provide mechanistic insights into regional selective vulnerabilities in Parkinson's disease, particularly the processes involving iron accumulation.
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Affiliation(s)
| | | | - Mina Ryten
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1B 5EH, UK
- NIHR Great Ormond Street Hospital Biomedical Research Centre, UCL, London, WC1N 1EH, UK
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, UCL, London, WC1N 1EH, UK
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, Malet Place Engineering Building, UCL, London, WC1E 6BT, UK
| | - Ana Luisa Gil-Martinez
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1B 5EH, UK
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, UCL, London, WC1N 1EH, UK
| | | | - Peter McColgan
- Huntington’s Disease Centre, UCL Institute of Neurology, London, WC1B 5EH, UK
| | | | - Andrew J Lees
- Reta Lila Weston Institute of Neurological Studies, London, WC1N 1PJ, UK
| | - Rimona S Weil
- Dementia Research Centre, UCL, London, WC1N 3AR, UK
- Wellcome Centre for Human Neuroimaging, UCL, London, WC1N 3AR, UK
- Movement Disorders Consortium, UCL, London, WC1N 3BG, UK
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Lüsebrink F, Mattern H, Yakupov R, Acosta-Cabronero J, Ashtarayeh M, Oeltze-Jafra S, Speck O. Comprehensive ultrahigh resolution whole brain in vivo MRI dataset as a human phantom. Sci Data 2021; 8:138. [PMID: 34035308 PMCID: PMC8149725 DOI: 10.1038/s41597-021-00923-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 04/13/2021] [Indexed: 11/09/2022] Open
Abstract
Here, we present an extension to our previously published structural ultrahigh resolution T1-weighted magnetic resonance imaging (MRI) dataset with an isotropic resolution of 250 µm, consisting of multiple additional ultrahigh resolution contrasts. Included are up to 150 µm Time-of-Flight angiography, an updated 250 µm structural T1-weighted reconstruction, 330 µm quantitative susceptibility mapping, up to 450 µm structural T2-weighted imaging, 700 µm T1-weighted back-to-back scans, 800 µm diffusion tensor imaging, one hour continuous resting-state functional MRI with an isotropic spatial resolution of 1.8 mm as well as more than 120 other structural T1-weighted volumes together with multiple corresponding proton density weighted acquisitions collected over ten years. All data are from the same participant and were acquired on the same 7 T scanner. The repository contains the unprocessed data as well as (pre-)processing results. The data were acquired in multiple studies with individual goals. This is a unique and comprehensive collection comprising a "human phantom" dataset. Therefore, we compiled, processed, and structured the data, making them publicly available for further investigation.
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Affiliation(s)
- Falk Lüsebrink
- Medicine and Digitalization, Department of Neurology, Medical Faculty, Otto-von-Guericke University, Magdeburg, Germany.
- Biomedical Magnetic Resonance, Faculty of Natural Sciences, Otto-von-Guericke University, Magdeburg, Germany.
| | - Hendrik Mattern
- Biomedical Magnetic Resonance, Faculty of Natural Sciences, Otto-von-Guericke University, Magdeburg, Germany
| | - Renat Yakupov
- German Center of Neurodegenerative Diseases (DZNE), site Magdeburg, Germany
| | | | - Mohammad Ashtarayeh
- Department of Systems Neuroscience, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Steffen Oeltze-Jafra
- Medicine and Digitalization, Department of Neurology, Medical Faculty, Otto-von-Guericke University, Magdeburg, Germany
- German Center of Neurodegenerative Diseases (DZNE), site Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Oliver Speck
- Biomedical Magnetic Resonance, Faculty of Natural Sciences, Otto-von-Guericke University, Magdeburg, Germany
- German Center of Neurodegenerative Diseases (DZNE), site Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
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Dusek P, Lescinskij A, Ruzicka F, Acosta-Cabronero J, Bruha R, Sieger T, Hajek M, Dezortova M. Associations of Brain Atrophy and Cerebral Iron Accumulation at MRI with Clinical Severity in Wilson Disease. Radiology 2021; 299:662-672. [PMID: 33754827 DOI: 10.1148/radiol.2021202846] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background Abnormal findings at brain MRI in patients with neurologic Wilson disease (WD) are characterized by signal intensity changes and cerebral atrophy. T2 signal hypointensities and atrophy are largely irreversible with treatment; their relationship with permanent disability has not been systematically investigated. Purpose To investigate associations of regional brain atrophy and iron accumulation at MRI with clinical severity in participants with neurologic WD who are undergoing long-term anti-copper treatment. Materials and Methods Participants with WD and controls were compared in a prospective study performed from 2015 to 2019. MRI at 3.0 T included three-dimensional T1-weighted and six-echo multigradient-echo pulse sequences for morphometry and quantitative susceptibility mapping, respectively. Neurologic severity was assessed with the Unified WD Rating Scale (UWDRS). Automated multi-atlas segmentation pipeline with dual contrast (susceptibility and T1) was used for the calculation of volumes and mean susceptibilities in deep gray matter nuclei. Additionally, whole-brain analysis using deformation and surface-based morphometry was performed. Least absolute shrinkage and selection operator regression was used to assess the association of regional volumes and susceptibilities with the UWDRS score. Results Twenty-nine participants with WD (mean age, 47 years ± 9 [standard deviation]; 15 women) and 26 controls (mean age, 45 years ± 12; 14 women) were evaluated. Whole-brain analysis demonstrated atrophy of the deep gray matter nuclei, brainstem, internal capsule, motor cortex and corticospinal pathway, and visual cortex and optic radiation in participants with WD (P < .05 at voxel level, corrected for family-wise error). The UWDRS score was negatively correlated with volumes of putamen (r = -0.63, P < .001), red nucleus (r = -0.58, P = .001), globus pallidus (r = -0.53, P = .003), and substantia nigra (r = -0.50, P = .006) but not with susceptibilities. Only the putaminal volume was identified as a stable factor associated with the UWDRS score (R2 = 0.38, P < .001) using least absolute shrinkage and selection operator regression. Conclusion Individuals with Wilson disease (WD) had widespread brain atrophy most pronounced in the central structures. The putaminal volume was associated with the Unified WD Rating Scale score and can be used as a surrogate imaging marker of clinical severity. © RSNA, 2021 Supplemental material is available for this article. See also the editorial by Du and Bydder in this issue.
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Affiliation(s)
- Petr Dusek
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Artem Lescinskij
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Filip Ruzicka
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Julio Acosta-Cabronero
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Radan Bruha
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Tomas Sieger
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Milan Hajek
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
| | - Monika Dezortova
- From the Department of Radiology (P.D., A.L.), Department of Neurology and Centre of Clinical Neuroscience (P.D., F.R.) and Fourth Department of Internal Medicine (R.B.), First Faculty of Medicine, Charles University and General University Hospital, Katerinska 30, 120 00, Prague 2, Czech Republic; Tenoke, Cambridge, England (J.A.C.); Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic (T.S.); and Magnetic Resonance Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic (M.H., M.D.)
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Rotta J, Perosa V, Yakupov R, Kuijf HJ, Schreiber F, Dobisch L, Oltmer J, Assmann A, Speck O, Heinze HJ, Acosta-Cabronero J, Duzel E, Schreiber S. Detection of Cerebral Microbleeds With Venous Connection at 7-Tesla MRI. Neurology 2021; 96:e2048-e2057. [PMID: 33653897 DOI: 10.1212/wnl.0000000000011790] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Accepted: 01/28/2021] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE Cerebral microbleeds (MBs) are a common finding in patients with cerebral small vessel disease (CSVD) and Alzheimer disease as well as in healthy elderly people, but their pathophysiology remains unclear. To investigate a possible role of veins in the development of MBs, we performed an exploratory study, assessing in vivo presence of MBs with a direct connection to a vein. METHODS 7-Tesla (7T) MRI was conducted and MBs were counted on quantitative susceptibility mapping (QSM). A submillimeter resolution QSM-based venogram allowed identification of MBs with a direct spatial connection to a vein. RESULTS A total of 51 people (mean age [SD] 70.5 [8.6] years, 37% female) participated in the study: 20 had CSVD (cerebral amyloid angiopathy [CAA] with strictly lobar MBs [n = 8], hypertensive arteriopathy [HA] with strictly deep MBs [n = 5], or mixed lobar and deep MBs [n = 7], 72.4 [6.1] years, 30% female) and 31 were healthy controls (69.4 [9.9] years, 42% female). In our cohort, we counted a total of 96 MBs with a venous connection, representing 14% of all detected MBs on 7T QSM. Most venous MBs (86%, n = 83) were observed in lobar locations and all of these were cortical. Patients with CAA showed the highest ratio of venous to total MBs (19%) (HA = 9%, mixed = 18%, controls = 5%). CONCLUSION Our findings establish a link between cerebral MBs and the venous vasculature, pointing towards a possible contribution of veins to CSVD in general and to CAA in particular. Pathologic studies are needed to confirm our observations.
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Affiliation(s)
- Johanna Rotta
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Valentina Perosa
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK.
| | - Renat Yakupov
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Hugo J Kuijf
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Frank Schreiber
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Laura Dobisch
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Jan Oltmer
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Anne Assmann
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Oliver Speck
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Hans-Jochen Heinze
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Julio Acosta-Cabronero
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Emrah Duzel
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
| | - Stefanie Schreiber
- From the Department of Neurology (J.R., V.P., F.S., A.A., H.-J.H., S.S.) and Institute of Physics (O.S.), Otto-von-Guericke University; Institute of Cognitive Neurology and Dementia Research (IKND) (V.P., R.Y., J.O., H.-J.H., E.D.), Magdeburg, Germany; J. Philip Kistler Stroke Research Center (V.P.), Massachusetts General Hospital, Boston; German Center for Neurodegenerative Diseases (DZNE) (R.Y., F.S., L.D., O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands; Leibniz-Institute for Neurobiology (LIN) (O.S., H.-J.H., E.D.); Center for Behavioral Brain Sciences (CBBS) (O.S., H.-J.H., E.D., S.S.), Magdeburg, Germany; Tenoke Limited (J.A.-C.), Cambridge, UK; and Institute of Cognitive Neuroscience (E.D.), University College London, UK
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Liu KY, Acosta-Cabronero J, Hong YT, Yi YJ, Hämmerer D, Howard R. FDG-PET assessment of the locus coeruleus in Alzheimer's disease. Neuroimage Rep 2021; 1:100002. [PMID: 34396361 PMCID: PMC8262255 DOI: 10.1016/j.ynirp.2020.100002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 12/09/2020] [Accepted: 12/15/2020] [Indexed: 12/11/2022]
Abstract
Sensitive and reliable in vivo imaging of the locus coeruleus (LC) is important to develop and evaluate its potential as a biomarker in neurodegenerative diseases such as Alzheimer's disease (AD). It is not known whether AD-related alterations in LC integrity can be detected using 18F-labelled fluoro-2-deoxyglucose (FDG) positron emission tomography (PET). Mean FDG-PET images from AD patients (N = 193) and controls (N = 256) from the ADNI database were co-registered to a study-wise anatomical template. Regional LC median standardized uptake value ratio (SUVR) values were obtained using four previously published LC masks and normalized to values from pons and cerebellar vermis reference regions. To support the validity of our methods, other regions previously reported to be most and least affected metabolically in AD were also compared to controls. The LC did not show between-group differences in FDG-PET signal, whereas the mammillary bodies did, despite these regions having comparable volumes and SUVR ranges. Brain regions previously reported to be most and least affected metabolically in AD compared to controls showed medium-to-large and small effect sizes for SUVR differences respectively. The results do not support the current application of LC FDG-PET signal as an in vivo biomarker for AD. Methodological and demographic factors potentially contributing to these findings are discussed. Future research may investigate age-related differences in LC FDG-PET signal and higher resolution images to fully explore its biomarker potential.
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Affiliation(s)
- Kathy Y. Liu
- Division of Psychiatry, University College London, UK
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, UK
- Tenoke Ltd., Cambridge, UK
| | - Young T. Hong
- Wolfson Brain Imaging Centre, University of Cambridge, UK
| | - Yeo-Jin Yi
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Dorothea Hämmerer
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, UK
| | - Robert Howard
- Division of Psychiatry, University College London, UK
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Milovic C, Prieto C, Bilgic B, Uribe S, Acosta-Cabronero J, Irarrazaval P, Tejos C. Comparison of parameter optimization methods for quantitative susceptibility mapping. Magn Reson Med 2021; 85:480-494. [PMID: 32738103 PMCID: PMC7722179 DOI: 10.1002/mrm.28435] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 06/10/2020] [Accepted: 06/26/2020] [Indexed: 12/28/2022]
Abstract
PURPOSE Quantitative Susceptibility Mapping (QSM) is usually performed by minimizing a functional with data fidelity and regularization terms. A weighting parameter controls the balance between these terms. There is a need for techniques to find the proper balance that avoids artifact propagation and loss of details. Finding the point of maximum curvature in the L-curve is a popular choice, although it is slow, often unreliable when using variational penalties, and has a tendency to yield overregularized results. METHODS We propose 2 alternative approaches to control the balance between the data fidelity and regularization terms: 1) searching for an inflection point in the log-log domain of the L-curve, and 2) comparing frequency components of QSM reconstructions. We compare these methods against the conventional L-curve and U-curve approaches. RESULTS Our methods achieve predicted parameters that are better correlated with RMS error, high-frequency error norm, and structural similarity metric-based parameter optimizations than those obtained with traditional methods. The inflection point yields less overregularization and lower errors than traditional alternatives. The frequency analysis yields more visually appealing results, although with larger RMS error. CONCLUSION Our methods provide a robust parameter optimization framework for variational penalties in QSM reconstruction. The L-curve-based zero-curvature search produced almost optimal results for typical QSM acquisition settings. The frequency analysis method may use a 1.5 to 2.0 correction factor to apply it as a stand-alone method for a wider range of signal-to-noise-ratio settings. This approach may also benefit from fast search algorithms such as the binary search to speed up the process.
