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Semiautomated Algorithm for the Diagnosis of Multiple System Atrophy With Predominant Parkinsonism

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 differentia...

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Detalles Bibliográficos
Autores principales: Lee, Woong-Woo, Kim, Han-Joon, Lee, Hong Ji, Kim, Han Byul, Park, Kwang Suk, Sohn, Chul-Ho, Jeon, Beomseok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Movement Disorder Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536910/
https://www.ncbi.nlm.nih.gov/pubmed/35880384
http://dx.doi.org/10.14802/jmd.21178
Descripción
Sumario: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 phase-shift 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.