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Cagol A, Tsagkas C, Granziera C. Advanced Brain Imaging in Central Nervous System Demyelinating Diseases. Neuroimaging Clin N Am 2024; 34:335-357. [PMID: 38942520 DOI: 10.1016/j.nic.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.
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Affiliation(s)
- Alessandro Cagol
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland; Department of Health Sciences, University of Genova, Via A. Pastore, 1 16132 Genova, Italy. https://twitter.com/CagolAlessandr0
| | - Charidimos Tsagkas
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), 10 Center Drive, Bethesda, MD 20892, USA
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Hegenheimermattweg 167b, 4123 Allschwil, Switzerland; Department of Neurology, University Hospital Basel, Petersgraben 4, 4031 Basel, Switzerland; Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Spitalstrasse 2, 4031 Basel, Switzerland.
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Harper JG, York EN, Meijboom R, Kampaite A, Thrippleton MJ, Kearns PKA, Valdés Hernández MDC, Chandran S, Waldman AD. Quantitative T 1 brain mapping in early relapsing-remitting multiple sclerosis: longitudinal changes, lesion heterogeneity and disability. Eur Radiol 2024; 34:3826-3839. [PMID: 37943312 PMCID: PMC11166797 DOI: 10.1007/s00330-023-10351-6] [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: 03/29/2023] [Revised: 07/20/2023] [Accepted: 08/29/2023] [Indexed: 11/10/2023]
Abstract
OBJECTIVES To quantify brain microstructural changes in recently diagnosed relapsing-remitting multiple sclerosis (RRMS) using longitudinal T1 measures, and determine their associations with clinical disability. METHODS Seventy-nine people with recently diagnosed (< 6 months) RRMS were recruited from a single-centre cohort sub-study, and underwent baseline and 1-year brain MRI, including variable flip angle T1 mapping. Median T1 was measured in white matter lesions (WML), normal-appearing white matter (NAWM), cortical/deep grey matter (GM), thalami, basal ganglia and medial temporal regions. Prolonged T1 (≥ 2.00 s) and supramedian T1 (relative to cohort WML values) WML voxel counts were also measured. Longitudinal change was assessed with paired t-tests and compared with Bland-Altman limits of agreement from healthy control test-retest data. Regression analyses determined relationships with Expanded Disability Status Scale (EDSS) score and dichotomised EDSS outcomes (worsening or stable/improving). RESULTS Sixty-two people with RRMS (mean age 37.2 ± 10.9 [standard deviation], 48 female) and 11 healthy controls (age 44 ± 11, 7 female) contributed data. Prolonged and supramedian T1 WML components increased longitudinally (176 and 463 voxels, respectively; p < .001), and were associated with EDSS score at baseline (p < .05) and follow-up (supramedian: p < .01; prolonged: p < .05). No cohort-wide median T1 changes were found; however, increasing T1 in WML, NAWM, cortical/deep GM, basal ganglia and thalami was positively associated with EDSS worsening (p < .05). CONCLUSION T1 is sensitive to brain microstructure changes in early RRMS. Prolonged WML T1 components and subtle changes in NAWM and GM structures are associated with disability. CLINICAL RELEVANCE STATEMENT MRI T1 brain mapping quantifies disability-associated white matter lesion heterogeneity and subtle microstructural damage in normal-appearing brain parenchyma in recently diagnosed RRMS, and shows promise for early objective disease characterisation and stratification. KEY POINTS • Quantitative T1 mapping detects brain microstructural damage and lesion heterogeneity in recently diagnosed relapsing-remitting multiple sclerosis. • T1 increases in lesions and normal-appearing parenchyma, indicating microstructural damage, are associated with worsening disability. • Brain T1 measures are objective markers of disability-relevant pathology in early multiple sclerosis.
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Affiliation(s)
- James G Harper
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
| | - Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK.
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.
- Anne Rowling Regenerative Neurology Clinic, Edinburgh, UK.
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Patrick K A Kearns
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh BioQuarter: Chancellors Building, Edinburgh, EH16 4SB, UK.
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK.
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Santini T, Chen C, Zhu W, Liou JJ, Walker E, Venkatesh S, Farhat N, Sajewski A, Alkhateeb S, Saranathan M, Xia Z, Ibrahim TS. Hippocampal subfields and thalamic nuclei associations with clinical outcomes in multiple sclerosis: An ultrahigh field MRI study. Mult Scler Relat Disord 2024; 86:105520. [PMID: 38582026 PMCID: PMC11081814 DOI: 10.1016/j.msard.2024.105520] [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: 11/03/2023] [Revised: 02/14/2024] [Accepted: 02/25/2024] [Indexed: 04/08/2024]
Abstract
BACKGROUND Previous studies have shown that thalamic and hippocampal neurodegeneration is associated with clinical decline in Multiple Sclerosis (MS). However, contributions of the specific thalamic nuclei and hippocampal subfields require further examination. OBJECTIVE Using 7 Tesla (7T) magnetic resonance imaging (MRI), we investigated the cross-sectional associations between functionally grouped thalamic nuclei and hippocampal subfields volumes and T1 relaxation times (T1-RT) and subsequent clinical outcomes in MS. METHODS High-resolution T1-weighted and T2-weighted images were acquired at 7T (n=31), preprocessed, and segmented using the Thalamus Optimized Multi Atlas Segmentation (THOMAS, for thalamic nuclei) and the Automatic Segmentation of Hippocampal Subfields (ASHS, for hippocampal subfields) packages. We calculated Pearson correlations between hippocampal subfields and thalamic nuclei volumes and T1-RT and subsequent multi-modal rater-determined and patient-reported clinical outcomes (∼2.5 years after imaging acquisition), correcting for confounders and multiple tests. RESULTS Smaller volume bilaterally in the anterior thalamus region correlated with worse performance in gait function, as measured by the Patient Determined Disease Steps (PDDS). Additionally, larger volume in most functional groups of thalamic nuclei correlated with better visual information processing and cognitive function, as measured by the Symbol Digit Modalities Test (SDMT). In bilateral medial and left posterior thalamic regions, there was an inverse association between volumes and T1-RT, potentially indicating higher tissue degeneration in these regions. We also observed marginal associations between the right hippocampal subfields (both volumes and T1-RT) and subsequent clinical outcomes, though they did not survive correction for multiple testing. CONCLUSION Ultrahigh field MRI identified markers of structural damage in the thalamic nuclei associated with subsequently worse clinical outcomes in individuals with MS. Longitudinal studies will enable better understanding of the role of microstructural integrity in these brain regions in influencing MS outcomes.
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Affiliation(s)
- Tales Santini
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Chenyi Chen
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Wen Zhu
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Jr-Jiun Liou
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Elizabeth Walker
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Shruthi Venkatesh
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Nadim Farhat
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Andrea Sajewski
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Salem Alkhateeb
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | | | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States.
| | - Tamer S Ibrahim
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States; Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States.
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Gong Z, Bilgel M, Kiely M, Triebswetter C, Ferrucci L, Resnick SM, Spencer RG, Bouhrara M. Lower myelin content is associated with more rapid cognitive decline among cognitively unimpaired individuals. Alzheimers Dement 2023; 19:3098-3107. [PMID: 36720000 PMCID: PMC10387505 DOI: 10.1002/alz.12968] [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: 10/15/2022] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 02/01/2023]
Abstract
INTRODUCTION The influence of myelination on longitudinal changes in cognitive performance remains unclear. METHODS For each participant (N = 123), longitudinal cognitive scores were calculated. Myelin content was probed using myelin water fraction (MWF) or longitudinal relaxation rate (R1 ); both are MRI measures sensitive to myelin, with MWF being specific. RESULTS Lower MWF was associated with steeper declines in executive function (p < .02 in all regions) and lower R1 was associated with steeper declines in verbal fluency (p < .03 in all regions). Additionally, lower R1 was associated with steeper declines in executive function (p < .02 in all regions) and memory (p < .04 in occipital and cerebral white matter) but did not survive Bonferroni correction. DISCUSSION We demonstrate significant relationships between myelin content and the rates of change in cognitive performance among cognitively normal individuals. These findings highlight the importance of myelin in cognitive functioning and suggest MWF and R1 as imaging biomarkers to predict cognitive changes.
