Disentangling white-matter damage from physiological fibre orientation dispersion in multiple sclerosis.

diffusion MRI fibre orientation dispersion microscopic fractional anisotropy multiple sclerosis tensor-valued diffusion encoding

Journal

Brain communications
ISSN: 2632-1297
Titre abrégé: Brain Commun
Pays: England
ID NLM: 101755125

Informations de publication

Date de publication:
2020
Historique:
received: 21 03 2020
revised: 20 04 2020
accepted: 07 05 2020
entrez: 21 9 2020
pubmed: 22 9 2020
medline: 22 9 2020
Statut: epublish

Résumé

Multiple sclerosis leads to diffuse damage of the central nervous system, affecting also the normal-appearing white matter. Demyelination and axonal degeneration reduce regional fractional anisotropy in normal-appearing white matter, which can be routinely mapped with diffusion tensor imaging. However, the standard fractional anisotropy metric is also sensitive to physiological variations in orientation dispersion of white matter fibres. This complicates the detection of disease-related damage in large parts of cerebral white matter where microstructure physiologically displays a high degree of fibre dispersion. To resolve this ambiguity, we employed a novel tensor-valued encoding method for diffusion MRI, which yields a microscopic fractional anisotropy metric that is unaffected by regional variations in orientation dispersion. In 26 patients with relapsing-remitting multiple sclerosis, 14 patients with primary-progressive multiple sclerosis and 27 age-matched healthy controls, we compared standard fractional anisotropy mapping with the novel microscopic fractional anisotropy mapping method, focusing on normal-appearing white matter. Mean microscopic fractional anisotropy and standard fractional anisotropy of normal-appearing white matter were significantly reduced in both patient groups relative to healthy controls, but microscopic fractional anisotropy yielded a better reflection of disease-related white-matter alterations. The reduction in mean microscopic fractional anisotropy showed a significant positive linear relationship with physical disability, as reflected by the expanded disability status scale. Mean reduction of microscopic fractional anisotropy in normal-appearing white matter also scaled positively with individual cognitive dysfunction, as measured with the symbol digit modality test. Mean microscopic fractional anisotropy reduction in normal-appearing white matter also showed a positive relationship with total white-matter lesion load as well as lesion load in specific tract systems. None of these relationships between normal-appearing white-matter microstructure and clinical, cognitive or structural measures emerged when using mean fractional anisotropy. Together, the results provide converging evidence that microscopic fractional anisotropy mapping substantially advances the assessment of cerebral white matter in multiple sclerosis by disentangling microstructure damage from variations in physiological fibre orientation dispersion at the stage of data acquisition. Since tensor-valued encoding can be implemented in routine diffusion MRI, microscopic fractional anisotropy mapping bears considerable potential for the future assessment of disease progression in normal-appearing white matter in both relapsing-remitting and progressive forms of multiple sclerosis as well as other white-matter-related brain diseases.

Identifiants

pubmed: 32954329
doi: 10.1093/braincomms/fcaa077
pii: fcaa077
pmc: PMC7472898
doi:

Types de publication

Journal Article

Langues

eng

Pagination

fcaa077

Informations de copyright

© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.