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Affiliation(s)
- Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
| | - Claudia Prieto
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Sergio Uribe
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
- Department of Radiology, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | | | - Pablo Irarrazaval
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
- Institute for Biological and Medical Engineering, Pontificia Universidad Catolica de Chile, 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 Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
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10
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Milovic C, Tejos C, Acosta-Cabronero J, Özbay PS, Schwesser F, Marques JP, Irarrazaval P, Bilgic B, Langkammer C. The 2016 QSM Challenge: Lessons learned and considerations for a future challenge design. Magn Reson Med 2020; 84:1624-1637. [PMID: 32086836 PMCID: PMC7526054 DOI: 10.1002/mrm.28185] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 11/09/2019] [Accepted: 01/06/2020] [Indexed: 11/06/2022]
Abstract
PURPOSE The 4th International Workshop on MRI Phase Contrast and QSM (2016, Graz, Austria) hosted the first QSM Challenge. A single-orientation gradient recalled echo acquisition was provided, along with COSMOS and the χ33 STI component as ground truths. The submitted solutions differed more than expected depending on the error metric used for optimization and were generally over-regularized. This raised (unanswered) questions about the ground truths and the metrics utilized. METHODS We investigated the influence of background field remnants by applying additional filters. We also estimated the anisotropic contributions from the STI tensor to the apparent susceptibility to amend the χ33 ground truth and to investigate the impact on the reconstructions. Lastly, we used forward simulations from the COSMOS reconstruction to investigate the impact noise had on the metric scores. RESULTS Reconstructions compared against the amended STI ground truth returned lower errors. We show that the background field remnants had a minor impact in the errors. In the absence of inconsistencies, all metrics converged to the same regularization weights, whereas structural similarity index metric was more insensitive to such inconsistencies. CONCLUSION There was a mismatch between the provided data and the ground truths due to the presence of unaccounted anisotropic susceptibility contributions and noise. Given the lack of reliable ground truths when using in vivo acquisitions, simulations are suggested for future QSM Challenges.
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Affiliation(s)
- Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, 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 Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
| | | | - Pinar Senay Özbay
- Laboratory of Functional and Molecular Imaging, National Institutes of Health, Bethesda, MD, USA
| | - Ferdinand Schwesser
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, The State University of New York, NY, USA
- Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, NY, USA
| | - Jose Pedro Marques
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Pablo Irarrazaval
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
- Institute for Biological and Medical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Berkin Bilgic
- Martinos Center for Biomedical Imaging, Harvard Medical School, MA, USA
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11
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Spotorno N, Acosta-Cabronero J, Stomrud E, Lampinen B, Strandberg OT, van Westen D, Hansson O. Relationship between cortical iron and tau aggregation in Alzheimer's disease. Brain 2020; 143:1341-1349. [PMID: 32330946 PMCID: PMC7241946 DOI: 10.1093/brain/awaa089] [Citation(s) in RCA: 87] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 02/05/2020] [Accepted: 02/10/2020] [Indexed: 12/14/2022] Open
Abstract
A growing body of evidence suggests that the dysregulation of neuronal iron may play a critical role in Alzheimer's disease. Recent MRI studies have established a relationship between iron accumulation and amyloid-β aggregation. The present study provides further insight demonstrating a relationship between iron and tau accumulation using magnetic resonance-based quantitative susceptibility mapping and tau-PET in n = 236 subjects with amyloid-β pathology (from the Swedish BioFINDER-2 study). Both voxel-wise and regional analyses showed a consistent association between differences in bulk magnetic susceptibility, which can be primarily ascribed to an increase in iron content, and tau-PET signal in regions known to be affected in Alzheimer's disease. Subsequent analyses revealed that quantitative susceptibility specifically mediates the relationship between tau-PET and cortical atrophy measures, thus suggesting a modulatory effect of iron burden on the disease process. We also found evidence suggesting the relationship between quantitative susceptibility and tau-PET is stronger in younger participants (age ≤ 65). Together, these results provide in vivo evidence of an association between iron deposition and both tau aggregation and neurodegeneration, which help advance our understanding of the role of iron dysregulation in the Alzheimer's disease aetiology.
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Affiliation(s)
- Nicola Spotorno
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | | | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Björn Lampinen
- Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden
| | - Olof T Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Danielle van Westen
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Liu KY, Acosta-Cabronero J, Cardenas-Blanco A, Loane C, Berry AJ, Betts MJ, Kievit RA, Henson RN, Düzel E, Howard R, Hämmerer D. Corrigendum to in vivo visualization of age-related differences in the locus coeruleus Neurobiology of Aging Volume 74, February 2019, Pages 101-111. Neurobiol Aging 2020; 91:172-174. [PMID: 32312580 PMCID: PMC7242897 DOI: 10.1016/j.neurobiolaging.2020.03.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Affiliation(s)
- Kathy Y Liu
- Division of Psychiatry, University College London, London, UK.
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK
| | - Arturo Cardenas-Blanco
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Clare Loane
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Alex J Berry
- Camden & Islington NHS Foundation Trust, London, UK
| | - Matthew J Betts
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Rogier A Kievit
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Richard N Henson
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany; Institute of Cognitive Neuroscience, University College London, London, UK
| | - Robert Howard
- Division of Psychiatry, University College London, London, UK
| | - Dorothea Hämmerer
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany; Institute of Cognitive Neuroscience, University College London, London, UK
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13
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Thomas GEC, Leyland LA, Schrag AE, Lees AJ, Acosta-Cabronero J, Weil RS. Brain iron deposition is linked with cognitive severity in Parkinson's disease. J Neurol Neurosurg Psychiatry 2020; 91:418-425. [PMID: 32079673 PMCID: PMC7147185 DOI: 10.1136/jnnp-2019-322042] [Citation(s) in RCA: 101] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 01/14/2020] [Accepted: 01/22/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND Dementia is common in Parkinson's disease (PD) but measures that track cognitive change in PD are lacking. Brain tissue iron accumulates with age and co-localises with pathological proteins linked to PD dementia such as amyloid. We used quantitative susceptibility mapping (QSM) to detect changes related to cognitive change in PD. METHODS We assessed 100 patients with early-stage to mid-stage PD, and 37 age-matched controls using the Montreal Cognitive Assessment (MoCA), a validated clinical algorithm for risk of cognitive decline in PD, measures of visuoperceptual function and the Movement Disorders Society Unified Parkinson's Disease Rating Scale part 3 (UPDRS-III). We investigated the association between these measures and QSM, an MRI technique sensitive to brain tissue iron content. RESULTS We found QSM increases (consistent with higher brain tissue iron content) in PD compared with controls in prefrontal cortex and putamen (p<0.05 corrected for multiple comparisons). Whole brain regression analyses within the PD group identified QSM increases covarying: (1) with lower MoCA scores in the hippocampus and thalamus, (2) with poorer visual function and with higher dementia risk scores in parietal, frontal and medial occipital cortices, (3) with higher UPDRS-III scores in the putamen (all p<0.05 corrected for multiple comparisons). In contrast, atrophy, measured using voxel-based morphometry, showed no differences between groups, or in association with clinical measures. CONCLUSIONS Brain tissue iron, measured using QSM, can track cognitive involvement in PD. This may be useful to detect signs of early cognitive change to stratify groups for clinical trials and monitor disease progression.
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Affiliation(s)
| | | | - Anette-Eleonore Schrag
- Department of Clinical Neuroscience, UCL Institute of Neurology, London, UK
- Movement Disorders Consortium, University College London, London, UK
| | - Andrew John Lees
- Reta Lila Institute for Brain Studies, University College London, London, UK
| | | | - Rimona Sharon Weil
- Dementia Research Centre, UCL Institute of Neurology, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
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14
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Faber J, Giordano I, Jiang X, Kindler C, Spottke A, Acosta-Cabronero J, Nestor PJ, Machts J, Düzel E, Vielhaber S, Speck O, Dudesek A, Kamm C, Scheef L, Klockgether T. Prominent White Matter Involvement in Multiple System Atrophy of Cerebellar Type. Mov Disord 2020; 35:816-824. [PMID: 31994808 DOI: 10.1002/mds.27987] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 12/27/2019] [Accepted: 12/30/2019] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Sporadic degenerative ataxia patients fall into 2 major groups: multiple system atrophy with predominant cerebellar ataxia (MSA-C) and sporadic adult-onset ataxia (SAOA). Both groups have cerebellar volume loss, but little is known about the differential involvement of gray and white matter in MSA-C when compared with SAOA. OBJECTIVES The objective of this study was to identify structural differences of brain gray and white matter between both patient groups. METHODS We used magnetic resonance imaging to acquire T1-weighted images and diffusion tensor images from 12 MSA-C patients, 31 SAOA patients, and 55 healthy controls. Magnetic resonance imaging data were analyzed with voxel-based-morphometry, tract-based spatial statistics, and tractography-based regional diffusion tensor images analysis. RESULTS Whole-brain and cerebellar-focused voxel-based-morphometry analysis showed gray matter volume loss in both patient groups when compared with healthy controls, specifically in the cerebellar areas subserving sensorimotor functions. When compared with controls, the SAOA and MSA-C patients showed white matter loss in the cerebellum, whereas brainstem white matter was reduced only in the MSA-C patients. The tract-based spatial statistics revealed reduced fractional anisotropy within the pons and cerebellum in the MSA-C patients both in comparison with the SAOA patients and healthy controls. In addition, tractography-based regional analysis showed reduced fractional anisotropy along the corticospinal tracts in MSA-C, but not SAOA. CONCLUSION Although in our cohort extent and distribution of gray and white matter loss were similar between the MSA-C and SAOA patients, magnetic resonance imaging data showed prominent microstructural white matter involvement in the MSA-C patients that was not present in the SAOA patients. Our findings highlight the significance of microstructural white matter changes in the differentiation between both conditions. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Jennifer Faber
- Clinical Research, German Center for Neurodegenerative Diseases, Bonn, Germany.,Department of Neurology, University Hospital Bonn, Germany
| | - Ilaria Giordano
- Clinical Research, German Center for Neurodegenerative Diseases, Bonn, Germany.,Department of Neurology, University Hospital Bonn, Germany
| | - Xueyan Jiang
- Clinical Research, German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Christine Kindler
- Clinical Research, German Center for Neurodegenerative Diseases, Bonn, Germany.,Department of Neurology, University Hospital Bonn, Germany
| | - Annika Spottke
- Clinical Research, German Center for Neurodegenerative Diseases, Bonn, Germany.,Department of Neurology, University Hospital Bonn, Germany
| | | | - Peter J Nestor
- Queensland Brain Institute, University of Queensland, Brisbane, Australia.,Neuroscience and Cognitive Health Program, Mater Hospital, South Brisbane, Australia
| | - Judith Machts
- German Center for Neurodegenerative Diseases, Magdeburg, Germany.,Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases, Magdeburg, Germany.,Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Stefan Vielhaber
- German Center for Neurodegenerative Diseases, Magdeburg, Germany.,Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Oliver Speck
- German Center for Neurodegenerative Diseases, Magdeburg, Germany.,Department of Biomedical Magnetic Resonance, Faculty for Natural Sciences, Otto-von-Guericke University, Magdeburg, Germany.,Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Ales Dudesek
- Department of Neurology, University of Rostock, Rostock, Germany
| | - Christoph Kamm
- Department of Neurology, University of Rostock, Rostock, Germany
| | - Lukas Scheef
- Clinical Research, German Center for Neurodegenerative Diseases, Bonn, Germany.,Department of Radiology, University of Bonn, Bonn, Germany
| | - Thomas Klockgether
- Clinical Research, German Center for Neurodegenerative Diseases, Bonn, Germany.,Department of Neurology, University Hospital Bonn, Germany
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15
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Spotorno N, Hall S, Irwin DJ, Rumetshofer T, Acosta-Cabronero J, Deik AF, Spindler MA, Lee EB, Trojanowski JQ, van Westen D, Nilsson M, Grossman M, Nestor PJ, McMillan CT, Hansson O. Diffusion Tensor MRI to Distinguish Progressive Supranuclear Palsy from α-Synucleinopathies. Radiology 2019; 293:646-653. [PMID: 31617796 PMCID: PMC6889922 DOI: 10.1148/radiol.2019190406] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2019] [Revised: 07/21/2019] [Accepted: 08/21/2019] [Indexed: 01/25/2023]
Abstract
Background The differential diagnosis of progressive supranuclear palsy (PSP) and Lewy body disorders, which include Parkinson disease and dementia with Lewy bodies, is often challenging due to the overlapping symptoms. Purpose To develop a diagnostic tool based on diffusion tensor imaging (DTI) to distinguish between PSP and Lewy body disorders at the individual-subject level. Materials and Methods In this retrospective study, skeletonized DTI metrics were extracted from two independent data sets: the discovery cohort from the Swedish BioFINDER study and the validation cohort from the Penn Frontotemporal Degeneration Center (data collected between 2010 and 2018). Based on previous neuroimaging studies and neuropathologic evidence, a combination of regions hypothesized to be sensitive to pathologic features of PSP were identified (ie, the superior cerebellar peduncle and frontal white matter) and fractional anisotropy (FA) was used to compute an FA score for each individual. Classification performances were assessed by using logistic regression and receiver operating characteristic analysis. Results In the discovery cohort, 16 patients with PSP (mean age ± standard deviation, 73 years ± 5; eight women, eight men), 34 patients with Lewy body disorders (mean age, 71 years ± 6; 14 women, 20 men), and 44 healthy control participants (mean age, 66 years ± 8; 26 women, 18 men) were evaluated. The FA score distinguished between clinical PSP and Lewy body disorders with an area under the curve of 0.97 ± 0.04, a specificity of 91% (31 of 34), and a sensitivity of 94% (15 of 16). In the validation cohort, 34 patients with PSP (69 years ± 7; 22 women, 12 men), 25 patients with Lewy body disorders (70 years ± 7; nine women, 16 men), and 32 healthy control participants (64 years ± 7; 22 women, 10 men) were evaluated. The accuracy of the FA score was confirmed (area under the curve, 0.96 ± 0.04; specificity, 96% [24 of 25]; and sensitivity, 85% [29 of 34]). Conclusion These cross-validated findings lay the foundation for a clinical test to distinguish progressive supranuclear palsy from Lewy body disorders. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Shah in this issue.
