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Romascano D, Piredda GF, Caneschi S, Hilbert T, Corredor R, Maréchal B, Kober T, Ledoux JB, Fornari E, Hagmann P, Denervaud S. Normative volumes and relaxation times at 3T during brain development. Sci Data 2024; 11:429. [PMID: 38664431 PMCID: PMC11045735 DOI: 10.1038/s41597-024-03267-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
While research has unveiled and quantified brain markers of abnormal neurodevelopment, clinicians still work with qualitative metrics for MRI brain investigation. The purpose of the current article is to bridge the knowledge gap between case-control cohort studies and individual patient care. Here, we provide a unique dataset of seventy-three 3-to-17 years-old healthy subjects acquired with a 6-minute MRI protocol encompassing T1 and T2 relaxation quantitative sequence that can be readily implemented in the clinical setting; MP2RAGE for T1 mapping and the prototype sequence GRAPPATINI for T2 mapping. White matter and grey matter volumes were automatically quantified. We further provide normative developmental curves based on these two imaging sequences; T1, T2 and volume normative ranges with respect to age were computed, for each ROI of a pediatric brain atlas. This open-source dataset provides normative values allowing to position individual patients acquired with the same protocol on the brain maturation curve and as such provides potentially useful quantitative biomarkers facilitating precise and personalized care.
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Affiliation(s)
- David Romascano
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland.
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland.
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark.
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Samuele Caneschi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ricardo Corredor
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Signal Processing laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jean-Baptiste Ledoux
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | | | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
| | - Solange Denervaud
- Department of Radiology, Lausanne University Hospital and University of Lausanne, 1011, Lausanne, Switzerland
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Mahmoudi N, Dadak M, Bronzlik P, Maudsley AA, Sheriff S, Lanfermann H, Ding XQ. Microstructural and Metabolic Changes in Normal Aging Human Brain Studied with Combined Whole-Brain MR Spectroscopic Imaging and Quantitative MR Imaging. Clin Neuroradiol 2023; 33:993-1005. [PMID: 37336867 PMCID: PMC10654209 DOI: 10.1007/s00062-023-01300-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/27/2023] [Indexed: 06/21/2023]
Abstract
PURPOSE This study aimed to detect age-related brain metabolic and microstructural changes in healthy human brains by the use of whole-brain proton magnetic resonance spectroscopic imaging (1H‑MRSI) and quantitative MR imaging (qMRI). METHODS In this study, 60 healthy participants with evenly distributed ages (between 21 and 69 years) and sex underwent MRI examinations at 3T including whole-brain 1H‑MRSI. The concentrations of the metabolites N‑acetylaspartate (NAA), choline-containing compounds (Cho), total creatine and phosphocreatine (tCr), glutamine and glutamate (Glx), and myo-inositol (mI), as well as the brain relaxation times T2, T2' and T1 were measured in 12 regions of interest (ROI) in each hemisphere. Correlations between measured parameters and age were estimated with linear regression analysis and Pearson's correlation test. RESULTS Significant age-related changes of brain regional metabolite concentrations and tissue relaxation times were found: NAA decreased in eight of twelve ROIs, Cho increased in three ROIs, tCr in four ROIs, and mI in three ROIs. Glx displayed a significant decrease in one ROI and an increase in another ROI. T1 increased in four ROIs and T2 in one ROI, while T2' decreased in two ROIs. A negative correlation of tCr concentrations with T2' relaxation time was found in one ROI as well as the positive correlations of age-related T1 relaxation time with concentrations of tCr, mI, Glx and Cho in another ROI. CONCLUSION Normal aging in human brain is associated with coexistent brain regional metabolic alterations and microstructural changes, which may be related to age-related decline in cognitive, affective and psychomotor domains of life in the older population.
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Affiliation(s)
- N Mahmoudi
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany.
| | - M Dadak
- Department of Diagnostic and Interventional Radiology and Neuroradiology, St. Vincenz Hospital Paderborn, Paderborn, Germany
| | - P Bronzlik
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - A A Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, FL, USA
| | - S Sheriff
- Department of Radiology, University of Miami School of Medicine, Miami, FL, USA
| | - H Lanfermann
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - X-Q Ding
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
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Filo S, Shaharabani R, Bar Hanin D, Adam M, Ben-David E, Schoffman H, Margalit N, Habib N, Shahar T, Mezer AA. Non-invasive assessment of normal and impaired iron homeostasis in the brain. Nat Commun 2023; 14:5467. [PMID: 37699931 PMCID: PMC10497590 DOI: 10.1038/s41467-023-40999-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 08/17/2023] [Indexed: 09/14/2023] Open
Abstract
Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissue's iron homeostasis remains a challenge. We present a magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2* relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron ions. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors' iron homeostasis, and enhances the distinction between tumor tissue and non-pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains.
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Affiliation(s)
- Shir Filo
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Rona Shaharabani
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Daniel Bar Hanin
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Miriam Adam
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Eliel Ben-David
- The Department of Radiology, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Hanan Schoffman
- The Laboratory of Molecular Neuro-Oncology, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Nevo Margalit
- The Department of Neurosurgery, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Naomi Habib
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Tal Shahar
- The Laboratory of Molecular Neuro-Oncology, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
- The Department of Neurosurgery, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
- The Department of Neurosurgery, Tel Aviv Sourasky Medical Center, Affiliated with Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Aviv A Mezer
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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4
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Dinçer HA, Ağıldere AM, Gökçay D. T1 relaxation time is prolonged in healthy aging: a whole brain study. Turk J Med Sci 2023; 53:675-684. [PMID: 37476907 PMCID: PMC10387954 DOI: 10.55730/1300-0144.5630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 01/07/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND : Measurement of tissue characteristics such as the longitudinal relaxation time (T1) provides complementary information to the volumetric and surface based structural analyses. We aimed to investigate T1 relaxation time characteristics in healthy aging via an exploratory design in the whole brain. The data processing pipeline was designed to minimize errors related to aging effects such as atrophy. METHODS Sixty healthy participants underwent MRI scanning (28 F, 32 M, age range: 18-78, 30 young and 30 old) in November 2017-March 2018 at the Bilkent University UMRAM Center. Four images with varying flip angles with FLASH (fast low angle shot magnetic resonance imaging) sequence and a high-resolution structural image with MP-RAGE (Magnetization Prepared - RApid Gradient Echo) were acquired. T1 relaxation times of the entire brain were mapped by using the region of interest (ROI) based method on 134 brain areas in young and old populations. RESULTS T1 prolongation was observed in various subcortical (bilateral hippocampus, caudate and thalamus) and cortical brain structures (bilateral precentral gyrus, bilateral middle frontal gyrus, bilateral supplementary motor area (SMA), left middle occipital gyrus, bilateral postcentral gyrus and bilateral Heschl's gyrus) as well as cerebellar regions (GM regions of cerebellum: bilateral cerebellum III, cerebellum IV V, cerebellum X, cerebellar vermis u 4 5, cerebellar vermis u 9 and WM cerebellar regions: left cerebellum IX, bilateral cerebellum X and cerebellar vermis u 4 5). DISCUSSION T1 mapping provides a practical quantitative MRI (qMRI) methodology for studying the tissue characteristics in healthy aging. T1 values are significantly increased in the aging group among half of the studied ROIs (57 ROIs out of 134).
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Affiliation(s)
- Hayriye Aktaş Dinçer
- Department of Biomedical Engineering, Institute of Natural and Applied Sciences, Middle East Technical University, Ankara, Turkey
| | | | - Didem Gökçay
- Department of Medical Informatics, Informatics Institute, Middle East Technical University, Ankara, Turkey
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5
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Goto M, Fukunaga I, Hagiwara A, Fujita S, Hori M, Kamagata K, Aoki S, Abe O, Sakamoto H, Sakano Y, Kyogoku S, Daida H. Analysis of synthetic magnetic resonance images by multi-channel segmentation increases accuracy of volumetry in the putamen and decreases mis-segmentation in the dural sinuses. Acta Radiol 2023; 64:741-750. [PMID: 35350871 DOI: 10.1177/02841851221089835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Voxel-based morphometry (VBM) using magnetic resonance imaging (MR) has been used to estimate cortical atrophy associated with various diseases. However, there are mis-segmentations of segmented gray matter image in VBM. PURPOSE To study a twofold evaluation of single- and multi-channel segmentation using synthetic MR images: (1) mis-segmentation of segmented gray matter images in transverse and cavernous sinuses; and (2) accuracy and repeatability of segmented gray matter images. MATERIAL AND METHODS A total of 13 healthy individuals were scanned with 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) sequence on a 1.5-T scanner. Three of the 13 healthy participants were scanned five consecutive times for evaluation of repeatability. We used SyMRI software to create images with three contrasts: T1-weighted (T1W), T2-weighted (T2W), and proton density-weighted (PDW) images. Manual regions of interest (ROI) on T1W imaging were individually set as the gold standard in the transverse sinus, cavernous sinus, and putamen. Single-channel (T1W) and multi-channel (T1W + T2W, T1W + PDW, and T1W + T2W + PDW imaging) segmentations were performed with statistical parametric mapping 12 software. RESULTS We found that mis-segmentations in both the transverse and cavernous sinuses were large in single-channel segmentation compared with multi-channel segmentations. Furthermore, the accuracy of segmented gray matter images in the putamen was high in both multi-channel T1W + PDW and T1W + T2W + PDW segmentations compared with other segmentations. Finally, the highest repeatability of left putamen volumetry was found with multi-channel segmentation T1WI + PDWI. CONCLUSION Multi-channel segmentation with T1WI + PDWI provides good results for VBM compared with single-channel and other multi-channel segmentations.
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Affiliation(s)
- Masami Goto
- Department of Radiological Technology, Faculty of Health Science, 12847Juntendo University, Tokyo, Japan
| | - Issei Fukunaga
- Department of Radiological Technology, Faculty of Health Science, 12847Juntendo University, Tokyo, Japan
| | - Akifumi Hagiwara
- Department of Radiology, 12847Juntendo University School of Medicine, Tokyo, Japan
| | - Shohei Fujita
- Department of Radiology, 12847Juntendo University School of Medicine, Tokyo, Japan.,Department of Radiology, 13143The University of Tokyo Hospital, Tokyo, Japan
| | - Masaaki Hori
- Department of Radiology, 12847Juntendo University School of Medicine, Tokyo, Japan.,Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - Koji Kamagata
- Department of Radiology, 12847Juntendo University School of Medicine, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, 12847Juntendo University School of Medicine, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, 13143The University of Tokyo Hospital, Tokyo, Japan
| | - Hajime Sakamoto
- Department of Radiological Technology, Faculty of Health Science, 12847Juntendo University, Tokyo, Japan
| | - Yasuaki Sakano
- Department of Radiological Technology, Faculty of Health Science, 12847Juntendo University, Tokyo, Japan
| | - Shinsuke Kyogoku
- Department of Radiological Technology, Faculty of Health Science, 12847Juntendo University, Tokyo, Japan
| | - Hiroyuki Daida
- Department of Radiological Technology, Faculty of Health Science, 12847Juntendo University, Tokyo, Japan
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Mapping myelin in white matter with T1-weighted/T2-weighted maps: discrepancy with histology and other myelin MRI measures. Brain Struct Funct 2023; 228:525-535. [PMID: 36692695 PMCID: PMC9944377 DOI: 10.1007/s00429-022-02600-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 11/18/2022] [Indexed: 01/25/2023]
Abstract
The ratio of T1-weighted/T2-weighted magnetic resonance images (T1w/T2w MRI) has been successfully applied at the cortical level since 2011 and is now one of the most used myelin mapping methods. However, no reports have explored the histological validity of T1w/T2w myelin mapping in white matter. Here we compare T1w/T2w with ex vivo postmortem histology and in vivo MRI methods, namely quantitative susceptibility mapping (QSM) and multi-echo T2 myelin water fraction (MWF) mapping techniques. We report a discrepancy between T1w/T2w myelin maps of the human corpus callosum and the histology and analyse the putative causes behind such discrepancy. T1w/T2w does not positively correlate with Luxol Fast Blue (LFB)-Optical Density but shows a weak to moderate, yet significant, negative correlation. On the contrary, MWF is strongly and positively correlated with LFB, whereas T1w/T2w and MWF maps are weakly negatively correlated. The discrepancy between T1w/T2w MRI maps, MWF and histological myelin maps suggests caution in using T1w/T2w as a white matter mapping method at the callosal level. While T1w/T2w imaging may correlate with myelin content at the cortical level, it is not a specific method to map myelin density in white matter.
