Non-invasive quantification of inflammation, axonal and myelin injury in multiple sclerosis

The aim of this study was to determine the feasibility of diffusion basis spectrum imaging in multiple sclerosis at 7 T and to investigate the pathological substrates of tissue damage in lesions and normal-appearing white matter. To this end, 43 patients with multiple sclerosis (24 relapsing-remitti...

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Published in:	Brain (London, England : 1878) Vol. 144; no. 1; p. 213
Main Authors:	Schiavi, Simona, Petracca, Maria, Sun, Peng, Fleysher, Lazar, Cocozza, Sirio, El Mendili, Mohamed Mounir, Signori, Alessio, Babb, James S, Podranski, Kornelius, Song, Sheng-Kwei, Inglese, Matilde
Format:	Journal Article
Language:	English
Published:	England 12.02.2021
Subjects:	Adult Axons - pathology Diffusion Magnetic Resonance Imaging - methods Encephalitis - complications Encephalitis - diagnostic imaging Encephalitis - pathology Female Humans Male Middle Aged Multiple Sclerosis - complications Multiple Sclerosis - diagnostic imaging Myelin Sheath - pathology White Matter - diagnostic imaging White Matter - pathology axonal injury inflammation multiple sclerosis diffusion basis spectrum imaging
ISSN:	1460-2156, 1460-2156
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Abstract	The aim of this study was to determine the feasibility of diffusion basis spectrum imaging in multiple sclerosis at 7 T and to investigate the pathological substrates of tissue damage in lesions and normal-appearing white matter. To this end, 43 patients with multiple sclerosis (24 relapsing-remitting, 19 progressive), and 21 healthy control subjects were enrolled. White matter lesions were classified in T1-isointense, T1-hypointense and black holes. Mean values of diffusion basis spectrum imaging metrics (fibres, restricted and non-restricted fractions, axial and radial diffusivities and fractional anisotropy) were measured from whole brain white matter lesions and from both lesions and normal appearing white matter of the corpus callosum. Significant differences were found between T1-isointense and black holes (P ranging from 0.005 to <0.001) and between lesions' centre and rim (P < 0.001) for all the metrics. When comparing the three subject groups in terms of metrics derived from corpus callosum normal appearing white matter and T2-hyperintense lesions, a significant difference was found between healthy controls and relapsing-remitting patients for all metrics except restricted fraction and fractional anisotropy; between healthy controls and progressive patients for all metrics except restricted fraction and between relapsing-remitting and progressive multiple sclerosis patients for all metrics except fibres and restricted fractions (P ranging from 0.05 to <0.001 for all). Significant associations were found between corpus callosum normal-appearing white matter fibres fraction/non-restricted fraction and the Symbol Digit Modality Test (respectively, r = 0.35, P = 0.043; r = -0.35, P = 0.046), and between black holes radial diffusivity and Expanded Disability Status Score (r = 0.59, P = 0.002). We showed the feasibility of diffusion basis spectrum imaging metrics at 7 T, confirmed the role of the derived metrics in the characterization of lesions and normal appearing white matter tissue in different stages of the disease and demonstrated their clinical relevance. Thus, suggesting that diffusion basis spectrum imaging is a promising tool to investigate multiple sclerosis pathophysiology, monitor disease progression and treatment response.
AbstractList	The aim of this study was to determine the feasibility of diffusion basis spectrum imaging in multiple sclerosis at 7 T and to investigate the pathological substrates of tissue damage in lesions and normal-appearing white matter. To this end, 43 patients with multiple sclerosis (24 relapsing-remitting, 19 progressive), and 21 healthy control subjects were enrolled. White matter lesions were classified in T1-isointense, T1-hypointense and black holes. Mean values of diffusion basis spectrum imaging metrics (fibres, restricted and non-restricted fractions, axial and radial diffusivities and fractional anisotropy) were measured from whole brain white matter lesions and from both lesions and normal appearing white matter of the corpus callosum. Significant differences were found between T1-isointense and black holes (P ranging from 0.005 to <0.001) and between lesions' centre and rim (P < 0.001) for all the metrics. When comparing the three subject groups in terms of metrics derived from corpus callosum normal appearing white matter and T2-hyperintense lesions, a significant difference was found between healthy controls and relapsing-remitting patients for all metrics except restricted fraction and fractional anisotropy; between healthy controls and progressive patients for all metrics except restricted fraction and between relapsing-remitting and progressive multiple sclerosis patients for all metrics except fibres and restricted fractions (P ranging from 0.05 to <0.001 for all). Significant associations were found between corpus callosum normal-appearing white matter fibres fraction/non-restricted fraction and the Symbol Digit Modality Test (respectively, r = 0.35, P = 0.043; r = -0.35, P = 0.046), and between black holes radial diffusivity and Expanded Disability Status Score (r = 0.59, P = 0.002). We showed the feasibility of diffusion basis spectrum imaging metrics at 7 T, confirmed the role of the derived metrics in the characterization of lesions and normal appearing white matter tissue in different stages of the disease and demonstrated their clinical relevance. Thus, suggesting that diffusion basis spectrum imaging is a promising tool to investigate multiple sclerosis pathophysiology, monitor disease progression and treatment response. The aim of this study was to determine the feasibility of diffusion basis spectrum imaging in multiple sclerosis at 7 T and to investigate the pathological substrates of tissue damage in lesions and normal-appearing white matter. To this end, 43 patients with multiple sclerosis (24 relapsing-remitting, 19 progressive), and 21 healthy control subjects were enrolled. White matter lesions were classified in T1-isointense, T1-hypointense and black holes. Mean values of diffusion basis spectrum imaging metrics (fibres, restricted and non-restricted fractions, axial and radial diffusivities and fractional anisotropy) were measured