Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial

Background: Deep grey matter pathology is a key driver of disability worsening in people with multiple sclerosis. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique which quantifies local magnetic susceptibility from variations in phase produced by ch...

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Main Authors: Thomas Williams, Nevin John, Alberto Calvi, Alessia Bianchi, Floriana De Angelis, Anisha Doshi, Sarah Wright, Madiha Shatila, Marios C. Yiannakas, Fatima Chowdhury, Jon Stutters, Antonio Ricciardi, Ferran Prados, David MacManus, Francesco Grussu, Anita Karsa, Becky Samson, Marco Battiston, Claudia A.M. Gandini Wheeler-Kingshott, Karin Shmueli, Olga Ciccarelli, Frederik Barkhof, Jeremy Chataway, Wallace Brownlee, Claudia AM. Gandini Wheeler-Kingshott, Jonathan Stutters, Ferran Prados Carrasco, Marios Yiannakas, Megan Wynne, Marie Braisher, James Blackstone, Leanne Hockey, Josephine Parker, Jennifer Flight, Chris Frost, Jennifer Nicholas, Stuart Nixon, Judy Beveridge
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Language:English
Published: Elsevier 2024-09-01
Series:NeuroImage: Reports
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666956024000229
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author Thomas Williams
Nevin John
Alberto Calvi
Alessia Bianchi
Floriana De Angelis
Anisha Doshi
Sarah Wright
Madiha Shatila
Marios C. Yiannakas
Fatima Chowdhury
Jon Stutters
Antonio Ricciardi
Ferran Prados
David MacManus
Francesco Grussu
Anita Karsa
Becky Samson
Marco Battiston
Claudia A.M. Gandini Wheeler-Kingshott
Karin Shmueli
Olga Ciccarelli
Frederik Barkhof
Jeremy Chataway
Jeremy Chataway
Thomas Williams
Nevin John
Floriana De Angelis
Alberto Calvi
Alessia Bianchi
Sarah Wright
Madiha Shatila
Anisha Doshi
Wallace Brownlee
Claudia AM. Gandini Wheeler-Kingshott
Frederik Barkhof
Olga Ciccarelli
Jonathan Stutters
Ferran Prados Carrasco
Antonio Ricciardi
Marios Yiannakas
David MacManus
Megan Wynne
Marie Braisher
James Blackstone
Leanne Hockey
Josephine Parker
Jennifer Flight
Chris Frost
Jennifer Nicholas
Stuart Nixon
Judy Beveridge
author_facet Thomas Williams
Nevin John
Alberto Calvi
Alessia Bianchi
Floriana De Angelis
Anisha Doshi
Sarah Wright
Madiha Shatila
Marios C. Yiannakas
Fatima Chowdhury
Jon Stutters
Antonio Ricciardi
Ferran Prados
David MacManus
Francesco Grussu
Anita Karsa
Becky Samson
Marco Battiston
Claudia A.M. Gandini Wheeler-Kingshott
Karin Shmueli
Olga Ciccarelli
Frederik Barkhof
Jeremy Chataway
Jeremy Chataway
Thomas Williams
Nevin John
Floriana De Angelis
Alberto Calvi
Alessia Bianchi
Sarah Wright
Madiha Shatila
Anisha Doshi
Wallace Brownlee
Claudia AM. Gandini Wheeler-Kingshott
Frederik Barkhof
Olga Ciccarelli
Jonathan Stutters
Ferran Prados Carrasco
Antonio Ricciardi
Marios Yiannakas
David MacManus
Megan Wynne
Marie Braisher
James Blackstone
Leanne Hockey
Josephine Parker
Jennifer Flight
Chris Frost
Jennifer Nicholas
Stuart Nixon
Judy Beveridge
author_sort Thomas Williams
collection DOAJ
description Background: Deep grey matter pathology is a key driver of disability worsening in people with multiple sclerosis. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique which quantifies local magnetic susceptibility from variations in phase produced by changes in the local magnetic field. In the deep grey matter, susceptibility has previously been validated against tissue iron concentration. However, it currently remains unknown whether susceptibility is abnormal in older progressive MS cohorts, and whether it correlates with disability. Objectives: To investigate differences in mean regional susceptibility in deep grey matter between people with secondary progressive multiple sclerosis (SPMS) and healthy controls; to examine in patients the relationships between deep grey matter susceptibility and clinical and imaging measures of disease severity. Methods: Baseline data from a subgroup of the MS-STAT2 trial (simvastatin vs. placebo in SPMS, NCT03387670) were included. The subgroup underwent clinical assessments and an advanced MRI protocol at 3T. A cohort of age-matched healthy controls underwent the same MRI protocol. Susceptibility maps were reconstructed using a robust QSM pipeline from multi-echo 3D gradient-echo