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Decreased basal ganglia and thalamic iron in early psychotic spectrum disorders are associated with increased psychotic and schizotypal symptoms. Mol Psychiatry 2022; 27:5144-5153. [PMID: 36071113 PMCID: PMC9772130 DOI: 10.1038/s41380-022-01740-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 08/08/2022] [Accepted: 08/10/2022] [Indexed: 01/14/2023]
Abstract
Iron deficits have been reported as a risk factor for psychotic spectrum disorders (PSD). However, examinations of brain iron in PSD remain limited. The current study employed quantitative MRI to examine iron content in several iron-rich subcortical structures in 49 young adult individuals with PSD (15 schizophrenia, 17 schizoaffective disorder, and 17 bipolar disorder with psychotic features) compared with 35 age-matched healthy controls (HC). A parametric approach based on a two-pool magnetization transfer model was applied to estimate longitudinal relaxation rate (R1), which reflects both iron and myelin, and macromolecular proton fraction (MPF), which is specific to myelin. To describe iron content, a synthetic effective transverse relaxation rate (R2*) was modeled using a linear fitting of R1 and MPF. PSD patients compared to HC showed significantly reduced R1 and synthetic R2* across examined regions including the pallidum, ventral diencephalon, thalamus, and putamen areas. This finding was primarily driven by decreases in the subgroup with schizophrenia, followed by schizoaffective disorder. No significant group differences were noted for MPF between PSD and HC while for regional volume, significant reductions in patients were only observed in bilateral caudate, suggesting that R1 and synthetic R2* reductions in schizophrenia and schizoaffective patients likely reflect iron deficits that either occur independently or precede structural and myelin changes. Subcortical R1 and synthetic R2* were also found to be inversely related to positive symptoms within the PSD group and to schizotypal traits across the whole sample. These findings that decreased iron in subcortical regions are associated with PSD risk and symptomatology suggest that brain iron deficiencies may play a role in PSD pathology and warrant further study.
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Sui YV, Masurkar AV, Rusinek H, Reisberg B, Lazar M. Cortical myelin profile variations in healthy aging brain: A T1w/T2w ratio study. Neuroimage 2022; 264:119743. [PMID: 36368498 PMCID: PMC9904172 DOI: 10.1016/j.neuroimage.2022.119743] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 10/31/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022] Open
Abstract
Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.
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Affiliation(s)
- Yu Veronica Sui
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Corresponding author. (Y.V. Sui)
| | - Arjun V. Masurkar
- Department of Neurology, Center for Cognitive Neurology, NYU Grossman School of Medicine, New York, NY, USA,Department of Neuroscience and Physiology, NYU Grossman School of Medicine, New York, NY, USA,Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA
| | - Henry Rusinek
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Barry Reisberg
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Mariana Lazar
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA
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Wu J, Peng S, Zhang Y, Pan B, Chen H, Hu X, Gong NJ. Developmental trajectory of magnetic susceptibility in the healthy rhesus macaque brain. NMR IN BIOMEDICINE 2022; 35:e4750. [PMID: 35474524 DOI: 10.1002/nbm.4750] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 04/21/2022] [Accepted: 04/25/2022] [Indexed: 06/14/2023]
Abstract
Quantitative susceptibility mapping (QSM) is used to quantify iron deposition in non-human primates in our study. Although QSM has many applications in detecting iron deposits in the human brain, including the distribution of iron deposits in specific brain regions, the change of iron deposition with aging, and the comparison of iron deposits between diseased groups and healthy controls, few studies have applied QSM to non-human primates, while most animal brain experiments focus on biochemical and anatomical results instead of non-invasive experiments. Additionally, brain imaging in children's research is difficult, but can be substituted using young rhesus monkeys, which are very similar to humans, as research animals. Therefore, understanding the relationship between iron deposition and age in rhesus macaques' brains can offer insights into both the developmental trajectory of magnetic susceptibility in the animal model and the correlated evidence in children's research. Twenty-three healthy rhesus macaque monkeys (23 ± 7.85 years, range 2-29 years) were included in this research. Seven regions of interest (ROIs-globus pallidus, substantia nigra, dentate nucleus, caudate nucleus, putamen, thalamus, red nucleus) have been analyzed in terms of QSM and R2 * (apparent relaxation rate). Susceptibility in most ROIs correlated significantly with the growth of age, similarly to the results for R2 *, but showed different trends in the thalamus and red nucleus, which may be caused by the different sensitivities of myelination and iron deposition in R2 * and QSM analysis. By assessing the correlation between iron content and age in healthy rhesus macaques' brains using QSM, we provide a piece of pilot information on normality for advanced animal disease models. Meanwhile, this study also could serve as the normative basis for further clinical studies using QSM for iron content quantification. Due to the comparison of the susceptibility on the same experimental objects, this research can also provide practical support for future research on characteristics for QSM and R2 *.
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Affiliation(s)
- Jing Wu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Siyue Peng
- RadioDynamic Healthcare, Shanghai, Shanghai, China
| | - Yuhua Zhang
- National Resource Center for Non-human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Boyang Pan
- RadioDynamic Healthcare, Shanghai, Shanghai, China
| | - Honghua Chen
- RadioDynamic Healthcare, Shanghai, Shanghai, China
| | - Xintian Hu
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Nan-Jie Gong
- Vector Lab for Intelligent Medical Imaging and Neural Engineering, International Innovation Center of Tsinghua University, Shanghai, China
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10
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Fernandez-Alvarez M, Atienza M, Zallo F, Matute C, Capetillo-Zarate E, Cantero JL. Linking Plasma Amyloid Beta and Neurofilament Light Chain to Intracortical Myelin Content in Cognitively Normal Older Adults. Front Aging Neurosci 2022; 14:896848. [PMID: 35783126 PMCID: PMC9247578 DOI: 10.3389/fnagi.2022.896848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/23/2022] [Indexed: 11/29/2022] Open
Abstract
Evidence suggests that lightly myelinated cortical regions are vulnerable to aging and Alzheimer’s disease (AD). However, it remains unknown whether plasma markers of amyloid and neurodegeneration are related to deficits in intracortical myelin content, and whether this relationship, in turn, is associated with altered patterns of resting-state functional connectivity (rs-FC). To shed light into these questions, plasma levels of amyloid-β fragment 1–42 (Aβ1–42) and neurofilament light chain (NfL) were measured using ultra-sensitive single-molecule array (Simoa) assays, and the intracortical myelin content was estimated with the ratio T1-weigthed/T2-weighted (T1w/T2w) in 133 cognitively normal older adults. We assessed: (i) whether plasma Aβ1–42 and/or NfL levels were associated with intracortical myelin content at different cortical depths and (ii) whether cortical regions showing myelin reductions also exhibited altered rs-FC patterns. Surface-based multiple regression analyses revealed that lower plasma Aβ1–42 and higher plasma NfL were associated with lower myelin content in temporo-parietal-occipital regions and the insular cortex, respectively. Whereas the association with Aβ1–42 decreased with depth, the NfL-myelin relationship was most evident in the innermost layer. Older individuals with higher plasma NfL levels also exhibited altered rs-FC between the insula and medial orbitofrontal cortex. Together, these findings establish a link between plasma markers of amyloid/neurodegeneration and intracortical myelin content in cognitively normal older adults, and support the role of plasma NfL in boosting aberrant FC patterns of the insular cortex, a central brain hub highly vulnerable to aging and neurodegeneration.
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Affiliation(s)
- Marina Fernandez-Alvarez
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Mercedes Atienza
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Fatima Zallo
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Carlos Matute
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Estibaliz Capetillo-Zarate
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Jose L. Cantero
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- *Correspondence: Jose L. Cantero,
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11
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The Effect of Gadolinium-Based Contrast Agents on Longitudinal Changes of Magnetic Resonance Imaging Signal Intensities and Relaxation Times in the Aging Rat Brain. Invest Radiol 2022; 57:453-462. [PMID: 35125411 PMCID: PMC9172901 DOI: 10.1097/rli.0000000000000857] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
The aim of the study was to investigate the possible influence of changes in the brain caused by age on relaxometric and relaxation time–weighted magnetic resonance imaging (MRI) parameters in the deep cerebellar nuclei (DCN) and the globus pallidus (GP) of Gd-exposed and control rats over the course of 1 year.
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12
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Hertanu A, Soustelle L, Buron J, Le Priellec J, Cayre M, Le Troter A, Varma G, Alsop DC, Durbec P, Girard OM, Duhamel G. T 1D -weighted ihMT imaging - Part II. Investigating the long- and short-T 1D components correlation with myelin content. Comparison with R 1 and the macromolecular proton fraction. Magn Reson Med 2022; 87:2329-2346. [PMID: 35001427 DOI: 10.1002/mrm.29140] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 10/29/2021] [Accepted: 12/12/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE To investigate the long- and short-T1D components correlation with myelin content using inhomogeneous magnetization transfer (ihMT) high-pass and band-pass T1D -filters and to compare ihMT, R1 , and the macromolecular proton fraction (MPF) for myelin specific imaging. METHODS The 3D ihMT rapid gradient echo (ihMTRAGE) sequences with increasing switching times (Δt) were used to derive ihMT high-pass T1D -filters with increasing T1D cutoff values and an ihMT band-pass T1D -filter for components in the 100 µs to 1 ms range. 3D spoiled gradient echo quantitative MT (SPGR-qMT) protocols were used to derive R1 and MPF maps. The specificity of R1 , MPF, and ihMT T1D -filters was evaluated by comparison with two histological reference techniques for myelin imaging. RESULTS The higher contribution of long-T1D s as compared to the short components as Δt got longer led to an increase in the specificity to myelination. In contrast, focusing on the signal originating from a narrow range of short-T1D s (< 1 ms) as isolated by the band-pass T1D -filter led to lower specificity. In addition, the significantly lower r2 correlation coefficient of the band-pass T1D -filter suggests that the origin of short-T1D components is mostly associated with non-myelin protons. Also, the important contribution of short-T1D s to the estimated MPF, explains its low specificity to myelination as compared to the ihMT high-pass T1D -filters. CONCLUSION Long-T1D components imaging by means of ihMT high-pass T1D -filters is proposed as an MRI biomarker for myelin content. Future studies should enable the investigation of the sensitivity of ihMT T1D -filters for demyelinating processes.
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Affiliation(s)
- Andreea Hertanu
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Lucas Soustelle
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Julie Buron
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France.,Aix Marseille Univ, CNRS, IBDM, Marseille, France
| | | | - Myriam Cayre
- Aix Marseille Univ, CNRS, IBDM, Marseille, France
| | - Arnaud Le Troter
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Gopal Varma
- Division of MR Research, Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - David C Alsop
- Division of MR Research, Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Olivier M Girard
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Guillaume Duhamel
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
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13
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Miletić S, Bazin PL, Isherwood SJS, Keuken MC, Alkemade A, Forstmann BU. Charting human subcortical maturation across the adult lifespan with in vivo 7 T MRI. Neuroimage 2022; 249:118872. [PMID: 34999202 DOI: 10.1016/j.neuroimage.2022.118872] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 12/20/2021] [Accepted: 01/03/2022] [Indexed: 12/26/2022] Open
Abstract
The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures and ventricles, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.
