Neuropathological correlation supports automated image-based differential diagnosis in parkinsonism.

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 th...

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Publicado en:European Journal of Nuclear Medicine & Molecular Imaging Vol. 48; no. 11; pp. 3522 - 3530
Autores principales: 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
Formato: Journal Article
Publicado: Springer Nature Oct2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2021
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      pub: Springer Nature
      place: New York, New York
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        149727439
        10.1007/s00259-021-05302-6
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        atl: Neuropathological correlation supports automated image-based differential diagnosis in parkinsonism.
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          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
        affil: Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, 11030, Manhasset, NY, USA
      sug:
      ab: 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.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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