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Affiliation(s)
- Zhaoyuan Gong
- Magnetic Resonance Physics of Aging and Dementia (MRPAD) Unit, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, USA
| | - Murat Bilgel
- Brain Aging and Behavior Section, NIA, NIH, Baltimore, Maryland, USA
| | - Matthew Kiely
- Magnetic Resonance Physics of Aging and Dementia (MRPAD) Unit, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, USA
| | - Curtis Triebswetter
- Magnetic Resonance Physics of Aging and Dementia (MRPAD) Unit, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, NIA, NIH, Baltimore, Maryland, USA
| | - Susan M. Resnick
- Brain Aging and Behavior Section, NIA, NIH, Baltimore, Maryland, USA
| | - Richard G. Spencer
- Magnetic Resonance Imaging and Spectroscopy Section, NIA, NIH, Baltimore, Maryland, USA
| | - Mustapha Bouhrara
- Magnetic Resonance Physics of Aging and Dementia (MRPAD) Unit, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, USA
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Yan H, Chen H, Liu Y, Zhang Q, Guo Y, Fu Y, Ren H, Wang H, Wang C, Ge Y. Assessment of cognitive impairment after acute cerebral infarction with T1 relaxation time measured by MP2RAGE sequence and cerebral hemodynamic by transcranial Doppler. Front Neurol 2022; 13:1056423. [PMID: 36561306 PMCID: PMC9763460 DOI: 10.3389/fneur.2022.1056423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 11/23/2022] [Indexed: 12/12/2022] Open
Abstract
Objective This study aimed to investigate early brain microstructural changes discovered using magnetization-prepared two rapid acquisition gradient echo (MP2RAGE) sequence and cerebral hemodynamic using TCD for cognitive impairment after acute cerebral infarction. Methods We enrolled 43 patients with acute cerebral infarction and 21 healthy people in the study, who were subjected to cognitive assessments, the MP2RAGE sequence, and a cerebral hemodynamic examination. A total of 26 brain regions of interest were investigated. Furthermore, we used cerebral hemodynamics to explain brain microstructural changes, which helped us better understand the pathophysiology of cognitive impairment after acute cerebral infarction and guide treatment. Results T1 relaxation times in the left frontal lobe, right frontal lobe, right temporal lobe, left precuneus, left thalamus, right hippocampus, right head of caudate nucleus, and splenium of corpus callosum were substantially different across the three groups, which were significantly correlated with neuropsychological test scores. CI group patients had significantly lower cerebral blood flow velocity than those in the N-CI and Normal groups. The receiver operating curve analysis revealed that most T1 relaxation times had high sensitivity and specificity, especially on the right temporal lobe and right frontal lobe. There was a potential correlation between T1 relaxation times and MMSE scores through TCD parameters. Conclusion The MP2RAGE sequence can detect alterations in whole brain microstructure in patients with cognitive impairment after acute cerebral infarction. Brain microstructural changes could influence cognitive function through cerebral hemodynamics. T1 relaxation times on the right temporal lobe and the right frontal lobe are expected to be a prospective biomarker of cognitive impairment after acute cerebral infarction.
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Affiliation(s)
- Hongting Yan
- The Department of Neurology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Honghai Chen
- The Department of Radiology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Yanzhi Liu
- The Department of Neurology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Qiannan Zhang
- The Department of Neurology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Yunchu Guo
- The Department of Neurology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Yu Fu
- The Department of Neurology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Hongling Ren
- The Department of Neurology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Hairong Wang
- The Department of Neurology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Chun Wang
- The Department of Neurology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
| | - Yusong Ge
- The Department of Neurology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China
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Müller SJ, Khadhraoui E, Voit D, Riedel CH, Frahm J, Ernst M. First clinical application of a novel T1 mapping of the whole brain. Neuroradiol J 2022; 35:684-691. [PMID: 35446175 PMCID: PMC9626833 DOI: 10.1177/19714009221084244] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND The aim of this study was to evaluate the reproducibility and clinical value of the novel single-shot T1 mapping method for rapid and accurate multi-slice coverage of the whole brain, described by Wang et al. 2015. METHODS At a field strength of 3 Tesla, T1 mappings of 139 patients (51 of them without pathologic findings) and two repeats of five volunteers were performed at 0.5 mm in-plane resolution. Mean T1 values were determined in 18 manually segmented regions-of-interest without pathologic findings. Reproducibility of the repeated scans was calculated using mean coefficient of variations. Pathologies were grouped and separately evaluated. RESULTS The mean age of the cohort was 49 (range 1-95 years). T1 relaxation times for ordinary brain and pathologies were in accordance with the literature values. Intra- and inter-subject reproducibility was excellent, and mean coefficient of variations were 2.4% and 3.8%, respectively. DISCUSSION The novel rapid T1 mapping method is a reliable magnetic resonance imaging technique for identifying and quantifying normal brain structures and may thus serve as a basis for assessing pathologies. The fast and parallel online calculation enables a comfortable use in everyday clinical practice. We see a possible clinical value in a large spectrum of diseases, which should be investigated in further studies.
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Affiliation(s)
| | - Eya Khadhraoui
- Department of Neuroradiology, University Medical Center
Göttingen, Germany
| | - Dirk Voit
- Max Planck Institute for Biophysical
Chemistry, Göttingen, Germany
| | | | - Jens Frahm
- Max Planck Institute for Biophysical
Chemistry, Göttingen, Germany
| | - Marielle Ernst
- Department of Neuroradiology, University Medical Center
Göttingen, Germany
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De Stefano N, Battaglini M, Pareto D, Cortese R, Zhang J, Oesingmann N, Prados F, Rocca MA, Valsasina P, Vrenken H, Gandini Wheeler-Kingshott CAM, Filippi M, Barkhof F, Rovira À. MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies. Neuroimage Clin 2022; 34:102972. [PMID: 35245791 PMCID: PMC8892169 DOI: 10.1016/j.nicl.2022.102972] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 02/22/2022] [Accepted: 02/23/2022] [Indexed: 11/24/2022]
Abstract
Sharing data from cooperative studies is essential to develop new biomarkers in MS. Differences in MRI acquisition, analysis, storage represent a substantial constraint. We review the state of the art and developments in the harmonization of MRI. We provide recommendations to harmonize large MRI datasets in the MS field.
There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.
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Affiliation(s)
- Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
| | - Marco Battaglini
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Jian Zhang
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | | | - Ferran Prados
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering, UCL, London, WC1V 6LJ, United Kingdom; e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Paola Valsasina
- Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Hugo Vrenken
- Amsterdam Neuroscience, MS Center Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Brain MRI 3T Research Center, C. Mondino National Neurological Institute, Pavia, Italy; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy; Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Frederik Barkhof
- Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Center for Medical Imaging Computing, Medical Physics and Biomedical Engineering, UCL, London, WC1V 6LJ, United Kingdom; Amsterdam Neuroscience, MS Center Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
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O'Grady KP, Satish S, Owen QR, Box BA, Bagnato F, Combes AJE, Cook SR, Westervelt HJ, Feiler HR, Lawless RD, Sarma A, Malone SD, Ndolo JM, Yoon K, Dortch RD, Rogers BP, Smith SA. Relaxation-Compensated Chemical Exchange Saturation Transfer MRI in the Brain at 7T: Application in Relapsing-Remitting Multiple Sclerosis. Front Neurol 2022; 13:764690. [PMID: 35299614 PMCID: PMC8923037 DOI: 10.3389/fneur.2022.764690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 02/01/2022] [Indexed: 11/16/2022] Open
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) can probe tissue biochemistry in vivo with high resolution and sensitivity without requiring exogenous contrast agents. Applying CEST MRI at ultrahigh field provides advantages of increasing spectral resolution and improving sensitivity to metabolites with faster proton exchange rates such as glutamate, a critical neurotransmitter in the brain. Prior magnetic resonance spectroscopy and CEST MRI studies have revealed altered regulation of glutamate in patients with multiple sclerosis (MS). While CEST imaging facilitates new strategies for investigating the pathology underlying this complex and heterogeneous neurological disease, CEST signals are contaminated or diluted by concurrent effects (e.g., semi-solid magnetization transfer (MT) and direct water saturation) and are scaled by the T1 relaxation time of the free water pool which may also be altered in the context of disease. In this study of 20 relapsing-remitting MS patients and age- and sex-matched healthy volunteers, glutamate-weighted CEST data were acquired at 7.0 T. A Lorentzian fitting procedure was used to remove the asymmetric MT contribution from CEST z-spectra, and the apparent exchange-dependent relaxation (AREX) correction was applied using an R1 map derived from an inversion recovery sequence to further isolate glutamate-weighted CEST signals from concurrent effects. Associations between AREX and cognitive function were examined using the Minimal Assessment of Cognitive Function in MS battery. After isolating CEST effects from MT, direct water saturation, and T1 effects, glutamate-weighted AREX contrast remained higher in gray matter than in white matter, though the difference between these tissues decreased. Glutamate-weighted AREX in normal-appearing gray and white matter in MS patients did not differ from healthy gray and white matter but was significantly elevated in white matter lesions. AREX in some cortical regions and in white matter lesions correlated with disability and measures of cognitive function in MS patients. However, further studies with larger sample sizes are needed to confirm these relationships due to potential confounding effects. The application of MT and AREX corrections in this study demonstrates the importance of isolating CEST signals for more specific characterization of the contribution of metabolic changes to tissue pathology and symptoms in MS.
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Affiliation(s)
- Kristin P. O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Sanjana Satish
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Quinn R. Owen
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Bailey A. Box
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Francesca Bagnato
- Neuroimaging Unit, Division of Neuroimmunology, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Neurology, Nashville VA Medical Center, TN Valley Healthcare System, Nashville, TN, United States
| | - Anna J. E. Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Sarah R. Cook
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Holly James Westervelt
- Division of Behavioral and Cognitive Neurology, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Haley R. Feiler
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Richard D. Lawless
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Asha Sarma
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Shekinah D. Malone
- School of Medicine, Meharry Medical College, Nashville, TN, United States
| | - Josephine M. Ndolo
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Keejin Yoon
- Neuroimaging Unit, Division of Neuroimmunology, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Richard D. Dortch
- Department of Translational Neuroscience, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Baxter P. Rogers
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
- Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
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Thaler C, Hartramph I, Stellmann JP, Heesen C, Bester M, Fiehler J, Gellißen S. T1 Relaxation Times in the Cortex and Thalamus Are Associated With Working Memory and Information Processing Speed in Patients With Multiple Sclerosis. Front Neurol 2021; 12:789812. [PMID: 34925222 PMCID: PMC8678069 DOI: 10.3389/fneur.2021.789812] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 11/03/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Cortical and thalamic pathologies have been associated with cognitive impairment in patients with multiple sclerosis (MS). Objective: We aimed to quantify cortical and thalamic damage in patients with MS using a high-resolution T1 mapping technique and to evaluate the association of these changes with clinical and cognitive impairment. Methods: The study group consisted of 49 patients with mainly relapsing-remitting MS and 17 age-matched healthy controls who received 3T MRIs including a T1 mapping sequence (MP2RAGE). Mean T1 relaxation times (T1-RT) in the cortex and thalami were compared between patients with MS and healthy controls. Additionally, correlation analysis was performed to assess the relationship between MRI parameters and clinical and cognitive disability. Results: Patients with MS had significantly decreased normalized brain, gray matter, and white matter volumes, as well as increased T1-RT in the normal-appearing white matter, compared to healthy controls (p < 0.001). Partial correlation analysis with age, sex, and disease duration as covariates revealed correlations for T1-RT in the cortex (r = -0.33, p < 0.05), and thalami (right thalamus: r = -0.37, left thalamus: r = -0.50, both p < 0.05) with working memory and information processing speed, as measured by the Symbol-Digit Modalities Test. Conclusion: T1-RT in the cortex and thalamus correlate with information processing speed in patients with MS.