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Affiliation(s)
- Steven Miletić
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
| | - Pierre-Louis Bazin
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands; Max Planck Institute for Human Cognitive and Brain Sciences, Departments of Neurophysics and Neurology, Stephanstraße 1A, Leipzig, Germany
| | - Scott J S Isherwood
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Max C Keuken
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Anneke Alkemade
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Birte U Forstmann
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
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14
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MacDonald ME, Pike GB. MRI of healthy brain aging: A review. NMR IN BIOMEDICINE 2021; 34:e4564. [PMID: 34096114 DOI: 10.1002/nbm.4564] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 05/08/2021] [Accepted: 05/11/2021] [Indexed: 06/12/2023]
Abstract
We present a review of the characterization of healthy brain aging using MRI with an emphasis on morphology, lesions, and quantitative MR parameters. A scope review found 6612 articles encompassing the keywords "Brain Aging" and "Magnetic Resonance"; papers involving functional MRI or not involving imaging of healthy human brain aging were discarded, leaving 2246 articles. We first consider some of the biogerontological mechanisms of aging, and the consequences of aging in terms of cognition and onset of disease. Morphological changes with aging are reviewed for the whole brain, cerebral cortex, white matter, subcortical gray matter, and other individual structures. In general, volume and cortical thickness decline with age, beginning in mid-life. Prevalent silent lesions such as white matter hyperintensities, microbleeds, and lacunar infarcts are also observed with increasing frequency. The literature regarding quantitative MR parameter changes includes T1 , T2 , T2 *, magnetic susceptibility, spectroscopy, magnetization transfer, diffusion, and blood flow. We summarize the findings on how each of these parameters varies with aging. Finally, we examine how the aforementioned techniques have been used for age prediction. While relatively large in scope, we present a comprehensive review that should provide the reader with sound understanding of what MRI has been able to tell us about how the healthy brain ages.
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Affiliation(s)
- M Ethan MacDonald
- Department of Electrical and Software Engineering, University of Calgary, Calgary, Alberta, Canada
- Departments of Radiology and Clinical Neuroscience, University of Calgary, Calgary, Alberta, Canada
- Healthy Brain Aging Laboratory, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - G Bruce Pike
- Departments of Radiology and Clinical Neuroscience, University of Calgary, Calgary, Alberta, Canada
- Healthy Brain Aging Laboratory, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
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15
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Alrayashi R, Braun RD, Muca A, Kühl A, Hali M, Holt AG. Postmortem neuroimaging: Temporal and spatial sensitivity of manganese-enhanced magnetic resonance imaging (MEMRI) and impact of Mn 2+ uptake. Hear Res 2021; 407:108276. [PMID: 34107410 DOI: 10.1016/j.heares.2021.108276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 04/20/2021] [Accepted: 05/08/2021] [Indexed: 11/29/2022]
Abstract
Magnetic resonance imaging data collection and analysis have been challenges in the field of auditory neuroscience. Recent studies have addressed these concerns by using manganese-enhanced magnetic resonance imaging (MEMRI). Basic challenges for in vivo application of MEMRI in rodents includes how to set inclusion criteria for adequate Mn2+ uptake and whether valid data can be collected from brains postmortem. Since brain Mn2+ uptake is complete within 2-4 h and clearance can take 2-4 weeks, one assumption has been that Mn2+-enhanced R1 values continue to reliably reflect the degree of Mn2+-uptake for some indeterminate time after death. To address these issues, the impact of death on R1 values was determined in rats administered Mn2+ and rats that were not. Images of auditory nuclei were collected at fixed intervals from rats before and after death for up to 10 h postmortem. By taking a ratio of pituitary and muscle T1-W intensities (P/M), a reliable quantitative method for assessing adequate brain Mn2+ uptake was created and suggest that P/M ratios should be adopted to objectively measure the quality of the Mn2+ injection. Postmortem R1 values decreased in all brain regions in both the After Mn2+ and No Mn2+ groups. However, the time-course of postmortem changes in R1 was dependent on brain region and degree of Mn2+ uptake. Thus, postmortem R1 values not only differ after death, but vary with time and across brain regions. Postmortem R1 values in unfixed brain tissue, including the auditory nuclei, should be interpreted with caution.
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Affiliation(s)
- Rasheed Alrayashi
- Department of Ophthalmology, Visual, and Anatomical Sciences, Wayne State University School of Medicine, Detroit, MI, USA
| | - Rod D Braun
- Department of Ophthalmology, Visual, and Anatomical Sciences, Wayne State University School of Medicine, Detroit, MI, USA
| | - Antonela Muca
- Department of Ophthalmology, Visual, and Anatomical Sciences, Wayne State University School of Medicine, Detroit, MI, USA
| | - André Kühl
- Department of Ophthalmology, Visual, and Anatomical Sciences, Wayne State University School of Medicine, Detroit, MI, USA
| | - Mirabela Hali
- Department of Ophthalmology, Visual, and Anatomical Sciences, Wayne State University School of Medicine, Detroit, MI, USA
| | - Avril Genene Holt
- Department of Ophthalmology, Visual, and Anatomical Sciences, Wayne State University School of Medicine, Detroit, MI, USA; John D. Dingell VAMC, Detroit, MI, USA.
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16
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Crescenzo F, Marastoni D, Pisani AI, Tamanti A, Dapor C, Colombi A, Brillo A, Magliozzi R, Pizzini FB, Castellaro M, Calabrese M. The Prognostic Value of White-Matter Selective Double Inversion Recovery MRI Sequence in Multiple Sclerosis: An Exploratory Study. Diagnostics (Basel) 2021; 11:diagnostics11040686. [PMID: 33921278 PMCID: PMC8069390 DOI: 10.3390/diagnostics11040686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 04/08/2021] [Accepted: 04/09/2021] [Indexed: 11/30/2022] Open
Abstract
Using a white-matter selective double inversion recovery sequence (WM-DIR) that suppresses both grey matter (GM) and cerebrospinal fluid (CSF) signals, some white matter (WM) lesions appear surrounded by a dark rim. These dark rim lesions (DRLs) seem to be specific for multiple sclerosis (MS). They could be of great usefulness in clinical practice, proving to increase the MRI diagnostic criteria specificity. The aims of this study are the identification of DRLs on 1.5 T MRI, the exploration of the relationship between DRLs and disease course, the characterization of DRLs with respect to perilesional normal-appearing WM using magnetization transfer imaging, and the investigation of possible differences in the underlying tissue properties by assessing WM-DIR images obtained at 3.0 T MRI. DRLs are frequent in primary progressive MS (PPMS) patients. Amongst relapsing-remitting MS (RRMS) patients, DRLs are associated with a high risk of the disease worsening and secondary progressive MS (SPMS) conversion after 15 years. The mean magnetization transfer ratio (MTR) of DRLs is significantly different from the lesion without the dark rim, suggesting that DRLs correspond to more destructive lesions.
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Affiliation(s)
- Francesco Crescenzo
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
- Neurology Unit, Mater Salutis Hospital, Legnago, 37045 Verona, Italy
| | - Damiano Marastoni
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
| | - Anna Isabella Pisani
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
| | - Agnese Tamanti
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
| | - Caterina Dapor
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
| | - Annalisa Colombi
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
| | - Alessandro Brillo
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
| | - Roberta Magliozzi
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
| | | | - Marco Castellaro
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
| | - Massimiliano Calabrese
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, 37134 Verona, Italy; (F.C.); (D.M.); (A.I.P.); (A.T.); (C.D.); (A.C.); (A.B.); (R.M.); (M.C.)
- Correspondence:
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17
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Seiler A, Nöth U, Hok P, Reiländer A, Maiworm M, Baudrexel S, Meuth S, Rosenow F, Steinmetz H, Wagner M, Hattingen E, Deichmann R, Gracien RM. Multiparametric Quantitative MRI in Neurological Diseases. Front Neurol 2021; 12:640239. [PMID: 33763021 PMCID: PMC7982527 DOI: 10.3389/fneur.2021.640239] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 02/12/2021] [Indexed: 11/27/2022] Open
Abstract
Magnetic resonance imaging (MRI) is the gold standard imaging technique for diagnosis and monitoring of many neurological diseases. However, the application of conventional MRI in clinical routine is mainly limited to the visual detection of macroscopic tissue pathology since mixed tissue contrasts depending on hardware and protocol parameters hamper its application for the assessment of subtle or diffuse impairment of the structural tissue integrity. Multiparametric quantitative (q)MRI determines tissue parameters quantitatively, enabling the detection of microstructural processes related to tissue remodeling in aging and neurological diseases. In contrast to measuring tissue atrophy via structural imaging, multiparametric qMRI allows for investigating biologically distinct microstructural processes, which precede changes of the tissue volume. This facilitates a more comprehensive characterization of tissue alterations by revealing early impairment of the microstructural integrity and specific disease-related patterns. So far, qMRI techniques have been employed in a wide range of neurological diseases, including in particular conditions with inflammatory, cerebrovascular and neurodegenerative pathology. Numerous studies suggest that qMRI might add valuable information, including the detection of microstructural tissue damage in areas appearing normal on conventional MRI and unveiling the microstructural correlates of clinical manifestations. This review will give an overview of current qMRI techniques, the most relevant tissue parameters and potential applications in neurological diseases, such as early (differential) diagnosis, monitoring of disease progression, and evaluating effects of therapeutic interventions.
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Affiliation(s)
- Alexander Seiler
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - Pavel Hok
- Department of Neurology, Palacký University Olomouc and University Hospital Olomouc, Olomouc, Czechia
| | - Annemarie Reiländer
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Michelle Maiworm
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - Simon Baudrexel
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Sven Meuth
- Department of Neurology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Felix Rosenow
- Department of Neurology, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany.,Epilepsy Center Frankfurt Rhine-Main, Center of Neurology and Neurosurgery, University Hospital, Frankfurt, Germany
| | - Helmuth Steinmetz
- Department of Neurology, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - Marlies Wagner
- Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - Elke Hattingen
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany.,Department of Neuroradiology, Goethe University, Frankfurt, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
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18
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Xifra-Porxas A, Ghosh A, Mitsis GD, Boudrias MH. Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques. Neuroimage 2021; 231:117822. [PMID: 33549751 DOI: 10.1016/j.neuroimage.2021.117822] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 01/27/2021] [Accepted: 01/30/2021] [Indexed: 11/30/2022] Open
Abstract
Brain age prediction studies aim at reliably estimating the difference between the chronological age of an individual and their predicted age based on neuroimaging data, which has been proposed as an informative measure of disease and cognitive decline. As most previous studies relied exclusively on magnetic resonance imaging (MRI) data, we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves age prediction using a large cohort of healthy subjects (N = 613, age 18-88 years) from the Cam-CAN repository. To this end, we examined the performance of dimensionality reduction and multivariate associative techniques, namely Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA), to tackle the high dimensionality of neuroimaging data. Using MEG features (mean absolute error (MAE) of 9.60 years) yielded worse performance when compared to using MRI features (MAE of 5.33 years), but a stacking model combining both feature sets improved age prediction performance (MAE of 4.88 years). Furthermore, we found that PCA resulted in inferior performance, whereas CCA in conjunction with Gaussian process regression models yielded the best prediction performance. Notably, CCA allowed us to visualize the features that significantly contributed to brain age prediction. We found that MRI features from subcortical structures were more reliable age predictors than cortical features, and that spectral MEG measures were more reliable than connectivity metrics. Our results provide an insight into the underlying processes that are reflective of brain aging, yielding promise for the identification of reliable biomarkers of neurodegenerative diseases that emerge later during the lifespan.
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Affiliation(s)
- Alba Xifra-Porxas
- Graduate Program in Biological and Biomedical Engineering, McGill University, Montréal, Canada; Center for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Montréal, Canada
| | - Arna Ghosh
- Center for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Montréal, Canada; Integrated Program in Neuroscience, McGill University, Montréal, Canada
| | | | - Marie-Hélène Boudrias
- Center for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Montréal, Canada; School of Physical and Occupational Therapy, McGill University, Montréal, Canada.
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19
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Seiler A, Schöngrundner S, Stock B, Nöth U, Hattingen E, Steinmetz H, Klein JC, Baudrexel S, Wagner M, Deichmann R, Gracien RM. Cortical aging - new insights with multiparametric quantitative MRI. Aging (Albany NY) 2020; 12:16195-16210. [PMID: 32852283 PMCID: PMC7485732 DOI: 10.18632/aging.103629] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 06/22/2020] [Indexed: 02/07/2023]
Abstract
Understanding the microstructural changes related to physiological aging of the cerebral cortex is pivotal to differentiate healthy aging from neurodegenerative processes. The aim of this study was to investigate the age-related global changes of cortical microstructure and regional patterns using multiparametric quantitative MRI (qMRI) in healthy subjects with a wide age range. 40 healthy participants (age range: 2nd to 8th decade) underwent high-resolution qMRI including T1, PD as well as T2, T2* and T2′ mapping at 3 Tesla. Cortical reconstruction was performed with the FreeSurfer toolbox, followed by tests for correlations between qMRI parameters and age. Cortical T1 values were negatively correlated with age (p=0.007) and there was a widespread age-related decrease of cortical T1 involving the frontal and the parietotemporal cortex, while T2 was correlated positively with age, both in frontoparietal areas and globally (p=0.004). Cortical T2′ values showed the most widespread associations across the cortex and strongest correlation with age (r= -0.724, p=0.0001). PD and T2* did not correlate with age. Multiparametric qMRI allows to characterize cortical aging, unveiling parameter-specific patterns. Quantitative T2′ mapping seems to be a promising imaging biomarker of cortical age-related changes, suggesting that global cortical iron deposition is a prominent process in healthy aging.
