Magnetic resonance imaging‐guided focused ultrasound thalamotomy following contralateral radiofrequency thalamotomy for Parkinson’s disease: A case report

Abstract Background Although the thalamus is known to modulate basal ganglia function related to motor control activity, the abnormal changes within the thalamus during distinct medical complications have been scarcely investigated. In order to explore the feasibility of assessing iron accumulation in the thalamus as an informative biomarker for Parkinson’s disease (PD), this study was designed to employ quantitative susceptibility mapping using a 7 T magnetic resonance imaging system in cynomolgus monkeys. A 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-injected cynomolgus monkey and a healthy control (HC) were examined by 7 T magnetic resonance imaging. Positron emission tomography with 18F-N-(3-fluoro propyl)-2ß-carboxymethoxy-3ß-(4-iodophenyl) nortropane was also employed to identify the relationship between iron deposits and dopamine depletion. All acquired values were averaged within the volume of interest of the nigrostriatal pathway. Findings Compared with the HC, the overall elevation of iron deposition within the thalamus in the Parkinson’s disease model (about 53.81% increase) was similar to that in the substantia nigra (54.81%) region. Substantial susceptibility changes were observed in the intralaminar part of the thalamus (about 70.78% increase). Additionally, we observed that in the Parkinson’s disease model, binding potential values obtained from positron emission tomography were considerably decreased in the thalamus (97.51%) and substantia nigra (92.48%). Conclusions The increased iron deposition in the thalamus showed negative correlation with dopaminergic activity in PD, supporting the idea that iron accumulation affects glutaminergic inputs and dopaminergic neurons. This investigation indicates that the remarkable susceptibility changes in the thalamus could be an initial major diagnostic biomarker for Parkinson’s disease-related motor symptoms.

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Prefrontal and hippocampal atrophy using 7-tesla magnetic resonance imaging in patients with Parkinson’s disease

Acta Radiologica Open ◽

10.1177/2058460120988097 ◽

2021 ◽

Vol 10 (2) ◽

pp. 205846012098809

Author(s):

Byeong H Oh ◽

Hyeong C Moon ◽

Aryun Kim ◽

Hyeon J Kim ◽

Chae J Cheong ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Magnetic Resonance ◽

7 Tesla ◽

Cortical Atrophy ◽

Automated Segmentation ◽

Healthy Controls ◽

Segmentation Method ◽

Resonance Imaging

Background The 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. Purpose We 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 Methods High-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). Results After 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). Conclusion We 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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