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Affiliation(s)
- Nicola Spotorno
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Sara Hall
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - David J. Irwin
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Theodor Rumetshofer
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Julio Acosta-Cabronero
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Andres F. Deik
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Meredith A. Spindler
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Edward B. Lee
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - John Q. Trojanowski
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Danielle van Westen
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Markus Nilsson
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Murray Grossman
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Peter J. Nestor
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Corey T. McMillan
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
| | - Oskar Hansson
- From the Clinical Memory Research Unit, Department of Clinical
Sciences, Malmö, Lund University, Sölvegatan 19, 22100 Lund, Sweden
(N.S., S.H., D.v.W., O.H.); Penn Frontotemporal Degeneration Center, Department
of Neurology, Perelman School of Medicine, University of Pennsylvania,
Philadelphia, Pa (N.S., D.J.I., M.G., C.T.M.); Memory Clinic, Skåne
University Hospital, Malmö, Sweden (S.H., O.H.); Center for
Neurodegenerative Disease Research, Perelman School of Medicine, University of
Pennsylvania, Philadelphia, Pa (D.J.I., E.B.L., J.Q.T.); Department of
Diagnostic Radiology, Lund University, Lund, Sweden (T.R., D.v.W., M.N.);
Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology,
University College London, London, England (J.A.C.); Parkinson’s Disease
and Movement Disorders Center, Department of Neurology, Perelman School of
Medicine, University of Pennsylvania, Philadelphia, Pa (A.F.D., M.A.S.);
Alzheimer’s Disease Core Center, Department of Pathology and Laboratory
Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia,
Pa (E.B.L., J.Q.T.); and Queensland Brain Institute, University of Queensland
and Mater Misericordiae, Brisbane, Queensland, Australia (P.J.N.)
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16
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Dusek P, Mekle R, Skowronska M, Acosta-Cabronero J, Huelnhagen T, Robinson SD, Schubert F, Deschauer M, Els A, Ittermann B, Schottmann G, Madai VI, Paul F, Klopstock T, Kmiec T, Niendorf T, Wuerfel J, Schneider SA. Brain iron and metabolic abnormalities in C19orf12 mutation carriers: A 7.0 tesla MRI study in mitochondrial membrane protein-associated neurodegeneration. Mov Disord 2019; 35:142-150. [PMID: 31518459 DOI: 10.1002/mds.27827] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 07/20/2019] [Accepted: 07/24/2019] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Mitochondrial membrane protein-associated neurodegeneration is an autosomal-recessive disorder caused by C19orf12 mutations and characterized by iron deposits in the basal ganglia. OBJECTIVES The aim of this study was to quantify iron concentrations in deep gray matter structures using quantitative susceptibility mapping MRI and to characterize metabolic abnormalities in the pyramidal pathway using 1 H MR spectroscopy in clinically manifesting membrane protein-associated neurodegeneration patients and asymptomatic C19orf12 gene mutation heterozygous carriers. METHODS We present data of 4 clinically affected membrane protein-associated neurodegeneration patients (mean age: 21.0 ± 2.9 years) and 9 heterozygous gene mutation carriers (mean age: 50.4 ± 9.8 years), compared to age-matched healthy controls. MRI assessments were performed on a 7.0 Tesla whole-body system, consisting of whole-brain gradient-echo scans and short echo time, single-volume MR spectroscopy in the white matter of the precentral/postcentral gyrus. Quantitative susceptibility mapping, a surrogate marker for iron concentration, was performed using a state-of-the-art multiscale dipole inversion approach with focus on the globus pallidus, thalamus, putamen, caudate nucleus, and SN. RESULTS AND CONCLUSION In membrane protein-associated neurodegeneration patients, magnetic susceptibilities were 2 to 3 times higher in the globus pallidus (P = 0.02) and SN (P = 0.02) compared to controls. In addition, significantly higher magnetic susceptibility was observed in the caudate nucleus (P = 0.02). Non-manifesting heterozygous mutation carriers exhibited significantly increased magnetic susceptibility (relative to controls) in the putamen (P = 0.003) and caudate nucleus (P = 0.001), which may be an endophenotypic marker of genetic heterozygosity. MR spectroscopy revealed significantly increased levels of glutamate, taurine, and the combined concentration of glutamate and glutamine in membrane protein-associated neurodegeneration, which may be a correlate of corticospinal pathway dysfunction frequently observed in membrane protein-associated neurodegeneration patients. © 2019 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Petr Dusek
- Department of Neurology and Centre of Clinical Neuroscience, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Prague, Czechia.,Department of Radiology, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Prague, Czechia
| | - Ralf Mekle
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.,Center for Stroke Research Berlin (CSB), Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Marta Skowronska
- 2nd Department of Neurology, Institute of Psychiatry and Neurology, Warsaw, Poland
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom
| | - Till Huelnhagen
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Simon Daniel Robinson
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Florian Schubert
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Marcus Deschauer
- Department of Neurology, Technical University Munich, Munich, Germany
| | - Antje Els
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Gudrun Schottmann
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany
| | - Vince I Madai
- Center for Stroke Research Berlin (CSB), Charité Universitätsmedizin Berlin, Berlin, Germany.,Department of Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Friedemann Paul
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany
| | - Thomas Klopstock
- Department of Neurology with Friedrich-Baur-Institute, Ludwig-Maximilians-University of Munich, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Tomasz Kmiec
- Department of Neurology and Epileptology, The Children's Memorial Health Institute, Warsaw, Poland
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Jens Wuerfel
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitaetsmedizin Berlin, Berlin, Germany.,Medical Image Analysis Center and Department Biomedical Engineering, University Basel, Basel, Switzerland
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17
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Betts MJ, Kirilina E, Otaduy MCG, Ivanov D, Acosta-Cabronero J, Callaghan MF, Lambert C, Cardenas-Blanco A, Pine K, Passamonti L, Loane C, Keuken MC, Trujillo P, Lüsebrink F, Mattern H, Liu KY, Priovoulos N, Fliessbach K, Dahl MJ, Maaß A, Madelung CF, Meder D, Ehrenberg AJ, Speck O, Weiskopf N, Dolan R, Inglis B, Tosun D, Morawski M, Zucca FA, Siebner HR, Mather M, Uludag K, Heinsen H, Poser BA, Howard R, Zecca L, Rowe JB, Grinberg LT, Jacobs HIL, Düzel E, Hämmerer D. Locus coeruleus imaging as a biomarker for noradrenergic dysfunction in neurodegenerative diseases. Brain 2019; 142:2558-2571. [PMID: 31327002 PMCID: PMC6736046 DOI: 10.1093/brain/awz193] [Citation(s) in RCA: 179] [Impact Index Per Article: 35.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 04/12/2019] [Accepted: 05/01/2019] [Indexed: 12/20/2022] Open
Abstract
Pathological alterations to the locus coeruleus, the major source of noradrenaline in the brain, are histologically evident in early stages of neurodegenerative diseases. Novel MRI approaches now provide an opportunity to quantify structural features of the locus coeruleus in vivo during disease progression. In combination with neuropathological biomarkers, in vivo locus coeruleus imaging could help to understand the contribution of locus coeruleus neurodegeneration to clinical and pathological manifestations in Alzheimer's disease, atypical neurodegenerative dementias and Parkinson's disease. Moreover, as the functional sensitivity of the noradrenergic system is likely to change with disease progression, in vivo measures of locus coeruleus integrity could provide new pathophysiological insights into cognitive and behavioural symptoms. Locus coeruleus imaging also holds the promise to stratify patients into clinical trials according to noradrenergic dysfunction. In this article, we present a consensus on how non-invasive in vivo assessment of locus coeruleus integrity can be used for clinical research in neurodegenerative diseases. We outline the next steps for in vivo, post-mortem and clinical studies that can lay the groundwork to evaluate the potential of locus coeruleus imaging as a biomarker for neurodegenerative diseases.
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Affiliation(s)
- Matthew J Betts
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Center for Cognitive Neuroscience, Free University Berlin, Berlin, Germany
| | - Maria C G Otaduy
- Laboratory of Magnetic Resonance LIM44, Department and Institute of Radiology, Medical School of the University of São Paulo, Brazil
| | - Dimo Ivanov
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, MD, Maastricht, The Netherlands
| | | | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK
| | - Christian Lambert
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK
| | - Arturo Cardenas-Blanco
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Kerrin Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK
| | - Luca Passamonti
- Department of Clinical Neurosciences, University of Cambridge, UK
- Consiglio Nazionale delle Ricerche, Istituto di Bioimmagini e Fisiologia Molecolare (IBFM), Milan, Italy
| | - Clare Loane
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Max C Keuken
- University of Amsterdam, Integrative Model-based Cognitive Neuroscience research unit, Amsterdam, The Netherlands
- University of Leiden, Cognitive Psychology, Leiden, The Netherlands
| | - Paula Trujillo
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Falk Lüsebrink
- Department of Biomedical Magnetic Resonance, Institute for Physics, Otto-von-Guericke-University, Magdeburg, Germany
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Hendrik Mattern
- Department of Biomedical Magnetic Resonance, Institute for Physics, Otto-von-Guericke-University, Magdeburg, Germany
| | - Kathy Y Liu
- Division of Psychiatry, University College London, London, UK
| | - Nikos Priovoulos
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, The Netherlands
| | - Klaus Fliessbach
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Martin J Dahl
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Anne Maaß
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Christopher F Madelung
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark
| | - David Meder
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark
| | - Alexander J Ehrenberg
- Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Oliver Speck
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Department of Biomedical Magnetic Resonance, Institute for Physics, Otto-von-Guericke-University, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK
| | - Raymond Dolan
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK
- Max Planck Centre for Computational Psychiatry and Ageing, University College London, UK
| | - Ben Inglis
- Henry H. Wheeler, Jr. Brain Imaging Center, University of California, Berkeley, CA, USA
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, USA
| | - Markus Morawski
- Paul Flechsig Institute of Brain Research, Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Fabio A Zucca
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, Milan, Italy
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark
| | - Mara Mather
- Leonard Davis School of Gerontology and Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Kamil Uludag
- Centre for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Techna Institute and Koerner Scientist in MR Imaging, University Health Network, Toronto, Canada
| | - Helmut Heinsen
- University of São Paulo Medical School, São Paulo, Brazil
- Clinic of Psychiatry, University of Würzburg, Wurzburg, Germany
| | - Benedikt A Poser
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, MD, Maastricht, The Netherlands
| | - Robert Howard
- Division of Psychiatry, University College London, London, UK
| | - Luigi Zecca
- Institute of Biomedical Technologies, National Research Council of Italy, Segrate, Milan, Italy
- Department of Psychiatry, Columbia University Medical Center, New York State Psychiatric Institute, New York, USA
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, UK
| | - Lea T Grinberg
- Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- University of São Paulo Medical School, São Paulo, Brazil
- Global Brain Health Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Heidi I L Jacobs
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, MD, Maastricht, The Netherlands
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, The Netherlands
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Dorothea Hämmerer
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
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18
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Düzel E, Acosta-Cabronero J, Berron D, Biessels GJ, Björkman-Burtscher I, Bottlaender M, Bowtell R, Buchem MV, Cardenas-Blanco A, Boumezbeur F, Chan D, Clare S, Costagli M, de Rochefort L, Fillmer A, Gowland P, Hansson O, Hendrikse J, Kraff O, Ladd ME, Ronen I, Petersen E, Rowe JB, Siebner H, Stoecker T, Straub S, Tosetti M, Uludag K, Vignaud A, Zwanenburg J, Speck O. European Ultrahigh-Field Imaging Network for Neurodegenerative Diseases (EUFIND). Alzheimers Dement (Amst) 2019; 11:538-549. [PMID: 31388558 PMCID: PMC6675944 DOI: 10.1016/j.dadm.2019.04.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction The goal of European Ultrahigh-Field Imaging Network in Neurodegenerative Diseases (EUFIND) is to identify opportunities and challenges of 7 Tesla (7T) MRI for clinical and research applications in neurodegeneration. EUFIND comprises 22 European and one US site, including over 50 MRI and dementia experts as well as neuroscientists. Methods EUFIND combined consensus workshops and data sharing for multisite analysis, focusing on 7 core topics: clinical applications/clinical research, highest resolution anatomy, functional imaging, vascular systems/vascular pathology, iron mapping and neuropathology detection, spectroscopy, and quality assurance. Across these topics, EUFIND considered standard operating procedures, safety, and multivendor harmonization. Results The clinical and research opportunities and challenges of 7T MRI in each subtopic are set out as a roadmap. Specific MRI sequences for each subtopic were implemented in a pilot study presented in this report. Results show that a large multisite 7T imaging network with highly advanced and harmonized imaging sequences is feasible and may enable future multicentre ultrahigh-field MRI studies and clinical trials. Discussion The EUFIND network can be a major driver for advancing clinical neuroimaging research using 7T and for identifying use-cases for clinical applications in neurodegeneration.
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Affiliation(s)
- Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany.,Institute of Cognitive Neuroscience, University College London, London, UK.,Center for Behavioral Brain Science, Magdeburg, Germany
| | - Julio Acosta-Cabronero
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany.,7Lund University BioImaging Center, Lund University, Lund, Sweden
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Isabella Björkman-Burtscher
- 7Lund University BioImaging Center, Lund University, Lund, Sweden.,Departement of Radiology, Sahlgrenska Akademy, University of Gothenburg, Gothenburg, Sweden
| | | | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Mark V Buchem
- Department of Radiology, University Medical Center Leiden, Leiden, The Netherlands
| | - Arturo Cardenas-Blanco
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany
| | - Fawzi Boumezbeur
- NeuroSpin, CEA & Université Paris-Saclay, Gif-Sur-Yvette, France
| | - Dennis Chan
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Stuart Clare
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Mauro Costagli
- Imago 7 Research Foundation, Pisa, Italy.,Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Ludovic de Rochefort
- Center for Magnetic Resonance in Biology and Medicine (UMR 7339), CRMBM, CNRS - Aix Marseille Université, Marseille, France
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Oskar Hansson
- 7Lund University BioImaging Center, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Jeroen Hendrikse
- Department of Neurology, UMC Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Oliver Kraff
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany
| | - Mark E Ladd
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Physics and Astronomy and Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Itamar Ronen
- Department of Radiology, University Medical Center Leiden, Leiden, The Netherlands
| | - Esben Petersen
- Danish Center for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Hartwig Siebner
- Danish Center for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.,Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Tony Stoecker
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Sina Straub
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michela Tosetti
- Imago 7 Research Foundation, Pisa, Italy.,Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Kamil Uludag
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.,Techna Institute & Koerner Scientist in MR Imaging, University Health Network, Toronto, Ontario, Canada
| | | | - Jaco Zwanenburg
- Department of Neurology, UMC Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Oliver Speck
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany.,Center for Behavioral Brain Science, Magdeburg, Germany.,Biomedical Magnetic Resonance, Otto-von-Guericke University, Magdeburg, Germany.,Leibniz-Institute for Neurobiology (LIN), Magdeburg, Germany
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19
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Corbin N, Acosta-Cabronero J, Malik SJ, Callaghan MF. Robust 3D Bloch-Siegert based B 1 + mapping using multi-echo general linear modeling. Magn Reson Med 2019; 82:2003-2015. [PMID: 31321823 PMCID: PMC6771691 DOI: 10.1002/mrm.27851] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 04/16/2019] [Accepted: 05/19/2019] [Indexed: 02/06/2023]
Abstract
PURPOSE Quantitative MRI applications, such as mapping the T1 time of tissue, puts high demands on the accuracy and precision of transmit field ( B 1 + ) estimation. A candidate approach to satisfy these requirements exploits the difference in phase induced by the Bloch-Siegert frequency shift (BSS) of 2 acquisitions with opposite off-resonance frequency radiofrequency pulses. Interleaving these radiofrequency pulses ensures robustness to motion and scanner drifts; however, here we demonstrate that doing so also introduces a bias in the B 1 + estimates. THEORY AND METHODS It is shown here by means of simulation and experiments that the amplitude of the error depends on MR pulse sequence parameters, such as repetition time and radiofrequency spoiling increment, but more problematically, on the intrinsic properties, T1 and T2 , of the investigated tissue. To solve these problems, a new approach to BSS-based B 1 + estimation that uses a multi-echo acquisition and a general linear model to estimate the correct BSS-induced phase is presented. RESULTS In line with simulations, phantom and in vivo experiments confirmed that the general linear model-based method removed the dependency on tissue properties and pulse sequence settings. CONCLUSION The general linear model-based method is recommended as a more accurate approach to BSS-based B 1 + mapping.
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Affiliation(s)
- Nadège Corbin
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Shaihan J Malik
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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20
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Liu KY, Acosta-Cabronero J, Cardenas-Blanco A, Loane C, Berry AJ, Betts MJ, Kievit RA, Henson RN, Düzel E, Howard R, Hämmerer D. In vivo visualization of age-related differences in the locus coeruleus. Neurobiol Aging 2019; 74:101-111. [PMID: 30447418 PMCID: PMC6338679 DOI: 10.1016/j.neurobiolaging.2018.10.014] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 10/06/2018] [Accepted: 10/11/2018] [Indexed: 11/23/2022]
Abstract
The locus coeruleus (LC), the major origin of noradrenergic modulation of the central nervous system, may play an important role in neuropsychiatric disorders including Parkinson's disease and Alzheimer's disease. The pattern of age-related change of the LC across the life span is unclear. We obtained normalized, mean LC signal intensity values, that is, contrast ratios (CRs), from magnetization transfer-weighted images to investigate the relationship between LC CR and age in cognitively normal healthy adults (N = 605, age range 18-88 years). Study participants were part of the Cambridge Centre for Ageing and Neuroscience-an open-access, population-based data set. We found a quadratic relationship between LC CR and age, the peak occurring around 60 years, with no differences between males and females. Subregional analyses revealed that age-related decline in LC CR was confined to the rostral portion of the LC. Older adults showed greater variance in overall LC CR than younger adults, and the functional and clinical implications of these observed age-related differences require further investigation. Visualization of the LC in this study may inform how future scanning parameters can be optimized, and provides insight into how LC integrity changes across the life span.
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Affiliation(s)
- Kathy Y Liu
- Division of Psychiatry, University College London, London, UK.
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK
| | - Arturo Cardenas-Blanco
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Clare Loane
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Alex J Berry
- Camden & Islington NHS Foundation Trust, London, UK
| | - Matthew J Betts
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Rogier A Kievit
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Richard N Henson
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany; Institute of Cognitive Neuroscience, University College London, London, UK
| | - Robert Howard
- Division of Psychiatry, University College London, London, UK
| | - Dorothea Hämmerer
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany; Institute of Cognitive Neuroscience, University College London, London, UK
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21
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Milovic C, Bilgic B, Zhao B, Langkammer C, Tejos C, Acosta-Cabronero J. Weak-harmonic regularization for quantitative susceptibility mapping. Magn Reson Med 2019; 81:1399-1411. [PMID: 30265767 DOI: 10.1002/mrm.27483] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 07/10/2018] [Accepted: 07/15/2018] [Indexed: 01/23/2023]
Abstract
PURPOSE Background-field removal is a crucial preprocessing step for quantitative susceptibility mapping (QSM). Remnants from this step often contaminate the estimated local field, which in turn leads to erroneous tissue-susceptibility reconstructions. The present work aimed to mitigate this undesirable behavior with the development of a new approach that simultaneously decouples background contributions and local susceptibility sources on QSM inversion. METHODS Input phase data for QSM can be seen as a composite scalar field of local effects and residual background components. We developed a new weak-harmonic regularizer to constrain the latter and to separate the 2 components. The resulting optimization problem was solved with the alternating directions of multipliers method framework to achieve fast convergence. In addition, for convenience, a new alternating directions of multipliers method-based preconditioned nonlinear projection onto dipole fields solver was developed to enable initializations with wrapped-phase distributions. Weak-harmonic QSM, with and without nonlinear projection onto dipole fields preconditioning, was compared with the original (alternating directions of multipliers method-based) total variation QSM algorithm in phantom and in vivo experiments. RESULTS Weak-harmonic QSM returned improved reconstructions regardless of the method used for background-field removal, although the proposed nonlinear projection onto dipole fields method often obtained better results. Streaking and shadowing artifacts were substantially suppressed, and residual background components were effectively removed. CONCLUSION Weak-harmonic QSM with field preconditioning is a robust dipole inversion technique and has the potential to be extended as a single-step formulation for initialization with uncombined multi-echo data.
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Affiliation(s)
- Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile.,Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Berkin Bilgic
- Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, Massachusetts
| | - Bo Zhao
- Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, Massachusetts
| | | | - Cristian Tejos
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile.,Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom
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22
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Dusek P, Madai VI, Huelnhagen T, Bahn E, Matej R, Sobesky J, Niendorf T, Acosta-Cabronero J, Wuerfel J. The choice of embedding media affects image quality, tissue R 2 * , and susceptibility behaviors in post-mortem brain MR microscopy at 7.0T. Magn Reson Med 2018; 81:2688-2701. [PMID: 30506939 DOI: 10.1002/mrm.27595] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 09/19/2018] [Accepted: 10/14/2018] [Indexed: 12/22/2022]
Abstract
PURPOSE The quality and precision of post-mortem MRI microscopy may vary depending on the embedding medium used. To investigate this, our study evaluated the impact of 5 widely used media on: (1) image quality, (2) contrast of high spatial resolution gradient-echo (T1 and T2 * -weighted) MR images, (3) effective transverse relaxation rate (R2 * ), and (4) quantitative susceptibility measurements (QSM) of post-mortem brain specimens. METHODS Five formaldehyde-fixed brain slices were scanned using 7.0T MRI in: (1) formaldehyde solution (formalin), (2) phosphate-buffered saline (PBS), (3) deuterium oxide (D2 O), (4) perfluoropolyether (Galden), and (5) agarose gel. SNR and contrast-to-noise ratii (SNR/CNR) were calculated for cortex/white matter (WM) and basal ganglia/WM regions. In addition, median R2 * and QSM values were extracted from caudate nucleus, putamen, globus pallidus, WM, and cortical regions. RESULTS PBS, Galden, and agarose returned higher SNR/CNR compared to formalin and D2 O. Formalin fixation, and its use as embedding medium for scanning, increased tissue R2 * . Imaging with agarose, D2 O, and Galden returned lower R2 * values than PBS (and formalin). No major QSM offsets were observed, although spatial variance was increased (with respect to R2 * behaviors) for formalin and agarose. CONCLUSIONS Embedding media affect gradient-echo image quality, R2 * , and QSM in differing ways. In this study, PBS embedding was identified as the most stable experimental setup, although by a small margin. Agarose and Galden were preferred to formalin or D2 O embedding. Formalin significantly increased R2 * causing noisier data and increased QSM variance.
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Affiliation(s)
- Petr Dusek
- Department of Neurology, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Praha, Czech Republic.,Department of Radiology, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Praha, Czech Republic
| | - Vince Istvan Madai
- Department of Neurology and Center for Stroke Research Berlin (CSB), Charité-Universitaetsmedizin, Berlin, Germany
| | - Till Huelnhagen
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Erik Bahn
- Institute of Neuropathology, University Medicine Göttingen, Göttingen, Germany
| | - Radoslav Matej
- Department of Pathology and Molecular Medicine, Thomayer Hospital, Praha, Czech Republic.,Department of Pathology, Charles University, 1st Faculty of Medicine and General University Hospital in Prague, Praha, Czech Republic
| | - Jan Sobesky
- Department of Neurology and Center for Stroke Research Berlin (CSB), Charité-Universitaetsmedizin, Berlin, Germany.,Experimental and Clinical Research Center (ECRC), Charité-Universitaetsmedizin and Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.,Experimental and Clinical Research Center (ECRC), Charité-Universitaetsmedizin and Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Jens Wuerfel
- NeuroCure Clinical Research Center, Charité-Universitaetsmedizin, Berlin, Germany.,Medical Imaging Analysis Center AG, Basel, Switzerland.,Department of Biomedical Engineering, University Basel, Switzerland
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23
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Acosta-Cabronero J, Milovic C, Mattern H, Tejos C, Speck O, Callaghan MF. A robust multi-scale approach to quantitative susceptibility mapping. Neuroimage 2018; 183:7-24. [PMID: 30075277 PMCID: PMC6215336 DOI: 10.1016/j.neuroimage.2018.07.065] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 06/29/2018] [Accepted: 07/29/2018] [Indexed: 12/11/2022] Open
Abstract
Quantitative Susceptibility Mapping (QSM), best known as a surrogate for tissue iron content, is becoming a highly relevant MRI contrast for monitoring cellular and vascular status in aging, addiction, traumatic brain injury and, in general, a wide range of neurological disorders. In this study we present a new Bayesian QSM algorithm, named Multi-Scale Dipole Inversion (MSDI), which builds on the nonlinear Morphology-Enabled Dipole Inversion (nMEDI) framework, incorporating three additional features: (i) improved implementation of Laplace's equation to reduce the influence of background fields through variable harmonic filtering and subsequent deconvolution, (ii) improved error control through dynamic phase-reliability compensation across spatial scales, and (iii) scalewise use of the morphological prior. More generally, this new pre-conditioned QSM formalism aims to reduce the impact of dipole-incompatible fields and measurement errors such as flow effects, poor signal-to-noise ratio or other data inconsistencies that can lead to streaking and shadowing artefacts. In terms of performance, MSDI is the first algorithm to rank in the top-10 for all metrics evaluated in the 2016 QSM Reconstruction Challenge. It also demonstrated lower variance than nMEDI and more stable behaviour in scan-rescan reproducibility experiments for different MRI acquisitions at 3 and 7 Tesla. In the present work, we also explored new forms of susceptibility MRI contrast making explicit use of the differential information across spatial scales. Specifically, we show MSDI-derived examples of: (i) enhanced anatomical detail with susceptibility inversions from short-range dipole fields (hereby referred to as High-Pass Susceptibility Mapping or HPSM), (ii) high specificity to venous-blood susceptibilities for highly regularised HPSM (making a case for MSDI-based Venography or VenoMSDI), (iii) improved tissue specificity (and possibly statistical conditioning) for Macroscopic-Vessel Suppressed Susceptibility Mapping (MVSSM), and (iv) high spatial specificity and definition for HPSM-based Susceptibility-Weighted Imaging (HPSM-SWI) and related intensity projections.
