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Neuropathological correlation supports automated image-based differential diagnosis in parkinsonism.
Schindlbeck, Katharina A; Gupta, Deepak K; Tang, Chris C; O'Shea, Sarah A; Poston, Kathleen L; Choi, Yoon Young; Dhawan, Vijay; Vonsattel, Jean-Paul; Fahn, Stanley; Eidelberg, David.
Afiliação
  • Schindlbeck KA; Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA.
  • Gupta DK; Division of Movement Disorders, Columbia University Medical Center, New York, NY, USA.
  • Tang CC; Larner College of Medicine, University of Vermont Medical Center, Burlington, VT, USA.
  • O'Shea SA; Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA.
  • Poston KL; Division of Movement Disorders, Columbia University Medical Center, New York, NY, USA.
  • Choi YY; Department of Neurology, Boston University School of Medicine, Boston University, Boston, MA, USA.
  • Dhawan V; Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
  • Vonsattel JP; Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA.
  • Fahn S; Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA.
  • Eidelberg D; Division of Neuropathology, Columbia University Medical Center, New York, NY, USA.
Eur J Nucl Med Mol Imaging ; 48(11): 3522-3529, 2021 10.
Article em En | MEDLINE | ID: mdl-33839891
ABSTRACT

PURPOSE:

Up to 25% of patients diagnosed as idiopathic Parkinson's disease (IPD) have an atypical parkinsonian syndrome (APS). We had previously validated an automated image-based algorithm to discriminate between IPD, multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). While the algorithm was accurate with respect to the final clinical diagnosis after long-term expert follow-up, its relationship to the initial referral diagnosis and to the neuropathological gold standard is not known.

METHODS:

Patients with an uncertain diagnosis of parkinsonism were referred for 18F-fluorodeoxyglucose (FDG) PET to classify patients as IPD or as APS based on the automated algorithm. Patients were followed by a movement disorder specialist and subsequently underwent neuropathological examination. The image-based classification was compared to the neuropathological diagnosis in 15 patients with parkinsonism.

RESULTS:

At the time of referral to PET, the clinical impression was only 66.7% accurate. The algorithm correctly identified 80% of the cases as IPD or APS (p = 0.02) and 87.5% of the APS cases as MSA or PSP (p = 0.03). The final clinical diagnosis was 93.3% accurate (p < 0.001), but needed several years of expert follow-up.

CONCLUSION:

The image-based classifications agreed well with autopsy and can help to improve diagnostic accuracy during the period of clinical uncertainty.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Atrofia de Múltiplos Sistemas / Transtornos Parkinsonianos Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Atrofia de Múltiplos Sistemas / Transtornos Parkinsonianos Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article