Untangling the R2* contrast in multiple sclerosis: A combined MRI-histology study at 7.0 Tesla

Bagnato, Francesca; Hametner, Simon; Boyd, Emma; Endmayr, Verena; Shi, Yaping; Ikonomidou, Vasiliki N.; Chen, Guanhua; Pawate, Siddharama; Lassmann, Hans; Smith, Seth A.; Welch, E. Brian

doi:10.1371/journal.pone.0193839

Cited by 53 publications

(45 citation statements)

References 56 publications

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“…Therefore, a tight connection between iron and myelin content has to be assumed in WM. Myelin loss in MS is not only found in focally demyelinated lesions, but also extends to non‐lesional WM . Primarily, loss of myelin lipids rather than myelin proteins characterizes non‐lesional myelin loss, which occurs more diffusely than myelin loss within MS lesions .…”

Section: Discussionsupporting

confidence: 88%

“…Myelin loss in MS is not only found in focally demyelinated lesions, but also extends to non-lesional WM. 21,39,40 Primarily, loss of myelin lipids rather than myelin proteins characterizes non-lesional myelin loss, which occurs more diffusely than myelin loss within MS lesions. 41 Furthermore, a widespread decrease of iron in NAWM 23 and in focal lesions 42 has been shown to relate to disease duration.…”

Section: Discussionmentioning

confidence: 99%

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The role of iron and myelin in orientation dependent R₂^* of white matter

et al. 2019

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Brain myelin and iron content are important parameters in neurodegenerative diseases such as multiple sclerosis (MS). Both myelin and iron content influence the brain's R2* relaxation rate. However, their quantification based on R2* maps requires a realistic tissue model that can be fitted to the measured data. In structures with low myelin content, such as deep gray matter, R2* shows a linear increase with increasing iron content. In white matter, R2* is not only affected by iron and myelin but also by the orientation of the myelinated axons with respect to the external magnetic field. Here, we propose a numerical model which incorporates iron and myelin, as well as fibre orientation, to simulate R2* decay in white matter. Applying our model to fibre orientation‐dependent in vivo R2* data, we are able to determine a unique solution of myelin and iron content in global white matter. We determine an averaged myelin volume fraction of 16.02 ± 2.07% in non‐lesional white matter of patients with MS, 17.32 ± 2.20% in matched healthy controls, and 18.19 ± 2.98% in healthy siblings of patients with MS. Averaged iron content was 35.6 ± 8.9 mg/kg tissue in patients, 43.1 ± 8.3 mg/kg in controls, and 47.8 ± 8.2 mg/kg in siblings. All differences in iron content between groups were significant, while the difference in myelin content between MS patients and the siblings of MS patients was significant. In conclusion, we demonstrate that a model that combines myelin‐induced orientation‐dependent and iron‐induced orientation‐independent components is able to fit in vivo R2* data.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 99%

The role of iron and myelin in orientation dependent R₂^* of white matter

et al. 2019

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“…Effective transverse relaxation rate R2* is primarily affected by iron, local myelin content, fiber orientation, and water content (Bagnato et al 2018; Cohen-Adad 2014). R2* is decreased in MS NACGM and NAWM, suggesting a reduction in iron or myelin content, in keeping with histopathological (Hametner et al 2013) and MR evidence (Bagnato et al 2018; Hernández-torres et al 2015; Neema et al 2007; Paling et al 2012; Reitz et al 2016). In contrast to previous reports (Elkady et al 2017; Khalil et al, 2009, Khalil et al, 2011; Ropele et al 2014) , we did not observe any significant increase in R2* parameter in NADGM in MS patients.…”

Section: Discussionmentioning

confidence: 99%

Multiparameter MRI quantification of microstructural tissue alterations in multiple sclerosis

