Determination of brain iron content in patients with Parkinson's disease using magnetic susceptibility imaging.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhang W
PROVIDER: S-EPMC5552500 | biostudies-other | 2009 Dec
REPOSITORIES: biostudies-other
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Project description:Abnormal accumulation of iron is observed in neurodegenerative disorders. In Parkinson's disease, an excess of iron has been demonstrated in different structures of the basal ganglia and is suggested to be involved in the pathogenesis of the disease. Using the 6-hydroxydopamine (6-OHDA) rat model of Parkinson's disease, the edematous effect of 6-OHDA and its relation with striatal iron accumulation was examined utilizing in vivo magnetic resonance imaging (MRI). The results revealed that in comparison with control animals, injection of 6-OHDA into the rat striatum provoked an edematous process, visible in T2-weighted images that was accompanied by an accumulation of iron clearly detectable in T2*-weighted images. Furthermore, Prussian blue staining to detect iron in sectioned brains confirmed the existence of accumulated iron in the areas of T2* hypointensities. The presence of ED1-positive microglia in the lesioned striatum overlapped with this accumulation of iron, indicating areas of toxicity and loss of dopamine nerve fibers. Correlation analyses demonstrated a direct relation between the hyperintensities caused by the edema and the hypointensities caused by the accumulation of iron.
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Project description:This study tested the hypothesis that diffusion tensor imaging can detect alteration in microscopic integrity of white matter and basal ganglia regions known to be involved in Parkinson's disease (PD) pathology. It was also hypothesized that there is an association between diffusion abnormality and PD severity and subtype. Diffusion tensor imaging at 4 Tesla was obtained in 12 PD and 20 control subjects, and measures of fractional anisotropy and mean diffusivity were evaluated using both region-of-interest and voxel-based methods. Movement deficits and subtypes in PD subjects were assessed using the Motor Subscale (Part III) of the Unified Parkinson's Disease Rating Scale. Reduced fractional anisotropy (P < .05, corrected) was found in PD subjects in regions related to the precentral gyrus, substantia nigra, putamen, posterior striatum, frontal lobe, and the supplementary motor areas. Reduced fractional anisotropy in the substantia nigra correlated (P < .05, corrected) with the increased rating scale motor scores. Significant spatial correlations between fractional anisotropy alterations in the putamen and other PD-affected regions were also found in the context of PD subtypes index analysis. Our data suggest that microstructural alterations detected with diffusion tensor might serve as a potential biomarker for PD.
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Project description:Background: Parkinson's disease (PD) is a neurodegenerative disease in which the neostriatum, including the caudate nucleus (CN) and putamen (PU), has an important role in the pathophysiology. However, conventional magnetic resonance imaging (MRI) lacks sufficient specificity to diagnose PD. Therefore, the study's aim was to investigate the feasibility of using a radiomics approach to distinguish PD patients from healthy controls on T2-weighted images of the neostriatum and provide a basis for the clinical diagnosis of PD. Methods: T2-weighted images from 69 PD patients and 69 age- and sex-matched healthy controls were obtained on the same 3.0T MRI scanner. Regions of interest (ROIs) were manually placed at the CN and PU on the slices showing the largest respective sizes of the CN and PU. We extracted 274 texture features from each ROI and then used the least absolute shrinkage and selection operator regression to perform feature selection and radiomics signature building to identify the CN and PU radiomics signatures consisting of optimal features. We used a receiver operating characteristic curve analysis to assess the diagnostic performance of two radiomics signatures in a training group and estimate the generalization performance in the test group. Results: There were no significant differences in the demographic and clinical characteristics between the PD patients and healthy controls. The CN and PU radiomics signatures were built using 12 and 7 optimal features, respectively. The performance of the two radiomics signatures to distinguish PD patients from healthy controls was good. In the training and test groups, the AUCs of the CN radiomics signatures were 0.9410 (95% confidence interval [CI]: 0.8986-0.9833) and 0.7732 (95% CI: 0.6292-0.9173), respectively, and the AUCs of the PU radiomics signature were 0.8767 (95% CI: 0.8066-0.9469) and 0.7143 (95% CI: 0.5540-0.8746), respectively. Vertl_GlevNonU_R appeared simultaneously in both the CN and PU radiomics signatures as an optimal feature. A t-test analysis revealed significantly higher levels of texture values of the CN and PU in the PD patients than healthy controls (P < 0.05). Conclusion: Neostriatum radiomics signatures achieved good diagnostic performance for PD and potentially could serve as a basis for the clinical diagnosis of PD.
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Project description:BackgroundThe pathology of Parkinson's disease leads to morphological changes in brain structure. Currently, the progressive changes in gray matter volume that occur with time and are specific to patients with Parkinson's disease, compared to healthy controls, remain unclear. High-tesla magnetic resonance imaging might be useful in differentiating neurological disorders by brain cortical changes.PurposeWe aimed to investigate patterns in gray matter changes in patients with Parkinson's disease by using an automated segmentation method with 7-tesla magnetic resonance imaging.Material and methodsHigh-resolution T1-weighted 7 tesla magnetic resonance imaging volumes of 24 hemispheres were acquired from 12 Parkinson's disease patients and 12 age- and sex-matched healthy controls with median ages of 64.5 (range, 41-82) years and 60.5 (range, 25-74) years, respectively. Subgroup analysis was performed according to whether axial motor symptoms were present in the Parkinson's disease patients. Cortical volume, cortical thickness, and subcortical volume were measured using a high-resolution image processing technique based on the Desikan-Killiany-Tourville atlas and an automated segmentation method (FreeSurfer version 6.0).ResultsAfter cortical reconstruction, in 7 tesla magnetic resonance imaging volume segmental analysis, compared with the healthy controls, the Parkinson's disease patients showed global cortical atrophy, mostly in the prefrontal area (rostral middle frontal, superior frontal, inferior parietal lobule, medial orbitofrontal, rostral anterior cingulate area), and subcortical volume atrophy in limbic/paralimbic areas (fusiform, hippocampus, amygdala).ConclusionWe first demonstrated that 7 tesla magnetic resonance imaging detects structural abnormalities in Parkinson's disease patients compared to healthy controls using an automated segmentation method. Compared with the healthy controls, the Parkinson's disease patients showed global prefrontal cortical atrophy and hippocampal area atrophy.
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