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Affiliation(s)
- Christian Thaler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Isabelle Hartramph
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan-Patrick Stellmann
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Institute for Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,APHM La Timone, CEMEREM and Department of Neuroradiology, Marseille, France.,Aix-Marseille University, CNRS, CRMBM, UMR 7339, Marseille, France
| | - Christoph Heesen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Institute for Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Maxim Bester
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Susanne Gellißen
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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10
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Forodighasemabadi A, Rasoanandrianina H, El Mendili MM, Guye M, Callot V. An optimized MP2RAGE sequence for studying both brain and cervical spinal cord in a single acquisition at 3T. Magn Reson Imaging 2021; 84:18-26. [PMID: 34517015 DOI: 10.1016/j.mri.2021.08.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/25/2021] [Accepted: 08/25/2021] [Indexed: 11/30/2022]
Abstract
Magnetization Prepared 2 Rapid Acquisition Gradient Echo (MP2RAGE) is a T1 mapping technique that has been used broadly on brain and recently on cervical spinal cord (cSC). The growing interest for combined investigation of brain and SC in numerous pathologies of the central nervous system such as multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS) and traumatic injuries, now brings about the need for optimization with regards to this specific investigation. This implies large spatial coverage with high spatial resolution and short acquisition time, high CNR and low B1+ sensitivity, as well as high reproducibility and robust post-processing tools for T1 quantification in different regions of brain and SC. In this work, a dedicated protocol (referred to as Pr-BSC) has been optimized for simultaneous brain and cSC T1 MP2RAGE acquisition at 3T. After computer simulation optimization, the protocol was applied for in vivo validation experiments and compared to previously published state of the art protocols focusing on either the brain (Pr-B) or the cSC (Pr-SC). Reproducibility and in-ROI standard deviations were assessed on healthy volunteers in the perspective of future clinical use. The mean T1 values, obtained by the Pr-BSC, in brain white, gray and deep gray matters were: (mean ± in-ROI SD) 792 ± 27 ms, 1339 ± 139 ms and 1136 ± 88 ms, respectively. In cSC, T1 values for white matter corticospinal, posterior sensory, lateral sensory and rubro/reticulospinal tracts were 902 ± 41 ms, 920 ± 35 ms, 903 ± 46 ms, 891 ± 41 ms, respectively, and 954 ± 32 ms for anterior and intermediate gray matter. The Pr-BSC protocol showed excellent agreement with previously proposed Pr-B on brain and Pr-SC on cSC, with very high inter-scan reproducibility (coefficients of variation of 0.52 ± 0.36% and 1.12 ± 0.62% on brain and cSC, respectively). This optimized protocol covering both brain and cSC with a sub-millimetric isotropic spatial resolution in one acquisition of less than 8 min, opens up great perspectives for clinical applications focusing on degenerative tissue such as encountered in MS and ALS.
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Affiliation(s)
- Arash Forodighasemabadi
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France; Aix-Marseille Univ, Université Gustave Eiffel, LBA, Marseille, France; iLab-Spine International Associated Laboratory, Marseille-Montreal, France, Canada
| | - Henitsoa Rasoanandrianina
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France; Aix-Marseille Univ, Université Gustave Eiffel, LBA, Marseille, France; iLab-Spine International Associated Laboratory, Marseille-Montreal, France, Canada
| | - Mohamed Mounir El Mendili
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Maxime Guye
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Virginie Callot
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France; iLab-Spine International Associated Laboratory, Marseille-Montreal, France, Canada.
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11
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Ontaneda D, Raza PC, Mahajan KR, Arnold DL, Dwyer MG, Gauthier SA, Greve DN, Harrison DM, Henry RG, Li DKB, Mainero C, Moore W, Narayanan S, Oh J, Patel R, Pelletier D, Rauscher A, Rooney WD, Sicotte NL, Tam R, Reich DS, Azevedo CJ. Deep grey matter injury in multiple sclerosis: a NAIMS consensus statement. Brain 2021; 144:1974-1984. [PMID: 33757115 PMCID: PMC8370433 DOI: 10.1093/brain/awab132] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 01/28/2021] [Accepted: 02/01/2021] [Indexed: 11/13/2022] Open
Abstract
Although multiple sclerosis has traditionally been considered a white matter disease, extensive research documents the presence and importance of grey matter injury including cortical and deep regions. The deep grey matter exhibits a broad range of pathology and is uniquely suited to study the mechanisms and clinical relevance of tissue injury in multiple sclerosis using magnetic resonance techniques. Deep grey matter injury has been associated with clinical and cognitive disability. Recently, MRI characterization of deep grey matter properties, such as thalamic volume, have been tested as potential clinical trial end points associated with neurodegenerative aspects of multiple sclerosis. Given this emerging area of interest and its potential clinical trial relevance, the North American Imaging in Multiple Sclerosis (NAIMS) Cooperative held a workshop and reached consensus on imaging topics related to deep grey matter. Herein, we review current knowledge regarding deep grey matter injury in multiple sclerosis from an imaging perspective, including insights from histopathology, image acquisition and post-processing for deep grey matter. We discuss the clinical relevance of deep grey matter injury and specific regions of interest within the deep grey matter. We highlight unanswered questions and propose future directions, with the aim of focusing research priorities towards better methods, analysis, and interpretation of results.
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Affiliation(s)
- Daniel Ontaneda
- Cleveland Clinic Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland, OH 44195, USA
| | - Praneeta C Raza
- Cleveland Clinic Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland, OH 44195, USA
| | - Kedar R Mahajan
- Cleveland Clinic Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland, OH 44195, USA
| | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, The State University of New York, Buffalo, NY 14214, USA
| | - Susan A Gauthier
- Department of Neurology, Weill Cornell Medicine, New York, NY 10021, USA
| | - Douglas N Greve
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA
- Department of Radiology, Harvard Medical School, Boston, MA 02129, USA
| | - Daniel M Harrison
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Roland G Henry
- Department of Neurology, Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA
- The UC San Francisco and Berkeley Bioengineering Graduate Group, University of California San Francisco, San Francisco, CA 94143, USA
| | - David K B Li
- Department of Radiology and Medicine (Neurology), University of British Columbia, Vancouver, British Columbia V6T 2B5, Canada
| | - Caterina Mainero
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA
- Department of Radiology, Harvard Medical School, Boston, MA 02129, USA
| | - Wayne Moore
- Department of Pathology and Laboratory Medicine, and International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Jiwon Oh
- Division of Neurology, St. Michael’s Hospital, University of Toronto, Toronto, Ontario M5B 1W8, Canada
| | - Raihaan Patel
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Quebec H4H 1R3, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Daniel Pelletier
- Department of Neurology, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA
| | - Alexander Rauscher
- Physics and Astronomy, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - William D Rooney
- Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239, USA
| | - Nancy L Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Roger Tam
- Department of Radiology and Medicine (Neurology), University of British Columbia, Vancouver, British Columbia V6T 2B5, Canada
- Biomedical Engineering, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD 20824, USA
| | - Christina J Azevedo
- Department of Neurology, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA
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12
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Baucher G, Rasoanandrianina H, Levy S, Pini L, Troude L, Roche PH, Callot V. T1 Mapping for Microstructural Assessment of the Cervical Spinal Cord in the Evaluation of Patients with Degenerative Cervical Myelopathy. AJNR Am J Neuroradiol 2021; 42:1348-1357. [PMID: 33985954 DOI: 10.3174/ajnr.a7157] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 02/07/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Although current radiologic evaluation of degenerative cervical myelopathy by conventional MR imaging accurately demonstrates spondylosis or degenerative disc disease causing spinal cord dysfunction, conventional MR imaging still fails to provide satisfactory anatomic and clinical correlations. In this context, we assessed the potential value of quantitative cervical spinal cord T1 mapping regarding the evaluation of patients with degenerative cervical myelopathy. MATERIALS AND METHODS Twenty patients diagnosed with mild and moderate-to-severe degenerative cervical myelopathy and 10 healthy subjects were enrolled in a multiparametric MR imaging protocol. Cervical spinal cord T1 mapping was performed with the MP2RAGE sequence procedure. Retrieved data were processed and analyzed regarding the global spinal cord and white and anterior gray matter on the basis of the clinical severity and the spinal canal stenosis grading. RESULTS Noncompressed levels in healthy controls demonstrated significantly lower T1 values than noncompressed, mild, moderate, and severe stenotic levels in patients. Concerning the entire spinal cord T1 mapping, patients with moderate-to-severe degenerative cervical myelopathy had higher T1 values compared with healthy controls. Regarding the specific levels, patients with moderate-to-severe degenerative cervical myelopathy demonstrated a T1 value increase at C1, C7, and the level of maximal compression compared with healthy controls. Patients with mild degenerative cervical myelopathy had lower T1 values than those with moderate-to-severe degenerative cervical myelopathy at the level of maximal compression. Analyses of white and anterior gray matter confirmed similar results. Strong negative correlations between individual modified Japanese Orthopaedic Association scores and T1 values were also observed. CONCLUSIONS In this preliminary study, 3D-MP2RAGE T1 mapping demonstrated increased T1 values in the pathology tissue samples, with diffuse medullary alterations in all patients with degenerative cervical myelopathy, especially relevant at C1 (nonstenotic level) and at the maximal compression level. Encouraging correlations observed with the modified Japanese Orthopaedic Association score make this novel approach a potential quantitative biomarker related to clinical severity in degenerative cervical myelopathy. Nevertheless, patients with mild degenerative cervical myelopathy demonstrated nonsignificant results compared with healthy controls and should now be studied in multicenter studies with larger patient populations.