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Affiliation(s)
- Alexander Seiler
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Sophie Schöngrundner
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Benjamin Stock
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Elke Hattingen
- Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany
| | - Helmuth Steinmetz
- Department of Neurology, Goethe University, Frankfurt am Main, Germany
| | - Johannes C Klein
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Simon Baudrexel
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Marlies Wagner
- Department of Neuroradiology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt am Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
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20
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Straub S, Mangesius S, Emmerich J, Indelicato E, Nachbauer W, Degenhardt KS, Ladd ME, Boesch S, Gizewski ER. Toward quantitative neuroimaging biomarkers for Friedreich's ataxia at 7 Tesla: Susceptibility mapping, diffusion imaging, R 2 and R 1 relaxometry. J Neurosci Res 2020; 98:2219-2231. [PMID: 32731306 PMCID: PMC7590084 DOI: 10.1002/jnr.24701] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 06/12/2020] [Accepted: 07/08/2020] [Indexed: 01/21/2023]
Abstract
Friedreich's ataxia (FRDA) is a rare genetic disorder leading to degenerative processes. So far, no effective treatment has been found. Therefore, it is important to assist the development of medication with imaging biomarkers reflecting disease status and progress. Ten FRDA patients (mean age 37 ± 14 years; four female) and 10 age- and sex-matched controls were included. Acquisition of magnetic resonance imaging (MRI) data for quantitative susceptibility mapping, R1 , R2 relaxometry and diffusion imaging was performed at 7 Tesla. Results of volume of interest (VOI)-based analyses of the quantitative data were compared with a voxel-based morphometry (VBM) evaluation. Differences between patients and controls were assessed using the analysis of covariance (ANCOVA; p < 0.01) with age and sex as covariates, effect size of group differences, and correlations with disease characteristics with Spearman correlation coefficient. For the VBM analysis, a statistical threshold of 0.001 for uncorrected and 0.05 for corrected p-values was used. Statistically significant differences between FRDA patients and controls were found in five out of twelve investigated structures, and statistically significant correlations with disease characteristics were revealed. Moreover, VBM revealed significant white matter atrophy within regions of the brainstem, and the cerebellum. These regions overlapped partially with brain regions for which significant differences between healthy controls and patients were found in the VOI-based quantitative MRI evaluation. It was shown that two independent analyses provided overlapping results. Moreover, positive results on correlations with disease characteristics were found, indicating that these quantitative MRI parameters could provide more detailed information and assist the search for effective treatments.
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Affiliation(s)
- Sina Straub
- Division of Medical Physics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stephanie Mangesius
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Core Facility, Medical University of Innsbruck, Innsbruck, Austria
| | - Julian Emmerich
- Division of Medical Physics, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | | | - Wolfgang Nachbauer
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Katja S Degenhardt
- Division of Medical Physics, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Mark E Ladd
- Division of Medical Physics, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany.,Faculty of Medicine, Heidelberg University, Heidelberg, Germany
| | - Sylvia Boesch
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Elke R Gizewski
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria.,Neuroimaging Core Facility, Medical University of Innsbruck, Innsbruck, Austria
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21
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Age-related differences in cerebral blood flow and cortical thickness with an application to age prediction. Neurobiol Aging 2020; 95:131-142. [PMID: 32798960 DOI: 10.1016/j.neurobiolaging.2020.06.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 06/22/2020] [Accepted: 06/25/2020] [Indexed: 01/08/2023]
Abstract
Cerebral cortex thinning and cerebral blood flow (CBF) reduction are typically observed during normal healthy aging. However, imaging-based age prediction models have primarily used morphological features of the brain. Complementary physiological CBF information might result in an improvement in age estimation. In this study, T1-weighted structural magnetic resonance imaging and arterial spin labeling CBF images were acquired in 146 healthy participants across the adult life span. Sixty-eight cerebral cortex regions were segmented, and the cortical thickness and mean CBF were computed for each region. Linear regression with age was computed for each region and data type, and laterality and correlation matrices were computed. Sixteen predictive models were trained with the cortical thickness and CBF data alone as well as a combination of both data types. The age explained more variance in the cortical thickness data (average R2 of 0.21) than in the CBF data (average R2 of 0.09). All 16 models performed significantly better when combining both measurement types and using feature selection, and thus, we conclude that the inclusion of CBF data marginally improves age estimation.
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22
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Birkl C, Birkl-Toeglhofer AM, Kames C, Goessler W, Haybaeck J, Fazekas F, Ropele S, Rauscher A. The influence of iron oxidation state on quantitative MRI parameters in post mortem human brain. Neuroimage 2020; 220:117080. [PMID: 32585344 DOI: 10.1016/j.neuroimage.2020.117080] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 06/17/2020] [Accepted: 06/18/2020] [Indexed: 12/13/2022] Open
Abstract
A variety of Magnetic Resonance Imaging (MRI) techniques are known to be sensitive to brain iron content. In principle, iron sensitive MRI techniques are based on local magnetic field variations caused by iron particles in tissue. The purpose of this study was to investigate the sensitivity of MR relaxation and magnetization transfer parameters to changes in iron oxidation state compared to changes in iron concentration. Therefore, quantitative MRI parameters including R1, R2, R2∗, quantitative susceptibility maps (QSM) and magnetization transfer ratio (MTR) of post mortem human brain tissue were acquired prior and after chemical iron reduction to change the iron oxidation state and chemical iron extraction to decrease the total iron concentration. All assessed parameters were shown to be sensitive to changes in iron concentration whereas only R2, R2∗ and QSM were also sensitive to changes in iron oxidation state. Mass spectrometry confirmed that iron accumulated in the extraction solution but not in the reduction solution. R2∗ and QSM are often used as markers for iron content. Changes in these parameters do not necessarily reflect variations in iron content but may also be a result of changes in the iron's oxygenation state from ferric towards more ferrous iron or vice versa.
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Affiliation(s)
- Christoph Birkl
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada; Department of Neuroradiology, Medical University of Innsbruck, Austria; Department of Neurology, Medical University of Graz, Austria.
| | - Anna Maria Birkl-Toeglhofer
- Department of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Austria; Diagnostic and Research Institute of Pathology, Medical University of Graz, Austria
| | - Christian Kames
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada; Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Walter Goessler
- Institute of Chemistry, Analytical Chemistry, University of Graz, Austria
| | - Johannes Haybaeck
- Department of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Austria; Diagnostic and Research Institute of Pathology, Medical University of Graz, Austria
| | - Franz Fazekas
- Department of Neurology, Medical University of Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Austria
| | - Alexander Rauscher
- UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada; Department of Physics & Astronomy, University of British Columbia, Vancouver, BC, Canada; Department of Pediatrics (Division of Neurology), University of British Columbia, Vancouver, BC, Canada
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23
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Wei W, Zhang Y, Li Y, Meng Y, Li M, Wang Q, Deng W, Ma X, Palaniyappan L, Zhang N, Li T. Depth-dependent abnormal cortical myelination in first-episode treatment-naïve schizophrenia. Hum Brain Mapp 2020; 41:2782-2793. [PMID: 32239735 PMCID: PMC7294057 DOI: 10.1002/hbm.24977] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 02/14/2020] [Accepted: 02/25/2020] [Indexed: 02/05/2023] Open
Abstract
Myelination is key to effective message passing in the central nervous system and is likely linked to the pathogenesis of schizophrenia (SZ). Emerging evidence indicates that a large portion of intracortical myelin insulates inhibitory interneurons that are highly relevant to pathogenesis of schizophrenia. Here for the first time, we characterized intracortical myelination across the entire cortical surface in first‐episode treatment‐naïve patients with schizophrenia (FES) using T1w/T2w ratio of structural MRI, FES patients exhibited significantly higher myelin content in the left inferior parietal lobe, supramarginal gyrus, and superior temporal gyrus in the superficial layer, as well as left IPL in the middle layer, but significantly lower myelin content in the left middle insula and posterior cingulate gyrus. Years of education, a proxy for onset of functional decline, significantly altered the relationship between abnormal parietal and posterior cingulate myelination and clinical symptoms, indicating that the pathoplastic role of myelination hinges on the age of onset of functional decline. In addition, higher myelination generally related to better cognitive function in younger subjects but worse cognitive function in older subjects. We conclude that FES is characterized by increased myelination of the superficial layers of the parietal–temporal association cortex, but reduced myelination of the cingulo‐insular midcortical layer cortex. Intracortical myelin content affects both cognitive functioning and symptom burden in FES, with the effect conditional upon age and timing of onset of functional decline. These results suggest myelination might be a critical biological target for procognitive interventions in SZ.
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Affiliation(s)
- Wei Wei
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yamin Zhang
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yinfei Li
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Yajin Meng
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Mingli Li
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wei Deng
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xiaohong Ma
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Lena Palaniyappan
- Robarts Research Institute & Department of Psychiatry, University of Western Ontario, London, Ontario, Canada.,Lawson Health Research Institute, London, Ontario, Canada
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - Tao Li
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
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24
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Longitudinal Development of Brain Iron Is Linked to Cognition in Youth. J Neurosci 2020; 40:1810-1818. [PMID: 31988059 DOI: 10.1523/jneurosci.2434-19.2020] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 12/19/2019] [Accepted: 01/04/2020] [Indexed: 11/21/2022] Open
Abstract
Brain iron is vital to multiple aspects of brain function, including oxidative metabolism, myelination, and neurotransmitter synthesis. Atypical iron concentration in the basal ganglia is associated with neurodegenerative disorders in aging and cognitive deficits. However, the normative development of brain iron concentration in adolescence and its relationship to cognition are less well understood. Here, we address this gap in a longitudinal sample of 922 humans aged 8-26 years at the first visit (M = 15.1, SD = 3.72; 336 males, 486 females) with up to four multiecho T2* scans each. Using this sample of 1236 imaging sessions, we assessed the longitudinal developmental trajectories of tissue iron in the basal ganglia. We quantified tissue iron concentration using R2* relaxometry within four basal ganglia regions, including the caudate, putamen, nucleus accumbens, and globus pallidus. The longitudinal development of R2* was modeled using generalized additive mixed models (GAMMs) with splines to capture linear and nonlinear developmental processes. We observed significant increases in R2* across all regions, with the greatest and most prolonged increases occurring in the globus pallidus and putamen. Further, we found that the developmental trajectory of R2* in the putamen is significantly related to individual differences in cognitive ability, such that greater cognitive ability is increasingly associated with greater iron concentration through late adolescence and young-adulthood. Together, our results suggest a prolonged period of basal ganglia iron enrichment that extends into the mid-twenties, with diminished iron concentration associated with poorer cognitive ability during late adolescence.SIGNIFICANCE STATEMENT Brain tissue iron is essential to healthy brain function. Atypical basal ganglia tissue iron levels have been linked to impaired cognition in iron deficient children and adults with neurodegenerative disorders. However, the normative developmental trajectory of basal ganglia iron concentration during adolescence and its association with cognition are less well understood. In the largest study of tissue iron development yet reported, we characterize the developmental trajectory of tissue iron concentration across the basal ganglia during adolescence and provide evidence that diminished iron content is associated with poorer cognitive performance even in healthy youth. These results highlight the transition from adolescence to adulthood as a period of dynamic maturation of tissue iron concentration in the basal ganglia.
