Evaluation of white matter microstructure in pediatric onset multiple sclerosis with diffusion compartment imaging.


Journal

Journal of neuroimaging : official journal of the American Society of Neuroimaging
ISSN: 1552-6569
Titre abrégé: J Neuroimaging
Pays: United States
ID NLM: 9102705

Informations de publication

Date de publication:
11 2022
Historique:
revised: 20 07 2022
received: 14 03 2022
accepted: 05 08 2022
pubmed: 30 8 2022
medline: 11 11 2022
entrez: 29 8 2022
Statut: ppublish

Résumé

Pediatric-onset multiple sclerosis (POMS) shows earlier axonal involvement and greater axonal loss than in adults. We aim to characterize the white matter (WM) microstructural changes in POMS using a diffusion compartment imaging (DCI) model and compare it to standard diffusion tensor imaging (DTI). Eleven patients (2 males, mean age 18.8 ± 3.9 years) with a diagnosis of relapsing and remitting POMS (mean age at disease onset 13.8 ± 2.9 years, mean duration 5.1 ± 1.9 years) and healthy controls (8 males, mean age 26.4 ± 6.5 years) were recruited and imaged at 3 T. A 90-gradient set Cube and Sphere acquisition and a novel DCI model known as DIstribution of Anisotropic MicrOstructural eNvironments with Diffusion-weighted imaging (DIAMOND) were used to calculate a single anisotropic compartment, an isotropic compartment, and a free diffusion compartment. Lesions and contralateral normal-appearing white matter (NAWM) in patients and whole brain WM for controls were labeled. Eleven patients and 11 controls were recruited. When comparing lesions and contralateral NAWM in patients using DCI, compartmental axial diffusivity, radial diffusivity (cRD), and mean diffusivity (cMD) were higher in lesions. Conversely, compartmental fractional anisotropy (cFA) and heterogeneity index were lower in lesions. An analysis of DTI equivalents showed the same trends. In whole-brain NAWM of patients compared to controls, cRD and cMD were higher and cFA was lower in patients. Lesions in POMS can be accurately characterized by a DCI model. Incipient changes in NAWM seen in DCI may not be readily observable by DTI.

Sections du résumé

BACKGROUND AND PURPOSE
Pediatric-onset multiple sclerosis (POMS) shows earlier axonal involvement and greater axonal loss than in adults. We aim to characterize the white matter (WM) microstructural changes in POMS using a diffusion compartment imaging (DCI) model and compare it to standard diffusion tensor imaging (DTI).
METHODS
Eleven patients (2 males, mean age 18.8 ± 3.9 years) with a diagnosis of relapsing and remitting POMS (mean age at disease onset 13.8 ± 2.9 years, mean duration 5.1 ± 1.9 years) and healthy controls (8 males, mean age 26.4 ± 6.5 years) were recruited and imaged at 3 T. A 90-gradient set Cube and Sphere acquisition and a novel DCI model known as DIstribution of Anisotropic MicrOstructural eNvironments with Diffusion-weighted imaging (DIAMOND) were used to calculate a single anisotropic compartment, an isotropic compartment, and a free diffusion compartment. Lesions and contralateral normal-appearing white matter (NAWM) in patients and whole brain WM for controls were labeled.
RESULTS
Eleven patients and 11 controls were recruited. When comparing lesions and contralateral NAWM in patients using DCI, compartmental axial diffusivity, radial diffusivity (cRD), and mean diffusivity (cMD) were higher in lesions. Conversely, compartmental fractional anisotropy (cFA) and heterogeneity index were lower in lesions. An analysis of DTI equivalents showed the same trends. In whole-brain NAWM of patients compared to controls, cRD and cMD were higher and cFA was lower in patients.
CONCLUSION
Lesions in POMS can be accurately characterized by a DCI model. Incipient changes in NAWM seen in DCI may not be readily observable by DTI.

Identifiants

pubmed: 36036739
doi: 10.1111/jon.13038
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1098-1108

Subventions

Organisme : Office Of The Director, National Institutes Of Health of the National Institutes of Health (NIH)
ID : R01 NS121657
Organisme : Office Of The Director, National Institutes Of Health of the National Institutes of Health (NIH)
ID : R01 NS079788
Organisme : Office Of The Director, National Institutes Of Health of the National Institutes of Health (NIH)
ID : R01 EB019483
Organisme : Office Of The Director, National Institutes Of Health of the National Institutes of Health (NIH)
ID : S10OD025111

Informations de copyright

© 2022 American Society of Neuroimaging.