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Affiliation(s)
- G Baucher
- From the Neurochirurgie adulte (G.B., L.T., P.-H.R.), Assistance Publique-Hôpitaux de Marseille, Hôpital Universitaire Nord, Marseille, France
- Center for Magnetic Resonance in Biology and Medicine (G.B., H.R., L.P., S.L., V.C.), Assistance Publique-Hôpitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
- iLab-Spine International Associated Laboratory (G.B., H.R., S.L., P.-H.R., V.C.), Marseille-Montreal, France-Canada
| | - H Rasoanandrianina
- Center for Magnetic Resonance in Biology and Medicine (G.B., H.R., L.P., S.L., V.C.), Assistance Publique-Hôpitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
- Center for Magnetic Resonance in Biology and Medicine (H.R., L.P., S.L., V.C.), Aix-Marseille Université, Center National de la Recherche Scientifique, Marseille, France
- iLab-Spine International Associated Laboratory (G.B., H.R., S.L., P.-H.R., V.C.), Marseille-Montreal, France-Canada
| | - S Levy
- Center for Magnetic Resonance in Biology and Medicine (G.B., H.R., L.P., S.L., V.C.), Assistance Publique-Hôpitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
- Center for Magnetic Resonance in Biology and Medicine (H.R., L.P., S.L., V.C.), Aix-Marseille Université, Center National de la Recherche Scientifique, Marseille, France
- iLab-Spine International Associated Laboratory (G.B., H.R., S.L., P.-H.R., V.C.), Marseille-Montreal, France-Canada
| | - L Pini
- Center for Magnetic Resonance in Biology and Medicine (G.B., H.R., L.P., S.L., V.C.), Assistance Publique-Hôpitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
- Center for Magnetic Resonance in Biology and Medicine (H.R., L.P., S.L., V.C.), Aix-Marseille Université, Center National de la Recherche Scientifique, Marseille, France
| | - L Troude
- From the Neurochirurgie adulte (G.B., L.T., P.-H.R.), Assistance Publique-Hôpitaux de Marseille, Hôpital Universitaire Nord, Marseille, France
| | - P-H Roche
- From the Neurochirurgie adulte (G.B., L.T., P.-H.R.), Assistance Publique-Hôpitaux de Marseille, Hôpital Universitaire Nord, Marseille, France
- iLab-Spine International Associated Laboratory (G.B., H.R., S.L., P.-H.R., V.C.), Marseille-Montreal, France-Canada
| | - V Callot
- Center for Magnetic Resonance in Biology and Medicine (G.B., H.R., L.P., S.L., V.C.), Assistance Publique-Hôpitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
- Center for Magnetic Resonance in Biology and Medicine (H.R., L.P., S.L., V.C.), Aix-Marseille Université, Center National de la Recherche Scientifique, Marseille, France
- iLab-Spine International Associated Laboratory (G.B., H.R., S.L., P.-H.R., V.C.), Marseille-Montreal, France-Canada
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13
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RESUME N: A flexible class of multi-parameter qMRI protocols. Phys Med 2021; 88:23-36. [PMID: 34171573 DOI: 10.1016/j.ejmp.2021.04.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 03/16/2021] [Accepted: 04/02/2021] [Indexed: 12/30/2022] Open
Abstract
PURPOSE To introduce a class of fast 3D quantitative MRI (qMRI) schemes (RESUMEN, for N=1,…,4) that allow for a thorough characterization of microstructural properties of brain tissues. METHODS An arbitrary multi-echo GRE acquisition optimized for quantitative susceptibility mapping (QSM) is complemented with an appropriate low flip-angle GRE sequence drawn from four possible choices. The acquired signals are processed to analytically derive the longitudinal relaxation (R1) and free induction decay (R2∗) rates, as well as the proton density (PD) and QSM. A comprehensive modeling of the excitation and B1- profiles and of the RF-spoiling is included in the acquisition and processing pipeline. RESULTS The RESUMEN maps appear homogeneous throughout the field-of-view and exhibit comparable values and high SNR across the considered range of N values. CONCLUSIONS The introduced schemes represent a class of robust and flexible strategies to derive a thorough and fast qMRI study, suitable for a whole-brain acquisition with isotropic voxel resolution of 700 μm in less than 15 min.
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14
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Mostardeiro TR, Panda A, Campeau NG, Witte RJ, Larson NB, Sui Y, Lu A, McGee KP. Whole brain 3D MR fingerprinting in multiple sclerosis: a pilot study. BMC Med Imaging 2021; 21:88. [PMID: 34022832 PMCID: PMC8141188 DOI: 10.1186/s12880-021-00620-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 05/19/2021] [Indexed: 11/12/2022] Open
Abstract
Background MR fingerprinting (MRF) is a novel imaging method proposed for the diagnosis of Multiple Sclerosis (MS). This study aims to determine if MR Fingerprinting (MRF) relaxometry can differentiate frontal normal appearing white matter (F-NAWM) and splenium in patients diagnosed with MS as compared to controls and to characterize the relaxometry of demyelinating plaques relative to the time of diagnosis. Methods Three-dimensional (3D) MRF data were acquired on a 3.0T MRI system resulting in isotropic voxels (1 × 1 × 1 mm3) and a total acquisition time of 4 min 38 s. Data were collected on 18 subjects paired with 18 controls. Regions of interest were drawn over MRF-derived T1 relaxometry maps encompassing selected MS lesions, F-NAWM and splenium. T1 and T2 relaxometry features from those segmented areas were used to classify MS lesions from F-NAWM and splenium with T-distributed stochastic neighbor embedding algorithms. Partial least squares discriminant analysis was performed to discriminate NAWM and Splenium in MS compared with controls. Results Mean out-of-fold machine learning prediction accuracy for discriminant results between MS patients and controls for F-NAWM was 65 % (p = 0.21) and approached 90 % (p < 0.01) for the splenium. There was significant positive correlation between time since diagnosis and MS lesions mean T2 (p = 0.015), minimum T1 (p = 0.03) and negative correlation with splenium uniformity (p = 0.04). Perfect discrimination (AUC = 1) was achieved between selected features from MS lesions and F-NAWM. Conclusions 3D-MRF has the ability to differentiate between MS and controls based on relaxometry properties from the F-NAWM and splenium. Whole brain coverage allows the assessment of quantitative properties within lesions that provide chronological assessment of the time from MS diagnosis.
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Affiliation(s)
| | - Ananya Panda
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, USA
| | - Norbert G Campeau
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, USA
| | - Robert J Witte
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, USA
| | - Nicholas B Larson
- Department of Quantitative Health Sciences, Mayo Clinic, 200 1st St SW, Rochester, MN, USA
| | - Yi Sui
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, USA
| | - Aiming Lu
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, USA
| | - Kiaran P McGee
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, USA
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15
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Petracca M, Pontillo G, Moccia M, Carotenuto A, Cocozza S, Lanzillo R, Brunetti A, Brescia Morra V. Neuroimaging Correlates of Cognitive Dysfunction in Adults with Multiple Sclerosis. Brain Sci 2021; 11:346. [PMID: 33803287 PMCID: PMC8000635 DOI: 10.3390/brainsci11030346] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 03/02/2021] [Accepted: 03/04/2021] [Indexed: 02/06/2023] Open
Abstract
Cognitive impairment is a frequent and meaningful symptom in multiple sclerosis (MS), caused by the accrual of brain structural damage only partially counteracted by effective functional reorganization. As both these aspects can be successfully investigated through the application of advanced neuroimaging, here, we offer an up-to-date overview of the latest findings on structural, functional and metabolic correlates of cognitive impairment in adults with MS, focusing on the mechanisms sustaining damage accrual and on the identification of useful imaging markers of cognitive decline.
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Affiliation(s)
- Maria Petracca
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (G.P.); (S.C.); (A.B.)
- Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, 80125 Naples, Italy
| | - Marcello Moccia
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Antonio Carotenuto
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (G.P.); (S.C.); (A.B.)
| | - Roberta Lanzillo
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (G.P.); (S.C.); (A.B.)
| | - Vincenzo Brescia Morra
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
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16
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Pirastru A, Chen Y, Pelizzari L, Baglio F, Clerici M, Haacke EM, Laganà MM. Quantitative MRI using STrategically Acquired Gradient Echo (STAGE): optimization for 1.5 T scanners and T1 relaxation map validation. Eur Radiol 2021; 31:4504-4513. [PMID: 33409790 DOI: 10.1007/s00330-020-07515-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 09/24/2020] [Accepted: 11/12/2020] [Indexed: 11/24/2022]
Abstract
OBJECTIVES The strategically acquired gradient echo (STAGE) protocol, developed for 3T scanners, allows one to derive quantitative maps such as T1, T2*, proton density, and quantitative susceptibility mapping in about 5 min. Our aim was to adapt the STAGE sequences for 1.5T scanners which are still commonly used in clinical practice. Furthermore, the accuracy and repeatability of the STAGE-derived T1 estimate were tested. METHODS Flip angle (FA) optimization was performed using a theoretical simulation by maximizing signal-to-noise ratio, contrast-to-noise ratio, and T1 precision. The FA choice was further refined with the ISMRM/NIST phantom and in vivo acquisitions. The accuracy of the T1 estimate was assessed by comparing STAGE-derived T1 values with T1 maps obtained with an inversion recovery sequence. T1 accuracy was investigated for both the phantom and in vivo data. Finally, one subject was acquired 10 times once a week and a group of 27 subjects was scanned once. The T1 coefficient of variation (COV) was computed to assess scan-rescan and physiological variability, respectively. RESULTS The FA1,2 = 7°,38° were identified as the optimal FA pair at 1.5T. The T1 estimate errors were below 3% and 5% for phantom and in vivo measurements, respectively. COV for different tissues ranged from 1.8 to 4.8% for physiological variability, and between 0.8 and 2% for scan-rescan repeatability. CONCLUSION The optimized STAGE protocol can provide accurate and repeatable T1 mapping along with other qualitative images and quantitative maps in about 7 min on 1.5T scanners. This study provides the groundwork to assess the role of STAGE in clinical settings. KEY POINTS • The STAGE imaging protocol was optimized for use on 1.5T field strength scanners. • A practical STAGE protocol makes it possible to derive quantitative maps (i.e., T1, T2*, PD, and QSM) in about 7 min at 1.5T. • The T1 estimate derived from the STAGE protocol showed good accuracy and repeatability.
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Affiliation(s)
- Alice Pirastru
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Via Alfonso Capecelatro, 66, 20148, Milan, Italy
| | - Yongsheng Chen
- Department of Neurology, Wayne State University School of Medicine, 4201 St Antoine St, Detroit, MI 48201, USA
| | - Laura Pelizzari
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Via Alfonso Capecelatro, 66, 20148, Milan, Italy
| | - Francesca Baglio
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Via Alfonso Capecelatro, 66, 20148, Milan, Italy
| | - Mario Clerici
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Via Alfonso Capecelatro, 66, 20148, Milan, Italy.,Department of Pathophysiology and Transplantation, University of Milan, Via Francesco Sforza, 35, Milan, 20122, Italy
| | - E Mark Haacke
- Department of Neurology, Wayne State University School of Medicine, 4201 St Antoine St, Detroit, MI 48201, USA.,The MRI Institute for Biomedical Research, 30200 Telegraph Rd, Bingham Farms, MI 48025, USA.,Magnetic Resonance Innovations Inc, 30200 Telegraph Rd, Bingham Farms, MI 48025, USA.,Department of Radiology, Wayne State University School of Medicine, 3990 John R St, Detroit, MI 48201, USA
| | - Maria Marcella Laganà
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Via Alfonso Capecelatro, 66, 20148, Milan, Italy.
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Al-Radaideh A, Athamneh I, Alabadi H, Hbahbih M. Deep gray matter changes in relapsing-remitting multiple sclerosis detected by multi-parametric, high-resolution magnetic resonance imaging (MRI). Eur Radiol 2020; 31:706-715. [PMID: 32851443 DOI: 10.1007/s00330-020-07199-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 07/16/2020] [Accepted: 08/14/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVES To investigate a variety of magnetic resonance imaging (MRI) quantitative metrics, which reflect different aspects of microstructural damage in deep gray matter (dGM) regions and white matter T2 lesions in patients with relapsing-remitting multiple sclerosis (RRMS), and to determine the level of pathological interconnection between these two entities as well as their association with clinical disability. METHODS We recruited thirty RRMS patients along with thirty age-matched healthy controls (HCs). Both groups were scanned at 3 T MRI using 3D high-resolution T1-, T2-, and T2*-weighted, magnetization transfer (MT)-prepared gradient echo for MT ratio (MTR) mapping, and eight repeats of T1-weighted images acquired at different inversion times to create T1 maps. dGM structures were segmented from T1-weighted images using FreeSurfer, WM-T2 lesions were extracted from T2-weighted images, and iron maps were calculated from the phase part of the T2*-weighted sequence. Extracted dGM MRI indices were compared between both groups. In the RRMS group, dGM MRI indices were correlated with those of WM-T2 lesions, expanded disability status scale, and disease duration. RESULTS dGM volumetric metrics of RRMS patients were significantly (p < 0.01) smaller than those of HCs and showed a significant moderate association with lesions' load (p < 0.05) and lesions' iron concentration (p < 0.01). dGM MTRs of RRMS patients were significantly (p < 0.01) smaller than those of HCs and showed a significant (p < 0.01) moderate correlation with lesion T1 times. While T1 changes in some dGM regions of RRMS patients associated weakly with those of T2 lesions, dGM iron concentration did not show any association with any of lesions' metrics. Furthermore, lesions' MTR changes did not show any association with any dGM metrics. Most dGM metrics did not show any correlation with disease severity. Contrarily, most lesions' metrics showed weak association with disease severity. CONCLUSIONS dGM changes occur in a non-uniform pattern and, almost, do not link directly to MS disease severity. Contrarily, most WM-T2 lesions' metrics tend to correlate with MS disease severity better than those of dGM. KEY POINTS • Deep gray matter (dGM) structures are very much involved in the MS disease process and quite substantial neurodegeneration is undergone during the relapsing-remitting phase of the MS disease. • Deep gray matter (dGM) quantitative changes occur in a non-uniform and non-linked pattern and, except for CN's iron deposition, do not directly associate with the MS disease severity. • Most white matter T2 lesions' metrics tend to correlate with MS disease severity better than those of dGM structures.
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Affiliation(s)
- Ali Al-Radaideh
- Department of Medical Imaging, Faculty of Applied Medical Sciences, The Hashemite University, Zarqa, Jordan.
| | - Imad Athamneh
- Department of Radiology, King Hussein Medical Center, Jordanian Royal Medical Services, Amman, Jordan
| | - Hadeel Alabadi
- Department of Radiology, King Hussein Medical Center, Jordanian Royal Medical Services, Amman, Jordan
| | - Majed Hbahbih
- Department of Internal Medicine, Neurology, King Hussein Medical Centre, Jordanian Royal Medical Services, Amman, Jordan
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18
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Kirov II, Tal A. Potential clinical impact of multiparametric quantitative MR spectroscopy in neurological disorders: A review and analysis. Magn Reson Med 2020; 83:22-44. [PMID: 31393032 PMCID: PMC6814297 DOI: 10.1002/mrm.27912] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 06/06/2019] [Accepted: 06/29/2019] [Indexed: 12/12/2022]
Abstract
PURPOSE Unlike conventional MR spectroscopy (MRS), which only measures metabolite concentrations, multiparametric MRS also quantifies their longitudinal (T1 ) and transverse (T2 ) relaxation times, as well as the radiofrequency transmitter inhomogeneity (B1+ ). To test whether knowledge of these additional parameters can improve the clinical utility of brain MRS, we compare the conventional and multiparametric approaches in terms of expected classification accuracy in differentiating controls from patients with neurological disorders. THEORY AND METHODS A literature review was conducted to compile metabolic concentrations and relaxation times in a wide range of neuropathologies and regions of interest. Simulations were performed to construct receiver operating characteristic curves and compute the associated areas (area under the curve) to examine the sensitivity and specificity of MRS for detecting each pathology in each region. Classification accuracy was assessed using metabolite concentrations corrected using population-averages for T1 , T2 , and B1+ (conventional MRS); using metabolite concentrations corrected using per-subject values (multiparametric MRS); and using an optimal linear multiparametric estimator comprised of the metabolites' concentrations and relaxation constants (multiparametric MRS). Additional simulations were conducted to find the minimal intra-subject precision needed for each parameter. RESULTS Compared with conventional MRS, multiparametric approaches yielded area under the curve improvements for almost all neuropathologies and regions of interest. The median area under the curve increased by 0.14 over the entire dataset, and by 0.24 over the 10 instances with the largest individual increases. CONCLUSIONS Multiparametric MRS can substantially improve the clinical utility of MRS in diagnosing and assessing brain pathology, motivating the design and use of novel multiparametric sequences.