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25
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Kupeli A, Kocak M, Goktepeli M, Karavas E, Danisan G. Role of T1 mapping to evaluate brain aging in a healthy population. Clin Imaging 2020; 59:56-60. [DOI: 10.1016/j.clinimag.2019.09.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 07/24/2019] [Accepted: 09/23/2019] [Indexed: 11/25/2022]
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26
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Piredda GF, Hilbert T, Granziera C, Bonnier G, Meuli R, Molinari F, Thiran JP, Kober T. Quantitative brain relaxation atlases for personalized detection and characterization of brain pathology. Magn Reson Med 2019; 83:337-351. [PMID: 31418910 DOI: 10.1002/mrm.27927] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 07/08/2019] [Accepted: 07/12/2019] [Indexed: 12/20/2022]
Abstract
PURPOSE To exploit the improved comparability and hardware independency of quantitative MRI, databases of MR physical parameters in healthy tissue are required, to which tissue properties of patients can be compared. In this work, normative values for longitudinal and transverse relaxation times in the brain were established and tested in single-subject comparisons for detection of abnormal relaxation times. METHODS Relaxometry maps of the brain were acquired from 52 healthy volunteers. After spatially normalizing the volumes into a common space, T1 and T2 inter-subject variability within the healthy cohort was modeled voxel-wise. A method for a single-subject comparison against the atlases was developed by computing z-scores with respect to the established healthy norms. The comparison was applied to two multiple sclerosis and one clinically isolated syndrome cases for a proof of concept. RESULTS The established atlases exhibit a low variation in white matter structures (median RMSE of models equal to 32 ms for T1 and 4 ms for T2 ), indicating that relaxation times are in a narrow range for normal tissues. The proposed method for single-subject comparison detected relaxation time deviations from healthy norms in the example patient data sets. Relaxation times were found to be increased in brain lesions (mean z-scores >5). Moreover, subtle and confluent differences (z-scores ~2-4) were observed in clinically plausible regions (between lesions, corpus callosum). CONCLUSIONS Brain T1 and T2 quantitative norms were derived voxel-wise with low variability in healthy tissue. Example patient deviation maps demonstrated good sensitivity of the atlases for detecting relaxation time alterations.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Cristina Granziera
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Guillaume Bonnier
- Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Swiss Center for Electronics and Microtechnology, Neuchatel, Switzerland
| | - Reto Meuli
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Filippo Molinari
- Biolab, Department of Electronics and Telecommunication, Polytechnic University of Turin, Turin, Italy
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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27
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Lommers E, Simon J, Reuter G, Delrue G, Dive D, Degueldre C, Balteau E, Phillips C, Maquet P. Multiparameter MRI quantification of microstructural tissue alterations in multiple sclerosis. NEUROIMAGE-CLINICAL 2019; 23:101879. [PMID: 31176293 PMCID: PMC6555891 DOI: 10.1016/j.nicl.2019.101879] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 04/23/2019] [Accepted: 05/25/2019] [Indexed: 01/25/2023]
Abstract
Objectives Conventional MRI is not sensitive to many pathological processes underpinning multiple sclerosis (MS) ongoing in normal appearing brain tissue (NABT). Quantitative MRI (qMRI) and a multiparameter mapping (MPM) protocol are used to simultaneously quantify magnetization transfer (MT) saturation, transverse relaxation rate R2* (1/T2*) and longitudinal relaxation rate R1 (1/T1), and assess differences in NABT microstructure between MS patients and healthy controls (HC). Methods This prospective cross-sectional study involves 36 MS patients (21 females, 15 males; age range 22–63 years; 15 relapsing-remitting MS - RRMS; 21 primary or secondary progressive MS - PMS) and 36 age-matched HC (20 females, 16 males); age range 21–61 years). The qMRI maps are computed and segmented in lesions and 3 normal appearing cerebral tissue classes: normal appearing cortical grey matter (NACGM), normal appearing deep grey matter (NADGM), normal appearing white matter (NAWM). Individual median values are extracted for each tissue class and MR parameter. MANOVAs and stepwise regressions assess differences between patients and HC. Results MS patients are characterized by a decrease in MT, R2* and R1 within NACGM (p < .0001) and NAWM (p < .0001). In NADGM, MT decreases (p < .0001) but R2* and R1 remain normal. These observations tend to be more pronounced in PMS. Quantitative MRI parameters are independent predictors of clinical status: EDSS is significantly related to R1 in NACGM and R2* in NADGM; the latter also predicts motor score. Cognitive score is best predicted by MT parameter within lesions. Conclusions Multiparametric data of brain microstructure concord with the literature, predict clinical performance and suggest a diffuse reduction in myelin and/or iron content within NABT of MS patients. We revisit microstructural alterations of NABT in MS patients by simultaneously quantifying three MRI parameters. Data suggest reduction of MT/R2*/R1 in NABT of MS patients, suggesting a reduction in myelin and/or iron content. Quantitative MRI parameters in NABT are independent predictors of clinical status.
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Affiliation(s)
- Emilie Lommers
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium.
| | - Jessica Simon
- Psychology and Neurosciences of Cognition Research Unit, University of Liège, Belgium
| | - Gilles Reuter
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; Neurosurgery Department, CHU Liège, Belgium
| | - Gaël Delrue
- Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium
| | - Dominique Dive
- Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium
| | | | - Evelyne Balteau
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium
| | - Christophe Phillips
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; GIGA - in silico Medicine, University of Liège, Liège, Belgium
| | - Pierre Maquet
- GIGA - CRC in vivo Imaging, University of Liège, Liège, Belgium; Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Belgium
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28
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Travis KE, Castro MRH, Berman S, Dodson CK, Mezer AA, Ben-Shachar M, Feldman HM. More than myelin: Probing white matter differences in prematurity with quantitative T1 and diffusion MRI. Neuroimage Clin 2019; 22:101756. [PMID: 30901711 PMCID: PMC6428958 DOI: 10.1016/j.nicl.2019.101756] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 03/03/2019] [Accepted: 03/09/2019] [Indexed: 01/07/2023]
Abstract
OBJECTIVE We combined diffusion MRI (dMRI) with quantitative T1 (qT1) relaxometry in a sample of school-aged children born preterm and full term to determine whether reduced fractional anisotropy (FA) within the corpus callosum of the preterm group could be explained by a reduction in myelin content, as indexed by R1 (1/T1) from qT1 scans. METHODS 8-year-old children born preterm (n = 29; GA 22-32 weeks) and full term (n = 24) underwent dMRI and qT1 scans. Four subdivisions of the corpus callosum were segmented in individual native space according to cortical projection zones (occipital, temporal, motor and anterior-frontal). Fractional anisotropy (FA) and R1 were quantified along the tract trajectory of each subdivision and compared across two birth groups. RESULTS Compared to controls, preterm children demonstrated significantly decreased FA in 3 of 4 analyzed corpus callosum subdivisions (temporal, motor, and anterior frontal segments) and decreased R1 in only 2 of 4 corpus callosum subdivisions (temporal and motor segments). FA and RD were significantly associated with R1 within temporal but not anterior frontal subdivisions of the corpus callosum in the term group; RD correlated with R1 in the anterior subdivision in the preterm group only. CONCLUSIONS Myelin content, as indexed by R1, drives some but not all of the differences in white matter between preterm and term born children. Other factors, such as axonal diameter and directional coherence, likely contributed to FA differences in the anterior frontal segment of the corpus callosum that were not well explained by R1.
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Affiliation(s)
- Katherine E Travis
- Division of Developmental and Behavioral Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Maria R H Castro
- Division of Developmental and Behavioral Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Shai Berman
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Cory K Dodson
- Division of Developmental and Behavioral Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Aviv A Mezer
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Michal Ben-Shachar
- The Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel; Department of English Literature and Linguistics, Bar Ilan University, Ramat Gan, Israel
| | - Heidi M Feldman
- Division of Developmental and Behavioral Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
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29
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Vavasour IM, Meyers SM, Mädler B, Harris T, Fu E, Li DK, Traboulsee A, MacKay AL, Laule C. Multicenter Measurements of T1
Relaxation and Diffusion Tensor Imaging: Intra and Intersite Reproducibility. J Neuroimaging 2018; 29:42-51. [DOI: 10.1111/jon.12559] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 08/20/2018] [Accepted: 08/26/2018] [Indexed: 12/25/2022] Open
Affiliation(s)
- Irene M. Vavasour
- Department of Radiology; University of British Columbia, UBC MRI Research Centre; Vancouver British Columbia Canada
| | - Sandra M. Meyers
- Department of Physics and Astronomy; University of British Columbia; Vancouver British Columbia Canada
| | | | - Trudy Harris
- Department of Radiology; University of British Columbia, UBC MRI Research Centre; Vancouver British Columbia Canada
| | - Eric Fu
- Department of Statistics; University of British Columbia; Vancouver British Columbia Canada
| | - David K.B. Li
- Department of Radiology; University of British Columbia, UBC MRI Research Centre; Vancouver British Columbia Canada
- Department of Medicine; University of British Columbia; Vancouver British Columbia Canada
| | - Anthony Traboulsee
- Department of Medicine; University of British Columbia; Vancouver British Columbia Canada
| | - Alex L. MacKay
- Department of Radiology; University of British Columbia, UBC MRI Research Centre; Vancouver British Columbia Canada
- Department of Physics and Astronomy; University of British Columbia; Vancouver British Columbia Canada
| | - Cornelia Laule
- Department of Radiology; University of British Columbia, UBC MRI Research Centre; Vancouver British Columbia Canada
- Department of Physics and Astronomy; University of British Columbia; Vancouver British Columbia Canada
- Department of Pathology and Laboratory Medicine; University of British Columbia; Vancouver British Columbia Canada
- International Collaboration on Repair Discoveries (ICORD); University of British Columbia; Vancouver British Columbia Canada
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30
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Effect of Age on High T1 Signal Intensity of the Dentate Nucleus and Globus Pallidus in a Large Population Exposed to Gadodiamide. Invest Radiol 2018; 53:214-222. [DOI: 10.1097/rli.0000000000000431] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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31
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Uribe C, Segura B, Baggio HC, Abos A, Garcia-Diaz AI, Campabadal A, Marti MJ, Valldeoriola F, Compta Y, Bargallo N, Junque C. Gray/White Matter Contrast in Parkinson's Disease. Front Aging Neurosci 2018; 10:89. [PMID: 29636679 PMCID: PMC5881246 DOI: 10.3389/fnagi.2018.00089] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 03/16/2018] [Indexed: 12/24/2022] Open
Abstract
Gray/white matter contrast (GWC) decreases with aging and has been found to be a useful MRI biomarker in Alzheimer’s disease (AD), but its utility in Parkinson’s disease (PD) patients has not been investigated. The aims of the study were to test whether GWC is sensitive to aging changes in PD patients, if PD patients differ from healthy controls (HCs) in GWC, and whether the use of GWC data would improve the sensitivity of cortical thickness analyses to differentiate PD patients from controls. Using T1-weighted structural images, we obtained individual cortical thickness and GWC values from a sample of 90 PD patients and 27 controls. Images were processed with the automated FreeSurfer stream. GWC was computed by dividing the white matter (WM) by the gray matter (GM) values and projecting the ratios onto a common surface. The sample characteristics were: 52 patients and 14 controls were males; mean age of 64.4 ± 10.6 years in PD and 64.7 ± 8.6 years in controls; 8.0 ± 5.6 years of disease evolution; 15.6 ± 9.8 UPDRS; and a range of 1.5–3 in Hoehn and Yahr (H&Y) stage. In both PD and controls we observed significant correlations between GWC and age involving almost the entire cortex. When applying a stringent cluster-forming threshold of p < 0.0001, the correlation between GWC and age also involved the entire cortex in the PD group; in the control group, the correlation was found in the parahippocampal gyrus and widespread frontal and parietal areas. The GWC of PD patients did not differ from controls’, whereas cortical thickness analyses showed thinning in temporal and parietal cortices in the PD group. Cortical thinning remained unchanged after adjusting for GWC. GWC is a very sensitive measure for detecting aging effects, but did not provide additional information over other parameters of atrophy in PD.
