Investigation of grey matter abnormalities in multiple sclerosis patients by combined use of double inversion recovery sequences and diffusion tensor MRI at 3.0 Tesla

Han, Xuemei; Wang, X.; Wang, L.; Zheng, Zhao; Gu, Jingjing; Tang, Dejun; Liu, L.; Liu, S.

doi:10.1016/j.crad.2018.04.016

Cited by 3 publications

(4 citation statements)

References 28 publications

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“…Diffusion occurs with greater ease along tracts (parallel to axons) and less so when perpendicular to microstructural barriers (e.g., cell walls, extracellular sheets). Abnormalities in diffusion are often found in lesions and normal-appearing WM (NAWM) in pwMS [ 66 , 67 ]. Diffusion abnormalities in the middle and superior cerebellar peduncles correlate with T2 lesion load in these regions, as well as with whole-brain T2 lesion load and cerebellar GM volume [ 62 ].…”

Section: Neuroimaging Measures Of Cerebellar Dysfunctionmentioning

confidence: 99%

“…The residual signal fraction, a measure of the volume fraction of axons, was also able to distinguish between NAWM and lesions in pwMS [ 66 ]. Additionally, normal-appearing GM (NAGM) in pwMS has microstructural damage, the extent of which correlates with the number of lesions throughout the brain and with cognitive impairment [ 67 ]. NAGM mean diffusivity and fractional anisotropy also positively correlate with EDSS scores [ 67 ].…”

Section: Neuroimaging Measures Of Cerebellar Dysfunctionmentioning

confidence: 99%

“…Additionally, normal-appearing GM (NAGM) in pwMS has microstructural damage, the extent of which correlates with the number of lesions throughout the brain and with cognitive impairment [ 67 ]. NAGM mean diffusivity and fractional anisotropy also positively correlate with EDSS scores [ 67 ]. Diffusion imaging of the cerebellum can accurately group mean differences between pwMS and controls or between pwMS with and without clinical impairment measured by the EDSS, cerebellar, and brain stem FSS [ 62 ].…”

Section: Neuroimaging Measures Of Cerebellar Dysfunctionmentioning

confidence: 99%

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An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis

et al. 2022

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Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.

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Section: Neuroimaging Measures Of Cerebellar Dysfunctionmentioning

confidence: 99%

Section: Neuroimaging Measures Of Cerebellar Dysfunctionmentioning

confidence: 99%

Section: Neuroimaging Measures Of Cerebellar Dysfunctionmentioning

confidence: 99%

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An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis

et al. 2022

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“…On MRI scans, fractional anisotropy (FA) is found to be increased in the NAGM of MS, NAGM‒FA has a high correlation with the progression of physical disability in MS patients [ 13 ]. Furthermore, the NAGM exhibits microstructural damage, the severity of which is related to cognitive impairment and neurodegeneration in MS [ 12 , 14 ]. NAMG has gained attention in the field of MS research.…”

Section: Introductionmentioning

confidence: 99%

Identification of Y‒linked biomarkers and exploration of immune infiltration of normal-appearing gray matter in multiple sclerosis by bioinformatic analysis

Zhang,

Zhang

et al. 2024

Heliyon

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Increased cortical lesion load contributed to pathological changes beyond focal lesion in cortical gray matter of multiple sclerosis: a diffusion kurtosis imaging analysis

Zhu,

Yan,

Shi

et al. 2023

Cerebral Cortex

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Biomarkers specific to cortical gray matter (cGM) pathological changes of multiple sclerosis (MS) are desperately needed to better understand the disease progression. The cGM damage occurs in cortical lesion (CL) and normal-appearing cGM (NAcGM) areas. While the association between CL load and cGM damage has been reported, little is known about how different CL types, i.e. intracortical lesion (ICL) and leukocortical lesion (LCL) would be associated with cGM damage. In our study, relapsing–remitting MS patients and healthy controls were divided into 4 groups according to CL load level. NAcGM diffusion kurtosis imaging (DKI)/diffusion tensor imaging (DTI) values and cGM volume (cGMV) were used to characterize the pathological changes in cGM. Univariate general linear model was used for group comparisons and stepwise regression analysis was used to assess the effects of ICL volume and LCL volume on NAcGM damage. We found peak values in DKI/DTI values, cGMV and neuropsychological scores in high CL load group. Kurtosis fractional anisotropy (KFA) was the most sensitive in characterizing NAcGM damage, and LCL volume related more to NAcGM damage. Our findings suggested KFA could become a surrogate biomarker to cGM damage, and LCL might be the main factor in whole brain NAcGM damage.

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Investigation of grey matter abnormalities in multiple sclerosis patients by combined use of double inversion recovery sequences and diffusion tensor MRI at 3.0 Tesla

Cited by 3 publications

References 28 publications

An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis

An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis

Identification of Y‒linked biomarkers and exploration of immune infiltration of normal-appearing gray matter in multiple sclerosis by bioinformatic analysis

Increased cortical lesion load contributed to pathological changes beyond focal lesion in cortical gray matter of multiple sclerosis: a diffusion kurtosis imaging analysis

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