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Affiliation(s)
- Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
| | - Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile; Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Hendrik Mattern
- Department of Biomedical Magnetic Resonance, Institute of Experimental Physics, Otto von Guericke University, Magdeburg, Germany
| | - Cristian Tejos
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile; Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Oliver Speck
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Department of Biomedical Magnetic Resonance, Institute of Experimental Physics, Otto von Guericke University, Magdeburg, Germany; Center for Behavioural Brain Sciences, Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, United Kingdom
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24
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Mattern H, Sciarra A, Lüsebrink F, Acosta-Cabronero J, Speck O. Prospective motion correction improves high-resolution quantitative susceptibility mapping at 7T. Magn Reson Med 2018; 81:1605-1619. [PMID: 30298692 DOI: 10.1002/mrm.27509] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 07/12/2018] [Accepted: 08/06/2018] [Indexed: 12/12/2022]
Abstract
PURPOSE Recent literature has shown the potential of high-resolution quantitative susceptibility mapping (QSM) with ultra-high field MRI for imaging the anatomy, the vasculature, and investigating their magnetostatic properties. Higher spatial resolutions, however, translate to longer scans resulting, therefore, in higher vulnerability to, and likelihood of, subject movement. We propose a gradient-recalled echo sequence with prospective motion correction (PMC) to address such limitation. METHODS Data from 4 subjects were acquired at 7T. The effect of small and large motion on QSM with and without PMC was assessed qualitatively and quantitatively. Full brain QSM and QSM-based venograms with up to 0.33 mm isotropic voxel size were reconstructed. RESULTS With PMC, motion artifacts in QSM and QSM-based venograms were largely eliminated, enabling-in both large- and small-amplitude motion regimes-accurate depiction of the cortex, vasculature, and other small anatomical structures that are often blurred as a result of head movement or indiscernible at lower image resolutions. Quantitative analyses demonstrated that uncorrected motion could bias regional susceptibility distributions, a trend that was greatly reduced with PMC. CONCLUSION Qualitatively, PMC prevented image degradation because of motion artifacts, providing highly detailed QSM images and venograms. Quantitatively, PMC increased the reproducibility of susceptibility measures.
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Affiliation(s)
- Hendrik Mattern
- Department of Biomedical Magnetic Resonance, Institute for Physics, Otto-von-Guericke-University, Magdeburg, Germany
| | - Alessandro Sciarra
- Department of Biomedical Magnetic Resonance, Institute for Physics, Otto-von-Guericke-University, Magdeburg, Germany
| | - Falk Lüsebrink
- Department of Biomedical Magnetic Resonance, Institute for Physics, Otto-von-Guericke-University, Magdeburg, Germany
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, United Kingdom.,German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | - Oliver Speck
- Department of Biomedical Magnetic Resonance, Institute for Physics, Otto-von-Guericke-University, Magdeburg, Germany.,German Center for Neurodegenerative Diseases, Magdeburg, Germany.,Center for Behavioral Brain Sciences, Magdeburg, Germany.,Leibniz Institute for Neurobiology, Magdeburg, Germany
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25
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Schreiber S, Spotorno N, Schreiber F, Acosta-Cabronero J, Kaufmann J, Machts J, Debska-Vielhaber G, Garz C, Bittner D, Hensiek N, Dengler R, Petri S, Nestor PJ, Vielhaber S. Significance of CSF NfL and tau in ALS. J Neurol 2018; 265:2633-2645. [DOI: 10.1007/s00415-018-9043-0] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 06/25/2018] [Accepted: 08/30/2018] [Indexed: 01/01/2023]
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26
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Lanskey JH, McColgan P, Schrag AE, Acosta-Cabronero J, Rees G, Morris HR, Weil RS. Can neuroimaging predict dementia in Parkinson's disease? Brain 2018; 141:2545-2560. [PMID: 30137209 PMCID: PMC6113860 DOI: 10.1093/brain/awy211] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 06/26/2018] [Accepted: 06/29/2018] [Indexed: 12/17/2022] Open
Abstract
Dementia in Parkinson's disease affects 50% of patients within 10 years of diagnosis but there is wide variation in severity and timing. Thus, robust neuroimaging prediction of cognitive involvement in Parkinson's disease is important: (i) to identify at-risk individuals for clinical trials of potential new treatments; (ii) to provide reliable prognostic information for individuals and populations; and (iii) to shed light on the pathophysiological processes underpinning Parkinson's disease dementia. To date, neuroimaging has not made major contributions to predicting cognitive involvement in Parkinson's disease. This is perhaps unsurprising considering conventional methods rely on macroscopic measures of topographically distributed neurodegeneration, a relatively late event in Parkinson's dementia. However, new technologies are now emerging that could provide important insights through detection of other potentially relevant processes. For example, novel MRI approaches can quantify magnetic susceptibility as a surrogate for tissue iron content, and increasingly powerful mathematical approaches can characterize the topology of brain networks at the systems level. Here, we present an up-to-date overview of the growing role of neuroimaging in predicting dementia in Parkinson's disease. We discuss the most relevant findings to date, and consider the potential of emerging technologies to detect the earliest signs of cognitive involvement in Parkinson's disease.
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Affiliation(s)
- Juliette H Lanskey
- Institute of Neurology, UCL, Queen Square, London, UK
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Peter McColgan
- Huntington’s Disease Centre, UCL, Queen Square, London, UK
| | - Anette E Schrag
- Department of Clinical Neurosciences, Royal Free Campus UCL Institute of Neurology, UK
| | | | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, UCL, Queen Square, London, UK
- Institute of Cognitive Neuroscience, UCL, Queen Square, London, UK
| | - Huw R Morris
- Department of Clinical Neurosciences, Royal Free Campus UCL Institute of Neurology, UK
- Department of Movement Disorders, UCL, Queen Square, London, UK
| | - Rimona S Weil
- Wellcome Centre for Human Neuroimaging, UCL, Queen Square, London, UK
- UCL Dementia Research Centre, Queen Square, London, UK
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27
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Lee Y, Callaghan MF, Acosta-Cabronero J, Lutti A, Nagy Z. Establishing intra- and inter-vendor reproducibility of T1
relaxation time measurements with 3T MRI. Magn Reson Med 2018; 81:454-465. [DOI: 10.1002/mrm.27421] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 05/28/2018] [Accepted: 06/04/2018] [Indexed: 11/11/2022]
Affiliation(s)
- Yoojin Lee
- Laboratory for Social and Neural Systems Research; University of Zurich; Zürich Switzerland
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging; UCL Institute of Neurology; London United Kingdom
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging; UCL Institute of Neurology; London United Kingdom
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience,; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
| | - Zoltan Nagy
- Laboratory for Social and Neural Systems Research; University of Zurich; Zürich Switzerland
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28
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Perosa V, Schreiber S, Düzel E, Assmann A, Bittner D, Schreiber F, Acosta-Cabronero J. FV4. Comparing whole-brain susceptibility patterns in patients with Alzheimers disease and cerebral amyloid angiopathy: A QSM study. Clin Neurophysiol 2018. [DOI: 10.1016/j.clinph.2018.04.618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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29
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Acosta-Cabronero J, Machts J, Schreiber S, Abdulla S, Kollewe K, Petri S, Spotorno N, Kaufmann J, Heinze HJ, Dengler R, Vielhaber S, Nestor PJ. Quantitative Susceptibility MRI to Detect Brain Iron in Amyotrophic Lateral Sclerosis. Radiology 2018; 289:195-203. [PMID: 30040038 DOI: 10.1148/radiol.2018180112] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Purpose To investigate the whole-brain landscape of iron-related abnormalities in amyotrophic lateral sclerosis (ALS) by using the in vivo MRI technique of quantitative susceptibility mapping (QSM). Materials and Methods For this prospective study, 28 patients with ALS (mean age, 61 years; age range, 43-77 years; 18 men [mean age, 61 years; range, 43-77 years] and 10 women [mean age, 61 years; range, 47-74 years]) recruited between January 17, 2014, and September 4, 2015, and 39 matched control subjects (mean age, 61 years; age range, 39-77 years; 24 men [mean age, 62 years; range, 39-77 years] and 15 women [mean age, 59 years; range, 39-73 years]) were examined by using structural and susceptibility 3.0-T MRI techniques. Group data were cross sectionally compared with family-wise error (FWE) corrections by using voxel-based morphometry (random-field theory), cortical thickness analysis (Monte Carlo simulated), subcortical volumetry (Bonferroni-corrected Wilcoxon rank-sum testing), and QSM analysis (cluster-enhanced whole-brain permutation testing and Bonferroni-corrected rank-sum testing in regions of interest). In patients with ALS, a potential relationship between diffusion and susceptibility measurements in the corticospinal tracts (CSTs) was also examined by using Spearman rank-correlation tests. Results Conventional structural measures failed to identify atrophy in the present cohort (FWE P > .05). However, QSM identified several whole-brain abnormalities (FWE P < .05) in ALS. Regionally, higher susceptibility (expressed as means in parts per million ± standard errors of the mean) was confirmed in the motor cortex (ALS = 0.0188 ± 0.0003, control = 0.0173 ± 0.0003; P < .001), the left substantia nigra (ALS = 0.127 ± 0.004, control = 0.113 ± 0.003; P = .008), the right substantia nigra (ALS = 0.141 ± 0.005, control = 0.120 ± 0.003; P < .001), the globus pallidus (ALS = 0.086 ± 0.003, control = 0.075 ± 0.002; P = .003), and the red nucleus (ALS = 0.115 ± 0.004, control = 0.098 ± 0.003; P < .001). Lower susceptibility was found in CST white matter (ALS = -0.047 ± 0.001, control = -0.043 ± 0.001; P = .01). Nigral and pallidal QSM values were cross correlated in ALS (ρ2 = 0.42, P < .001), a phenomenon visually traceable in many individual patients. QSM in the CST in ALS also correlated with diffusion-tensor metrics in this tract (ρ2 = 0.25, P = .007). Conclusion Whole-brain MRI quantitative susceptibility mapping analysis is sensitive to tissue alterations in amyotrophic lateral sclerosis that may be relevant to pathologic changes. © RSNA, 2018.
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Affiliation(s)
- Julio Acosta-Cabronero
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Judith Machts
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Stefanie Schreiber
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Susanne Abdulla
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Katja Kollewe
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Susanne Petri
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Nicola Spotorno
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Joern Kaufmann
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Hans-Jochen Heinze
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Reinhard Dengler
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Stefan Vielhaber
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
| | - Peter J Nestor
- From the German Center for Neurodegenerative Diseases, Magdeburg, Germany (J.A., J.M., N.S., H.J.H., P.J.N.); Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, England (J.A.); Department of Neurology, Otto von Guericke University, Magdeburg, Germany (J.M., S.S., S.A., J.K., H.J.H., S.V.); Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany (S.A., K.K., S.P., R.D.); Leibniz Institute for Neurobiology, Magdeburg, Germany (H.J.H.); and Queensland Brain Institute, University of Queensland, Brisbane, Australia (P.J.N.)
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Mak E, Padilla C, Annus T, Wilson L, Hong YT, Acosta-Cabronero J, Fryer TD, Cardenas-Blanco A, Boros I, Coles JP, Aigbirhio FI, Menon DK, Nestor P, Zaman S, Holland AJ. P1‐449: MAPPING AMYLOID DEPOSITION ON CORTICAL ATROPHY IN DOWN SYNDROME: A COMBINED BASELINE AND 2‐YEAR LONGITUDINAL ANALYSIS. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
- Elijah Mak
- University of CambridgeCambridgeUnited Kingdom
| | | | - Tiina Annus
- University of CambridgeCambridgeUnited Kingdom
| | - Liam Wilson
- University of CambridgeCambridgeUnited Kingdom
| | | | | | | | | | | | | | | | | | - Peter Nestor
- Department of NeurologyOtto von Guericke UniversityMagdeburgGermany
| | - Shahid Zaman
- Cambridge Intellectual and Developmental Disabilities Research GroupUniversity of CambridgeCambridgeUnited Kingdom
| | - Anthony J. Holland
- Cambridge Intellectual and Developmental Disabilities Research GroupUniversity of CambridgeCambridgeUnited Kingdom
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Milovic C, Acosta-Cabronero J, Pinto JM, Mattern H, Andia M, Uribe S, Tejos C. A new discrete dipole kernel for quantitative susceptibility mapping. Magn Reson Imaging 2018; 51:7-13. [PMID: 29673893 DOI: 10.1016/j.mri.2018.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 04/13/2018] [Indexed: 10/17/2022]
Abstract
PURPOSE Most approaches for quantitative susceptibility mapping (QSM) are based on a forward model approximation that employs a continuous Fourier transform operator to solve a differential equation system. Such formulation, however, is prone to high-frequency aliasing. The aim of this study was to reduce such errors using an alternative dipole kernel formulation based on the discrete Fourier transform and discrete operators. METHODS The impact of such an approach on forward model calculation and susceptibility inversion was evaluated in contrast to the continuous formulation both with synthetic phantoms and in vivo MRI data. RESULTS The discrete kernel demonstrated systematically better fits to analytic field solutions, and showed less over-oscillations and aliasing artifacts while preserving low- and medium-frequency responses relative to those obtained with the continuous kernel. In the context of QSM estimation, the use of the proposed discrete kernel resulted in error reduction and increased sharpness. CONCLUSION This proof-of-concept study demonstrated that discretizing the dipole kernel is advantageous for QSM. The impact on small or narrow structures such as the venous vasculature might by particularly relevant to high-resolution QSM applications with ultra-high field MRI - a topic for future investigations. The proposed dipole kernel has a straightforward implementation to existing QSM routines.