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Affiliation(s)
- Carme Uribe
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Barbara Segura
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Hugo C Baggio
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Alexandra Abos
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Anna I Garcia-Diaz
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Anna Campabadal
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain.,Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Hospital Clinic, Barcelona, Spain
| | - Maria J Marti
- Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Hospital Clinic, Barcelona, Spain.,Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona, Barcelona, Spain.,Parkinson's Disease and Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Francesc Valldeoriola
- Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Hospital Clinic, Barcelona, Spain.,Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona, Barcelona, Spain.,Parkinson's Disease and Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Yaroslau Compta
- Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Hospital Clinic, Barcelona, Spain.,Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona, Barcelona, Spain.,Parkinson's Disease and Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Nuria Bargallo
- Centre de Diagnòstic per la Imatge, Hospital Clínic, Barcelona, Spain
| | - Carme Junque
- Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Spain.,Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Hospital Clinic, Barcelona, Spain.,Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona, Barcelona, Spain
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32
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Anblagan D, Valdés Hernández MC, Ritchie SJ, Aribisala BS, Royle NA, Hamilton IF, Cox SR, Gow AJ, Pattie A, Corley J, Starr JM, Muñoz Maniega S, Bastin ME, Deary IJ, Wardlaw JM. Coupled changes in hippocampal structure and cognitive ability in later life. Brain Behav 2018; 8:e00838. [PMID: 29484252 PMCID: PMC5822578 DOI: 10.1002/brb3.838] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Revised: 07/07/2017] [Accepted: 08/07/2017] [Indexed: 11/30/2022] Open
Abstract
Introduction The hippocampus plays an important role in cognitive abilities which often decline with advancing age. Methods In a longitudinal study of community-dwelling adults, we investigated whether there were coupled changes in hippocampal structure and verbal memory, working memory, and processing speed between the ages of 73 (N = 655) and 76 years (N = 469). Hippocampal structure was indexed by hippocampal volume, hippocampal volume as a percentage of intracranial volume (H_ICV), fractional anisotropy (FA), mean diffusivity (MD), and longitudinal relaxation time (T1). Results Mean levels of hippocampal volume, H_ICV, FA, T1, and all three cognitive abilities domains decreased, whereas MD increased, from age 73 to 76. At baseline, higher hippocampal volume was associated with better working memory and verbal memory, but none of these correlations survived correction for multiple comparisons. Higher FA, lower MD, and lower T1 at baseline were associated with better cognitive abilities in all three domains; only the correlation between baseline hippocampal MD and T1, and change in the three cognitive domains, survived correction for multiple comparisons. Individuals with higher hippocampal MD at age 73 experienced a greater decline in all three cognitive abilities between ages 73 and 76. However, no significant associations with changes in cognitive abilities were found with hippocampal volume, FA, and T1 measures at baseline. Similarly, no significant associations were found between cognitive abilities at age 73 and changes in the hippocampal MRI biomarkers between ages 73 and 76. Conclusion Our results provide evidence to better understand how the hippocampus ages in healthy adults in relation to the cognitive domains in which it is involved, suggesting that better hippocampal MD at age 73 predicts less relative decline in three important cognitive domains across the next 3 years. It can potentially assist in diagnosing early stages of aging-related neuropathologies, because in some cases, accelerated decline could predict pathologies.
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Affiliation(s)
- Devasuda Anblagan
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of Neuroimaging SciencesCentre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Scottish Imaging NetworkA Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Edinburgh Dementia Research CentreUK Dementia Research InstituteEdinburghUK
| | - Maria C. Valdés Hernández
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of Neuroimaging SciencesCentre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Scottish Imaging NetworkA Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Edinburgh Dementia Research CentreUK Dementia Research InstituteEdinburghUK
| | - Stuart J. Ritchie
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of PsychologyUniversity of EdinburghEdinburghUK
| | - Benjamin S. Aribisala
- Department of Neuroimaging SciencesCentre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Department of Computer ScienceLagos State UniversityLagosNigeria
| | - Natalie A. Royle
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of Neuroimaging SciencesCentre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Scottish Imaging NetworkA Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
| | - Iona F. Hamilton
- Department of Neuroimaging SciencesCentre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Edinburgh Dementia Research CentreUK Dementia Research InstituteEdinburghUK
| | - Simon R. Cox
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Scottish Imaging NetworkA Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Department of PsychologyUniversity of EdinburghEdinburghUK
| | - Alan J. Gow
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of PsychologySchool of Social SciencesHeriot‐Watt UniversityEdinburghUK
| | - Alison Pattie
- Department of PsychologyUniversity of EdinburghEdinburghUK
| | - Janie Corley
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of PsychologyUniversity of EdinburghEdinburghUK
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Alzheimer Scotland Dementia Research CentreUniversity of EdinburghEdinburghUK
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of Neuroimaging SciencesCentre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Scottish Imaging NetworkA Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Edinburgh Dementia Research CentreUK Dementia Research InstituteEdinburghUK
| | - Mark E. Bastin
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of Neuroimaging SciencesCentre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Scottish Imaging NetworkA Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Edinburgh Dementia Research CentreUK Dementia Research InstituteEdinburghUK
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of PsychologyUniversity of EdinburghEdinburghUK
| | - Joanna M. Wardlaw
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
- Department of Neuroimaging SciencesCentre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- Scottish Imaging NetworkA Platform for Scientific Excellence (SINAPSE) CollaborationEdinburghUK
- Edinburgh Dementia Research CentreUK Dementia Research InstituteEdinburghUK
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Goto M, Abe O, Miyati T, Aoki S, Gomi T, Takeda T. Mis-segmentation in voxel-based morphometry due to a signal intensity change in the putamen. Radiol Phys Technol 2017; 10:515-524. [PMID: 28975537 DOI: 10.1007/s12194-017-0424-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 09/20/2017] [Accepted: 09/20/2017] [Indexed: 11/25/2022]
Abstract
The aims of this study were to demonstrate an association between changes in the signal intensity of the putamen on three-dimensional T1-weighted magnetic resonance images (3D-T1WI) and mis-segmentation, using the voxel-based morphometry (VBM) 8 toolbox. The sagittal 3D-T1WIs of 22 healthy volunteers were obtained for VBM analysis using the 1.5-T MR scanner. We prepared five levels of 3D-T1WI signal intensity (baseline, same level, background level, low level, and high level) in regions of interest containing the putamen. Groups of smoothed, spatially normalized tissue images were compared to the baseline group using a paired t test. The baseline was compared to the other four levels. In all comparisons, significant volume changes were observed around and outside the area that included the signal intensity change. The present study demonstrated an association between a change in the signal intensity of the putamen on 3D-T1WI and changed volume in segmented tissue images.
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Affiliation(s)
- Masami Goto
- School of Allied Health Sciences, Kitasato University, Kitasato, 1-15-1 Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan.
| | - Osamu Abe
- Department of Radiology, The University of Tokyo Hospital, Tokyo, Japan
| | - Tosiaki Miyati
- Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Tsutomu Gomi
- School of Allied Health Sciences, Kitasato University, Kitasato, 1-15-1 Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan
| | - Tohoru Takeda
- School of Allied Health Sciences, Kitasato University, Kitasato, 1-15-1 Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan
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34
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Bonnier G, Maréchal B, Fartaria MJ, Falkowskiy P, Marques JP, Simioni S, Schluep M, Du Pasquier R, Thiran JP, Krueger G, Granziera C. The Combined Quantification and Interpretation of Multiple Quantitative Magnetic Resonance Imaging Metrics Enlightens Longitudinal Changes Compatible with Brain Repair in Relapsing-Remitting Multiple Sclerosis Patients. Front Neurol 2017; 8:506. [PMID: 29021778 PMCID: PMC5623825 DOI: 10.3389/fneur.2017.00506] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2017] [Accepted: 09/08/2017] [Indexed: 12/25/2022] Open
Abstract
Objective Quantitative and semi-quantitative MRI (qMRI) metrics provide complementary specificity and differential sensitivity to pathological brain changes compatible with brain inflammation, degeneration, and repair. Moreover, advanced magnetic resonance imaging (MRI) metrics with overlapping elements amplify the true tissue-related information and limit measurement noise. In this work, we combined multiple advanced MRI parameters to assess focal and diffuse brain changes over 2 years in a group of early-stage relapsing-remitting MS patients. Methods Thirty relapsing-remitting MS patients with less than 5 years disease duration and nine healthy subjects underwent 3T MRI at baseline and after 2 years including T1, T2, T2* relaxometry, and magnetization transfer imaging. To assess longitudinal changes in normal-appearing (NA) tissue and lesions, we used analyses of variance and Bonferroni correction for multiple comparisons. Multivariate linear regression was used to assess the correlation between clinical outcome and multiparametric MRI changes in lesions and NA tissue. Results In patients, we measured a significant longitudinal decrease of mean T2 relaxation times in NA white matter (p = 0.005) and a decrease of T1 relaxation times in the pallidum (p < 0.05), which are compatible with edema reabsorption and/or iron deposition. No longitudinal changes in qMRI metrics were observed in controls. In MS lesions, we measured a decrease in T1 relaxation time (p-value < 2.2e−16) and a significant increase in MTR (p-value < 1e−6), suggesting repair mechanisms, such as remyelination, increased axonal density, and/or a gliosis. Last, the evolution of advanced MRI metrics—and not changes in lesions or brain volume—were correlated to motor and cognitive tests scores evolution (Adj-R2 > 0.4, p < 0.05). In summary, the combination of multiple advanced MRI provided evidence of changes compatible with focal and diffuse brain repair at early MS stages as suggested by histopathological studies.