sequence. Regions of interest (ROIs) in the thalamus, globus pallidus and putamen were segmented from 3D T1-weighted images, and lesions segmented from 3D fluid-attenuated inversion recovery images. Linear regression was used to compare susceptibility from ROIs between patients and controls, adjusting for age and sex. Where significant differences were found, we further examined the associations between ROI susceptibility and clinical and imaging measures of MS severity. Results: 149 SPMS (77% female; mean age: 53 yrs; median Expanded Disability Status Scale (EDSS): 6.0 [interquartile range 4.5–6.0]) and 33 controls (52% female, mean age: 57) were included.Thalamic susceptibility was significantly lower in SPMS compared to controls: mean (SD) 28.6 (12.8) parts per billion (ppb) in SPMS vs. 39.2 (12.7) ppb in controls; regression coefficient: −12.0 [95% confidence interval: −17.0 to −7.1], p < 0.001. In contrast, globus pallidus and putamen susceptibility were similar between both groups.In SPMS, a 10 ppb lower thalamic susceptibility was associated with a +0.13 [+0.01 to +0.24] point higher EDSS (p < 0.05), a −2.4 [−3.8 to −1.0] point lower symbol digit modality test (SDMT, p = 0.001), and a −2.4 [−3.7 to −1.1] point lower Sloan low contrast acuity, 2.5% (p < 0.01).Lower thalamic susceptibility was also strongly associated with a higher T2 lesion volume (T2LV, p < 0.001) and lower normalised whole brain, deep grey matter and thalamic volumes (all p < 0.001). Conclusions: The reduced thalamic susceptibility found in SPMS compared to controls suggests that thalamic iron concentrations are lower at this advanced stage of the disease. The observed relationships between lower thalamic susceptibility and more severe physical, cognitive and visual disability suggests that reductions in thalamic iron may correlate with important mechanisms of clinical disease progression. Such mechanisms appear to intimately link reductions in thalamic iron with higher T2LV and the development of thalamic atrophy, encouraging further research into QSM-derived thalamic susceptibility as a biomarker of disease severity in SPMS.
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spelling doaj-art-a5f0c83cc2dc4adf9dbc117e4d8f1ca02025-08-20T03:20:00ZengElsevierNeuroImage: Reports2666-95602024-09-014310021610.1016/j.ynirp.2024.100216Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trialThomas Williams0Nevin John1Alberto Calvi2Alessia Bianchi3Floriana De Angelis4Anisha Doshi5Sarah Wright6Madiha Shatila7Marios C. Yiannakas8Fatima Chowdhury9Jon Stutters10Antonio Ricciardi11Ferran Prados12David MacManus13Francesco Grussu14Anita Karsa15Becky Samson16Marco Battiston17Claudia A.M. Gandini Wheeler-Kingshott18Karin Shmueli19Olga Ciccarelli20Frederik Barkhof21Jeremy Chataway22Jeremy Chataway23Thomas Williams24Nevin John25Floriana De Angelis26Alberto Calvi27Alessia Bianchi28Sarah Wright29Madiha Shatila30Anisha Doshi31Wallace Brownlee32Claudia AM. Gandini Wheeler-Kingshott33Frederik Barkhof34Olga Ciccarelli35Jonathan Stutters36Ferran Prados Carrasco37Antonio Ricciardi38Marios Yiannakas39David MacManus40Megan Wynne41Marie Braisher42James Blackstone43Leanne Hockey44Josephine Parker45Jennifer Flight46Chris Frost47Jennifer Nicholas48Stuart Nixon49Judy Beveridge50NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; Corresponding author. Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, WC1B 5EH, United Kingdom.NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; Monash University, Department of Medicine, School of Clinical Sciences, Clayton, AustraliaNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United Kingdom; Universitat Oberta de Catalunya, Barcelona, SpainNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United KingdomDepartment of Medical Physics and Biomedical Engineering, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, ItalyDepartment of Medical Physics and Biomedical Engineering, University College London, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, United KingdomNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; University College London, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, London, United Kingdom; National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, United Kingdom; Vrije Universiteit