from whole brain white matter lesions and from both lesions and normal appearing white matter of the corpus callosum. Significant differences were found between T1-isointense and black holes (P ranging from 0.005 to <0.001) and between lesions' centre and rim (P < 0.001) for all the metrics. When comparing the three subject groups in terms of metrics derived from corpus callosum normal appearing white matter and T2-hyperintense lesions, a significant difference was found between healthy controls and relapsing-remitting patients for all metrics except restricted fraction and fractional anisotropy; between healthy controls and progressive patients for all metrics except restricted fraction and between relapsing-remitting and progressive multiple sclerosis patients for all metrics except fibres and restricted fractions (P ranging from 0.05 to <0.001 for all). Significant associations were found between corpus callosum normal-appearing white matter fibres fraction/non-restricted fraction and the Symbol Digit Modality Test (respectively, r = 0.35, P = 0.043; r = -0.35, P = 0.046), and between black holes radial diffusivity and Expanded Disability Status Score (r = 0.59, P = 0.002). We showed the feasibility of diffusion basis spectrum imaging metrics at 7 T, confirmed the role of the derived metrics in the characterization of lesions and normal appearing white matter tissue in different stages of the disease and demonstrated their clinical relevance. Thus, suggesting that diffusion basis spectrum imaging is a promising tool to investigate multiple sclerosis pathophysiology, monitor disease progression and treatment response.The aim of this study was to determine the feasibility of diffusion basis spectrum imaging in multiple sclerosis at 7 T and to investigate the pathological substrates of tissue damage in lesions and normal-appearing white matter. To this end, 43 patients with multiple sclerosis (24 relapsing-remitting, 19 progressive), and 21 healthy control subjects were enrolled. White matter lesions were classified in T1-isointense, T1-hypointense and black holes. Mean values of diffusion basis spectrum imaging metrics (fibres, restricted and non-restricted fractions, axial and radial diffusivities and fractional anisotropy) were measured from whole brain white matter lesions and from both lesions and normal appearing white matter of the corpus callosum. Significant differences were found between T1-isointense and black holes (P ranging from 0.005 to <0.001) and between lesions' centre and rim (P < 0.001) for all the metrics. When comparing the three subject groups in terms of metrics derived from corpus callosum normal appearing white matter and T2-hyperintense lesions, a significant difference was found between healthy controls and relapsing-remitting patients for all metrics except restricted fraction and fractional anisotropy; between healthy controls and progressive patients for all metrics except restricted fraction and between relapsing-remitting and progressive multiple sclerosis patients for all metrics except fibres and restricted fractions (P ranging from 0.05 to <0.001 for all). Significant associations were found between corpus callosum normal-appearing white matter fibres fraction/non-restricted fraction and the Symbol Digit Modality Test (respectively, r = 0.35, P = 0.043; r = -0.35, P = 0.046), and between black holes radial diffusivity and Expanded Disability Status Score (r = 0.59, P = 0.002). We showed the feasibility of diffusion basis spectrum imaging metrics at 7 T, confirmed the role of the derived metrics in the characterization of lesions and normal appearing white matter tissue in different stages of the disease and demonstrated their clinical relevance. Thus, suggesting that diffusion basis spectrum imaging is a promising tool to investigate multiple sclerosis pathophysiology, monitor disease progression and treatment response.
Author	Cocozza, Sirio Inglese, Matilde Petracca, Maria El Mendili, Mohamed Mounir Babb, James S Schiavi, Simona Podranski, Kornelius Sun, Peng Fleysher, Lazar Signori, Alessio Song, Sheng-Kwei
Author_xml	– sequence: 1 givenname: Simona surname: Schiavi fullname: Schiavi, Simona organization: Ospedale Policlinico San Martino-IRCCS, Genoa, Italy – sequence: 2 givenname: Maria surname: Petracca fullname: Petracca, Maria organization: Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA – sequence: 3 givenname: Peng surname: Sun fullname: Sun, Peng organization: Radiology, Washington University School of Medicine, St. Louis, MO, USA – sequence: 4 givenname: Lazar surname: Fleysher fullname: Fleysher, Lazar organization: Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA – sequence: 5 givenname: Sirio surname: Cocozza fullname: Cocozza, Sirio organization: Department of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy – sequence: 6 givenname: Mohamed Mounir surname: El Mendili fullname: El Mendili, Mohamed Mounir organization: Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA – sequence: 7 givenname: Alessio surname: Signori fullname: Signori, Alessio organization: Department of Health Sciences, University of Genoa, Genoa, Italy – sequence: 8 givenname: James S surname: Babb fullname: Babb, James S organization: Department of Radiology, Center for Biomedical Imaging, New York University, Langone Medical Center, New York, USA – sequence: 9 givenname: Kornelius surname: Podranski fullname: Podranski, Kornelius organization: Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA – sequence: 10 givenname: Sheng-Kwei surname: Song fullname: Song, Sheng-Kwei organization: Biomedical MR Laboratory, Washington University School of Medicine, St. Louis, MO, USA – sequence: 11 givenname: Matilde surname: Inglese fullname: Inglese, Matilde organization: Ospedale Policlinico San Martino-IRCCS, Genoa, Italy
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/33253366$$D View this record in MEDLINE/PubMed
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SubjectTerms	Adult Axons - pathology Diffusion Magnetic Resonance Imaging - methods Encephalitis - complications Encephalitis - diagnostic imaging Encephalitis - pathology Female Humans Male Middle Aged Multiple Sclerosis - complications Multiple Sclerosis - diagnostic imaging Myelin Sheath - pathology White Matter - diagnostic imaging White Matter - pathology
Title	Non-invasive quantification of inflammation, axonal and myelin injury in multiple sclerosis
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