Références

J Neuroimaging. 2010 Oct;20(4):334-44
pubmed: 19453832
Hum Brain Mapp. 2019 Jun 1;40(8):2529-2545
pubmed: 30802367
PLoS One. 2015 Nov 03;10(11):e0141825
pubmed: 26528541
Neurologist. 2011 Jul;17(4):185-204
pubmed: 21712664
Neuroimage. 2012 Jul 16;61(4):1000-16
pubmed: 22484410
J Neurol Sci. 2018 Aug 15;391:127-133
pubmed: 30103962
Brain Pathol. 2015 Sep;25(5):565-74
pubmed: 25311358
IEEE Trans Med Imaging. 2010 Jan;29(1):196-205
pubmed: 19923044
Neuroimage. 2016 Nov 15;142:522-532
pubmed: 27450666
Neuroimage. 2018 Nov 15;182:62-79
pubmed: 29920374
NMR Biomed. 2017 Dec;30(12):
pubmed: 28915311
J Alzheimers Dis. 2014;41(1):69-83
pubmed: 24577476
Eur Radiol. 2016 Feb;26(2):515-23
pubmed: 26026721
NMR Biomed. 2019 Apr;32(4):e3841
pubmed: 29193413
Mult Scler Int. 2013;2013:671730
pubmed: 23606965
Neuroimage. 2011 Apr 1;55(3):880-90
pubmed: 21182970
Brain. 2015 May;138(Pt 5):1223-38
pubmed: 25724201
Mult Scler. 2001 Oct;7(5):290-7
pubmed: 11724444
Neuroimage. 2017 Feb 15;147:517-531
pubmed: 27903438
F1000Res. 2017 Oct 12;6:1828
pubmed: 29093810
Lancet. 2018 Apr 21;391(10130):1622-1636
pubmed: 29576504
Neuroimage. 2014 Dec;103:202-213
pubmed: 25219332
J Chem Phys. 2015 Mar 14;142(10):104201
pubmed: 25770532
J Magn Reson B. 1996 Jun;111(3):209-19
pubmed: 8661285
Neuroimage. 2015 Jan 1;104:241-52
pubmed: 25284306
Lancet Neurol. 2012 Apr;11(4):349-60
pubmed: 22441196
Neuroimage. 2016 Nov 1;141:313-325
pubmed: 27436594
Neuroimage Clin. 2015 Apr 10;8:110-6
pubmed: 26106534
Brain Topogr. 2014 May;27(3):393-402
pubmed: 24414091
J Neuroimaging. 2015 Mar-Apr;25(2):200-206
pubmed: 25318661
Neurology. 1983 Nov;33(11):1444-52
pubmed: 6685237
Neuroimage. 2003 Oct;20(2):870-88
pubmed: 14568458
Magn Reson Med. 2016 Jan;75(1):82-7
pubmed: 26418050
Magn Reson Med. 2016 Apr;75(4):1752-63
pubmed: 25974332
BMC Neurol. 2018 Dec 20;18(1):214
pubmed: 30572821
Neuroimage. 1999 Feb;9(2):179-94
pubmed: 9931268
J Neuroinflammation. 2012 Jul 02;9:156
pubmed: 22747960
Hum Brain Mapp. 2013 Nov;34(11):2747-66
pubmed: 22611035
Neuroimage. 2006 Jul 15;31(4):1487-505
pubmed: 16624579
Neuropathol Appl Neurobiol. 2011 Dec;37(7):698-710
pubmed: 21696413
Magn Reson Med. 2004 Dec;52(6):1358-72
pubmed: 15562495
J Magn Reson. 2013 Jan;226:13-8
pubmed: 23178533
Hum Brain Mapp. 2011 Jun;32(6):846-55
pubmed: 21495114
Magn Reson Med. 1995 Jan;33(1):41-52
pubmed: 7891534
Neuroimage. 2011 Apr 15;55(4):1566-76
pubmed: 21262366
Magn Reson Med. 2018 Aug;80(2):507-520
pubmed: 29266375
Mult Scler. 2015 Dec;21(14):1794-801
pubmed: 26106010
Eur J Radiol. 2012 Oct;81(10):2826-32
pubmed: 22172535
AJNR Am J Neuroradiol. 2007 Jun-Jul;28(6):1102-6
pubmed: 17569968
Handb Clin Neurol. 2014;122:15-58
pubmed: 24507512
Aging Dis. 2010 Dec;1(3):262-78
pubmed: 22396865
Radiology. 2011 Aug;260(2):541-50
pubmed: 21673227
J Neurol Neurosurg Psychiatry. 2011 Jan;82(1):72-7
pubmed: 20627965
PLoS One. 2019 Mar 28;14(3):e0214238
pubmed: 30921381
Neurology. 2000 Apr 11;54(7):1421-7
pubmed: 10751250
Neuroimage. 2005 May 15;26(1):258-65
pubmed: 15862226
NMR Biomed. 2019 Apr;32(4):e3998
pubmed: 30321478
Magn Reson Med. 2020 Feb;83(2):608-620
pubmed: 31517401
Neuroimage. 2016 Jul 15;135:345-62
pubmed: 26923372
Neuroimage. 2001 Jun;13(6 Pt 1):1174-85
pubmed: 11352623
Neuroimage. 2016 Jan 15;125:1063-1078
pubmed: 26481672
Mult Scler. 2016 Apr;22(5):608-19
pubmed: 26209593
J Neurol Sci. 2013 Jul 15;330(1-2):61-6
pubmed: 23643443
Eur J Radiol. 2012 Mar;81(3):e386-91
pubmed: 22257426
Neuroimage. 2012 Oct 15;63(1):1-10
pubmed: 22759994
Neurosci Biobehav Rev. 2006;30(6):749-61
pubmed: 16887187
Mult Scler. 2016 Jan;22(1):73-84
pubmed: 25921041
Magn Reson Med. 2019 May;81(5):3245-3261
pubmed: 30648753
Brain. 2019 Jul 1;142(7):1858-1875
pubmed: 31209474
Magn Reson Med. 2009 May;61(5):1255-60
pubmed: 19253405
NMR Biomed. 2002 Nov-Dec;15(7-8):435-55
pubmed: 12489094
J Magn Reson. 2017 Feb;275:98-113
pubmed: 28040623

Auteurs

Kasper Winther Andersen (KW)

Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark.

Samo Lasič (S)

Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark.
Random Walk Imaging, AB, 222 24 Lund, Sweden.

Henrik Lundell (H)

Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark.

Markus Nilsson (M)

Department of Radiology, Clinical Sciences, Lund, Lund University, 221 00 Lund, Sweden.

Daniel Topgaard (D)

Division of Physical Chemistry, Department of Chemistry, Lund University, 221 00 Lund, Sweden.

Finn Sellebjerg (F)

Danish Multiple Sclerosis Center, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark.

Filip Szczepankiewicz (F)

Department of Medical Radiation Physics, Clinical Sciences, Lund, Lund University, 221 00 Lund, Sweden.

Hartwig Roman Siebner (HR)

Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark.
Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark.
Department of Neurology, Copenhagen University Hospital Bispebjerg, 2400 Copenhagen NV, Denmark.

Morten Blinkenberg (M)

Danish Multiple Sclerosis Center, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark.

Tim B Dyrby (TB)

Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark.
Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2700 Kongens Lyngby, Denmark.

Classifications MeSH