Amsterdam, Department of Radiology &amp; Nuclear Medicine, VU University Medical Centre, Amsterdam, NetherlandsNMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom; Medical Research Council Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, United Kingdom; National Institute for Health Research, Biomedical Research Centre, University College London Hospitals, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United KingdomComprehensive Clinical Trials Unit [CCTU], Institute of Clinical Trials and Methodology, University College London, London, United KingdomComprehensive Clinical Trials Unit [CCTU], Institute of Clinical Trials and Methodology, University College London, London, United KingdomComprehensive Clinical Trials Unit [CCTU], Institute of Clinical Trials and Methodology, University College London, London, United KingdomComprehensive Clinical Trials Unit [CCTU], Institute of Clinical Trials and Methodology, University College London, London, United KingdomCentre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, United KingdomCentre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United Kingdom; Comprehensive Clinical Trials Unit [CCTU], Institute of Clinical Trials and Methodology, University College London, London, United Kingdom; Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, United KingdomQueen Square Multiple Sclerosis Centre, University College London and University College London Hospitals NHS Foundation Trust, London, United Kingdom; Comprehensive Clinical Trials Unit [CCTU], Institute of Clinical Trials and Methodology, University College London, London, United Kingdom; Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, United KingdomBackground: Deep grey matter pathology is a key driver of disability worsening in people with multiple sclerosis. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique which quantifies local magnetic susceptibility from variations in phase produced by changes in the local magnetic field. In the deep grey matter, susceptibility has previously been validated against tissue iron concentration. However, it currently remains unknown whether susceptibility is abnormal in older progressive MS cohorts, and whether it correlates with disability. Objectives: To investigate differences in mean regional susceptibility in deep grey matter between people with secondary progressive multiple sclerosis (SPMS) and healthy controls; to examine in patients the relationships between deep grey matter susceptibility and clinical and imaging measures of disease severity. Methods: Baseline data from a subgroup of the MS-STAT2 trial (simvastatin vs. placebo in SPMS, NCT03387670) were included. The subgroup underwent clinical assessments and an advanced MRI protocol at 3T. A cohort of age-matched healthy controls underwent the same MRI protocol. Susceptibility maps were reconstructed using a robust QSM pipeline from multi-echo 3D gradient-echo sequence. Regions of interest (ROIs) in the thalamus, globus pallidus and putamen were segmented from 3D T1-weighted images, and lesions segmented from 3D fluid-attenuated inversion recovery images. Linear regression was used to compare susceptibility from ROIs between patients and controls, adjusting for age and sex. Where significant differences were found, we further examined the associations between ROI susceptibility and clinical and imaging measures of MS severity. Results: 149 SPMS (77% female; mean age: 53 yrs; median Expanded Disability Status Scale (EDSS): 6.0 [interquartile range 4.5–6.0]) and 33 controls (52% female, mean age: 57) were included.Thalamic susceptibility was significantly lower in SPMS compared to controls: mean (SD) 28.6 (12.8) parts per billion (ppb) in SPMS vs. 39.2 (12.7) ppb in controls; regression coefficient: −12.0 [95% confidence interval: −17.0 to −7.1], p < 0.001. In contrast, globus pallidus and putamen susceptibility were similar between both groups.In SPMS, a 10 ppb lower thalamic susceptibility was associated with a +0.13 [+0.01 to +0.24] point higher EDSS (p < 0.05), a −2.4 [−3.8 to −1.0] point lower symbol digit modality test (SDMT, p = 0.001), and a −2.4 [−3.7 to −1.1] point lower Sloan low contrast acuity, 2.5% (p < 0.01).Lower thalamic susceptibility was also strongly associated