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Affiliation(s)
- Ivan I. Kirov
- Center for Advanced Imaging Innovation and Research (CAIR), Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, Department of Radiology, 660 1 Avenue, New York, NY 10016, United States of America
| | - Assaf Tal
- Department of Chemical and Biological Physics, Weizmann Institute of Science, 234 Herzel St., Rehovot 7610001, Israel
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19
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Anterior fissure, central canal, posterior septum and more: New insights into the cervical spinal cord gray and white matter regional organization using T1 mapping at 7T. Neuroimage 2020; 205:116275. [DOI: 10.1016/j.neuroimage.2019.116275] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 09/16/2019] [Accepted: 10/10/2019] [Indexed: 12/12/2022] Open
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20
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Radetz A, Koirala N, Krämer J, Johnen A, Fleischer V, Gonzalez-Escamilla G, Cerina M, Muthuraman M, Meuth SG, Groppa S. Gray matter integrity predicts white matter network reorganization in multiple sclerosis. Hum Brain Mapp 2019; 41:917-927. [PMID: 32026599 PMCID: PMC7268008 DOI: 10.1002/hbm.24849] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Revised: 10/16/2019] [Accepted: 10/17/2019] [Indexed: 01/19/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease leading to gray matter atrophy and brain network reconfiguration as a response to increasing tissue damage. We evaluated whether white matter network reconfiguration appears subsequently to gray matter damage, or whether the gray matter degenerates following alterations in white matter networks. MRI data from 83 patients with clinically isolated syndrome and early relapsing-remitting MS were acquired at two time points with a follow-up after 1 year. White matter network integrity was assessed based on probabilistic tractography performed on diffusion-weighted data using graph theoretical analyses. We evaluated gray matter integrity by computing cortical thickness and deep gray matter volume in 94 regions at both time points. The thickness of middle temporal cortex and the volume of deep gray matter regions including thalamus, caudate, putamen, and brain stem showed significant atrophy between baseline and follow-up. White matter network dynamics, as defined by modularity and distance measure changes over time, were predicted by deep gray matter volume of the atrophying anatomical structures. Initial white matter network properties, on the other hand, did not predict atrophy. Furthermore, gray matter integrity at baseline significantly predicted physical disability at 1-year follow-up. In a sub-analysis, deep gray matter volume was significantly related to cognitive performance at baseline. Hence, we postulate that atrophy of deep gray matter structures drives the adaptation of white matter networks. Moreover, deep gray matter volumes are highly predictive for disability progression and cognitive performance.
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Affiliation(s)
- Angela Radetz
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Nabin Koirala
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Julia Krämer
- Department of Neurology, University of Münster, Münster, Germany
| | - Andreas Johnen
- Department of Neurology, University of Münster, Münster, Germany
| | - Vinzenz Fleischer
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Manuela Cerina
- Department of Neurology, University of Münster, Münster, Germany
| | - Muthuraman Muthuraman
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sven G Meuth
- Department of Neurology, University of Münster, Münster, Germany
| | - Sergiu Groppa
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
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21
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Rasoanandrianina H, Massire A, Taso M, Guye M, Ranjeva JP, Kober T, Callot V. Regional T 1 mapping of the whole cervical spinal cord using an optimized MP2RAGE sequence. NMR IN BIOMEDICINE 2019; 32:e4142. [PMID: 31393649 DOI: 10.1002/nbm.4142] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 05/20/2019] [Accepted: 06/18/2019] [Indexed: 06/10/2023]
Abstract
The recently-proposed MP2RAGE sequence was purposely optimized for cervical spinal cord imaging at 3T. Sequence parameters were chosen to optimize gray/white matter T1 contrast with sub-millimetric resolution and scan-time < 10 min while preserving reliable T1 determination with minimal B1+ variation effects within a range of values compatible with pathologies and surrounding structures. Results showed good agreements with IR-based measurements, high MP2RAGE-based T1 reproducibility and preliminary evidences of age- and tract-related T1 variations in the healthy spinal cord.
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Affiliation(s)
- Henitsoa Rasoanandrianina
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- Aix-Marseille University, IFSTTAR, LBA UMR_T24, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Aurélien Massire
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Manuel Taso
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center & Harvard Medical School, Boston, Massachusetts, USA
| | - Maxime Guye
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Virginie Callot
- Aix-Marseille University, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
- iLab-Spine International Associated Laboratory, Marseille, France-, Montreal, Canada
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22
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Cortical quantitative MRI parameters are related to the cognitive status in patients with relapsing-remitting multiple sclerosis. Eur Radiol 2019; 30:1045-1053. [PMID: 31602513 DOI: 10.1007/s00330-019-06437-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 08/08/2019] [Accepted: 09/04/2019] [Indexed: 12/22/2022]
Abstract
OBJECTIVES We aimed to assess cortical damage in patients with relapsing-remitting multiple sclerosis (RRMS)/clinically isolated syndrome (CIS) with a multiparametric, surface-based quantitative MRI (qMRI) approach and to evaluate the correlation of imaging-derived parameters with cognitive scores, hypothesizing that qMRI parameters are correlated with cognitive abilities. METHODS Multiparametric qMRI-data (T1, T2 and T2* relaxation times and proton density (PD)) were obtained from 34 patients/24 matched healthy control subjects. Cortical qMRI values were analyzed on the reconstructed cortical surface with Freesurfer. We tested for group differences of cortical microstructural parameters between the healthy and patient collectives and for partial Pearson correlations of qMRI parameters with cognitive scores, correcting for age. RESULTS Cortical T2-/T2*-/PD values and four cognitive parameters differed between groups (p ≤ 0.046). These cognitive scores, reflecting information processing speed, verbal memory, visuospatial abilities, and attention, were correlated with cortical T2 (p ≤ 0.02) and T2* (p ≤ 0.03). Cortical changes appeared heterogeneous across the cortex and their distribution differed between the parameters. Vertex-wise correlation of T2 with neuropsychological parameters revealed specific patterns of cortical damage being related to distinct cognitive deficits. CONCLUSIONS Microstructural changes are distributed heterogeneously across the cortex in RRMS/CIS. QMRI has the potential to provide surrogate parameters for the assessment of cognitive impairment in these patients for clinical studies. The characteristics of cognitive impairment in RRMS might depend on the distribution of cortical changes. KEY POINTS • The goal of the presented study was to investigate cortical changes in RRMS/CIS and their relation to the cognitive status, using multiparametric quantitative MRI. • Cortical T2, T2*, and PD increases observed in patients appeared heterogeneous across the cortex and their distribution differed between the parameters. • Vertex-wise correlation of T2 with neuropsychological scores revealed specific patterns of cortical changes being related to distinct cognitive deficits.
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23
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Waterton JC, Hines CDG, Hockings PD, Laitinen I, Ziemian S, Campbell S, Gottschalk M, Green C, Haase M, Hassemer K, Juretschke HP, Koehler S, Lloyd W, Luo Y, Mahmutovic Persson I, O'Connor JPB, Olsson LE, Pindoria K, Schneider JE, Sourbron S, Steinmann D, Strobel K, Tadimalla S, Teh I, Veltien A, Zhang X, Schütz G. Repeatability and reproducibility of longitudinal relaxation rate in 12 small-animal MRI systems. Magn Reson Imaging 2019; 59:121-129. [PMID: 30872166 PMCID: PMC6477178 DOI: 10.1016/j.mri.2019.03.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 01/29/2019] [Accepted: 03/08/2019] [Indexed: 12/13/2022]
Abstract
BACKGROUND Many translational MR biomarkers derive from measurements of the water proton longitudinal relaxation rate R1, but evidence for between-site reproducibility of R1 in small-animal MRI is lacking. OBJECTIVE To assess R1 repeatability and multi-site reproducibility in phantoms for preclinical MRI. METHODS R1 was measured by saturation recovery in 2% agarose phantoms with five nickel chloride concentrations in 12 magnets at 5 field strengths in 11 centres on two different occasions within 1-13 days. R1 was analysed in three different regions of interest, giving 360 measurements in total. Root-mean-square repeatability and reproducibility coefficients of variation (CoV) were calculated. Propagation of reproducibility errors into 21 translational MR measurements and biomarkers was estimated. Relaxivities were calculated. Dynamic signal stability was also measured. RESULTS CoV for day-to-day repeatability (N = 180 regions of interest) was 2.34% and for between-centre reproducibility (N = 9 centres) was 1.43%. Mostly, these do not propagate to biologically significant between-centre error, although a few R1-based MR biomarkers were found to be quite sensitive even to such small errors in R1, notably in myocardial fibrosis, in white matter, and in oxygen-enhanced MRI. The relaxivity of aqueous Ni2+ in 2% agarose varied between 0.66 s-1 mM-1 at 3 T and 0.94 s-1 mM-1 at 11.7T. INTERPRETATION While several factors affect the reproducibility of R1-based MR biomarkers measured preclinically, between-centre propagation of errors arising from intrinsic equipment irreproducibility should in most cases be small. However, in a few specific cases exceptional efforts might be required to ensure R1-reproducibility.
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Affiliation(s)
- John C Waterton
- Bioxydyn Ltd, Manchester Science Park, Rutherford House, Pencroft Way, MANCHESTER M15 6SZ, United Kingdom; Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, MANCHESTER M13 9PL, United Kingdom.
| | | | - Paul D Hockings
- Antaros Medical, BioVenture Hub, 43183 Mölndal, Sweden; MedTech West, Chalmers University of Technology, Gothenburg, Sweden.
| | - Iina Laitinen
- Sanofi-Aventis Deutschland GmbH, R&D TIM - Bioimaging Germany, Industriepark Höchst, D-65926 Frankfurt am Main, Germany.
| | - Sabina Ziemian
- Bayer AG, Research and Development, Pharmaceuticals, MR and CT Contrast Media Research, Müllerstraße 178, D-13353 Berlin, Germany.
| | - Simon Campbell
- In-Vivo Bioimaging UK, RD Platform Technology & Science, GSK Medicines Research Centre, Gunnels Wood Road, STEVENAGE, Hertfordshire, SG1 2NY, United Kingdom.
| | - Michael Gottschalk
- Lund University BioImaging Center, Klinikgatan 32, SE-222-42 Lund, Sweden.
| | - Claudia Green
- Bayer AG, Research and Development, Pharmaceuticals, MR and CT Contrast Media Research, Müllerstraße 178, D-13353 Berlin, Germany.
| | - Michael Haase
- In-Vivo Bioimaging UK, RD Platform Technology & Science, GSK Medicines Research Centre, Gunnels Wood Road, STEVENAGE, Hertfordshire, SG1 2NY, United Kingdom.
