Effect of aging on magnetic resonance measures differentiating progressive supranuclear palsy from Parkinson's disease

2014 ◽  
Vol 29 (4) ◽  
pp. 488-495 ◽  
Author(s):  
Maurizio Morelli ◽  
Gennarina Arabia ◽  
Demetrio Messina ◽  
Basilio Vescio ◽  
Maria Salsone ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Resonance ◽  
Progressive Supranuclear Palsy

Differentiation of Parkinson's disease and progressive supranuclear palsy with magnetic resonance imaging: The first Brazilian experience

2007 ◽  
Vol 13 (7) ◽  
pp. 389-393 ◽  
Author(s):  
Orlando G.P. Barsottini ◽  
Henrique B. Ferraz ◽  
Antonio C.M. Maia ◽  
Carlos J. Silva ◽  
Antonio J. Rocha
Keyword(s):  
Magnetic Resonance Imaging ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Resonance ◽  
Progressive Supranuclear Palsy ◽  
Resonance Imaging

scholarly journals Diagnostic Performance of the Magnetic Resonance Parkinsonism Index in Differentiating Progressive Supranuclear Palsy from Parkinson’s Disease: An Updated Systematic Review and Meta-Analysis

Diagnostics ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 12
Author(s):  
Seongken Kim ◽  
Chong Hyun Suh ◽  
Woo Hyun Shim ◽  
Sang Joon Kim
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Resonance ◽  
Progressive Supranuclear Palsy ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
Management Strategies ◽  
Area Under The Curve ◽  
Summary Receiver Operating Characteristic ◽  
Meta Regression

Progressive supranuclear palsy (PSP) and Parkinson’s disease (PD) are difficult to differentiate especially in the early stages. We aimed to investigate the diagnostic performance of the magnetic resonance parkinsonism index (MRPI) in differentiating PSP from PD. A systematic literature search of PubMed-MEDLINE and EMBASE was performed to identify original articles evaluating the diagnostic performance of the MRPI in differentiating PSP from PD published up to 20 February 2021. The pooled sensitivity, specificity, and 95% CI were calculated using the bivariate random-effects model. The area under the curve (AUC) was calculated using a hierarchical summary receiver operating characteristic (HSROC) model. Meta-regression was performed to explain the effects of heterogeneity. A total of 14 original articles involving 484 PSP patients and 1243 PD patients were included. In all studies, T1-weighted images were used to calculate the MRPI. Among the 14 studies, nine studies used 3D T1-weighted images. The pooled sensitivity and specificity for the diagnostic performance of the MRPI in differentiating PSP from PD were 96% (95% CI, 87–99%) and 98% (95% CI, 91–100%), respectively. The area under the HSROC curve was 0.99 (95% CI, 0.98–1.00). Heterogeneity was present (sensitivity: I2 = 97.29%; specificity: I2 = 98.82%). Meta-regression showed the association of the magnet field strength with heterogeneity. Studies using 3 T MRI showed significantly higher sensitivity (100%) and specificity (100%) than those of studies using 1.5 T MRI (sensitivity of 98% and specificity of 97%) (p < 0.01). Thus, the MRPI could accurately differentiate PSP from PD and support the implementation of appropriate management strategies for patients with PSP.

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