J Mov Disord.
2022 Sep;15(3):232-240. 10.14802/jmd.21178.
Semiautomated Algorithm for the Diagnosis of Multiple System Atrophy With Predominant Parkinsonism
- Affiliations
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- 1Department of Neurology, Nowon Eulji Medical Center, Eulji University, Seoul, Korea
- 2Department of Neurology, Eulji University College of Medicine, Daejeon, Korea
- 3Department of Neurology, Seoul National University Hospital, Seoul, Korea
- 4Department of Neurology, Seoul National University College of Medicine, Seoul, Korea
- 5Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea
- 6Department of Radiology, Seoul National University Hospital, Seoul, Korea
- 7Department of Radiology, Seoul National University College of Medicine, Seoul, Korea
- KMID: 2533687
- DOI: http://doi.org/10.14802/jmd.21178
Abstract
Objective
Putaminal iron deposition is an important feature that helps differentiate multiple system atrophy with predominant parkinsonism (MSA-p) from Parkinson’s disease (PD). Most previous studies used visual inspection or quantitative methods with manual manipulation to perform this differentiation. We investigated the value of a new semiautomated diagnostic algorithm using 3T-MR susceptibility-weighted imaging for MSA-p.
Methods
This study included 26 MSA-p, 68 PD, and 41 normal control (NC) subjects. The algorithm was developed in 2 steps: 1) determine the image containing the remarkable putaminal margin and 2) calculate the phase-shift values, which reflect the iron concentration. The next step was to identify the best differentiating conditions among several combinations. The highest phaseshift value of each subject was used to assess the most effective diagnostic set.
Results
The raw phase-shift values were present along the lateral margin of the putamen in each group. It demonstrates an anterior- to-posterior gradient that was identified most frequently in MSA-p. The average of anterior 5 phase shift values were used for normalization. The highest area under the receiver operating characteristic curve (0.874, 80.8% sensitivity, and 86.7% specificity) of MSA-p versus PD was obtained under the combination of 3 or 4 vertical pixels and one dominant side when the normalization methods were applied. In the subanalysis for the MSA-p patients with a longer disease duration, the performance of the algorithm improved.
Conclusion
This algorithm detected the putaminal lateral margin well, provided insight into the iron distribution of the putaminal rim of MSA-p, and demonstrated good performance in differentiating MSA-p from PD.
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