| | - Katja Hassemer
- Sanofi-Aventis Deutschland GmbH, R&D TIM - Bioimaging Germany, Industriepark Höchst, D-65926 Frankfurt am Main, Germany.
| | - Hans-Paul Juretschke
- Sanofi-Aventis Deutschland GmbH, R&D TIM - Bioimaging Germany, Industriepark Höchst, D-65926 Frankfurt am Main, Germany
| | - Sascha Koehler
- Bruker BioSpin MRI GmbH, Rudolf-Plank-Straße 23, D-76275 Ettlingen, Germany.
| | - William Lloyd
- Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, MANCHESTER M13 9PL, United Kingdom.
| | - Yanping Luo
- iSAT Discovery, Abbvie, 1 North Waukegan Road, North Chicago, IL, 60064-1802, United States of America.
| | - Irma Mahmutovic Persson
- Department of Translational Sciences, Medical Radiation Physics, Lund University, Skåne University Hospital, SE-205 02 Malmö, Sweden.
| | - James P B O'Connor
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology Medicine & Health, University of Manchester, Manchester Academic Health Sciences Centre, MANCHESTER M20 4BX, United Kingdom. james.o'
| | - Lars E Olsson
- Department of Translational Sciences, Medical Radiation Physics, Lund University, Skåne University Hospital, SE-205 02 Malmö, Sweden.
| | - Kashmira Pindoria
- In-Vivo Bioimaging UK, RD Platform Technology & Science, GSK Medicines Research Centre, Gunnels Wood Road, STEVENAGE, Hertfordshire, SG1 2NY, United Kingdom.
| | - Jurgen E Schneider
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, United Kingdom.
| | - Steven Sourbron
- Leeds Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, LIGHT Labs, Clarendon Way, LEEDS LS2 9JT, United Kingdom.
| | - Denise Steinmann
- Sanofi-Aventis Deutschland GmbH, R&D TIM - Bioimaging Germany, Industriepark Höchst, D-65926 Frankfurt am Main, Germany.
| | - Klaus Strobel
- Bruker BioSpin MRI GmbH, Rudolf-Plank-Straße 23, D-76275 Ettlingen, Germany.
| | - Sirisha Tadimalla
- Leeds Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, LIGHT Labs, Clarendon Way, LEEDS LS2 9JT, United Kingdom.
| | - Irvin Teh
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, United Kingdom.
| | - Andor Veltien
- Radboud university medical center, Radiology (766), P.O.Box 9101, 6500, HB, Nijmegen, the Netherlands.
| | - Xiaomeng Zhang
- iSAT Discovery, Abbvie, 1 North Waukegan Road, North Chicago, IL, 60064-1802, United States of America.
| | - Gunnar Schütz
- Bayer AG, Research and Development, Pharmaceuticals, MR and CT Contrast Media Research, Müllerstraße 178, D-13353 Berlin, Germany.
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24
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Megna R, Alfano B, Lanzillo R, Costabile T, Comerci M, Vacca G, Carotenuto A, Moccia M, Servillo G, Prinster A, Brescia Morra V, Quarantelli M. Brain tissue volumes and relaxation rates in multiple sclerosis: implications for cognitive impairment. J Neurol 2018; 266:361-368. [PMID: 30498912 DOI: 10.1007/s00415-018-9139-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Revised: 11/07/2018] [Accepted: 11/22/2018] [Indexed: 12/19/2022]
Abstract
OBJECTIVE Both normal gray matter atrophy and brain tissue relaxation rates, in addition to total lesion volume, have shown significant correlations with cognitive test scores in multiple sclerosis (MS). Aim of the study was to assess the relative contributions of macro- and microstructural changes of both normal and abnormal brain tissues, probed, respectively, by their volumes and relaxation rates, to the cognitive status and physical disability of MS patients. METHODS MRI studies from 241 patients with relapsing-remitting MS were retrospectively analyzed by fully automated multiparametric relaxometric segmentation. Ordinal backward regression analysis was applied to the resulting volumes and relaxation rates of both normal (gray matter, normal-appearing white matter and CSF) and abnormal (T2-weighted lesions) brain tissues, controlling for age, sex and disease duration, to identify the main independent contributors to the cognitive status, as measured by the percentage of failed tests at a cognitive test battery (Rao's Brief Repeatable Battery and Stroop test, available in 186 patients), and to the physical disability, as assessed by the Expanded Disability Status Scale (EDSS). RESULTS The R1 relaxation rate (a putative marker of tissue disruption) of the MS lesions appeared the single most significant contributor to cognitive impairment (p < 0.001). On the contrary, the EDSS appeared mainly affected by the decrease in R2 of the gray matter (p < 0.0001), (possibly influenced by cortical plaques, edema and inflammation). CONCLUSIONS In RR-MS the tissue damage in white matter lesions appears the single main determinant of the cognitive status of patients, likely through disconnection phenomena, while the physical disability appears related to the involvement of gray matter.
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Affiliation(s)
- Rosario Megna
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy
| | - Bruno Alfano
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy
| | - Roberta Lanzillo
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Teresa Costabile
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Marco Comerci
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy
| | - Giovanni Vacca
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Antonio Carotenuto
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Marcello Moccia
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Giuseppe Servillo
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Anna Prinster
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy
| | - Vincenzo Brescia Morra
- Department of Neurosciences, Reproductive Science and Odontostomatology, University "Federico II", Naples, Italy
| | - Mario Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, Via De Amicis, 95, 80145, Naples, Italy.
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Palaniyappan L, Das T, Dempster K. The neurobiology of transition to psychosis: clearing the cache. J Psychiatry Neurosci 2017; 42:294-299. [PMID: 28834527 PMCID: PMC5573571 DOI: 10.1503/jpn.170137] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
The prepsychotic phase of schizophrenia is not only important for indicated prevention strategies, but also crucial for developing mechanistic models of the emergence of frank psychosis (transition). This commentary highlights the work of Dukart and colleagues, published in this issue of the Journal of Psychiatry and Neurosicence, who sought to identify MRI-based anatomic endophenotypes of psychosis in a well-characterized sample of patients with at-risk mental state (ARMS) and first-episode psychosis (FEP). Conceptual and translational challenges in clarifying the neurobiology of transitional prepsychotic states are discussed. A role of intracortical myelin in the neurobiology of transition is proposed. Transition may not be an outcome of "progressive structural deficits"; it may occur due to inadequate compensatory responses in the predisposed. The need to revise our current "deficit-oriented" models of neurobiology of psychosis in the wake of burgeoning evidence indicating a dynamic process of cortical reorganization is emphasized.
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Affiliation(s)
- Lena Palaniyappan
- Correspondence to: L. Palaniyappan, Prevention & Early Intervention Program for Psychoses (PEPP), A2-636, LHSC-VH, 800 Commissioners Road, London, Ont., Canada N6A 5W9;
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Louapre C, Govindarajan ST, Giannì C, Madigan N, Sloane JA, Treaba CA, Herranz E, Kinkel RP, Mainero C. Heterogeneous pathological processes account for thalamic degeneration in multiple sclerosis: Insights from 7 T imaging. Mult Scler 2017; 24:1433-1444. [PMID: 28803512 DOI: 10.1177/1352458517726382] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Thalamic degeneration impacts multiple sclerosis (MS) prognosis. OBJECTIVE To investigate heterogeneous thalamic pathology, its correlation with white matter (WM), cortical lesions and thickness, and as function of distance from cerebrospinal fluid (CSF). METHODS In 41 MS subjects and 17 controls, using 3 and 7 T imaging, we tested for (1) differences in thalamic volume and quantitative T2* (q-T2*) (2) globally and (3) within concentric bands originating from the CSF/thalamus interface; (4) the relation between thalamic, cortical, and WM metrics; and (5) the contribution of magnetic resonance imaging (MRI) metrics to clinical scores. We also assessed MS thalamic lesion distribution as a function of distance from CSF. RESULTS Thalamic lesions were mainly located next to the ventricles. Thalamic volume was decreased in MS versus controls ( p < 10-2); global q-T2* was longer in secondary progressive multiple sclerosis (SPMS) only ( p < 10-2), indicating myelin and/or iron loss. Thalamic atrophy and longer q-T2* correlated with WM lesion volume ( p < 0.01). In relapsing-remitting MS, q-T2* thalamic abnormalities were located next to the WM ( p < 0.01 (uncorrected), p = 0.09 (corrected)), while they were homogeneously distributed in SPMS. Cortical MRI metrics were the strongest predictors of clinical outcome. CONCLUSION Heterogeneous pathological processes affect the thalamus in MS. While focal lesions are likely mainly driven by CSF-mediated factors, overall thalamic degeneration develops in association with WM lesions.
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Affiliation(s)
- Céline Louapre
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
| | - Sindhuja T Govindarajan
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Costanza Giannì
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
| | - Nancy Madigan
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jacob A Sloane
- Harvard Medical School, Boston, MA, USA; Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Constantina A Treaba
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
| | - Elena Herranz
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
| | - Revere P Kinkel
- Department of Neuroscience, University of California San Diego, San Diego, CA, USA
| | - Caterina Mainero
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA/Harvard Medical School, Boston, MA, USA
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Uddin MN, McPhee KC, Blevins G, Wilman AH. Recovery of accurate T 2 from historical 1.5 tesla proton density and T 2 -weighted images: Application to 7-year T 2 changes in multiple sclerosis brain. Magn Reson Imaging 2017; 37:21-26. [DOI: 10.1016/j.mri.2016.11.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Revised: 11/11/2016] [Accepted: 11/12/2016] [Indexed: 01/12/2023]
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28
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Liu Y, Buck JR, Ikonomidou VN. Generalized min-max bound-based MRI pulse sequence design framework for wide-range T1 relaxometry: A case study on the tissue specific imaging sequence. PLoS One 2017; 12:e0172573. [PMID: 28222197 PMCID: PMC5319767 DOI: 10.1371/journal.pone.0172573] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Accepted: 02/07/2017] [Indexed: 11/18/2022] Open
Abstract
This paper proposes a new design strategy for optimizing MRI pulse sequences for T1 relaxometry. The design strategy optimizes the pulse sequence parameters to minimize the maximum variance of unbiased T1 estimates over a range of T1 values using the Cramér-Rao bound. In contrast to prior sequences optimized for a single nominal T1 value, the optimized sequence using our bound-based strategy achieves improved precision and accuracy for a broad range of T1 estimates within a clinically feasible scan time. The optimization combines the downhill simplex method with a simulated annealing process. To show the effectiveness of the proposed strategy, we optimize the tissue specific imaging (TSI) sequence. Preliminary Monte Carlo simulations demonstrate that the optimized TSI sequence yields improved precision and accuracy over the popular driven-equilibrium single-pulse observation of T1 (DESPOT1) approach for normal brain tissues (estimated T1 700–2000 ms at 3.0T). The relative mean estimation error (MSE) for T1 estimation is less than 1.7% using the optimized TSI sequence, as opposed to less than 7.0% using DESPOT1 for normal brain tissues. The optimized TSI sequence achieves good stability by keeping the MSE under 7.0% over larger T1 values corresponding to different lesion tissues and the cerebrospinal fluid (up to 5000 ms). The T1 estimation accuracy using the new pulse sequence also shows improvement, which is more pronounced in low SNR scenarios.
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Affiliation(s)
- Yang Liu
- Department of Electrical and Computer Engineering, University of Massachusetts Dartmouth, Dartmouth, MA, United States of America
- * E-mail:
| | - John R. Buck
- Department of Electrical and Computer Engineering, University of Massachusetts Dartmouth, Dartmouth, MA, United States of America
| | - Vasiliki N. Ikonomidou
- Department of Bioengineering, George Mason University, Fairfax, VA, United States of America
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29
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Thaler C, Faizy TD, Sedlacik J, Holst B, Stürner K, Heesen C, Stellmann JP, Fiehler J, Siemonsen S. T1 Recovery Is Predominantly Found in Black Holes and Is Associated with Clinical Improvement in Patients with Multiple Sclerosis. AJNR Am J Neuroradiol 2016; 38:264-269. [PMID: 28059711 DOI: 10.3174/ajnr.a5004] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 09/08/2016] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Quantitative MR imaging parameters help to evaluate disease progression in multiple sclerosis and increase correlation with clinical disability. We therefore hypothesized that T1 values might be a marker for ongoing tissue damage or even remyelination and may help increase clinical correlation. MATERIALS AND METHODS MR imaging was performed in 17 patients with relapsing-remitting MS at baseline and after 12 months of starting immunotherapy with dimethyl fumarate. On baseline images, lesion segmentation was performed for normal-appearing white matter, T2 hyperintense (FLAIR lesions), T1 hypointense (black holes), and contrast-enhancing lesions, and T1 relaxation times were obtained at baseline and after 12 months. Changes in clinical status were assessed by using the Expanded Disability Status Scale and Symbol Digit Modalities Test at both dates (Expanded Disability Status Scale-difference/Symbol Digit Modalities Test-diff). RESULTS The highest T1 relaxation time at baseline was measured in black holes (1460.2 ± 209.46 ms) followed by FLAIR lesions (1400.38 ± 189.1 ms), pure FLAIR lesions (1327.5 ± 210.04 ms), contrast-enhancing lesions (1205.59 ± 199.95 ms), and normal-appearing white matter (851.34 ± 30.61 ms). After 12 months, T1 values had decreased significantly in black holes (1369.4 ± 267.81 ms), contrast-enhancing lesions (1079.57 ± 183.36 ms) (both P < .001), and normal-appearing white matter (841.98 ± 36.1 ms, P = .006). With the Jonckheere-Terpstra Test, better clinical scores were associated with decreasing T1 relaxation times in black holes (P < .05). CONCLUSIONS T1 relaxation time is a useful quantitative MR imaging technique, which helps detect changes in MS lesions with time. We assume that these changes are associated with the degree of myelination within the lesions themselves and are pronounced in black holes. Additionally, decreasing T1 values in black holes were associated with clinical improvement.
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Affiliation(s)
- C Thaler
- From the Departments of Diagnostic and Interventional Neuroradiology (C.T., T.D.F., J.S., B.H., J.F., S.S.)
| | - T D Faizy
- From the Departments of Diagnostic and Interventional Neuroradiology (C.T., T.D.F., J.S., B.H., J.F., S.S.)
| | - J Sedlacik
- From the Departments of Diagnostic and Interventional Neuroradiology (C.T., T.D.F., J.S., B.H., J.F., S.S.)
| | - B Holst
- From the Departments of Diagnostic and Interventional Neuroradiology (C.T., T.D.F., J.S., B.H., J.F., S.S.)
| | - K Stürner
- Neurology (K.S., C.H., J.-P.S.).,Institute for Neuroimmunology and Clinical MS Research (K.S., C.H., J.-P.S., S.S.), University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - C Heesen
- Neurology (K.S., C.H., J.-P.S.).,Institute for Neuroimmunology and Clinical MS Research (K.S., C.H., J.-P.S., S.S.), University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - J-P Stellmann
- Neurology (K.S., C.H., J.-P.S.).,Institute for Neuroimmunology and Clinical MS Research (K.S., C.H., J.-P.S., S.S.), University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - J Fiehler
- From the Departments of Diagnostic and Interventional Neuroradiology (C.T., T.D.F., J.S., B.H., J.F., S.S.)
| | - S Siemonsen
- From the Departments of Diagnostic and Interventional Neuroradiology (C.T., T.D.F., J.S., B.H., J.F., S.S.).,Institute for Neuroimmunology and Clinical MS Research (K.S., C.H., J.-P.S., S.S.), University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
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30
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Paul F. Pathology and MRI: exploring cognitive impairment in MS. Acta Neurol Scand 2016; 134 Suppl 200:24-33. [PMID: 27580903 DOI: 10.1111/ane.12649] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/07/2016] [Indexed: 01/24/2023]
Abstract
Cognitive impairment is a frequent symptom in people with multiple sclerosis, affecting up to 70% of patients. This article reviews the published association of cognitive dysfunction with neuroimaging findings. Cognitive impairment has been related to focal T2 hyperintense lesions, diffuse white matter damage and corical and deep gray matter atrophy. Focal lesions cannot sufficiently explain cognitive dysfunction in MS; microstructural tissue damage detectable by diffusion tensor imaging and gray matter atrophy are probably at least as relevant. Resting state functional magnetic resonance imaging is increasingly used to investigate the contribution of functional connectivity changes to cognitive function in MS. The fact that at least one third of MS patients are not overtly cognitively impaired despite significant radiographic tissue damage argues for protective factors (brain reserve, cognitive reserve) that require further clarification. It is concluded that the reported correlations between imaging findings and cognitive function do not imply causality. Well conceived and sufficiently powered longitudinal studies are lacking. Such studies would help unravel protective mechanisms against cogniitve decline and identify suitable imaging techniques to monitor cognitive function in individual patients with MS.
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Affiliation(s)
- F. Paul
- NeuroCure Clinical Research Center and Clinical and Experimental Multiple Sclerosis Research Center; Department of Neurology; Charité - Universitaetsmedizin Berlin; Berlin Germany
- Experimental and Clinical Research Center; Max Delbrueck Center for Molecular Medicine and Charité - Universitaetsmedizin Berlin; Berlin Germany
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31
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Rimkus CDM, Steenwijk MD, Barkhof F. Causes, effects and connectivity changes in MS-related cognitive decline. Dement Neuropsychol 2016; 10:2-11. [PMID: 29213424 PMCID: PMC5674907 DOI: 10.1590/s1980-57642016dn10100002] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Cognitive decline is a frequent but undervalued aspect of multiple sclerosis (MS). Currently, it remains unclear what the strongest determinants of cognitive dysfunction are, with grey matter damage most directly related to cognitive impairment. Multi-parametric studies seem to indicate that individual factors of MS-pathology are highly interdependent causes of grey matter atrophy and permanent brain damage. They are associated with intermediate functional effects (e.g. in functional MRI) representing a balance between disconnection and (mal) adaptive connectivity changes. Therefore, a more comprehensive MRI approach is warranted, aiming to link structural changes with functional brain organization. To better understand the disconnection syndromes and cognitive decline in MS, this paper reviews the associations between MRI metrics and cognitive performance, by discussing the interactions between multiple facets of MS pathology as determinants of brain damage and how they affect network efficiency.
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Affiliation(s)
- Carolina de Medeiros Rimkus
- Department of Radiology, Laboratory of Medical Investigation (LIM-44), Faculty of Medicine of the University of São Paulo, São Paulo SP, Brazil and Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Department of Radiology, Laboratory of Medical Investigation (LIM-44), Faculty of Medicine of the University of São Paulo, São Paulo SP, Brazil and Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Martijn D Steenwijk
- Department of Radiology, Laboratory of Medical Investigation (LIM-44), Faculty of Medicine of the University of São Paulo, São Paulo SP, Brazil and Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands and Department of Physics and Medical technology, Neuroscience campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology, Laboratory of Medical Investigation (LIM-44), Faculty of Medicine of the University of São Paulo, São Paulo SP, Brazil and Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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