scholarly journals Combining Diffusion Tensor Imaging and Susceptibility Weighted Imaging on the Substantia Nigra of 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine (MPTP)-induced Rhesus Monkey Model of Parkinson’s Disease

Author(s):  
Q Zhang ◽  
L Li ◽  
B Miao ◽  
H Niu
2016 ◽  
Vol 37 (7) ◽  
pp. 2547-2556 ◽  
Author(s):  
Jason Langley ◽  
Daniel E. Huddleston ◽  
Michael Merritt ◽  
Xiangchuan Chen ◽  
Rebecca McMurray ◽  
...  

2021 ◽  
Vol 11 (11) ◽  
pp. 1235
Author(s):  
Niels Bergsland ◽  
Laura Pelizzari ◽  
Maria Marcella Laganá ◽  
Sonia Di Tella ◽  
Federica Rossetto ◽  
...  

The substantia nigra (SN) pars compacta (SNpc) and pars reticulata (SNpr) are differentially affected in Parkinson’s disease (PD). Separating the SNpc and SNpr is challenging with standard magnetic resonance imaging (MRI). Diffusion tensor imaging (DTI) allows for the characterization of SN microstructure in a non-invasive manner. In this study, 29 PD patients and 28 healthy controls (HCs) were imaged with 1.5T MRI for DTI. Images were nonlinearly registered to standard space and SNpc and SNpr DTI parameters were measured. ANCOVA and receiver operator characteristic (ROC) analyses were performed. Clinical associations were assessed with Spearman correlations. Multiple corrections were controlled for false discovery rate. PD patients presented with significantly increased SNpc axial diffusivity (AD) (1.207 ± 0.068 versus 1.156 ± 0.045, p = 0.024), with ROC analysis yielding an under the curve of 0.736. Trends with Unified Parkinson’s Disease Rating Scale (UPDRS) III scores were identified for SNpc MD (rs = 0.449), AD (rs = 0.388), and radial diffusivity (rs = 0.391) (all p < 0.1). A trend between baseline SNpr MD and H&Y change (rs = 0.563, p = 0.081) over 2.9 years of follow-up was identified (n = 14). In conclusion, SN microstructure shows robust, clinically meaningful associations in PD.


2011 ◽  
Vol 26 (9) ◽  
pp. 1627-1632 ◽  
Author(s):  
Guangwei Du ◽  
Mechelle M. Lewis ◽  
Martin Styner ◽  
Michele L. Shaffer ◽  
Suman Sen ◽  
...  

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