Automated Imaging Differentiation for Parkinsonism
by Vaillancourt, David E. | Barmpoutis, Angelos | Wu, Samuel S. | et al.
JAMA Neurology, March 17, 2025, pp. E1-E10. https://doi.org/10.1001/jamaneurol.2025.0112
JAMA Neurology, March 17, 2025, pp. E1-E10. https://doi.org/10.1001/jamaneurol.2025.0112
Description
Question Does 3-T magnetic resonance imaging paired with machine learning meet primary end points for differentiating Parkinson disease (PD), multiple system atrophy (MSA) parkinsonian variant, and progressive supranuclear palsy (PSP)?
Findings The multicenter Automated Imaging Differentiation of Parkinsonism cohort study of 249 patients and a retrospective cohort of 396 patients showed excellent discrimination of PD vs atypical parkinsonism, MSA vs PSP, PD vs MSA, and PD vs PSP. AIDP machine learning predicted postmortem neuropathology in 93.8% of autopsy cases.
Meaning Results of this study suggest the use of Automated Imaging Differentiation of Parkinsonism in the diagnostic workup for common neurodegenerative forms of parkinsonism.
