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Updated: Aug 1, 2025
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Structural MRI Ratios Fail to Distinguish Progressive Supranuclear Palsy From Parkinson Disease in Individual
Chadrick Dewey1, Fabricio Feltrin1, Bhavya Shah1
1Department of Neurology (CD, SL, SC, RD), Department of Radiology (FF, BS, MP, JD, MA), Division of Neuroradiology, and Perot Foundation Neuroscience Translational Research Center (MM), O'Donnell Brain Institute, University of Texas Southwestern Medical Center.
Background And Objectives:
Parkinson disease (PD) and progressive supranuclear palsy (PSP) are often difficult to differentiate in the clinic. The MR parkinsonism index (MRPI) has been recommended to assist in making this distinction. We aimed to assess the usefulness of this tool in our real-world practice of movement disorders.
Methods:
We prospectively obtained MRI scans on consecutive patients with movement disorders with a clinical indication for imaging and obtained measures of MRI regions of interest (ROIs) from our neuroradiologists. The authors reviewed all MRI scans and corrected any errors in the original ROI drawings for this analysis. We retrospectively assigned diagnoses using established consensus criteria from progress notes stored in our electronic medical record. We analyzed the data using multinomial logistic regression models and receiver operating curve analysis to determine the predictive accuracy of the MRI ratios.
Results:
MRI measures and consensus diagnoses were available on 130 patients with PD, 54 with PSP, and 77 diagnosed as other. The out-of-sample prediction error rate of our 5 regression models ranged from 45% to 59%. The average sensitivity and specificity of the 5 models in the testing sample were 53% and 80%, respectively. The positive predictive value of an MRPI ≥13.55 (the published cutoff) in our patients was 79%.
Discussion:
These results indicate that MRI measures of brain structures were not effective at predicting diagnosis in individual patients. We conclude that the search for a biomarker that can differentiate PSP from PD must continue.
Insights
The MR parkinsonism index (MRPI) using MRI brain scans showed limited accuracy in distinguishing Parkinson disease (PD) from progressive supranuclear palsy (PSP) in a real-world setting. Further research is needed to find reliable biomarkers for differentiating these movement disorders.
Area of Science:
- Neurology
- Radiology
- Biomarker Discovery
Background:
- Parkinson disease (PD) and progressive supranuclear palsy (PSP) present similar symptoms, complicating clinical diagnosis.
- The MR parkinsonism index (MRPI) is a proposed imaging biomarker to aid in differentiating PD from PSP.
Purpose of the Study:
- To evaluate the real-world effectiveness of the MR parkinsonism index (MRPI) in distinguishing between PD and PSP.
Main Methods:
- Prospective MRI acquisition and retrospective diagnosis assignment based on consensus criteria.
- Analysis of MRI regions of interest (ROIs) using multinomial logistic regression and receiver operating curve analysis.
Main Results:
- The study included 130 PD, 54 PSP, and 77 other movement disorder patients.
- Out-of-sample prediction error rates for diagnostic models ranged from 45% to 59%.
- The MRPI showed an average sensitivity of 53% and specificity of 80% in differentiating PD and PSP.
Conclusions:
- MRI measures, including the MRPI, were not sufficiently accurate for predicting individual diagnoses of PD or PSP.
- The development of novel biomarkers is essential for accurate differentiation between these neurodegenerative conditions.
Related Concept Videos
01:15Parkinson's Disease: Overview
01:37Neural Regulation
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