Diagnostic potential of automated subcortical volume segmentation in atypical parkinsonism.

Objective: To determine whether automated and observer-independent volumetric MRI analysis is able to discriminate among patients with Parkinson disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP) in early to moderately advanced stages of disease.Methods: T1-weighte...

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Publicado en:Neurology Vol. 86; no. 13; pp. 1242 - 1250
Autores principales: Scherfler, Christoph, Göbel, Georg, Müller, Christoph, Nocker, Michael, Wenning, Gregor K., Schocke, Michael, Poewe, Werner, Seppi, Klaus
Formato: diagnostic images research tables/charts Journal Article
Publicado: Lippincott Williams & Wilkins 3/29/2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 3/29/2016
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      pub: Lippincott Williams & Wilkins
      place: Baltimore, Maryland
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        10.1212/WNL.0000000000002518
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        atl: Diagnostic potential of automated subcortical volume segmentation in atypical parkinsonism.
      aug:
        au:
          Scherfler, Christoph
          Göbel, Georg
          Müller, Christoph
          Nocker, Michael
          Wenning, Gregor K.
          Schocke, Michael
          Poewe, Werner
          Seppi, Klaus
        affil: Department of Neurology, Medical University of Innsbruck, Austria
      sug:
        subj:
          Brain Stem Pathology
          Basal Ganglia Pathology
          Cerebellum Pathology
          Parkinsonian Disorders Diagnosis
          Neurodegenerative Diseases
          Aged
          Body Weights and Measures
          Supranuclear Palsy, Progressive Diagnosis
          Middle Age
          Male
          Female
          Magnetic Resonance Imaging Methods
          Human
          Aged: 65+ years
          Middle Aged: 45-64 years
          Male
          Female
      ab: Objective: To determine whether automated and observer-independent volumetric MRI analysis is able to discriminate among patients with Parkinson disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP) in early to moderately advanced stages of disease.Methods: T1-weighted volumetric MRI from patients with clinically probable PD (n = 40), MSA (n = 40), and PSP (n = 30) and a mean disease duration of 2.8 ± 1.7 y were examined using automated volume measures of 22 subcortical regions. The clinical follow-up period was 2.5 ± 1.2 years. The data were split into a training (n = 72) and a test set (n = 38). The training set was used to build a C4.5 decision tree model in order to classify patients as MSA, PSP, or PD. The classification algorithm was examined by the test set using the final clinical diagnosis at last follow-up as diagnostic gold standard.Results: The midbrain and putaminal volume as well as the cerebellar gray matter compartment were identified as the most significant brain regions to construct a prediction model. The diagnostic accuracy for PD vs MSA or PSP was 97.4%. In contrast, diagnostic accuracy based on validated clinical consensus criteria at the time of MRI acquisition was 62.9%.Conclusions: Volume segmentation of subcortical brain areas differentiates PD from MSA and PSP and improves diagnostic accuracy in patients presenting with early to moderately advanced stage parkinsonism.Classification Of Evidence: This study provides Class III evidence that automated MRI analysis accurately discriminates among early-stage PD, MSA, and PSP.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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