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Affiliation(s)
- Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Avda. Vicuña Mackenna 4686, Macul, Santiago, Chile; Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Avda. Vicuña Mackenna 4686, Macul, Santiago, Chile.
| | - Julio Acosta-Cabronero
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London. 12 Queen Square, London WC1N 3BG, UK; German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Haus 64, 39120 Magdeburg, Germany.
| | - José Miguel Pinto
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Avda. Vicuña Mackenna 4686, Macul, Santiago, Chile; Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Avda. Vicuña Mackenna 4686, Macul, Santiago, Chile.
| | - Hendrik Mattern
- Department of Biomedical Magnetic Resonance, Institute of Experimental Physics, Otto von Guericke-University. Universitaetsplatz 2, 39106 Magdeburg, Germany.
| | - Marcelo Andia
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Avda. Vicuña Mackenna 4686, Macul, Santiago, Chile; Department of Radiology, School of Medicine, Pontificia Universidad Catolica de Chile. Avda. Libertador Bernardo OHiggins 340, Santiago, Chile.
| | - Sergio Uribe
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Avda. Vicuña Mackenna 4686, Macul, Santiago, Chile; Department of Radiology, School of Medicine, Pontificia Universidad Catolica de Chile. Avda. Libertador Bernardo OHiggins 340, Santiago, Chile.
| | - Cristian Tejos
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Avda. Vicuña Mackenna 4686, Macul, Santiago, Chile; Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Avda. Vicuña Mackenna 4686, Macul, Santiago, Chile.
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32
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Machts J, Cardenas-Blanco A, Acosta-Cabronero J, Kaufmann J, Loewe K, Kasper E, Schuster C, Prudlo J, Vielhaber S, Nestor PJ. Prefrontal cortical thickness in motor neuron disease. Neuroimage Clin 2018; 18:648-655. [PMID: 29876256 PMCID: PMC5987868 DOI: 10.1016/j.nicl.2018.03.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 02/23/2018] [Accepted: 03/01/2018] [Indexed: 02/06/2023]
Abstract
Objective To examine whether the distribution of prefrontal cortical thickness in patients with motor neuron disease is normal or bimodal and how it compares to the normal population. Methods 158 patients with motor neuron disease (MND) and 86 healthy controls (HC) were enrolled in a prospective, two-center study with a common structural MRI protocol. Cortical thickness measures were extracted for the prefrontal cortex, premotor cortex, motor cortex, and occipital cortex using FreeSurfer, adjusted for age and sex, and tested for normality of distribution. Results Cortical thickness measures of the bilateral prefrontal, premotor, motor, and occipital cortex were normally distributed in patients and healthy controls. MND-related cortical thinning was observed in the right motor cortex (p = 0.002), reflected in a significantly higher proportion of MND cases being worse than −1 standard deviation of the healthy control mean: 29.1% in the right motor cortex (p = 0.002). Cortical thinning of the left motor cortex was a function of clinical phenotype and physical disability. Left prefrontal cortical thickness was reduced in patients with additional cognitive and/or behavioural deficits compared to MND patients without cognitive deficits. Prefrontal, premotor, motor, and occipital cortical thickness was related to patients' general cognitive abilities. Conclusion The study shows that prefrontal cortical thickness in MND is normally distributed but shifted towards thinner cortex in MND patients with cognitive and/or behavioural impairment. The distribution of thickness values did not indicate the assumption of a bimodal distribution although patients with comorbid cognitive deficits are more likely to suffer from prefrontal cortical thinning. There is an increased prevalence of prefrontal cortical thinning in MND patients with cognitive and/or behavioural impairment. Distribution of thickness values among different MND subgroups appear unimodal. Thinning is dependent of clinical phenotype, disease severity, and cognitive impairment.
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Affiliation(s)
- Judith Machts
- Department of Neurology, Otto-von-Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, Leipziger Straße 44, 39120 Magdeburg, Germany.
| | - Arturo Cardenas-Blanco
- German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, Leipziger Straße 44, 39120 Magdeburg, Germany
| | - Julio Acosta-Cabronero
- German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, Leipziger Straße 44, 39120 Magdeburg, Germany
| | - Joern Kaufmann
- Department of Neurology, Otto-von-Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany
| | - Kristian Loewe
- Department of Neurology, Otto-von-Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany; Department of Computer Science, Otto-von-Guericke University, Universitaetsplatz 2, 39106 Magdeburg, Germany
| | - Elisabeth Kasper
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock, Gehlsheimer Straße 20, 18147 Rostock, Germany
| | - Christina Schuster
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock, Gehlsheimer Straße 20, 18147 Rostock, Germany
| | - Johannes Prudlo
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock, Gehlsheimer Straße 20, 18147 Rostock, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto-von-Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, Leipziger Straße 44, 39120 Magdeburg, Germany
| | - Peter J Nestor
- German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, Leipziger Straße 44, 39120 Magdeburg, Germany
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Milovic C, Bilgic B, Zhao B, Acosta-Cabronero J, Tejos C. Fast nonlinear susceptibility inversion with variational regularization. Magn Reson Med 2018; 80:814-821. [PMID: 29322560 DOI: 10.1002/mrm.27073] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 11/27/2017] [Accepted: 12/13/2017] [Indexed: 12/15/2022]
Abstract
PURPOSE Quantitative susceptibility mapping can be performed through the minimization of a function consisting of data fidelity and regularization terms. For data consistency, a Gaussian-phase noise distribution is often assumed, which breaks down when the signal-to-noise ratio is low. A previously proposed alternative is to use a nonlinear data fidelity term, which reduces streaking artifacts, mitigates noise amplification, and results in more accurate susceptibility estimates. We hereby present a novel algorithm that solves the nonlinear functional while achieving computation speeds comparable to those for a linear formulation. METHODS We developed a nonlinear quantitative susceptibility mapping algorithm (fast nonlinear susceptibility inversion) based on the variable splitting and alternating direction method of multipliers, in which the problem is split into simpler subproblems with closed-form solutions and a decoupled nonlinear inversion hereby solved with a Newton-Raphson iterative procedure. Fast nonlinear susceptibility inversion performance was assessed using numerical phantom and in vivo experiments, and was compared against the nonlinear morphology-enabled dipole inversion method. RESULTS Fast nonlinear susceptibility inversion achieves similar accuracy to nonlinear morphology-enabled dipole inversion but with significantly improved computational efficiency. CONCLUSION The proposed method enables accurate reconstructions in a fraction of the time required by state-of-the-art quantitative susceptibility mapping methods. Magn Reson Med 80:814-821, 2018. © 2018 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Carlos Milovic
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile.,Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Berkin Bilgic
- Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts, USA
| | - Bo Zhao
- Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts, USA
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, United Kingdom
| | - Cristian Tejos
- Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, Santiago, Chile.,Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
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Cole JH, Annus T, Wilson LR, Remtulla R, Hong YT, Fryer TD, Acosta-Cabronero J, Cardenas-Blanco A, Smith R, Menon DK, Zaman SH, Nestor PJ, Holland AJ. Brain-predicted age in Down syndrome is associated with beta amyloid deposition and cognitive decline. Neurobiol Aging 2017; 56:41-49. [PMID: 28482213 PMCID: PMC5476346 DOI: 10.1016/j.neurobiolaging.2017.04.006] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 03/09/2017] [Accepted: 04/09/2017] [Indexed: 02/04/2023]
Abstract
Individuals with Down syndrome (DS) are more likely to experience earlier onset of multiple facets of physiological aging. This includes brain atrophy, beta amyloid deposition, cognitive decline, and Alzheimer's disease—factors indicative of brain aging. Here, we employed a machine learning approach, using structural neuroimaging data to predict age (i.e., brain-predicted age) in people with DS (N = 46) and typically developing controls (N = 30). Chronological age was then subtracted from brain-predicted age to generate a brain-predicted age difference (brain-PAD) score. DS participants also underwent [11C]-PiB positron emission tomography (PET) scans to index the levels of cerebral beta amyloid deposition, and cognitive assessment. Mean brain-PAD in DS participants' was +2.49 years, significantly greater than controls (p < 0.001). The variability in brain-PAD was associated with the presence and the magnitude of PiB-binding and levels of cognitive performance. Our study indicates that DS is associated with premature structural brain aging, and that age-related alterations in brain structure are associated with individual differences in the rate of beta amyloid deposition and cognitive impairment.
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Affiliation(s)
- James H Cole
- Computational, Cognitive & Clinical Neuroimaging Laboratory (C3NL), Division of Brain Sciences, Imperial College London, London, UK.
| | - Tiina Annus
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Liam R Wilson
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Young T Hong
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Tim D Fryer
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | | | | | - Robert Smith
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - David K Menon
- Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Shahid H Zaman
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Peter J Nestor
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Anthony J Holland
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, UK
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35
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Annus T, Wilson LR, Acosta-Cabronero J, Cardenas-Blanco A, Hong YT, Fryer TD, Coles JP, Menon DK, Zaman SH, Holland AJ, Nestor PJ. The Down syndrome brain in the presence and absence of fibrillar β-amyloidosis. Neurobiol Aging 2017; 53:11-19. [PMID: 28192686 PMCID: PMC5391869 DOI: 10.1016/j.neurobiolaging.2017.01.009] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2016] [Revised: 01/01/2017] [Accepted: 01/06/2017] [Indexed: 11/26/2022]
Abstract
People with Down syndrome (DS) have a neurodevelopmentally distinct brain and invariably developed amyloid neuropathology by age 50. This cross-sectional study aimed to provide a detailed account of DS brain morphology and the changes occuring with amyloid neuropathology. Forty-six adults with DS underwent structural and amyloid imaging—the latter using Pittsburgh compound B (PIB) to stratify the cohort into PIB-positive (n = 19) and PIB-negative (n = 27). Age-matched controls (n = 30) underwent structural imaging. Group differences in deep gray matter volumetry and cortical thickness were studied. PIB-negative people with DS have neurodevelopmentally atypical brain, characterized by disproportionately thicker frontal and occipitoparietal cortex and thinner motor cortex and temporal pole with larger putamina and smaller hippocampi than controls. In the presence of amyloid neuropathology, the DS brains demonstrated a strikingly similar pattern of posterior dominant cortical thinning and subcortical atrophy in the hippocampus, thalamus, and striatum, to that observed in non-DS Alzheimer's disease. Care must be taken to avoid underestimating amyloid-associated morphologic changes in DS due to disproportionate size of some subcortical structures and thickness of the cortex.
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Affiliation(s)
- Tiina Annus
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Douglas House, Cambridge, UK.
| | - Liam R Wilson
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Douglas House, Cambridge, UK
| | - Julio Acosta-Cabronero
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London, UK
| | | | - Young T Hong
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Tim D Fryer
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Jonathan P Coles
- Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK
| | - David K Menon
- Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Shahid H Zaman
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Douglas House, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Elizabeth House, Fulbourn Hospital, Fulbourn, Cambridge, UK
| | - Anthony J Holland
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Douglas House, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Elizabeth House, Fulbourn Hospital, Fulbourn, Cambridge, UK
| | - Peter J Nestor
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
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Acosta-Cabronero J, Cardenas-Blanco A, Betts MJ, Butryn M, Valdes-Herrera JP, Galazky I, Nestor PJ. The whole-brain pattern of magnetic susceptibility perturbations in Parkinson's disease. Brain 2016; 140:118-131. [PMID: 27836833 DOI: 10.1093/brain/aww278] [Citation(s) in RCA: 126] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Revised: 09/14/2016] [Accepted: 09/18/2016] [Indexed: 12/13/2022] Open
Abstract
Although iron-mediated oxidative stress has been proposed as a potential pathomechanism in Parkinson's disease, the global distribution of iron accumulation in Parkinson's disease has not yet been elucidated. This study used a new magnetic resonance imaging contrast, quantitative susceptibility mapping, and state-of-the-art methods to map for the first time the whole-brain landscape of magnetostatic alterations as a surrogate for iron level changes in n = 25 patients with idiopathic Parkinson's disease versus n = 50 matched controls. In addition to whole-brain analysis, a regional study including sub-segmentation of the substantia nigra into dorsal and ventral regions and qualitative assessment of susceptibility maps in single subjects were also performed. The most remarkable basal ganglia effect was an apparent magnetic susceptibility increase-consistent with iron deposition-in the dorsal substantia nigra, though an effect was also observed in ventral regions. Increased bulk susceptibility, additionally, was detected in rostral pontine areas and in a cortical pattern tightly concordant with known Parkinson's disease distributions of α-synuclein pathology. In contrast, the normally iron-rich cerebellar dentate nucleus returned a susceptibility reduction suggesting decreased iron content. These results are in agreement with previous post-mortem studies in which iron content was evaluated in specific regions of interest; however, extensive neocortical and cerebellar changes constitute a far more complex pattern of iron dysregulation than was anticipated. Such findings also stand in stark contrast to the lack of statistically significant group change using conventional magnetic resonance imaging methods namely voxel-based morphometry, cortical thickness analysis, subcortical volumetry and tract-based diffusion tensor analysis; confirming the potential of whole-brain quantitative susceptibility mapping as an in vivo biomarker in Parkinson's disease.