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Affiliation(s)
- Guillaume Bonnier
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Benedicte Maréchal
- Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare, Lausanne, Switzerland.,Signal Processing Laboratory 5 LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Mário João Fartaria
- Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare, Lausanne, Switzerland.,Signal Processing Laboratory 5 LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Pavel Falkowskiy
- Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare, Lausanne, Switzerland.,Signal Processing Laboratory 5 LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - José P Marques
- Donders Centre for Cognitive Neuroimaging, Radbound University, Nijmegen, Netherlands
| | - Samanta Simioni
- Neuropsychology, Institution de Lavigny, Denens, Switzerland
| | - Myriam Schluep
- Neurology Service and Neuroimmunology Laboratory, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Renaud Du Pasquier
- Neurology Service and Neuroimmunology Laboratory, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory 5 LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Gunnar Krueger
- Siemens Medical Solutions USA IM MR COL NEZ, Burlington, MA, United States
| | - Cristina Granziera
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States.,Neurology Service and Neuroimmunology Laboratory, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
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35
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Okubo G, Okada T, Yamamoto A, Fushimi Y, Okada T, Murata K, Togashi K. Relationship between aging and T
1
relaxation time in deep gray matter: A voxel-based analysis. J Magn Reson Imaging 2017; 46:724-731. [DOI: 10.1002/jmri.25590] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Accepted: 11/28/2016] [Indexed: 02/06/2023] Open
Affiliation(s)
- Gosuke Okubo
- Department of Diagnostic Imaging and Nuclear Medicine; Kyoto University Graduate School of Medicine; Kyoto Kyoto Japan
| | - Tomohisa Okada
- Department of Diagnostic Imaging and Nuclear Medicine; Kyoto University Graduate School of Medicine; Kyoto Kyoto Japan
| | - Akira Yamamoto
- Department of Diagnostic Imaging and Nuclear Medicine; Kyoto University Graduate School of Medicine; Kyoto Kyoto Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine; Kyoto University Graduate School of Medicine; Kyoto Kyoto Japan
| | - Tsutomu Okada
- Department of Diagnostic Imaging and Nuclear Medicine; Kyoto University Graduate School of Medicine; Kyoto Kyoto Japan
| | | | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine; Kyoto University Graduate School of Medicine; Kyoto Kyoto Japan
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36
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Marques JP, Khabipova D, Gruetter R. Studying cyto and myeloarchitecture of the human cortex at ultra-high field with quantitative imaging: R1, R2* and magnetic susceptibility. Neuroimage 2017; 147:152-163. [DOI: 10.1016/j.neuroimage.2016.12.009] [Citation(s) in RCA: 74] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Revised: 11/30/2016] [Accepted: 12/05/2016] [Indexed: 12/15/2022] Open
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37
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Hagberg GE, Bause J, Ethofer T, Ehses P, Dresler T, Herbert C, Pohmann R, Shajan G, Fallgatter A, Pavlova MA, Scheffler K. Whole brain MP2RAGE-based mapping of the longitudinal relaxation time at 9.4T. Neuroimage 2017; 144:203-216. [DOI: 10.1016/j.neuroimage.2016.09.047] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 09/16/2016] [Accepted: 09/20/2016] [Indexed: 11/16/2022] Open
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38
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Magnetisation-prepared rapid gradient-echo versus inversion recovery turbo spin-echo T1-weighted images for segmentation of deep grey matter structures at 3 T. Clin Radiol 2016; 71:1304-1308. [DOI: 10.1016/j.crad.2016.09.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Revised: 08/19/2016] [Accepted: 09/08/2016] [Indexed: 01/27/2023]
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39
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Bou Fakhredin R, Saade C, Kerek R, El-Jamal L, Khoury SJ, El-Merhi F. Imaging in multiple sclerosis: A new spin on lesions. J Med Imaging Radiat Oncol 2016; 60:577-586. [DOI: 10.1111/1754-9485.12498] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Accepted: 06/04/2016] [Indexed: 12/21/2022]
Affiliation(s)
- Rayan Bou Fakhredin
- Diagnostic Radiology Department; American University of Beirut Medical Center; Beirut Lebanon
| | - Charbel Saade
- Diagnostic Radiology Department; American University of Beirut Medical Center; Beirut Lebanon
| | - Racha Kerek
- Diagnostic Radiology Department; American University of Beirut Medical Center; Beirut Lebanon
| | - Lara El-Jamal
- Diagnostic Radiology Department; American University of Beirut Medical Center; Beirut Lebanon
| | - Samia J Khoury
- Department of Neurology; American University of Beirut Medical Center; Beirut Lebanon
| | - Fadi El-Merhi
- Diagnostic Radiology Department; American University of Beirut Medical Center; Beirut Lebanon
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40
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Gracien RM, Nürnberger L, Hok P, Hof SM, Reitz SC, Rüb U, Steinmetz H, Hilker-Roggendorf R, Klein JC, Deichmann R, Baudrexel S. Evaluation of brain ageing: a quantitative longitudinal MRI study over 7 years. Eur Radiol 2016; 27:1568-1576. [PMID: 27379992 DOI: 10.1007/s00330-016-4485-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Revised: 05/27/2016] [Accepted: 06/21/2016] [Indexed: 12/31/2022]
Abstract
OBJECTIVES T1 relaxometry is a promising tool for the assessment of microstructural changes during brain ageing. Previous cross-sectional studies demonstrated increasing T1 values in white and decreasing T1 values in grey matter over the lifetime. However, these findings have not yet been confirmed on the basis of a longitudinal study. In this longitudinal study over 7 years, T1 relaxometry was used to investigate the dynamics of age-related microstructural changes in older healthy subjects. METHODS T1 mapping was performed in 17 healthy subjects (range 51-77 years) at baseline and after 7 years. Advanced cortical and white matter segmentation was used to determine mean T1 values in the cortex and white matter. RESULTS The analysis revealed a decrease of mean cortical T1 values over 7 years, the rate of T1 reduction being more prominent in subjects with higher age. T1 decreases were predominantly localized in the lateral frontal, parietal and temporal cortex. In contrast, mean white matter T1 values remained stable. CONCLUSIONS T1 mapping is shown to be sensitive to age-related microstructural changes in healthy ageing subjects in a longitudinal setting. Data of a cohort in late adulthood and the senescence period demonstrate a decrease of cortical T1 values over 7 years, most likely reflecting decreasing water content and increased iron concentrations. KEY POINTS • T1 mapping is sensitive to age-related microstructural changes in a longitudinal setting. • T1 decreases were predominantly localized in the lateral frontal, parietal and temporal cortex. • The rate of T1 reduction was more prominent in subjects with higher age. • These changes most likely reflect decreasing cortical water and increasing iron concentrations.
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Affiliation(s)
- René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt/Main, Germany. .,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.
| | - Lucas Nürnberger
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Pavel Hok
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Department of Neurology, Palacky University, Olomouc, Czech Republic
| | - Stephanie-Michelle Hof
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Sarah C Reitz
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Udo Rüb
- Dr. Senckenberg Chronomedical Institute, Goethe University, Frankfurt/Main, Germany
| | | | - Rüdiger Hilker-Roggendorf
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Johannes C Klein
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
| | - Simon Baudrexel
- Department of Neurology, Goethe University, Frankfurt/Main, Germany.,Brain Imaging Center, Goethe University, Frankfurt/Main, Germany
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Knight MJ, McCann B, Tsivos D, Couthard E, Kauppinen RA. Quantitative T 1 and T 2 MRI signal characteristics in the human brain: different patterns of MR contrasts in normal ageing. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2016; 29:833-842. [PMID: 27333937 PMCID: PMC5124042 DOI: 10.1007/s10334-016-0573-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2015] [Revised: 06/06/2016] [Accepted: 06/09/2016] [Indexed: 01/25/2023]
Abstract
Objective The objective of this study was to examine age-dependent changes in both T1-weighted and T2-weighted image contrasts and spin-echo T2 relaxation time in the human brain during healthy ageing. Methods A total of 37 participants between the ages of 49 and 87 years old were scanned with a 3 Tesla system, using T1-weighted, T2 weighted and quantitative spin-echo T2 imaging. Contrast between image intensities and T2 values was calculated for various regions, including between individual hippocampal subfields. Results The T1 contrast-to-noise (CNR) and gray:white signal intensity ratio (GWR) did not change in the hippocampus, but it declined in the cingulate cortex with age. In contrast, T2 CNR and GWR declined in both brain regions. T2 relaxation time was almost constant in gray matter and most (but not all) hippocampal subfields, but increased substantially in white matter, pointing to an age effect on water relaxation in white matter. Conclusions Changes in T1 and T2 MR characteristics influence the appearance of brain images in later life and should be considered in image analyses of aged subjects. It is speculated that alterations at the cell biology level, with concomitant alterations to the local magnetic environment, reduce dephasing and subsequently prolong spin-echo T2 through reduced diffusion effects in later life. Electronic supplementary material The online version of this article (doi:10.1007/s10334-016-0573-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Michael J Knight
- School of Experimental Psychology, University of Bristol, 12a Priory Road, Bristol, BS8 1TU, UK.
| | - Bryony McCann
- School of Experimental Psychology, University of Bristol, 12a Priory Road, Bristol, BS8 1TU, UK
| | - Demitra Tsivos
- Institute of Clinical Neuroscience, University of Bristol, Level 1 Learning and Research Building, Bristol, BS10 5NB, UK
| | - Elizabeth Couthard
- Institute of Clinical Neuroscience, University of Bristol, Level 1 Learning and Research Building, Bristol, BS10 5NB, UK
- North Bristol NHS Trust, Southmead Road, Westbury-on-Trym, Bristol, BS10 5NB, UK
| | - Risto A Kauppinen
- School of Experimental Psychology, University of Bristol, 12a Priory Road, Bristol, BS8 1TU, UK
- Clinical Research and Imaging Centre, University of Bristol, 60 St Michael's Hill, Bristol, BS2 8DX, UK
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42
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Vidal-Piñeiro D, Walhovd KB, Storsve AB, Grydeland H, Rohani DA, Fjell AM. Accelerated longitudinal gray/white matter contrast decline in aging in lightly myelinated cortical regions. Hum Brain Mapp 2016; 37:3669-84. [PMID: 27228371 DOI: 10.1002/hbm.23267] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2015] [Revised: 05/11/2016] [Accepted: 05/13/2016] [Indexed: 12/12/2022] Open
Abstract
Highly myelinated cortical regions seem to develop early and are more robust to age-related decline. By use of different magnetic resonance imaging (MRI) measures such as contrast between T1- and T2-weighted MRI scans (T1w/T2w) it is now possible to assess correlates of myelin content in vivo. Further, previous studies indicate that gray/white matter contrast (GWC) become blurred as individuals' age, apparently reflecting age-related changes in myelin structure. Here we address whether longitudinal changes in GWC are dependent on initial myelin content within tissue as defined by baseline T1w/T2w contrast, and hypothesize that lightly myelinated regions undergo more decline longitudinally. A sample of 207 healthy adult participants (range: 20-84 years) was scanned twice (interscan interval: 3.6 years). Results showed widespread longitudinal reductions of GWC throughout the cortical surface, especially in the frontal cortices, mainly driven by intensity decay in the white matter. Annual rate of GWC blurring showed acceleration with age in temporal and medial prefrontal regions. Moreover, the anatomical distribution of increased rate of GWC decline with advancing age was strongly related to baseline levels of intracortical myelin. This study provides a first evidence of accelerated regional GWC blurring with advancing age, relates GWC patterns to cortical myeloarchitectonics and supports the hypothesis of increased age-related vulnerability of lightly myelinated areas. Hum Brain Mapp 37:3669-3684, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Didac Vidal-Piñeiro
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Kristine B Walhovd
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Andreas B Storsve
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Håkon Grydeland
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Darius A Rohani
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Anders M Fjell
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
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Valdés Hernández M, Allerhand M, Glatz A, Clayson L, Muñoz Maniega S, Gow A, Royle N, Bastin M, Starr J, Deary I, Wardlaw J. Do white matter hyperintensities mediate the association between brain iron deposition and cognitive abilities in older people? Eur J Neurol 2016; 23:1202-9. [PMID: 27094820 PMCID: PMC4950475 DOI: 10.1111/ene.13006] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Accepted: 03/02/2016] [Indexed: 12/28/2022]
Abstract
BACKGROUND AND PURPOSE Several studies have reported associations between brain iron deposits (IDs), white matter hyperintensities (WMHs) and cognitive ability in older individuals. Whether the association between brain IDs and cognitive abilities in older people is mediated by or independent of total brain tissue damage represented by WMHs visible on structural magnetic resonance imaging (MRI) was examined. METHODS Data from 676 community-dwelling individuals from the Lothian Birth Cohort 1936, with Mini-Mental State Examination scores >24, who underwent detailed cognitive testing and multimodal brain MRI at mean age 72.7 years were analysed. Brain IDs were assessed automatically following manual editing. WMHs were assessed semi-automatically. Brain microbleeds were visually counted. Structural equation modelling was used to test for mediation. RESULTS Overall, 72.8% of the sample had IDs with a median total volume of 0.040 ml (i.e. 0.004% of the total brain volume). The total volume of IDs, significantly and negatively associated with general cognitive function (standardized β = -0.17, P < 0.01), was significantly and positively associated with WMH volume (std β = 0.13, P = 0.03). WMH volume had a significant negative association with general cognitive function, independent of IDs (std β = -0.13, P < 0.01). The association between cognition and IDs in the brain stem (and minimally the total brain iron load) was partially and significantly mediated by WMH volume (P = 0.03). CONCLUSIONS The negative association between brain IDs and cognitive ability in the elderly is partially mediated by WMHs, with this mediation mainly arising from the iron deposition load in the brain stem. IDs might be an indicator of small vessel disease that predisposes to white matter damage, affecting the neuronal networks underlying higher cognitive functioning.
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Affiliation(s)
- M Valdés Hernández
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - M Allerhand
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - A Glatz
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - L Clayson
- College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
| | - S Muñoz Maniega
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - A Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, School of Life Sciences, Heriot-Watt University, Edinburgh, UK
| | - N Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - M Bastin
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - J Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - I Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - J Wardlaw
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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Stüber C, Pitt D, Wang Y. Iron in Multiple Sclerosis and Its Noninvasive Imaging with Quantitative Susceptibility Mapping. Int J Mol Sci 2016; 17:ijms17010100. [PMID: 26784172 PMCID: PMC4730342 DOI: 10.3390/ijms17010100] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Revised: 01/05/2016] [Accepted: 01/07/2016] [Indexed: 01/06/2023] Open
Abstract
Iron is considered to play a key role in the development and progression of Multiple Sclerosis (MS). In particular, iron that accumulates in myeloid cells after the blood-brain barrier (BBB) seals may contribute to chronic inflammation, oxidative stress and eventually neurodegeneration. Magnetic resonance imaging (MRI) is a well-established tool for the non-invasive study of MS. In recent years, an advanced MRI method, quantitative susceptibility mapping (QSM), has made it possible to study brain iron through in vivo imaging. Moreover, immunohistochemical investigations have helped defining the lesional and cellular distribution of iron in MS brain tissue. Imaging studies in MS patients and of brain tissue combined with histological studies have provided important insights into the role of iron in inflammation and neurodegeneration in MS.