with a higher T2 lesion volume (T2LV, p < 0.001) and lower normalised whole brain, deep grey matter and thalamic volumes (all p < 0.001). Conclusions: The reduced thalamic susceptibility found in SPMS compared to controls suggests that thalamic iron concentrations are lower at this advanced stage of the disease. The observed relationships between lower thalamic susceptibility and more severe physical, cognitive and visual disability suggests that reductions in thalamic iron may correlate with important mechanisms of clinical disease progression. Such mechanisms appear to intimately link reductions in thalamic iron with higher T2LV and the development of thalamic atrophy, encouraging further research into QSM-derived thalamic susceptibility as a biomarker of disease severity in SPMS.http://www.sciencedirect.com/science/article/pii/S2666956024000229Multiple sclerosisDeep grey matterThalamusIronQuantitative susceptibility mapping
spellingShingle Thomas Williams
Nevin John
Alberto Calvi
Alessia Bianchi
Floriana De Angelis
Anisha Doshi
Sarah Wright
Madiha Shatila
Marios C. Yiannakas
Fatima Chowdhury
Jon Stutters
Antonio Ricciardi
Ferran Prados
David MacManus
Francesco Grussu
Anita Karsa
Becky Samson
Marco Battiston
Claudia A.M. Gandini Wheeler-Kingshott
Karin Shmueli
Olga Ciccarelli
Frederik Barkhof
Jeremy Chataway
Jeremy Chataway
Thomas Williams
Nevin John
Floriana De Angelis
Alberto Calvi
Alessia Bianchi
Sarah Wright
Madiha Shatila
Anisha Doshi
Wallace Brownlee
Claudia AM. Gandini Wheeler-Kingshott
Frederik Barkhof
Olga Ciccarelli
Jonathan Stutters
Ferran Prados Carrasco
Antonio Ricciardi
Marios Yiannakas
David MacManus
Megan Wynne
Marie Braisher
James Blackstone
Leanne Hockey
Josephine Parker
Jennifer Flight
Chris Frost
Jennifer Nicholas
Stuart Nixon
Judy Beveridge
Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial
NeuroImage: Reports
Multiple sclerosis
Deep grey matter
Thalamus
Iron
Quantitative susceptibility mapping
title Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial
title_full Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial
title_fullStr Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial
title_full_unstemmed Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial
title_short Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial
title_sort investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping cross sectional analysis from the ms stat2 randomised controlled trial
topic Multiple sclerosis
Deep grey matter
Thalamus
Iron
Quantitative susceptibility mapping
url http://www.sciencedirect.com/science/article/pii/S2666956024000229
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AT leannehockey investigatingtherelationshipbetweenthalamicironconcentrationanddiseaseseverityinsecondaryprogressivemultiplesclerosisusingquantitativesusceptibilitymappingcrosssectionalanalysisfromthemsstat2randomisedcontrolledtrial
AT josephineparker investigatingtherelationshipbetweenthalamicironconcentrationanddiseaseseverityinsecondaryprogressivemultiplesclerosisusingquantitativesusceptibilitymappingcrosssectionalanalysisfromthemsstat2randomisedcontrolledtrial
AT jenniferflight investigatingtherelationshipbetweenthalamicironconcentrationanddiseaseseverityinsecondaryprogressivemultiplesclerosisusingquantitativesusceptibilitymappingcrosssectionalanalysisfromthemsstat2randomisedcontrolledtrial
AT chrisfrost investigatingtherelationshipbetweenthalamicironconcentrationanddiseaseseverityinsecondaryprogressivemultiplesclerosisusingquantitativesusceptibilitymappingcrosssectionalanalysisfromthemsstat2randomisedcontrolledtrial
AT jennifernicholas investigatingtherelationshipbetweenthalamicironconcentrationanddiseaseseverityinsecondaryprogressivemultiplesclerosisusingquantitativesusceptibilitymappingcrosssectionalanalysisfromthemsstat2randomisedcontrolledtrial
AT stuartnixon investigatingtherelationshipbetweenthalamicironconcentrationanddiseaseseverityinsecondaryprogressivemultiplesclerosisusingquantitativesusceptibilitymappingcrosssectionalanalysisfromthemsstat2randomisedcontrolledtrial
AT judybeveridge investigatingtherelationshipbetweenthalamicironconcentrationanddiseaseseverityinsecondaryprogressivemultiplesclerosisusingquantitativesusceptibilitymappingcrosssectionalanalysisfromthemsstat2randomisedcontrolledtrial