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Affiliation(s)
- Julio Acosta-Cabronero
- 1 German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany
| | - Arturo Cardenas-Blanco
- 1 German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany
| | - Matthew J Betts
- 1 German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany
| | - Michaela Butryn
- 2 Department of Neurology, Otto-von-Guericke University, Leipziger Strasse 44, 39120 Magdeburg, Germany
| | - Jose P Valdes-Herrera
- 1 German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany
| | - Imke Galazky
- 2 Department of Neurology, Otto-von-Guericke University, Leipziger Strasse 44, 39120 Magdeburg, Germany
| | - Peter J Nestor
- 1 German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany
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Betts MJ, Acosta-Cabronero J, Cardenas-Blanco A, Nestor PJ, Düzel E. High-resolution characterisation of the aging brain using simultaneous quantitative susceptibility mapping (QSM) and R2* measurements at 7T. Neuroimage 2016; 138:43-63. [PMID: 27181761 DOI: 10.1016/j.neuroimage.2016.05.024] [Citation(s) in RCA: 76] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Revised: 04/28/2016] [Accepted: 05/07/2016] [Indexed: 12/12/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) has recently emerged as a novel magnetic resonance imaging (MRI) method to detect non-haem iron deposition, calcifications, demyelination and vascular lesions in the brain. It has been suggested that QSM is more sensitive than the more conventional quantifiable MRI measure, namely the transverse relaxation rate, R2*. Here, we conducted the first high-resolution, whole-brain, simultaneously acquired, comparative study of the two techniques using 7Tesla MRI. We asked which of the two techniques would be more sensitive to explore global differences in tissue composition in elderly adults relative to young subjects. Both QSM and R2* revealed strong age-related differences in subcortical regions, hippocampus and cortical grey matter, particularly in superior frontal regions, motor/premotor cortices, insula and cerebellar regions. Within the basal ganglia system-but also hippocampus and cerebellar dentate nucleus-, QSM was largely in agreement with R2* with the exception of the globus pallidus. QSM, however, provided superior anatomical contrast and revealed age-related differences in the thalamus and in white matter, which were otherwise largely undetected by R2* measurements. In contrast, in occipital cortex, age-related differences were much greater with R2* compared to QSM. The present study, therefore, demonstrated that in vivo QSM using ultra-high field MRI provides a novel means to characterise age-related differences in the human brain, but also combining QSM and R2* using multi-gradient recalled echo imaging can potentially provide a more complete picture of mineralisation, demyelination and/or vascular alterations in aging and disease.
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Affiliation(s)
- Matthew J Betts
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
| | | | - Arturo Cardenas-Blanco
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany
| | - Peter J Nestor
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120 Magdeburg, Germany; Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AR, UK
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Cardenas-Blanco A, Machts J, Acosta-Cabronero J, Kaufmann J, Abdulla S, Kollewe K, Petri S, Schreiber S, Heinze HJ, Dengler R, Vielhaber S, Nestor PJ. Structural and diffusion imaging versus clinical assessment to monitor amyotrophic lateral sclerosis. Neuroimage Clin 2016; 11:408-414. [PMID: 27104135 PMCID: PMC4827722 DOI: 10.1016/j.nicl.2016.03.011] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Revised: 02/24/2016] [Accepted: 03/14/2016] [Indexed: 01/20/2023]
Abstract
Amyotrophic lateral sclerosis is a progressive neurodegenerative disease that affects upper and lower motor neurons. Observational and intervention studies can be tracked using clinical measures such as the revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) but for a complete understanding of disease progression, objective in vivo biomarkers of both central and peripheral motor pathway pathology are highly desirable. The aim of this study was to determine the utility of structural and diffusion imaging as central nervous system biomarkers compared to the standard clinical measure, ALSFRS-R, to track longitudinal evolution using three time-point measurements. N = 34 patients with ALS were scanned and clinically assessed three times at a mean of three month time intervals. The MRI biomarkers were structural T1-weighted volumes for cortical thickness measurement as well as deep grey matter volumetry, voxel-based morphometry and diffusion tensor imaging (DTI). Cortical thickness focused specifically on the precentral gyrus while quantitative DTI biomarkers focused on the corticospinal tracts. The evolution of imaging biomarkers and ALSFRS-R scores over time were analysed using a mixed effects model that accounted for the scanning interval as a fixed effect variable, and, the initial measurements and time from onset as random variables. The mixed effects model showed a significant decrease in the ALSFRS-R score, (p < 0.0001, and an annual rate of change (AROC) of − 7.3 points). Similarly, fractional anisotropy of the corticospinal tract showed a significant decrease (p = 0.009, AROC = − 0.0066) that, in turn, was driven by a significant increase in radial diffusivity combined with a trend to decrease in axial diffusivity. No significant change in cortical thickness of the precentral gyrus was found (p > 0.5). In addition, deep grey matter volumetry and voxel-based morphometry also identified no significant changes. Furthermore, the availability of three time points was able to indicate that there was a linear progression in both clinical and fractional anisotropy measures adding to the validity of these results. The results indicate that DTI is clearly a superior imaging marker compared to atrophy for tracking the evolution of the disease and can act as a central nervous biomarker in longitudinal studies. It remains, however, less sensitive than the ALSFRS-R score for monitoring decline over time. Three time points were used for the first time to assess imaging biomarkers in ALS. Fractional anisotropy of the corticospinal tract showed linear decline. No atrophy measure was useful to track change. The ALSFRS-R clinical scale remains more sensitive than imaging biomarkers.
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Affiliation(s)
- Arturo Cardenas-Blanco
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany.
| | - Judith Machts
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany.
| | - Julio Acosta-Cabronero
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany.
| | - Joern Kaufmann
- Department of Neurology, Otto-von-Guericke University, Leipziger Strasse 44, 39120 Magdeburg, Germany.
| | - Susanne Abdulla
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany; Department of Neurology, Otto-von-Guericke University, Leipziger Strasse 44, 39120 Magdeburg, Germany; Department of Neurology, Hannover Medical School, Carl-Neuberg-Strasse 1, 30625 Hannover, Germany.
| | - Katja Kollewe
- Department of Neurology, Hannover Medical School, Carl-Neuberg-Strasse 1, 30625 Hannover, Germany.
| | - Susanne Petri
- Department of Neurology, Hannover Medical School, Carl-Neuberg-Strasse 1, 30625 Hannover, Germany.
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany; Department of Neurology, Otto-von-Guericke University, Leipziger Strasse 44, 39120 Magdeburg, Germany.
| | - Hans-Jochen Heinze
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany; Department of Neurology, Otto-von-Guericke University, Leipziger Strasse 44, 39120 Magdeburg, Germany; Leibniz Institute for Neurobiology, Brenneckestrasse 6, 39118 Magdeburg, Germany.
| | - Reinhard Dengler
- Department of Neurology, Hannover Medical School, Carl-Neuberg-Strasse 1, 30625 Hannover, Germany.
| | - Stefan Vielhaber
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany; Department of Neurology, Otto-von-Guericke University, Leipziger Strasse 44, 39120 Magdeburg, Germany.
| | - Peter J Nestor
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120 Magdeburg, Germany.
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Annus T, Wilson LR, Hong YT, Acosta-Cabronero J, Fryer TD, Cardenas-Blanco A, Smith R, Boros I, Coles JP, Aigbirhio FI, Menon DK, Zaman SH, Nestor PJ, Holland AJ. The pattern of amyloid accumulation in the brains of adults with Down syndrome. Alzheimers Dement 2015; 12:538-45. [PMID: 26362596 PMCID: PMC4867786 DOI: 10.1016/j.jalz.2015.07.490] [Citation(s) in RCA: 111] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Revised: 06/26/2015] [Accepted: 07/14/2015] [Indexed: 11/17/2022]
Abstract
INTRODUCTION Adults with Down syndrome (DS) invariably develop Alzheimer's disease (AD) neuropathology. Understanding amyloid deposition in DS can yield crucial information about disease pathogenesis. METHODS Forty-nine adults with DS aged 25-65 underwent positron emission tomography with Pittsburgh compound-B (PIB). Regional PIB binding was assessed with respect to age, clinical, and cognitive status. RESULTS Abnormal PIB binding became evident from 39 years, first in striatum followed by rostral prefrontal-cingulo-parietal regions, then caudal frontal, rostral temporal, primary sensorimotor and occipital, and finally parahippocampal cortex, thalamus, and amygdala. PIB binding was related to age, diagnostic status, and cognitive function. DISCUSSION PIB binding in DS, first appearing in striatum, began around age 40 and was strongly associated with dementia and cognitive decline. The absence of a substantial time lag between amyloid accumulation and cognitive decline contrasts to sporadic/familial AD and suggests this population's suitability for an amyloid primary prevention trial.
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Affiliation(s)
- Tiina Annus
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - Liam R Wilson
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Young T Hong
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | | | - Tim D Fryer
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | | | - Robert Smith
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Istvan Boros
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Jonathan P Coles
- Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Franklin I Aigbirhio
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - David K Menon
- Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Shahid H Zaman
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Fulbourn Hospital, Cambridge, UK
| | - Peter J Nestor
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Anthony J Holland
- Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Fulbourn Hospital, Cambridge, UK
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Gruslys A, Acosta-Cabronero J, Nestor PJ, Williams GB, Ansorge RE. A new fast accurate nonlinear medical image registration program including surface preserving regularization. IEEE Trans Med Imaging 2014; 33:2118-2127. [PMID: 24968094 DOI: 10.1109/tmi.2014.2332370] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Recently inexpensive graphical processing units (GPUs) have become established as a viable alternative to traditional CPUs for many medical image processing applications. GPUs offer the potential of very significant improvements in performance at low cost and with low power consumption. One way in which GPU programs differ from traditional CPU programs is that increasingly elaborate calculations per voxel may not impact of the overall processing time because memory accesses can dominate execution time. This paper presents a new GPU based elastic image registration program named Ezys. The Ezys image registration algorithm belongs to the wide class of diffeomorphic demons but uses surface preserving image smoothing and regularization filters designed for a GPU that would be computationally expensive on a CPU. We describe the methods used in Ezys and present results from two important neuroscience applications. Firstly inter-subject registration for transfer of anatomical labels and secondly longitudinal intra-subject registration to quantify atrophy in individual subjects. Both experiments showed that Ezys registration compares favorably with other popular elastic image registration programs. We believe Ezys is a useful tool for neuroscience and other applications, and also demonstrates the value of developing of novel image processing filters specifically designed for GPUs.
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Diaz-de-Grenu LZ, Acosta-Cabronero J, Williams GB, Nestor PJ. Comparing voxel-based iterative sensitivity and voxel-based morphometry to detect abnormalities in T2-weighted MRI. Neuroimage 2014; 100:379-84. [PMID: 24954279 DOI: 10.1016/j.neuroimage.2014.06.030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2013] [Revised: 06/04/2014] [Accepted: 06/09/2014] [Indexed: 10/25/2022] Open
Abstract
This study aimed to test the superiority proposed by Abbott et al. (2011) of their Voxel based iterative sensitivity (VBIS) method over Voxel Based Morphometry using T2-weighted images (T2-VBM), in detecting intensity changes in Alzheimer's disease (AD). A comparison was made first in simulated intensity lesions and then in AD patients. Intensity changes were evaluated in the whole-brain with VBIS and with a simple intensity-based approach and in specific tissue classes with the conventional VBM method of using tissue probability segments. Results showed that VBIS performed well in the simulated environment though it showed no superiority in detecting the lesion compared to the much simpler VBM approach. The VBIS method, however, failed to detect any meaningful signal intensity reduction in AD patient data. Moreover, its whole brain approach was contaminated by the excess cerebrospinal fluid signal (very bright on T2-weighted scans) in areas of maximal measurable atrophy (mesial temporal lobes); this gave rise to spurious signal intensity increases in these regions in AD. The same artefact was observed for both intensity-based methods but not with the conventional VBM approach of performing statistics on grey matter segments. In conclusion, no evidence was found to indicate that VBIS offers benefits over T2-VBM in AD, nor in simulation intensity lesions. The study highlights the necessity of empirically testing voxel-based analysis techniques rather than merely claiming superiority of one method over another on theoretical grounds.
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Affiliation(s)
- Lara Z Diaz-de-Grenu
- Herchel Smith Building for Brain and Mind Sciences, Department of Clinical Neurosciences, University of Cambridge School of Clinical Medicine, Cambridge, UK.
| | - Julio Acosta-Cabronero
- Herchel Smith Building for Brain and Mind Sciences, Department of Clinical Neurosciences, University of Cambridge School of Clinical Medicine, Cambridge, UK; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
| | - Guy B Williams
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge School of Clinical Medicine, Cambridge, UK.
| | - Peter J Nestor
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
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Acosta-Cabronero J, Nestor PJ. Diffusion tensor imaging in Alzheimer's disease: insights into the limbic-diencephalic network and methodological considerations. Front Aging Neurosci 2014; 6:266. [PMID: 25324775 PMCID: PMC4183111 DOI: 10.3389/fnagi.2014.00266] [Citation(s) in RCA: 74] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2014] [Accepted: 09/15/2014] [Indexed: 11/25/2022] Open
Abstract
Glucose hypometabolism and gray matter atrophy are well known consequences of Alzheimer's disease (AD). Studies using these measures have shown that the earliest clinical stages, in which memory impairment is a relatively isolated feature, are associated with degeneration in an apparently remote group of areas—mesial temporal lobe (MTL), diencephalic structures such as anterior thalamus and mammillary bodies, and posterior cingulate. These sites are thought to be strongly anatomically inter-connected via a limbic-diencephalic network. Diffusion tensor imaging or DTI—an imaging technique capable of probing white matter tissue microstructure—has recently confirmed degeneration of the white matter connections of the limbic-diencephalic network in AD by way of an unbiased analysis strategy known as tract-based spatial statistics (TBSS). The present review contextualizes the relevance of these findings, in which the fornix is likely to play a fundamental role in linking MTL and diencephalon. An interesting by-product of this work has been in showing that alterations in diffusion behavior are complex in AD—while early studies tended to focus on fractional anisotropy, recent work has highlighted that this measure is not the most sensitive to early changes. Finally, this review will discuss in detail several technical aspects of DTI both in terms of image acquisition and TBSS analysis as both of these factors have important implications to ensure reliable observations are made that inform understanding of neurodegenerative diseases.