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Affiliation(s)
- Carsten Stüber
- Department of Radiology, Weill Cornell Medical College, New York, NY 10044, USA.
- Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT 06511, USA.
| | - David Pitt
- Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT 06511, USA.
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, NY 10044, USA.
- Department of Biomedical Engineering, Cornell University, Ithaca, NY 14853, USA.
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45
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Stüber C, Pitt D, Wang Y. Iron in Multiple Sclerosis and Its Noninvasive Imaging with Quantitative Susceptibility Mapping. Int J Mol Sci 2016. [PMID: 26784172 DOI: 10.3390/ijmsl17010100] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/27/2023] Open
Abstract
Iron is considered to play a key role in the development and progression of Multiple Sclerosis (MS). In particular, iron that accumulates in myeloid cells after the blood-brain barrier (BBB) seals may contribute to chronic inflammation, oxidative stress and eventually neurodegeneration. Magnetic resonance imaging (MRI) is a well-established tool for the non-invasive study of MS. In recent years, an advanced MRI method, quantitative susceptibility mapping (QSM), has made it possible to study brain iron through in vivo imaging. Moreover, immunohistochemical investigations have helped defining the lesional and cellular distribution of iron in MS brain tissue. Imaging studies in MS patients and of brain tissue combined with histological studies have provided important insights into the role of iron in inflammation and neurodegeneration in MS.
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Affiliation(s)
- Carsten Stüber
- Department of Radiology, Weill Cornell Medical College, New York, NY 10044, USA.
- Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT 06511, USA.
| | - David Pitt
- Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT 06511, USA.
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, NY 10044, USA.
- Department of Biomedical Engineering, Cornell University, Ithaca, NY 14853, USA.
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46
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Badve C, Yu A, Rogers M, Ma D, Liu Y, Schluchter M, Sunshine J, Griswold M, Gulani V. Simultaneous T 1 and T 2 Brain Relaxometry in Asymptomatic Volunteers using Magnetic Resonance Fingerprinting. ACTA ACUST UNITED AC 2015; 1:136-144. [PMID: 26824078 PMCID: PMC4727840 DOI: 10.18383/j.tom.2015.00166] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Magnetic resonance fingerprinting (MRF) is an imaging tool that produces multiple magnetic resonance imaging parametric maps from a single scan. Herein we describe the normal range and progression of MRF-derived relaxometry values with age in healthy individuals. In total, 56 normal volunteers (24 men and 32 women) aged 11-71 years were scanned. Regions of interest were drawn on T1 and T2 maps in 38 areas, including lobar and deep white matter (WM), deep gray nuclei, thalami, and posterior fossa structures. Relaxometry differences were assessed using a forward stepwise selection of a baseline model that included either sex, age, or both, where variables were included if they contributed significantly (P < .05). In addition, differences in regional anatomy, including comparisons between hemispheres and between anatomical subcomponents, were assessed by paired t tests. MRF-derived T1 and T2 in frontal WM regions increased with age, whereas occipital and temporal regions remained relatively stable. Deep gray nuclei such as substantia nigra, were found to have age-related decreases in relaxometry. Differences in sex were observed in T1 and T2 of temporal regions, the cerebellum, and pons. Men were found to have more rapid age-related changes in frontal and parietal WM. Regional differences were identified between hemispheres, between the genu and splenium of the corpus callosum, and between posteromedial and anterolateral thalami. In conclusion, MRF quantification measures relaxometry trends in healthy individuals that are in agreement with the current understanding of neurobiology and has the ability to uncover additional patterns that have not yet been explored.
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Affiliation(s)
- Chaitra Badve
- Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, 11100 Euclid Avenue, Cleveland, Ohio 44106, USA
| | - Alice Yu
- School of Medicine, Case Western Reserve University, 11100 Euclid Avenue, Cleveland, Ohio 44106, USA
| | - Matthew Rogers
- School of Medicine, Case Western Reserve University, 11100 Euclid Avenue, Cleveland, Ohio 44106, USA
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106, USA
| | - Yiying Liu
- Biostatistics and Bioinformatics Core, Case Western Reserve University, 11100 Euclid Avenue, Cleveland, Ohio 44106, USA
| | - Mark Schluchter
- Biostatistics and Bioinformatics Core, Case Western Reserve University, 11100 Euclid Avenue, Cleveland, Ohio 44106, USA
| | - Jeffrey Sunshine
- Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, 11100 Euclid Avenue, Cleveland, Ohio 44106, USA
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, 11100 Euclid Avenue, Cleveland, Ohio 44106, USA; Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106, USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, 11100 Euclid Avenue, Cleveland, Ohio 44106, USA; Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106, USA
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47
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Del C Valdés Hernández M, Ritchie S, Glatz A, Allerhand M, Muñoz Maniega S, Gow AJ, Royle NA, Bastin ME, Starr JM, Deary IJ, Wardlaw JM. Brain iron deposits and lifespan cognitive ability. AGE (DORDRECHT, NETHERLANDS) 2015; 37:100. [PMID: 26378028 PMCID: PMC5005839 DOI: 10.1007/s11357-015-9837-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Accepted: 09/07/2015] [Indexed: 06/05/2023]
Abstract
Several studies have reported associations between brain iron deposits and cognitive status, and cardiovascular and neurodegenerative diseases in older individuals, but the mechanisms underlying these associations remain unclear. We explored the associations between regional brain iron deposits and different factors of cognitive ability (fluid intelligence, speed and memory) in a large sample (n = 662) of individuals with a mean age of 73 years. Brain iron deposits in the corpus striatum were extracted automatically. Iron deposits in other parts of the brain (i.e., white matter, thalamus, brainstem and cortex), brain tissue volume and white matter hyperintensities (WMH) were assessed separately and semi-automatically. Overall, 72.8 % of the sample had iron deposits. The total volume of iron deposits had a small but significant negative association with all three cognitive ability factors in later life (mean r = -0.165), but no relation to intelligence in childhood (r = 0.043, p = 0.282). Regression models showed that these iron deposit associations were still present after control for a variety of vascular health factors, and were separable from the association of WMH with cognitive ability. Iron deposits were also associated with cognition across the lifespan, indicating that they are relevant for cognitive ability only at older ages. Iron deposits might be an indicator of small vessel disease that affects the neuronal networks underlying higher cognitive functioning.
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Affiliation(s)
- Maria Del C Valdés Hernández
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK.
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
| | - Stuart Ritchie
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Andreas Glatz
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK
| | - Mike Allerhand
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz Maniega
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Alan J Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, School of Life Sciences, Heriot-Watt University, Edinburgh, UK
| | - Natalie A Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Department of Medical and Radiological Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - John M Starr
- Department of Geriatric Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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48
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Zimny A, Neska-Matuszewska M, Bladowska J, Sąsiadek MJ. Intracranial Lesions with Low Signal Intensity on T2-weighted MR Images - Review of Pathologies. Pol J Radiol 2015; 80:40-50. [PMID: 25628772 PMCID: PMC4307690 DOI: 10.12659/pjr.892146] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2014] [Accepted: 08/29/2014] [Indexed: 11/17/2022] Open
Abstract
In this article we presented intracranial pathological substances and lesions with low signal intensity on T2-weighted images. Eight groups of substances were discussed i.e. 1. Gadolinium-based contrast materials, 2. hemoglobin degradation products 3. melanin, 4. mucous- or protein-containing lesions, 5. highly cellular lesions, 6. lesions containing mineral substances such as: calcium, copper and iron, 7. turbulent and rapid blood or CSF flow 8. air-containing spaces. Appropriate interpretation of signal intensity as well as analysis of lesion location and clinical symptoms enable a correct choice of a further diagnostic algorithm or, in many cases, final diagnosis based exclusively on an MRI examination.
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Affiliation(s)
- Anna Zimny
- Department of General and Interventional Radiology and Neuroradiology, Wrocław Medical University, Wrocław, Poland
| | - Małgorzata Neska-Matuszewska
- Department of General and Interventional Radiology and Neuroradiology, Wrocław Medical University, Wrocław, Poland
| | - Joanna Bladowska
- Department of General and Interventional Radiology and Neuroradiology, Wrocław Medical University, Wrocław, Poland
| | - Marek J Sąsiadek
- Department of General and Interventional Radiology and Neuroradiology, Wrocław Medical University, Wrocław, Poland
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49
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Gray matter myelination of 1555 human brains using partial volume corrected MRI images. Neuroimage 2014; 105:473-85. [PMID: 25449739 DOI: 10.1016/j.neuroimage.2014.10.054] [Citation(s) in RCA: 111] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2014] [Revised: 09/19/2014] [Accepted: 10/19/2014] [Indexed: 11/23/2022] Open
Abstract
The myelin content of the cortex changes over the human lifetime and aberrant cortical myelination is associated with diseases such as schizophrenia and multiple sclerosis. Recently magnetic resonance imaging (MRI) techniques have shown potential in differentiating between myeloarchitectonically distinct cortical regions in vivo. Here we introduce a new algorithm for correcting partial volume effects present in mm-scale MRI images which was used to investigate the myelination pattern of the cerebral cortex in 1555 clinically normal subjects using the ratio of T1-weighted (T1w) and T2-weighted (T2w) MRI images. A significant linear cross-sectional age increase in T1w/T2w estimated myelin was detected across an 18 to 35 year age span (highest value of ~ 1%/year compared to mean T1w/T2w myelin value at 18 years). The cortex was divided at mid-thickness and the value of T1w/T2w myelin calculated for the inner and outer layers separately. The increase in T1w/T2w estimated myelin occurs predominantly in the inner layer for most cortical regions. The ratio of the inner and outer layer T1w/T2w myelin was further validated using high-resolution in vivo MRI scans and also a high-resolution MRI scan of a postmortem brain. Additionally, the relationships between cortical thickness, curvature and T1w/T2w estimated myelin were found to be significant, although the relationships varied across the cortex. We discuss these observations as well as limitations of using the T1w/T2w ratio as an estimate of cortical myelin.
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50
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Lorio S, Lutti A, Kherif F, Ruef A, Dukart J, Chowdhury R, Frackowiak RS, Ashburner J, Helms G, Weiskopf N, Draganski B. Disentangling in vivo the effects of iron content and atrophy on the ageing human brain. Neuroimage 2014; 103:280-289. [PMID: 25264230 PMCID: PMC4263529 DOI: 10.1016/j.neuroimage.2014.09.044] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2014] [Revised: 09/15/2014] [Accepted: 09/17/2014] [Indexed: 01/06/2023] Open
Abstract
Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. To this end we acquired maps of longitudinal relaxation rate R1, effective transverse relaxation rate R2* and magnetization transfer - MT, from healthy subjects (n=96, aged 21-88 years) using a well-established multi-parameter mapping qMRI protocol. Within the framework of voxel-based quantification we find higher grey matter volume in basal ganglia, cerebellar dentate and prefrontal cortex when tissue classification is based on MT maps compared with T1 maps. These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes.
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Affiliation(s)
- S Lorio
- LREN, Dept. of Clinical Neurosciences, CHUV, University of Lausanne, Lausanne Switzerland
| | - A Lutti
- LREN, Dept. of Clinical Neurosciences, CHUV, University of Lausanne, Lausanne Switzerland
| | - F Kherif
- LREN, Dept. of Clinical Neurosciences, CHUV, University of Lausanne, Lausanne Switzerland
| | - A Ruef
- LREN, Dept. of Clinical Neurosciences, CHUV, University of Lausanne, Lausanne Switzerland
| | - J Dukart
- LREN, Dept. of Clinical Neurosciences, CHUV, University of Lausanne, Lausanne Switzerland
| | - R Chowdhury
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, UCL, London, UK
| | - R S Frackowiak
- LREN, Dept. of Clinical Neurosciences, CHUV, University of Lausanne, Lausanne Switzerland
| | - J Ashburner
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, UCL, London, UK
| | - G Helms
- University Medical Centre, UMG, Dept. of Cognitive Neurology, Göttingen, Germany
| | - N Weiskopf
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, UCL, London, UK
| | - B Draganski
- LREN, Dept. of Clinical Neurosciences, CHUV, University of Lausanne, Lausanne Switzerland; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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