scholarly journals Correlation of dystonia severity and iron accumulation in Rett syndrome

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tz-Yun Jan ◽  
Lee-Chin Wong ◽  
Ming-Tao Yang ◽  
Chien-Feng Judith Huang ◽  
Chia-Jui Hsu ◽  
...  

AbstractIndividuals with Rett syndrome (RTT) commonly demonstrate Parkinsonian features and dystonia at teen age; however, the pathological reason remains unclear. Abnormal iron accumulation in deep gray matter were reported in some Parkinsonian-related disorders. In this study, we investigated the iron accumulation in deep gray matter of RTT and its correlation with dystonia severity. We recruited 18 RTT-diagnosed participants with MECP2 mutations, from age 4 to 28, and 28 age-gender matched controls and investigated the iron accumulation by susceptibility weighted image (SWI) in substantia nigra (SN), globus pallidus (GP), putamen, caudate nucleus, and thalamus. Pearson’s correlation was applied for the relation between iron accumulation and dystonia severity. In RTT, the severity of dystonia scales showed significant increase in subjects older than 10 years, and the contrast ratios of SWI also showed significant differences in putamen, caudate nucleus and the average values of SN, putamen, and GP between RTT and controls. The age demonstrated moderate to high negative correlations with contrast ratios. The dystonia scales were correlated with the average contrast ratio of SN, putamen and GP, indicating iron accumulation in dopaminergic system and related grey matter. As the first SWI study for RTT individuals, we found increased iron deposition in dopaminergic system and related grey matter, which may partly explain the gradually increased dystonia.

2017 ◽  
Vol 46 (5) ◽  
pp. 1464-1473 ◽  
Author(s):  
Ahmed M. Elkady ◽  
Dana Cobzas ◽  
Hongfu Sun ◽  
Gregg Blevins ◽  
Alan H. Wilman

2021 ◽  
Author(s):  
Peter Raab ◽  
Stefan Ropele ◽  
Eva Bültmann ◽  
Rolf Salcher ◽  
Heinrich Lanfermann ◽  
...  

Abstract Purpose Aging is the most significant determinant for brain iron accumulation in the deep grey matter. Data on brain iron evolution during brain maturation in early childhood are limited. The purpose of this study was to investigate age-related iron deposition in the deep grey matter in children using quantitative susceptibility (QSM) and R2* mapping. Methods We evaluated brain MRI scans of 74 children (age 6–154 months, mean 40 months). A multi-echo gradient-echo sequence obtained at 3 Tesla was used for the QSM and R2* calculation. Susceptibility of the pallidum, head of caudate nucleus, and putamen was correlated with age and compared between sexes. Results Susceptibility changes in all three nuclei correlated with age (correlation coefficients for QSM/R2*: globus pallidus 0.955/0.882, caudate nucleus 0.76/0.65, and putamen 0.643/0.611). During the first 2 years, the R2* values increased more rapidly than the QSM values, indicating a combined effect of iron deposition and myelination, followed by a likely dominating effect of iron deposition. There was no significant gender difference. Conclusion QSM and R2* can monitor myelin maturation processes and iron accumulation in the deep grey nuclei of the brain in early life and may be a promising tool for the detection of deviations of this normal process. Susceptibility in the deep nuclei is almost similar early after birth and increases more quickly in the pallidum. The combined use of QSM and R2* analysis is beneficial.


Stroke ◽  
2020 ◽  
Vol 51 (6) ◽  
pp. 1750-1757 ◽  
Author(s):  
Chengyue Sun ◽  
Yue Wu ◽  
Chen Ling ◽  
Zhiying Xie ◽  
Qingle Kong ◽  
...  

Background and Purpose— Distribution patterns of iron deposition in deep gray matter and their association with clinical characteristics in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) remain unclear. We aimed to evaluate iron deposition in deep gray matter in patients with CADASIL using 7.0-T susceptibility-weighted imaging and mapping and to explore its correlations with clinical characteristics. Methods— Thirty-nine patients with CADASIL, confirmed via genetic analysis or skin biopsy, were enrolled. We examined patients using the Mini-Mental State Examination, modified Rankin Scale, and brain 7.0-T magnetic resonance imaging and obtained magnetic resonance imaging lesion loads, small vessel disease scores, and susceptibility mapping. The following regions of interest were selected: caudate nucleus, putamen, globus pallidus, thalamus, substantia nigra, and red nucleus. The quantitative differences in the susceptibility of deep gray matter between the CADASIL and control groups and the correlations between deep gray matter susceptibility and clinical characteristics were identified. Results— Compared with the control group, the CADASIL group showed significantly increased susceptibility of caudate nucleus, putamen, thalamus, substantia nigra, and red nucleus. The susceptibility of deep gray matter in basal ganglia region, including caudate nucleus, putamen, and thalamus, significantly increased with age or disease duration and positively correlated with small vessel disease scores in patients with CADASIL. Moreover, the susceptibility of thalamus positively correlated with modified Rankin Scale scores after adjusting for age and disease duration and that of putamen negatively correlated with Mini-Mental State Examination scores in patients with CADASIL after adjusting for age. Conclusions— Our findings indicate an association between abnormal iron deposition in deep gray matter of patients with CADASIL and their clinical characteristics. Therefore, excess iron deposition in deep gray matter, as indicated by 7.0-T susceptibility-weighted imaging and mapping, might not only be a novel magnetic resonance imaging feature but also a potential biomarker for CADASIL severity.


2020 ◽  
Author(s):  
Charlie C. Park ◽  
Dean W. Thongkham ◽  
Gelareh Sadigh ◽  
Amit M. Saindane ◽  
Renxin Chu ◽  
...  

NeuroImage ◽  
2017 ◽  
Vol 148 ◽  
pp. 115-122 ◽  
Author(s):  
Michal Juhás ◽  
Hongfu Sun ◽  
Matthew R.G. Brown ◽  
Marnie B. MacKay ◽  
Karl F. Mann ◽  
...  

NeuroImage ◽  
2006 ◽  
Vol 29 (2) ◽  
pp. 505-514 ◽  
Author(s):  
D.A. Carone ◽  
R.H.B. Benedict ◽  
M.G. Dwyer ◽  
D.L. Cookfair ◽  
B. Srinivasaraghavan ◽  
...  

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