Lommers

Simon

Reuter

et al. 2019

NeuroImage: Clinical

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Objectives Conventional MRI is not sensitive to many pathological processes underpinning multiple sclerosis (MS) ongoing in normal appearing brain tissue (NABT). Quantitative MRI (qMRI) and a multiparameter mapping (MPM) protocol are used to simultaneously quantify magnetization transfer (MT) saturation, transverse relaxation rate R2* (1/T2*) and longitudinal relaxation rate R1 (1/T1), and assess differences in NABT microstructure between MS patients and healthy controls (HC). Methods This prospective cross-sectional study involves 36 MS patients (21 females, 15 males; age range 22–63 years; 15 relapsing-remitting MS - RRMS; 21 primary or secondary progressive MS - PMS) and 36 age-matched HC (20 females, 16 males); age range 21–61 years). The qMRI maps are computed and segmented in lesions and 3 normal appearing cerebral tissue classes: normal appearing cortical grey matter (NACGM), normal appearing deep grey matter (NADGM), normal appearing white matter (NAWM). Individual median values are extracted for each tissue class and MR parameter. MANOVAs and stepwise regressions assess differences between patients and HC. Results MS patients are characterized by a decrease in MT, R2* and R1 within NACGM ( p < .0001) and NAWM ( p < .0001). In NADGM, MT decreases ( p < .0001) but R2* and R1 remain normal. These observations tend to be more pronounced in PMS. Quantitative MRI parameters are independent predictors of clinical status: EDSS is significantly related to R1 in NACGM and R2* in NADGM; the latter also predicts motor score. Cognitive score is best predicted by MT parameter within lesions. Conclusions Multiparametric data of brain microstructure concord with the literature, predict clinical performance and suggest a diffuse reduction in myelin and/or iron content within NABT of MS patients.

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“…NAWM was defined as any area displaying normal signal on T2‐w TSE and FLAIR images. Care was taken to avoid areas of dirty WM and those in the vicinity of a lesion. T2‐lesions were defined as any area of hyperintense signal on T2‐w TSE and FLAIR images that did not have a corresponding hypo‐intense signal on T1‐w TSE MRI.…”

Section: Methodsmentioning

confidence: 99%

Probing axons using multi‐compartmental diffusion in multiple sclerosis

Bagnato

Franco

et al. 2019

Ann Clin Transl Neurol

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Objects The diffusion‐based spherical mean technique (SMT) provides a novel model to relate multi‐b‐value diffusion magnetic resonance imaging (MRI) data to features of tissue microstructure. We propose the first clinical application of SMT to image the brain of patients with multiple sclerosis (MS) and investigate clinical feasibility and translation. Methods Eighteen MS patients and nine age‐ and sex‐matched healthy controls (HCs) underwent a 3.0 Tesla scan inclusive of clinical sequences and SMT images (isotropic resolution of 2 mm). Axial diffusivity (AD), apparent axonal volume fraction (Vax), and effective neural diffusivity (Dax) parametric maps were fitted. Differences in AD, Vax, and Dax between anatomically matched regions reflecting different tissues types were estimated using generalized linear mixed models for binary outcomes. Results Differences were seen in all SMT‐derived parameters between chronic black holes (cBHs) and T2‐lesions (P ≤ 0.0016), in Vax and AD between T2‐lesions and normal appearing white matter (NAWM) (P < 0.0001), but not between the NAWM and normal WM in HCs. Inverse correlations were seen between Vax and AD in cBHs (r = −0.750, P = 0.02); in T2‐lesions Dax values were associated with Vax (r = 0.824, P < 0.0001) and AD (r = 0.570, P = 0.014). Interpretations SMT‐derived metrics are sensitive to pathological changes and hold potential for clinical application in MS patients.

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Untangling the R2* contrast in multiple sclerosis: A combined MRI-histology study at 7.0 Tesla

Cited by 53 publications

References 56 publications

The role of iron and myelin in orientation dependent R₂^* of white matter

The role of iron and myelin in orientation dependent R₂^* of white matter

Multiparameter MRI quantification of microstructural tissue alterations in multiple sclerosis

Probing axons using multi‐compartmental diffusion in multiple sclerosis

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Untangling the R2* contrast in multiple sclerosis: A combined MRI-histology study at 7.0 Tesla

Cited by 53 publications

References 56 publications

The role of iron and myelin in orientation dependent R2* of white matter

The role of iron and myelin in orientation dependent R2* of white matter

Multiparameter MRI quantification of microstructural tissue alterations in multiple sclerosis

Probing axons using multi‐compartmental diffusion in multiple sclerosis

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The role of iron and myelin in orientation dependent R₂^* of white matter

The role of iron and myelin in orientation dependent R₂^* of white matter