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Affiliation(s)
- Julio Acosta-Cabronero
- Brain Plasticity and Neurodegeneration Group, German Center for Neurodegenerative Diseases (DZNE) Magdeburg, Germany
| | - Peter J Nestor
- Brain Plasticity and Neurodegeneration Group, German Center for Neurodegenerative Diseases (DZNE) Magdeburg, Germany
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Cardenas-Blanco A, Machts J, Acosta-Cabronero J, Kaufmann J, Abdulla S, Kollewe K, Petri S, Heinze HJ, Dengler R, Vielhaber S, Nestor PJ. Central white matter degeneration in bulbar- and limb-onset amyotrophic lateral sclerosis. J Neurol 2014; 261:1961-7. [PMID: 25059391 DOI: 10.1007/s00415-014-7434-4] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Revised: 07/03/2014] [Accepted: 07/04/2014] [Indexed: 11/30/2022]
Abstract
Previous studies using diffusion tensor imaging (DTI) have examined for differences between bulbar- and limb-onset amyotrophic lateral sclerosis (ALS). Findings between studies have been markedly inconsistent, though possibly as a consequence of poor matching for confounding variables. To address this problem, this study contrasted the DTI profiles of limb-onset (ALS-L) and bulbar-onset (ALS-B) in groups that were tightly matched for the potential confounding effects of power, age, cognitive impairment and motor dysfunction. 14 ALS-L and 14 ALS-B patients were selected from a large prospective study so as to be matched on clinical and demographic features. All subjects, including 29 controls, underwent neuropsychological and neurological assessment. Tract-based spatial statistics and region of interest techniques were used to analyse fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (λ₁). Extensive bilateral FA and RD changes along the corticospinal tract were found in ALS-B compared to controls, p (corrected) <0.05; a similar distribution was seen for ALS-L at a less stringent statistical threshold. ROI analyses also showed more significant changes in ALS-B than ALS-L when each was compared to controls; for FA, MD and RD the changes reached statistical significance in the direct contrast between the two patient groups. With careful matching for confounding factors, the results suggest that ALS-B is associated with greater central white matter degeneration than ALS-L, possibly contributing to the known worse prognosis of ALS-B. The study, however, found no evidence that the spatial distribution of white matter degeneration differs between these groups.
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Affiliation(s)
- Arturo Cardenas-Blanco
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Strasse 44, 39120, Magdeburg, Germany,
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Diaz-de-Grenu LZ, Acosta-Cabronero J, Chong YFV, Pereira JMS, Sajjadi SA, Williams GB, Nestor PJ. A brief history of voxel-based grey matter analysis in Alzheimer's disease. J Alzheimers Dis 2014; 38:647-59. [PMID: 24037033 DOI: 10.3233/jad-130362] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Voxel-based morphometry (VBM) and cortical thickness measurement are common techniques to identify regional atrophy in neurodegenerative diseases such as Alzheimer's disease (AD). Because studies employing these methods draw conclusions regarding patterns of regional cortical degeneration, it is important to be aware of their possible limitations. To evaluate the effect of different VBM versions, we performed voxel-based analyses through successive versions-from SPM99 to SPM8-as well as FSL-VBM on n = 20 AD patients and n = 20 controls. Reproducibility was assessed in an independent sample, again of n = 20 per group, from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Further, we tested the hypothesis that VBM can sensitively detect hippocampal atrophy, but is relatively insensitive to changes in the cortical ribbon, by contrasting VBM with FreeSurfer cortical thickness measurements. The results with both datasets confirmed that VBM preferentially identifies grey matter lesions in the mesial temporal lobe but is largely insensitive to isocortical atrophy. In contrast, FreeSurfer identified thinning of cortical ribbon association cortex more significant in post- rather than pre-Rolandic areas and with relative preservation of primary sensory-motor regions-in other words precisely as would be expected in AD. The results highlight a bias that VBM has toward detecting mesial temporal lobe atrophy. This finding has important implications for interpretation of clinical and cognitive studies in AD.
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Affiliation(s)
- Lara Z Diaz-de-Grenu
- Herchel Smith Building for Brain and Mind Sciences, Department of Clinical Neurosciences, University of Cambridge School of Clinical Medicine, Cambridge, UK
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del Campo N, Fryer TD, Hong YT, Smith R, Brichard L, Acosta-Cabronero J, Chamberlain SR, Tait R, Izquierdo D, Regenthal R, Dowson J, Suckling J, Baron JC, Aigbirhio FI, Robbins TW, Sahakian BJ, Müller U. A positron emission tomography study of nigro-striatal dopaminergic mechanisms underlying attention: implications for ADHD and its treatment. ACTA ACUST UNITED AC 2013; 136:3252-70. [PMID: 24163364 PMCID: PMC4125626 DOI: 10.1093/brain/awt263] [Citation(s) in RCA: 73] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Through the combined use of 18F-fallypride positron emission tomography and magnetic resonance imaging this study examined the neural mechanisms underlying the attentional deficits associated with attention deficit/hyperactivity disorder and their potential reversal with a single therapeutic dose of methylphenidate. Sixteen adult patients with attention deficit/hyperactivity disorder and 16 matched healthy control subjects were positron emission tomography and magnetic resonance imaging scanned and tested on a computerized sustained attention task after oral methylphenidate (0.5 mg/kg) and placebo administration in a within-subject, double-blind, cross-over design. Although patients with attention deficit/hyperactivity disorder as a group showed significant attentional deficits and reduced grey matter volume in fronto-striato-cerebellar and limbic networks, they had equivalent D2/D3 receptor availability and equivalent increases in endogenous dopamine after methylphenidate treatment to that observed in healthy control subjects. However, poor attentional performers drawn from both the attention deficit/hyperactivity disorder and the control groups had significantly reduced left caudate dopamine activity. Methylphenidate significantly increased dopamine levels in all nigro-striatal regions, thereby normalizing dopamine levels in the left caudate in low performers. Behaviourally, methylphenidate improved sustained attention in a baseline performance-dependent manner, irrespective of diagnosis. This finding was accompanied by an equally performance-dependent effect of the drug on dopamine release in the midbrain, whereby low performers showed reduced dopamine release in this region. Collectively, these findings support a dimensional model of attentional deficits and underlying nigro-striatal dopaminergic mechanisms of attention deficit/hyperactivity disorder that extends into the healthy population. Moreover, they confer midbrain dopamine autoreceptors a hitherto neglected role in the therapeutic effects of oral methylphenidate in attention deficit/hyperactivity disorder. The absence of significant case–control differences in D2/D3 receptor availability (despite the observed relationships between dopamine activity and attention) suggests that dopamine dysregulation per se is unlikely to be the primary cause underlying attention deficit/hyperactivity disorder pathology in adults. This conclusion is reinforced by evidence of neuroanatomical changes in the same set of patients with attention deficit/hyperactivity disorder.
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Affiliation(s)
- Natalia del Campo
- 1 Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
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Acosta-Cabronero J, Williams GB, Cardenas-Blanco A, Arnold RJ, Lupson V, Nestor PJ. In vivo quantitative susceptibility mapping (QSM) in Alzheimer's disease. PLoS One 2013; 8:e81093. [PMID: 24278382 PMCID: PMC3836742 DOI: 10.1371/journal.pone.0081093] [Citation(s) in RCA: 204] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2013] [Accepted: 10/09/2013] [Indexed: 12/12/2022] Open
Abstract
Background This study explores the magnetostatic properties of the Alzheimer's disease brain using a recently proposed, magnetic resonance imaging, postprocessed contrast mechanism. Quantitative susceptibility mapping (QSM) has the potential to monitor in vivo iron levels by reconstructing magnetic susceptibility sources from field perturbations. However, with phase data acquired at a single head orientation, the technique relies on several theoretical approximations and requires fast-evolving regularisation strategies. Methods In this context, the present study describes a complete methodological framework for magnetic susceptibility measurements with a review of its theoretical foundations. Findings and Significance The regional and whole-brain cross-sectional comparisons between Alzheimer's disease subjects and matched controls indicate that there may be significant magnetic susceptibility differences for deep brain nuclei – particularly the putamen – as well as for posterior grey and white matter regions. The methodology and findings described suggest that the QSM method is ready for larger-scale clinical studies.
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Affiliation(s)
- Julio Acosta-Cabronero
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Neurology Unit, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
- * E-mail:
| | - Guy B. Williams
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
| | | | - Robert J. Arnold
- Neurology Unit, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Victoria Lupson
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Peter J. Nestor
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
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Pereira JMS, Acosta-Cabronero J, Pengas G, Xiong L, Nestor PJ, Williams GB. VBM with viscous fluid registration of gray matter segments in SPM. Front Aging Neurosci 2013; 5:30. [PMID: 23874298 PMCID: PMC3711012 DOI: 10.3389/fnagi.2013.00030] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2013] [Accepted: 06/21/2013] [Indexed: 11/13/2022] Open
Abstract
Improved registration of gray matter segments in SPM has been achieved with the DARTEL algorithm. Previous work from our group suggested, however, that such improvements may not translate to studies of clinical groups. To address the registration issue in atrophic brains, this paper relaxed the condition of diffeomorphism, central to DARTEL, and made use of a viscous fluid registration model with limited regularization constraints to register the modulated gray matter probability maps to an intra-population template. Quantitative analysis of the registration results after the additional viscous fluid step showed no worsening of co-localization of fiducials compared to DARTEL or unified segmentation methods, and the resulting voxel based morphometry (VBM) analyses were able to better identify atrophic regions and to produce results with fewer apparent false positives. DARTEL showed great sensitivity to atrophy, but the resulting VBM maps presented broad, amorphous regions of significance that are hard to interpret. We propose that the condition of diffeomorphism is not necessary for basic VBM studies in atrophic populations, but also that it has disadvantages that must be taken into consideration before a study. The presented viscous fluid registration method is proposed for VBM studies to enhance sensitivity and localizing power.
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Affiliation(s)
- Joao M S Pereira
- Laboratory of Biostatistics and Medical Informatics, IBILI - Faculty of Medicine, University of Coimbra Coimbra, Portugal ; Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge Cambridge, UK
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Sajjadi SA, Acosta-Cabronero J, Patterson K, Diaz-de-Grenu LZ, Williams GB, Nestor PJ. Diffusion tensor magnetic resonance imaging for single subject diagnosis in neurodegenerative diseases. Brain 2013; 136:2253-61. [DOI: 10.1093/brain/awt118] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Acosta-Cabronero J, Alley S, Williams GB, Pengas G, Nestor PJ. Diffusion tensor metrics as biomarkers in Alzheimer's disease. PLoS One 2012; 7:e49072. [PMID: 23145075 PMCID: PMC3492261 DOI: 10.1371/journal.pone.0049072] [Citation(s) in RCA: 90] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2012] [Accepted: 10/04/2012] [Indexed: 11/18/2022] Open
Abstract
Background Although diffusion tensor imaging has been a major research focus for Alzheimer’s disease in recent years, it remains unclear whether it has sufficient stability to have biomarker potential. To date, frequently inconsistent results have been reported, though lack of standardisation in acquisition and analysis make such discrepancies difficult to interpret. There is also, at present, little knowledge of how the biometric properties of diffusion tensor imaging might evolve in the course of Alzheimer’s disease. Methods The biomarker question was addressed in this study by adopting a standardised protocol both for the whole brain (tract-based spatial statistics), and for a region of interest: the midline corpus callosum. In order to study the evolution of tensor changes, cross-sectional data from very mild (N = 21) and mild (N = 22) Alzheimer’s disease patients were examined as well as a longitudinal cohort (N = 16) that had been rescanned at 12 months. Findings and Significance The results revealed that increased axial and mean diffusivity are the first abnormalities to occur and that the first region to develop such significant differences was mesial parietal/splenial white matter; these metrics, however, remained relatively static with advancing disease indicating they are suitable as ‘state-specific’ markers. In contrast, increased radial diffusivity, and therefore decreased fractional anisotropy–though less detectable early–became increasingly abnormal with disease progression, and, in the splenium of the corpus callosum, correlated significantly with dementia severity; these metrics therefore appear ‘stage-specific’ and would be ideal for monitoring disease progression. In addition, the cross-sectional and longitudinal analyses showed that the progressive abnormalities in radial diffusivity and fractional anisotropy always occurred in areas that had first shown an increase in axial and mean diffusivity. Given that the former two metrics correlate with dementia severity, but the latter two did not, it would appear that increased axial diffusivity represents an upstream event that precedes neuronal loss.
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Affiliation(s)
- Julio Acosta-Cabronero
- Cognition, Memory and Language Group, Neurology Unit, Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.
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Alexander SK, Acosta-Cabronero J, Pengas G, Diaz-de-Grenu L, Nestor PJ. BEYOND THE HIPPOCAMPUS: MEMORY IMPAIRMENT IN AD MIGHT ALSO RELATE TO RETROSPLENIAL DAMAGE. J Neurol Neurosurg Psychiatry 2012. [DOI: 10.1136/jnnp-2012-304200a.58] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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