Références

Longoni G, Brown RA, MomayyezSiahkal P, et al. White matter changes in paediatric multiple sclerosis and monophasic demyelinating disorders. Brain. 2017;140:1300-15.
Alroughani R, Boyko A. Pediatric multiple sclerosis: a review. BMC Neurology. 2018;18:27.
Gorman MP, Healy BC, Polgar-Turcsanyi M, et al. Increased relapse rate in pediatric-onset compared with adult-onset multiple sclerosis. Arch Neurol. 2009;66:54-9.
Benson LA, Healy BC, Gorman MP, et al. Elevated relapse rates in pediatric compared to adult MS persist for at least 6 years. Mult Scler Relat Disord. 2014;3:186-93.
McKay KA, Hillert J, Manouchehrinia A. Long-term disability progression of pediatric-onset multiple sclerosis. Neurology. 2019;92:e2764-73.
Pfeifenbring S, Bunyan RF, Metz I, et al. Extensive acute axonal damage in pediatric multiple sclerosis lesions. Ann Neurol. 2015;77:655-67.
Vishwas MS, Healy BC, Pienaar R, et al. Diffusion tensor analysis of pediatric multiple sclerosis and clinically isolated syndromes. AJNR Am J Neuroradiol. 2013;34:417-23.
Granberg T, Fan Q, Treaba CA, et al. In vivo characterization of cortical and white matter neuroaxonal pathology in early multiple sclerosis. Brain. 2017;140:2912-26.
Hagiwara A, Kamagata K, Shimoji K, et al. White matter abnormalities in multiple sclerosis evaluated by quantitative synthetic MRI, diffusion tensor imaging, and neurite orientation dispersion and density imaging. AJNR Am J Neuroradiol. 2019;40:1642-8.
Scherrer B, Schwartzman A, Taquet M, et al. Characterizing brain tissue by assessment of the distribution of anisotropic microstructural environments in diffusion-compartment imaging (DIAMOND). Magn Reson Med. 2016;76:963-77.
Scherrer B, Warfield SK. Parametric representation of multiple white matter fascicles from cube and sphere diffusion MRI. PLoS One. 2012;7:e48232.
Yushkevich PA, Gao null Y, Gerig G. ITK-SNAP: an interactive tool for semi-automatic segmentation of multi-modality biomedical images. Annu Int Conf IEEE Eng Med Biol Soc. 2016;2016:3342-5.
Warfield SK, Zou KH, Wells WM. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation. IEEE Trans Med Imaging. 2004;23:903-21.
Lakhani DA, Schilling KG, Xu J, et al. Advanced multicompartment diffusion MRI models and their application in multiple sclerosis. AJNR Am J Neuroradiol. 2020;41:751-7.
Kutzelnigg A, Lassmann H. Pathology of multiple sclerosis and related inflammatory demyelinating diseases. In: Goodin DS, ed. Handbook of clinical neurology. Vol. 122. Elsevier; 2014;15-58.
Trapp BD, Peterson J, Ransohoff RM, et al. Axonal transection in the lesions of multiple sclerosis. N Engl J Med. 1998;338:278-85.
Commowick O, Fillard P, Clatz O, et al. Detection of DTI white matter abnormalities in multiple sclerosis patients. Med Image Comput Comput Assist Interv. 2008;11:975-82.
Sbardella E, Tona F, Petsas N, et al. DTI measurements in multiple sclerosis: evaluation of brain damage and clinical implications. Mult Scler Int. 2013;2013:671730.
Wang Y, Sun P, Wang Q, et al. Differentiation and quantification of inflammation, demyelination and axon injury or loss in multiple sclerosis. Brain. 2015;138:1223-38.
Schmierer K, Wheeler-Kingshott CAM, Boulby PA, et al. Diffusion tensor imaging of post mortem multiple sclerosis brain. Neuroimage. 2007;35:467-77.
Vishwas MS, Chitnis T, Pienaar R, et al. Tract-based analysis of callosal, projection, and association pathways in pediatric patients with multiple sclerosis: a preliminary study. AJNR Am J Neuroradiol. 2010;31:121-8.
Aliotta R, Cox JL, Donohue K, et al. Tract-based spatial statistics analysis of diffusion-tensor imaging data in pediatric- and adult-onset multiple sclerosis. Hum Brain Mapp. 2014;35:53-60.
Tortorella P, Rocca MA, Mezzapesa DM, et al. MRI quantification of gray and white matter damage in patients with early-onset multiple sclerosis. J Neurol. 2006;253:903-7.
Huang SY, Fan Q, Machado N, et al. Corpus callosum axon diameter relates to cognitive impairment in multiple sclerosis. Ann Clin Transl Neurol. 2019;6:882-92.
Miller DH, Barkhof F, Frank JA, et al. Measurement of atrophy in multiple sclerosis: pathological basis, methodological aspects and clinical relevance. Brain. 2002;125:1676-95.
Lassmann H. Pathology and disease mechanisms in different stages of multiple sclerosis. J Neurol Sci. 2013;333:1-4.
Grussu F, Schneider T, Tur C, et al. Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology? Ann Clin Transl Neurol. 2017;4:663-79.

Auteurs

Fedel Machado-Rivas (F)

Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Camilo Jaimes (C)

Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Benoit Scherrer (B)

Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Leslie A Benson (LA)

Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Mark P Gorman (MP)

Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Simon K Warfield (SK)

Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Onur Afacan (O)

Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH